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Sample records for trait loci influencing

  1. Influence analysis in quantitative trait loci detection.

    Science.gov (United States)

    Dou, Xiaoling; Kuriki, Satoshi; Maeno, Akiteru; Takada, Toyoyuki; Shiroishi, Toshihiko

    2014-07-01

    This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

    Science.gov (United States)

    A. Groover; M. Devey; T. Fiddler; J. Lee; R. Megraw; T. Mitchel-Olds; B. Sherman; S. Vujcic; C. Williams; D. Neale

    1994-01-01

    We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.) . QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (>2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among...

  3. Quantitative Trait Loci in Inbred Lines

    NARCIS (Netherlands)

    Jansen, R.C.

    2001-01-01

    Quantitative traits result from the influence of multiple genes (quantitative trait loci) and environmental factors. Detecting and mapping the individual genes underlying such 'complex' traits is a difficult task. Fortunately, populations obtained from crosses between inbred lines are relatively

  4. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    NARCIS (Netherlands)

    Scott, Robert A.; Lagou, Vasiliki; Welch, Ryan P.; Wheeler, Eleanor; Montasser, May E.; Luan, Jian'an; Mägi, Reedik; Strawbridge, Rona J.; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J.; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C. D.; Jukema, J. Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V.; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J.; Evans, David M.; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S.; Hui, Jennie; Bielak, Lawrence F.; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R.; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tõnu; Mihailov, Evelin; Fraser, Ross M.; Fall, Tove; Voight, Benjamin F.; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M.; Morris, Andrew P.; Rayner, Nigel W.; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S.; Willems, Sara M.; Chines, Peter S.; Jackson, Anne U.; Kang, Hyun Min; Stringham, Heather M.; Song, Kijoung; Tanaka, Toshiko; Peden, John F.; Goel, Anuj; Hicks, Andrew A.; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J.; Bruinenberg, Marcel; Pankow, James S.; North, Kari E.; Forouhi, Nita G.; Loos, Ruth J. F.; Edkins, Sarah; Varga, Tibor V.; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J. L.; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B.; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L.; Rivadeneira, Fernando; Uitterlinden, Andre G.; Palmer, Colin N. A.; Doney, Alex S. F.; Willemsen, Gonneke; Smit, Johannes H.; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L.; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L.; Fowkes, Gerard R.; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H.; Basart, Hanneke V.; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E.; Boehm, Bernhard O.; Peters, Annette; Pramstaller, Peter P.; Province, Michael A.; Borecki, Ingrid B.; Hastie, Nicholas D.; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M.; Bergman, Richard N.; Collins, Francis S.; Tuomilehto, Jaakko; Watanabe, Richard M.; de Geus, Eco J. C.; Penninx, Brenda W.; Hofman, Albert; Oostra, Ben A.; Psaty, Bruce M.; Vollenweider, Peter; Wilson, James F.; Wright, Alan F.; Hovingh, G. Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K. E.; Kyvik, Kirsten O.; Kaprio, Jaakko; Price, Jackie F.; Dedoussis, George V.; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R.; van Duijn, Cornelia M.; Morris, Andrew D.; Toenjes, Anke; Peyser, Patricia A.; Beilby, John P.; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R.; Schwarz, Peter E. H.; Lakka, Timo A.; Rauramaa, Rainer; Adair, Linda S.; Smith, George Davey; Spector, Tim D.; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Boomsma, Dorret I.; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L.; Sattar, Naveed; Harris, Tamara B.; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L.; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J.; Bouatia-Naji, Nabila; McCarthy, Mark I.; Franks, Paul W.; Meigs, James B.; Teslovich, Tanya M.; Florez, Jose C.; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

    2012-01-01

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes

  5. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    NARCIS (Netherlands)

    Scott, Robert A.; Lagou, Vasiliki; Welch, Ryan P.; Wheeler, Eleanor; Montasser, May E.; Luan, Jian'an; Maegi, Reedik; Strawbridge, Rona J.; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J.; Yengo, Loic; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C. D.; Jukema, J. Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V.; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J.; Evans, David M.; St Pourcain, Beate; Wu, Ying; Andrews, Jeanette S.; Hui, Jennie; Bielak, Lawrence F.; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R.; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tonu; Mihailov, Evelin; Fraser, Ross M.; Fall, Tove; Voight, Benjamin F.; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M.; Morris, Andrew P.; Rayner, Nigel W.; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S.; Willems, Sara M.; Chines, Peter S.; Jackson, Anne U.; Kang, Hyun Min; Stringham, Heather M.; Song, Kijoung; Tanaka, Toshiko; Peden, John F.; Goel, Anuj; Hicks, Andrew A.; An, Ping; Mueller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J.; Bruinenberg, Marcel; Pankow, James S.; North, Kari E.; Forouhi, Nita G.; Loos, Ruth J. F.; Edkins, Sarah; Varga, Tibor V.; Hallmans, Goeran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J. L.; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B.; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L.; Rivadeneira, Fernando; Uitterlinden, Andre G.; Palmer, Colin N. A.; Doney, Alex S. F.; Willemsen, Gonneke; Smit, Johannes H.; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L.; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L.; Fowkes, Gerard R.; Kovacs, Peter; Lindstrom, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H.; Basart, Hanneke V.; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E.; Boehm, Bernhard O.; Peters, Annette; Pramstaller, Peter P.; Province, Michael A.; Borecki, Ingrid B.; Hastie, Nicholas D.; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M.; Bergman, Richard N.; Collins, Francis S.; Tuomilehto, Jaakko; Watanabe, Richard M.; de Geus, Eco J. C.; Penninx, Brenda W.; Hofman, Albert; Oostra, Ben A.; Psaty, Bruce M.; Vollenweider, Peter; Wilson, James F.; Wright, Alan F.; Hovingh, G. Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K. E.; Kyvik, Kirsten O.; Kaprio, Jaakko; Price, Jackie F.; Dedoussis, George V.; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R.; van Duijn, Cornelia M.; Morris, Andrew D.; Toenjes, Anke; Peyser, Patricia A.; Beilby, John P.; Koerner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R.; Schwarz, Peter E. H.; Lakka, Timo A.; Rauramaa, Rainer; Adair, Linda S.; Smith, George Davey; Spector, Tim D.; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Boomsma, Dorret I.; Stefansson, Kari; van der Harst, Pim; Dupuis, Josee; Pedersen, Nancy L.; Sattar, Naveed; Harris, Tamara B.; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L.; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J.; Bouatia-Naji, Nabila; McCarthy, Mark I.; Franks, Paul W.; Meigs, James B.; Teslovich, Tanya M.; Florez, Jose C.; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Ines

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes

  6. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

    DEFF Research Database (Denmark)

    Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P

    2012-01-01

    Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes...

  7. Detection of quantitative trait loci in broilers

    NARCIS (Netherlands)

    Kaam, van J.T.

    2000-01-01

    This dissertation deals with the development and application of methods for the detection of genes with a substantial influence on quantitative traits, so called quantitative trait loci (QTLs) in broilers. For the purpose of detection of QTLs, an experiment was initiated. A three generation

  8. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits

    DEFF Research Database (Denmark)

    Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas

    2012-01-01

    Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European an...... = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p...

  9. Obesity-Susceptibility Loci and Their Influence on Adiposity-Related Traits in Transition from Adolescence to Adulthood - The HUNT Study

    Science.gov (United States)

    Cuypers, Koenraad Frans; Loos, Ruth J. F.; Kvaløy, Kirsti; Kulle, Bettina; Romundstad, Pål; Holmen, Turid Lingaas

    2012-01-01

    Introduction Obesity-susceptibility loci have been related to adiposity traits in adults and may affect body fat estimates in adolescence. There are indications that different sets of obesity-susceptibility loci influence level of and change in obesity-related traits from adolescence to adulthood. Objectives To investigate whether previously reported obesity-susceptible loci in adults influence adiposity traits in adolescence and change in BMI and waist circumference (WC) from adolescence into young adulthood. We also examined whether physical activity modifies the effects of these genetic loci on adiposity-related traits. Methods Nine obesity-susceptibility variants were genotyped in 1 643 adolescents (13–19 years old) from the HUNT study, Norway, who were followed-up into young adulthood. Lifestyle was assessed using questionnaires and anthropometric measurements were taken. The effects of genetic variants individually and combined in a genetic predisposition score (GPS) on obesity-related traits were studied cross-sectionally and longitudinally. A modifying effect of physical activity was tested. Results The GPS was significantly associated to BMI (B: 0.046 SD/allele [0.020, 0.073], p = 0.001) in adolescence and in young adulthood (B: 0.041 SD/allele [0.015, 0.067], p = 0.002) as it was to waist circumference (WC). The GPS was not associated to change in BMI (p = 0.762) or WC (p = 0.726). We found no significant interaction effect between the GPS and physical activity. Conclusions Our observations suggest that obesity-susceptibility loci established in adults affect BMI and WC already in adolescence. However, an association with change in adiposity-related traits from adolescence to adulthood could not be verified for these loci. Neither could an attenuating effect of physical activity on the association between the obesity-susceptibility genes and body fat estimates be revealed. PMID:23094032

  10. Obesity-susceptibility loci and their influence on adiposity-related traits in transition from adolescence to adulthood--the HUNT study.

    Science.gov (United States)

    Cuypers, Koenraad Frans; Loos, Ruth J F; Kvaløy, Kirsti; Kulle, Bettina; Romundstad, Pål; Holmen, Turid Lingaas

    2012-01-01

    Obesity-susceptibility loci have been related to adiposity traits in adults and may affect body fat estimates in adolescence. There are indications that different sets of obesity-susceptibility loci influence level of and change in obesity-related traits from adolescence to adulthood. To investigate whether previously reported obesity-susceptible loci in adults influence adiposity traits in adolescence and change in BMI and waist circumference (WC) from adolescence into young adulthood. We also examined whether physical activity modifies the effects of these genetic loci on adiposity-related traits. Nine obesity-susceptibility variants were genotyped in 1 643 adolescents (13-19 years old) from the HUNT study, Norway, who were followed-up into young adulthood. Lifestyle was assessed using questionnaires and anthropometric measurements were taken. The effects of genetic variants individually and combined in a genetic predisposition score (GPS) on obesity-related traits were studied cross-sectionally and longitudinally. A modifying effect of physical activity was tested. The GPS was significantly associated to BMI (B: 0.046 SD/allele [0.020, 0.073], p = 0.001) in adolescence and in young adulthood (B: 0.041 SD/allele [0.015, 0.067], p = 0.002) as it was to waist circumference (WC). The GPS was not associated to change in BMI (p = 0.762) or WC (p = 0.726). We found no significant interaction effect between the GPS and physical activity. Our observations suggest that obesity-susceptibility loci established in adults affect BMI and WC already in adolescence. However, an association with change in adiposity-related traits from adolescence to adulthood could not be verified for these loci. Neither could an attenuating effect of physical activity on the association between the obesity-susceptibility genes and body fat estimates be revealed.

  11. Quantitative Trait Loci Affecting Calving Traits in Danish Holstein Cattle

    DEFF Research Database (Denmark)

    Thomasen, J R; Guldbrandtsen, B; Sørensen, P

    2008-01-01

    The objectives of this study were 1) to detect quantitative trait loci (QTL) affecting direct and maternal calving traits at first calving in the Danish Holstein population, 2) to distinguish between pleiotropic and linked QTL for chromosome regions affecting more than one trait, and 3) to detect...

  12. Quantitative trait loci for rice yield-related traits using recombinant ...

    Indian Academy of Sciences (India)

    2011-08-19

    Aug 19, 2011 ... Abstract. The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for ...

  13. Two alternative recessive quantitative trait loci influence resistance to spring black stem and leaf spot in Medicago truncatula

    Directory of Open Access Journals (Sweden)

    Oliver Richard P

    2008-03-01

    Full Text Available Abstract Background Knowledge of the genetic basis of plant resistance to necrotrophic pathogens is incomplete and has been characterised in relatively few pathosystems. In this study, the cytology and genetics of resistance to spring black stem and leaf spot caused by Phoma medicaginis, an economically important necrotrophic pathogen of Medicago spp., was examined in the model legume M. truncatula. Results Macroscopically, the resistant response of accession SA27063 was characterised by small, hypersensitive-like spots following inoculation while the susceptible interaction with accessions A17 and SA3054 showed necrotic lesions and spreading chlorosis. No unique cytological differences were observed during early infection (2 populations segregating for resistance to spring black stem and leaf spot were established between SA27063 and the two susceptible accessions, A17 and SA3054. The cross between SA27063 and A17 represented a wider cross than between SA27063 and SA3054, as evidenced by higher genetic polymorphism, reduced fertility and aberrant phenotypes of F2 progeny. In the SA27063 × A17 F2 population a highly significant quantitative trait locus (QTL, LOD = 7.37; P Phoma medicaginis one (rnpm1 genetically mapped to the top arm of linkage group 4 (LG4. rnpm1 explained 33.6% of the phenotypic variance in the population's response to infection depicted on a 1–5 scale and was tightly linked to marker AW256637. A second highly significant QTL (LOD = 6.77; P rnpm2, was located on the lower arm of LG8 in the SA27063 × SA3054 map. rnpm2 explained 29.6% of the phenotypic variance and was fine mapped to a 0.8 cM interval between markers h2_16a6a and h2_21h11d. rnpm1 is tightly linked to a cluster of Toll/Interleukin1 receptor-nucleotide binding site-leucine-rich repeat (TIR-NBS-LRR genes and disease resistance protein-like genes, while no resistance gene analogues (RGAs are apparent in the genomic sequence of the reference accession A17 at the

  14. Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals

    Science.gov (United States)

    Tanaka, Toshiko; Morris, Andrew P.; Small, Kerrin; Isaacs, Aaron; Beekman, Marian; Coassin, Stefan; Lohman, Kurt; Qi, Lu; Kanoni, Stavroula; Pankow, James S.; Uh, Hae-Won; Wu, Ying; Bidulescu, Aurelian; Rasmussen-Torvik, Laura J.; Greenwood, Celia M. T.; Ladouceur, Martin; Grimsby, Jonna; Manning, Alisa K.; Liu, Ching-Ti; Kooner, Jaspal; Mooser, Vincent E.; Vollenweider, Peter; Kapur, Karen A.; Chambers, John; Wareham, Nicholas J.; Langenberg, Claudia; Frants, Rune; Willems-vanDijk, Ko; Oostra, Ben A.; Willems, Sara M.; Lamina, Claudia; Winkler, Thomas W.; Psaty, Bruce M.; Tracy, Russell P.; Brody, Jennifer; Chen, Ida; Viikari, Jorma; Kähönen, Mika; Pramstaller, Peter P.; Evans, David M.; St. Pourcain, Beate; Sattar, Naveed; Wood, Andrew R.; Bandinelli, Stefania; Carlson, Olga D.; Egan, Josephine M.; Böhringer, Stefan; van Heemst, Diana; Kedenko, Lyudmyla; Kristiansson, Kati; Nuotio, Marja-Liisa; Loo, Britt-Marie; Harris, Tamara; Garcia, Melissa; Kanaya, Alka; Haun, Margot; Klopp, Norman; Wichmann, H.-Erich; Deloukas, Panos; Katsareli, Efi; Couper, David J.; Duncan, Bruce B.; Kloppenburg, Margreet; Adair, Linda S.; Borja, Judith B.; Wilson, James G.; Musani, Solomon; Guo, Xiuqing; Johnson, Toby; Semple, Robert; Teslovich, Tanya M.; Allison, Matthew A.; Redline, Susan; Buxbaum, Sarah G.; Mohlke, Karen L.; Meulenbelt, Ingrid; Ballantyne, Christie M.; Dedoussis, George V.; Hu, Frank B.; Liu, Yongmei; Paulweber, Bernhard; Spector, Timothy D.; Slagboom, P. Eline; Ferrucci, Luigi; Jula, Antti; Perola, Markus; Raitakari, Olli; Florez, Jose C.; Salomaa, Veikko; Eriksson, Johan G.; Frayling, Timothy M.; Hicks, Andrew A.; Lehtimäki, Terho; Smith, George Davey; Siscovick, David S.; Kronenberg, Florian; van Duijn, Cornelia; Loos, Ruth J. F.; Waterworth, Dawn M.; Meigs, James B.; Dupuis, Josee; Richards, J. Brent

    2012-01-01

    Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10−8–1.2×10−43). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (pgenetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance. PMID:22479202

  15. Quantitative Trait Loci for Fertility Traits in Finnish Ayrshire Cattle

    DEFF Research Database (Denmark)

    Schulman, Nina F; Sahana, Goutam; Lund, Mogens S

    2008-01-01

    A whole genome scan was carried out to detect quantitative trait loci (QTL) for fertility traits in Finnish Ayrshire cattle. The mapping population consisted of 12 bulls and 493 sons. Estimated breeding values for days open, fertility treatments, maternal calf mortality and paternal non-return rate...... combinations, which were observed significant in the regression method. Twenty-two chromosome-wise significant QTL were detected. Several of the detected QTL areas were overlapping with milk production QTL previously identified in the same population. Multi-trait QTL analyses were carried out to test...... if these effects were due to a pleiotropic QTL affecting fertility and milk yield traits or to linked QTL causing the effects. This distinction could only be made with confidence on BTA1 where a QTL affecting milk yield is linked to a pleiotropic QTL affecting days open and fertility treatments...

  16. Detection and utilisation of quantitative trait loci in dairy cattle

    NARCIS (Netherlands)

    Spelman, R.J.

    1998-01-01

    The focus of the thesis is on the detection of quantitative trait loci (QTL) in dairy cattle and their utilisation in breeding programmes. Analysis of one bovine chromosome for quantitative trait loci for milk production traits is described and a QTL for protein percent was identified that

  17. Nonparametric functional mapping of quantitative trait loci.

    Science.gov (United States)

    Yang, Jie; Wu, Rongling; Casella, George

    2009-03-01

    Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

  18. Genetic mapping of quantitative trait loci (QTLs) with effects on ...

    African Journals Online (AJOL)

    Genetic mapping of quantitative trait loci (QTLs) with effects on resistance to flower bud thrips ( Megalurothrips sjostedti ) identified in recombinant inbred lines of cowpea ( Vigna unguiculata (L.) Walp)

  19. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

    NARCIS (Netherlands)

    Liu, C. (Chunyu); A. Kraja (Aldi); J.A. Smith (Jennifer A); J. Brody (Jennifer); N. Franceschini (Nora); J.C. Bis (Joshua); K.M. Rice (Kenneth); A.C. Morrison (Alanna); Y. Lu (Yingchang); Weiss, S. (Stefan); X. Guo (Xiuqing); W. Palmas (Walter); L.W. Martin (Lisa); Y.D. Chen (Y.); Surendran, P. (Praveen); F. Drenos (Fotios); Cook, J.P. (James P.); P. Auer (Paul); A.Y. Chu (Audrey); Giri, A. (Ayush); Zhao, W. (Wei); M. Jakobsdottir (Margret); Lin, L.-A. (Li-An); J.M. Stafford (Jeanette M.); N. Amin (Najaf); Mei, H. (Hao); J. Yao (Jiefen); J.M. Voorman (Jeanine); M.G. Larson (Martin); M.L. Grove (Megan); A.V. Smith (Albert Vernon); S.J. Hwang; H. Chen (Han); T. Huan (Tianxiao); Kosova, G. (Gulum); N.O. Stitziel (Nathan); S. Kathiresan (Sekar); N.J. Samani (Nilesh); H. Schunkert (Heribert); P. Deloukas (Panagiotis); M. Li (Man); C. Fuchsberger (Christian); C. Pattaro (Cristian); M. Gorski (Mathias); C. Kooperberg (Charles); G. Papanicolaou (George); Rossouw, J.E. (Jacques E.); J.D. Faul (Jessica D.); S.L.R. Kardia (Sharon); C. Bouchard (Claude); L.J. Raffel (Leslie); Uitterlinden, A.G. (André G.); O.H. Franco (Oscar); R. Vasan (Ramachandran); C.J. O'Donnell (Christopher); K.D. Taylor (Kent); K.Y. Liu; E.P. Bottinger (Erwin); R.F. Gottesman (Rebecca); E.W. Daw (E. Warwick); F. Giulianini (Franco); S.K. Ganesh (Santhi); E. Salfati (Elias); T.B. Harris (Tamara); Launer, L.J. (Lenore J.); M. Dörr (Marcus); S.B. Felix (Stephan); R. Rettig (Rainer); H. Völzke (Henry); E. Kim (Eric); W.-J. Lee (Wen-Jane); I.T. Lee; Sheu, W.H.-H. (Wayne H.-H.); Tsosie, K.S. (Krystal S.); Edwards, D.R.V. (Digna R. Velez); Y. Liu (YongMei); Correa, A. (Adolfo); D.R. Weir (David); U. Völker (Uwe); P.M. Ridker (Paul); E.A. Boerwinkle (Eric); V. Gudnason (Vilmundur); A. Reiner (Alexander); Van Duijn, C.M. (Cornelia M.); I.B. Borecki (Ingrid); T.L. Edwards (Todd L.); A. Chakravarti (Aravinda); Rotter, J.I. (Jerome I.); B.M. Psaty (Bruce); R.J.F. Loos (Ruth); M. Fornage (Myriam); G.B. Ehret (Georg); C. Newton-Cheh (Christopher); D. Levy (Daniel); D.I. Chasman (Daniel)

    2016-01-01

    textabstractMeta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood

  20. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

    Science.gov (United States)

    Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas; Perry, John R B; Yuan, Xin; Scott, Robert A; Henneman, Peter; Heid, Iris M; Kizer, Jorge R; Lyytikäinen, Leo-Pekka; Fuchsberger, Christian; Tanaka, Toshiko; Morris, Andrew P; Small, Kerrin; Isaacs, Aaron; Beekman, Marian; Coassin, Stefan; Lohman, Kurt; Qi, Lu; Kanoni, Stavroula; Pankow, James S; Uh, Hae-Won; Wu, Ying; Bidulescu, Aurelian; Rasmussen-Torvik, Laura J; Greenwood, Celia M T; Ladouceur, Martin; Grimsby, Jonna; Manning, Alisa K; Liu, Ching-Ti; Kooner, Jaspal; Mooser, Vincent E; Vollenweider, Peter; Kapur, Karen A; Chambers, John; Wareham, Nicholas J; Langenberg, Claudia; Frants, Rune; Willems-Vandijk, Ko; Oostra, Ben A; Willems, Sara M; Lamina, Claudia; Winkler, Thomas W; Psaty, Bruce M; Tracy, Russell P; Brody, Jennifer; Chen, Ida; Viikari, Jorma; Kähönen, Mika; Pramstaller, Peter P; Evans, David M; St Pourcain, Beate; Sattar, Naveed; Wood, Andrew R; Bandinelli, Stefania; Carlson, Olga D; Egan, Josephine M; Böhringer, Stefan; van Heemst, Diana; Kedenko, Lyudmyla; Kristiansson, Kati; Nuotio, Marja-Liisa; Loo, Britt-Marie; Harris, Tamara; Garcia, Melissa; Kanaya, Alka; Haun, Margot; Klopp, Norman; Wichmann, H-Erich; Deloukas, Panos; Katsareli, Efi; Couper, David J; Duncan, Bruce B; Kloppenburg, Margreet; Adair, Linda S; Borja, Judith B; Wilson, James G; Musani, Solomon; Guo, Xiuqing; Johnson, Toby; Semple, Robert; Teslovich, Tanya M; Allison, Matthew A; Redline, Susan; Buxbaum, Sarah G; Mohlke, Karen L; Meulenbelt, Ingrid; Ballantyne, Christie M; Dedoussis, George V; Hu, Frank B; Liu, Yongmei; Paulweber, Bernhard; Spector, Timothy D; Slagboom, P Eline; Ferrucci, Luigi; Jula, Antti; Perola, Markus; Raitakari, Olli; Florez, Jose C; Salomaa, Veikko; Eriksson, Johan G; Frayling, Timothy M; Hicks, Andrew A; Lehtimäki, Terho; Smith, George Davey; Siscovick, David S; Kronenberg, Florian; van Duijn, Cornelia; Loos, Ruth J F; Waterworth, Dawn M; Meigs, James B; Dupuis, Josee; Richards, J Brent; Voight, Benjamin F; Scott, Laura J; Steinthorsdottir, Valgerdur; Dina, Christian; Welch, Ryan P; Zeggini, Eleftheria; Huth, Cornelia; Aulchenko, Yurii S; Thorleifsson, Gudmar; McCulloch, Laura J; Ferreira, Teresa; Grallert, Harald; Amin, Najaf; Wu, Guanming; Willer, Cristen J; Raychaudhuri, Soumya; McCarroll, Steve A; Hofmann, Oliver M; Segrè, Ayellet V; van Hoek, Mandy; Navarro, Pau; Ardlie, Kristin; Balkau, Beverley; Benediktsson, Rafn; Bennett, Amanda J; Blagieva, Roza; Boerwinkle, Eric; Bonnycastle, Lori L; Boström, Kristina Bengtsson; Bravenboer, Bert; Bumpstead, Suzannah; Burtt, Noël P; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn; Crawford, Gabe; Doney, Alex S F; Elliott, Katherine S; Elliott, Amanda L; Erdos, Michael R; Fox, Caroline S; Franklin, Christopher S; Ganser, Martha; Gieger, Christian; Grarup, Niels; Green, Todd; Griffin, Simon; Groves, Christopher J; Guiducci, Candace; Hadjadj, Samy; Hassanali, Neelam; Herder, Christian; Isomaa, Bo; Jackson, Anne U; Johnson, Paul R V; Jørgensen, Torben; Kao, Wen H L; Kong, Augustine; Kraft, Peter; Kuusisto, Johanna; Lauritzen, Torsten; Li, Man; Lieverse, Aloysius; Lindgren, Cecilia M; Lyssenko, Valeriya; Marre, Michel; Meitinger, Thomas; Midthjell, Kristian; Morken, Mario A; Narisu, Narisu; Nilsson, Peter; Owen, Katharine R; Payne, Felicity; Petersen, Ann-Kristin; Platou, Carl; Proença, Christine; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, N William; Robertson, Neil R; Rocheleau, Ghislain; Roden, Michael; Sampson, Michael J; Saxena, Richa; Shields, Beverley M; Shrader, Peter; Sigurdsson, Gunnar; Sparsø, Thomas; Strassburger, Klaus; Stringham, Heather M; Sun, Qi; Swift, Amy J; Thorand, Barbara; Tichet, Jean; Tuomi, Tiinamaija; van Dam, Rob M; van Haeften, Timon W; van Herpt, Thijs; van Vliet-Ostaptchouk, Jana V; Walters, G Bragi; Weedon, Michael N; Wijmenga, Cisca; Witteman, Jacqueline; Bergman, Richard N; Cauchi, Stephane; Collins, Francis S; Gloyn, Anna L; Gyllensten, Ulf; Hansen, Torben; Hide, Winston A; Hitman, Graham A; Hofman, Albert; Hunter, David J; Hveem, Kristian; Laakso, Markku; Morris, Andrew D; Palmer, Colin N A; Rudan, Igor; Sijbrands, Eric; Stein, Lincoln D; Tuomilehto, Jaakko; Uitterlinden, Andre; Walker, Mark; Watanabe, Richard M; Abecasis, Goncalo R; Boehm, Bernhard O; Campbell, Harry; Daly, Mark J; Hattersley, Andrew T; Pedersen, Oluf; Barroso, Inês; Groop, Leif; Sladek, Rob; Thorsteinsdottir, Unnur; Wilson, James F; Illig, Thomas; Froguel, Philippe; van Duijn, Cornelia M; Stefansson, Kari; Altshuler, David; Boehnke, Michael; McCarthy, Mark I; Soranzo, Nicole; Wheeler, Eleanor; Glazer, Nicole L; Bouatia-Naji, Nabila; Mägi, Reedik; Randall, Joshua; Elliott, Paul; Rybin, Denis; Dehghan, Abbas; Hottenga, Jouke Jan; Song, Kijoung; Goel, Anuj; Lajunen, Taina; Doney, Alex; Cavalcanti-Proença, Christine; Kumari, Meena; Timpson, Nicholas J; Zabena, Carina; Ingelsson, Erik; An, Ping; O'Connell, Jeffrey; Luan, Jian'an; Elliott, Amanda; McCarroll, Steven A; Roccasecca, Rosa Maria; Pattou, François; Sethupathy, Praveen; Ariyurek, Yavuz; Barter, Philip; Beilby, John P; Ben-Shlomo, Yoav; Bergmann, Sven; Bochud, Murielle; Bonnefond, Amélie; Borch-Johnsen, Knut; Böttcher, Yvonne; Brunner, Eric; Bumpstead, Suzannah J; Chen, Yii-Der Ida; Chines, Peter; Clarke, Robert; Coin, Lachlan J M; Cooper, Matthew N; Crisponi, Laura; Day, Ian N M; de Geus, Eco J C; Delplanque, Jerome; Fedson, Annette C; Fischer-Rosinsky, Antje; Forouhi, Nita G; Franzosi, Maria Grazia; Galan, Pilar; Goodarzi, Mark O; Graessler, Jürgen; Grundy, Scott; Gwilliam, Rhian; Hallmans, Göran; Hammond, Naomi; Han, Xijing; Hartikainen, Anna-Liisa; Hayward, Caroline; Heath, Simon C; Hercberg, Serge; Hillman, David R; Hingorani, Aroon D; Hui, Jennie; Hung, Joe; Kaakinen, Marika; Kaprio, Jaakko; Kesaniemi, Y Antero; Kivimaki, Mika; Knight, Beatrice; Koskinen, Seppo; Kovacs, Peter; Kyvik, Kirsten Ohm; Lathrop, G Mark; Lawlor, Debbie A; Le Bacquer, Olivier; Lecoeur, Cécile; Li, Yun; Mahley, Robert; Mangino, Massimo; Martínez-Larrad, María Teresa; McAteer, Jarred B; McPherson, Ruth; Meisinger, Christa; Melzer, David; Meyre, David; Mitchell, Braxton D; Mukherjee, Sutapa; Naitza, Silvia; Neville, Matthew J; Orrù, Marco; Pakyz, Ruth; Paolisso, Giuseppe; Pattaro, Cristian; Pearson, Daniel; Peden, John F; Pedersen, Nancy L; Pfeiffer, Andreas F H; Pichler, Irene; Polasek, Ozren; Posthuma, Danielle; Potter, Simon C; Pouta, Anneli; Province, Michael A; Rayner, Nigel W; Rice, Kenneth; Ripatti, Samuli; Rivadeneira, Fernando; Rolandsson, Olov; Sandbaek, Annelli; Sandhu, Manjinder; Sanna, Serena; Sayer, Avan Aihie; Scheet, Paul; Seedorf, Udo; Sharp, Stephen J; Shields, Beverley; Sigurðsson, Gunnar; Sijbrands, Eric J G; Silveira, Angela; Simpson, Laila; Singleton, Andrew; Smith, Nicholas L; Sovio, Ulla; Swift, Amy; Syddall, Holly; Syvänen, Ann-Christine; Tönjes, Anke; Uitterlinden, André G; van Dijk, Ko Willems; Varma, Dhiraj; Visvikis-Siest, Sophie; Vitart, Veronique; Vogelzangs, Nicole; Waeber, Gérard; Wagner, Peter J; Walley, Andrew; Ward, Kim L; Watkins, Hugh; Wild, Sarah H; Willemsen, Gonneke; Witteman, Jaqueline C M; Yarnell, John W G; Zelenika, Diana; Zethelius, Björn; Zhai, Guangju; Zhao, Jing Hua; Zillikens, M Carola; Borecki, Ingrid B; Meneton, Pierre; Magnusson, Patrik K E; Nathan, David M; Williams, Gordon H; Silander, Kaisa; Bornstein, Stefan R; Schwarz, Peter; Spranger, Joachim; Karpe, Fredrik; Shuldiner, Alan R; Cooper, Cyrus; Serrano-Ríos, Manuel; Lind, Lars; Palmer, Lyle J; Hu, Frank B; Franks, Paul W; Ebrahim, Shah; Marmot, Michael; Kao, W H Linda; Pramstaller, Peter Paul; Wright, Alan F; Stumvoll, Michael; Hamsten, Anders; Buchanan, Thomas A; Valle, Timo T; Rotter, Jerome I; Penninx, Brenda W J H; Boomsma, Dorret I; Cao, Antonio; Scuteri, Angelo; Schlessinger, David; Uda, Manuela; Ruokonen, Aimo; Jarvelin, Marjo-Riitta; Peltonen, Leena; Mooser, Vincent; Sladek, Robert; Musunuru, Kiran; Smith, Albert V; Edmondson, Andrew C; Stylianou, Ioannis M; Koseki, Masahiro; Pirruccello, James P; Chasman, Daniel I; Johansen, Christopher T; Fouchier, Sigrid W; Peloso, Gina M; Barbalic, Maja; Ricketts, Sally L; Bis, Joshua C; Feitosa, Mary F; Orho-Melander, Marju; Melander, Olle; Li, Xiaohui; Li, Mingyao; Cho, Yoon Shin; Go, Min Jin; Kim, Young Jin; Lee, Jong-Young; Park, Taesung; Kim, Kyunga; Sim, Xueling; Ong, Rick Twee-Hee; Croteau-Chonka, Damien C; Lange, Leslie A; Smith, Joshua D; Ziegler, Andreas; Zhang, Weihua; Zee, Robert Y L; Whitfield, John B; Thompson, John R; Surakka, Ida; Spector, Tim D; Smit, Johannes H; Sinisalo, Juha; Scott, James; Saharinen, Juha; Sabatti, Chiara; Rose, Lynda M; Roberts, Robert; Rieder, Mark; Parker, Alex N; Pare, Guillaume; O'Donnell, Christopher J; Nieminen, Markku S; Nickerson, Deborah A; Montgomery, Grant W; McArdle, Wendy; Masson, David; Martin, Nicholas G; Marroni, Fabio; Lucas, Gavin; Luben, Robert; Lokki, Marja-Liisa; Lettre, Guillaume; Launer, Lenore J; Lakatta, Edward G; Laaksonen, Reijo; Kyvik, Kirsten O; König, Inke R; Khaw, Kay-Tee; Kaplan, Lee M; Johansson, Åsa; Janssens, A Cecile J W; Igl, Wilmar; Hovingh, G Kees; Hengstenberg, Christian; Havulinna, Aki S; Hastie, Nicholas D; Harris, Tamara B; Haritunians, Talin; Hall, Alistair S; Groop, Leif C; Gonzalez, Elena; Freimer, Nelson B; Erdmann, Jeanette; Ejebe, Kenechi G; Döring, Angela; Dominiczak, Anna F; Demissie, Serkalem; Deloukas, Panagiotis; de Faire, Ulf; Crawford, Gabriel; Chen, Yii-der I; Caulfield, Mark J; Boekholdt, S Matthijs; Assimes, Themistocles L; Quertermous, Thomas; Seielstad, Mark; Wong, Tien Y; Tai, E-Shyong; Feranil, Alan B; Kuzawa, Christopher W; Taylor, Herman A; Gabriel, Stacey B; Holm, Hilma; Gudnason, Vilmundur; Krauss, Ronald M; Ordovas, Jose M; Munroe, Patricia B; Kooner, Jaspal S; Tall, Alan R; Hegele, Robert A; Kastelein, John J P; Schadt, Eric E; Strachan, David P; Reilly, Muredach P; Samani, Nilesh J; Schunkert, Heribert; Cupples, L Adrienne; Sandhu, Manjinder S; Ridker, Paul M; Rader, Daniel J; Kathiresan, Sekar

    2012-01-01

    Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

  1. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

    Directory of Open Access Journals (Sweden)

    Zari Dastani

    Full Text Available Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8-1.2×10(-43. Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans, we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4. We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3, n = 22,044, increased triglycerides (p = 2.6×10(-14, n = 93,440, increased waist-to-hip ratio (p = 1.8×10(-5, n = 77,167, increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3, n = 15,234, increased fasting insulin (p = 0.015, n = 48,238, but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13, n = 96,748 and decreased BMI (p = 1.4×10(-4, n = 121,335. These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

  2. Unraveling possible association between quantitative trait loci (QTL ...

    African Journals Online (AJOL)

    Unraveling possible association between quantitative trait loci (QTL) for partial resistance and nonhost resistance in food barley ( Hordeum vulgaris L.) ... Abstract. Many quantitative trait loci (QTLs) in different barley populations were discovered for resistance to Puccinia hordei and heterologous rust species. Partial ...

  3. Identification of quantitative trait loci for salinity tolerance in rice ...

    Indian Academy of Sciences (India)

    J. B. BIZIMANA

    2017-08-16

    indica), and a salt tolerant, Hasawi (aus), were used to identify quantitative trait loci (QTLs) linked to salinity tolerance. One hundred and ninety four polymorphic SNP markers were used to construct a genetic linkage map ...

  4. Genetic mapping of quantitative trait loci in crops

    OpenAIRE

    Yang Xu; Pengcheng Li; Zefeng Yang; Chenwu Xu

    2017-01-01

    Dissecting the genetic architecture of complex traits is an ongoing challenge for geneticists. Two complementary approaches for genetic mapping, linkage mapping and association mapping have led to successful dissection of complex traits in many crop species. Both of these methods detect quantitative trait loci (QTL) by identifying marker–trait associations, and the only fundamental difference between them is that between mapping populations, which directly determine mapping resolution and pow...

  5. Quantitative trait loci for flowering time and morphological traits in multiple populations of Brassica rapa

    NARCIS (Netherlands)

    Lou, P.; Jianjun Zhao, Jianjun; Kim, J.S.; Shen, Shuxing; Pino del Carpio, D.; Song, Xiaofei; Jin, M.; Vreugdenhil, D.; Wang, Xiaowu; Koornneef, M.; Bonnema, A.B.

    2007-01-01

    Wide variation for morphological traits exists in Brassica rapa and the genetic basis of this morphological variation is largely unknown. Here is a report on quantitative trait loci (QTL) analysis of flowering time, seed and pod traits, growth-related traits, leaf morphology, and turnip formation in

  6. Quantitative trait loci on chromosomes 2p, 4p, and 13q influence bone mineral density of the forearm and hip in Mexican Americans.

    Science.gov (United States)

    Kammerer, Candace M; Schneider, Jennifer L; Cole, Shelley A; Hixson, James E; Samollow, Paul B; O'Connell, Jeffrey R; Perez, Reina; Dyer, Thomas D; Almasy, Laura; Blangero, John; Bauer, Richard L; Mitchell, Braxton D

    2003-12-01

    We performed a genome scan using BMD data of the forearm and hip on 664 individuals in 29 Mexican-American families. We obtained evidence for QTL on chromosome 4p, affecting forearm BMD overall, and on chromosomes 2p and 13q, affecting hip BMD in men. The San Antonio Family Osteoporosis Study (SAFOS) was designed to identify genes and environmental factors that influence bone mineral density (BMD) using data from large Mexican-American families. We performed a genome-wide linkage analysis using 416 highly polymorphic microsatellite markers spaced approximately 9.5 cM apart to locate and identify quantitative trait loci (QTL) that affect BMD of the forearm and hip. Multipoint variance components linkage analyses were done using data on all 664 subjects, as well as two subgroups of 259 men and 261 premenopausal women, from 29 families for which genotypic and phenotypic data were available. We obtained significant evidence for a QTL affecting forearm (radius midpoint) BMD in men and women combined on chromosome 4p near D4S2639 (maximum LOD = 4.33, genomic p = 0.006) and suggestive evidence for a QTL on chromosome 12q near locus D12S2070 (maximum conditional LOD = 2.35). We found suggestive evidence for a QTL influencing trochanter BMD on chromosome 6 (maximum LOD = 2.27), but no evidence for QTL affecting the femoral neck in men and women combined. In men, we obtained evidence for QTL affecting neck and trochanter BMD on chromosomes 2p near D2S1780 (maximum LOD = 3.98, genomic p = 0.013) and 13q near D13S788 (maximum LOD = 3.46, genomic p = 0.039), respectively. We found no evidence for QTL affecting forearm or hip BMD in premenopausal women. These results provide strong evidence that a QTL on chromosome 4p affects radius BMD in Mexican-American men and women, as well as evidence that QTL on chromosomes 2p and 13q affect hip BMD in men. Our results are consistent with some reports in humans and mice. J Bone Miner Res 2003;18:2245-2252

  7. Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids.

    Science.gov (United States)

    Baack, Eric J; Sapir, Yuval; Chapman, Mark A; Burke, John M; Rieseberg, Loren H

    2008-01-01

    The strength and extent of gene flow from crops into wild populations depends, in part, on the fitness of the crop alleles, as well as that of alleles at linked loci. Interest in crop-wild gene flow has increased with the advent of transgenic plants, but nontransgenic crop-wild hybrids can provide case studies to understand the factors influencing introgression, provided that the genetic architecture and the fitness effects of loci are known. This study used recombinant inbred lines (RILs) generated from a cross between crop and wild sunflowers to assess selection on domestication traits and quantitative trait loci (QTL) in two contrasting environments, in Indiana and Nebraska, USA. Only a small fraction of plants (9%) produced seed in Nebraska, due to adverse weather conditions, while the majority of plants (79%) in Indiana reproduced. Phenotypic selection analysis found that a mixture of crop and wild traits were favoured in Indiana (i.e. had significant selection gradients), including larger leaves, increased floral longevity, larger disk diameter, reduced ray flower size and smaller achene (seed) mass. Selection favouring early flowering was detected in Nebraska. QTLs for fitness were found at the end of linkage groups six (LG6) and nine (LG9) in both field sites, each explaining 11-12% of the total variation. Crop alleles were favoured on LG9, but wild alleles were favoured on LG6. QTLs for numerous domestication traits overlapped with the fitness QTLs, including flowering date, achene mass, head number, and disk diameter. It remains to be seen if these QTL clusters are the product of multiple linked genes, or individual genes with pleiotropic effects. These results indicate that crop trait values and alleles may sometimes be favoured in a noncrop environment and across broad geographical regions.

  8. Quantitative trait loci (QTL) mapping for inflorescence length traits in ...

    African Journals Online (AJOL)

    User

    2011-05-02

    May 2, 2011 ... quantitative and nine morphological traits were recorded for each individual in the F2 population and F3 families (Table 1). Traits were assessed as the mean of three measurements when all flowers on the first three inflorescences measured were in full flower. Nine morphological traits were stem, petiole, ...

  9. Mapping quantitative trait loci for binary trait in the F2: 3 design

    Indian Academy of Sciences (India)

    In the analysis of inheritance of quantitative traits with low heritability, an F2:3 design that genotypes plants in F2 and phenotypes plants in F2:3 progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F2:3 design have been well developed, those for binary traits ...

  10. Qualitative trait loci analysis for seed yield and component traits in ...

    African Journals Online (AJOL)

    VANITHA

    2014-02-05

    Feb 5, 2014 ... Qualitative trait loci analysis for seed yield and component traits in sunflower. J. Vanitha*, N. Manivannan and ... improvement, plant breeders deal with several qualitative traits. However, the most difficult problem is the ... Characteristics of parental lines. Character. TNHSF239-68-1-1-1 (female). 17B (male).

  11. Mapping of quantitative trait loci controlling Orobanche foetida Poir ...

    African Journals Online (AJOL)

    In this study we have identified and map the quantitative trait loci (QTL) controlling resistance to O. foetida in faba bean (Vicia faba) and studied their stability in two different environments. One hundred and forty four Recombinant Inbred Lines (RILs) derived from the cross between a susceptible and a resistant parent were ...

  12. Quantitative trait loci analysis of individual and total isoflavone ...

    Indian Academy of Sciences (India)

    Soybean isoflavones play diverse roles in human health, including cancers, osteoporosis, heart disease, menopausal symptoms and pabulums. The objective of this study was to identify the quantitative trait loci (QTL) associated with the isoflavones daidzein (DC), genistein (GeC), glycitein (GlC) and total isoflavone ...

  13. Quantitative trait loci mapping and genetic dissection for lint ...

    Indian Academy of Sciences (India)

    2014-08-01

    Aug 1, 2014 ... Quantitative trait loci mapping and genetic dissection for lint percentage in upland cotton (Gossypium hirsutum). MIN WANG1, CHENGQI LI2 and QINGLIAN WANG2∗. 1Beijing Key Laboratory of Plant Resources Research and Development, Beijing Technology and Business University,. Beijing 100048 ...

  14. Quantitative trait loci analysis of individual and total isoflavone ...

    Indian Academy of Sciences (India)

    2014-08-19

    Aug 19, 2014 ... Abstract. Soybean isoflavones play diverse roles in human health, including cancers, osteoporosis, heart disease, menopausal symptoms and pabulums. The objective of this study was to identify the quantitative trait loci (QTL) associated with the isoflavones daidzein (DC), genistein (GeC), glycitein (GlC) ...

  15. Quantitative trait loci (QTL) mapping for inflorescence length traits in ...

    African Journals Online (AJOL)

    A molecular linkage map was constructed using a F2 population derived from the cross (Meidou2012 × Nanhui 23). The map covers 1302.4 cm with 131 loci (122 RAPD and nine morphological markers) and consist 14 linkage groups. In the F2 population and derived F3 families, a total of 46 QTLs explained from 8.1 to ...

  16. Linkage Analysis of Quantitative Trait Loci in the Presence of Heterogeneity

    DEFF Research Database (Denmark)

    Ekstrøm, Claus Thorn; Dalgaard, Peter

    2003-01-01

    EM-algorithm; Gaussian mixture; Heterogeneity; Linkage; Population admixture; Quantitative trait loci (QTL); Variance components......EM-algorithm; Gaussian mixture; Heterogeneity; Linkage; Population admixture; Quantitative trait loci (QTL); Variance components...

  17. Comparative mapping of quantitative trait loci for tassel-related traits ...

    Indian Academy of Sciences (India)

    Comparative mapping of quantitative trait loci for tassel-related traits of maize in F2:3 populations and RIL populations. QIANG YI1*, YINGHONG LIU2*, XIANGGE ZHANG1, XIANBIN HOU1, JUNJIE ZHANG3,. HANMEI LIU3, YUFENG HU1, GUOWU YU1, YUBI HUANG1+. 1Agronomy College, Sichuan Agricultural ...

  18. Quantitative trait loci for milk production and functional traits in two Danish Cattle breeds

    DEFF Research Database (Denmark)

    Mai, M D; Rychtarova, J; Zink, V

    2010-01-01

    Quantitative trait loci (QTL) in Danish Jersey and Danish Red cattle were independently mapped by least squares regression analysis. For Jersey breed, five grandsire families were genotyped for 186 markers on 16 chromosomes (BTAs). Eight traits analysed were milk yield (MY), fat percentage (FP...

  19. Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle

    NARCIS (Netherlands)

    Schrooten, C.; Bovenhuis, H.; Coppieters, W.; Arendonk, van J.A.M.

    2000-01-01

    A granddaughter design was used to locate quantitative trait loci determining conformation and functional traits in dairy cattle. In this granddaughter design, consisting of 20 Holstein Friesian grandsires and 833 sons, genotypes were determined for 277 microsatellite markers covering the whole

  20. Mapping quantitative trait loci for binary trait in the F2:3 design

    Indian Academy of Sciences (India)

    In the analysis of inheritance of quantitative traits with low heritability, an F2:3 design that genotypes plants in F2 and phe- notypes plants in F2:3 progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F2:3 design have been well developed, those for binary traits ...

  1. Quantitative trait loci analysis of swine meat quality traits

    DEFF Research Database (Denmark)

    Li, H D; Lund, M S; Christensen, O F

    2010-01-01

    loss, and the Minolta color measurements L*, a*, and b* representing meat lightness, redness, and yellowness, respectively. The families consist of 3,883 progenies of 12 Duroc boars that were evaluated to identify the QTL. The linkage map consists of 462 SNP markers on 18 porcine autosomes...... were estimated from a posterior distribution of the QTL position. In total, 31 QTL for the 6 meat quality traits were found to be significant at the 5% chromosome-wide level, among which 11 QTL were significant at the 5% genome-wide level and 5 of these were significant at the 0.1% genome-wide level...... will be helpful for fine mapping and identifying genes affecting meat quality traits, and tightly linked markers may be incorporated into marker-assisted selection programs...

  2. PEMETAAN QUANTITATIVE TRAIT LOCI UNTUK SIFAT BERSKALA KATEGORIK

    Directory of Open Access Journals (Sweden)

    Farit Mochamad Afendi

    2007-04-01

    Full Text Available Genes or regions on chromosome underlying a quantitative trait are called quantitative trait loci (QTL. Characterizing genes controlling quantitative trait on their position in chromosome and their effect on trait is through a process called QTL mapping. In estimating the QTL position and its effect, QTL mapping utilizes the association between QTL and DNA makers. However, many important traits are obtained in categorical scale, such as resistance from certain disease. From a theoritical point of view, QTL mapping method assuming continuous trait could not be applied to categorical trait. This research was facusing on the assessment of the performance of maximum likehood (ML and regression (REG approach employed in QTL mapping for binary trait by means of simulation study. The simulation study to evaluate the performance of ML and REG approach was conducted by taking into accounte several factors that may affecting the performance of both approaches. The factors are (1 maker density, (2 QTL effect, (3 sample size, and (4 shape of phenotypic distribution. Form simulation study, it was obtained that the two approaches showing comparable performance. Hence, QTL analysis could be performed using these two approaches due to their similar performance

  3. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

    Science.gov (United States)

    Berndt, Sonja I.; Gustafsson, Stefan; Mägi, Reedik; Ganna, Andrea; Wheeler, Eleanor; Feitosa, Mary F.; Justice, Anne E.; Monda, Keri L.; Croteau-Chonka, Damien C.; Day, Felix R.; Esko, Tõnu; Fall, Tove; Ferreira, Teresa; Gentilini, Davide; Jackson, Anne U.; Luan, Jian’an; Randall, Joshua C.; Vedantam, Sailaja; Willer, Cristen J.; Winkler, Thomas W.; Wood, Andrew R.; Workalemahu, Tsegaselassie; Hu, Yi-Juan; Lee, Sang Hong; Liang, Liming; Lin, Dan-Yu; Min, Josine L.; Neale, Benjamin M.; Thorleifsson, Gudmar; Yang, Jian; Albrecht, Eva; Amin, Najaf; Bragg-Gresham, Jennifer L.; Cadby, Gemma; den Heijer, Martin; Eklund, Niina; Fischer, Krista; Goel, Anuj; Hottenga, Jouke-Jan; Huffman, Jennifer E.; Jarick, Ivonne; Johansson, Åsa; Johnson, Toby; Kanoni, Stavroula; Kleber, Marcus E.; König, Inke R.; Kristiansson, Kati; Kutalik, Zoltán; Lamina, Claudia; Lecoeur, Cecile; Li, Guo; Mangino, Massimo; McArdle, Wendy L.; Medina-Gomez, Carolina; Müller-Nurasyid, Martina; Ngwa, Julius S.; Nolte, Ilja M.; Paternoster, Lavinia; Pechlivanis, Sonali; Perola, Markus; Peters, Marjolein J.; Preuss, Michael; Rose, Lynda M.; Shi, Jianxin; Shungin, Dmitry; Smith, Albert Vernon; Strawbridge, Rona J.; Surakka, Ida; Teumer, Alexander; Trip, Mieke D.; Tyrer, Jonathan; Van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Waite, Lindsay L.; Zhao, Jing Hua; Absher, Devin; Asselbergs, Folkert W.; Atalay, Mustafa; Attwood, Antony P.; Balmforth, Anthony J.; Basart, Hanneke; Beilby, John; Bonnycastle, Lori L.; Brambilla, Paolo; Bruinenberg, Marcel; Campbell, Harry; Chasman, Daniel I.; Chines, Peter S.; Collins, Francis S.; Connell, John M.; Cookson, William; de Faire, Ulf; de Vegt, Femmie; Dei, Mariano; Dimitriou, Maria; Edkins, Sarah; Estrada, Karol; Evans, David M.; Farrall, Martin; Ferrario, Marco M.; Ferrières, Jean; Franke, Lude; Frau, Francesca; Gejman, Pablo V.; Grallert, Harald; Grönberg, Henrik; Gudnason, Vilmundur; Hall, Alistair S.; Hall, Per; Hartikainen, Anna-Liisa; Hayward, Caroline; Heard-Costa, Nancy L.; Heath, Andrew C.; Hebebrand, Johannes; Homuth, Georg; Hu, Frank B.; Hunt, Sarah E.; Hyppönen, Elina; Iribarren, Carlos; Jacobs, Kevin B.; Jansson, John-Olov; Jula, Antti; Kähönen, Mika; Kathiresan, Sekar; Kee, Frank; Khaw, Kay-Tee; Kivimaki, Mika; Koenig, Wolfgang; Kraja, Aldi T.; Kumari, Meena; Kuulasmaa, Kari; Kuusisto, Johanna; Laitinen, Jaana H.; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Lind, Lars; Lindström, Jaana; Liu, Jianjun; Liuzzi, Antonio; Lokki, Marja-Liisa; Lorentzon, Mattias; Madden, Pamela A.; Magnusson, Patrik K.; Manunta, Paolo; Marek, Diana; März, Winfried; Mateo Leach, Irene; McKnight, Barbara; Medland, Sarah E.; Mihailov, Evelin; Milani, Lili; Montgomery, Grant W.; Mooser, Vincent; Mühleisen, Thomas W.; Munroe, Patricia B.; Musk, Arthur W.; Narisu, Narisu; Navis, Gerjan; Nicholson, George; Nohr, Ellen A.; Ong, Ken K.; Oostra, Ben A.; Palmer, Colin N.A.; Palotie, Aarno; Peden, John F.; Pedersen, Nancy; Peters, Annette; Polasek, Ozren; Pouta, Anneli; Pramstaller, Peter P.; Prokopenko, Inga; Pütter, Carolin; Radhakrishnan, Aparna; Raitakari, Olli; Rendon, Augusto; Rivadeneira, Fernando; Rudan, Igor; Saaristo, Timo E.; Sambrook, Jennifer G.; Sanders, Alan R.; Sanna, Serena; Saramies, Jouko; Schipf, Sabine; Schreiber, Stefan; Schunkert, Heribert; Shin, So-Youn; Signorini, Stefano; Sinisalo, Juha; Skrobek, Boris; Soranzo, Nicole; Stančáková, Alena; Stark, Klaus; Stephens, Jonathan C.; Stirrups, Kathleen; Stolk, Ronald P.; Stumvoll, Michael; Swift, Amy J.; Theodoraki, Eirini V.; Thorand, Barbara; Tregouet, David-Alexandre; Tremoli, Elena; Van der Klauw, Melanie M.; van Meurs, Joyce B.J.; Vermeulen, Sita H.; Viikari, Jorma; Virtamo, Jarmo; Vitart, Veronique; Waeber, Gérard; Wang, Zhaoming; Widén, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Winkelmann, Bernhard R.; Witteman, Jacqueline C.M.; Wolffenbuttel, Bruce H.R.; Wong, Andrew; Wright, Alan F.; Zillikens, M. Carola; Amouyel, Philippe; Boehm, Bernhard O.; Boerwinkle, Eric; Boomsma, Dorret I.; Caulfield, Mark J.; Chanock, Stephen J.; Cupples, L. Adrienne; Cusi, Daniele; Dedoussis, George V.; Erdmann, Jeanette; Eriksson, Johan G.; Franks, Paul W.; Froguel, Philippe; Gieger, Christian; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hengstenberg, Christian; Hicks, Andrew A.; Hingorani, Aroon; Hinney, Anke; Hofman, Albert; Hovingh, Kees G.; Hveem, Kristian; Illig, Thomas; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Keinanen-Kiukaanniemi, Sirkka M.; Kiemeney, Lambertus A.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Levinson, Douglas F.; Martin, Nicholas G.; Metspalu, Andres; Morris, Andrew D.; Nieminen, Markku S.; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Ouwehand, Willem H.; Palmer, Lyle J.; Penninx, Brenda; Power, Chris; Province, Michael A.; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Ridker, Paul M.; Ripatti, Samuli; Salomaa, Veikko; Samani, Nilesh J.; Snieder, Harold; Sørensen, Thorkild I.A.; Spector, Timothy D.; Stefansson, Kari; Tönjes, Anke; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; van der Harst, Pim; Vollenweider, Peter; Wallaschofski, Henri; Wareham, Nicholas J.; Watkins, Hugh; Wichmann, H.-Erich; Wilson, James F.; Abecasis, Goncalo R.; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunian, Talin; Heid, Iris M.; Hunter, David; Kaplan, Robert C.; Karpe, Fredrik; Moffatt, Miriam; Mohlke, Karen L.; O’Connell, Jeffrey R.; Pawitan, Yudi; Schadt, Eric E.; Schlessinger, David; Steinthorsdottir, Valgerdur; Strachan, David P.; Thorsteinsdottir, Unnur; van Duijn, Cornelia M.; Visscher, Peter M.; Di Blasio, Anna Maria; Hirschhorn, Joel N.; Lindgren, Cecilia M.; Morris, Andrew P.; Meyre, David; Scherag, André; McCarthy, Mark I.; Speliotes, Elizabeth K.; North, Kari E.; Loos, Ruth J.F.; Ingelsson, Erik

    2014-01-01

    Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups. PMID:23563607

  4. Novel quantitative trait loci for blood pressure and related traits on rat chromosomes 1, 10, and 18.

    Science.gov (United States)

    Kovács, P; Voigt, B; Klöting, I

    1997-06-18

    Hypertension and diabetes mellitus are known to be frequently associated. The genetic dissection of diseases such as hypertension or diabetes mellitus is possible by using experimental crosses, which allow identification of loci influencing phenotypic traits (quantitative trait loci - QTLs). In this study the spontaneously hypertensive rat (SHR) and spontaneously diabetic, but normotensive rat (BB/OK) were crossed and the F2 population was analysed in order to search for QTLs on selected chromosomes (1, 10, 18) for blood pressure and some metabolic traits related to diabetes, renal function and hypertension. There were 3 regions found on chromosome 1 which showed linkage to blood pressure. The strongest evidence for linkage was observed between loci Igf2 and D1Mgh12. On chromosome 10 there was a QTL for blood pressure found between Ppy and Abp and on chromosome 18 there were three regions (Ttr-Grl, Tilp-Gja1, Olf-D18Mit9) with linkage to blood pressure. Since the 24 hr albumin and phosphate excretion correlated with blood pressure in F2 hybrids, the same regions were linked to both parameters. Region with linkage to serum concentrations of cholesterol (probably located beyond the terminal marker Ttr of the linkage group) were also found. The results of this study with a new F2(BB x SHR) population confirm the existence of previously described blood pressure loci (Sa and Bp2) and showed novel QTLs on chromosomes 1, 10 and 18.

  5. Functional mapping imprinted quantitative trait loci underlying developmental characteristics

    Directory of Open Access Journals (Sweden)

    Li Gengxin

    2008-03-01

    Full Text Available Abstract Background Genomic imprinting, a phenomenon referring to nonequivalent expression of alleles depending on their parental origins, has been widely observed in nature. It has been shown recently that the epigenetic modification of an imprinted gene can be detected through a genetic mapping approach. Such an approach is developed based on traditional quantitative trait loci (QTL mapping focusing on single trait analysis. Recent studies have shown that most imprinted genes in mammals play an important role in controlling embryonic growth and post-natal development. For a developmental character such as growth, current approach is less efficient in dissecting the dynamic genetic effect of imprinted genes during individual ontology. Results Functional mapping has been emerging as a powerful framework for mapping quantitative trait loci underlying complex traits showing developmental characteristics. To understand the genetic architecture of dynamic imprinted traits, we propose a mapping strategy by integrating the functional mapping approach with genomic imprinting. We demonstrate the approach through mapping imprinted QTL controlling growth trajectories in an inbred F2 population. The statistical behavior of the approach is shown through simulation studies, in which the parameters can be estimated with reasonable precision under different simulation scenarios. The utility of the approach is illustrated through real data analysis in an F2 family derived from LG/J and SM/J mouse stains. Three maternally imprinted QTLs are identified as regulating the growth trajectory of mouse body weight. Conclusion The functional iQTL mapping approach developed here provides a quantitative and testable framework for assessing the interplay between imprinted genes and a developmental process, and will have important implications for elucidating the genetic architecture of imprinted traits.

  6. Quantitative trait loci for rice yield-related traits using recombinant ...

    Indian Academy of Sciences (India)

    2011-08-19

    Aug 19, 2011 ... [Bai X. F., Luo L. J., Yan W. H., Kovi M. R. and Xing Y. Z. 2011 Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars. J. Genet. 90, 209–215]. Introduction. Rice is the staple food for most of the people in the world. With the increasing world population ...

  7. Genome Scan Detects Quantitative Trait Loci Affecting Female Fertility Traits in Danish and Swedish Holstein Cattle

    DEFF Research Database (Denmark)

    Höglund, Johanna Karolina; Guldbrandtsen, B; Su, G

    2009-01-01

    Data from the joint Nordic breeding value prediction for Danish and Swedish Holstein grandsire families were used to locate quantitative trait loci (QTL) for female fertility traits in Danish and Swedish Holstein cattle. Up to 36 Holstein grandsires with over 2,000 sons were genotyped for 416 mic...... for QTL segregating on Bos taurus chromosome (BTA)1, BTA7, BTA10, and BTA26. On each of these chromosomes, several QTL were detected affecting more than one of the fertility traits investigated in this study. Evidence for segregation of additional QTL on BTA2, BTA9, and BTA24 was found...

  8. Quantitative trait loci for yield and morphological traits in maize under drought stress

    Directory of Open Access Journals (Sweden)

    Nikolić Ana

    2011-01-01

    Full Text Available Drought is one of the most important factors contributing to crop yield loss. In order to develop maize varieties with drought tolerance, it is necessary to explore the genetic basis. Mapping quantitative trait loci (QTL that control the yield and associate agronomic traits is one way of understanding drought genetics. QTLs associated with grain yield (GY, leaf width (LW3, LW4 plant height (PH, ear height (EH, leaf number (NL, tassel branch number (TBN and tassel length (TL were studied with composite interval mapping. A total of 43 QTLs were detected, distributed on all chromosomes, except chromosome 9. Phenotypic variability determined for the identified QTLs for all the traits was in the range from 20.99 to 87.24%. Mapping analysis identified genomic regions associated with two traits in a manner that was consistent with phenotypic correlation among traits, supporting either pleiotropy or tight linkage among QTLs.

  9. 52 Genetic Loci Influencing Myocardial Mass

    Science.gov (United States)

    van der Harst, Pim; van Setten, Jessica; Verweij, Niek; Vogler, Georg; Franke, Lude; Maurano, Matthew T.; Wang, Xinchen; Leach, Irene Mateo; Eijgelsheim, Mark; Sotoodehnia, Nona; Hayward, Caroline; Sorice, Rossella; Meirelles, Osorio; Lyytikäinen, Leo-Pekka; Polašek, Ozren; Tanaka, Toshiko; Arking, Dan E.; Ulivi, Sheila; Trompet, Stella; Müller-Nurasyid, Martina; Smith, Albert V.; Dörr, Marcus; Kerr, Kathleen F.; Magnani, Jared W.; Fabiola Del Greco, M.; Zhang, Weihua; Nolte, Ilja M.; Silva, Claudia T.; Padmanabhan, Sandosh; Tragante, Vinicius; Esko, Tõnu; Abecasis, Gonçalo R.; Adriaens, Michiel E.; Andersen, Karl; Barnett, Phil; Bis, Joshua C.; Bodmer, Rolf; Buckley, Brendan M.; Campbell, Harry; Cannon, Megan V.; Chakravarti, Aravinda; Chen, Lin Y.; Delitala, Alessandro; Devereux, Richard B.; Doevendans, Pieter A.; Dominiczak, Anna F.; Ferrucci, Luigi; Ford, Ian; Gieger, Christian; Harris, Tamara B.; Haugen, Eric; Heinig, Matthias; Hernandez, Dena G.; Hillege, Hans L.; Hirschhorn, Joel N.; Hofman, Albert; Hubner, Norbert; Hwang, Shih-Jen; Iorio, Annamaria; Kähönen, Mika; Kellis, Manolis; Kolcic, Ivana; Kooner, Ishminder K.; Kooner, Jaspal S.; Kors, Jan A.; Lakatta, Edward G.; Lage, Kasper; Launer, Lenore J.; Levy, Daniel; Lundby, Alicia; Macfarlane, Peter W.; May, Dalit; Meitinger, Thomas; Metspalu, Andres; Nappo, Stefania; Naitza, Silvia; Neph, Shane; Nord, Alex S.; Nutile, Teresa; Okin, Peter M.; Olsen, Jesper V.; Oostra, Ben A.; Penninger, Josef M.; Pennacchio, Len A.; Pers, Tune H.; Perz, Siegfried; Peters, Annette; Pinto, Yigal M.; Pfeufer, Arne; Pilia, Maria Grazia; Pramstaller, Peter P.; Prins, Bram P.; Raitakari, Olli T.; Raychaudhuri, Soumya; Rice, Ken M.; Rossin, Elizabeth J.; Rotter, Jerome I.; Schafer, Sebastian; Schlessinger, David; Schmidt, Carsten O.; Sehmi, Jobanpreet; Silljé, Herman H.W.; Sinagra, Gianfranco; Sinner, Moritz F.; Slowikowski, Kamil; Soliman, Elsayed Z.; Spector, Timothy D.; Spiering, Wilko; Stamatoyannopoulos, John A.; Stolk, Ronald P.; Strauch, Konstantin; Tan, Sian-Tsung; Tarasov, Kirill V.; Trinh, Bosco; Uitterlinden, Andre G.; van den Boogaard, Malou; van Duijn, Cornelia M.; van Gilst, Wiek H.; Viikari, Jorma S.; Visscher, Peter M.; Vitart, Veronique; Völker, Uwe; Waldenberger, Melanie; Weichenberger, Christian X.; Westra, Harm-Jan; Wijmenga, Cisca; Wolffenbuttel, Bruce H.; Yang, Jian; Bezzina, Connie R.; Munroe, Patricia B.; Snieder, Harold; Wright, Alan F.; Rudan, Igor; Boyer, Laurie A.; Asselbergs, Folkert W.; van Veldhuisen, Dirk J.; Stricker, Bruno H.; Psaty, Bruce M.; Ciullo, Marina; Sanna, Serena; Lehtimäki, Terho; Wilson, James F.; Bandinelli, Stefania; Alonso, Alvaro; Gasparini, Paolo; Jukema, J. Wouter; Kääb, Stefan; Gudnason, Vilmundur; Felix, Stephan B.; Heckbert, Susan R.; de Boer, Rudolf A.; Newton-Cheh, Christopher; Hicks, Andrew A.; Chambers, John C.; Jamshidi, Yalda; Visel, Axel; Christoffels, Vincent M.; Isaacs, Aaron; Samani, Nilesh J.; de Bakker, Paul I.W.

    2017-01-01

    BACKGROUND Myocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death. OBJECTIVES This meta-analysis sought to gain insights into the genetic determinants of myocardial mass. METHODS We carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment. RESULTS We identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10−8. These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo. CONCLUSIONS Taken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets. PMID:27659466

  10. Mapping of quantitative trait loci for flesh colour and growth traits in Atlantic salmon (Salmo salar

    Directory of Open Access Journals (Sweden)

    Moen Thomas

    2010-06-01

    Full Text Available Abstract Background Flesh colour and growth related traits in salmonids are both commercially important and of great interest from a physiological and evolutionary perspective. The aim of this study was to identify quantitative trait loci (QTL affecting flesh colour and growth related traits in an F2 population derived from an isolated, landlocked wild population in Norway (Byglands Bleke and a commercial production population. Methods One hundred and twenty-eight informative microsatellite loci distributed across all 29 linkage groups in Atlantic salmon were genotyped in individuals from four F2 families that were selected from the ends of the flesh colour distribution. Genotyping of 23 additional loci and two additional families was performed on a number of linkage groups harbouring putative QTL. QTL analysis was performed using a line-cross model assuming fixation of alternate QTL alleles and a half-sib model with no assumptions about the number and frequency of QTL alleles in the founder populations. Results A moderate to strong phenotypic correlation was found between colour, length and weight traits. In total, 13 genome-wide significant QTL were detected for all traits using the line-cross model, including three genome-wide significant QTL for flesh colour (Chr 6, Chr 26 and Chr 4. In addition, 32 suggestive QTL were detected (chromosome-wide P Conclusions A large number of significant and suggestive QTL for flesh colour and growth traits were found in an F2 population of Atlantic salmon. Chr 26 and Chr 4 presented the strongest evidence for significant QTL affecting flesh colour, while Chr 10, Chr 5, and Chr 4 presented the strongest evidence for significant QTL affecting growth traits (length and weight. These QTL could be strong candidates for use in marker-assisted selection and provide a starting point for further characterisation of the genetic components underlying flesh colour and growth.

  11. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals

    NARCIS (Netherlands)

    Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas; Perry, John R. B.; Yuan, Xin; Scott, Robert A.; Henneman, Peter; Heid, Iris M.; Kizer, Jorge R.; Lyytikäinen, Leo-Pekka; Fuchsberger, Christian; Tanaka, Toshiko; Morris, Andrew P.; Small, Kerrin; Isaacs, Aaron; Beekman, Marian; Coassin, Stefan; Lohman, Kurt; Qi, Lu; Kanoni, Stavroula; Pankow, James S.; Uh, Hae-Won; Wu, Ying; Bidulescu, Aurelian; Rasmussen-Torvik, Laura J.; Greenwood, Celia M. T.; Ladouceur, Martin; Grimsby, Jonna; Manning, Alisa K.; Liu, Ching-Ti; Kooner, Jaspal; Mooser, Vincent E.; Vollenweider, Peter; Kapur, Karen A.; Chambers, John; Wareham, Nicholas J.; Langenberg, Claudia; Frants, Rune; Willems-Vandijk, Ko; Oostra, Ben A.; Willems, Sara M.; Lamina, Claudia; Winkler, Thomas W.; Psaty, Bruce M.; Tracy, Russell P.; Brody, Jennifer; Chen, Ida; Viikari, Jorma; Kähönen, Mika; Pramstaller, Peter P.; Evans, David M.; St Pourcain, Beate; Sattar, Naveed; Wood, Andrew R.; Bandinelli, Stefania; Carlson, Olga D.; Egan, Josephine M.; Böhringer, Stefan; van Heemst, Diana; Kedenko, Lyudmyla; Kristiansson, Kati; Nuotio, Marja-Liisa; Loo, Britt-Marie; Harris, Tamara; Garcia, Melissa; Kanaya, Alka; Haun, Margot; Klopp, Norman; Wichmann, H.-Erich; Deloukas, Panos; Katsareli, Efi; Couper, David J.; Duncan, Bruce B.; Kloppenburg, Margreet; Adair, Linda S.; Borja, Judith B.; Wilson, James G.; Musani, Solomon; Guo, Xiuqing; Johnson, Toby; Semple, Robert; Teslovich, Tanya M.; Allison, Matthew A.; Redline, Susan; Buxbaum, Sarah G.; Mohlke, Karen L.; Meulenbelt, Ingrid; Ballantyne, Christie M.; Dedoussis, George V.; Hu, Frank B.; Liu, Yongmei; Paulweber, Bernhard; Spector, Timothy D.; Slagboom, P. Eline; Ferrucci, Luigi; Jula, Antti; Perola, Markus; Raitakari, Olli; Florez, Jose C.; Salomaa, Veikko; Eriksson, Johan G.; Frayling, Timothy M.; Hicks, Andrew A.; Lehtimäki, Terho; Smith, George Davey; Siscovick, David S.; Kronenberg, Florian; van Duijn, Cornelia; Loos, Ruth J. F.; Waterworth, Dawn M.; Meigs, James B.; Dupuis, Josee; Richards, J. Brent; Voight, Benjamin F.; Scott, Laura J.; Steinthorsdottir, Valgerdur; Dina, Christian; Welch, Ryan P.; Zeggini, Eleftheria; Huth, Cornelia; Aulchenko, Yurii S.; Thorleifsson, Gudmar; Mcculloch, Laura J.; Ferreira, Teresa; Grallert, Harald; Amin, Najaf; Wu, Guanming; Willer, Cristen J.; Raychaudhuri, Soumya; Mccarroll, Steve A.; Hofmann, Oliver M.; Segrè, Ayellet V.; van Hoek, Mandy; Navarro, Pau; Ardlie, Kristin; Balkau, Beverley; Benediktsson, Rafn; Bennett, Amanda J.; Blagieva, Roza; Boerwinkle, Eric; Bonnycastle, Lori L.; Boström, Kristina Bengtsson; Bravenboer, Bert; Bumpstead, Suzannah; Burtt, Noël P.; Charpentier, Guillaume; Chines, Peter S.; Cornelis, Marilyn; Crawford, Gabe; Doney, Alex S. F.; Elliott, Katherine S.; Elliott, Amanda L.; Erdos, Michael R.; Fox, Caroline S.; Franklin, Christopher S.; Ganser, Martha; Gieger, Christian; Grarup, Niels; Green, Todd; Griffin, Simon; Groves, Christopher J.; Guiducci, Candace; Hadjadj, Samy; Hassanali, Neelam; Herder, Christian; Isomaa, Bo; Jackson, Anne U.; Johnson, Paul R. V.; Jørgensen, Torben; Kao, Wen H. L.; Kong, Augustine; Kraft, Peter; Kuusisto, Johanna; Lauritzen, Torsten; Li, Man; Lieverse, Aloysius; Lindgren, Cecilia M.; Lyssenko, Valeriya; Marre, Michel; Meitinger, Thomas; Midthjell, Kristian; Morken, Mario A.; Narisu, Narisu; Nilsson, Peter; Owen, Katharine R.; Payne, Felicity; Petersen, Ann-Kristin; Platou, Carl; Proença, Christine; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, N. William; Robertson, Neil R.; Rocheleau, Ghislain; Roden, Michael; Sampson, Michael J.; Saxena, Richa; Shields, Beverley M.; Shrader, Peter; Sigurdsson, Gunnar; Sparsø, Thomas; Strassburger, Klaus; Stringham, Heather M.; Sun, Qi; Swift, Amy J.; Thorand, Barbara; Tichet, Jean; Tuomi, Tiinamaija; van Dam, Rob M.; van Haeften, Timon W.; van Herpt, Thijs; van Vliet-Ostaptchouk, Jana V.; Walters, G. Bragi; Weedon, Michael N.; Wijmenga, Cisca; Witteman, Jacqueline; Bergman, Richard N.; Cauchi, Stephane; Collins, Francis S.; Gloyn, Anna L.; Gyllensten, Ulf; Hansen, Torben; Hide, Winston A.; Hitman, Graham A.; Hofman, Albert; Hunter, David J.; Hveem, Kristian; Laakso, Markku; Morris, Andrew D.; Palmer, Colin N. A.; Rudan, Igor; Sijbrands, Eric; Stein, Lincoln D.; Tuomilehto, Jaakko; Uitterlinden, Andre; Walker, Mark; Watanabe, Richard M.; Abecasis, Goncalo R.; Boehm, Bernhard O.; Campbell, Harry; Daly, Mark J.; Hattersley, Andrew T.; Pedersen, Oluf; Barroso, Inês; Groop, Leif; Sladek, Rob; Thorsteinsdottir, Unnur; Wilson, James F.; Illig, Thomas; Froguel, Philippe; van Duijn, Cornelia M.; Stefansson, Kari; Altshuler, David; Boehnke, Michael; McCarthy, Mark I.; Soranzo, Nicole; Wheeler, Eleanor; Glazer, Nicole L.; Bouatia-Naji, Nabila; Mägi, Reedik; Randall, Joshua; Elliott, Paul; Rybin, Denis; Dehghan, Abbas; Hottenga, Jouke Jan; Song, Kijoung; Goel, Anuj; Lajunen, Taina; Doney, Alex; Cavalcanti-Proença, Christine; Kumari, Meena; Timpson, Nicholas J.; Zabena, Carina; Ingelsson, Erik; An, Ping; O'Connell, Jeffrey; Luan, Jian'an; Elliott, Amanda; McCarroll, Steven A.; Roccasecca, Rosa Maria; Pattou, François; Sethupathy, Praveen; Ariyurek, Yavuz; Barter, Philip; Beilby, John P.; Ben-Shlomo, Yoav; Bergmann, Sven; Bochud, Murielle; Bonnefond, Amélie; Borch-Johnsen, Knut; Böttcher, Yvonne; Brunner, Eric; Bumpstead, Suzannah J.; Chen, Yii-Der Ida; Chines, Peter; Clarke, Robert; Coin, Lachlan J. M.; Cooper, Matthew N.; Crisponi, Laura; Day, Ian N. M.; de Geus, Eco J. C.; Delplanque, Jerome; Fedson, Annette C.; Fischer-Rosinsky, Antje; Forouhi, Nita G.; Franzosi, Maria Grazia; Galan, Pilar; Goodarzi, Mark O.; Graessler, Jürgen; Grundy, Scott; Gwilliam, Rhian; Hallmans, Göran; Hammond, Naomi; Han, Xijing; Hartikainen, Anna-Liisa; Hayward, Caroline; Heath, Simon C.; Hercberg, Serge; Hillman, David R.; Hingorani, Aroon D.; Hui, Jennie; Hung, Joe; Kaakinen, Marika; Kaprio, Jaakko; Kesaniemi, Y. Antero; Kivimaki, Mika; Knight, Beatrice; Koskinen, Seppo; Kovacs, Peter; Kyvik, Kirsten Ohm; Lathrop, G. Mark; Lawlor, Debbie A.; Le Bacquer, Olivier; Lecoeur, Cécile; Li, Yun; Mahley, Robert; Mangino, Massimo; Martínez-Larrad, María Teresa; McAteer, Jarred B.; McPherson, Ruth; Meisinger, Christa; Melzer, David; Meyre, David; Mitchell, Braxton D.; Mukherjee, Sutapa; Naitza, Silvia; Neville, Matthew J.; Orrù, Marco; Pakyz, Ruth; Paolisso, Giuseppe; Pattaro, Cristian; Pearson, Daniel; Peden, John F.; Pedersen, Nancy L.; Pfeiffer, Andreas F. H.; Pichler, Irene; Polasek, Ozren; Posthuma, Danielle; Potter, Simon C.; Pouta, Anneli; Province, Michael A.; Rayner, Nigel W.; Rice, Kenneth; Ripatti, Samuli; Rivadeneira, Fernando; Rolandsson, Olov; Sandbaek, Annelli; Sandhu, Manjinder; Sanna, Serena; Sayer, Avan Aihie; Scheet, Paul; Seedorf, Udo; Sharp, Stephen J.; Shields, Beverley; Sigurðsson, Gunnar; Sijbrands, Eric J. G.; Silveira, Angela; Simpson, Laila; Singleton, Andrew; Smith, Nicholas L.; Sovio, Ulla; Swift, Amy; Syddall, Holly; Syvänen, Ann-Christine; Tönjes, Anke; Uitterlinden, André G.; van Dijk, Ko Willems; Varma, Dhiraj; Visvikis-Siest, Sophie; Vitart, Veronique; Vogelzangs, Nicole; Waeber, Gérard; Wagner, Peter J.; Walley, Andrew; Ward, Kim L.; Watkins, Hugh; Wild, Sarah H.; Willemsen, Gonneke; Witteman, Jaqueline C. M.; Yarnell, John W. G.; Zelenika, Diana; Zethelius, Björn; Zhai, Guangju; Zhao, Jing Hua; Zillikens, M. Carola; Borecki, Ingrid B.; Meneton, Pierre; Magnusson, Patrik K. E.; Nathan, David M.; Williams, Gordon H.; Silander, Kaisa; Bornstein, Stefan R.; Schwarz, Peter; Spranger, Joachim; Karpe, Fredrik; Shuldiner, Alan R.; Cooper, Cyrus; Serrano-Ríos, Manuel; Lind, Lars; Palmer, Lyle J.; Franks, Paul W.; Ebrahim, Shah; Marmot, Michael; Kao, W. H. Linda; Pramstaller, Peter Paul; Wright, Alan F.; Stumvoll, Michael; Hamsten, Anders; Buchanan, Thomas A.; Valle, Timo T.; Rotter, Jerome I.; Penninx, Brenda W. J. H.; Boomsma, Dorret I.; Cao, Antonio; Scuteri, Angelo; Schlessinger, David; Uda, Manuela; Ruokonen, Aimo; Jarvelin, Marjo-Riitta; Peltonen, Leena; Mooser, Vincent; Sladek, Robert; Musunuru, Kiran; Smith, Albert V.; Edmondson, Andrew C.; Stylianou, Ioannis M.; Koseki, Masahiro; Pirruccello, James P.; Chasman, Daniel I.; Johansen, Christopher T.; Fouchier, Sigrid W.; Peloso, Gina M.; Barbalic, Maja; Ricketts, Sally L.; Bis, Joshua C.; Feitosa, Mary F.; Orho-Melander, Marju; Melander, Olle; Li, Xiaohui; Li, Mingyao; Cho, Yoon Shin; Go, Min Jin; Kim, Young Jin; Lee, Jong-Young; Park, Taesung; Kim, Kyunga; Sim, Xueling; Ong, Rick Twee-Hee; Croteau-Chonka, Damien C.; Lange, Leslie A.; Smith, Joshua D.; Ziegler, Andreas; Zhang, Weihua; Zee, Robert Y. L.; Whitfield, John B.; Thompson, John R.; Surakka, Ida; Spector, Tim D.; Smit, Johannes H.; Sinisalo, Juha; Scott, James; Saharinen, Juha; Sabatti, Chiara; Rose, Lynda M.; Roberts, Robert; Rieder, Mark; Parker, Alex N.; Pare, Guillaume; O'Donnell, Christopher J.; Nieminen, Markku S.; Nickerson, Deborah A.; Montgomery, Grant W.; McArdle, Wendy; Masson, David; Martin, Nicholas G.; Marroni, Fabio; Lucas, Gavin; Luben, Robert; Lokki, Marja-Liisa; Lettre, Guillaume; Launer, Lenore J.; Lakatta, Edward G.; Laaksonen, Reijo; Kyvik, Kirsten O.; König, Inke R.; Khaw, Kay-Tee; Kaplan, Lee M.; Johansson, Åsa; Janssens, A. Cecile J. W.; Igl, Wilmar; Hovingh, G. Kees; Hengstenberg, Christian; Havulinna, Aki S.; Hastie, Nicholas D.; Harris, Tamara B.; Haritunians, Talin; Hall, Alistair S.; Groop, Leif C.; Gonzalez, Elena; Freimer, Nelson B.; Erdmann, Jeanette; Ejebe, Kenechi G.; Döring, Angela; Dominiczak, Anna F.; Demissie, Serkalem; Deloukas, Panagiotis; de Faire, Ulf; Crawford, Gabriel; Chen, Yii-der I.; Caulfield, Mark J.; Boekholdt, S. Matthijs; Assimes, Themistocles L.; Quertermous, Thomas; Seielstad, Mark; Wong, Tien Y.; Tai, E.-Shyong; Feranil, Alan B.; Kuzawa, Christopher W.; Taylor, Herman A.; Gabriel, Stacey B.; Holm, Hilma; Gudnason, Vilmundur; Krauss, Ronald M.; Ordovas, Jose M.; Munroe, Patricia B.; Kooner, Jaspal S.; Tall, Alan R.; Hegele, Robert A.; Kastelein, John J. P.; Schadt, Eric E.; Strachan, David P.; Reilly, Muredach P.; Samani, Nilesh J.; Schunkert, Heribert; Cupples, L. Adrienne; Sandhu, Manjinder S.; Ridker, Paul M.; Rader, Daniel J.; Kathiresan, Sekar; Olson, Jean; Kronmal, Richard; Robbins, John; Chaves, Paulo H.; Burke, Gregory; Kuller, Lewis H.; Tracy, Russell; Gottdiener, John; Prineas, Ronald; Becker, James T.; Enright, Paul; Klein, Ronald; O'Leary, Daniel H.

    2012-01-01

    Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European

  12. Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: A multi-ethnic meta-analysis of 45,891 individuals

    NARCIS (Netherlands)

    Z. Dastani (Zari); M.-F. Hivert (Marie-France); N.J. Timpson (Nicholas); J.R.B. Perry (John); X. Yuan (Xin); R.A. Scott (Robert); P. Hennemann (Peter); I.M. Heid (Iris); J.R. Kizer (Jorge); L.-P. Lyytikäinen (Leo-Pekka); C. Fuchsberger (Christian); T. Tanaka (Toshiko); A.P. Morris (Andrew); K.S. Small (Kerrin); A.J. Isaacs (Aaron); M. Beekman (Marian); S. Coassin (Stefan); K. Lohman (Kurt); L. Qi (Lu); S. Kanoni (Stavroula); J.S. Pankow (James); H.-W. Uh (Hae-Won); Y. Wu (Ying); A. Bidulescu (Aurelian); L.J. Rasmussen-Torvik (Laura); C.M.T. Greenwood (Celia); M. Ladouceur (Martin); J.L. Grimsby (Jonna); A.K. Manning (Alisa); C.-T. Liu (Ching-Ti); J.S. Kooner (Jaspal); V. Mooser (Vincent); P. Vollenweider (Peter); K. Kapur (Karen); J. Chambers (John); N.J. Wareham (Nick); C. Langenberg (Claudia); R.R. Frants (Rune); J.A.P. Willems van Dijk (Ko); B.A. Oostra (Ben); S.M. Willems (Sara); C. Lamina (Claudia); T.W. Winkler (Thomas); B.M. Psaty (Bruce); R.P. Tracy (Russell); J. Brody (Jennifer); I. Chen (Ida); J. Viikari (Jorma); M. Kähönen (Mika); P.P. Pramstaller (Peter Paul); D.M. Evans (David); B. St Pourcain (Beate); N. Sattar (Naveed); A.R. Wood (Andrew); S. Bandinelli (Stefania); O.D. Carlson (Olga); J.M. Egan (Josephine); S. Böhringer (Stefan); D. van Heemst (Diana); L. Kedenko (Lyudmyla); K. Kristiansson (Kati); M.-L. Nuotio (Marja-Liisa); B.-M. Loo (Britt-Marie); T.B. Harris (Tamara); M. Garcia (Melissa); A. Kanaya (Alka); M. Haun (Margot); N. Klopp (Norman); H.E. Wichmann (Erich); P. Deloukas (Panagiotis); E. Katsareli (Efi); D.J. Couper (David); B.B. Duncan (Bruce); M. Kloppenburg (Margreet); L.S. Adair (Linda); J.B. Borja (Judith); J.G. Wilson (James); S. Musani (Solomon); X. Guo (Xiuqing); T. Johnson (Toby); R.K. Semple (Robert); T.M. Teslovich (Tanya); M.A. Allison (Matthew); S. Redline (Susan); S.G. Buxbaum (Sarah); K.L. Mohlke (Karen); I. Meulenbelt (Ingrid); C. Ballantyne (Christie); G.V. Dedoussis (George); F.B. Hu (Frank B.); Y. Liu (YongMei); B. Paulweber (Bernhard); T.D. Spector (Tim); P.E. Slagboom (Eline); L. Ferrucci (Luigi); A. Jula (Antti); M. Perola (Markus); O.T. Raitakari (Olli T.); J.C. Florez (Jose); V. Salomaa (Veikko); J.G. Eriksson (Johan); T.M. Frayling (Timothy); A.A. Hicks (Andrew); T. Lehtimäki (Terho); G.D. Smith (George Davey); D.S. Siscovick (David); F. Kronenberg (Florian); C.M. van Duijn (Cornelia); R.J.F. Loos (Ruth); D.M. Waterworth (Dawn); J.B. Meigs (James); J. Dupuis (Josée); J.B. Richards (Brent)

    2012-01-01

    textabstractCirculating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of

  13. Mapping quantitative trait loci for immune capacity in the pig.

    Science.gov (United States)

    Edfors-Lilja, I; Wattrang, E; Marklund, L; Moller, M; Andersson-Eklund, L; Andersson, L; Fossum, C

    1998-07-15

    Immune capacity traits show considerable genetic variation in outbred populations. To identify quantitative trait loci (QTLs) for immune capacity in the pig, various measures of immune function (total and differential leukocyte counts, neutrophil phagocytosis, mitogen-induced proliferation, IL-2 production, and virus induced IFN-alpha production in whole blood cultures, and Ab responses to two Escherichia coli antigens) were determined in 200 F2 animals from a wild pig-Swedish Yorkshire intercross. The pedigree has been typed for 236 genetic markers covering all autosomes, the X chromosome and the X/Y pseudoautosomal region. Through interval mapping using a least-squares method, four QTLs with significant effects were identified; one for total leukocyte counts, one for mitogen-induced proliferation, one for prevaccination levels of Abs to E. coli Ag K88, and one for Ab response to the O149 Ag. In addition, several putative QTLs were indicated. The results from the present study conclusively show that it is possible to identify QTLs for immune capacity traits in outbred pig populations by genome analysis.

  14. Quantitative trait loci analysis of melon (Cucumis melo L.) domestication-related traits.

    Science.gov (United States)

    Díaz, Aurora; Martín-Hernández, Ana Montserrat; Dolcet-Sanjuan, Ramón; Garcés-Claver, Ana; Álvarez, José María; Garcia-Mas, Jordi; Picó, Belén; Monforte, Antonio José

    2017-09-01

    Loci on LGIV, VI, and VIII of melon genome are involved in the control of fruit domestication-related traits and they are candidate to have played a role in the domestication of the crop. The fruit of wild melons is very small (20-50 g) without edible pulp, contrasting with the large size and high pulp content of cultivated melon fruits. An analysis of quantitative trait loci (QTL) controlling fruit morphology domestication-related traits was carried out using an in vitro maintained F 2 population from the cross between the Indian wild melon "Trigonus" and the western elite cultivar 'Piel de Sapo'. Twenty-seven QTL were identified in at least two out of the three field trials. Six of them were also being detected in BC1 and BC3 populations derived from the same cross. Ten of them were related to fruit morphological traits, 12 to fruit size characters, and 5 to pulp content. The Trigonus alleles decreased the value of the characters, except for the QTL at andromonoecious gene at linkage group (LG) II, and the QTL for pulp content at LGV. QTL genotypes accounted for a considerable degree of the total phenotypic variation, reaching up to 46%. Around 66% of the QTL showed additive gene action, 19% exhibited dominance, and 25% consisted of overdominance. The regions on LGIV, VI, and VIII included the QTL with more consistent and strong effects on domestication-related traits. QTLs on those regions were validated in BC2S1, BC2S2, and BC3 families, with "Trigonus" allele decreasing the fruit morphological traits in all cases. The validated QTL could represent loci involved in melon domestication, although further experiments as genomic variation studies across wild and cultivated genotypes would be necessary to confirm this hypothesis.

  15. Quantitative trait loci for udder conformation and other udder traits in Finnish Ayrshire cattle

    Directory of Open Access Journals (Sweden)

    N.F. SCHULMAN

    2008-12-01

    Full Text Available Udder traits are important due to their correlation with clinical mastitis which causes major economic losses to the dairy farms. Chromosomal areas associated with udder conformation traits, milking speed and leakage could be used in breeding programs to improve both udder traits and mastitis resistance. Quantitative trait loci (QTL mapping for udder traits was carried out on bovine chromosomes (BTA 9, 11, 14, 18, 20, 23, and 29, where earlier studies have indicated QTL for mastitis. A granddaughter design with 12 Ayrshire sire families and 360 sons was used. The sires and sons were typed for 35 markers. The traits analysed were udder depth, fore udder attachment, central ligament, distance from udder to floor, body stature, fore teat length, udder balance, rear udder height, milking speed, and leakage. Associations between markers and traits were analysed with multiple marker regression. Five genome-wise significant QTL were detected: stature on BTA14 and 23, udder balance on BTA23, rear udder height on BTA11, and central ligament on BTA23. On BTA11 and 14 the suggested QTL positions for udder traits are at the same position as previously detected QTL for mastitis and somatic cell count.;

  16. Comparing Quantitative Trait Loci and Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Bing Han

    2008-01-01

    Full Text Available We develop methods to compare the positions of quantitative trait loci (QTL with a set of genes selected by other methods, such as microarray experiments, from a sequenced genome. We apply our methods to QTL for addictive behavior in mouse, and a set of genes upregulated in a region of the brain associated with addictive behavior, the nucleus accumbens (NA. The association between the QTL and NA genes is not significantly stronger than expected by chance. However, chromosomes 2 and 16 do show strong associations suggesting that genes on these chromosomes might be associated with addictive behavior. The statistical methodology developed for this study can be applied to similar studies to assess the mutual information in microarray and QTL analyses.

  17. Quantitative trait loci linked to PRNP gene controlling health and production traits in INRA 401 sheep

    Directory of Open Access Journals (Sweden)

    Brunel Jean-Claude

    2007-07-01

    Full Text Available Abstract In this study, the potential association of PrP genotypes with health and productive traits was investigated. Data were recorded on animals of the INRA 401 breed from the Bourges-La Sapinière INRA experimental farm. The population consisted of 30 rams and 852 ewes, which produced 1310 lambs. The animals were categorized into three PrP genotype classes: ARR homozygous, ARR heterozygous, and animals without any ARR allele. Two analyses differing in the approach considered were carried out. Firstly, the potential association of the PrP genotype with disease (Salmonella resistance and production (wool and carcass traits was studied. The data used included 1042, 1043 and 1013 genotyped animals for the Salmonella resistance, wool and carcass traits, respectively. The different traits were analyzed using an animal model, where the PrP genotype effect was included as a fixed effect. Association analyses do not indicate any evidence of an effect of PrP genotypes on traits studied in this breed. Secondly, a quantitative trait loci (QTL detection approach using the PRNP gene as a marker was applied on ovine chromosome 13. Interval mapping was used. Evidence for one QTL affecting mean fiber diameter was found at 25 cM from the PRNP gene. However, a linkage between PRNP and this QTL does not imply unfavorable linkage disequilibrium for PRNP selection purposes.

  18. Fast and Accurate Detection of Multiple Quantitative Trait Loci

    Science.gov (United States)

    Nettelblad, Carl; Holmgren, Sverker

    2013-01-01

    Abstract We present a new computational scheme that enables efficient and reliable quantitative trait loci (QTL) scans for experimental populations. Using a standard brute-force exhaustive search effectively prohibits accurate QTL scans involving more than two loci to be performed in practice, at least if permutation testing is used to determine significance. Some more elaborate global optimization approaches, for example, DIRECT have been adopted earlier to QTL search problems. Dramatic speedups have been reported for high-dimensional scans. However, since a heuristic termination criterion must be used in these types of algorithms, the accuracy of the optimization process cannot be guaranteed. Indeed, earlier results show that a small bias in the significance thresholds is sometimes introduced. Our new optimization scheme, PruneDIRECT, is based on an analysis leading to a computable (Lipschitz) bound on the slope of a transformed objective function. The bound is derived for both infinite- and finite-size populations. Introducing a Lipschitz bound in DIRECT leads to an algorithm related to classical Lipschitz optimization. Regions in the search space can be permanently excluded (pruned) during the optimization process. Heuristic termination criteria can thus be avoided. Hence, PruneDIRECT has a well-defined error bound and can in practice be guaranteed to be equivalent to a corresponding exhaustive search. We present simulation results that show that for simultaneous mapping of three QTLS using permutation testing, PruneDIRECT is typically more than 50 times faster than exhaustive search. The speedup is higher for stronger QTL. This could be used to quickly detect strong candidate eQTL networks. PMID:23919387

  19. Genes and quality trait loci (QTLs) associated with firmness in Malus x domestica

    KAUST Repository

    Marondedze, Claudius

    2013-03-31

    Fruit firmness, a quality quantitative trait, has long been established as a key textural property and one of the essential parameters for estimating ripening and shelf life of apples. Loss of firmness, also referred to as fruit softening, is undesirable in apples and represents a serious problem for growers in many countries. This results in the reduction of apple shelf life and in turn influences its commercialization. Low firmness impacts negatively on the sensory values of juiciness, crunchiness and crispness. Fruit firmness is affected by the inheritance of alleles at multiple loci and their possible interactions with the environment. Identification of these loci is key for the determination of genetic candidate markers that can be implemented in marker assisted selection and breeding for trees and/or cultivars that can yield firmer fruits with economic value. In turn, this technique can help reduce the time needed to evaluate plants and new cultivars could become available faster. This review provides an overview of quantitative trait loci (QTL), including additional putative QTLs that we have identified, and genes associated with firmness and their importance to biotechnology, the breeding industry and eventually the consumers.

  20. Quantitative trait loci (QTL mapping for growth traits on bovine chromosome 14

    Directory of Open Access Journals (Sweden)

    Marcelo Miyata

    2007-03-01

    Full Text Available Quantitative trait loci (QTL mapping in livestock allows the identification of genes that determine the genetic variation affecting traits of economic interest. We analyzed the birth weight and weight at 60 days QTL segregating on bovine chromosome BTA14 in a F2 resource population using genotypes produced from seven microsatellite markers. Phenotypes were derived from 346 F2 progeny produced from crossing Bos indicus Gyr x Holstein Bos taurus F1 parents. Interval analysis to detect QTL for birth weight revealed the presence of a QTL (p < 0.05 at 1 centimorgan (cM from the centromere with an additive effect of 1.210 ± 0.438 kg. Interval analysis for weight at 60 days revealed the presence of a QTL (p < 0.05 at 0 cM from the centromere with an additive effect of 2.122 ± 0.735 kg. The region to which the QTL were assigned is described in the literature as responsible for some growth traits, milk yield, milk composition, fat deposition and has also been related to reproductive traits such as daughter pregnancy rate and ovulation rate. The effects of the QTL described on other traits were not investigated.

  1. Quantitative Trait Loci for Mercury Tolerance in Rice Seedlings

    Directory of Open Access Journals (Sweden)

    Chong-qing WANG

    2013-05-01

    Full Text Available Mercury (Hg is one of the most toxic heavy metals to living organisms and its conspicuous effect is the inhibition of root growth. However, little is known about the molecular genetic basis for root growth under excess Hg2+ stress. To map quantitative trait loci (QTLs in rice for Hg2+ tolerance, a population of 120 recombinant inbred lines derived from a cross between two japonica cultivars Yuefu and IRAT109 was grown in 0.5 mmol/L CaCl2 solution. Relative root length (RRL, percentage of the seminal root length in +HgCl2 to –HgCl2, was used for assessing Hg2+ tolerance. In a dose-response experiment, Yuefu had a higher RRL than IRAT109 and showed the most significant difference at the Hg2+ concentration of 1.5 μmol/L. Three putative QTLs for RRL were detected on chromosomes 1, 2 and 5, and totally explained about 35.7% of the phenotypic variance in Hg2+ tolerance. The identified QTLs for RRL might be useful for improving Hg2+ tolerance of rice by molecular marker-assisted selection.

  2. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

    NARCIS (Netherlands)

    Ried, J.S.; Jeff, J.M.; Chu, A.Y.; Bragg-Gresham, J.L.; van Dongen, J.; Huffman, J.E.; Ahluwalia, T.S.; Cadby, G.; Eklund, N.; Eriksson, J.; de Geus, E.J.C.; Hottenga, J.J.; Penninx, B.W.J.H.; Willemsen, G.; Boomsma, D.I.; McCarthy, M.I.; North, K.E.; O'Connell, J.R.; Schlessinger, D.; Thorsteinsdottir, U.; Strachan, D.P.; Frayling, T.M.; Hirschhorn, J.N.; Müller-Nurasyid, M.; Loos, R.J.F.

    2016-01-01

    Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates

  3. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

    DEFF Research Database (Denmark)

    Ried, J. S.; Jeff, J. M.; Chu, Audrey Y

    2016-01-01

    Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates...

  4. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

    NARCIS (Netherlands)

    J.S. Ried (Janina); J. Jeff (Janina); A.Y. Chu (Audrey Y); Bragg-Gresham, J.L. (Jennifer L.); J. van Dongen (Jenny); J.E. Huffman (Jennifer); T.S. Ahluwalia (Tarunveer Singh); G. Cadby (Gemma); N. Eklund (Niina); J. Eriksson (Joel); T. Esko (Tõnu); M.F. Feitosa (Mary Furlan); A. Goel (Anuj); M. Gorski (Mathias); C. Hayward (Caroline); N.L. Heard-Costa (Nancy); A.U. Jackson (Anne); Jokinen, E. (Eero); S. Kanoni (Stavroula); K. Kristiansson (Kati); Z. Kutalik (Zoltán); J. Lahti (Jari); J. Luan (Jian'An); R. Mägi (Reedik); A. Mahajan (Anubha); M. Mangino (Massimo); M.C. Medina-Gomez (Carolina); K.L. Monda (Keri); I.M. Nolte (Ilja); L. Perusse (Louis); I. Prokopenko (Inga); Qi, L. (Lu); L.M. Rose (Lynda); Salvi, E. (Erika); Smith, M.T. (Megan T.); H. Snieder (Harold); Standáková, A. (Alena); Ju Sung, Y. (Yun); I. Tachmazidou (Ioanna); A. Teumer (Alexander); G. Thorleifsson (Gudmar); P. van der Harst (Pim); Walker, R.W. (Ryan W.); S.R. Wang (Sophie); S.H. Wild (Sarah); S.M. Willems (Sara); A. Wong (Andrew); W. Zhang (Weihua); E. Albrecht (Eva); A. Couto-Alves (Alexessander); S.J.L. Bakker (Stephan); Barlassina, C. (Cristina); T.M. Bartz (Traci M.); J.P. Beilby (John); C. Bellis (Claire); Bergman, R.N. (Richard N.); S.M. Bergmann (Sven); J. Blangero (John); M. Blüher (Matthias); E.A. Boerwinkle (Eric); L.L. Bonnycastle (Lori); S.R. Bornstein (Stefan R.); M. Bruinenberg (M.); H. Campbell (Harry); Y.-D.I. Chen (Yii-Der Ida); Chiang, C.W.K. (Charleston W. K.); P.S. Chines (Peter); F.S. Collins (Francis); Cucca, F. (Fracensco); L.A. Cupples (Adrienne); D'avila, F. (Francesca); E.J.C. de Geus (Eco); G.V. Dedoussis (George); M. Dimitriou (Maria); A. Döring (Angela); K. Hagen (Knut); A.-E. Farmaki (Aliki-Eleni); M. Farrall (Martin); T. Ferreira (Teresa); K. Fischer (Krista); N.G. Forouhi (Nita); N. Friedrich (Nele); A.P. Gjesing (Anette); N. Glorioso (Nicola); M.J. Graff (Maud J.L.); H. Grallert (Harald); N. Grarup (Niels); J. Gräßler (Jürgen); J. Grewal (Jagvir); A. Hamsten (Anders); Harder, M.N. (Marie Neergaard); Hartman, C.A. (Catharina A.); Hassinen, M. (Maija); N. Hastie (Nick); A.T. Hattersley (Andrew); A.S. Havulinna (Aki); M. Heliovaara (Markku); H.L. Hillege (Hans); A. Hofman (Albert); O.L. Holmen (Oddgeir); G. Homuth (Georg); J.J. Hottenga (Jouke Jan); J. Hui (Jennie); L.L.N. Husemoen (Lise Lotte); P.G. Hysi (Pirro); A.J. Isaacs (Aaron); T. Ittermann (Till); S. Jalilzadeh (Shapour); A. James (Alan); T. Jorgensen (Torben); P. Jousilahti (Pekka); A. Jula (Antti); Marie Justesen, J. (Johanne); A.E. Justice (Anne); M. Kähönen (Mika); M. Karaleftheri (Maria); Tee Khaw, K. (Kay); S. Keinanen-Kiukaanniemi (Sirkka); L. Kinnunen (Leena); P. Knekt; H. Koistinen (Heikki); I. Kolcic (Ivana); I.K. Kooner (Ishminder K.); S. Koskinen (Seppo); P. Kovacs (Peter); T. Kyriakou (Theodosios); Laitinen, T. (Tomi); C. Langenberg (Claudia); A. Lewin (Alex); P. Lichtner (Peter); C.M. Lindgren (Cecilia); J. Lindström (Jaana); A. Linneberg (Allan); R. Lorbeer (Roberto); M. Lorentzon (Mattias); R.N. Luben (Robert); V. Lyssenko (Valeriya); S. Männistö (Satu); P. Manunta (Paolo); I.M. Leach (Irene Mateo); W.L. McArdle (Wendy); Mcknight, B. (Barbara); K.L. Mohlke (Karen); E. Mihailov (Evelin); L. Milani (Lili); R. Mills (Rebecca); M.E. Montasser (May E.); A.P. Morris (Andrew); G. Müller (Gabriele); Musk, A.W. (Arthur W.); N. Narisu (Narisu); K.K. Ong (Ken K.); B.A. Oostra (Ben); C. Osmond (Clive); A. Palotie (Aarno); J.S. Pankow (James); L. Paternoster (Lavinia); B.W.J.H. Penninx (Brenda); I. Pichler (Irene); M.G. Pilia (Maria Grazia); O. Polasek (Ozren); P.P. Pramstaller (Peter Paul); O.T. Raitakari (Olli T.); T. Rankinen (Tuomo); Rao, D.C.; N.W. Rayner (Nigel William); Ribel-Madsen, R. (Rasmus); Rice, T.K. (Treva K.); Richards, M. (Marcus); P.M. Ridker (Paul); F. Rivadeneira Ramirez (Fernando); Ryan, K.A. (Kathy A.); S. Sanna (Serena); M.A. Sarzynski (Mark A.); S. Scholtens (Salome); R.A. Scott (Robert); S. Sebert (Sylvain); L. Southam (Lorraine); T. Sparsø (Thomas); V. Steinthorsdottir (Valgerdur); K. Stirrups (Kathy); R.P. Stolk (Ronald); K. Strauch (Konstantin); H.M. Stringham (Heather); M. Swertz (Morris); A.J. Swift (Amy); A. Tönjes (Anke); E. Tsafantakis (Emmanouil); P.J. van der Most (Peter); J.V. van Vliet-Ostaptchouk (Jana); L. Vandenput (Liesbeth); Vartiainen, E. (Erkki); C. Venturini (Cristina); N. Verweij (Niek); J. Viikari (Jorma); Vitart, V. (Veronique); M.-C. Vohl (Marie-Claude); J.M. Vonk (Judith); G. Waeber (Gérard); E. Widen (Elisabeth); G.A.H.M. Willemsen (Gonneke); T. Wilsgaard (Tom); T.W. Winkler (Thomas W.); A.F. Wright (Alan); L.M. Yerges-Armstrong (Laura); Zhao, J.H. (Jing Hua); M.C. Zillikens (Carola); D.I. Boomsma (Dorret); C. Bouchard (Claude); J.C. Chambers (John); D.I. Chasman (Daniel); D. Cusi (Daniele); R.T. Gansevoort (Ron); C. Gieger (Christian); T. Hansen (T.); A.A. Hicks (Andrew); Hu, F. (Frank); K. Hveem (Kristian); M.-R. Jarvelin (Marjo-Riitta); E. Kajantie (Eero); J.S. Kooner (Jaspal S.); D. Kuh (Diana); J. Kuusisto (Johanna); M. Laakso (Markku); T.A. Lakka (Timo); T. Lehtimäki (Terho); A. Metspalu (Andres); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); Palmer, L.J. (Lyle J.); O. Pedersen (Oluf); M. Perola (Markus); A. Peters (Annette); B.M. Psaty (Bruce); Puolijoki, H. (Hannu); R. Rauramaa (Rainer); I. Rudan (Igor); V. Salomaa (Veikko); P.E.H. Schwarz (Peter); Shudiner, A.R. (Alan R.); J.H. Smit (Jan); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); J-A. Zwart (John-Anker); M. Stumvoll (Michael); Tremblay, A. (Angelo); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); Uusitupa, M. (Matti); U. Völker (Uwe); P. Vollenweider (Peter); N.J. Wareham (Nick); H. Watkins (Hugh); J.F. Wilson (James); E. Zeggini (Eleftheria); G.R. Abecasis (Gonçalo); M. Boehnke (Michael); I.B. Borecki (Ingrid); P. Deloukas (Panagiotis); C.M. van Duijn (Cornelia); C.S. Fox (Caroline); L. Groop (Leif); I.M. Heid (Iris); Hunter, D.J. (David J.); R.C. Kaplan (Robert); M.I. McCarthy (Mark); K.E. North (Kari); J.R. O´Connell; Schlessinger, D. (David); U. Thorsteinsdottir (Unnur); D.P. Strachan (David); T.M. Frayling (Timothy); J.N. Hirschhorn (Joel); M. Müller-Nurasyid (Martina); R.J.F. Loos (Ruth)

    2016-01-01

    textabstractLarge consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that

  5. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

    DEFF Research Database (Denmark)

    Ried, Janina S; Jeff M, Janina; Chu, Audrey Y

    2016-01-01

    Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculate...

  6. Mapping of quantitative trait loci (QTL) for production, resistance and tolerance traits in Salix. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Roennberg-Waestljung, Ann Christin; Bertholdsson, Nils-Ove; Glynn, Carolyn; Weih, Martin; Aahman, Inger [SLU, Uppsala (Sweden). Dept. of Plant Biology and Forest Genetics

    2004-05-01

    Quantitative trait loci (QTL) for growth traits, water use efficiency and tolerance/resistance against metals and herbivores have been identified. A hybrid F2 population originating from a cross between a Salix dasyclados-clone (SW901290) and a S. viminalis-clone ('Jorunn') was used for the different studies in this project. The growth response was analyzed in a greenhouse experiment with two water treatments, normal and drought. In addition, three field experiments with contrasting soils and climates were established. QTL specific for each treatment or field environment but also QTL stable over the treatments or field environments were detected. Each QTL explained from 8 to 29 % of the phenotypic variation depending on trait, treatment or field environment. Clusters of QTL for different traits were mapped indicating a common genetic base or tightly-linked QTL. Stable QTL identified for dryweight can be useful tools for early selection in Salix. In a separate greenhouse experiment, with a subset of ten genotypes from the F2 population, we show that genotype is more important than irrigation treatment for production of phenolic substances as well as for resistance to herbivory by P vulgatissima.

  7. Identification of quantitative trait loci for wool traits in Iranian Baluchi sheep. Indian Journal of Animal Sciences

    DEFF Research Database (Denmark)

    Dashab, G R; Aslaminejad, A; Nassiri, M R

    2012-01-01

    Regions on 3 ovine chromosomes (OAR1, 5 and 25) were selected to study quantitative trait loci (QTL) segregating for wool traits in Baluchi sheep, an indigenous sheep breed in Iran. Progenies (503) from 13 half-sib families were genotyped for 15 microsatellite markers. The average number of proge...

  8. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

    DEFF Research Database (Denmark)

    Berndt, Sonja I; Gustafsson, Stefan; Mägi, Reedik

    2013-01-01

    Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass ...

  9. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

    NARCIS (Netherlands)

    Berndt, S.I.; Gustafsson, S.; Magi, R.; Ganna, A.; Wheeler, E.; Feitosa, M.F.; Justice, A.E.; Monda, K.L.; Croteau-Chonka, D.C.; Day, F.R.; Esko, T.; Fall, T.; Ferreira, T.; Gentilini, D.; Jackson, A.U.; Luan, J.; Randall, J.C.; Vedantam, S.; Willer, C.J.; Winkler, T.W.; Wood, A.R.; Workalemahu, T.; Hu, Y.J.; Lee, S.; Liang, L.; Lin, D.Y.; Min, J.L.; Neale, B.M.; Thorleifsson, G.; Yang, J.; Albrecht, E.; Amin, N.; Bragg-Gresham, J.L.; Cadby, G.; Heijer, M. den; Eklund, N.; Fischer, K.; Goel, A.; Hottenga, J.J.; Huffman, J.E.; Jarick, I.; Johansson, A; Johnson, T.; Kanoni, S.; Kleber, M.E.; Konig, I.R.; Kristiansson, K.; Kutalik, Z.; Lamina, C.; Lecoeur, C.; Li, G.; Mangino, M.; McArdle, W.L.; Medina-Gomez, C.; Muller-Nurasyid, M.; Ngwa, J.S.; Nolte, I.M.; Paternoster, L.; Pechlivanis, S.; Perola, M.; Peters, M.J.; Preuss, M.; Rose, L.M.; Shi, J.; Shungin, D.; Smith, A.V.; Strawbridge, R.J.; Surakka, I.; Teumer, A.; Trip, M.D.; Tyrer, J.; Vliet-Ostaptchouk, J.V. Van; Vandenput, L.; Waite, L.L.; Zhao, J.H.; Absher, D.; Asselbergs, F.W.; Atalay, M.; Attwood, A.P.; Balmforth, A.J.; Basart, H.; Beilby, J.; Bonnycastle, L.L.; Brambilla, P.; Bruinenberg, M.; Campbell, H.; Chasman, D.I.; Chines, P.S.; Collins, F.S.; Connell, J.M.; Cookson, W.O.; Faire, U. de; Vegt, F. de; Dei, M.; Dimitriou, M.; Edkins, S.; Estrada, K.; Evans, D.M.; Farrall, M.; Ferrario, M.M.; Vermeulen, S.; Kiemeney, L.A.L.M.; et al.,

    2013-01-01

    Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass

  10. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

    NARCIS (Netherlands)

    S.I. Berndt (Sonja); S. Gustafsson (Stefan); R. Mägi (Reedik); A. Ganna (Andrea); E. Wheeler (Eleanor); M.F. Feitosa (Mary Furlan); A.E. Justice (Anne); K.L. Monda (Keri); D.C. Croteau-Chonka (Damien); F.R. Day (Felix); T. Esko (Tõnu); M. Fall (Magnus); T. Ferreira (Teresa); D. Gentilini (Davide); A.U. Jackson (Anne); J. Luan; J.C. Randall (Joshua); S. Vedantam (Sailaja); C.J. Willer (Cristen); T.W. Winkler (Thomas); A.R. Wood (Andrew); T. Workalemahu (Tsegaselassie); Y.-J. Hu (Yi-Juan); S.H. Lee (Sang Hong); L. Liang (Liming); D.Y. Lin (Dan); J. Min (Josine); B.M. Neale (Benjamin); G. Thorleifsson (Gudmar); J. Yang (Jian); E. Albrecht (Eva); N. Amin (Najaf); J.L. Bragg-Gresham (Jennifer L.); G. Cadby (Gemma); M. den Heijer (Martin); N. Eklund (Niina); K. Fischer (Krista); A. Goel (Anuj); J.J. Hottenga (Jouke Jan); J.E. Huffman (Jennifer); I. Jarick (Ivonne); A. Johansson (Åsa); T. Johnson (Toby); S. Kanoni (Stavroula); M.E. Kleber (Marcus); I.R. König (Inke); K. Kristiansson (Kati); Z. Kutalik (Zoltán); C. Lamina (Claudia); C. Lecoeur (Cécile); G. Li (Guo); M. Mangino (Massimo); W.L. McArdle (Wendy); M.C. Medina-Gomez (Carolina); M. Müller-Nurasyid (Martina); J.S. Ngwa; I.M. Nolte (Ilja); L. Paternoster (Lavinia); S. Pechlivanis (Sonali); M. Perola (Markus); M.J. Peters (Marjolein); M. Preuss (Michael); L.M. Rose (Lynda); J. Shi (Jianxin); D. Shungin (Dmitry); G.D. Smith; R.J. Strawbridge (Rona); I. Surakka (Ida); A. Teumer (Alexander); M.D. Trip (Mieke); J.P. Tyrer (Jonathan); J.V. van Vliet-Ostaptchouk (Jana); L. Vandenput (Liesbeth); L. Waite (Lindsay); J.H. Zhao (Jing Hua); D. Absher (Devin); F.W. Asselbergs (Folkert); M. Atalay (Mustafa); A.P. Attwood (Antony); A.J. Balmforth (Anthony); D.C.G. Basart (Dick); J.P. Beilby (John); L.L. Bonnycastle (Lori); P. Brambilla (Paolo); M. Bruinenberg (M.); H. Campbell (Harry); D.I. Chasman (Daniel); P.S. Chines (Peter); F.S. Collins (Francis); J. Connell (John); W. O Cookson (William); U. de Faire (Ulf); F. de Vegt (Femmie); M. Dei (Mariano); M. Dimitriou (Maria); T. Edkins (Ted); K. Estrada Gil (Karol); D.M. Evans (David); M. Farrall (Martin); F. Ferrario (Franco); J. Ferrières (Jean); L. Franke (Lude); F. Frau (Francesca); P.V. Gejman (Pablo); H. Grallert (Harald); H. Grönberg (Henrik); V. Gudnason (Vilmundur); A. Hall (Anne); A.S. Hall (Alistair); A.L. Hartikainen; C. Hayward (Caroline); N.L. Heard-Costa (Nancy); A.C. Heath (Andrew); J. Hebebrand (Johannes); G. Homuth (Georg); F.B. Hu (Frank); S.E. Hunt (Sarah); E. Hyppönen (Elina); C. Iribarren (Carlos); K.B. Jacobs (Kevin); J.-O. Jansson (John-Olov); A. Jula (Antti); M. Kähönen (Mika); S. Kathiresan (Sekar); F. Kee (F.); K-T. Khaw (Kay-Tee); M. Kivimaki (Mika); W. Koenig (Wolfgang); A. Kraja (Aldi); M. Kumari (Meena); K. Kuulasmaa (Kari); J. Kuusisto (Johanna); J. Laitinen (Jaana); T.A. Lakka (Timo); C. Langenberg (Claudia); L.J. Launer (Lenore); L. Lind (Lars); J. Lindstrom (Jaana); J. Liu (Jianjun); A. Liuzzi (Antonio); M.L. Lokki; M. Lorentzon (Mattias); P.A. Madden (Pamela); P.K. Magnusson (Patrik); P. Manunta (Paolo); D. Marek (Diana); W. März (Winfried); I.M. Leach (Irene Mateo); B. McKnight (Barbara); S.E. Medland (Sarah Elizabeth); E. Mihailov (Evelin); L. Milani (Lili); G.W. Montgomery (Grant); V. Mooser (Vincent); T.W. Mühleisen (Thomas); P. Munroe (Patricia); A.W. Musk (Arthur); N. Narisu (Narisu); G. Navis (Gerjan); G. Nicholson (Ggeorge); C. Nohr (Christian); K. Ong (Ken); B.A. Oostra (Ben); C.N.A. Palmer (Colin); A. Palotie (Aarno); J. Peden (John); N. Pedersen; A. Peters (Annette); O. Polasek (Ozren); A. Pouta (Anneli); P.P. Pramstaller (Peter Paul); I. Prokopenko (Inga); C. Pütter (Carolin); A. Radhakrishnan (Aparna); O. Raitakari (Olli); A. Rendon (Augusto); F. Rivadeneira Ramirez (Fernando); I. Rudan (Igor); T. Saaristo (Timo); J.G. Sambrook (Jennifer); A.R. Sanders (Alan); S. Sanna (Serena); J. Saramies (Jouko); S. Schipf (Sabine); S. Schreiber (Stefan); H. Schunkert (Heribert); S.-Y. Shin; S. Signorini (Stefano); J. Sinisalo (Juha); B. Skrobek (Boris); N. Soranzo (Nicole); A. Stancáková (Alena); K. Stark (Klaus); J. Stephens (Jonathan); K. Stirrups (Kathy); R.P. Stolk (Ronald); M. Stumvoll (Michael); A.J. Swift (Amy); E.V. Theodoraki (Eirini); B. Thorand (Barbara); D.-A. Tregouet (David-Alexandre); E. Tremoli (Elena); M.M. van der Klauw (Melanie); J.B.J. van Meurs (Joyce); S.H.H.M. Vermeulen (Sita); J. Viikari (Jorma); J. Virtamo (Jarmo); V. Vitart (Veronique); G. Waeber (Gérard); Z. Wang (Zhaoming); E. Widen (Elisabeth); S.H. Wild (Sarah); G.A.H.M. Willemsen (Gonneke); B. Winkelmann; J.C.M. Witteman (Jacqueline); B.H.R. Wolffenbuttel (Bruce); A. Wong (Andrew); A.F. Wright (Alan); M.C. Zillikens (Carola); P. Amouyel (Philippe); B.O. Boehm (Bernhard); E.A. Boerwinkle (Eric); D.I. Boomsma (Dorret); M. Caulfield (Mark); S.J. Chanock (Stephen); L.A. Cupples (Adrienne); D. Cusi (Daniele); G.V. Dedoussis (George); J. Erdmann (Jeanette); J.G. Eriksson (Johan); P.W. Franks (Paul); P. Froguel (Philippe); C. Gieger (Christian); U. Gyllensten (Ulf); A. Hamsten (Anders); T.B. Harris (Tamara); C. Hengstenberg (Christian); A.A. Hicks (Andrew); A. Hingorani (Aroon); A. Hinney (Anke); A. Hofman (Albert); G.K. Hovingh (Kees); K. Hveem (Kristian); T. Illig (Thomas); M.-R. Jarvelin (Marjo-Riitta); K.-H. Jöckel (Karl-Heinz); S. Keinanen-Kiukaanniemi (Sirkka); L.A.L.M. Kiemeney (Bart); D. Kuh (Diana); M. Laakso (Markku); T. Lehtimäki (Terho); D.F. Levinson (Douglas); N.G. Martin (Nicholas); A. Metspalu (Andres); A.D. Morris (Andrew); M.S. Nieminen (Markku); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); W.H. Ouwehand (Willem); C. Palmer (Cameron); B.W.J.H. Penninx (Brenda); C. Power (Christopher); M.A. Province (Mike); B.M. Psaty (Bruce); L. Qi (Lu); R. Rauramaa (Rainer); P.M. Ridker (Paul); S. Ripatti (Samuli); V. Salomaa (Veikko); N.J. Samani (Nilesh); H. Snieder (Harold); H.G. Sorensen; T.D. Spector (Timothy); J-A. Zwart (John-Anker); A. Tönjes (Anke); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); M. Uusitupa (Matti); P. van der Harst (Pim); P. Vollenweider (Peter); H. Wallaschofski (Henri); N.J. Wareham (Nick); H. Watkins (Hugh); H.E. Wichmann (Heinz Erich); J.F. Wilson (James F); G.R. Abecasis (Gonçalo); T.L. Assimes (Themistocles); I. Barroso (Inês); M. Boehnke (Michael); I.B. Borecki (Ingrid); P. Deloukas (Panagiotis); C. Fox (Craig); T.M. Frayling (Timothy); L. Groop (Leif); T. Haritunian (Talin); I.M. Heid (Iris); D. Hunter (David); R.C. Kaplan (Robert); F. Karpe (Fredrik); M.F. Moffatt (Miriam); K.L. Mohlke (Karen); J.R. O´Connell; Y. Pawitan (Yudi); E.E. Schadt (Eric); D. Schlessinger (David); V. Steinthorsdottir (Valgerdur); D.P. Strachan (David); U. Thorsteinsdottir (Unnur); C.M. van Duijn (Cornelia); P.M. Visscher (Peter); A.M. Di Blasio (Anna Maria); J.N. Hirschhorn (Joel); C.M. Lindgren (Cecilia); A.D. Morris (Andrew); D. Meyre (David); A. Scherag (Andre); M.I. McCarthy (Mark); E.K. Speliotes (Elizabeth); K.E. North (Kari); R.J.F. Loos (Ruth); E. Ingelsson (Erik)

    2013-01-01

    textabstractApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of

  11. Mapping of quantitative trait loci for oil content in cottonseed kernel

    Indian Academy of Sciences (India)

    Cottonseed oil content is a quantitative trait controlled by genes in the tetraploid embryo and tetraploid maternal plant genomes, and the knowledge of quantitative trait loci (QTLs) and the genetic effects related to oil content in both genomes could facilitate the improvement in its quality and quantity. However, till date, QTL ...

  12. Mapping of quantitative trait loci for oil content in cottonseed kernel

    Indian Academy of Sciences (India)

    embryo and tetraploid maternal plant genomes, and the knowledge of quantitative trait loci (QTLs) and the genetic effects related to oil content in both genomes could facilitate the improvement in its quality and quantity. However, till date, QTL mapping and genetic analysis related to this trait in cotton have only been ...

  13. Mapping the quantitative trait loci (QTL) controlling seed morphology in sunflower (Helianthus annuus L.)

    Science.gov (United States)

    This paper reports the results of analyzing the quantitative trait loci (QTL) underlying sunflower seed morphological traits in a segregating population derived from an oilseed by confection cross. A linkage map containing 165 target region amplification polymorphism (TRAP) and 44 simple sequence re...

  14. Quantitative trait loci identification and meta-analysis for rice panicle-related traits.

    Science.gov (United States)

    Wu, Yahui; Huang, Ming; Tao, Xingxing; Guo, Tao; Chen, Zhiqiang; Xiao, Wuming

    2016-10-01

    Rice yield is a complex trait controlled by quantitative trait loci (QTLs). In the past three decades, thousands of QTLs for rice yield traits have been detected, but only a very small percentage has been cloned to date, as identifying the QTL genes requires a substantial investment of time and money. Meta-analysis provides a simple, reliable, and economical method for integrating information from multiple QTL studies across various environmental and genetic backgrounds, detecting consistent QTLs powerfully and estimating their genetic positions precisely. In this study, we aimed to locate consistent QTL regions associated with rice panicle traits by applying a genome-wide QTL meta-analysis approach. We first conducted a QTL analysis of 5 rice panicle traits using 172 plants in 2011 and 138 plants in 2012 from an F2 population derived from a cross between Nipponbare and H71D rice cultivators. A total of 54 QTLs were detected, and these were combined with 1085 QTLs collected from 82 previous studies to perform a meta-analysis using BioMercator v4.2. The integration of 82 maps resulted in a consensus map with 6970 markers and a total map length of 1823.1 centimorgan (cM), on which 837 QTLs were projected. These QTLs were then integrated into 87 meta-quantitative trait loci (MQTLs) by meta-analysis, and the 95 % confidence intervals (CI) of them were smaller than the mean value of the original QTLs. Also, 30 MQTLs covered 47 of the 54 QTLs detected from the cross between Nipponbare and H71D in this study. Among them, the two major and stable QTLs, spp10.1 and sd10.1, were found to be included in MQTL10.4. The three other major QTLs, pl3.1, sb2.1, and sb10.1, were included in MQTL3.3, MQTL2.2, and MQTL10.3, respectively. A total of 21 of the 87 MQTLs' phenotypic variation were >20 %. In total, 24 candidate genes were found in 15 MQTLs that spanned physical intervals <0.2 Mb, including genes that have been cloned previously, e.g., EP3, LP, MIP1, HTD1, DSH1, and Os

  15. Identification of genetic loci shared between schizophrenia and the Big Five personality traits.

    Science.gov (United States)

    Smeland, Olav B; Wang, Yunpeng; Lo, Min-Tzu; Li, Wen; Frei, Oleksandr; Witoelar, Aree; Tesli, Martin; Hinds, David A; Tung, Joyce Y; Djurovic, Srdjan; Chen, Chi-Hua; Dale, Anders M; Andreassen, Ole A

    2017-05-22

    Schizophrenia is associated with differences in personality traits, and recent studies suggest that personality traits and schizophrenia share a genetic basis. Here we aimed to identify specific genetic loci shared between schizophrenia and the Big Five personality traits using a Bayesian statistical framework. Using summary statistics from genome-wide association studies (GWAS) on personality traits in the 23andMe cohort (n = 59,225) and schizophrenia in the Psychiatric Genomics Consortium cohort (n = 82,315), we evaluated overlap in common genetic variants. The Big Five personality traits neuroticism, extraversion, openness, agreeableness and conscientiousness were measured using a web implementation of the Big Five Inventory. Applying the conditional false discovery rate approach, we increased discovery of genetic loci and identified two loci shared between neuroticism and schizophrenia and six loci shared between openness and schizophrenia. The study provides new insights into the relationship between personality traits and schizophrenia by highlighting genetic loci involved in their common genetic etiology.

  16. Genome-wide haplotype analysis of cis expression quantitative trait loci in monocytes.

    Directory of Open Access Journals (Sweden)

    Sophie Garnier

    Full Text Available In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ~2,1 × 10(9 haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >10(4-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2 × 10(-4 (~0.05/412, 193 haplotypic signals replicated. 1000 G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000 G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

  17. Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

    Directory of Open Access Journals (Sweden)

    Asif Iqbal

    2015-11-01

    Full Text Available Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS, eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24, Commission Internationale de l’Eclairage lightness in meat color (CIE L, redness in meat color (CIE a, yellowness in meat color (CIE b, filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA. A SAS general linear model procedure (SAS version 9.2 was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP under a linear regression model (PLINK version 1.07. The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05 SNPs or quantitative trait loci (QTL were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.

  18. Quantitative trait loci controlling cyanogenic glucoside and dry matter content in cassava (Manihot esculenta Crantz) roots.

    Science.gov (United States)

    Balyejusa Kizito, Elizabeth; Rönnberg-Wästljung, Ann-Christin; Egwang, Thomas; Gullberg, Urban; Fregene, Martin; Westerbergh, Anna

    2007-09-01

    Cassava (Manihot esculenta Crantz) is a starchy root crop grown in the tropics mainly by small-scale farmers even though agro-industrial processing is rapidly increasing. For this processing market improved varieties with high dry matter root content (DMC) is required. Potentially toxic cyanogenic glucosides are synthesized in the leaves and translocated to the roots. Selection for varieties with low cyanogenic glucoside potential (CNP) and high DMC is among the principal objectives in cassava breeding programs. However, these traits are highly influenced by the environmental conditions and the genetic control of these traits is not well understood. An S(1) population derived from a cross between two bred cassava varieties (MCOL 1684 and Rayong 1) that differ in CNP and DMC was used to study the heritability and genetic basis of these traits. A broad-sense heritability of 0.43 and 0.42 was found for CNP and DMC, respectively. The moderate heritabilities for DMC and CNP indicate that the phenotypic variation of these traits is explained by a genetic component. We found two quantitative trait loci (QTL) on two different linkage groups controlling CNP and six QTL on four different linkage groups controlling DMC. One QTL for CNP and one QTL for DMC mapped near each other, suggesting pleiotrophy and/or linkage of QTL. The two QTL for CNP showed additive effects while the six QTL for DMC showed additive effect, dominance or overdominance. This study is a first step towards developing molecular marker tools for efficient breeding of CNP and DMC in cassava.

  19. Identification of quantitative trait loci associated with bone traits and body weight in an F2 resource population of chickens*

    Directory of Open Access Journals (Sweden)

    Schreiweis Melissa A

    2005-11-01

    Full Text Available Abstract Bone fractures at the end of lay are a significant problem in egg-laying strains of hens. The objective of the current study was to identify quantitative trait loci (QTL associated with bone mineralization and strength in a chicken resource population. Layer (White Leghorn hens and broiler (Cobb-Cobb roosters lines were crossed to generate an F2 population of 508 hens over seven hatches, and 26 traits related to bone integrity, including bone mineral density (BMD and content (BMC, were measured. Genotypes of 120 microsatellite markers on 28 autosomal groups were determined, and interval mapping was conducted to identify QTL regions. Twenty-three tests representing three chromosomal regions (chromosomes 4, 10 and 27 contained significant QTL that surpassed the 5% genome-wise threshold, and 47 tests representing 15 chromosomes identified suggestive QTL that surpassed the 5% chromosome-wise threshold. Although no significant QTL influencing BMD and BMC were detected after adjusting for variation in body weight and egg production, multiple suggestive QTL were found. These results support previous experiments demonstrating an important genetic regulation of bone strength in chickens, but suggest the regulation may be due to the effects of multiple genes that each account for relatively small amounts of variation in bone strength.

  20. A Genome Scan for Quantitative Trait Loci Affecting Average Daily ...

    Indian Academy of Sciences (India)

    reviewer

    reproductive system, cell proliferation and differentiation, protein folding and levels of gene transcription thereupon affect muscle growth and fat deposit in sheep. In different periods of ADG and KR traits, some of significant markers were same and some of them were different. The records related to ADG and KR traits are ...

  1. Confirmation of quantitative trait loci affecting fatness in chickens

    NARCIS (Netherlands)

    Jennen, D.G.J.; Vereijken, A.L.J.; Bovenhuis, H.; Crooijmans, R.P.M.A.; Poel, van der J.J.; Groenen, M.A.M.

    2005-01-01

    In this report we describe the analysis of an advanced intercross line (AIL) to confirm the quantitative trait locus (QTL) regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each

  2. Characterization of variation and quantitative trait loci related to ...

    Indian Academy of Sciences (India)

    Towards the end, 197 recombinant inbred lines from a cross were grown over two seasons to characterize variability for seven biomass and 23 terpenoid indole alkaloids content-traits and yield-traits. The recombinant inbred lines were genotyped for 178 DNA markers which formed a framework genetic map of eight linkage ...

  3. Bayesian analysis of interacting quantitative trait loci (QTL) for yield ...

    African Journals Online (AJOL)

    Jane

    2011-10-17

    Oct 17, 2011 ... genetic map, spanning the tomato genome of 808.4 cM long was constructed with 112 SSR markers distributing on 16 linkage ... governing simultaneously first flower node and number of flowers per truss. Key words: Tomato, SSR ... map and location of QTL for yield traits. Traits evaluation. The node of first ...

  4. Quantitative trait loci mapping of calving and conformation traits on Bos taurus autosome 18 in the German Holstein population.

    Science.gov (United States)

    Brand, B; Baes, C; Mayer, M; Reinsch, N; Seidenspinner, T; Thaller, G; Kühn, Ch

    2010-03-01

    Linkage, linkage disequilibrium, and combined linkage and linkage disequilibrium analyses were performed to map quantitative trait loci (QTL) affecting calving and conformation traits on Bos taurus autosome 18 (BTA18) in the German Holstein population. Six paternal half-sib families consisting of a total of 1,054 animals were genotyped on 28 genetic markers in the telomeric region on BTA18 spanning approximately 30 Mb. Calving traits, body type traits, and udder type traits were investigated. Using univariately estimated breeding values, maternal and direct effects on calving ease and stillbirth were analyzed separately for first- and further-parity calvings. The QTL initially identified by separate linkage and linkage disequilibrium analyses could be confirmed by a combined linkage and linkage disequilibrium analysis for udder composite index, udder depth, fore udder attachment, front teat placement, body depth, rump angle, and direct effects on calving ease and stillbirth. Concurrence of QTL peaks and a similar shape of restricted log-likelihood ratio profiles were observed between udder type traits and for body depth and calving traits, respectively. Association analyses were performed for markers flanking the most likely QTL positions by applying a mixed model including a fixed allele effect of the maternally inherited allele and a random polygenic effect. Results indicated that microsatellite marker DIK4234 (located at 53.3 Mb) is associated with maternal effects on stillbirth, direct effects on calving ease, and body depth. A comparison of effects for maternally inherited DIK4234 alleles indicated a favorable, positive correlation of maternal and direct effects on calving. Additionally, the association of maternally inherited DIK4234 marker alleles with body depth implied that conformation traits might provide the functional background of the QTL for calving traits. For udder type traits, the strong coincidence of QTL peaks and the position of the QTL in a

  5. Identification of major quantitative trait loci underlying floral pollination syndrome divergence in Penstemon.

    Science.gov (United States)

    Wessinger, Carolyn A; Hileman, Lena C; Rausher, Mark D

    2014-08-05

    Distinct floral pollination syndromes have emerged multiple times during the diversification of flowering plants. For example, in western North America, a hummingbird pollination syndrome has evolved more than 100 times, generally from within insect-pollinated lineages. The hummingbird syndrome is characterized by a suite of floral traits that attracts and facilitates pollen movement by hummingbirds, while at the same time discourages bee visitation. These floral traits generally include large nectar volume, red flower colour, elongated and narrow corolla tubes and reproductive organs that are exerted from the corolla. A handful of studies have examined the genetic architecture of hummingbird pollination syndrome evolution. These studies find that mutations of relatively large effect often explain increased nectar volume and transition to red flower colour. In addition, they suggest that adaptive suites of floral traits may often exhibit a high degree of genetic linkage, which could facilitate their fixation during pollination syndrome evolution. Here, we explore these emerging generalities by investigating the genetic basis of floral pollination syndrome divergence between two related Penstemon species with different pollination syndromes--bee-pollinated P. neomexicanus and closely related hummingbird-pollinated P. barbatus. In an F2 mapping population derived from a cross between these two species, we characterized the effect size of genetic loci underlying floral trait divergence associated with the transition to bird pollination, as well as correlation structure of floral trait variation. We find the effect sizes of quantitative trait loci for adaptive floral traits are in line with patterns observed in previous studies, and find strong evidence that suites of floral traits are genetically linked. This linkage may be due to genetic proximity or pleiotropic effects of single causative loci. Interestingly, our data suggest that the evolution of floral traits

  6. Comparative mapping reveals quantitative trait loci that affect spawning time in coho salmon (Oncorhynchus kisutch

    Directory of Open Access Journals (Sweden)

    Cristian Araneda

    2012-01-01

    Full Text Available Spawning time in salmonids is a sex-limited quantitative trait that can be modified by selection. In rainbow trout (Oncorhynchus mykiss, various quantitative trait loci (QTL that affect the expression of this trait have been discovered. In this study, we describe four microsatellite loci associated with two possible spawning time QTL regions in coho salmon (Oncorhynchus kisutch. The four loci were identified in females from two populations (early and late spawners produced by divergent selection from the same base population. Three of the loci (OmyFGT34TUF, One2ASC and One19ASC that were strongly associated with spawning time in coho salmon (p < 0.0002 were previously associated with QTL for the same trait in rainbow trout; a fourth loci (Oki10 with a suggestive association (p = 0.00035 mapped 10 cM from locus OmyFGT34TUF in rainbow trout. The changes in allelic frequency observed after three generations of selection were greater than expected because of genetic drift. This work shows that comparing information from closely-related species is a valid strategy for identifying QTLs for marker-assisted selection in species whose genomes are poorly characterized or lack a saturated genetic map.

  7. Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk

    DEFF Research Database (Denmark)

    Buitenhuis, Albert Johannes; Sundekilde, Ulrik; Poulsen, Nina Aagaard

    2013-01-01

    Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. F...... for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25...

  8. Bayesian analysis of interacting quantitative trait loci (QTL) for yield ...

    African Journals Online (AJOL)

    7×Lycopersicon pimpinellifolium LA2184 was used for genome-wide linkage analysis for yield traits in tomato. The genetic map, spanning the tomato genome of 808.4 cM long was constructed with 112 SSR markers distributing on 16 linkage ...

  9. Mapping quantitative trait loci associated with yield and yield ...

    Indian Academy of Sciences (India)

    identify reproductive stage specific QTLs for salinity tolerance. Genetic linkage map was constructed using 123 microsatellite markers on 232 F2 progenies. Totally 35 QTLs for 11 traits under salinity stress were detected with LOD > 3, out of which. 28 QTLs that explained from 5.9 to 30.0% phenotypic variation were found to ...

  10. Quantitative trait loci (QTL) analysis of flag leaf senescence in wheat ...

    African Journals Online (AJOL)

    The objective of this study was to detect quantitative trait loci (QTL) associated with drought tolerance in wheat genotypes by simple sequence repeat (SSR) markers and to provide valuable information for marker assisted selection. SSR markers linked to flag leaf senescence (FLS) was identified in two DNA pools, which ...

  11. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci

    NARCIS (Netherlands)

    Jansen, R.C.; Ooijen, J.W. van; Stam, P.; Lister, C.; Dean, C.

    1995-01-01

    The interval mapping method is widely used for the genetic mapping of quantitative trait loci (QTLs), though true resolution of quantitative variation into QTLs is hampered with this method. Separation of QTLs is troublesome, because single-QTL is models are fitted. Further, genotype-by-environment

  12. Comparison of quantitative trait loci for rice yield, panicle length and ...

    Indian Academy of Sciences (India)

    2011-08-19

    Aug 19, 2011 ... [Liu T., Li L., Zhang Y., Xu C., Li X. and Xing Y. 2011 Comparison of quantitative trait loci for rice yield, panicle length and spikelet density across three connected populations. J. Genet. 90, 377–382]. Introduction. Enhancing crop yield is one of the top priorities in crop breeding programmes. Among various ...

  13. Quantitative trait loci for resistance to maize streak virus disease in ...

    African Journals Online (AJOL)

    Maize streak virus disease is an important disease of maize in Kenya. In this study, we mapped and characterized quantitative trait loci affecting resistance to maize streak virus in maize populations of S4 families from the cross of one resistant MAL13 and one susceptible MAL9 recombinant inbred lines. Resistance was ...

  14. Meta-Analysis of Results from Quantitative Trait Loci Mapping Studies on Pig Chromosome 4

    NARCIS (Netherlands)

    Moraes Silva, De K.M.; Bastiaansen, J.W.M.; Knol, E.F.; Merks, J.W.M.; Lopes, P.S.; Guimaraes, R.M.; Arendonk, van J.A.M.

    2011-01-01

    Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this

  15. CBCL Pediatric Bipolar Disorder Profile and ADHD: Comorbidity and Quantitative Trait Loci Analysis

    Science.gov (United States)

    McGough, James J.; Loo, Sandra K.; McCracken, James T.; Dang, Jeffery; Clark, Shaunna; Nelson, Stanley F.; Smalley, Susan L.

    2008-01-01

    The pediatric bipolar disorder profile of the Child Behavior checklist is used to differentiate patterns of comorbidity and to search for quantitative trait loci in multiple affected ADHD sibling pairs. The CBCL-PBD profiling identified 8 percent of individuals with severe psychopathology and increased rates of oppositional defiant, conduct and…

  16. Quantitative trait loci associated with the tocochromanol (vitamin E) pathway in barley

    Science.gov (United States)

    In this study, the Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- alpha-, beta-, delta-, gamma-tocopherol and tocotrienol- were assayed. We found...

  17. Evaluation and Quantitative trait loci mapping of resistance to powdery mildew in lettuce

    Science.gov (United States)

    Lettuce (Lactuca sativa L.) is the major leafy vegetable that is susceptible to powdery mildew disease under greenhouse and field conditions. We mapped quantitative trait loci (QTLs) for resistance to powdery mildew under greenhouse conditions in an interspecific population derived from a cross betw...

  18. Quantitative trait loci for floral morphology in Arabidopsis thaliana.

    OpenAIRE

    Juenger, T; Purugganan, M; Mackay, T F

    2000-01-01

    A central question in biology is how genes control the expression of quantitative variation. We used statistical methods to estimate genetic variation in eight Arabidopsis thaliana floral characters (fresh flower mass, petal length, petal width, sepal length, sepal width, long stamen length, short stamen length, and pistil length) in a cosmopolitan sample of 15 ecotypes. In addition, we used genome-wide quantitative trait locus (QTL) mapping to evaluate the genetic basis of variation in these...

  19. Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11

    DEFF Research Database (Denmark)

    Schulman, N F; Sahana, G; Iso-Touru, T

    2009-01-01

    Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red......, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis...

  20. H2DB: a heritability database across multiple species by annotating trait-associated genomic loci.

    Science.gov (United States)

    Kaminuma, Eli; Fujisawa, Takatomo; Tanizawa, Yasuhiro; Sakamoto, Naoko; Kurata, Nori; Shimizu, Tokurou; Nakamura, Yasukazu

    2013-01-01

    H2DB (http://tga.nig.ac.jp/h2db/), an annotation database of genetic heritability estimates for humans and other species, has been developed as a knowledge database to connect trait-associated genomic loci. Heritability estimates have been investigated for individual species, particularly in human twin studies and plant/animal breeding studies. However, there appears to be no comprehensive heritability database for both humans and other species. Here, we introduce an annotation database for genetic heritabilities of various species that was annotated by manually curating online public resources in PUBMED abstracts and journal contents. The proposed heritability database contains attribute information for trait descriptions, experimental conditions, trait-associated genomic loci and broad- and narrow-sense heritability specifications. Annotated trait-associated genomic loci, for which most are single-nucleotide polymorphisms derived from genome-wide association studies, may be valuable resources for experimental scientists. In addition, we assigned phenotype ontologies to the annotated traits for the purposes of discussing heritability distributions based on phenotypic classifications.

  1. Genetic variation at loci controlling quality traits in spring wheat

    International Nuclear Information System (INIS)

    Ali, N.; Iqbal, M.; Asif, M.

    2013-01-01

    Selection for quality traits in bread wheat (Triticum aestivum L.) during early breeding generations requires quick analytical methods that need small grain samples. Marker assisted selection can be useful for the improvement of quality traits in wheat. The present study was conducted to screen 117 Pakistani adapted spring wheat varieties with DNA markers linked with genes controlling composition of low and high molecular weight glutenin subunits (LMW-GS and HMW-GS, respectively), starch viscosity, Polyphenol oxidase (PPO) activity and grain hardness. DNA fragments associated with the presence/absence of quality related genes were amplified using Polymerase chain reaction (PCR) and detected using agarose gel electrophoresis. Positive allele of beta-secalin, which indicates presence of 1B.1R translocation, was found in 77 (66%) varieties. The marker PPO05 was found in 30 (26%) varieties, indicating lower PPO activity. Grain hardness controlled by Pinb-D1b allele was present in 49 (42%) varieties. Allele Wx-B1b which confers superior noodle quality was found in 48 (41%) varieties. HMW-GS encoded by Glu-D1d allele that exerts a positive effect on dough strength was present in 115 (98%) varieties. LMW-GS alleles Glu-A3d and Glu-B3 were observed in 21 (18%) and 76 (65%) varieties, respectively. Results of the present study may help wheat breeders in selecting parents for improving desirable quality attributes of future wheat varieties. The varieties, identified having desirable quality genes, in this study can be used in the wheat breeding programs aiming to improve quality traits. Early generation marker assisted selection can help to efficiently utilize resources of a breeding program. (author)

  2. Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry (Fragaria × ananassa).

    Science.gov (United States)

    Zorrilla-Fontanesi, Yasmín; Cabeza, Amalia; Domínguez, Pedro; Medina, Juan Jesús; Valpuesta, Victoriano; Denoyes-Rothan, Beatrice; Sánchez-Sevilla, José F; Amaya, Iraida

    2011-09-01

    Breeding for fruit quality traits in strawberry (Fragaria × ananassa, 2n = 8x = 56) is complex due to the polygenic nature of these traits and the octoploid constitution of this species. In order to improve the efficiency of genotype selection, the identification of quantitative trait loci (QTL) and associated molecular markers will constitute a valuable tool for breeding programs. However, the implementation of these markers in breeding programs depends upon the complexity and stability of QTLs across different environments. In this work, the genetic control of 17 agronomical and fruit quality traits was investigated in strawberry using a F(1) population derived from an intraspecific cross between two contrasting selection lines, '232' and '1392'. QTL analyses were performed over three successive years based on the separate parental linkage maps and a pseudo-testcross strategy. The integrated strawberry genetic map consists of 338 molecular markers covering 37 linkage groups, thus exceeding the 28 chromosomes. 33 QTLs were identified for 14 of the 17 studied traits and approximately 37% of them were stable over time. For each trait, 1-5 QTLs were identified with individual effects ranging between 9.2 and 30.5% of the phenotypic variation, indicating that all analysed traits are complex and quantitatively inherited. Many QTLs controlling correlated traits were co-located in homoeology group V, indicating linkage or pleiotropic effects of loci. Candidate genes for several QTLs controlling yield, anthocyanins, firmness and L-ascorbic acid are proposed based on both their co-localization and predicted function. We also report conserved QTLs among strawberry and other Rosaceae based on their syntenic location.

  3. Confirmation of quantitative trait loci affecting fatness in chickens

    Directory of Open Access Journals (Sweden)

    Poel Jan

    2005-03-01

    Full Text Available Abstract In this report we describe the analysis of an advanced intercross line (AIL to confirm the quantitative trait locus (QTL regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each generation from generation 2 (G2 onwards until generation 9 (G9 was reached. QTL for abdominal fat weight (AFW and/or percentage abdominal fat (AF% on chromosomes 1, 3 and 27 were confirmed in the G9 population. In addition, evidence for QTL for body weight at the age of 5 (BW5 and 7 (BW7 weeks and for the percentage of intramuscular fat (IF% were found on chromosomes 1, 3, 15, and 27. Significant evidence for QTL was detected on chromosome 1 for BW5 and BW7. Suggestive evidence was found on chromosome 1 for AFW, AF% and IF%, on chromosome 15 for BW5, and on chromosome 27 for AF% and IF%. Furthermore, evidence on the chromosome-wise level was found on chromosome 3 for AFW, AF%, and BW7 and on chromosome 27 for BW5. For chromosomes 4 and 18, test statistics did not exceed the significance threshold.

  4. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

    Science.gov (United States)

    Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F; Graff, Misa; Fisher, Virginia A; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S; Ahluwalia, Tarunveer S; Chu, Audrey Y; Heard-Costa, Nancy L; Lim, Elise; Perez, Jeremiah; Eicher, John D; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E; Jackson, Anne U; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P S; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A; Stančáková, Alena; Strawbridge, Rona J; Stringham, Heather M; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vedantam, Sailaja L; Verweij, Niek; Vink, Jacqueline M; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E; Zubair, Niha; Abecasis, Gonçalo R; Adair, Linda S; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J L; Bartz, Traci M; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M; Buyske, Steve; Campbell, Harry; Chambers, John C; Collins, Francis S; Curran, Joanne E; de Borst, Gert J; de Craen, Anton J M; de Geus, Eco J C; Dedoussis, George; Delgado, Graciela E; den Ruijter, Hester M; Eiriksdottir, Gudny; Eriksson, Anna L; Esko, Tõnu; Faul, Jessica D; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas D; Heath, Andrew C; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A; Jørgensen, Marit E; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Leander, Karin; Lee, Nanette R; Lind, Lars; Lindgren, Cecilia M; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A F; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G; McKenzie, Colin A; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W; Musk, Aw Bill; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Peyser, Patricia A; Pisinger, Charlotta; Porteous, David J; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Rice, Treva; Ridker, Paul M; Rose, Lynda M; Bien, Stephanie A; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A; Sennblad, Bengt; Siemelink, Marten A; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A; Stott, David J; Swertz, Morris A; Swift, Amy J; Taylor, Kent D; Tayo, Bamidele O; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R G J; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A; Boomsma, Dorret I; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I; Chen, Yii-DerIda; Chines, Peter S; Cooper, Richard S; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jörgen; Gudnason, Vilmundur; Haiman, Christopher A; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D; Wouter Jukema, J; Kardia, Sharon L R; Kivimaki, Mika; Kooner, Jaspal S; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I; Metspalu, Andres; Morris, Andrew P; Ohlsson, Claes; Palmer, Lyle J; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Smith, Blair H; Sørensen, Thorkild I A; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J; Weir, David R; Whitfield, John B; Wilson, James F; Tyrrell, Jessica; Frayling, Timothy M; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S; Hirschhorn, Joel N; Hunter, David J; Spector, Tim D; Strachan, David P; van Duijn, Cornelia M; Heid, Iris M; Mohlke, Karen L; Marchini, Jonathan; Loos, Ruth J F; Kilpeläinen, Tuomas O; Liu, Ching-Ti; Borecki, Ingrid B; North, Kari E; Cupples, L Adrienne

    2017-04-26

    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

  5. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

    Science.gov (United States)

    Justice, Anne E.; Winkler, Thomas W.; Feitosa, Mary F.; Graff, Misa; Fisher, Virginia A.; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S.; Ahluwalia, Tarunveer S.; Chu, Audrey Y.; Heard-Costa, Nancy L.; Lim, Elise; Perez, Jeremiah; Eicher, John D.; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F.; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E.; Jackson, Anne U.; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E.; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P. S.; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A.; Stančáková, Alena; Strawbridge, Rona J.; Stringham, Heather M.; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W.; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vedantam, Sailaja L.; Verweij, Niek; Vink, Jacqueline M.; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E.; Zubair, Niha; Abecasis, Gonçalo R.; Adair, Linda S.; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J. L.; Bartz, Traci M.; Beilby, John; Bergman, Richard N.; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L.; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M.; Buyske, Steve; Campbell, Harry; Chambers, John C.; Collins, Francis S.; Curran, Joanne E.; de Borst, Gert J.; de Craen, Anton J. M.; de Geus, Eco J. C.; Dedoussis, George; Delgado, Graciela E.; den Ruijter, Hester M.; Eiriksdottir, Gudny; Eriksson, Anna L.; Esko, Tõnu; Faul, Jessica D.; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B.; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B.; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas D.; Heath, Andrew C.; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J.; Hollensted, Mette; Holmen, Oddgeir L.; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L.; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A.; Jørgensen, Marit E.; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A.; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K.; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Leander, Karin; Lee, Nanette R.; Lind, Lars; Lindgren, Cecilia M.; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A. F.; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G.; McKenzie, Colin A.; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W.; Musk, AW (Bill); Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M.; Oldehinkel, Albertine J.; Olden, Matthias; Ong, Ken K.; Padmanabhan, Sandosh; Peyser, Patricia A.; Pisinger, Charlotta; Porteous, David J.; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rasmussen-Torvik, Laura J.; Rawal, Rajesh; Rice, Treva; Ridker, Paul M.; Rose, Lynda M.; Bien, Stephanie A.; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A.; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A.; Sennblad, Bengt; Siemelink, Marten A.; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A.; Stott, David J.; Swertz, Morris A.; Swift, Amy J.; Taylor, Kent D.; Tayo, Bamidele O.; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M.; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R. G. J.; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H. R.; Wong, Andrew; Wright, Alan F.; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A.; Boomsma, Dorret I.; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I.; Chen, Yii-DerIda; Chines, Peter S.; Cooper, Richard S.; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W.; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans- Jörgen; Gudnason, Vilmundur; Haiman, Christopher A.; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D.; Wouter Jukema, J; Kardia, Sharon L. R.; Kivimaki, Mika; Kooner, Jaspal S.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I.; Metspalu, Andres; Morris, Andrew P.; Ohlsson, Claes; Palmer, Lyle J.; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Smith, Blair H.; Sørensen, Thorkild I. A.; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J.; Weir, David R.; Whitfield, John B.; Wilson, James F.; Tyrrell, Jessica; Frayling, Timothy M.; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S.; Hirschhorn, Joel N.; Hunter, David J.; Spector, Tim D.; Strachan, David P.; van Duijn, Cornelia M.; Heid, Iris M.; Mohlke, Karen L.; Marchini, Jonathan; Loos, Ruth J. F.; Kilpeläinen, Tuomas O.; Liu, Ching-Ti; Borecki, Ingrid B.; North, Kari E.; Cupples, L Adrienne

    2017-01-01

    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution. PMID:28443625

  6. Validation and dissection of quantitative trait loci for leaf traits in ...

    Indian Academy of Sciences (India)

    Keywords. flag leaf length; yield traits; quantitative trait locus; residual heterozygous line; rice (Oryza sativa L.). ..... Effects of the QTLs located in interval RM4923-RM402 on the number of spikelets per panicle. (NSP), number of grains per panicle (NGP) and grain weight per panicle (GWP). Genotypic mean. NIL set. Trait. Z.

  7. Mapping quantitative trait loci (QTL in sheep. IV. Analysis of lactation persistency and extended lactation traits in sheep

    Directory of Open Access Journals (Sweden)

    Lam Mary K

    2011-06-01

    Full Text Available Abstract Background In sheep dairy production, total lactation performance, and length of lactation of lactation are of economic significance. A more persistent lactation has been associated with improved udder health. An extended lactation is defined by a longer period of milkability. This study is the first investigation to examine the presence of quantitative trait loci (QTL for extended lactation and lactation persistency in sheep. Methods An (Awassi × Merino × Merino single-sire backcross family with 172 ewes was used to map QTL for lactation persistency and extended lactation traits on a framework map of 189 loci across all autosomes. The Wood model was fitted to data from multiple lactations to estimate parameters of ovine lactation curves, and these estimates were used to derive measures of lactation persistency and extended lactation traits of milk, protein, fat, lactose, useful yield, and somatic cell score. These derived traits were subjected to QTL analyses using maximum likelihood estimation and regression analysis. Results Overall, one highly significant (LOD > 3.0, four significant (2.0 Conclusion This study identified ten novel QTL for lactation persistency and extended lactation in sheep, but results suggest that lactation persistency and extended lactation do not have a major gene in common. These results provide a basis for further validation in extended families and other breeds as well as targeting regions for genome-wide association mapping using high-density SNP arrays.

  8. Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology.

    Science.gov (United States)

    Hill, Camilla B; Taylor, Julian D; Edwards, James; Mather, Diane; Langridge, Peter; Bacic, Antony; Roessner, Ute

    2015-04-01

    Mapping of quantitative trait loci associated with levels of individual metabolites (mQTL) was combined with the mapping of agronomic traits to investigate the genetic basis of variation and co-variation in metabolites, agronomic traits, and plant phenology in a field-grown bread wheat population. Metabolome analysis was performed using liquid chromatography-mass spectrometry resulting in identification of mainly polar compounds, including secondary metabolites. A total of 558 metabolic features were obtained from the flag leaves of 179 doubled haploid lines, of which 197 features were putatively identified, mostly as alkaloids, flavonoids and phenylpropanoids. Coordinated genetic control was observed for several groups of metabolites, such as organic acids influenced by two loci on chromosome 7A. Five major phenology-related loci, which were introduced as cofactors in the analyses, differed in their impact upon metabolic and agronomic traits with QZad-aww-7A having more impact on the expression of both metabolite and agronomic QTL than Ppd-B1, Vrn-A1, Eps, and QZad-aww-7D. This QTL study validates the utility of combining agronomic and metabolomic traits as an approach to identify potential trait enhancement targets for breeding selection and reinforces previous results that demonstrate the importance of including plant phenology in the assessment of useful traits in this wheat mapping population. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  9. Association Mapping Reveals Genetic Loci Associated with Important Agronomic Traits in Lentinula edodes, Shiitake Mushroom

    Science.gov (United States)

    Li, Chuang; Gong, Wenbing; Zhang, Lin; Yang, Zhiquan; Nong, Wenyan; Bian, Yinbing; Kwan, Hoi-Shan; Cheung, Man-Kit; Xiao, Yang

    2017-01-01

    Association mapping is a robust approach for the detection of quantitative trait loci (QTLs). Here, by genotyping 297 genome-wide molecular markers of 89 Lentinula edodes cultivars in China, the genetic diversity, population structure and genetic loci associated with 11 agronomic traits were examined. A total of 873 alleles were detected in the tested strains with a mean of 2.939 alleles per locus, and the Shannon's information index was 0.734. Population structure analysis revealed two robustly differentiated groups among the Chinese L. edodes cultivars (FST = 0.247). Using the mixed linear model, a total of 43 markers were detected to be significantly associated with four traits. The number of markers associated with traits ranged from 9 to 26, and the phenotypic variations explained by each marker varied from 12.07% to 31.32%. Apart from five previously reported markers, the remaining 38 markers were newly reported here. Twenty-one markers were identified as simultaneously linked to two to four traits, and five markers were associated with the same traits in cultivation tests performed in two consecutive years. The 43 traits-associated markers were related to 97 genes, and 24 of them were related to 10 traits-associated markers detected in both years or identified previously, 13 of which had a >2-fold expression change between the mycelium and primordium stages. Our study has provided candidate markers for marker-assisted selection (MAS) and useful clues for understanding the genetic architecture of agronomic traits in the shiitake mushroom. PMID:28261189

  10. Mapping the quantitative trait loci (QTL) controlling seed morphology and disk diameter in sunflower (Helianthus annuus L.)

    Science.gov (United States)

    Several seed morphological traits, along with disk diameter, differ greatly between oilseed and confection sunflower types, which are bred for different end-use purposes. This paper reports the results of analyzing the quantitative trait loci (QTL) underlying seed morphological traits and disk diam...

  11. Mapping quantitative trait loci (QTLs for fatty acid composition in an interspecific cross of oil palm

    Directory of Open Access Journals (Sweden)

    Sharma Mukesh

    2009-08-01

    Full Text Available Abstract Background Marker Assisted Selection (MAS is well suited to a perennial crop like oil palm, in which the economic products are not produced until several years after planting. The use of DNA markers for selection in such crops can greatly reduce the number of breeding cycles needed. With the use of DNA markers, informed decisions can be made at the nursery stage, regarding which individuals should be retained as breeding stock, which are satisfactory for agricultural production, and which should be culled. The trait associated with oil quality, measured in terms of its fatty acid composition, is an important agronomic trait that can eventually be tracked using molecular markers. This will speed up the production of new and improved oil palm planting materials. Results A map was constructed using AFLP, RFLP and SSR markers for an interspecific cross involving a Colombian Elaeis oleifera (UP1026 and a Nigerian E. guinneensis (T128. A framework map was generated for the male parent, T128, using Joinmap ver. 4.0. In the paternal (E. guineensis map, 252 markers (199 AFLP, 38 RFLP and 15 SSR could be ordered in 21 linkage groups (1815 cM. Interval mapping and multiple-QTL model (MQM mapping (also known as composite interval mapping, CIM were used to detect quantitative trait loci (QTLs controlling oil quality (measured in terms of iodine value and fatty acid composition. At a 5% genome-wide significance threshold level, QTLs associated with iodine value (IV, myristic acid (C14:0, palmitic acid (C16:0, palmitoleic acid (C16:1, stearic acid (C18:0, oleic acid (C18:1 and linoleic acid (C18:2 content were detected. One genomic region on Group 1 appears to be influencing IV, C14:0, C16:0, C18:0 and C18:1 content. Significant QTL for C14:0, C16:1, C18:0 and C18:1 content was detected around the same locus on Group 15, thus revealing another major locus influencing fatty acid composition in oil palm. Additional QTL for C18:0 was detected on Group 3

  12. Genetic background (DDD/Sgn versus C57BL/6J) strongly influences postnatal growth of male mice carrying the A(y) allele at the agouti locus: identification of quantitative trait loci associated with diabetes and body weight loss.

    Science.gov (United States)

    Suto, Jun-ichi; Satou, Kunio

    2013-05-04

    Mice carrying the A(y) allele at the agouti locus become obese and are heavier than their non-A(y) littermates. However, this does not hold true for the genetic background of the DDD mouse strain. At 22 weeks of age, DDD.Cg-A(y) females are heavier than DDD females, whereas DDD.Cg-A(y) males are lighter than DDD males. This study aimed to determine the possible cause and identify the genes responsible for the lower body weight of DDD.Cg-A(y) males. Growth curves of DDD.Cg-A(y) mice were analyzed and compared with those of B6.Cg-A(y) mice from 5 to 25 weeks. In DDD.Cg-A(y) males, body weight gain stopped between 16 and 17 weeks and the body weight gradually decreased; thus, the lower body weight was a consequence of body weight loss. Quantitative trait locus (QTL) mapping was performed in backcrossed (BC) males of DDD × (B6 × DDD.Cg-A(y)) F(1)-A(y) mice. For the body weight at 25 weeks, significant QTLs were identified on chromosomes 1 and 4. The DDD allele was associated with a lower body weight at both loci. In particular, the QTL on chromosome 4 interacted with the A(y) allele. Furthermore, suggestive QTLs for plasma glucose and high molecular weight adiponectin levels were coincidentally mapped to chromosome 4. The DDD allele was associated with increased glucose and decreased adiponectin levels. When the body weight at 25 weeks and plasma glucose levels were considered as dependent and independent variables, respectively, BC A(y) males were classified into two groups according to statistical analysis using the partition method. Mice of one group had significantly higher glucose and lower adiponectin levels than those of the other group and exhibited body weight loss as observed with DDD-A(y) males. The lower body weight of DDD.Cg-A(y) male mice was a consequence of body weight loss. Diabetes mellitus has been suggested to be a possible contributory factor causing body weight loss. The QTL on distal chromosome 4 contained the major responsible genes. This QTL

  13. Mapping quantitative trait loci for binary trait in the F2:3 design

    Indian Academy of Sciences (India)

    cross populations derived from the cross between two inbred lines. Typically, QTL mapping statistics assumes that each. F2 individual is genotyped for the markers and phenotyped for the trait. However, the power in the detection of QTL for a trait with low heritability is relatively low. To increase the power, an F2:3 design, ...

  14. Network-based group variable selection for detecting expression quantitative trait loci (eQTL

    Directory of Open Access Journals (Sweden)

    Zhang Xuegong

    2011-06-01

    Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

  15. Quantitative trait loci in hop (Humulus lupulus L.) reveal complex genetic architecture underlying variation in sex, yield and cone chemistry.

    Science.gov (United States)

    McAdam, Erin L; Freeman, Jules S; Whittock, Simon P; Buck, Emily J; Jakse, Jernej; Cerenak, Andreja; Javornik, Branka; Kilian, Andrzej; Wang, Cai-Hong; Andersen, Dave; Vaillancourt, René E; Carling, Jason; Beatson, Ron; Graham, Lawrence; Graham, Donna; Darby, Peter; Koutoulis, Anthony

    2013-05-30

    Hop (Humulus lupulus L.) is cultivated for its cones, the secondary metabolites of which contribute bitterness, flavour and aroma to beer. Molecular breeding methods, such as marker assisted selection (MAS), have great potential for improving the efficiency of hop breeding. The success of MAS is reliant on the identification of reliable marker-trait associations. This study used quantitative trait loci (QTL) analysis to identify marker-trait associations for hop, focusing on traits related to expediting plant sex identification, increasing yield capacity and improving bittering, flavour and aroma chemistry. QTL analysis was performed on two new linkage maps incorporating transferable Diversity Arrays Technology (DArT) markers. Sixty-three QTL were identified, influencing 36 of the 50 traits examined. A putative sex-linked marker was validated in a different pedigree, confirming the potential of this marker as a screening tool in hop breeding programs. An ontogenetically stable QTL was identified for the yield trait dry cone weight; and a QTL was identified for essential oil content, which verified the genetic basis for variation in secondary metabolite accumulation in hop cones. A total of 60 QTL were identified for 33 secondary metabolite traits. Of these, 51 were pleiotropic/linked, affecting a substantial number of secondary metabolites; nine were specific to individual secondary metabolites. Pleiotropy and linkage, found for the first time to influence multiple hop secondary metabolites, have important implications for molecular selection methods. The selection of particular secondary metabolite profiles using pleiotropic/linked QTL will be challenging because of the difficulty of selecting for specific traits without adversely changing others. QTL specific to individual secondary metabolites, however, offer unequalled value to selection programs. In addition to their potential for selection, the QTL identified in this study advance our understanding of the

  16. Generalized linear model for mapping discrete trait loci implemented with LASSO algorithm.

    Directory of Open Access Journals (Sweden)

    Jun Xing

    Full Text Available Generalized estimating equation (GEE algorithm under a heterogeneous residual variance model is an extension of the iteratively reweighted least squares (IRLS method for continuous traits to discrete traits. In contrast to mixture model-based expectation-maximization (EM algorithm, the GEE algorithm can well detect quantitative trait locus (QTL, especially large effect QTLs located in large marker intervals in the manner of high computing speed. Based on a single QTL model, however, the GEE algorithm has very limited statistical power to detect multiple QTLs because of ignoring other linked QTLs. In this study, the fast least absolute shrinkage and selection operator (LASSO is derived for generalized linear model (GLM with all possible link functions. Under a heterogeneous residual variance model, the LASSO for GLM is used to iteratively estimate the non-zero genetic effects of those loci over entire genome. The iteratively reweighted LASSO is therefore extended to mapping QTL for discrete traits, such as ordinal, binary, and Poisson traits. The simulated and real data analyses are conducted to demonstrate the efficiency of the proposed method to simultaneously identify multiple QTLs for binary and Poisson traits as examples.

  17. Generalized linear model for mapping discrete trait loci implemented with LASSO algorithm.

    Science.gov (United States)

    Xing, Jun; Gao, Huijiang; Wu, Yang; Wu, Yani; Li, Hongwang; Yang, Runqing

    2014-01-01

    Generalized estimating equation (GEE) algorithm under a heterogeneous residual variance model is an extension of the iteratively reweighted least squares (IRLS) method for continuous traits to discrete traits. In contrast to mixture model-based expectation-maximization (EM) algorithm, the GEE algorithm can well detect quantitative trait locus (QTL), especially large effect QTLs located in large marker intervals in the manner of high computing speed. Based on a single QTL model, however, the GEE algorithm has very limited statistical power to detect multiple QTLs because of ignoring other linked QTLs. In this study, the fast least absolute shrinkage and selection operator (LASSO) is derived for generalized linear model (GLM) with all possible link functions. Under a heterogeneous residual variance model, the LASSO for GLM is used to iteratively estimate the non-zero genetic effects of those loci over entire genome. The iteratively reweighted LASSO is therefore extended to mapping QTL for discrete traits, such as ordinal, binary, and Poisson traits. The simulated and real data analyses are conducted to demonstrate the efficiency of the proposed method to simultaneously identify multiple QTLs for binary and Poisson traits as examples.

  18. Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure

    Science.gov (United States)

    Wain, Louise V; Verwoert, Germaine C; O’Reilly, Paul F; Shi, Gang; Johnson, Toby; Johnson, Andrew D; Bochud, Murielle; Rice, Kenneth M; Henneman, Peter; Smith, Albert V; Ehret, Georg B; Amin, Najaf; Larson, Martin G; Mooser, Vincent; Hadley, David; Dörr, Marcus; Bis, Joshua C; Aspelund, Thor; Esko, Tõnu; Janssens, A Cecile JW; Zhao, Jing Hua; Heath, Simon; Laan, Maris; Fu, Jingyuan; Pistis, Giorgio; Luan, Jian’an; Arora, Pankaj; Lucas, Gavin; Pirastu, Nicola; Pichler, Irene; Jackson, Anne U; Webster, Rebecca J; Zhang, Feng; Peden, John F; Schmidt, Helena; Tanaka, Toshiko; Campbell, Harry; Igl, Wilmar; Milaneschi, Yuri; Hotteng, Jouke-Jan; Vitart, Veronique; Chasman, Daniel I; Trompet, Stella; Bragg-Gresham, Jennifer L; Alizadeh, Behrooz Z; Chambers, John C; Guo, Xiuqing; Lehtimäki, Terho; Kühnel, Brigitte; Lopez, Lorna M; Polašek, Ozren; Boban, Mladen; Nelson, Christopher P; Morrison, Alanna C; Pihur, Vasyl; Ganesh, Santhi K; Hofman, Albert; Kundu, Suman; Mattace-Raso, Francesco US; Rivadeneira, Fernando; Sijbrands, Eric JG; Uitterlinden, Andre G; Hwang, Shih-Jen; Vasan, Ramachandran S; Wang, Thomas J; Bergmann, Sven; Vollenweider, Peter; Waeber, Gérard; Laitinen, Jaana; Pouta, Anneli; Zitting, Paavo; McArdle, Wendy L; Kroemer, Heyo K; Völker, Uwe; Völzke, Henry; Glazer, Nicole L; Taylor, Kent D; Harris, Tamara B; Alavere, Helene; Haller, Toomas; Keis, Aime; Tammesoo, Mari-Liis; Aulchenko, Yurii; Barroso, Inês; Khaw, Kay-Tee; Galan, Pilar; Hercberg, Serge; Lathrop, Mark; Eyheramendy, Susana; Org, Elin; Sõber, Siim; Lu, Xiaowen; Nolte, Ilja M; Penninx, Brenda W; Corre, Tanguy; Masciullo, Corrado; Sala, Cinzia; Groop, Leif; Voight, Benjamin F; Melander, Olle; O’Donnell, Christopher J; Salomaa, Veikko; d’Adamo, Adamo Pio; Fabretto, Antonella; Faletra, Flavio; Ulivi, Sheila; Del Greco, M Fabiola; Facheris, Maurizio; Collins, Francis S; Bergman, Richard N; Beilby, John P; Hung, Joseph; Musk, A William; Mangino, Massimo; Shin, So-Youn; Soranzo, Nicole; Watkins, Hugh; Goel, Anuj; Hamsten, Anders; Gider, Pierre; Loitfelder, Marisa; Zeginigg, Marion; Hernandez, Dena; Najjar, Samer S; Navarro, Pau; Wild, Sarah H; Corsi, Anna Maria; Singleton, Andrew; de Geus, Eco JC; Willemsen, Gonneke; Parker, Alex N; Rose, Lynda M; Buckley, Brendan; Stott, David; Orru, Marco; Uda, Manuela; van der Klauw, Melanie M; Zhang, Weihua; Li, Xinzhong; Scott, James; Chen, Yii-Der Ida; Burke, Gregory L; Kähönen, Mika; Viikari, Jorma; Döring, Angela; Meitinger, Thomas; Davies, Gail; Starr, John M; Emilsson, Valur; Plump, Andrew; Lindeman, Jan H; ’t Hoen, Peter AC; König, Inke R; Felix, Janine F; Clarke, Robert; Hopewell, Jemma C; Ongen, Halit; Breteler, Monique; Debette, Stéphanie; DeStefano, Anita L; Fornage, Myriam; Mitchell, Gary F; Smith, Nicholas L; Holm, Hilma; Stefansson, Kari; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Samani, Nilesh J; Preuss, Michael; Rudan, Igor; Hayward, Caroline; Deary, Ian J; Wichmann, H-Erich; Raitakari, Olli T; Palmas, Walter; Kooner, Jaspal S; Stolk, Ronald P; Jukema, J Wouter; Wright, Alan F; Boomsma, Dorret I; Bandinelli, Stefania; Gyllensten, Ulf B; Wilson, James F; Ferrucci, Luigi; Schmidt, Reinhold; Farrall, Martin; Spector, Tim D; Palmer, Lyle J; Tuomilehto, Jaakko; Pfeufer, Arne; Gasparini, Paolo; Siscovick, David; Altshuler, David; Loos, Ruth JF; Toniolo, Daniela; Snieder, Harold; Gieger, Christian; Meneton, Pierre; Wareham, Nicholas J; Oostra, Ben A; Metspalu, Andres; Launer, Lenore; Rettig, Rainer; Strachan, David P; Beckmann, Jacques S; Witteman, Jacqueline CM; Erdmann, Jeanette; van Dijk, Ko Willems; Boerwinkle, Eric; Boehnke, Michael; Ridker, Paul M; Jarvelin, Marjo-Riitta; Chakravarti, Aravinda; Abecasis, Goncalo R; Gudnason, Vilmundur; Newton-Cheh, Christopher; Levy, Daniel; Munroe, Patricia B; Psaty, Bruce M; Caulfield, Mark J; Rao, Dabeeru C

    2012-01-01

    Numerous genetic loci influence systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans 1-3. We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N=74,064) and follow-up studies (N=48,607), we identified at genome-wide significance (P= 2.7×10-8 to P=2.3×10-13) four novel PP loci (at 4q12 near CHIC2/PDGFRAI, 7q22.3 near PIK3CG, 8q24.12 in NOV, 11q24.3 near ADAMTS-8), two novel MAP loci (3p21.31 in MAP4, 10q25.3 near ADRB1) and one locus associated with both traits (2q24.3 near FIGN) which has recently been associated with SBP in east Asians. For three of the novel PP signals, the estimated effect for SBP was opposite to that for DBP, in contrast to the majority of common SBP- and DBP-associated variants which show concordant effects on both traits. These findings indicate novel genetic mechanisms underlying blood pressure variation, including pathways that may differentially influence SBP and DBP. PMID:21909110

  19. Two candidate genes for two quantitative trait loci epistatically attenuate hypertension in a novel pathway.

    Science.gov (United States)

    Chauvet, Cristina; Ménard, Annie; Deng, Alan Y

    2015-09-01

    Multiple quantitative trait loci (QTLs) for blood pressure (BP) have been detected in rat models of human polygenic hypertension. They influence BP physiologically via epistatic modules. Little is known about the causal genes and virtually nothing is known on modularized mechanisms governing their regulatory connections. Two genes responsible for two individual BP QTLs on rat Chromosome 18 have been identified that belong to the same epistatic module. Treacher Collins-Franceschetti syndrome 1 (Tcof1) gene is the only function candidate for C18QTL3. Haloacid dehalogenase like hydrolase domain containing 2 (Hdhd2), although a gene of previously unknown function, is C18QTL4, and encodes a newly identified phosphatase. The current work has provided the premier evidence that Hdhd2/C18QTL4 and Tcof1/C18QTL3 may be involved in polygenic hypertension. Hdhd2/C18QTL4 can regulate the function of Tcof1/C18QTL3 via de-phosphorylation, and, for the first time, furbishes a molecular mechanism in support of a genetically epistatic hierarchy between two BP QTLs, and thus authenticates the epistasis-common pathway paradigm. The pathway initiated by Hdhd2/C18QTL4 upstream of Tcof1/C18QTL3 reveals novel mechanistic insights into BP modulations. Their discovery might yield innovative therapeutic targets and diagnostic tools predicated on a novel BP cause and mechanism that is determined by a regulatory hierarchy. Optimizing the de-phosphorylation capability and its downstream target could be antihypertensive. The conceptual paradigm of an order and regulatory hierarchy may help unravel genetic and molecular relationships among certain human BP QTLs.

  20. Linkage of DNA Methylation Quantitative Trait Loci to Human Cancer Risk

    Directory of Open Access Journals (Sweden)

    Holger Heyn

    2014-04-01

    Full Text Available Epigenetic regulation and, in particular, DNA methylation have been linked to the underlying genetic sequence. DNA methylation quantitative trait loci (meQTL have been identified through significant associations between the genetic and epigenetic codes in physiological and pathological contexts. We propose that interrogating the interplay between polymorphic alleles and DNA methylation is a powerful method for improving our interpretation of risk alleles identified in genome-wide association studies that otherwise lack mechanistic explanation. We integrated patient cancer risk genotype data and genome-scale DNA methylation profiles of 3,649 primary human tumors, representing 13 solid cancer types. We provide a comprehensive meQTL catalog containing DNA methylation associations for 21% of interrogated cancer risk polymorphisms. Differentially methylated loci harbor previously reported and as-yet-unidentified cancer genes. We suggest that such regulation at the DNA level can provide a considerable amount of new information about the biology of cancer-risk alleles.

  1. Analysis combining correlated glaucoma traits identifies five new risk loci for open-angle glaucoma.

    Science.gov (United States)

    Gharahkhani, Puya; Burdon, Kathryn P; Cooke Bailey, Jessica N; Hewitt, Alex W; Law, Matthew H; Pasquale, Louis R; Kang, Jae H; Haines, Jonathan L; Souzeau, Emmanuelle; Zhou, Tiger; Siggs, Owen M; Landers, John; Awadalla, Mona; Sharma, Shiwani; Mills, Richard A; Ridge, Bronwyn; Lynn, David; Casson, Robert; Graham, Stuart L; Goldberg, Ivan; White, Andrew; Healey, Paul R; Grigg, John; Lawlor, Mitchell; Mitchell, Paul; Ruddle, Jonathan; Coote, Michael; Walland, Mark; Best, Stephen; Vincent, Andrea; Gale, Jesse; RadfordSmith, Graham; Whiteman, David C; Montgomery, Grant W; Martin, Nicholas G; Mackey, David A; Wiggs, Janey L; MacGregor, Stuart; Craig, Jamie E

    2018-02-15

    Open-angle glaucoma (OAG) is a major cause of blindness worldwide. To identify new risk loci for OAG, we performed a genome-wide association study in 3,071 OAG cases and 6,750 unscreened controls, and meta-analysed the results with GWAS data for intraocular pressure (IOP) and optic disc parameters (the overall meta-analysis sample size varying between 32,000 to 48,000 participants), which are glaucoma-related traits. We identified and independently validated four novel genome-wide significant associations within or near MYOF and CYP26A1, LINC02052 and CRYGS, LMX1B, and LMO7 using single variant tests, one additional locus (C9) using gene-based tests, and two genetic pathways - "response to fluid shear stress" and "abnormal retina morphology" - in pathway-based tests. Interestingly, some of the new risk loci contribute to risk of other genetically-correlated eye diseases including myopia and age-related macular degeneration. To our knowledge, this study is the first integrative study to combine genetic data from OAG and its correlated traits to identify new risk variants and genetic pathways, highlighting the future potential of combining genetic data from genetically-correlated eye traits for the purpose of gene discovery and mapping.

  2. Comparative mapping of quantitative trait loci for tassel-related traits ...

    Indian Academy of Sciences (India)

    Knapp S. J., Bridges W. C. 1990 Using molecular markers to estimate quantitative trait locus parameters; power and genetic variances for unreplicated and replicated progeny. Genetics 126, 769–777. Knapp S. J., Stroup W. W., Ross W. M. 1985 Exact confidence intervals for heritability on a progeny mean basis. Crop Sci.

  3. Validation and dissection of quantitative trait loci for leaf traits in ...

    Indian Academy of Sciences (India)

    Validation and dissection of a QTL region for leaf traits in rice which has been reported in a number of independent studies were conducted. Three sets of near isogenic lines (NILs) were originated from a residual heterozygous line derived the indica cross Zhenshan 97B/Milyang 46. They were overlapping and totally ...

  4. Comparative mapping of quantitative trait loci for tassel-related traits ...

    Indian Academy of Sciences (India)

    QIANG YI

    2018-03-15

    Mar 15, 2018 ... families across six environments and in 301 recombinant inbred lines (RILs) across three environments, where all the plants were derived from a cross between 08-641 and Ye478. We compared the genetic architecture of the two traits across two generations through combined analysis. In total, 27 ...

  5. Detection of quantitative trait loci on chromosomes 1,2,3,12,14,15, X in pigs: performance characteristics

    NARCIS (Netherlands)

    Paixao, D.M.; Carneiro, P.L.S.; Paiva, S.R.; Sousa, K.R.S.; Verardo, L.L.; Braccini Neto, J.; Pinto, A.P.G.; Marubayashi Hidalgo, A.; Nascimento, C.; Périssé, I.V.; Lopes, P.S.; Guimaraes, S.E.F.

    2013-01-01

    The accomplishment of the present study had the objective of mapping Quantitative Trait Loci (QTL) related to performance traits in a F2 pig population developed by mating two Brazilian Piau breed sires with 18 dams from a commercial line (Landrace × Large White × Pietrain). The linkage map for this

  6. Identification of Genetic Loci Associated with Quality Traits in Almond via Association Mapping.

    Directory of Open Access Journals (Sweden)

    Carolina Font i Forcada

    Full Text Available To design an appropriate association study, we need to understand population structure and the structure of linkage disequilibrium within and among populations as well as in different regions of the genome in an organism. In this study, we have used a total of 98 almond accessions, from five continents located and maintained at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA; Spain, and 40 microsatellite markers. Population structure analysis performed in 'Structure' grouped the accessions into two principal groups; the Mediterranean (Western-Europe and the non-Mediterranean, with K = 3, being the best fit for our data. There was a strong subpopulation structure with linkage disequilibrium decaying with increasing genetic distance resulting in lower levels of linkage disequilibrium between more distant markers. A significant impact of population structure on linkage disequilibrium in the almond cultivar groups was observed. The mean r2 value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits, five models comprising both general linear models and mixed linear models were selected to test the marker trait associations. The mixed linear model (MLM approach using co-ancestry values from population structure and kinship estimates (K model as covariates identified a maximum of 16 significant associations for chemical traits and 12 for physical traits. This study reports for the first time the use of association mapping for determining marker-locus trait associations in a world-wide almond germplasm collection. It is likely that association mapping will have the most immediate and largest impact on the tier of crops such as almond with the greatest economic value.

  7. Chromosomal assignment of quantitative trait loci influencing modified hole board behavior in laboratory mice using consomic strains, with special reference to anxiety-related behavior and mouse chromosome 19.

    Science.gov (United States)

    Laarakker, Marijke C; Ohl, Frauke; van Lith, Hein A

    2008-03-01

    Male mice from a panel of chromosome substitution strains (CSS, also called consomic strains or lines)--in which a single full-length chromosome from the A/J inbred strain has been transferred onto the genetic background of the C57BL/6J inbred strain--and the parental strains were examined in the modified hole board test. This behavioral test allows to assess for a variety of different motivational systems in parallel (i.e. anxiety, risk assessment, exploration, memory, locomotion, and arousal). Such an approach is essential for behavioral characterization since the motivational system of interest is strongly influenced by other behavioral systems. Both univariate and bivariate analyses, as well as a factor analysis, were performed. The C57BL/6J and A/J mouse parental inbred strains differed in all motivational systems. The chromosome substitution strain survey indicated that nearly all mouse chromosomes (with the exception of chromosome 2) each contain at least one quantitative trait locus (QTL) that is involved in modified hole board behavior. The results agreed well with previous reports of QTLs for anxiety-related behavior using the A/J and C57BL/6J as parental strains. The present study confirmed that mouse chromosomes 5, 8, 10, 15, 18 and 19 likely contain at least one anxiety QTL. There was also evidence for a novel anxiety QTL on the Y chromosome. With respect to anxiety-related avoidance behavior towards an unprotected area, we have special interest for mouse chromosome 19. CSS-19 (C57BL/6J-Chr19(A)/NaJ) differed in avoidance behavior from the C57BL/6J, but not in locomotion. Thus pleiotropic contribution of locomotion could be excluded.

  8. Quantitative trait loci for resistance to trichostrongylid infection in Spanish Churra sheep

    Directory of Open Access Journals (Sweden)

    Primitivo Fermin San

    2009-10-01

    Full Text Available Abstract Background For ruminants reared on grazing systems, gastrointestinal nematode (GIN parasite infections represent the class of diseases with the greatest impact on animal health and productivity. Among the many possible strategies for controlling GIN infection, the enhancement of host resistance through the selection of resistant animals has been suggested by many authors. Because of the difficulty of routinely collecting phenotypic indicators of parasite resistance, information derived from molecular markers may be used to improve the efficiency of classical genetic breeding. Methods A total of 181 microsatellite markers evenly distributed along the 26 sheep autosomes were used in a genome scan analysis performed in a commercial population of Spanish Churra sheep to detect chromosomal regions associated with parasite resistance. Following a daughter design, we analysed 322 ewes distributed in eight half-sib families. The phenotypes studied included two faecal egg counts (LFEC0 and LFEC1, anti-Teladorsagia circumcincta LIV IgA levels (IgA and serum pepsinogen levels (Peps. Results The regression analysis revealed one QTL at the 5% genome-wise significance level on chromosome 6 for LFEC1 within the marker interval BM4621-CSN3. This QTL was found to be segregating in three out of the eight families analysed. Four other QTL were identified at the 5% chromosome-wise level on chromosomes 1, 10 and 14. Three of these QTL influenced faecal egg count, and the other one had an effect on IgA levels. Conclusion This study has successfully identified segregating QTL for parasite resistance traits in a commercial population. For some of the QTL detected, we have identified interesting coincidences with QTL previously reported in sheep, although most of those studies have been focused on young animals. Some of these coincidences might indicate that some common underlying loci affect parasite resistance traits in different sheep breeds. The

  9. Mapping quantitative trait loci affecting Arabidopsis thaliana seed morphology features extracted computationally from images.

    Science.gov (United States)

    Moore, Candace R; Gronwall, David S; Miller, Nathan D; Spalding, Edgar P

    2013-01-01

    Seeds are studied to understand dispersal and establishment of the next generation, as units of agricultural yield, and for other important reasons. Thus, elucidating the genetic architecture of seed size and shape traits will benefit basic and applied plant biology research. This study sought quantitative trait loci (QTL) controlling the size and shape of Arabidopsis thaliana seeds by computational analysis of seed phenotypes in recombinant inbred lines derived from the small-seeded Landsberg erecta × large-seeded Cape Verde Islands accessions. On the order of 10(3) seeds from each recombinant inbred line were automatically measured with flatbed photo scanners and custom image analysis software. The eight significant QTL affecting seed area explained 63% of the variation, and overlapped with five of the six major-axis (length) QTL and three of the five minor-axis (width) QTL, which accounted for 57% and 38% of the variation in those traits, respectively. Because the Arabidopsis seed is exalbuminous, lacking an endosperm at maturity, the results are relatable to embryo length and width. The Cvi allele generally had a positive effect of 2.6-4.0%. Analysis of variance showed heritability of the three traits ranged between 60% and 73%. Repeating the experiment with 2.2 million seeds from a separate harvest of the RIL population and approximately 0.5 million seeds from 92 near-isogenic lines confirmed the aforementioned results. Structured for download are files containing phenotype measurements, all sets of seed images, and the seed trait measuring tool.

  10. Quantitative trait Loci association mapping by imputation of strain origins in multifounder crosses.

    Science.gov (United States)

    Zhou, Jin J; Ghazalpour, Anatole; Sobel, Eric M; Sinsheimer, Janet S; Lange, Kenneth

    2012-02-01

    Although mapping quantitative traits in inbred strains is simpler than mapping the analogous traits in humans, classical inbred crosses suffer from reduced genetic diversity compared to experimental designs involving outbred animal populations. Multiple crosses, for example the Complex Trait Consortium's eight-way cross, circumvent these difficulties. However, complex mating schemes and systematic inbreeding raise substantial computational difficulties. Here we present a method for locally imputing the strain origins of each genotyped animal along its genome. Imputed origins then serve as mean effects in a multivariate Gaussian model for testing association between trait levels and local genomic variation. Imputation is a combinatorial process that assigns the maternal and paternal strain origin of each animal on the basis of observed genotypes and prior pedigree information. Without smoothing, imputation is likely to be ill-defined or jump erratically from one strain to another as an animal's genome is traversed. In practice, one expects to see long stretches where strain origins are invariant. Smoothing can be achieved by penalizing strain changes from one marker to the next. A dynamic programming algorithm then solves the strain imputation process in one quick pass through the genome of an animal. Imputation accuracy exceeds 99% in practical examples and leads to high-resolution mapping in simulated and real data. The previous fastest quantitative trait loci (QTL) mapping software for dense genome scans reduced compute times to hours. Our implementation further reduces compute times from hours to minutes with no loss in statistical power. Indeed, power is enhanced for full pedigree data.

  11. Design database for quantitative trait loci (QTL) data warehouse, data mining, and meta-analysis.

    Science.gov (United States)

    Hu, Zhi-Liang; Reecy, James M; Wu, Xiao-Lin

    2012-01-01

    A database can be used to warehouse quantitative trait loci (QTL) data from multiple sources for comparison, genomic data mining, and meta-analysis. A robust database design involves sound data structure logistics, meaningful data transformations, normalization, and proper user interface designs. This chapter starts with a brief review of relational database basics and concentrates on issues associated with curation of QTL data into a relational database, with emphasis on the principles of data normalization and structure optimization. In addition, some simple examples of QTL data mining and meta-analysis are included. These examples are provided to help readers better understand the potential and importance of sound database design.

  12. A Molecular Genetic Linkage Map of Eucommia ulmoides and Quantitative Trait Loci (QTL Analysis for Growth Traits

    Directory of Open Access Journals (Sweden)

    Yu Li

    2014-01-01

    Full Text Available Eucommia ulmoides is an economically important tree species for both herbal medicine and organic chemical industry. Effort to breed varieties with improved yield and quality is limited by the lack of knowledge on the genetic basis of the traits. A genetic linkage map of E. ulmoides was constructed from a full-sib family using sequence-related amplified polymorphism, amplified fragment length polymorphism, inter-simple sequence repeat and simple sequence repeat markers. In total, 706 markers were mapped in 25 linkage groups covering 2133 cM. The genetic linkage map covered approximately 89% of the estimated E. ulmoides genome with an average of 3.1 cM between adjacent markers. The present genetic linkage map was used to identify quantitative trait loci (QTL affecting growth-related traits. Eighteen QTLs were found to explain 12.4%–33.3% of the phenotypic variance. This genetic linkage map provides a tool for marker-assisted selection and for studies of genome in E. ulmoides.

  13. Seventy-five genetic loci influencing the human red blood cell

    Science.gov (United States)

    van der Harst, Pim; Zhang, Weihua; Leach, Irene Mateo; Rendon, Augusto; Verweij, Niek; Sehmi, Joban; Paul, Dirk S.; Elling, Ulrich; Allayee, Hooman; Li, Xinzhong; Radhakrishnan, Aparna; Tan, Sian-Tsung; Voss, Katrin; Weichenberger, Christian X.; Albers, Cornelis A.; Al-Hussani, Abtehale; Asselbergs, Folkert W.; Ciullo, Marina; Danjou, Fabrice; Dina, Christian; Esko, Tõnu; Evans, David M.; Franke, Lude; Gögele, Martin; Hartiala, Jaana; Hersch, Micha; Holm, Hilma; Hottenga, Jouke-Jan; Kanoni, Stavroula; Kleber, Marcus E.; Lagou, Vasiliki; Langenberg, Claudia; Lopez, Lorna M.; Lyytikäinen, Leo-Pekka; Melander, Olle; Murgia, Federico; Nolte, Ilja M.; O’Reilly, Paul F.; Padmanabhan, Sandosh; Parsa, Afshin; Pirastu, Nicola; Porcu, Eleonora; Portas, Laura; Prokopenko, Inga; Ried, Janina S.; Shin, So-Youn; Tang, Clara S.; Teumer, Alexander; Traglia, Michela; Ulivi, Sheila; Westra, Harm-Jan; Yang, Jian; Zhao, Jing Hua; Anni, Franco; Abdellaoui, Abdel; Attwood, Antony; Balkau, Beverley; Bandinelli, Stefania; Bastardot, François; Benyamin, Beben; Boehm, Bernhard O.; Cookson, William O.; Das, Debashish; de Bakker, Paul I. W.; de Boer, Rudolf A.; de Geus, Eco J. C.; de Moor, Marleen H.; Dimitriou, Maria; Domingues, Francisco S.; Döring, Angela; Engström, Gunnar; Eyjolfsson, Gudmundur Ingi; Ferrucci, Luigi; Fischer, Krista; Galanello, Renzo; Garner, Stephen F.; Genser, Bernd; Gibson, Quince D.; Girotto, Giorgia; Gudbjartsson, Daniel Fannar; Harris, Sarah E.; Hartikainen, Anna-Liisa; Hastie, Claire E.; Hedblad, Bo; Illig, Thomas; Jolley, Jennifer; Kähönen, Mika; Kema, Ido P.; Kemp, John P.; Liang, Liming; Lloyd-Jones, Heather; Loos, Ruth J. F.; Meacham, Stuart; Medland, Sarah E.; Meisinger, Christa; Memari, Yasin; Mihailov, Evelin; Miller, Kathy; Moffatt, Miriam F.; Nauck, Matthias; Novatchkova, Maria; Nutile, Teresa; Olafsson, Isleifur; Onundarson, Pall T.; Parracciani, Debora; Penninx, Brenda W.; Perseu, Lucia; Piga, Antonio; Pistis, Giorgio; Pouta, Anneli; Puc, Ursula; Raitakari, Olli; Ring, Susan M.; Robino, Antonietta; Ruggiero, Daniela; Ruokonen, Aimo; Saint-Pierre, Aude; Sala, Cinzia; Salumets, Andres; Sambrook, Jennifer; Schepers, Hein; Schmidt, Carsten Oliver; Silljé, Herman H. W.; Sladek, Rob; Smit, Johannes H.; Starr, John M.; Stephens, Jonathan; Sulem, Patrick; Tanaka, Toshiko; Thorsteinsdottir, Unnur; Tragante, Vinicius; van Gilst, Wiek H.; van Pelt, L. Joost; van Veldhuisen, Dirk J.; Völker, Uwe; Whitfield, John B.; Willemsen, Gonneke; Winkelmann, Bernhard R.; Wirnsberger, Gerald; Algra, Ale; Cucca, Francesco; d’Adamo, Adamo Pio; Danesh, John; Deary, Ian J.; Dominiczak, Anna F.; Elliott, Paul; Fortina, Paolo; Froguel, Philippe; Gasparini, Paolo; Greinacher, Andreas; Hazen, Stanley L.; Jarvelin, Marjo-Riitta; Khaw, Kay Tee; Lehtimäki, Terho; Maerz, Winfried; Martin, Nicholas G.; Metspalu, Andres; Mitchell, Braxton D.; Montgomery, Grant W.; Moore, Carmel; Navis, Gerjan; Pirastu, Mario; Pramstaller, Peter P.; Ramirez-Solis, Ramiro; Schadt, Eric; Scott, James; Shuldiner, Alan R.; Smith, George Davey; Smith, J. Gustav; Snieder, Harold; Sorice, Rossella; Spector, Tim D.; Stefansson, Kari; Stumvoll, Michael; Wilson Tang, W. H.; Toniolo, Daniela; Tönjes, Anke; Visscher, Peter M.; Vollenweider, Peter; Wareham, Nicholas J.; Wolffenbuttel, Bruce H. R.; Boomsma, Dorret I.; Beckmann, Jacques S.; Dedoussis, George V.; Deloukas, Panos; Ferreira, Manuel A.; Sanna, Serena; Uda, Manuela; Hicks, Andrew A.; Penninger, Josef Martin; Gieger, Christian; Kooner, Jaspal S.; Ouwehand, Willem H.; Soranzo, Nicole; Chambers, John C

    2013-01-01

    Anaemia is a chief determinant of globalill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P <10−8, which together explain 4–9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function. PMID:23222517

  14. Seventy-five genetic loci influencing the human red blood cell.

    Science.gov (United States)

    van der Harst, Pim; Zhang, Weihua; Mateo Leach, Irene; Rendon, Augusto; Verweij, Niek; Sehmi, Joban; Paul, Dirk S; Elling, Ulrich; Allayee, Hooman; Li, Xinzhong; Radhakrishnan, Aparna; Tan, Sian-Tsung; Voss, Katrin; Weichenberger, Christian X; Albers, Cornelis A; Al-Hussani, Abtehale; Asselbergs, Folkert W; Ciullo, Marina; Danjou, Fabrice; Dina, Christian; Esko, Tõnu; Evans, David M; Franke, Lude; Gögele, Martin; Hartiala, Jaana; Hersch, Micha; Holm, Hilma; Hottenga, Jouke-Jan; Kanoni, Stavroula; Kleber, Marcus E; Lagou, Vasiliki; Langenberg, Claudia; Lopez, Lorna M; Lyytikäinen, Leo-Pekka; Melander, Olle; Murgia, Federico; Nolte, Ilja M; O'Reilly, Paul F; Padmanabhan, Sandosh; Parsa, Afshin; Pirastu, Nicola; Porcu, Eleonora; Portas, Laura; Prokopenko, Inga; Ried, Janina S; Shin, So-Youn; Tang, Clara S; Teumer, Alexander; Traglia, Michela; Ulivi, Sheila; Westra, Harm-Jan; Yang, Jian; Zhao, Jing Hua; Anni, Franco; Abdellaoui, Abdel; Attwood, Antony; Balkau, Beverley; Bandinelli, Stefania; Bastardot, François; Benyamin, Beben; Boehm, Bernhard O; Cookson, William O; Das, Debashish; de Bakker, Paul I W; de Boer, Rudolf A; de Geus, Eco J C; de Moor, Marleen H; Dimitriou, Maria; Domingues, Francisco S; Döring, Angela; Engström, Gunnar; Eyjolfsson, Gudmundur Ingi; Ferrucci, Luigi; Fischer, Krista; Galanello, Renzo; Garner, Stephen F; Genser, Bernd; Gibson, Quince D; Girotto, Giorgia; Gudbjartsson, Daniel Fannar; Harris, Sarah E; Hartikainen, Anna-Liisa; Hastie, Claire E; Hedblad, Bo; Illig, Thomas; Jolley, Jennifer; Kähönen, Mika; Kema, Ido P; Kemp, John P; Liang, Liming; Lloyd-Jones, Heather; Loos, Ruth J F; Meacham, Stuart; Medland, Sarah E; Meisinger, Christa; Memari, Yasin; Mihailov, Evelin; Miller, Kathy; Moffatt, Miriam F; Nauck, Matthias; Novatchkova, Maria; Nutile, Teresa; Olafsson, Isleifur; Onundarson, Pall T; Parracciani, Debora; Penninx, Brenda W; Perseu, Lucia; Piga, Antonio; Pistis, Giorgio; Pouta, Anneli; Puc, Ursula; Raitakari, Olli; Ring, Susan M; Robino, Antonietta; Ruggiero, Daniela; Ruokonen, Aimo; Saint-Pierre, Aude; Sala, Cinzia; Salumets, Andres; Sambrook, Jennifer; Schepers, Hein; Schmidt, Carsten Oliver; Silljé, Herman H W; Sladek, Rob; Smit, Johannes H; Starr, John M; Stephens, Jonathan; Sulem, Patrick; Tanaka, Toshiko; Thorsteinsdottir, Unnur; Tragante, Vinicius; van Gilst, Wiek H; van Pelt, L Joost; van Veldhuisen, Dirk J; Völker, Uwe; Whitfield, John B; Willemsen, Gonneke; Winkelmann, Bernhard R; Wirnsberger, Gerald; Algra, Ale; Cucca, Francesco; d'Adamo, Adamo Pio; Danesh, John; Deary, Ian J; Dominiczak, Anna F; Elliott, Paul; Fortina, Paolo; Froguel, Philippe; Gasparini, Paolo; Greinacher, Andreas; Hazen, Stanley L; Jarvelin, Marjo-Riitta; Khaw, Kay Tee; Lehtimäki, Terho; Maerz, Winfried; Martin, Nicholas G; Metspalu, Andres; Mitchell, Braxton D; Montgomery, Grant W; Moore, Carmel; Navis, Gerjan; Pirastu, Mario; Pramstaller, Peter P; Ramirez-Solis, Ramiro; Schadt, Eric; Scott, James; Shuldiner, Alan R; Smith, George Davey; Smith, J Gustav; Snieder, Harold; Sorice, Rossella; Spector, Tim D; Stefansson, Kari; Stumvoll, Michael; Tang, W H Wilson; Toniolo, Daniela; Tönjes, Anke; Visscher, Peter M; Vollenweider, Peter; Wareham, Nicholas J; Wolffenbuttel, Bruce H R; Boomsma, Dorret I; Beckmann, Jacques S; Dedoussis, George V; Deloukas, Panos; Ferreira, Manuel A; Sanna, Serena; Uda, Manuela; Hicks, Andrew A; Penninger, Josef Martin; Gieger, Christian; Kooner, Jaspal S; Ouwehand, Willem H; Soranzo, Nicole; Chambers, John C

    2012-12-20

    Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

  15. Plastic expression of heterochrony quantitative trait loci (hQTLs) for leaf growth in the common bean (Phaseolus vulgaris).

    Science.gov (United States)

    Jiang, Libo; Clavijo, Jose A; Sun, Lidan; Zhu, Xuli; Bhakta, Mehul S; Gezan, Salvador A; Carvalho, Melissa; Vallejos, C Eduardo; Wu, Rongling

    2015-08-01

    Heterochrony, that is, evolutionary changes in the relative timing of developmental events and processes, has emerged as a key concept that links evolution and development. Genes associated with heterochrony encode molecular components of developmental timing mechanisms. However, our understanding of how heterochrony genes alter the expression of heterochrony in response to environmental changes remains very limited. We applied functional mapping to find quantitative trait loci (QTLs) responsible for growth trajectories of leaf area and leaf mass in the common bean (Phaseolus vulgaris) grown in two contrasting environments. We identified three major QTLs pleiotropically expressed under the two environments. Further characterization of the temporal pattern of these QTLs indicates that they are heterochrony QTLs (hQTLs) in terms of their role in influencing four heterochronic parameters: the timing of the inflection point, the timing of maximum acceleration and deceleration, and the duration of linear growth. The pattern of gene action by the hQTLs on each parameter was unique, being environmentally dependent and varying between two allometrically related leaf growth traits. These results provide new insights into the complexity of genetic mechanisms that control trait formation in plants and provide novel findings that will be of use in studying the evolutionary trends. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  16. Quantitative trait loci contributing to physiological and behavioural ethanol responses after acute and chronic treatment.

    Science.gov (United States)

    Drews, Eva; Rácz, Ildiko; Lacava, Amalia Diaz; Barth, Alexander; Bilkei-Gorzó, Andras; Wienker, Thomas F; Zimmer, Andreas

    2010-03-01

    The aim of the present study was the identification of gene loci that contribute to the development and manifestation of behaviours related to acute and chronic alcohol exposure, as well as to alcohol withdrawal. For this purpose, we performed a serial behavioural phenotyping of 534 animals from the second filial (F2) generation of a C57BL/6J and C3H/HeJ mice intercross in paradigms with relevance to alcohol dependence. First, ethanol-induced hypothermia was determined in ethanol-naive animals. The mice then received an ethanol solution for several weeks as their only fluid source. Ethanol tolerance, locomotor activity and anxiety-related behaviours were evaluated. The ethanol was next withdrawn and the withdrawal severity was assessed. The ethanol-experienced animals were finally analysed in a two-bottle choice paradigm to determine ethanol preference and stress-induced changes in ethanol preference. The genotypes of these mice were subsequently assessed by microsatellite marker mapping. We genotyped 264 markers with an average marker distance of 5.56 cM, which represents a high-density whole genome coverage. Quantitative trait loci (QTL) were subsequently identified using univariate analysis performed with the R/qtl tool, which is an extensible, interactive environment for mapping QTL in experimental crosses. We found QTL that have already been published, thus validating the serial phenotyping protocol, and identified several novel loci. Our analysis demonstrates that the various responses to ethanol are regulated by independent groups of genes.

  17. Quantitative trait loci mapping and gene network analysis implicate protocadherin-15 as a determinant of brain serotonin transporter expression.

    Science.gov (United States)

    Ye, R; Carneiro, A M D; Han, Q; Airey, D; Sanders-Bush, E; Zhang, B; Lu, L; Williams, R; Blakely, R D

    2014-03-01

    Presynaptic serotonin (5-hydroxytryptamine, 5-HT) transporters (SERT) regulate 5-HT signaling via antidepressant-sensitive clearance of released neurotransmitter. Polymorphisms in the human SERT gene (SLC6A4) have been linked to risk for multiple neuropsychiatric disorders, including depression, obsessive-compulsive disorder and autism. Using BXD recombinant inbred mice, a genetic reference population that can support the discovery of novel determinants of complex traits, merging collective trait assessments with bioinformatics approaches, we examine phenotypic and molecular networks associated with SERT gene and protein expression. Correlational analyses revealed a network of genes that significantly associated with SERT mRNA levels. We quantified SERT protein expression levels and identified region- and gender-specific quantitative trait loci (QTLs), one of which associated with male midbrain SERT protein expression, centered on the protocadherin-15 gene (Pcdh15), overlapped with a QTL for midbrain 5-HT levels. Pcdh15 was also the only QTL-associated gene whose midbrain mRNA expression significantly associated with both SERT protein and 5-HT traits, suggesting an unrecognized role of the cell adhesion protein in the development or function of 5-HT neurons. To test this hypothesis, we assessed SERT protein and 5-HT traits in the Pcdh15 functional null line (Pcdh15(av-) (3J) ), studies that revealed a strong, negative influence of Pcdh15 on these phenotypes. Together, our findings illustrate the power of multidimensional profiling of recombinant inbred lines in the analysis of molecular networks that support synaptic signaling, and that, as in the case of Pcdh15, can reveal novel relationships that may underlie risk for mental illness. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

  18. 'MN1606SP' by 'Spencer' filial soybean population reveals novel quantitative trait loci and interactions among loci conditioning SDS resistance.

    Science.gov (United States)

    Luckew, Alexander S; Swaminathan, Sivakumar; Leandro, Leonor F; Orf, James H; Cianzio, Silvia R

    2017-10-01

    Four novel QTL and interactions among QTL were identified in this research, using as a parent line the most SDS-resistant genotype within soybean cultivars of the US early maturity groups. Soybean sudden death syndrome (SDS) reduces soybean yield in most of the growing areas of the world. The causal agent of SDS, soilborne fungus Fusarium virguliforme (Fv), releases phytotoxins taken up by the plant to produce chlorosis and necrosis in the leaves. Planting resistant cultivars is the most successful management practice to control the disease. The objective of this study was to identify quantitative trait loci (QTL) associated with the resistance response of MN1606SP to SDS. A mapping population of F 2:3 lines created by crossing the highly resistant cultivar 'MN1606SP' and the susceptible cultivar 'Spencer' was phenotyped in the greenhouse at three different planting times, each with three replications. Plants were artificially inoculated using SDS infested sorghum homogeneously mixed with the soil. Data were collected on three disease criteria, foliar disease incidence (DI), foliar leaf scorch disease severity (DS), and root rot severity. Disease index (DX) was calculated as DI × DS. Ten QTL were identified for the different disease assessment criteria, three for DI, four for DX, and three for root rot severity. Three QTL identified for root rot severity and one QTL for disease incidence are considered novel, since no previous reports related to these QTL are available. Among QTL, two interactions were detected between four different QTL. The interactions suggest that resistance to SDS is not only dependent on additive gene effects. The novel QTL and the interactions observed in this study will be useful to soybean breeders for improvement of SDS resistance in soybean germplasm.

  19. A genome-wide association study identifies protein quantitative trait loci (pQTLs.

    Directory of Open Access Journals (Sweden)

    David Melzer

    2008-05-01

    locations. The identification of protein quantitative trait loci (pQTLs may be a powerful complementary method of improving our understanding of disease pathways.

  20. Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

    Science.gov (United States)

    Yap, John Stephen; Fan, Jianqing; Wu, Rongling

    2009-12-01

    Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

  1. Genetic and Molecular Mechanisms of Quantitative Trait Loci Controlling Maize Inflorescence Architecture.

    Science.gov (United States)

    Li, Manfei; Zhong, Wanshun; Yang, Fang; Zhang, Zuxin

    2018-03-01

    The establishment of inflorescence architecture is critical for the reproduction of flowering plant species. The maize plant generates two types of inflorescences, the tassel and the ear, and their architectures have a large effect on grain yield and yield-related traits that are genetically controlled by quantitative trait loci (QTLs). Since ear and tassel architecture are deeply affected by the activity of inflorescence meristems, key QTLs and genes regulating meristematic activity have important impacts on inflorescence development and show great potential for optimizing grain yield. Isolation of yield trait-related QTLs is challenging, but these QTLs have direct application in maize breeding. Additionally, characterization and functional dissection of QTLs can provide genetic and molecular knowledge of quantitative variation in inflorescence architecture. In this review, we summarize currently identified QTLs responsible for the establishment of ear and tassel architecture and discuss the potential genetic control of four ear-related and four tassel-related traits. In recent years, several inflorescence architecture-related QTLs have been characterized at the gene level. We review the mechanisms of these characterized QTLs.

  2. Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

    Directory of Open Access Journals (Sweden)

    Ying Wu

    2013-03-01

    Full Text Available Genome-wide association studies (GWAS have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG, high-density lipoprotein cholesterol (HDL-C, and low-density lipoprotein cholesterol (LDL-C, respectively, in individuals of African American (n = 6,832, East Asian (n = 9,449, and European (n = 10,829 ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4 in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

  3. Genomic Regions Influencing Seminal Root Traits in Barley

    Directory of Open Access Journals (Sweden)

    Hannah Robinson

    2016-03-01

    Full Text Available Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley ( L.. Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH population (ND24260 × ‘Flagship’ comprising 330 lines genotyped with diversity array technology (DArT markers were evaluated for seminal root angle (deviation from vertical and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL for seminal root traits (root angle, two QTL; root number, five QTL were detected in the DH population. A major QTL influencing both root angle and root number (/ was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat ( L., and sorghum [ (L. Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

  4. Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

    DEFF Research Database (Denmark)

    Ansari-Mahyari, S; Berg, P; Lund, M S

    2009-01-01

    In fine mapping of a large-scale experimental population where collection of phenotypes are very expensive, difficult to record or time-demanding, selective phenotyping could be used to phenotype the most informative individuals. Linkage analyses based sampling criteria (LAC) and linkage...... disequilibrium-based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals...... the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However...

  5. Quantitative trait loci mapping of genome regions controlling permethrin resistance in the mosquito Aedes aegypti.

    Science.gov (United States)

    Saavedra-Rodriguez, Karla; Strode, Clare; Flores Suarez, Adriana; Fernandez Salas, Ildefonso; Ranson, Hilary; Hemingway, Janet; Black, William C

    2008-10-01

    The mosquito Aedes aegypti is the principal vector of dengue and yellow fever flaviviruses. Permethrin is an insecticide used to suppress Ae. aegypti adult populations but metabolic and target site resistance to pyrethroids has evolved in many locations worldwide. Quantitative trait loci (QTL) controlling permethrin survival in Ae. aegypti were mapped in an F(3) advanced intercross line. Parents came from a collection of mosquitoes from Isla Mujeres, México, that had been selected for permethrin resistance for two generations and a reference permethrin-susceptible strain originally from New Orleans. Following a 1-hr permethrin exposure, 439 F(3) adult mosquitoes were phenotyped as knockdown resistant, knocked down/recovered, or dead. For QTL mapping, single nucleotide polymorphisms (SNPs) were identified at 22 loci with potential antixenobiotic activity including genes encoding cytochrome P450s (CYP), esterases (EST), or glutathione transferases (GST) and at 12 previously mapped loci. Seven antixenobiotic genes mapped to chromosome I, six to chromosome II, and nine to chromosome III. Two QTL of major effect were detected on chromosome III. One corresponds with a SNP previously associated with permethrin resistance in the para sodium channel gene and the second with the CCEunk7o esterase marker. Additional QTL but of relatively minor effect were also found. These included two sex-linked QTL on chromosome I affecting knockdown and recovery and a QTL affecting survival and recovery. On chromosome II, one QTL affecting survival and a second affecting recovery were detected. The patterns confirm that mutations in the para gene cause target-site insensitivity and are the major source of permethrin resistance but that other genes dispersed throughout the genome contribute to recovery and survival of mosquitoes following permethrin exposure.

  6. Identification of quantitative trait loci for growth and carcass composition in cattle.

    Science.gov (United States)

    Casas, E; Keele, J W; Shackelford, S D; Koohmaraie, M; Stone, R T

    2004-02-01

    A genomic screening to detect quantitative trait loci (QTL) affecting growth, carcass composition and meat quality traits was pursued. Two hundred nineteen microsatellite markers were genotyped on 176 of 620 (28%) progeny from a Brahman x Angus sire mated to mostly MARC III dams. Selective genotyping, based on retail product yield (%) and fat yield (%), was used to select individuals to be genotyped. Traits included in the study were birth weight (kg), hot carcass weight (kg), retail product yield, fat yield, marbling score (400 = slight00 and 500 = small00), USDA yield grade, and estimated kidney, heart and pelvic fat (%). The QTL were classified as significant when the expected number of false positives (ENFP) was less than 0.05 (F-statistic greater than 17.3), and suggestive when the ENFP was ENFP = 0.02) was detected for marbling score at centimorgan (cM) 54 on chromosome 2. Suggestive QTL were detected for fat yield at 50 cM, for retail product yield at 53 cM, and for USDA yield grade at 63 cM on chromosome 1, for marbling score at 56 cM, for retail product yield at 70 cM, and for estimated kidney, heart and pelvic fat at 79 cM on chromosome 3, for marbling score at 44 cM, for hot carcass weight at 49 cM, and for estimated kidney, heart and pelvic fat at 62 cM on chromosome 16, and for fat yield at 35 cM on chromosome 17. Two suggestive QTL for birth weight were identified, one at 12 cM on chromosome 20 and the other at 56 cM on chromosome 21. An additional suggestive QTL was detected for retail product yield, for fat yield, and for USDA yield grade at 26 cM on chromosome 26. Results presented here represent the initial search for quantitative trait loci in this family. Validation of detected QTL in other populations will be necessary.

  7. The first genetic map of the American cranberry: exploration of synteny conservation and quantitative trait loci.

    Science.gov (United States)

    Georgi, Laura; Johnson-Cicalese, Jennifer; Honig, Josh; Das, Sushma Parankush; Rajah, Veeran D; Bhattacharya, Debashish; Bassil, Nahla; Rowland, Lisa J; Polashock, James; Vorsa, Nicholi

    2013-03-01

    The first genetic map of cranberry (Vaccinium macrocarpon) has been constructed, comprising 14 linkage groups totaling 879.9 cM with an estimated coverage of 82.2 %. This map, based on four mapping populations segregating for field fruit-rot resistance, contains 136 distinct loci. Mapped markers include blueberry-derived simple sequence repeat (SSR) and cranberry-derived sequence-characterized amplified region markers previously used for fingerprinting cranberry cultivars. In addition, SSR markers were developed near cranberry sequences resembling genes involved in flavonoid biosynthesis or defense against necrotrophic pathogens, or conserved orthologous set (COS) sequences. The cranberry SSRs were developed from next-generation cranberry genomic sequence assemblies; thus, the positions of these SSRs on the genomic map provide information about the genomic location of the sequence scaffold from which they were derived. The use of SSR markers near COS and other functional sequences, plus 33 SSR markers from blueberry, facilitates comparisons of this map with maps of other plant species. Regions of the cranberry map were identified that showed conservation of synteny with Vitis vinifera and Arabidopsis thaliana. Positioned on this map are quantitative trait loci (QTL) for field fruit-rot resistance (FFRR), fruit weight, titratable acidity, and sound fruit yield (SFY). The SFY QTL is adjacent to one of the fruit weight QTL and may reflect pleiotropy. Two of the FFRR QTL are in regions of conserved synteny with grape and span defense gene markers, and the third FFRR QTL spans a flavonoid biosynthetic gene.

  8. Mapping Quantitative Trait Loci affecting biochemical and morphological fruit properties in eggplant (Solanum melongena L.

    Directory of Open Access Journals (Sweden)

    Laura eToppino

    2016-03-01

    Full Text Available Eggplant berries are a source of health-promoting metabolites including antioxidant and nutraceutical compounds, mainly anthocyanins and chlorogenic acid; however, they also contain some anti-nutritional compounds such as steroidal glycoalkaloids (SGA and saponins, which are responsible for the bitter taste of the flesh and with potential toxic effects on humans. Up to now, Quantitative Trait Loci (QTL for the metabolic content are far from being characterized in eggplant, thus hampering the application of breeding programs aimed at improving its fruit quality. Here we report on the identification of some QTL for the fruit metabolic content in an F2 intraspecific mapping population of 156 individuals, obtained by crossing the eggplant breeding lines ‘305E40’ x ‘67/3’. The same population was previously employed for the development of a RAD-tag based linkage map and the identification of QTL associated to morphological and physiological traits. The mapping population was biochemically characterized for both fruit basic qualitative data, like dry matter, °Brix, sugars and organic acids, as well as for health-related compounds such chlorogenic acid, (the main flesh monomeric phenol, the two peel anthocyanins (i.e. delphinidin-3-rutinoside (D3R and delphinidin-3-(p-coumaroylrutinoside-5-glucoside (nasunin and the two main steroidal glycoalkaloids, solasonine and solamargine. For most of the traits, one major QTL (PVE ≥ 10% was spotted and putative orthologies with other Solanaceae crops are discussed. The present results supply valuable information to eggplant breeders on the inheritance of key fruit quality traits, thus providing potential tools to assist future breeding programs.

  9. Quantitative trait loci mapping reveals candidate pathways regulating cell cycle duration in Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Siwo Geoffrey

    2010-10-01

    Full Text Available Abstract Background Elevated parasite biomass in the human red blood cells can lead to increased malaria morbidity. The genes and mechanisms regulating growth and development of Plasmodium falciparum through its erythrocytic cycle are not well understood. We previously showed that strains HB3 and Dd2 diverge in their proliferation rates, and here use quantitative trait loci mapping in 34 progeny from a cross between these parent clones along with integrative bioinformatics to identify genetic loci and candidate genes that control divergences in cell cycle duration. Results Genetic mapping of cell cycle duration revealed a four-locus genetic model, including a major genetic effect on chromosome 12, which accounts for 75% of the inherited phenotype variation. These QTL span 165 genes, the majority of which have no predicted function based on homology. We present a method to systematically prioritize candidate genes using the extensive sequence and transcriptional information available for the parent lines. Putative functions were assigned to the prioritized genes based on protein interaction networks and expression eQTL from our earlier study. DNA metabolism or antigenic variation functional categories were enriched among our prioritized candidate genes. Genes were then analyzed to determine if they interact with cyclins or other proteins known to be involved in the regulation of cell cycle. Conclusions We show that the divergent proliferation rate between a drug resistant and drug sensitive parent clone is under genetic regulation and is segregating as a complex trait in 34 progeny. We map a major locus along with additional secondary effects, and use the wealth of genome data to identify key candidate genes. Of particular interest are a nucleosome assembly protein (PFL0185c, a Zinc finger transcription factor (PFL0465c both on chromosome 12 and a ribosomal protein L7Ae-related on chromosome 4 (PFD0960c.

  10. CBCL pediatric bipolar disorder profile and ADHD: comorbidity and quantitative trait loci analysis.

    Science.gov (United States)

    McGough, James J; Loo, Sandra K; McCracken, James T; Dang, Jeffrey; Clark, Shaunna; Nelson, Stanley F; Smalley, Susan L

    2008-10-01

    The pediatric bipolar disorder profile of the Child Behavior Checklist (CBCL-PBD), a parent-completed measure that avoids clinician ideological bias, has proven useful in differentiating patients with attention-deficit/hyperactivity disorder (ADHD). We used CBCL-PBD profiles to distinguish patterns of comorbidity and to search for quantitative trait loci in a genomewide scan in a sample of multiple affected ADHD sibling pairs. A total of 540 ADHD subjects ages 5 to 18 years were assessed with the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version and CBCL. Parents were assessed with the Schedule for Affective Disorders and Schizophrenia-Lifetime version supplemented by the Schedule for Affective Disorders and Schizophrenia for School-Age Children for disruptive behavioral disorders. Patterns of psychiatric comorbidity were contrasted based on the CBCL-PBD profile. A quantitative trait loci variance component analysis was used to identify potential genomic regions that may harbor susceptibility genes for the CBCL-PBD quantitative phenotype. Bipolar spectrum disorders represented less than 2% of the overall sample. The CBCL-PBD classification was associated with increased generalized anxiety disorder (p =.001), oppositional defiant disorder (p =.008), conduct disorder (p =.003), and parental substance abuse (p =.005). A moderately significant linkage signal (multipoint maximum lod score = 2.5) was found on chromosome 2q. The CBCL-PBD profile distinguishes a subset of ADHD patients with significant comorbidity. Linkage analysis of the CBCL-PBD phenotype suggests certain genomic regions that merit further investigation for genes predisposing to severe psychopathology.

  11. Identification of QTL and Qualitative Trait Loci for Agronomic Traits Using SNP Markers in the Adzuki Bean.

    Science.gov (United States)

    Li, Yuan; Yang, Kai; Yang, Wei; Chu, Liwei; Chen, Chunhai; Zhao, Bo; Li, Yisong; Jian, Jianbo; Yin, Zhichao; Wang, Tianqi; Wan, Ping

    2017-01-01

    The adzuki bean ( Vigna angularis ) is an important grain legume. Fine mapping of quantitative trait loci (QTL) and qualitative trait genes plays an important role in gene cloning, molecular-marker-assisted selection (MAS), and trait improvement. However, the genetic control of agronomic traits in the adzuki bean remains poorly understood. Single-nucleotide polymorphisms (SNPs) are invaluable in the construction of high-density genetic maps. We mapped 26 agronomic QTLs and five qualitative trait genes related to pigmentation using 1,571 polymorphic SNP markers from the adzuki bean genome via restriction-site-associated DNA sequencing of 150 members of an F 2 population derived from a cross between cultivated and wild adzuki beans. We mapped 11 QTLs for flowering time and pod maturity on chromosomes 4, 7, and 10. Six 100-seed weight (SD100WT) QTLs were detected. Two major flowering time QTLs were located on chromosome 4, firstly VaFld4.1 (PEVs 71.3%), co-segregating with SNP marker s690-144110, and VaFld4.2 (PEVs 67.6%) at a 0.974 cM genetic distance from the SNP marker s165-116310. Three QTLs for seed number per pod ( Snp3.1, Snp3.2 , and Snp4.1 ) were mapped on chromosomes 3 and 4. One QTL VaSdt4.1 of seed thickness (SDT) and three QTLs for branch number on the main stem were detected on chromosome 4. QTLs for maximum leaf width (LFMW) and stem internode length were mapped to chromosomes 2 and 9, respectively. Trait genes controlling the color of the seed coat, pod, stem and flower were mapped to chromosomes 3 and 1. Three candidate genes, VaAGL, VaPhyE , and VaAP2 , were identified for flowering time and pod maturity. VaAGL encodes an agamous-like MADS-box protein of 379 amino acids. VaPhyE encodes a phytochrome E protein of 1,121 amino acids. Four phytochrome genes ( VaPhyA1, VaPhyA2, VaPhyB , and VaPhyE ) were identified in the adzuki bean genome. We found candidate genes VaAP2/ERF.81 and VaAP2/ERF.82 of SD100WT, VaAP2-s4 of SDT, and VaAP2/ERF.86 of LFMW. A

  12. Construction of a genetic linkage map and analysis of quantitative trait loci associated with the agronomically important traits of Pleurotus eryngii

    Science.gov (United States)

    Chak Han Im; Young-Hoon Park; Kenneth E. Hammel; Bokyung Park; Soon Wook Kwon; Hojin Ryu; Jae-San Ryu

    2016-01-01

    Breeding new strains with improved traits is a long-standing goal of mushroom breeders that can be expedited by marker-assisted selection (MAS). We constructed a genetic linkage map of Pleurotus eryngii based on segregation analysis of markers in postmeiotic monokaryons from KNR2312. In total, 256 loci comprising 226 simple sequence-repeat (SSR) markers, 2 mating-type...

  13. A Genome Scan to Detect Quantitative Trait Loci for Economically Important Traits in Holstein Cattle Using Two Methods and a Dense Single Nucleotide Polymorphism Map

    NARCIS (Netherlands)

    Daetwyler, H.D.; Schenkel, F.S.; Sargolzaei, M.; Robinson, J.A.B.

    2008-01-01

    Genome scans for detection of bovine quantitative trait loci (QTL) were performed via variance component linkage analysis and linkage disequilibrium single-locus regression (LDRM). Four hundred eighty-four Holstein sires, of which 427 were from 10 grandsire families, were genotyped for 9,919 single

  14. Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz).

    Science.gov (United States)

    Thanyasiriwat, T; Sraphet, S; Whankaew, S; Boonseng, O; Bao, J; Lightfoot, D A; Tangphatsornruang, S; Triwitayakorn, K

    2014-01-01

    Starch pasting viscosity is an important quality trait in cassava (Manihot esculenta Crantz) cultivars. The aim here was to identify loci and candidate genes associated with the starch pasting viscosity. Quantitative trait loci (QTL) mapping for seven pasting viscosity parameters was carried out using 100 lines of an F1 mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee. Starch samples were obtained from roots of cassava grown in 2008 and 2009 at Rayong, and in 2009 at Lop Buri province, Thailand. The traits showed continuous distribution among the F1 progeny with transgressive variation. Fifteen QTL were identified from mean trait data, with Logarithm of Odds (LOD) values from 2.77-13.01 and phenotype variations explained (PVE) from10.0-48.4%. In addition, 48 QTL were identified in separate environments. The LOD values ranged from 2.55-8.68 and explained 6.6-43.7% of phenotype variation. The loci were located on 19 linkage groups. The most important QTL for pasting temperature (PT) (qPT.1LG1) from mean trait values showed largest effect with highest LOD value (13.01) and PVE (48.4%). The QTL co-localised with PT and pasting time (PTi) loci that were identified in separate environments. Candidate genes were identified within the QTL peak regions. However, the major genes of interest, encoding the family of glycosyl or glucosyl transferases and hydrolases, were located at the periphery of QTL peaks. The loci identified could be effectively applied in breeding programmes to improve cassava starch quality. Alleles of candidate genes should be further studied in order to better understand their effects on starch quality traits. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

  15. Mapping quantitative trait loci controlling early growth in a (longleaf pine × slash pine) × slash pine BC1 family

    Science.gov (United States)

    C. Weng; Thomas L. Kubisiak; C. Dana. Nelson; M. Stine

    2002-01-01

    Random amplified polymorphic DNA (RAPD) markers were employed to map the genome and quantitative trait loci controlling the early growth of a pine hybrid F1 tree (Pinus palustris Mill. × P. elliottii Engl.) and a recurrent slash pine tree (P. ellottii Engl.) in a (longleaf pine × slash pine...

  16. Quantitative trait loci for tibial bone strength in C57BL/6J and C3H ...

    Indian Academy of Sciences (India)

    Abstract. Three-point bending technology has been widely used in the measurement of bone strength. Quantitative trait loci (QTLs) for ... mapping was conducted using Map Manager QTX software. Data show that (i) both elastic modulus ... will provide a wealth of information for the understanding of genetics of osteoporosis.

  17. Mapping of quantitative trait loci associated with partial resistance to phytophthora sojae and flooding tolerance in soybean

    Science.gov (United States)

    Phytophthora root rot (PRR) caused by Phytophthora sojae Kaufm. & Gerd. and flooding can limit growth and productivity, of soybean [Glycine max (L.) Merr.], especially on poorly drained soils. The primary objective of this research project was to map quantitative trait loci (QTL) associated with f...

  18. Quantitative trait loci analysis of flowering time related traits identified in recombinant inbred lines of cowpea (Vigna unguiculata).

    Science.gov (United States)

    Andargie, Mebeasealassie; Pasquet, Remy S; Muluvi, Geoffrey M; Timko, Michael P

    2013-05-01

    Flowering time is a major adaptive trait in plants and an important selection criterion in the breeding for genetic improvement of crop species. QTLs for the time of flower opening and days to flower were identified in a cross between a short duration domesticated cowpea (Vigna unguiculata (L.) Walp.) variety, 524B, and a relatively long duration wild accession, 219-01. A set of 159 F7 lines was grown under greenhouse conditions and scored for the flowering time associated phenotypes of time of flower opening and days to flower. Using a LOD threshold of 2.0, putative QTLs were identified and placed on a linkage map consisting of 202 SSR markers and four morphological loci. A total of five QTLs related to the time of flower opening were identified, accounting for 8.8%-29.8% of the phenotypic variation. Three QTLs for days to flower were detected, accounting for 5.7%-18.5% of the phenotypic variation. The major QTL of days to flower and time of flower opening were both mapped on linkage group 1. The QTLs identified in this study provide a strong foundation for further validation and fine mapping for developing an efficient way to restrain the gene flow between the cultivated and wild plants.

  19. Mapping of imprinted quantitative trait loci using immortalized F2 populations.

    Directory of Open Access Journals (Sweden)

    Yongxian Wen

    Full Text Available Mapping of imprinted quantitative trait loci (iQTLs is helpful for understanding the effects of genomic imprinting on complex traits in animals and plants. At present, the experimental designs and corresponding statistical methods having been proposed for iQTL mapping are all based on temporary populations including F2 and BC1, which can be used only once and suffer some other shortcomings respectively. In this paper, we propose a framework for iQTL mapping, including methods of interval mapping (IM and composite interval mapping (CIM based on conventional low-density genetic maps and point mapping (PM and composite point mapping (CPM based on ultrahigh-density genetic maps, using an immortalized F2 (imF2 population generated by random crosses between recombinant inbred lines or doubled haploid lines. We demonstrate by simulations that imF2 populations are very desirable and the proposed statistical methods (especially CIM and CPM are very powerful for iQTL mapping, with which the imprinting effects as well as the additive and dominance effects of iQTLs can be unbiasedly estimated.

  20. A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

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    Jing Qian

    Full Text Available Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs.We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT, to identify protein-coding gene association with 14 cardiometabolic (CMD related traits across 6 publicly available genome wide association (GWA meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1.We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes.We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and

  1. The identification of loci for immune traits in chickens using a genome-wide association study.

    Science.gov (United States)

    Zhang, Lei; Li, Peng; Liu, Ranran; Zheng, Maiqing; Sun, Yan; Wu, Dan; Hu, Yaodong; Wen, Jie; Zhao, Guiping

    2015-01-01

    The genetic improvement of disease resistance in poultry continues to be a challenge. To identify candidate genes and loci responsible for these traits, genome-wide association studies using the chicken 60k high density single nucleotide polymorphism (SNP) array for six immune traits, total serum immunoglobulin Y (IgY) level, numbers of, and the ratio of heterophils and lymphocytes, and antibody responses against Avian Influenza Virus (AIV) and Sheep Red Blood Cell (SRBC), were performed. RT-qPCR was used to quantify the relative expression of the identified candidate genes. Nine significantly associated SNPs (P IL4I1, CD1b, GNB2L1, TRIM27 and ZNF692) located in this region, changes in IL4I1, CD1b transcripts were consistent with the concentrations of IgY, while abundances of TRIM27 and ZNF692 showed reciprocal changes to those of IgY concentrations. This study has revealed 39 SNPs associated with six immune traits (total serum IgY level, numbers of, and the ratio of heterophils and lymphocytes, and antibody responses against AIV and SRBC) in Beijing-You chickens. The narrow region spanning 247kb on chromosome 16 is an important QTL for serum total IgY concentration. Five candidate genes related to IgY level validated here are novel and may play critical roles in the modulation of immune responses. Potentially useful candidate SNPs for marker-assisted selection for disease resistance are identified. It is highly likely that these candidate genes play roles in various aspects of the immune response in chickens.

  2. Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

    Science.gov (United States)

    Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

    2015-12-01

    Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

  3. [Influence of personality traits on collage works].

    Science.gov (United States)

    Miyazawa, Shiho

    2004-10-01

    The present study investigated whether personality traits may influence the outcome of collage works. In this study, 60 undergraduates were asked to fill Revised NEO Personality Inventory (NEO-PI-R) and generate collage works. The relations between the five factors of the NEO-PI-R (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness) and some evaluation measures of collage works (constructional features of collage works and characteristic behavior patterns in the process of their generation) were examined. Results indicated that several subscales of personality traits were substantially correlated with some indices of both two measures. These findings suggest that collage work may be a useful tool for psychological assessment.

  4. Multiple Linkage Disequilibrium Mapping Methods to Validate Additive Quantitative Trait Loci in Korean Native Cattle (Hanwoo

    Directory of Open Access Journals (Sweden)

    Yi Li

    2015-07-01

    Full Text Available The efficiency of genome-wide association analysis (GWAS depends on power of detection for quantitative trait loci (QTL and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM, a combined linkage and linkage disequilibrium analysis (LDLA and a BayesCπ approach. The phenotypes of 486 steers were collected for weaning weight (WWT, yearling weight (YWT, carcass weight (CWT, backfat thickness (BFT, longissimus dorsi muscle area, and marbling score (Marb. Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX] may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

  5. Quantitative trait loci for mercury accumulation in maize (Zea mays L. identified using a RIL population.

    Directory of Open Access Journals (Sweden)

    Zhongjun Fu

    Full Text Available To investigate the genetic mechanism of mercury accumulation in maize (Zea mays L., a population of 194 recombinant inbred lines derived from an elite hybrid Yuyu 22, was used to identify quantitative trait loci (QTLs for mercury accumulation at two locations. The results showed that the average Hg concentration in the different tissues of maize followed the order: leaves > bracts > stems > axis > kernels. Twenty-three QTLs for mercury accumulation in five tissues were detected on chromosomes 1, 4, 7, 8, 9 and 10, which explained 6.44% to 26.60% of the phenotype variance. The QTLs included five QTLs for Hg concentration in kernels, three QTLs for Hg concentration in the axis, six QTLs for Hg concentration in stems, four QTLs for Hg concentration in bracts and five QTLs for Hg concentration in leaves. Interestingly, three QTLs, qKHC9a, qKHC9b, and qBHC9 were in linkage with two QTLs for drought tolerance. In addition, qLHC1 was in linkage with two QTLs for arsenic accumulation. The study demonstrated the concentration of Hg in Hg-contaminated paddy soil could be reduced, and maize production maintained simultaneously by selecting and breeding maize Hg pollution-safe cultivars (PSCs.

  6. Quantitative trait loci for a neurocranium deformity, lack of operculum, in gilthead seabream (Sparus aurata L.).

    Science.gov (United States)

    Negrín-Báez, D; Navarro, A; Afonso, J M; Toro, M A; Zamorano, M J

    2016-04-01

    Lack of operculum, a neurocranial deformity, is the most common external abnormality to be found among industrially produced gilthead seabream (Sparus aurata L.), and this entails significant financial losses. This study conducts, for the first time in this species, a quantitative trait loci (QTL) analysis of the lack of operculum. A total of 142 individuals from a paternal half-sibling family (six full-sibling families) were selected for QTL mapping. They had previously shown a highly significant association with the prevalence of lack of operculum in a segregation analysis. All the fish were genotyped for 106 microsatellite markers using a set of multiplex PCRs (ReMsa1-ReMsa13). A linear regression methodology was used for the QTL analysis. Four QTL were detected for this deformity, two of which (QTLOP1 and QTLOP2) were significant. They were located at LG (linkage group) nine and LG10 respectively. Both QTL showed a large effect (about 27%), and furthermore, the association between lack of operculum and sire allelic segregation observed was statistically significant in the QTLOP1 analysis. These results represent a significant step towards including marker-assisted selection for this deformity in genetic breeding programmes to reduce the incidence of the deformity in the species. © 2016 Stichting International Foundation for Animal Genetics.

  7. Genome-wide quantitative trait loci mapping of the human cerebrospinal fluid proteome.

    Science.gov (United States)

    Sasayama, Daimei; Hattori, Kotaro; Ogawa, Shintaro; Yokota, Yuuki; Matsumura, Ryo; Teraishi, Toshiya; Hori, Hiroaki; Ota, Miho; Yoshida, Sumiko; Kunugi, Hiroshi

    2017-01-01

    Cerebrospinal fluid (CSF) is virtually the only one accessible source of proteins derived from the central nervous system (CNS) of living humans and possibly reflects the pathophysiology of a variety of neuropsychiatric diseases. However, little is known regarding the genetic basis of variation in protein levels of human CSF. We examined CSF levels of 1,126 proteins in 133 subjects and performed a genome-wide association analysis of 514,227 single nucleotide polymorphisms (SNPs) to detect protein quantitative trait loci (pQTLs). To be conservative, Spearman's correlation was used to identify an association between genotypes of SNPs and protein levels. A total of 421 cis and 25 trans SNP-protein pairs were significantly correlated at a false discovery rate (FDR) of less than 0.01 (nominal P genome-wide association studies. The present findings suggest that genetic variations play an important role in the regulation of protein expression in the CNS. The obtained database may serve as a valuable resource to understand the genetic bases for CNS protein expression pattern in humans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Fine Mapping of QUICK ROOTING 1 and 2, Quantitative Trait Loci Increasing Root Length in Rice

    Directory of Open Access Journals (Sweden)

    Yuka Kitomi

    2018-02-01

    Full Text Available The volume that the root system can occupy is associated with the efficiency of water and nutrient uptake from soil. Genetic improvement of root length, which is a limiting factor for root distribution, is necessary for increasing crop production. In this report, we describe identification of two quantitative trait loci (QTLs for maximal root length, QUICK ROOTING 1 (QRO1 on chromosome 2 and QRO2 on chromosome 6, in cultivated rice (Oryza sativa L.. We measured the maximal root length in 26 lines carrying chromosome segments from the long-rooted upland rice cultivar Kinandang Patong in the genetic background of the short-rooted lowland cultivar IR64. Five lines had longer roots than IR64. By rough mapping of the target regions in BC4F2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC4F3 recombinant homozygous lines. QRO1 was mapped between markers RM5651 and RM6107, which delimit a 1.7-Mb interval on chromosome 2, and QRO2 was mapped between markers RM20495 and RM3430-1, which delimit an 884-kb interval on chromosome 6. Both QTLs may be promising gene resources for improving root system architecture in rice.

  9. The identification of loci for immune traits in chickens using a genome-wide association study.

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    Full Text Available The genetic improvement of disease resistance in poultry continues to be a challenge. To identify candidate genes and loci responsible for these traits, genome-wide association studies using the chicken 60k high density single nucleotide polymorphism (SNP array for six immune traits, total serum immunoglobulin Y (IgY level, numbers of, and the ratio of heterophils and lymphocytes, and antibody responses against Avian Influenza Virus (AIV and Sheep Red Blood Cell (SRBC, were performed. RT-qPCR was used to quantify the relative expression of the identified candidate genes. Nine significantly associated SNPs (P < 2.81E-06 and 30 SNPs reaching the suggestively significant level (P < 5.62E-05 were identified. Five of the 10 SNPs that were suggestively associated with the antibody response to SRBC were located within or close to previously reported QTL regions. Fifteen SNPs reached a suggestive significance level for AIV antibody titer and seven were found on the sex chromosome Z. Seven suggestive markers involving five different SNPs were identified for the numbers of heterophils and lymphocytes, and the heterophil/lymphocyte ratio. Nine significant SNPs, all on chromosome 16, were significantly associated with serum total IgY concentration, and the five most significant were located within a narrow region spanning 6.4kb to 253.4kb (P = 1.20E-14 to 5.33E-08. After testing expression of five candidate genes (IL4I1, CD1b, GNB2L1, TRIM27 and ZNF692 located in this region, changes in IL4I1, CD1b transcripts were consistent with the concentrations of IgY, while abundances of TRIM27 and ZNF692 showed reciprocal changes to those of IgY concentrations. This study has revealed 39 SNPs associated with six immune traits (total serum IgY level, numbers of, and the ratio of heterophils and lymphocytes, and antibody responses against AIV and SRBC in Beijing-You chickens. The narrow region spanning 247kb on chromosome 16 is an important QTL for serum total Ig

  10. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat

    Science.gov (United States)

    Maccaferri, Marco; El-Feki, Walid; Nazemi, Ghasemali; Salvi, Silvio; Canè, Maria Angela; Colalongo, Maria Chiara; Stefanelli, Sandra; Tuberosa, Roberto

    2016-01-01

    Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs. PMID:26880749

  11. Prioritizing quantitative trait loci for root system architecture in tetraploid wheat.

    Science.gov (United States)

    Maccaferri, Marco; El-Feki, Walid; Nazemi, Ghasemali; Salvi, Silvio; Canè, Maria Angela; Colalongo, Maria Chiara; Stefanelli, Sandra; Tuberosa, Roberto

    2016-02-01

    Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  12. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

    Directory of Open Access Journals (Sweden)

    Jingjing Liang

    2017-05-01

    Full Text Available Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8 for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4 and multiple-trait analyses identified one novel locus (FRMD3 for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

  13. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations

    OpenAIRE

    Liang, Jingjing; Le, Thu H.; Edwards, Digna R. Velez; Tayo, Bamidele O.; Gaulton, Kyle J.; Smith, Jennifer A.; Lu, Yingchang; Jensen, Richard A.; Chen, Guanjie; Yanek, Lisa R.; Schwander, Karen; Tajuddin, Salman M.; Sofer, Tamar; Kim, Wonji; Kayima, James

    2017-01-01

    © 2017 Public Library of Science. All Rights Reserved. Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genom...

  14. Systems genetics of liver fibrosis: identification of fibrogenic and expression quantitative trait loci in the BXD murine reference population.

    Directory of Open Access Journals (Sweden)

    Rabea A Hall

    Full Text Available The progression of liver fibrosis in response to chronic injury varies considerably among individual patients. The underlying genetics is highly complex due to large numbers of potential genes, environmental factors and cell types involved. Here, we provide the first toxicogenomic analysis of liver fibrosis induced by carbon tetrachloride in the murine 'genetic reference panel' of recombinant inbred BXD lines. Our aim was to define the core of risk genes and gene interaction networks that control fibrosis progression. Liver fibrosis phenotypes and gene expression profiles were determined in 35 BXD lines. Quantitative trait locus (QTL analysis identified seven genomic loci influencing fibrosis phenotypes (pQTLs with genome-wide significance on chromosomes 4, 5, 7, 12, and 17. Stepwise refinement was based on expression QTL mapping with stringent selection criteria, reducing the number of 1,351 candidate genes located in the pQTLs to a final list of 11 cis-regulated genes. Our findings demonstrate that the BXD reference population represents a powerful experimental resource for shortlisting the genes within a regulatory network that determine the liver's vulnerability to chronic injury.

  15. Genome-wide analysis identifies 12 loci influencing human reproductive behavior

    DEFF Research Database (Denmark)

    Barban, Nicola; Jansen, Rick; de Vlaming, Ronald

    2016-01-01

    The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified......-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits....

  16. Genetic mapping of quantitative trait loci for tuber-cadmium and zinc concentration in potato reveals associations with maturity and both overlapping and independent components of genetic control.

    Science.gov (United States)

    Mengist, Molla F; Alves, Sheila; Griffin, Denis; Creedon, Joanne; McLaughlin, Mike J; Jones, Peter W; Milbourne, Dan

    2018-04-01

    Cd is a toxic metal, whilst Zn is an essential for plant and human health. Both can accumulate in potato tubers. We examine the genetic control of this process. The aim of this study was to map quantitative trait loci (QTLs) influencing tuber concentrations of cadmium (Cd) and zinc (Zn). We developed a segregating population comprising 188 F 1 progeny derived from crossing two tetraploid cultivars exhibiting divergent tuber-Cd-accumulation phenotypes. These progeny were genotyped using the SolCap 8303 SNP array, and evaluated for Cd, Zn, and maturity-related traits. Linkage and QTL mapping were performed using TetraploidSNPMap software, which incorporates all allele dosage information. The final genetic map comprised 3755 SNP markers with average marker density of 2.94 per cM. Tuber-Cd and Zn concentrations were measured in the segregating population over 2 years. QTL mapping identified four loci for tuber-Cd concentration on chromosomes 3, 5, 6, and 7, which explained genetic variance ranging from 5 to 33%, and five loci for tuber-Zn concentration on chromosome 1, 3, 5, and, 6 explaining from 5 to 38% of genetic variance. Among the QTL identified for tuber-Cd concentration, three loci coincided with tuber-Zn concentration. The largest effect QTL for both tuber-Cd and Zn concentration coincided with the maturity locus on chromosome 5 where earliness was associated with increased tuber concentration of both metals. Coincident minor-effect QTL for Cd and Zn sharing the same direction of effect was also found on chromosomes 3 and 6, and these were unrelated to maturity The results indicate partially overlapping genetic control of tuber-Cd and Zn concentration in the cross, involving both maturity-related and non-maturity-related mechanisms.

  17. Quantitative trait loci for broomrape (Orobanche cumana Wallr.) resistance in sunflower.

    Science.gov (United States)

    Pérez-Vich, B; Akhtouch, B; Knapp, S J; Leon, A J; Velasco, L; Fernández-Martínez, J M; Berry, S T

    2004-06-01

    Broomrape (Orobanche cumana Wallr.) is a root parasite of sunflower that is regarded as one of the most important constraints of sunflower production in the Mediterranean region. Breeding for resistance is the most effective method of control. P-96 is a sunflower line which shows dominant resistance to broomrape race E and recessive resistance to the very new race F. The objective of this study was to map and characterize quantitative trait loci (QTL) for resistance to race E and to race F of broomrape in P-96. A population from a cross between P-96 and the susceptible line P-21 was phenotyped for broomrape resistance in four experiments, two for race E and two for race F, by measuring different resistance parameters (resistance or susceptibility, number of broomrape per plant, and proportion of resistant plants per F(3) family). This population was also genotyped with microsatellite and RFLP markers. A linkage map comprising 103 marker loci distributed on 17 linkage groups was developed, and composite interval mapping analyses were performed. In total, five QTL ( or1.1, or3.1, or7.1 or13.1 and or13.2) for resistance to race E and six QTL ( or1.1, or4.1, or5.1, or13.1, or13.2 and or16.1) for resistance to race F of broomrape were detected on 7 of the 17 linkage groups. Phenotypic variance for race E resistance was mainly explained by the major QTL or3.1 associated to the resistance or susceptibility character ( R(2)=59%), while race F resistance was explained by QTL with a small to moderate effect ( R(2) from 15.0% to 38.7%), mainly associated with the number of broomrape per plant. Or3.1 was race E-specific, while or1.1, or13.1 and or13.2 of were non-race specific. Or13.1, and or13.2 were stable across the four experiments. Or3.1, and or7.1 were stable over the two race E experiments and or1.1 and or5.1 over the two race F experiments. The results from this study suggest that resistance to broomrape in sunflower is controlled by a combination of qualitative, race

  18. High-throughput SNP genotyping in Cucurbita pepo for map construction and quantitative trait loci mapping.

    Science.gov (United States)

    Esteras, Cristina; Gómez, Pedro; Monforte, Antonio J; Blanca, José; Vicente-Dólera, Nelly; Roig, Cristina; Nuez, Fernando; Picó, Belén

    2012-02-22

    Cucurbita pepo is a member of the Cucurbitaceae family, the second- most important horticultural family in terms of economic importance after Solanaceae. The "summer squash" types, including Zucchini and Scallop, rank among the highest-valued vegetables worldwide. There are few genomic tools available for this species.The first Cucurbita transcriptome, along with a large collection of Single Nucleotide Polymorphisms (SNP), was recently generated using massive sequencing. A set of 384 SNP was selected to generate an Illumina GoldenGate assay in order to construct the first SNP-based genetic map of Cucurbita and map quantitative trait loci (QTL). We herein present the construction of the first SNP-based genetic map of Cucurbita pepo using a population derived from the cross of two varieties with contrasting phenotypes, representing the main cultivar groups of the species' two subspecies: Zucchini (subsp. pepo) × Scallop (subsp. ovifera). The mapping population was genotyped with 384 SNP, a set of selected EST-SNP identified in silico after massive sequencing of the transcriptomes of both parents, using the Illumina GoldenGate platform. The global success rate of the assay was higher than 85%. In total, 304 SNP were mapped, along with 11 SSR from a previous map, giving a map density of 5.56 cM/marker. This map was used to infer syntenic relationships between C. pepo and cucumber and to successfully map QTL that control plant, flowering and fruit traits that are of benefit to squash breeding. The QTL effects were validated in backcross populations. Our results show that massive sequencing in different genotypes is an excellent tool for SNP discovery, and that the Illumina GoldenGate platform can be successfully applied to constructing genetic maps and performing QTL analysis in Cucurbita. This is the first SNP-based genetic map in the Cucurbita genus and is an invaluable new tool for biological research, especially considering that most of these markers are located in

  19. High-throughput SNP genotyping in Cucurbita pepo for map construction and quantitative trait loci mapping

    Directory of Open Access Journals (Sweden)

    Esteras Cristina

    2012-02-01

    Full Text Available Abstract Background Cucurbita pepo is a member of the Cucurbitaceae family, the second- most important horticultural family in terms of economic importance after Solanaceae. The "summer squash" types, including Zucchini and Scallop, rank among the highest-valued vegetables worldwide. There are few genomic tools available for this species. The first Cucurbita transcriptome, along with a large collection of Single Nucleotide Polymorphisms (SNP, was recently generated using massive sequencing. A set of 384 SNP was selected to generate an Illumina GoldenGate assay in order to construct the first SNP-based genetic map of Cucurbita and map quantitative trait loci (QTL. Results We herein present the construction of the first SNP-based genetic map of Cucurbita pepo using a population derived from the cross of two varieties with contrasting phenotypes, representing the main cultivar groups of the species' two subspecies: Zucchini (subsp. pepo × Scallop (subsp. ovifera. The mapping population was genotyped with 384 SNP, a set of selected EST-SNP identified in silico after massive sequencing of the transcriptomes of both parents, using the Illumina GoldenGate platform. The global success rate of the assay was higher than 85%. In total, 304 SNP were mapped, along with 11 SSR from a previous map, giving a map density of 5.56 cM/marker. This map was used to infer syntenic relationships between C. pepo and cucumber and to successfully map QTL that control plant, flowering and fruit traits that are of benefit to squash breeding. The QTL effects were validated in backcross populations. Conclusion Our results show that massive sequencing in different genotypes is an excellent tool for SNP discovery, and that the Illumina GoldenGate platform can be successfully applied to constructing genetic maps and performing QTL analysis in Cucurbita. This is the first SNP-based genetic map in the Cucurbita genus and is an invaluable new tool for biological research

  20. The Expression Quantitative Trait Loci in Immune Pathways and their Effect on Cutaneous Melanoma Prognosis.

    Science.gov (United States)

    Vogelsang, Matjaz; Martinez, Carlos N; Rendleman, Justin; Bapodra, Anuj; Malecek, Karolina; Romanchuk, Artur; Kazlow, Esther; Shapiro, Richard L; Berman, Russell S; Krogsgaard, Michelle; Osman, Iman; Kirchhoff, Tomas

    2016-07-01

    The identification of personalized germline markers with biologic relevance for the prediction of cutaneous melanoma prognosis is highly demanded but to date, it has been largely unsuccessful. As melanoma progression is controlled by host immunity, here we present a novel approach interrogating immunoregulatory pathways using the genome-wide maps of expression quantitative trait loci (eQTL) to reveal biologically relevant germline variants modulating cutaneous melanoma outcomes. Using whole genome eQTL data from a healthy population, we identified 385 variants significantly impacting the expression of 268 immune-relevant genes. The 40 most significant eQTLs were tested in a prospective cohort of 1,221 patients with cutaneous melanoma for their association with overall (OS) and recurrence-free survival using Cox regression models. We identified highly significant associations with better melanoma OS for rs6673928, impacting IL19 expression (HR, 0.56; 95% CI, 0.41-0.77; P = 0.0002) and rs6695772, controlling the expression of BATF3 (HR, 1.64; 95% CI, 1.19-2.24; P = 0.0019). Both associations map in the previously suspected melanoma prognostic locus at 1q32. Furthermore, we show that their combined effect on melanoma OS is substantially enhanced reaching the level of clinical applicability (HR, 1.92; 95% CI, 1.43-2.60; P = 2.38e-5). Our unique approach of interrogating lymphocyte-specific eQTLs reveals novel and biologically relevant immunomodulatory eQTL predictors of cutaneous melanoma prognosis that are independent of current histopathologic markers. The significantly enhanced combined effect of identified eQTLs suggests the personalized utilization of both SNPs in a clinical setting, strongly indicating the promise of the proposed design for the discovery of prognostic or risk germline markers in other cancers. Clin Cancer Res; 22(13); 3268-80. ©2016 AACR. ©2016 American Association for Cancer Research.

  1. Identification of quantitative trait loci controlling linolenic acid concentration in PI483463 (Glycine soja).

    Science.gov (United States)

    Ha, Bo-Keun; Kim, Hyun-Jee; Velusamy, Vijayanand; Vuong, Tri D; Nguyen, Henry T; Shannon, J Grover; Lee, Jeong-Dong

    2014-07-01

    The QTLs controlling alpha-linolenic acid concentration from wild soybean were mapped on nine soybean chromosomes with various phenotypic variations. New QTLs for alpha-linolenic acid were detected in wild soybean. Alpha-linolenic acid (ALA) is a polyunsaturated fatty acid desired in human and animal diets. Some wild soybean (Glycine soja) genotypes are high in ALA. The objective of this study was to identify quantitative trait loci (QTLs) controlling ALA concentration in a wild soybean accession, PI483463. In total, 188 recombinant inbred lines of F5:6, F5:7, and F5:8 generations derived from a cross of wild soybean PI483463 (~15 % ALA) and cultivar Hutcheson (~9 % ALA) were planted in four environments. Harvested seeds were used to measure fatty acid concentration. Single nucleotide polymorphism markers of the universal soybean linkage panel (USLP 1.0) and simple sequence repeat markers were used for molecular genotyping. Nine putative QTLs were identified that controlled ALA concentration by model-based composite interval mapping and mapped to different soybean chromosomes. The QTLs detected in four environments explained 2.4-7.9 % of the total phenotypic variation (PV). Five QTLs, qALA5_3, qALA6_1, qALA14_1, qALA15_1, and qALA17_1, located on chromosomes 5, 6, 14, 15, and 17 were identified by model-based composite interval mapping and composite interval mapping in two individual environments. Among them, qALA6_1 showed the highest contribution to the PV with 10.0-10.2 % in two environments. The total detected QTLs for additive and epistatic effects explained 52.4 % of the PV for ALA concentration. These findings will provide useful information for understanding genetic structure and marker-assisted breeding programs to increase ALA concentration in seeds derived from wild soybean PI483463.

  2. Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus

    Science.gov (United States)

    Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

    2015-01-01

    Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10–56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa. PMID:26695430

  3. Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus.

    Directory of Open Access Journals (Sweden)

    Fagen Li

    Full Text Available Dense genetic maps, along with quantitative trait loci (QTLs detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR, expressed sequence tag (EST derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS, and diversity arrays technology (DArT markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus and with the E. grandis genome sequence. Fifty-three QTLs for growth (10-56 months of age and wood density (56 months were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa.

  4. Ancestral genes can control the ability of horizontally acquired loci to confer new traits.

    Directory of Open Access Journals (Sweden)

    H Deborah Chen

    2011-07-01

    Full Text Available Horizontally acquired genes typically function as autonomous units conferring new abilities when introduced into different species. However, we reasoned that proteins preexisting in an organism might constrain the functionality of a horizontally acquired gene product if it operates on an ancestral pathway. Here, we determine how the horizontally acquired pmrD gene product activates the ancestral PmrA/PmrB two-component system in Salmonella enterica but not in the closely related bacterium Escherichia coli. The Salmonella PmrD protein binds to the phosphorylated PmrA protein (PmrA-P, protecting it from dephosphorylation by the PmrB protein. This results in transcription of PmrA-dependent genes, including those conferring polymyxin B resistance. We now report that the E. coli PmrD protein can activate the PmrA/PmrB system in Salmonella even though it cannot do it in E. coli, suggesting that these two species differ in an additional component controlling PmrA-P levels. We establish that the E. coli PmrB displays higher phosphatase activity towards PmrA-P than the Salmonella PmrB, and we identified a PmrB subdomain responsible for this property. Replacement of the E. coli pmrB gene with the Salmonella homolog was sufficient to render E. coli resistant to polymyxin B under PmrD-inducing conditions. Our findings provide a singular example whereby quantitative differences in the biochemical activities of orthologous ancestral proteins dictate the ability of a horizontally acquired gene product to confer species-specific traits. And they suggest that horizontally acquired genes can potentiate selection at ancestral loci.

  5. Quantitative trait loci associated with longevity of lettuce seeds under conventional and controlled deterioration storage conditions.

    Science.gov (United States)

    Schwember, Andrés R; Bradford, Kent J

    2010-10-01

    Lettuce (Lactuca sativa L.) seeds have poor shelf life and exhibit thermoinhibition (fail to germinate) above ∼25°C. Seed priming (controlled hydration followed by drying) alleviates thermoinhibition by increasing the maximum germination temperature, but reduces lettuce seed longevity. Controlled deterioration (CD) or accelerated ageing storage conditions (i.e. elevated temperature and relative humidity) are used to study seed longevity and to predict potential seed lifetimes under conventional storage conditions. Seeds produced in 2002 and 2006 of a recombinant inbred line (RIL) population derived from a cross between L. sativa cv. Salinas×L. serriola accession UC96US23 were utilized to identify quantitative trait loci (QTLs) associated with seed longevity under CD and conventional storage conditions. Multiple longevity-associated QTLs were identified under both conventional and CD storage conditions for control (non-primed) and primed seeds. However, seed longevity was poorly correlated between the two storage conditions, suggesting that deterioration processes under CD conditions are not predictive of ageing in conventional storage conditions. Additionally, the same QTLs were not identified when RIL populations were grown in different years, indicating that lettuce seed longevity is strongly affected by production environment. Nonetheless, a major QTL on chromosome 4 [Seed longevity 4.1 (Slg4.1)] was responsible for almost 23% of the phenotypic variation in viability of the conventionally stored control seeds of the 2006 RIL population, with improved longevity conferred by the Salinas allele. QTL analyses may enable identification of mechanisms responsible for the sensitivity of primed seeds to CD conditions and breeding for improved seed longevity.

  6. Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus.

    Science.gov (United States)

    Li, Fagen; Zhou, Changpin; Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

    2015-01-01

    Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10-56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa.

  7. Enrichment of inflammatory bowel disease and colorectal cancer risk variants in colon expression quantitative trait loci.

    Science.gov (United States)

    Hulur, Imge; Gamazon, Eric R; Skol, Andrew D; Xicola, Rosa M; Llor, Xavier; Onel, Kenan; Ellis, Nathan A; Kupfer, Sonia S

    2015-02-27

    Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with diseases of the colon including inflammatory bowel diseases (IBD) and colorectal cancer (CRC). However, the functional role of many of these SNPs is largely unknown and tissue-specific resources are lacking. Expression quantitative trait loci (eQTL) mapping identifies target genes of disease-associated SNPs. This study provides a comprehensive eQTL map of distal colonic samples obtained from 40 healthy African Americans and demonstrates their relevance for GWAS of colonic diseases. 8.4 million imputed SNPs were tested for their associations with 16,252 expression probes representing 12,363 unique genes. 1,941 significant cis-eQTL, corresponding to 122 independent signals, were identified at a false discovery rate (FDR) of 0.01. Overall, among colon cis-eQTL, there was significant enrichment for GWAS variants for IBD (Crohn's disease [CD] and ulcerative colitis [UC]) and CRC as well as type 2 diabetes and body mass index. ERAP2, ADCY3, INPP5E, UBA7, SFMBT1, NXPE1 and REXO2 were identified as target genes for IBD-associated variants. The CRC-associated eQTL rs3802842 was associated with the expression of C11orf93 (COLCA2). Enrichment of colon eQTL near transcription start sites and for active histone marks was demonstrated, and eQTL with high population differentiation were identified. Through the comprehensive study of eQTL in the human colon, this study identified novel target genes for IBD- and CRC-associated genetic variants. Moreover, bioinformatic characterization of colon eQTL provides a tissue-specific tool to improve understanding of biological differences in diseases between different ethnic groups.

  8. TraitMap: an XML-based genetic-map database combining multigenic loci and biomolecular networks.

    Science.gov (United States)

    Heida, Naohiko; Hasegawa, Yoshikazu; Mochizuki, Yoshiki; Hirosawa, Katsura; Konagaya, Akihiko; Toyoda, Tetsuro

    2004-08-04

    Most ordinary traits are well described by multiple measurable parameters. Thus, in the course of elucidating the genes responsible for a given trait, it is necessary to conduct and integrate the genetic mapping of each parameter. However, the integration of multiple mapping results from different publications is prevented by the fact that they are conventionally published and accumulated in printed forms or graphics which are difficult for computers to reuse for further analyses. We have defined an XML-based schema as a container of genetic mapping results, and created a database named TraitMap containing curator-checked data records based on published papers of mapping results in Homosapiens, Mus musculus, and Arabidopsis thaliana. TraitMap is the first database of mapping charts in genetics, and is integrated in a web-based retrieval framework: termed Genome Phenome Superhighway (GPS) system, where it is possible to combine and visualize multiple mapping records in a two-dimensional display. Since most traits are regulated by multiple genes, the system associates every combination of genetic loci to biomolecular networks, and thus helps us to estimate molecular-level candidate networks responsible for a given trait. It is demonstrated that a combined analysis of two diabetes-related traits (susceptibility to insulin resistance and non-HDL cholesterol level) suggests that molecular-level relationships such as the interaction among leptin receptor (Lepr), peroxisome proliferators-activated receptor-gamma (Pparg) and insulin receptor substrate 1 (Irs1), are candidate causal networks affecting the traits in a multigenic manner. TraitMap database and GPS are accessible at http://omicspace.riken.jp/gps/

  9. Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L..

    Directory of Open Access Journals (Sweden)

    Yong Zhou

    Full Text Available Identification of quantitative trait loci (QTLs associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN, total root length (TRL, root dry weight (RDW, maximum root length (MRL, root thickness (RTH, total absorption area (TAA and root vitality (RV, using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY. Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.

  10. Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

    Science.gov (United States)

    Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J; Tropf, Felix C; Shen, Xia; Wilson, James F; Chasman, Daniel I; Nolte, Ilja M; Tragante, Vinicius; van der Laan, Sander W; Perry, John R B; Kong, Augustine; Ahluwalia, Tarunveer S; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J; Gieger, Christian; Gunderson, Erica P; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F; McMahon, George; Meddens, S Fleur W; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A; Monnereau, Claire; van der Most, Peter J; Myhre, Ronny; Nalls, Mike A; Nutile, Teresa; Kalafati, Ioanna Panagiota; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B; Rich-Edwards, Janet; Rietveld, Cornelius A; Robino, Antonietta; Rose, Lynda M; Rueedi, Rico; Ryan, Kathleen A; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A; Stolk, Lisette; Streeten, Elizabeth; Tönjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I; Buring, Julie E; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R; Cucca, Francesco; Toniolo, Daniela; Davey-Smith, George; Deary, Ian J; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M; de Geus, Eco J C; Eriksson, Johan G; Evans, Denis A; Faul, Jessica D; Sala, Cinzia Felicita; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J F; de Haan, Hugoline G; Haerting, Johannes; Harris, Tamara B; Heath, Andrew C; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hyppönen, Elina; Jacobsson, Bo; Jaddoe, Vincent W V; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L R; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William G; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia M; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; McQuillan, Ruth; Medland, Sarah E; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Traglia, Michela; Milani, Lili; Mitchell, Paul; Montgomery, Grant W; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W J H; Perola, Markus; Peyser, Patricia A; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M; Ring, Susan M; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D; Starr, John M; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tung, Joyce Y; Uitterlinden, André G; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G; Wang, Jie Jin; Wareham, Nicholas J; Weir, David R; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F; Zondervan, Krina T; Stefansson, Kari; Krueger, Robert F; Lee, James J; Benjamin, Daniel J; Cesarini, David; Koellinger, Philipp D; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C

    2016-12-01

    The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

  11. Genome-wide analysis identifies 12 loci influencing human reproductive behavior

    Science.gov (United States)

    Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco JC.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W. V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda WJH; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.

    2017-01-01

    The genetic architecture of human reproductive behavior – age at first birth (AFB) and number of children ever born (NEB) – has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified and the underlying mechanisms of AFB and NEB are poorly understood. We report the largest genome-wide association study to date of both sexes including 251,151 individuals for AFB and 343,072 for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study, and four additional loci in a gene-based effort. These loci harbor genes that are likely to play a role – either directly or by affecting non-local gene expression – in human reproduction and infertility, thereby increasing our understanding of these complex traits. PMID:27798627

  12. Localization of quantitative trait loci for diapause and other photoperiodically regulated life history traits important in adaptation to seasonally varying environments.

    Science.gov (United States)

    Tyukmaeva, Venera I; Veltsos, Paris; Slate, Jon; Gregson, Emma; Kauranen, Hannele; Kankare, Maaria; Ritchie, Michael G; Butlin, Roger K; Hoikkala, Anneli

    2015-06-01

    Seasonally changing environments at high latitudes present great challenges for the reproduction and survival of insects, and photoperiodic cues play an important role in helping them to synchronize their life cycle with prevalent and forthcoming conditions. We have mapped quantitative trait loci (QTL) responsible for the photoperiodic regulation of four life history traits, female reproductive diapause, cold tolerance, egg-to-eclosion development time and juvenile body weight in Drosophila montana strains from different latitudes in Canada and Finland. The F2 progeny of the cross was reared under a single photoperiod (LD cycle 16:8), which the flies from the Canadian population interpret as early summer and the flies from the Finnish population as late summer. The analysis revealed a unique QTL for diapause induction on the X chromosome and several QTL for this and the other measured traits on the 4th chromosome. Flies' cold tolerance, egg-to-eclosion development time and juvenile body weight had several QTL also on the 2nd, 3rd and 5th chromosome, some of the peaks overlapping with each other. These results suggest that while the downstream output of females' photoperiodic diapause response is partly under a different genetic control from that of the other traits in the given day length, all traits also share some QTL, possibly involving genes with pleiotropic effects and/or multiple tightly linked genes. Nonoverlapping QTL detected for some of the traits also suggest that the traits are potentially capable of independent evolution, even though this may be restricted by epistatic interactions and/or correlations and trade-offs between the traits. © 2015 John Wiley & Sons Ltd.

  13. Identification of quantitative trait loci for carcass composition and meat quality traits in a commercial finishing cross

    NARCIS (Netherlands)

    Wijk, van H.J.; Dibbits, B.W.; Baron, E.E.; Brings, A.D.; Harlizius, B.; Groenen, M.A.M.; Knol, E.F.; Bovenhuis, H.

    2006-01-01

    A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Pie¿train/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4

  14. Quantitative Trait Loci Analysis of Folate Content in Dry Beans, Phaseolus vulgaris L.

    Directory of Open Access Journals (Sweden)

    S. Khanal

    2013-01-01

    Full Text Available Dry beans (Phaseolus vulgaris L. contain high levels of folates, yet the level of folate may vary among different genotypes. Folates are essential vitamins and folate deficiencies may lead to a number of health problems. Among the different forms of folates, 5-methyltetrahydrofolate (5MTHF comprises more than 80% of the total folate in dry beans. The objectives of this paper were to compare selected genotypes of dry beans for the folate content of the dry seeds and to identify quantitative trait loci (QTL associated with the folate content in a population derived from an inter-gene-pool cross of dry beans. The folate content was examined in three large-seeded (AC Elk, Redhawk, and Taylor and one medium-seeded (Othello dry bean genotypes, their six F1 (i.e., one-way diallel crosses, and the F2 of Othello/Redhawk that were evaluated in the field in 2009. Total folate and 5MTHF contents were measured twice with one-hour time interval. The significant variation (P<0.05 in the folate content was observed among the parental genotypes, their F1 progeny, and members of the F2 population, ranging from 147 to 345 μg/100 g. There was a reduction in the 5MTHF and total folate contents in the second compared to the first measurement. Dark red kidney variety Redhawk consistently had the highest and pinto Othello had the lowest total folate and 5MTHF contents in both measurements. A single marker QTL analysis identified three QTL for total folate and 5MTHF contents in the first measurement and one marker for the total folate in the second measurement in the F2. These QTL had significant dominance effects and individually accounted for 7.7% to 10.5% of the total phenotypic variance. The total phenotypic variance explained by the four QTL was 18% for 5MTHF and 19% for total folate in the first measurement, but only 8% for total folate in the second measurement.

  15. Expression quantitative trait loci (eQTL mapping in Puerto Rican children.

    Directory of Open Access Journals (Sweden)

    Wei Chen

    Full Text Available Expression quantitative trait loci (eQTL have been identified using tissue or cell samples from diverse human populations, thus enhancing our understanding of regulation of gene expression. However, few studies have attempted to identify eQTL in racially admixed populations such as Hispanics.We performed a systematic eQTL study to identify regulatory variants of gene expression in whole blood from 121 Puerto Rican children with (n = 63 and without (n = 58 asthma. Genome-wide genotyping was conducted using the Illumina Omni2.5M Bead Chip, and gene expression was assessed using the Illumina HT-12 microarray. After completing quality control, we performed a pair-wise genome analysis of ~15 K transcripts and ~1.3 M SNPs for both local and distal effects. This analysis was conducted under a regression framework adjusting for age, gender and principal components derived from both genotypic and mRNA data. We used a false discovery rate (FDR approach to identify significant eQTL signals, which were next compared to top eQTL signals from existing eQTL databases. We then performed a pathway analysis for our top genes.We identified 36,720 local pairs in 3,391 unique genes and 1,851 distal pairs in 446 unique genes at FDR <0.05, corresponding to unadjusted P values lower than 1.5x10-4 and 4.5x10-9, respectively. A significant proportion of genes identified in our study overlapped with those identified in previous studies. We also found an enrichment of disease-related genes in our eQTL list.We present results from the first eQTL study in Puerto Rican children, who are members of a unique Hispanic cohort disproportionately affected with asthma, prematurity, obesity and other common diseases. Our study confirmed eQTL signals identified in other ethnic groups, while also detecting additional eQTLs unique to our study population. The identified eQTLs will help prioritize findings from future genome-wide association studies in Puerto Ricans.

  16. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

    Directory of Open Access Journals (Sweden)

    Momoko Horikoshi

    2015-07-01

    Full Text Available Reference panels from the 1000 Genomes (1000G Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS, supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI at genome-wide significance, and two for fasting glucose (FG, none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3 and FG (GCK and G6PC2. The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

  17. Two-part zero-inflated negative binomial regression model for quantitative trait loci mapping with count trait.

    Science.gov (United States)

    Moghimbeigi, Abbas

    2015-05-07

    Poisson regression models provide a standard framework for quantitative trait locus (QTL) mapping of count traits. In practice, however, count traits are often over-dispersed relative to the Poisson distribution. In these situations, the zero-inflated Poisson (ZIP), zero-inflated generalized Poisson (ZIGP) and zero-inflated negative binomial (ZINB) regression may be useful for QTL mapping of count traits. Added genetic variables to the negative binomial part equation, may also affect extra zero data. In this study, to overcome these challenges, I apply two-part ZINB model. The EM algorithm with Newton-Raphson method in the M-step uses for estimating parameters. An application of the two-part ZINB model for QTL mapping is considered to detect associations between the formation of gallstone and the genotype of markers. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Quantitative trait loci mapping in Brassica rapa revealed the structural and functional conservation of genetic loci governing morphological and yield component traits in the A, B, and C subgenomes of Brassica species.

    Science.gov (United States)

    Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

    2013-02-01

    Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species.

  19. Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

    Science.gov (United States)

    Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

    2013-01-01

    Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

  20. Identifying quantitative trait loci and determining closely related stalk traits for rind penetrometer resistance in a high-oil maize population.

    Science.gov (United States)

    Hu, Haixiao; Meng, Yujie; Wang, Hongwu; Liu, Hai; Chen, Shaojiang

    2012-05-01

    Stalk lodging in maize causes annual yield losses between 5 and 20% worldwide. Many studies have indicated that maize stalk strength significantly negatively correlates with lodging observed in the field. Rind penetrometer resistance (RPR) measurements can be used to effectively evaluate maize stalk strength, but little is known about the genetic basis of this parameter. The objective of this study was to explore a genetic model and detect quantitative trait loci (QTL) of RPR and determine relationships between RPR and other stalk traits, especially cell wall chemical components. RPR is quantitative trait in nature, and both additive and non-additive effects may be important to consider for the improvement of RPR. Nine additive-effect QTLs covering nine chromosomes, except chromosome 5, and one pair of epistatic QTLs were detected for RPR. CeSA11 involved in cellulose synthesis and colorless2 involved in lignin synthesis were identified as possible candidate genes for RPR. Internode diameter (InD), fresh weight of internode (FreW), dry weight of internode (DryW), fresh weight and dry weight as well as cell wall components per unit volume significantly positively correlated with RPR. The internode water content (InW) significantly negatively correlated with RPR. Notably, these traits significantly correlated with RPR, and the QTLs of these traits co-localized with those of RPR. The corresponding results obtained from correlation analysis and QTL mapping suggested the presence of pleitropism or linkage between genes and indicated that these different approaches may be used for cross authentication of relationships between different traits.

  1. Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions

    Science.gov (United States)

    Gu, Junfei; Yin, Xinyou; Struik, Paul C.; Stomph, Tjeerd Jan; Wang, Huaqi

    2012-01-01

    Photosynthesis is fundamental to biomass production, but sensitive to drought. To understand the genetics of leaf photosynthesis, especially under drought, upland rice cv. Haogelao, lowland rice cv. Shennong265, and 94 of their introgression lines (ILs) were studied at flowering and grain filling under drought and well-watered field conditions. Gas exchange and chlorophyll fluorescence measurements were conducted to evaluate eight photosynthetic traits. Since these traits are very sensitive to fluctuations in microclimate during measurements under field conditions, observations were adjusted for microclimatic differences through both a statistical covariant model and a physiological approach. Both approaches identified leaf-to-air vapour pressure difference as the variable influencing the traits most. Using the simple sequence repeat (SSR) linkage map for the IL population, 1–3 quantitative trait loci (QTLs) were detected per trait–stage–treatment combination, which explained between 7.0% and 30.4% of the phenotypic variance of each trait. The clustered QTLs near marker RM410 (the interval from 57.3 cM to 68.4 cM on chromosome 9) were consistent over both development stages and both drought and well-watered conditions. This QTL consistency was verified by a greenhouse experiment under a controlled environment. The alleles from the upland rice at this interval had positive effects on net photosynthetic rate, stomatal conductance, transpiration rate, quantum yield of photosystem II (PSII), and the maximum efficiency of light-adapted open PSII. However, the allele of another main QTL from upland rice was associated with increased drought sensitivity of photosynthesis. These results could potentially be used in breeding programmes through marker-assisted selection to improve drought tolerance and photosynthesis simultaneously. PMID:21984650

  2. Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

    Directory of Open Access Journals (Sweden)

    Wang Xiaoqiang

    2012-04-01

    Full Text Available Abstract Background Quantitative trait loci (QTL detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i

  3. Mapping quantitative trait loci conferring resistance to rice black-streaked virus in maize (Zea mays L.).

    Science.gov (United States)

    Luan, Junwen; Wang, Fei; Li, Yujie; Zhang, Bin; Zhang, Juren

    2012-08-01

    Maize rough dwarf disease (MRDD) is one of the most serious virus diseases of maize worldwide, and it causes great reduction of maize production. In China, the pathogen was shown to be rice black-streaked virus (RBSDV). Currently, MRDD has spread broadly and leads to significant loss in China. However, there has been little research devoted to this disease. Our aims were to identify the markers and loci underlying resistance to this virus disease. In this study, segregation populations were constructed from two maize elite lines '90110', which is highly resistant to MRDD and 'Ye478', which is highly susceptible to MRDD. The F(2) and BC(1) populations were used for bulk sergeant analysis (BSA) to identify resistance-related markers. One hundred and twenty F(7:9) RILs were used for quantitative trait loci (QTL) mapping through the experiment of multiple environments over 3 years. Natural occurrence and artificial inoculation were both used and combined to determine the phenotype of plants. Five QTL, qMRD2, qMRD6, qMRD7, qMRD8 and qMRD10 were measured in the experiments. The qMRD8 on chromosome 8 was proved to be one major QTL conferring resistance to RBSDV disease in almost all traits and environments, which explained 12.0-28.9 % of the phenotypic variance for disease severity in this present study.

  4. Identification and characterization of quantitative trait loci that control seed dormancy in Arabidopsis

    NARCIS (Netherlands)

    Bentsink, L.; Koornneef, M.

    2011-01-01

    Seed dormancy is a trait that is under multigenic control and affected strongly by environmental factors. Thus, seed dormancy is a typical quantitative trait. Natural accessions of Arabidopsis thaliana exhibit a great deal of genetic variation for seed dormancy. This natural variation can be used to

  5. Quantitative trait loci (QTL) analysis of flag leaf senescence in wheat ...

    African Journals Online (AJOL)

    PAVILION DV6

    2012-07-10

    Jul 10, 2012 ... the genetic control of this trait and the QTLs identified on chromosome 2D, associated with better ... allowed the identification of regions controlling some traits related to the response to drought. Different ..... closely linked with target alleles present a useful tool in plant breeding, since they can help to detect ...

  6. Fine mapping of quantitative trait loci underlying sensory meat quality traits in three French beef cattle breeds.

    Science.gov (United States)

    Allais, S; Levéziel, H; Hocquette, J F; Rousset, S; Denoyelle, C; Journaux, L; Renand, G

    2014-10-01

    Improving the traits that underlie meat quality is a major challenge in the beef industry. The objective of this paper was to detect QTL linked to sensory meat quality traits in 3 French beef cattle breeds. We genotyped 1,059, 1,219, and 947 young bulls and their sires belonging to the Charolais, Limousin, and Blonde d'Aquitaine breeds, respectively, using the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). After estimating relevant genetic parameters using VCE software, we performed a linkage disequilibrium and linkage analysis on 4 meat traits: intramuscular fat content, muscle lightness, shear force, and tenderness score. Heritability coefficients largely ranged between 0.10 and 0.24; however, they reached a maximum of 0.44 and 0.50 for intramuscular fat content and tenderness score, respectively, in the Charolais breed. The 2 meat texture traits, shear force and tenderness score, were strongly genetically correlated (-0.91 in the Charolais and Limousin breed and -0.86 in the Blonde d'Aquitaine breed), indicating that they are 2 different measures of approximately the same trait. The genetic correlation between tenderness and intramuscular fat content differed across breeds. Using a significance threshold of 5 × 10(-4) for QTL detection, we found more than 200 significant positions across the 29 autosomal chromosomes for the 4 traits in the Charolais and Blonde d'Aquitaine breeds; in contrast, there were only 78 significant positions in the Limousin breed. Few QTL were common across breeds. We detected QTL for intramuscular fat content located near the myostatin gene in the Charolais and Blonde d'Aquitaine breeds. No mutation in this gene has been reported for the Blonde d'Aquitaine breed; therefore, it suggests that an unknown mutation could be segregating in this breed. We confirmed that, in certain breeds, markers in the calpastatin and calpain 1 gene regions affect tenderness. We also found new QTL as several QTL on chromosome 3 that are

  7. Quantitative trait loci mapping for fatty acid composition traits in perirenal and back fat using a Japanese wild boar x Large White intercross.

    Science.gov (United States)

    Nii, M; Hayashi, T; Tani, F; Niki, A; Mori, N; Fujishima-Kanaya, N; Komatsu, M; Aikawa, K; Awata, T; Mikawa, S

    2006-08-01

    Here, we analysed quantitative trait loci (QTL) for fatty acid composition, one of the factors affecting fat quality, in a Japanese wild boar x Large White cross. We found 25 significant effects for 17 traits at 13 positions at the 5% genome-wise level, of which 16 effects for 12 traits at 10 positions were significant at the 1% level. QTL for saturated fatty acids (SFA) in back fat were mapped to swine (Sus scrofa) chromosomes (SSC) 1p, 9 and 15. QTL for unsaturated fatty acids in back fat were mapped to SSC1p, 1q, 4, 5, 9, 15 and 17. Using a regression model that fits back fat thickness as a covariate, two of the QTL for linoleic acid content on SSC4 and SSC17 were not significant, but one QTL for total SFA composition was detected on SSC5 with correction for back fat thickness. Wild boar alleles at six of seven QTL tended to increase SFAs and to decrease unsaturated fatty acids. QTL for fatty acid composition in perirenal fat were mapped on SSC2, 3, 4, 5, 6, 14, 16 and X. QTL for melting point (in back fat samples) were mapped on SSC1, 2 and 15. Wild boar alleles in QTL on SSC1 and SSC15 were associated with elevated melting points whereas those on SSC2 were associated with lower melting point measurements.

  8. Quantitative trait loci for hip dysplasia in a cross-breed canine pedigree.

    Science.gov (United States)

    Todhunter, Rory J; Mateescu, Raluca; Lust, George; Burton-Wurster, Nancy I; Dykes, Nathan L; Bliss, Stuart P; Williams, Alma J; Vernier-Singer, Margaret; Corey, Elizabeth; Harjes, Carlos; Quaas, Richard L; Zhang, Zhiwu; Gilbert, Robert O; Volkman, Dietrich; Casella, George; Wu, Rongling; Acland, Gregory M

    2005-09-01

    Canine hip dysplasia is a common developmental inherited trait characterized by hip laxity, subluxation or incongruity of the femoral head and acetabulum in affected hips. The inheritance pattern is complex and the mutations contributing to trait expression are unknown. In the study reported here, 240 microsatellite markers distributed in 38 autosomes and the X chromosome were genotyped on 152 dogs from three generations of a crossbred pedigree based on trait-free Greyhound and dysplastic Labrador Retriever founders. Interval mapping was undertaken to map the QTL underlying the quantitative dysplastic traits of maximum passive hip laxity (the distraction index), the dorsolateral subluxation score, and the Norberg angle. Permutation testing was used to derive the chromosome-wide level of significance at p<0.05 for each QTL. Chromosomes 4, 9, 10, 11 (p<0.01), 16, 20, 22, 25, 29 (p<0.01), 30, 35, and 37 harbor putative QTL for one or more traits. Successful detection of QTL was due to the cross-breed pedigree, multiple-trait measurements, control of environmental background, and marked advancement in canine mapping tools.

  9. A random model for mapping imprinted quantitative trait loci in a structured pedigree: an implication for mapping canine hip dysplasia.

    Science.gov (United States)

    Liu, Tian; Todhunter, Rory J; Wu, Song; Hou, Wei; Mateescu, Raluca; Zhang, Zhiwu; Burton-Wurster, Nancy I; Acland, Gregory M; Lust, George; Wu, Rongling

    2007-08-01

    Genetic imprinting may have played a more notable role in shaping embryonic development of plants, animals, and humans than previously appreciated. Quantitative trait loci that are imprinted (iQTL) exert monoallelic effects, depending on the parent of origin, which is an exception to the laws of Mendelian genetics. In this article, we present a modified random effect-based mapping model to use in a genome-wide scan for the distribution of iQTL that contribute to genetic variance for a complex trait in a structured pedigree. This model, implemented with the maximum likelihood method, capitalizes on a network of relatedness for maternally and paternally derived alleles through identical-by-descent sharing, thus allowing for the discrimination of the genetic variances due to alleles derived from maternal and paternal parents. The model was employed to map iQTL responsible for canine hip dysplasia in a multihierarchical canine pedigree, founded with seven greyhounds and six Labrador retrievers. Of eight significant QTL detected, three, located on CFA1, CFA8, and CF28, were found to trigger significant parent-of-origin effects on the age of femoral capital ossification measured at the left and right hips of a canine. The detected iQTL provide important candidate regions for fine-mapping of imprinted genes and for studying their structure and function in the control of complex traits.

  10. Identification of heterotic loci associated with yield-related traits in Chinese common wild rice (Oryza rufipogon Griff.).

    Science.gov (United States)

    Luo, Xiaojin; Wu, Shuang; Tian, Feng; Xin, Xiaoyun; Zha, Xiaojun; Dong, Xianxin; Fu, Yongcai; Wang, Xiangkun; Yang, Jinshui; Sun, Chuanqing

    2011-07-01

    Many rice breeding programs have currently reached yield plateaus as a result of limited genetic variability in parental strains. Dongxiang common wild rice (Oryza rufipogon Griff.) is the progenitor of cultivated rice (Oryza sativa L.) and serves as an important gene pool for the genetic improvement of rice cultivars. In this study, heterotic loci (HLs) associated with six yield-related traits were identified in wild and cultivated rice and investigated using a set of 265 introgression lines (ILs) of O. rufipogon Griff. in the background of the Indica high-yielding cultivar Guichao 2 (O. sativa L.). Forty-two HLs were detected by a single point analysis of mid-parent heterosis values from test cross F(1) offspring, and 30 (71.5%) of these HLs showed significantly positive effects, consistent with the superiority shown by the F(1) test cross population in the six yield-related traits under study. Genetic mapping of hsp11, a locus responsible for the number of spikelets per panicle, confirmed the utility of these HLs. The results indicate that favorable HLs capable of improving agronomic traits are available. The identification of HLs between wild rice and cultivated rice could lead to a new strategy for the application of heterosis in rice breeding. Copyright © 2011. Published by Elsevier Ireland Ltd.

  11. Identification of quantitative trait loci controlling root and shoot traits associated with drought tolerance in a lentil (Lens culinaris Medik. recombinant inbred line population

    Directory of Open Access Journals (Sweden)

    Omar Idrissi

    2016-08-01

    Full Text Available Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding programs. In all, 252 co-dominant and dominant markers were used for Quantitative Trait Loci (QTL analysis on 132 lentil recombinant inbred lines based on greenhouse experiments for root and shoot traits during two seasons under progressive drought-stressed conditions. Eighteen QTLs controlling a total of 14 root and shoot traits were identified. A QTL-hotspot genomic region related to a number of root and shoot characteristics associated with drought tolerance such as dry root biomass, root surface area, lateral root number, dry shoot biomass and shoot length was identified. Interestingly, a QTL related to root-shoot ratio, an important trait for drought avoidance, explaining the highest phenotypic variance of 27.6 % and 28.9 % for the two consecutive seasons, respectively, was detected. This QTL was closed to the co-dominant SNP marker TP6337 and also flanked by the two SNP TP518 and TP1280. An important QTL related to lateral root number was found close to TP3371 and flanked by TP5093 and TP6072 SNP markers. Also, a QTL associated with specific root length was identified close to TP1873 and flanked by F7XEM6b SRAP marker and TP1035 SNP marker. These two QTLs were detected in both seasons. Our results could be used for marker-assisted selection in lentil breeding programs targeting root and shoot characteristics conferring drought avoidance as an efficient alternative to slow and labour-intensive conventional breeding methods.

  12. Identification of quantitative trait loci for the fatty acid composition in Korean native chicken.

    Science.gov (United States)

    Jin, Shil; Seo, Dongwon; Choi, Nu Ri; Manjula, Prabuddha; Cahyadi, Muhammad; Jung, Samooel; Jo, Cheorun; Lee, Jun Heon; Park, Hee Bok

    2018-01-26

    Fatty acid composition is one of the most important meat quality traits because it can contribute to functional, sensorial, and nutritional factors. In this study, quantitative trait locus (QTL) analyses for fatty acid composition traits were investigated in thigh and breast meat of Korean native chicken (KNC). In total, 18 fatty acid composition traits were investigated from each meat sample using 88 parents, and 595 F1 chicks of 20 week old. Genotype assessment was performed using 171 informative DNA markers on 26 autosomes. The KNC linkage map was constructed by CRI-MAP software, which calculated genetic distances, with map orders between markers. The half-sib and full-sib QTL analyses were performed using GridQTL and SOLAR programs, respectively. In total, 30 QTLs (12 in the thigh and 18 in the breast meat) were detected by the half-sib analysis and 7 QTLs (3 in the thigh and 4 in the breast meat) were identified by the full-sib analysis. With further verification of the QTL regions using additional markers and positional candidate gene studies, these results can provide valuable information for determining causative mutations affecting the fatty acid composition of KNC meat. Moreover, these findings may aid in the selection of birds with favorable fatty acid composition traits.

  13. Discovery of quantitative trait loci for resistance to parasitic nematode infection in sheep: I. Analysis of outcross pedigrees

    Directory of Open Access Journals (Sweden)

    Greer Gordon J

    2006-07-01

    Full Text Available Abstract Background Currently most pastoral farmers rely on anthelmintic drenches to control gastrointestinal parasitic nematodes in sheep. Resistance to anthelmintics is rapidly increasing in nematode populations such that on some farms none of the drench families are now completely effective. It is well established that host resistance to nematode infection is a moderately heritable trait. This study was undertaken to identify regions of the genome, quantitative trait loci (QTL that contain genes affecting resistance to parasitic nematodes. Results Rams obtained from crossing nematode parasite resistant and susceptible selection lines were used to derive five large half-sib families comprising between 348 and 101 offspring per sire. Total offspring comprised 940 lambs. Extensive measurements for a range of parasite burden and immune function traits in all offspring allowed each lamb in each pedigree to be ranked for relative resistance to nematode parasites. Initially the 22 most resistant and 22 most susceptible progeny from each pedigree were used in a genome scan that used 203 microsatellite markers spread across all sheep autosomes. This study identified 9 chromosomes with regions showing sufficient linkage to warrant the genotyping of all offspring. After genotyping all offspring with markers covering Chromosomes 1, 3, 4, 5, 8, 12, 13, 22 and 23, the telomeric end of chromosome 8 was identified as having a significant QTL for parasite resistance as measured by the number of Trichostrongylus spp. adults in the abomasum and small intestine at the end of the second parasite challenge. Two further QTL for associated immune function traits of total serum IgE and T. colubiformis specific serum IgG, at the end of the second parasite challenge, were identified on chromosome 23. Conclusion Despite parasite resistance being a moderately heritable trait, this large study was able to identify only a single significant QTL associated with it. The QTL

  14. Combined use of phenotypic and genotypic information in sampling animalsfor genotyping in detection of quantitative trait loci

    DEFF Research Database (Denmark)

    Ansari-Mahyari, S; Berg, P

    2008-01-01

    Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error...... of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phenotypic and genotypic information. In comparison, animals were randomly genotyped either within or across families. One hundred data sets were simulated each with 30 half-sib families and 120 daughters per family....... The strategies were compared in these datasets with respect to estimated effect and position of a QTL within a previously defined genomic region at genotyping 10, 20 or 30% of the animals. Combined linkage disequilibrium linkage analysis (LDLA) was applied in a variance component approach. Power to detect QTL...

  15. Association Mapping of Quantitative Trait Loci for Mineral Element Contents in Whole Grain Rice (Oryza sativa L.).

    Science.gov (United States)

    Huang, Yan; Sun, Chengxiao; Min, Jie; Chen, Yaling; Tong, Chuan; Bao, Jinsong

    2015-12-23

    Mineral elements in brown rice grain play an important role in human health. In this study, variations in the content of iron (Fe), zinc (Zn), selenium (Se), cadmium (Cd), and lead (Pb) in 378 accessions of brown rice were investigated, and association mapping was used to detect the quantitative trait loci (QTLs) responsible for the variation. Among seven subpopulations, the mean values of Zn and Cd in the japonica group were significantly higher than in the indica groups. The population structure accounted for from 5.7% (Se) to 22.1% (Pb) of the total variation. Correlation analyses showed that Pb was positively correlated with the other minerals (P rice grain by marker-assisted selection (MAS).

  16. Inheritance analysis and mapping of quantitative trait loci (QTL controlling individual anthocyanin compounds in purple barley (Hordeum vulgare L. grains.

    Directory of Open Access Journals (Sweden)

    Xiao-Wei Zhang

    Full Text Available Anthocyanin-rich barley can have great potential in promoting human health and in developing nutraceuticals and functional foods. As different anthocyanin compounds have different antioxidant activities, breeding cultivars with pre-designed anthocyanin compositions could be highly desirable. Working toward this possibility, we assessed and reported for the first time the genetic control of individual anthocyanin compounds in barley. Of the ten anthocyanins assessed, two, peonidin-3-glucoside (P3G and cyanidin-3-glucoside (C3G, were major components in the purple pericarp barley genotype RUSSIA68. Quantitative trait locus (QTL mapping showed that both anthocyanin compounds were the interactive products of two loci, one located on chromosome arm 2HL and the other on 7HS. However, the two different anthocyanin components seem to be controlled by different interactions between the two loci. The effects of the 7HS locus on P3G and C3G were difficult to detect without removing the effect of the 2HL locus. At least one copy of the 2HL alleles from the purple pericarp parent was required for the synthesis of P3G. This does not seem to be the case for the production of C3G which was produced in each of all the different allele combinations between the two loci. Typical maternal effect was also observed in the inheritance of purple pericarp grains in barley. The varied values of different compounds, coupled with their different genetic controls, highlight the need for targeting individual anthocyanins in crop breeding and food processing.

  17. Inheritance analysis and mapping of quantitative trait loci (QTL) controlling individual anthocyanin compounds in purple barley (Hordeum vulgare L.) grains.

    Science.gov (United States)

    Zhang, Xiao-Wei; Jiang, Qian-Tao; Wei, Yu-Ming; Liu, Chunji

    2017-01-01

    Anthocyanin-rich barley can have great potential in promoting human health and in developing nutraceuticals and functional foods. As different anthocyanin compounds have different antioxidant activities, breeding cultivars with pre-designed anthocyanin compositions could be highly desirable. Working toward this possibility, we assessed and reported for the first time the genetic control of individual anthocyanin compounds in barley. Of the ten anthocyanins assessed, two, peonidin-3-glucoside (P3G) and cyanidin-3-glucoside (C3G), were major components in the purple pericarp barley genotype RUSSIA68. Quantitative trait locus (QTL) mapping showed that both anthocyanin compounds were the interactive products of two loci, one located on chromosome arm 2HL and the other on 7HS. However, the two different anthocyanin components seem to be controlled by different interactions between the two loci. The effects of the 7HS locus on P3G and C3G were difficult to detect without removing the effect of the 2HL locus. At least one copy of the 2HL alleles from the purple pericarp parent was required for the synthesis of P3G. This does not seem to be the case for the production of C3G which was produced in each of all the different allele combinations between the two loci. Typical maternal effect was also observed in the inheritance of purple pericarp grains in barley. The varied values of different compounds, coupled with their different genetic controls, highlight the need for targeting individual anthocyanins in crop breeding and food processing.

  18. Genetic association for renal traits among participants of African ancestry reveals new loci for renal function.

    Directory of Open Access Journals (Sweden)

    Ching-Ti Liu

    2011-09-01

    Full Text Available Chronic kidney disease (CKD is an increasing global public health concern, particularly among populations of African ancestry. We performed an interrogation of known renal loci, genome-wide association (GWA, and IBC candidate-gene SNP association analyses in African Americans from the CARe Renal Consortium. In up to 8,110 participants, we performed meta-analyses of GWA and IBC array data for estimated glomerular filtration rate (eGFR, CKD (eGFR 30 mg/g and interrogated the 250 kb flanking region around 24 SNPs previously identified in European Ancestry renal GWAS analyses. Findings were replicated in up to 4,358 African Americans. To assess function, individually identified genes were knocked down in zebrafish embryos by morpholino antisense oligonucleotides. Expression of kidney-specific genes was assessed by in situ hybridization, and glomerular filtration was evaluated by dextran clearance. Overall, 23 of 24 previously identified SNPs had direction-consistent associations with eGFR in African Americans, 2 of which achieved nominal significance (UMOD, PIP5K1B. Interrogation of the flanking regions uncovered 24 new index SNPs in African Americans, 12 of which were replicated (UMOD, ANXA9, GCKR, TFDP2, DAB2, VEGFA, ATXN2, GATM, SLC22A2, TMEM60, SLC6A13, and BCAS3. In addition, we identified 3 suggestive loci at DOK6 (p-value = 5.3×10(-7 and FNDC1 (p-value = 3.0×10(-7 for UACR, and KCNQ1 with eGFR (p = 3.6×10(-6. Morpholino knockdown of kcnq1 in the zebrafish resulted in abnormal kidney development and filtration capacity. We identified several SNPs in association with eGFR in African Ancestry individuals, as well as 3 suggestive loci for UACR and eGFR. Functional genetic studies support a role for kcnq1 in glomerular development in zebrafish.

  19. Quantitative trait loci (QTL) mapping of resistance to strongyles and coccidia in the free-living Soay sheep (Ovis aries).

    Science.gov (United States)

    Beraldi, Dario; McRae, Allan F; Gratten, Jacob; Pilkington, Jill G; Slate, Jon; Visscher, Peter M; Pemberton, Josephine M

    2007-01-01

    A genome-wide scan was performed to detect quantitative trait loci (QTL) for resistance to gastrointestinal parasites and ectoparasitic keds segregating in the free-living Soay sheep population on St. Kilda (UK). The mapping panel consisted of a single pedigree of 882 individuals of which 588 were genotyped. The Soay linkage map used for the scans comprised 251 markers covering the whole genome at average spacing of 15cM. The traits here investigated were the strongyle faecal egg count (FEC), the coccidia faecal oocyst count (FOC) and a count of keds (Melophagus ovinus). QTL mapping was performed by means of variance component analysis so that the genetic parameters of the study traits were also estimated and compared with previous studies in Soay and domestic sheep. Strongyle FEC and coccidia FOC showed moderate heritability (h(2)=0.26 and 0.22, respectively) in lambs but low heritability in adults (h(2)<0.10). Ked count appeared to have very low h(2) in both lambs and adults. Genome scans were performed for the traits with moderate heritability and two genomic regions reached the level of suggestive linkage for coccidia FOC in lambs (logarithm of the odds=2.68 and 2.21 on chromosomes 3 and X, respectively). We believe this is the first study to report a QTL search for parasite resistance in a free-living animal population and therefore may represent a useful reference for similar studies aimed at understanding the genetics of host-parasite co-evolution in the wild.

  20. Detection of quantitative trait loci (QTL) related to grilsing and late sexual maturation in Atlantic salmon (Salmo salar).

    Science.gov (United States)

    Gutierrez, Alejandro P; Lubieniecki, Krzysztof P; Fukui, Steve; Withler, Ruth E; Swift, Bruce; Davidson, William S

    2014-02-01

    In Atlantic salmon aquaculture, early sexual maturation represents a major problem for producers. This is especially true for grilse, which mature after one sea winter before reaching a desirable harvest weight, rather than after two sea winters. Salmon maturing as grilse have a much lower market value than later maturing individuals. For this reason, most companies desire fish that grow fast and mature late. Marker-assisted selection has the potential to improve the efficiency of selection against early maturation and for late sexual maturation; however, studies identifying age of sexual maturation-related genetic markers are lacking for Atlantic salmon. Therefore, we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype five families from the Mainstream Canada broodstock program and search for SNPs associated with early (grilsing) or late sexual maturation. There were 529 SNP loci that were variable across all five families, and this was the set that was used for quantitative trait loci (QTL) analysis. GridQTL identified two chromosomes, Ssa10 and Ssa21, containing QTL related to grilsing. In contrast, only one QTL, on Ssa18, was found linked to late maturation in Atlantic salmon. Our previous work on these five families did not identify genome-wide significant growth-related QTL on Ssa10, Ssa21, or Ssa18. Therefore, taken together, these results suggest that both grilsing and late sexual maturation are controlled independently of one another and also from growth-related traits. The identification of genomic regions associated with grilsing or late sexual maturation provide an opportunity to incorporate this information into selective breeding programs that will enhance Atlantic salmon farming.

  1. Self-Confirmation and Ascertainment of the Candidate Genomic Regions of Complex Trait Loci - A None-Experimental Solution.

    Directory of Open Access Journals (Sweden)

    Lishi Wang

    Full Text Available Over the past half century, thousands of quantitative trait loci (QTL have been identified by using animal models and plant populations. However, the none-reliability and imprecision of the genomic regions of these loci have remained the major hurdle for the identification of the causal genes for the correspondent traits. We used a none-experimental strategy of strain number reduction for testing accuracy and ascertainment of the candidate region for QTL. We tested the strategy in over 400 analyses with data from 47 studies. These studies include: 1 studies with recombinant inbred (RI strains of mice. We first tested two previously mapped QTL with well-defined genomic regions; We then tested additional four studies with known QTL regions; and finally we examined the reliability of QTL in 38 sets of data which are produced from relatively large numbers of RI strains, derived from C57BL/6J (B6 X DBA/2J (D2, known as BXD RI mouse strains; 2 studies with RI strains of rats and plants; and 3 studies using F2 populations in mice, rats and plants. In these cases, our method identified the reliability of mapped QTL and localized the candidate genes into the defined genomic regions. Our data also suggests that LRS score produced by permutation tests does not necessarily confirm the reliability of the QTL. Number of strains are not the reliable indicators for the accuracy of QTL either. Our strategy determines the reliability and accuracy of the genomic region of a QTL without any additional experimental study such as congenic breeding.

  2. Mapping epistasis and environment × QTX interaction based on four -omics genotypes for the detected QTX loci controlling complex traits in tobacco

    Directory of Open Access Journals (Sweden)

    Liyuan Zhou

    2013-12-01

    Full Text Available Using newly developed methods and software, association mapping was conducted for chromium content and total sugar in tobacco leaf, based on four -omics datasets. Our objective was to collect data on genotype and phenotype for 60 leaf samples at four developmental stages, from three plant architectural positions and for three cultivars that were grown in two locations. Association mapping was conducted to detect genetic variants at quantitative trait SNP (QTS loci, quantitative trait transcript (QTT differences, quantitative trait protein (QTP variability, and quantitative trait metabolite (QTM changes, which can be summarized as QTX locus variation. The total heritabilities of the four -omics loci for both traits tested were 23.60% for epistasis and 15.26% for treatment interaction. Epistasis and environment × treatment interaction had important impacts on complex traits at all -omics levels. For decreasing chromium content and increasing total sugar in tobacco leaf, six methylated loci can be directly used for marker-assisted selection, and expression of ten QTTs, seven QTPs and six QTMs can be modified by selection or cultivation.

  3. Identification of quantitative trait loci for cadmium tolerance and accumulation in wheat

    DEFF Research Database (Denmark)

    Ci, Dunwei; Jiang, Dong; Li, Sishen

    2012-01-01

    effects coming from Ch) while the remaining 12 QTLs were negative (with the additive effects contributed by Sh). No QTL were detected in the same region on the chromosomes of wheat. The results indicated that genetic mechanisms controlling the traits of Cd tolerance were independent from each other...

  4. Mapping of quantitative trait loci for oil content in cottonseed kernel

    Indian Academy of Sciences (India)

    related to oil content in both genomes could facilitate the improvement in its quality and quantity. However, till date, QTL mapping and genetic analysis related to this trait in cotton have only been conducted in the tetraploid embryo genome. In the current experiment, an IF2 population of cottonseed kernels from the random ...

  5. Variation in seed dormancy quantitative trait loci in Arabidopsis thaliana originating from one site

    NARCIS (Netherlands)

    Silady, R.A.; Effgen, S.; Koornneef, M.; Reymond, M.

    2011-01-01

    A Quantitative Trait Locus (QTL) analysis was performed using two novel Recombinant Inbred Line (RIL) populations, derived from the progeny between two Arabidopsis thaliana genotypes collected at the same site in Kyoto (Japan) crossed with the reference laboratory strain Landsberg erecta (Ler). We

  6. Basal host resistance of barley to powdery mildew: connecting quantitative trait loci and candidate genes

    NARCIS (Netherlands)

    Aghnoum, R.; Marcel, T.C.; Johrde, A.; Pecchioni, N.; Schweizer, P.; Niks, R.E.

    2010-01-01

    The basal resistance of barley to powdery mildew (Blumeria graminis f. sp. hordei) is a quantitatively inherited trait that is based on nonhypersensitive mechanisms of defense. A functional genomic approach indicates that many plant candidate genes are involved in the defense against formation of

  7. Complex pedigree analysis to detect quantitative trait loci in dairy cattle

    NARCIS (Netherlands)

    Bink, M.C.A.M.

    1998-01-01

    In dairy cattle, many quantitative traits of economic importance show phenotypic variation. For breeding purposes the analysis of this phenotypic variation and uncovering the contribution of genetic factors is very important. Usually, the individual gene effects contributing to the

  8. Comparison of quantitative trait loci for rice yield, panicle length and ...

    Indian Academy of Sciences (India)

    2011-08-19

    Aug 19, 2011 ... segregation of all QTL alleles was not possible because it has few connections ... A total of 694 simple-sequence repeat (SSR) markers that were well ... Teqing allele. All the four QTLs were detected in only one year (figure 1; table 2). For PL trait, five QTLs were detected on chromosomes 2,. 5, 6, 9 and 12.

  9. Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean.

    Science.gov (United States)

    Sonah, Humira; O'Donoughue, Louise; Cober, Elroy; Rajcan, Istvan; Belzile, François

    2015-02-01

    Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  10. Detection of novel quantitative trait loci for cutaneous melanoma by genome-wide scan in the MeLiM swine model

    Czech Academy of Sciences Publication Activity Database

    Du, Z. Q.; Vincent-Naulleau, S.; Gilbert, H.; Vignoles, F.; Créchet, F.; Shimogiri, T.; Yasue, H.; Leplat, J. J.; Bouet, S.; Gruand, J.; Horák, Vratislav; Milan, D.; Le Roy, P.; Geffrotin, C.

    2006-01-01

    Roč. 120, - (2006), s. 303-320 ISSN 0020-7136 Institutional research plan: CEZ:AV0Z50450515 Keywords : swine melanoma * quantitative trait loci * MC1R Subject RIV: FD - Oncology ; Hematology Impact factor: 4.693, year: 2006

  11. Tan spot susceptibility governed by the Tsn1 locus and race-nonspecific resistance quantitative trait loci in a population derived from the wheat lines Salamouni and Katepwa

    Science.gov (United States)

    Wheat-tan spot interactions are known to have an inverse gene-for-gene relationship where pathogen-produced necrotrophic effectors are recognized by host sensitivity genes to cause susceptibility. However, broad-spectrum non race-specific resistance quantitative trait loci (QTL) that do not conform...

  12. Short communication: Genome-wide scan for bovine milk-fat composition. II. Quantitative trait loci for long-chain fatty acids

    NARCIS (Netherlands)

    Schennink, A.; Stoop, W.M.; Visker, M.H.P.W.; Poel, van der J.J.; Bovenhuis, H.; Arendonk, van J.A.M.

    2009-01-01

    We present the results of a genome-wide scan to identify quantitative trait loci (QTL) that contribute to genetic variation in long-chain milk fatty acids. Milk-fat composition phenotypes were available on 1,905 Dutch Holstein-Friesian cows. A total of 849 cows and their 7 sires were genotyped for

  13. Genomewide rapid association using mixed model and regression: A fast and simple method for genomewide pedigree-based quantitative trait loci association analysis

    NARCIS (Netherlands)

    Y.S. Aulchenko (Yurii); D.-J. de Koning; C. Haley (Chris)

    2007-01-01

    textabstractFor pedigree-based quantitative trait loci (QTL) association analysis, a range of methods utilizing within-family variation such as transmission- disequilibrium test (TDT)-based methods have been developed. In scenarios where stratification is not a concern, methods exploiting

  14. Genes and quantitative trait loci (QTL) controlling trace element concentrations in perennial grasses grown on phytotoxic soil contaminated with heavy metals

    Science.gov (United States)

    Perennial grasses cover diverse soils throughout the world, including sites contaminated with heavy metals, producing forages that must be safe for livestock and wildlife. Chromosome regions known as quantitative trait loci (QTLs) controlling forage mineral concentrations were mapped in a populatio...

  15. Do Gender and Personality Traits Influence Awareness of Deal Sites?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2015-01-01

    Deal sites exist for a decade now but there are still some people who have not heard about them. The research pre-sented in the paper investigates if gender and personality traits influence awareness of deal sites. Big Five Inventory-10 is used to measure personality traits. The findings...... are that gender does not influence awareness, and neuroticism is the most significant personality trait influencing awareness of deal sites - the more neurotic the person is, the higher is the probability that he or she has never heard of deal sites....

  16. Do Gender and Personality Traits Influence Use of Deal Sites?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2015-01-01

    Deal sites became widespread, there are numerous both international and local players in the market. The research presented in the paper investigates if gender and personality traits influence use (versus non-use) of deal sites. Big Five Inventory-10 is used to measure personality traits...

  17. Personality Traits among Inmates of Aba Prison in Nigeria: Influence ...

    African Journals Online (AJOL)

    Background: Personality traits are the basic elements in the study of personality and it influences decision making by affecting our choices about whether to engage in different behaviours. Knowledge of the different personality traits among prison inmate is useful as it will assists in the development of interventions and ...

  18. Stability of quantitative trait loci for growth and wood properties across multiple pedigrees and environments in Eucalyptus globulus.

    Science.gov (United States)

    Freeman, Jules S; Potts, Brad M; Downes, Geoffrey M; Pilbeam, David; Thavamanikumar, Saravanan; Vaillancourt, René E

    2013-06-01

    · Eucalypts are one of the most planted tree genera worldwide, and there is increasing interest in marker-assisted selection for tree improvement. Implementation of marker-assisted selection requires a knowledge of the stability of quantitative trait loci (QTLs). This study aims to investigate the stability of QTLs for wood properties and growth across contrasting sites and multiple pedigrees of Eucalyptus globulus. · Saturated linkage maps were constructed using 663 genotypes from four separate families, grown at three widely separated sites, and were employed to construct a consensus map. This map was used for QTL analysis of growth, wood density and wood chemical traits, including pulp yield. · Ninety-eight QTLs were identified across families and sites: 87 for wood properties and 11 for growth. These QTLs mapped to 38 discrete regions, some of which co-located with candidate genes. Although 16% of QTLs were verified across different families, 24% of wood property QTLs and 38% of growth QTLs exhibited significant genotype-by-environment interaction. · This study provides the most detailed assessment of the effect of environment and pedigree on QTL detection in the genus. Despite markedly different environments and pedigrees, many QTLs were stable, providing promising targets for the application of marker-assisted selection. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  19. I.4 Screening Experimental Designs for Quantitative Trait Loci, Association Mapping, Genotype-by Environment Interaction, and Other Investigations.

    Science.gov (United States)

    Federer, Walter T; Crossa, José

    2012-01-01

    Crop breeding programs using conventional approaches, as well as new biotechnological tools, rely heavily on data resulting from the evaluation of genotypes in different environmental conditions (agronomic practices, locations, and years). Statistical methods used for designing field and laboratory trials and for analyzing the data originating from those trials need to be accurate and efficient. The statistical analysis of multi-environment trails (MET) is useful for assessing genotype × environment interaction (GEI), mapping quantitative trait loci (QTLs), and studying QTL × environment interaction (QEI). Large populations are required for scientific study of QEI, and for determining the association between molecular markers and quantitative trait variability. Therefore, appropriate control of local variability through efficient experimental design is of key importance. In this chapter we present and explain several classes of augmented designs useful for achieving control of variability and assessing genotype effects in a practical and efficient manner. A popular procedure for unreplicated designs is the one known as "systematically spaced checks." Augmented designs contain "c" check or standard treatments replicated "r" times, and "n" new treatments or genotypes included once (usually) in the experiment.

  20. Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti

    Energy Technology Data Exchange (ETDEWEB)

    Severson, D.W.; Thathy, V.; Mori, A. [Univ. of Wisconsin, Madison, WI (United States)] [and others

    1995-04-01

    Susceptibility of the mosquito Aedes aegypti to the malarial parasite Plasmodium gallinaceum was investigated as a quantitative trait using restriction fragment length polymorphisms (RFLP). Two F{sub 2} populations of mosquitoes were independently prepared from pairwise matings between a highly susceptible and a refractory strain of A. aegypti. RFLP were tested for association with oocyst development on the mosquito midgut. Two putative quantitative trait loci (QTL) were identified that significantly affect susceptibility. One QTL, pgs [2,LF98], is located on chromosome 2 and accounted for 65 and 49% of the observed phenotypic variance in the two populations, respectively. A second QTL, pgs[3,MalI], is located on chromosome 3 and accounted for 14 and 10% of the observed phenotypic variance in the two populations, respectively. Both QTL exhibit a partial dominance effect on susceptibility, wherein the dominance effect is derived from the refractory parent. No indication of epistasis between these QTL was detected. Evidence suggests that either a tightly linked cluster of independent genes or a single locus affecting susceptibility to various mosquito-borne parasites and pathogens has evolved near the LF98 locus; in addition to P. gallinaceum susceptibility, this general genome region has previously been implicated in susceptibility to the filaria nematode Brugia malayi and the yellow fever virus. 35 refs., 2 figs., 3 tabs.

  1. Identification and Characterization of Quantitative Trait Loci for Shattering in Japonica Rice Landrace Jiucaiqing from Taihu Lake Valley, China

    Directory of Open Access Journals (Sweden)

    Jinping Cheng

    2016-11-01

    Full Text Available Easy shattering reduces yield from grain loss during rice ( L. harvest. We characterized a nonshattering rice landrace Jiucaiqing from Taihu Lake valley in China. The breaking tensile strength (BTS; grams force, gf of the grain pedicel was measured using a digital force gauge to evaluate the degree of shattering at 0, 7, 14, 21, 28, and 35 d after heading (DAH. The BTS of Jiucaiqing did not significantly decrease with increasing DAH, maintaining a level of 152.2 to 195.9 gf, while that of IR26 decreased greatly during 0 to 14 DAH and finally stabilized at ∼100 gf. Then the chromosome segment substitution lines (CSSLs and near isogenic lines (NILs of Jiucaiqing in IR26 background were developed for quantitative trait loci (QTL mapping. Four putative QTL (, , , and for shattering were detected, and the was confirmed on chromosome 1. We further mapped to a 98.4-kb region, which contains 14 genes. Os01g62920 was considered to be a strong candidate for , which colocated with . Further quantitative real-time polymerase chain reaction (PCR analyses confirmed that the QTL can significantly decrease the expression of shattering related genes (, , , , and especially at the middle development stage at 10 and 15 cm panicle length, which causes rice shattering decrease. The elite allele and the NIL with desirable agronomic traits identified in this study could be useful for rice breeding.

  2. An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus).

    Science.gov (United States)

    Ren, Yi; McGregor, Cecilia; Zhang, Yan; Gong, Guoyi; Zhang, Haiying; Guo, Shaogui; Sun, Honghe; Cai, Wantao; Zhang, Jie; Xu, Yong

    2014-01-20

    Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A

  3. An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

    Science.gov (United States)

    2014-01-01

    Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

  4. A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.

    Directory of Open Access Journals (Sweden)

    Schaffer Arthur

    2011-07-01

    Full Text Available Abstract Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L. over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS. Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org, an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability

  5. Bovine Mastitis Resistance: Novel Quantitative Trait Loci and the Role of Bovine Mammary Epithelial Cells

    OpenAIRE

    Kurz, Jacqueline P.

    2018-01-01

    Bovine mastitis, or inflammation of the mammary gland, has substantial economic and animal welfare implications. A genetic basis for mastitis resistance traits is recognized and can be used to guide selective breeding programs. The discovery of regions of the genome associated with mastitis resistance, and knowledge of the underlying molecular mechanisms responsible, can facilitate development of efficient mastitis control and therapeutic strategies. The objectives of this dissertation resear...

  6. Identification of quantitative trait loci associated with boiled seed hardness in soybean

    Science.gov (United States)

    Hirata, Kaori; Masuda, Ryoichi; Tsubokura, Yasutaka; Yasui, Takeshi; Yamada, Tetsuya; Takahashi, Koji; Nagaya, Taiko; Sayama, Takashi; Ishimoto, Masao; Hajika, Makita

    2014-01-01

    Boiled seed hardness is an important factor in the processing of soybean food products such as nimame and natto. Little information is available on the genetic basis for boiled seed hardness, despite the wide variation in this trait. DNA markers linked to the gene controlling this trait should be useful in soybean breeding programs because of the difficulty of its evaluation. In this report, quantitative trait locus (QTL) analysis was performed to reveal the genetic factors associated with boiled seed hardness using a recombinant inbred line population developed from a cross between two Japanese cultivars, ‘Natto-shoryu’ and ‘Hyoukei-kuro 3’, which differ largely in boiled seed hardness, which in ‘Natto-shoryu’ is about twice that of ‘Hyoukei-kuro 3’. Two significantly stable QTLs, qHbs3-1 and qHbs6-1, were identified on chromosomes 3 and 6, for which the ‘Hyoukei-kuro 3’ alleles contribute to decrease boiled seed hardness for both QTLs. qHbs3-1 also showed significant effects in progeny of a residual heterozygous line and in a different segregating population. Given its substantial effect on boiled seed hardness, SSR markers closely linked to qHbs3-1, such as BARCSOYSSR_03_0165 and BARCSOYSSR_03_0185, could be useful for marker-assisted selection in soybean breeding. PMID:25914591

  7. Genetic mapping of quantitative trait loci for aseasonal reproduction in sheep.

    Science.gov (United States)

    Mateescu, R G; Thonney, M L

    2010-10-01

    The productivity and economic prosperity of sheep farming could benefit greatly from more effective methods of selection for year-round lambing. Identification of QTL for aseasonal reproduction in sheep could lead to more accurate selection and faster genetic improvement. One hundred and twenty microsatellite markers were genotyped on 159 backcross ewes from a Dorset × East Friesian crossbred pedigree. Interval mapping was undertaken to map the QTL underlying several traits describing aseasonal reproduction including the number of oestrous cycles, maximum level of progesterone prior to breeding, pregnancy status determined by progesterone level, pregnancy status determined by ultrasound, lambing status and number of lambs born. Seven chromosomes (1, 3, 12, 17, 19, 20 and 24) were identified to harbour putative QTL for one or more component traits used to describe aseasonal reproduction. Ovine chromosomes 12, 17, 19 and 24 harbour QTL significant at the 5% chromosome-wide level, chromosomes 3 and 20 harbour QTL that exceeded the threshold at the 1% chromosome-wide level, while the QTL identified on chromosome 1 exceeded the 1% experiment-wide significance level. These results are a first step towards understanding the genetic mechanism of this complex trait and show that variation in aseasonal reproduction is associated with multiple chromosomal regions. © 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.

  8. Quantitative trait loci for bone lengths on chromosome 5 using dual energy X-Ray absorptiometry imaging in the Twins UK cohort.

    Directory of Open Access Journals (Sweden)

    Usha Chinappen-Horsley

    Full Text Available Human height is a highly heritable and complex trait but finding important genes has proven more difficult than expected. One reason might be the composite measure of height which may add heterogeneity and noise. The aim of this study was to conduct a genome-wide linkage scan to identify quantitative trait loci (QTL for lengths of spine, femur, tibia, humerus and radius. These were investigated as alternative measures for height in a large, population-based twin sample with the potential to find genes underlying bone size and bone diseases. 3,782 normal Caucasian females, 18-80 years old, with whole body dual energy X-ray absorptiometry (DXA images were used. A novel and reproducible method, linear pixel count (LPC was used to measure skeletal sizes on DXA images. Intraclass correlations and heritability estimates were calculated for lengths of spine, femur, tibia, humerus and radius on monozygotic (MZ; n = 1,157 and dizygotic (DZ; n = 2,594 twins. A genome-wide linkage scan was performed on 2000 DZ twin subjects. All skeletal sites excluding spine were highly correlated. Intraclass correlations showed results for MZ twins to be significantly higher than DZ twins for all traits. Heritability results were as follows: spine, 66%; femur, 73%; tibia, 65%; humerus, 57%; radius, 68%. Results showed reliable evidence of highly suggestive linkage on chromosome 5 for spine (LOD score = 3.0 and suggestive linkage for femur (LOD score = 2.19 in the regions of 105cM and 155cM respectively. We have shown strong heritability of all skeletal sizes measured in this study and provide preliminary evidence that spine length is linked to the chromosomal region 5q15-5q23.1. Bone size phenotype appears to be more useful than traditional height measures to uncover novel genes. Replication and further fine mapping of this region is ongoing to determine potential genes influencing bone size and diseases affecting bone.

  9. Genome-wide association scan meta-analysis identifies three loci influencing adiposity and fat distribution

    NARCIS (Netherlands)

    C.M. Lindgren (Cecilia); I.M. Heid (Iris); J.C. Randall (Joshua); C. Lamina (Claudia); V. Steinthorsdottir (Valgerdur); L. Qi (Lu); E.K. Speliotes (Elizabeth); G. Thorleifsson (Gudmar); C.J. Willer (Cristen); B.M. Herrera (Blanca); A.U. Jackson (Anne); N. Lim (Noha); P. Scheet (Paul); N. Soranzo (Nicole); N. Amin (Najaf); Y.S. Aulchenko (Yurii); J.C. Chambers (John); A. Drong (Alexander); J. Luan; H.N. Lyon (Helen); F. Rivadeneira Ramirez (Fernando); S. Sanna (Serena); N.J. Timpson (Nicholas); M.C. Zillikens (Carola); H.Z. Jing; P. Almgren (Peter); S. Bandinelli (Stefania); A.J. Bennett (Amanda); R.N. Bergman (Richard); L.L. Bonnycastle (Lori); S. Bumpstead (Suzannah); S.J. Chanock (Stephen); L. Cherkas (Lynn); P.S. Chines (Peter); L. Coin (Lachlan); C. Cooper (Charles); G. Crawford (Gabe); A. Doering (Angela); A. Dominiczak (Anna); A.S.F. Doney (Alex); S. Ebrahim (Shanil); P. Elliott (Paul); M.R. Erdos (Michael); K. Estrada Gil (Karol); L. Ferrucci (Luigi); G. Fischer (Guido); N.G. Forouhi (Nita); C. Gieger (Christian); H. Grallert (Harald); C.J. Groves (Christopher); S.M. Grundy (Scott); C. Guiducci (Candace); D. Hadley (David); A. Hamsten (Anders); A.S. Havulinna (Aki); A. Hofman (Albert); R. Holle (Rolf); J.W. Holloway (John); T. Illig (Thomas); B. Isomaa (Bo); L.C. Jacobs (Leonie); K. Jameson (Karen); P. Jousilahti (Pekka); F. Karpe (Fredrik); J. Kuusisto (Johanna); J. Laitinen (Jaana); G.M. Lathrop (Mark); D.A. Lawlor (Debbie); M. Mangino (Massimo); W.L. McArdle (Wendy); T. Meitinger (Thomas); M.A. Morken (Mario); A.P. Morris (Andrew); P. Munroe (Patricia); N. Narisu (Narisu); A. Nordström (Anna); B.A. Oostra (Ben); C.N.A. Palmer (Colin); F. Payne (Felicity); J. Peden (John); I. Prokopenko (Inga); F. Renström (Frida); A. Ruokonen (Aimo); V. Salomaa (Veikko); M.S. Sandhu (Manjinder); L.J. Scott (Laura); A. Scuteri (Angelo); K. Silander (Kaisa); K. Song (Kijoung); X. Yuan (Xin); H.M. Stringham (Heather); A.J. Swift (Amy); T. Tuomi (Tiinamaija); M. Uda (Manuela); P. Vollenweider (Peter); G. Waeber (Gérard); C. Wallace (Chris); G.B. Walters (Bragi); M.N. Weedon (Michael); J.C.M. Witteman (Jacqueline); C. Zhang (Cuilin); M. Caulfield (Mark); F.S. Collins (Francis); G.D. Smith; I.N.M. Day (Ian); P.W. Franks (Paul); A.T. Hattersley (Andrew); F.B. Hu (Frank); M.-R. Jarvelin (Marjo-Riitta); A. Kong (Augustine); J.S. Kooner (Jaspal); M. Laakso (Markku); E. Lakatta (Edward); V. Mooser (Vincent); L. Peltonen (Leena Johanna); N.J. Samani (Nilesh); T.D. Spector (Timothy); D.P. Strachan (David); T. Tanaka (Toshiko); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); P. Tikka-Kleemola (Päivi); N.J. Wareham (Nick); H. Watkins (Hugh); D. Waterworth (Dawn); M. Boehnke (Michael); P. Deloukas (Panagiotis); L. Groop (Leif); D.J. Hunter (David); U. Thorsteinsdottir (Unnur); D. Schlessinger (David); H.E. Wichmann (Erich); T.M. Frayling (Timothy); G.R. Abecasis (Gonçalo); J.N. Hirschhorn (Joel); R.J.F. Loos (Ruth); J-A. Zwart (John-Anker); K.L. Mohlke (Karen); I. Barroso (Inês); M.I. McCarthy (Mark)

    2009-01-01

    textabstractTo identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the

  10. Genome-wide association study identifies 22 new loci for body dimension and body weight traits in a White Duroc×Erhualian F intercross population

    Directory of Open Access Journals (Sweden)

    Jiuxiu Ji

    2017-08-01

    Full Text Available Objective Growth-related traits are important economic traits in the swine industry. However, the genetic mechanism of growth-related traits is little known. The aim of this study was to screen the candidate genes and molecular markers associated with body dimension and body weight traits in pigs. Methods A genome-wide association study (GWAS on body dimension and body weight traits was performed in a White Duroc×Erhualian F2 intercross by the illumina PorcineSNP60K Beadchip. A mixed linear model was used to assess the association between single nucleotide polymorphisms (SNPs and the phenotypes. Results In total, 611 and 79 SNPs were identified significantly associated with body dimension traits and body weight respectively. All SNPs but 62 were located into 23 genomic regions (quantitative trait loci, QTLs on 14 autosomal and X chromosomes in Sus scrofa Build 10.2 assembly. Out of the 23 QTLs with the suggestive significance level (5×10−4, three QTLs exceeded the genome-wide significance threshold (1.15×10−6. Except the one on Sus scrofa chromosome (SSC 7 which was reported previously all the QTLs are novel. In addition, we identified 5 promising candidate genes, including cell division cycle 7 for abdominal circumference, pleiomorphic adenoma gene 1 and neuropeptides B/W receptor 1 for both body weight and cannon bone circumference on SSC4, phosphoenolpyruvate carboxykinase 1, and bone morphogenetic protein 7 for hip circumference on SSC17. Conclusion The results have not only demonstrated a number of potential genes/loci associated with the growth-related traits in pigs, but also laid a foundation for studying the genes’ role and further identifying causative variants underlying these loci.

  11. Identification of quantitative trait loci for body temperature, body weight, breast yield, and digestibility in an advanced intercross line of chickens under heat stress.

    Science.gov (United States)

    Van Goor, Angelica; Bolek, Kevin J; Ashwell, Chris M; Persia, Mike E; Rothschild, Max F; Schmidt, Carl J; Lamont, Susan J

    2015-12-17

    Losses in poultry production due to heat stress have considerable negative economic consequences. Previous studies in poultry have elucidated a genetic influence on response to heat. Using a unique chicken genetic resource, we identified genomic regions associated with body temperature (BT), body weight (BW), breast yield, and digestibility measured during heat stress. Identifying genes associated with a favorable response during high ambient temperature can facilitate genetic selection of heat-resilient chickens. Generations F18 and F19 of a broiler (heat-susceptible) × Fayoumi (heat-resistant) advanced intercross line (AIL) were used to fine-map quantitative trait loci (QTL). Six hundred and thirty-one birds were exposed to daily heat cycles from 22 to 28 days of age, and phenotypes were measured before heat treatment, on the 1st day and after 1 week of heat treatment. BT was measured at these three phases and BW at pre-heat treatment and after 1 week of heat treatment. Breast muscle yield was calculated as the percentage of BW at day 28. Ileal feed digestibility was assayed from digesta collected from the ileum at day 28. Four hundred and sixty-eight AIL were genotyped using the 600 K Affymetrix chicken SNP (single nucleotide polymorphism) array. Trait heritabilities were estimated using an animal model. A genome-wide association study (GWAS) for these traits and changes in BT and BW was conducted using Bayesian analyses. Candidate genes were identified within 200-kb regions around SNPs with significant association signals. Heritabilities were low to moderate (0.03 to 0.35). We identified QTL for BT on Gallus gallus chromosome (GGA)14, 15, 26, and 27; BW on GGA1 to 8, 10, 14, and 21; dry matter digestibility on GGA19, 20 and 21; and QTL of very large effect for breast muscle yield on GGA1, 15, and 22 with a single 1-Mb window on GGA1 explaining more than 15% of the genetic variation. This is the first study to estimate heritabilities and perform GWAS using this

  12. Molecular mapping reveals structural rearrangements and quantitative trait loci underlying traits with local adaptation in semi-wild Xishuangbanna cucumber (Cucumis sativus L. var. xishuangbannanesis Qi et Yuan).

    Science.gov (United States)

    Bo, Kailiang; Ma, Zheng; Chen, Jinfeng; Weng, Yiqun

    2015-01-01

    Comparative genetic mapping revealed the origin of Xishuangbanna cucumber through diversification selection after domestication. QTL mapping provided insights into the genetic basis of traits under diversification selection during crop evolution. The Xishuangbanna cucumber, Cucumis sativus L. var. xishuangbannanesis Qi et Yuan (XIS), is a semi-wild landrace from the tropical southwest China with some unique traits that are very useful for cucumber breeding, such as tolerance to low light, large fruit size, heavy fruit weight, and orange flesh color in mature fruits. In this study, using 124 recombinant inbred lines (RILs) derived from the cross of the XIS cucumber with a cultivated cucumber inbred line, we developed a linkage map with 269 microsatellite (or simple sequence repeat) markers which covered 705.9 cM in seven linkage groups. Comparative analysis of orders of common marker loci or marker-anchored draft genome scaffolds among the wild (C. sativus var. hardwickii), semi-wild, and cultivated cucumber genetic maps revealed that the XIS cucumber shares major chromosomal rearrangements in chromosomes 4, 5, and 7 between the wild and cultivated cucumbers suggesting that the XIS cucumber originated through diversifying selection after cucumber domestication. Several XIS-specific minor structural changes were identified in chromosomes 1 and 6. QTL mapping with the 124 RILs in four environments identified 13 QTLs for domestication and diversifying selection-related traits including 2 for first female flowering time (fft1.1, fft6.1), 5 for mature fruit length (fl1.1, fl3.1, fl4.1, fl6.1, and fl7.1), 3 for fruit diameter (fd1.1, fd4.1, and fd6.1), and 3 for fruit weight (fw2.1, fw4.1, and fw6.1). Six of the 12 QTLs were consistently detected in all four environments. Among the 13 QTLs, fft1.1, fl1.1, fl3.1, fl7.1, fd4.1, and fw6.1 were major-effect QTLs for respective traits with each explaining at least 10 % of the observed phenotypic variations. Results from this

  13. Psychopathic Traits Moderate Peer Influence on Adolescent Delinquency

    Science.gov (United States)

    Kerr, Margaret; Van Zalk, Maarten; Stattin, Hakan

    2012-01-01

    Background: Peer influence on adolescent delinquency is well established, but little is known about moderators of peer influence. In this study, we examined adolescents' (targets) and their peers' psychopathic personality traits as moderators of peer influence on delinquency in peer networks. We used three separate dimensions of the psychopathic…

  14. A genome scan for quantitative trait loci affecting the Salmonella carrier-state in the chicken

    Directory of Open Access Journals (Sweden)

    Bumstead Nat

    2005-09-01

    Full Text Available Abstract Selection for increased resistance to Salmonella colonisation and excretion could reduce the risk of foodborne Salmonella infection. In order to identify potential loci affecting resistance, differences in resistance were identified between the N and 61 inbred lines and two QTL research performed. In an F2 cross, the animals were inoculated at one week of age with Salmonella enteritidis and cloacal swabs were carried out 4 and 5 wk post inoculation (thereafter called CSW4F2 and CSW4F2 and caecal contamination (CAECF2 was assessed 1 week later. The animals from the (N × 61 × N backcross were inoculated at six weeks of age with Salmonella typhimurium and cloacal swabs were studied from wk 1 to 4 (thereafter called CSW1BC to CSW4BC. A total of 33 F2 and 46 backcross progeny were selectively genotyped for 103 and 135 microsatellite markers respectively. The analysis used least-squares-based and non-parametric interval mapping. Two genome-wise significant QTL were observed on Chromosome 1 for CSW2BC and on Chromosome 2 for CSW4F2, and four suggestive QTL for CSW5F2 on Chromosome 2, for CSW5F2 and CSW2BC on chromosome 5 and for CAECF2 on chromosome 16. These results suggest new regions of interest and the putative role of SAL1.

  15. Identification of quantitative trait loci for ABA sensitivity at seed germination and seedling stages in rice.

    Science.gov (United States)

    You, Jun; Li, Qiang; Yue, Bing; Xue, Wei-Ya; Luo, Li-Jun; Xiong, Li-Zhong

    2006-06-01

    Abscisic acid (ABA) is one of the important plant hormones, which plays a critical role in seed development and adaptation to abiotic stresses. The sensitivity of rice (Oryza sativa L.) to exogenous ABA at seed germination and seedling stages was investigated in the recombinant inbred line (RIL) population derived from a cross between irrigated rice Zhenshan 97 and upland rice IRAT109, using relative germination vigor (RGV), relative germination rate (RGR) and leaf rolling scores of spraying (LRS) or culturing (LRC) with ABA as sensitivity indexes. The phenotypic correlation analysis revealed that only RGV at germination stage was positively correlated to ABA sensitivity at seedling stage. QTL detection using composite interval mapping (CIM) and mixed linear model was conducted to dissect the genetic basis of ABA sensitivity, and the single-locus QTLs detected by both methods are in good agreement with each other. Five single QTLs and six pairs of epistatic QTLs were detected for ABA sensitivity at germination stage. Eight single QTLs and five pairs of epistatic QTLs were detected for ABA sensitivity at seedling stage. Two QTLs were common between LRS and LRC; and one common QTL was detected for RGV, LRS and LRC simultaneously. These results indicated that both single and epistatic loci were involved in the ABA sensitivity in rice, and the genetic basis of ABA sensitivity at seed germination and seedling stage was largely different.

  16. Identification and mapping of leaf, stem and stripe rust resistance quantitative trait loci and their interactions in durum wheat.

    Science.gov (United States)

    Singh, A; Pandey, M P; Singh, A K; Knox, R E; Ammar, K; Clarke, J M; Clarke, F R; Singh, R P; Pozniak, C J; Depauw, R M; McCallum, B D; Cuthbert, R D; Randhawa, H S; Fetch, T G

    2013-02-01

    Leaf rust (Puccinia triticina Eriks.), stripe rust (Puccinia striiformis f. tritici Eriks.) and stem rust (Puccinia graminis f. sp. tritici) cause major production losses in durum wheat (Triticum turgidum L. var. durum). The objective of this research was to identify and map leaf, stripe and stem rust resistance loci from the French cultivar Sachem and Canadian cultivar Strongfield. A doubled haploid population from Sachem/Strongfield and parents were phenotyped for seedling reaction to leaf rust races BBG/BN and BBG/BP and adult plant response was determined in three field rust nurseries near El Batan, Obregon and Toluca, Mexico. Stripe rust response was recorded in 2009 and 2011 nurseries near Toluca and near Njoro, Kenya in 2010. Response to stem rust was recorded in field nurseries near Njoro, Kenya, in 2010 and 2011. Sachem was resistant to leaf, stripe and stem rust. A major leaf rust quantitative trait locus (QTL) was identified on chromosome 7B at Xgwm146 in Sachem. In the same region on 7B, a stripe rust QTL was identified in Strongfield. Leaf and stripe rust QTL around DArT marker wPt3451 were identified on chromosome 1B. On chromosome 2B, a significant leaf rust QTL was detected conferred by Strongfield, and at the same QTL, a Yr gene derived from Sachem conferred resistance. Significant stem rust resistance QTL were detected on chromosome 4B. Consistent interactions among loci for resistance to each rust type across nurseries were detected, especially for leaf rust QTL on 7B. Sachem and Strongfield offer useful sources of rust resistance genes for durum rust breeding.

  17. Quantitative trait loci for lodging resistance, plant height and partial resistance to mycosphaerella blight in field pea (Pisum sativum L.).

    Science.gov (United States)

    Tar'an, B; Warkentin, T; Somers, D J; Miranda, D; Vandenberg, A; Blade, S; Woods, S; Bing, D; Xue, A; DeKoeyer, D; Penner, G

    2003-11-01

    With the development of genetic maps and the identification of the most-likely positions of quantitative trait loci (QTLs) on these maps, molecular markers for lodging resistance can be identified. Consequently, marker-assisted selection (MAS) has the potential to improve the efficiency of selection for lodging resistance in a breeding program. This study was conducted to identify genetic loci associated with lodging resistance, plant height and reaction to mycosphaerella blight in pea. A population consisting of 88 recombinant inbred lines (RILs) was developed from a cross between Carneval and MP1401. The RILs were evaluated in 11 environments across the provinces of Manitoba, Saskatchewan and Alberta, Canada in 1998, 1999 and 2000. One hundred and ninety two amplified fragment length polymorphism (AFLP) markers, 13 random amplified polymorphic DNA (RAPD) markers and one sequence tagged site (STS) marker were assigned to ten linkage groups (LGs) that covered 1,274 centi Morgans (cM) of the pea genome. Six of these LGs were aligned with the previous pea map. Two QTLs were identified for lodging resistance that collectively explained 58% of the total phenotypic variation in the mean environment. Three QTLs were identified each for plant height and resistance to mycosphaerella blight, which accounted for 65% and 36% of the total phenotypic variation, respectively, in the mean environment. These QTLs were relatively consistent across environments. The AFLP marker that was associated with the major locus for lodging resistance was converted into the sequence-characterized amplified-region (SCAR) marker. The presence or absence of the SCAR marker corresponded well with the lodging reaction of 50 commercial pea varieties.

  18. Systems genomics study reveals expression quantitative trait loci, regulator genes and pathways associated with boar taint in pigs.

    Directory of Open Access Journals (Sweden)

    Markus Drag

    Full Text Available Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed to identify expression quantitative trait loci (eQTLs with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS were slaughtered at ~100 kg. Gene expression profiles were obtained by RNA-Seq, and genotype data were obtained by an Illumina 60K Porcine SNP chip. Following quality control and filtering, 10,545 and 12,731 genes from liver and testis were included in the eQTL analysis, together with 20,827 SNP variants. A total of 205 and 109 single-tissue eQTLs associated with 102 and 58 unique genes were identified in liver and testis, respectively. By employing a multivariate Bayesian hierarchical model, 26 eQTLs were identified as significant multi-tissue eQTLs. The highest densities of eQTLs were found on pig chromosomes SSC12, SSC1, SSC13, SSC9 and SSC14. Functional characterisation of eQTLs revealed functions within regulation of androgen and the intracellular steroid hormone receptor signalling pathway and of xenobiotic metabolism by cytochrome P450 system and cellular response to oestradiol. A QTL enrichment test revealed 89 QTL traits curated by the Animal Genome PigQTL database to be significantly overlapped by the genomic coordinates of cis-acting eQTLs. Finally, a subset of 35 cis-acting eQTLs overlapped with known boar taint QTL traits. These eQTLs could be useful in the development of a DNA test for boar taint but careful monitoring of other overlapping QTL traits should be performed to avoid any negative consequences of selection.

  19. A cautionary note on ignoring polygenic background when mapping quantitative trait loci via recombinant congenic strains.

    Science.gov (United States)

    Loredo-Osti, J Concepción

    2014-01-01

    In gene mapping, it is common to test for association between the phenotype and the genotype at a large number of loci, i.e., the same response variable is used repeatedly to test a large number of non-independent and non-nested hypotheses. In many of these genetic problems, the underlying model is a mixed model consistent of one or very few major genes concurrently with a genetic background effect, usually thought as of polygenic nature and, consequently, modeled through a random effects term with a well-defined covariance structure dependent upon the kinship between individuals. Either because the interest lies only on the major genes or to simplify the analysis, it is habitual to drop the random effects term and use a simple linear regression model, sometimes complemented with testing via resampling as an attempt to minimize the consequences of this practice. Here, it is shown that dropping the random effects term has not only extreme negative effects on the control of the type I error rate, but it is also unlikely to be fixed by resampling because, whenever the mixed model is correct, this practice does not allow to meet some basic requirements of resampling in a gene mapping context. Furthermore, simulations show that the type I error rates when the random term is ignored can be unacceptably high. As an alternative, this paper introduces a new bootstrap procedure to handle the specific case of mapping by using recombinant congenic strains under a linear mixed model. A simulation study showed that the type I error rates of the proposed procedure are very close to the nominal ones, although they tend to be slightly inflated for larger values of the random effects variance. Overall, this paper illustrates the extent of the adverse consequences of ignoring random effects term due to polygenic factors while testing for genetic linkage and warns us of potential modeling issues whenever simple linear regression for a major gene yields multiple significant linkage

  20. Location of Vibrio anguillarum resistance-associated trait loci in half-smooth tongue sole Cynoglossus semilaevis at its microsatellite linkage map

    Science.gov (United States)

    Tang, Zhihong; Guo, Li; Liu, Yang; Shao, Changwei; Chen, Songlin; Yang, Guanpin

    2016-11-01

    A cultured female half-smooth tongue sole ( Cynoglossus semilaevis) was crossed with a wild male, yielding the first filial generation of pseudo-testcrossing from which 200 fish were randomly selected to locate the Vibrio anguillarum resistance trait in half-smooth tongue sole at its microsatellite linkage map. In total, 129 microsatellites were arrayed into 18 linkage groups, ≥4 each. The map reconstructed was 852.85 cM in length with an average spacing of 7.68 cM, covering 72.07% of that expected (1 183.35 cM). The V. anguillarum resistance trait was a composite rather than a unit trait, which was tentatively partitioned into Survival time in Hours After V. anguillarum Infection (SHAVI) and Immunity of V. Anguillarum Infection (IVAI). Above a logarithm of the odds (LOD) threshold of 2.5, 18 loci relative to SHAVI and 3 relative to IVAI were identified. The 3 loci relative to IVAI explained 18.78%, 5.87% and 6.50% of the total phenotypic variation in immunity. The microsatellites bounding the 3 quantitative trait loci (QTLs) of IVAI may in future aid to the selection of V. anguillarum-immune half-smooth tongue sole varieties, and facilitate cloning the gene(s) controlling such immunity.

  1. A Conceptual Framework for Mapping Quantitative Trait Loci Regulating Ontogenetic Allometry

    Science.gov (United States)

    Li, Hongying; Huang, Zhongwen; Gai, Junyi; Wu, Song; Zeng, Yanru; Li, Qin; Wu, Rongling

    2007-01-01

    Although ontogenetic changes in body shape and its associated allometry has been studied for over a century, essentially nothing is known about their underlying genetic and developmental mechanisms. One of the reasons for this ignorance is the unavailability of a conceptual framework to formulate the experimental design for data collection and statistical models for data analyses. We developed a framework model for unraveling the genetic machinery for ontogenetic changes of allometry. The model incorporates the mathematical aspects of ontogenetic growth and allometry into a maximum likelihood framework for quantitative trait locus (QTL) mapping. As a quantitative platform, the model allows for the testing of a number of biologically meaningful hypotheses to explore the pleiotropic basis of the QTL that regulate ontogeny and allometry. Simulation studies and real data analysis of a live example in soybean have been performed to investigate the statistical behavior of the model and validate its practical utilization. The statistical model proposed will help to study the genetic architecture of complex phenotypes and, therefore, gain better insights into the mechanistic regulation for developmental patterns and processes in organisms. PMID:18043752

  2. Identification of major quantitative trait loci for root diameter in synthetic hexaploid wheat under phosphorus-deficient conditions.

    Science.gov (United States)

    Wu, Fangkun; Yang, Xilan; Wang, Zhiqiang; Deng, Mei; Ma, Jian; Chen, Guoyue; Wei, Yuming; Liu, Yaxi

    2017-11-01

    Synthetic hexaploid wheat (SHW) possesses numerous genes for resistance to stress, including phosphorus (P) deficiency. Root diameter (RDM) plays an important role in P-deficiency tolerance, but information related to SHW is still limited. Thus, the objective of this study was to investigate the genetic architecture of RDM in SHW under P-deficient conditions. To this end, we measured the RDM of 138 F 9 recombinant inbred lines derived from an F 2 population of a synthetic hexaploid wheat line (SHW-L1) and a common wheat line (Chuanmai32) under two P conditions, P sufficiency (PS) and P deficiency (PD), and mapped quantitative trait loci (QTL) for RDM using an enriched high-density genetic map, containing 120,370 single nucleotide polymorphisms, 733 diversity arrays technology markers, and 119 simple sequence repeats. We identified seven RDM QTL for P-deficiency tolerance that individually explained 11-14.7% of the phenotypic variation. Five putative candidate genes involved in root composition, energy supply, and defense response were predicted. Overall, our results provided essential information for cloning genes related to P-deficiency tolerance in common wheat that might help in breeding P-deficiency-tolerant wheat cultivars.

  3. Identifying Quantitative Trait Loci (QTLs) and Developing Diagnostic Markers Linked to Orange Rust Resistance in Sugarcane (Saccharum spp.).

    Science.gov (United States)

    Yang, Xiping; Islam, Md S; Sood, Sushma; Maya, Stephanie; Hanson, Erik A; Comstock, Jack; Wang, Jianping

    2018-01-01

    Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of table sugar used in the world and has become a promising feedstock for biofuel production. Sugarcane production has been threatened by many diseases, and fungicide applications for disease control have been opted out for sustainable agriculture. Orange rust is one of the major diseases impacting sugarcane production worldwide. Identifying quantitative trait loci (QTLs) and developing diagnostic markers are valuable for breeding programs to expedite release of superior sugarcane cultivars for disease control. In this study, an F 1 segregating population derived from a cross between two hybrid sugarcane clones, CP95-1039 and CP88-1762, was evaluated for orange rust resistance in replicated trails. Three QTLs controlling orange rust resistance in sugarcane (qORR109, qORR4 and qORR102) were identified for the first time ever, which can explain 58, 12 and 8% of the phenotypic variation, separately. We also characterized 1,574 sugarcane putative resistance ( R ) genes. These sugarcane putative R genes and simple sequence repeats in the QTL intervals were further used to develop diagnostic markers for marker-assisted selection of orange rust resistance. A PCR-based Resistance gene-derived maker, G1 was developed, which showed significant association with orange rust resistance. The putative QTLs and marker developed in this study can be effectively utilized in sugarcane breeding programs to facilitate the selection process, thus contributing to the sustainable agriculture for orange rust disease control.

  4. Uncovering tomato quantitative trait loci and candidate genes for fruit cuticular lipid composition using the Solanum pennellii introgression line population.

    Science.gov (United States)

    Fernandez-Moreno, Josefina-Patricia; Levy-Samoha, Dorit; Malitsky, Sergey; Monforte, Antonio J; Orzaez, Diego; Aharoni, Asaph; Granell, Antonio

    2017-05-17

    The cuticle is a specialized cell wall layer that covers the outermost surface of the epidermal cells and has important implications for fruit permeability and pathogen susceptibility. In order to decipher the genetic control of tomato fruit cuticle composition, an introgression line (IL) population derived from a biparental cross between Solanum pennellii (LA0716) and the Solanum lycopersicum cultivar M82 was used to build a first map of associated quantitative trait loci (QTLs). A total of 24 cuticular waxes and 26 cutin monomers were determined. They showed changes associated with 18 genomic regions distributed in nine chromosomes affecting 19 ILs. Out of the five main fruit cuticular components described for the wild species S. pennellii, three of them were associated with IL3.4, IL12.1, and IL7.4.1, causing an increase in n-alkanes (≥C30), a decrease in amyrin content, and a decrease in cuticle thickness of ~50%, respectively. Moreover, we also found a QTL associated with increased levels of amyrins in IL3.4. In addition, we propose some candidate genes on the basis of their differential gene expression and single nucleotide polymorphism variability between the introgressed and the recurrent alleles, which will be the subjects of further investigation. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  5. Quantitative Trait Loci from Two Genotypes of Oat (Avena sativa) Conditioning Resistance to Puccinia coronata.

    Science.gov (United States)

    Babiker, Ebrahiem M; Gordon, Tyler C; Jackson, Eric W; Chao, Shiaoman; Harrison, Stephen A; Carson, Martin L; Obert, Don E; Bonman, J Michael

    2015-02-01

    Developing oat cultivars with partial resistance to crown rust would be beneficial and cost-effective for disease management. Two recombinant inbred-line populations were generated by crossing the susceptible cultivar Provena with two partially resistant sources, CDC Boyer and breeding line 94197A1-9-2-2-2-5. A third mapping population was generated by crossing the partially resistant sources to validate the quantitative trait locus (QTL) results. The three populations were evaluated for crown rust severity in the field at Louisiana State University (LSU) in 2009 and 2010 and at the Cereal Disease Laboratory (CDL) in St. Paul, MN, in 2009, 2010, and 2011. An iSelect platform assay containing 5,744 oat single nucleotide polymorphisms was used to genotype the populations. From the 2009 CDL test, linkage analyses revealed two QTLs for partial resistance in the Provena/CDC Boyer population on chromosome 19A. One of the 19A QTLs was also detected in the 2009 LSU test. Another QTL was detected on chromosome 12D in the CDL 2009 test. In the Provena/94197A1-9-2-2-2-5 population, only one QTL was detected, on chromosome 13A, in the CDL 2011 test. The 13A QTL from the Provena/94197A1-9-2-2-2-5 population was validated in the CDC Boyer/94197A1-9-2-2-2-5 population in the CDL 2010 and 2011 tests. Comparative analysis of the significant marker sequences with the rice genome database revealed 15 candidate genes for disease resistance on chromosomes 4 and 6 of rice. These genes could be potential targets for cloning from the two resistant parents.

  6. Dissecting quantitative trait loci for boron efficiency across multiple environments in Brassica napus.

    Directory of Open Access Journals (Sweden)

    Zunkang Zhao

    Full Text Available High yield is the most important goal in crop breeding, and boron (B is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC were identified under low and normal B conditions, singly explaining 4.15-23.16% and 0.53-14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27-4.95% and 1.17-3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS.

  7. Dissecting Quantitative Trait Loci for Boron Efficiency across Multiple Environments in Brassica napus

    Science.gov (United States)

    Zhao, Zunkang; Wu, Likun; Nian, Fuzhao; Ding, Guangda; Shi, Taoxiong; Zhang, Didi; Shi, Lei; Xu, Fangsen; Meng, Jinling

    2012-01-01

    High yield is the most important goal in crop breeding, and boron (B) is an essential micronutrient for plants. However, B deficiency, leading to yield decreases, is an agricultural problem worldwide. Brassica napus is one of the most sensitive crops to B deficiency, and considerable genotypic variation exists among different cultivars in response to B deficiency. To dissect the genetic basis of tolerance to B deficiency in B. napus, we carried out QTL analysis for seed yield and yield-related traits under low and normal B conditions using the double haploid population (TNDH) by two-year and the BQDH population by three-year field trials. In total, 80 putative QTLs and 42 epistatic interactions for seed yield, plant height, branch number, pod number, seed number, seed weight and B efficiency coefficient (BEC) were identified under low and normal B conditions, singly explaining 4.15–23.16% and 0.53–14.38% of the phenotypic variation. An additive effect of putative QTLs was a more important controlling factor than the additive-additive effect of epistatic interactions. Four QTL-by-environment interactions and 7 interactions between epistatic interactions and the environment contributed to 1.27–4.95% and 1.17–3.68% of the phenotypic variation, respectively. The chromosome region on A2 of SYLB-A2 for seed yield under low B condition and BEC-A2 for BEC in the two populations was equivalent to the region of a reported major QTL, BE1. The B. napus homologous genes of Bra020592 and Bra020595 mapped to the A2 region and were speculated to be candidate genes for B efficiency. These findings reveal the complex genetic basis of B efficiency in B. napus. They provide a basis for the fine mapping and cloning of the B efficiency genes and for breeding B-efficient cultivars by marker-assisted selection (MAS). PMID:23028855

  8. Identification of stable quantitative trait loci (QTLs) for fiber quality traits across multiple environments in Gossypium hirsutum recombinant inbred line population.

    Science.gov (United States)

    Jamshed, Muhammad; Jia, Fei; Gong, Juwu; Palanga, Koffi Kibalou; Shi, Yuzhen; Li, Junwen; Shang, Haihong; Liu, Aiying; Chen, Tingting; Zhang, Zhen; Cai, Juan; Ge, Qun; Liu, Zhi; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Or Rashid, Harun; Sarfraz, Zareen; Hassan, Murtaza; Gong, Wankui; Yuan, Youlu

    2016-03-08

    The identification of quantitative trait loci (QTLs) that are stable and consistent across multiple environments and populations plays an essential role in marker-assisted selection (MAS). In the present study, we used 28,861 simple sequence repeat (SSR) markers, which included 12,560 Gossypium raimondii (D genome) sequence-based SSR markers to identify polymorphism between two upland cotton strains 0-153 and sGK9708. A total of 851 polymorphic primers were finally selected and used to genotype 196 recombinant inbred lines (RIL) derived from a cross between 0 and 153 and sGK9708 and used to construct a linkage map. The RIL population was evaluated for fiber quality traits in six locations in China for five years. Stable QTLs identified in this intraspecific cross could be used in future cotton breeding program and with fewer obstacles. The map covered a distance of 4,110 cM, which represents about 93.2 % of the upland cotton genome, and with an average distance of 5.2 cM between adjacent markers. We identified 165 QTLs for fiber quality traits, of which 47 QTLs were determined to be stable across multiple environments. Most of these QTLs aggregated into clusters with two or more traits. A total of 30 QTL clusters were identified which consisted of 103 QTLs. Sixteen clusters in the At sub-genome comprised 44 QTLs, whereas 14 clusters in the Dt sub-genome that included 59 QTLs for fiber quality were identified. Four chromosomes, including chromosome 4 (c4), c7, c14, and c25 were rich in clusters harboring 5, 4, 5, and 6 clusters respectively. A meta-analysis was performed using Biomercator V4.2 to integrate QTLs from 11 environmental datasets on the RIL populations of the above mentioned parents and previous QTL reports. Among the 165 identified QTLs, 90 were identified as common QTLs, whereas the remaining 75 QTLs were determined to be novel QTLs. The broad sense heritability estimates of fiber quality traits were high for fiber length (0.93), fiber strength (0

  9. Quantitative trait loci involved in sex determination and body growth in the gilthead sea bream (Sparus aurata L. through targeted genome scan.

    Directory of Open Access Journals (Sweden)

    Dimitrios Loukovitis

    Full Text Available Among vertebrates, teleost fish exhibit a considerably wide range of sex determination patterns that may be influenced by extrinsic parameters. However even for model fish species like the zebrafish Danio rerio the precise mechanisms involved in primary sex determination have not been studied extensively. The zebrafish, a gonochoristic species, is lacking discernible sex chromosomes and the sex of juvenile fish is difficult to determine. Sequential protandrous hermaphrodite species provide distinct determination of the gender and allow studying the sex determination process by looking at the mechanism of sex reversal. This is the first attempt to understand the genetic basis of phenotypic variation for sex determination and body weight in a sequential protandrous hermaphrodite species, the gilthead sea bream (Sparus aurata. This work demonstrates a fast and efficient strategy for Quantitative Trait Loci (QTL detection in the gilthead sea bream, a non-model but target hermaphrodite fish species. Therefore a comparative mapping approach was performed to query syntenies against two other Perciformes, the European sea bass (Dicentrarchus labrax, a gonochoristic species and the Asian sea bass (Lates calcarifer a protandrous hermaphrodite. In this manner two significant QTLs, one QTL affecting both body weight and sex and one QTL affecting sex, were detected on the same linkage group. The co-segregation of the two QTLs provides a genomic base to the observed genetic correlation between these two traits in sea bream as well as in other teleosts. The identification of QTLs linked to sex reversal and growth, will contribute significantly to a better understanding of the complex nature of sex determination in S. aurata where most individuals reverse to the female sex at the age of two years through development and maturation of the ovarian portion of the gonad and regression of the testicular area. [Genomic sequences reported in this manuscript have been

  10. Identification of X-linked quantitative trait loci affecting cold tolerance in Drosophila melanogaster and fine mapping by selective sweep analysis.

    Science.gov (United States)

    Svetec, Nicolas; Werzner, Annegret; Wilches, Ricardo; Pavlidis, Pavlos; Alvarez-Castro, José M; Broman, Karl W; Metzler, Dirk; Stephan, Wolfgang

    2011-02-01

    Drosophila melanogaster is a cosmopolitan species that colonizes a great variety of environments. One trait that shows abundant evidence for naturally segregating genetic variance in different populations of D. melanogaster is cold tolerance. Previous work has found quantitative trait loci (QTL) exclusively on the second and the third chromosomes. To gain insight into the genetic architecture of cold tolerance on the X chromosome and to compare the results with our analyses of selective sweeps, a mapping population was derived from a cross between substitution lines that solely differed in the origin of their X chromosome: one originates from a European inbred line and the other one from an African inbred line. We found a total of six QTL for cold tolerance factors on the X chromosome of D. melanogaster. Although the composite interval mapping revealed slightly different QTL profiles between sexes, a coherent model suggests that most QTL overlapped between sexes, and each explained around 5-14% of the genetic variance (which may be slightly overestimated). The allelic effects were largely additive, but we also detected two significant interactions. Taken together, this provides evidence for multiple QTL that are spread along the entire X chromosome and whose effects range from low to intermediate. One detected transgressive QTL influences cold tolerance in different ways for the two sexes. While females benefit from the European allele increasing their cold tolerance, males tend to do better with the African allele. Finally, using selective sweep mapping, the candidate gene CG16700 for cold tolerance colocalizing with a QTL was identified. © 2010 Blackwell Publishing Ltd.

  11. Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on the disease phenotypes of dairy cows with experimentally induced Escherichia coli mastitis

    DEFF Research Database (Denmark)

    Khatun, Momena; Sørensen, Peter; Jørgensen, Hanne Birgitte Hede

    2013-01-01

    Several quantitative trait loci (QTL) affecting mastitis incidence and mastitis-related traits such as somatic cell score exist in dairy cows. Previously, QTL haplotypes associated with susceptibility to Escherichia coli mastitis in Nordic Holstein-Friesian (HF) cows were identified on Bos taurus...... the HH group did. However, we also found interactions between the effects of haplotype and biopsy for body temperature, heart rate, and PMNL. In conclusion, when challenged with E. coli mastitis, HF cows with the specific Bos taurus autosome 9-located QTL haplotypes were associated with differences...

  12. Mapping quantitative trait loci conferring resistance to a widely virulent isolate of Cochliobolus sativus in wild barley accession PI 466423.

    Science.gov (United States)

    Haas, Matthew; Menke, Jon; Chao, Shiaoman; Steffenson, Brian J

    2016-10-01

    This research characterized the genetics of resistance of wild barley accession PI 466423 to a widely virulent pathotype of Cochliobolus sativus . Breeding lines were identified that combine the Midwest Six-rowed Durable Resistance Haplotype and resistance to the virulent isolate ND4008. Spot blotch, caused by Cochliobolus sativus, is a historically important foliar disease of barley (Hordeum vulgare L.) in the Upper Midwest region of the USA. However, for the last 50 years this disease has been of little consequence due to the deployment of resistant six-rowed malting cultivars. These durably resistant cultivars carry the Midwest Six-rowed Durable Resistant Haplotype (MSDRH) comprised of three Quantitative Trait Loci (QTL) on chromosomes 1H, 3H and 7H, originally contributed by breeding line NDB112. Recent reports of C. sativus isolates (e.g. ND4008) with virulence on NDB112 indicate that widely grown cultivars of the region are vulnerable to spot blotch epidemics. Wild barley (H. vulgare ssp. spontaneum), the progenitor of cultivated barley, is a rich source of novel alleles, especially for disease resistance. Wild barley accession PI 466423 is highly resistant to C. sativus isolate ND4008. To determine the genetic architecture of resistance to isolate ND4008 in PI 466423, we phenotyped and genotyped an advanced backcross population (N = 244) derived from the wild accession and the recurrent parent 'Rasmusson', a Minnesota cultivar with the MSDRH. Disease phenotyping was done on BC2F4 seedlings in the greenhouse using isolate ND4008. The Rasmusson/PI 466423 population was genotyped with 7842 single nucleotide polymorphic markers. QTL analysis using composite interval mapping revealed four resistance loci on chromosomes 1H, 2H, 4H and 5H explaining 10.3, 7.4, 6.4 and 8.4 % of the variance, respectively. Resistance alleles on chromosomes 1H, 4H and 5H were contributed by PI 466423, whereas the one on chromosome 2H was contributed by Rasmusson. All four

  13. Genotyping-by-sequencing markers facilitate the identification of quantitative trait loci controlling resistance to Penicillium expansum in Malus sieversii

    Science.gov (United States)

    Wisniewski, Michael; Fazio, Gennaro; Burchard, Erik; Gutierrez, Benjamin; Levin, Elena; Droby, Samir

    2017-01-01

    Blue mold caused by Penicillium expansum is the most important postharvest disease of apple worldwide and results in significant financial losses. There are no defined sources of resistance to blue mold in domesticated apple. However, resistance has been described in wild Malus sieversii accessions, including plant introduction (PI)613981. The objective of the present study was to identify the genetic loci controlling resistance to blue mold in this accession. We describe the first quantitative trait loci (QTL) reported in the Rosaceae tribe Maleae conditioning resistance to P. expansum on genetic linkage group 3 (qM-Pe3.1) and linkage group 10 (qM-Pe10.1). These loci were identified in a M.× domestica ‘Royal Gala’ X M. sieversii PI613981 family (GMAL4593) based on blue mold lesion diameter seven days post-inoculation in mature, wounded apple fruit inoculated with P. expansum. Phenotypic analyses were conducted in 169 progeny over a four year period. PI613981 was the source of the resistance allele for qM-Pe3.1, a QTL with a major effect on blue mold resistance, accounting for 27.5% of the experimental variability. The QTL mapped from 67.3 to 74 cM on linkage group 3 of the GMAL4593 genetic linkage map. qM-Pe10.1 mapped from 73.6 to 81.8 cM on linkage group 10. It had less of an effect on resistance, accounting for 14% of the experimental variation. ‘Royal Gala’ was the primary contributor to the resistance effect of this QTL. However, resistance-associated alleles in both parents appeared to contribute to the least square mean blue mold lesion diameter in an additive manner at qM-Pe10.1. A GMAL4593 genetic linkage map composed of simple sequence repeats and ‘Golden Delicious’ single nucleotide polymorphism markers was able to detect qM-Pe10.1, but failed to detect qM-Pe3.1. The subsequent addition of genotyping-by-sequencing markers to the linkage map provided better coverage of the PI613981 genome on linkage group 3 and facilitated discovery of q

  14. Quantitative Trait Loci and Maternal Effects Affecting the Strong Grain Dormancy of Wild Barley (Hordeum vulgare ssp. spontaneum

    Directory of Open Access Journals (Sweden)

    Shingo Nakamura

    2017-10-01

    Full Text Available Wild barley (Hordeum vulgare ssp. spontaneum has strong grain dormancy, a trait that may enhance its survival in non-cultivated environments; by contrast, cultivated barley (Hordeum vulgare ssp. vulgare has weaker dormancy, allowing uniform germination in cultivation. Malting barley cultivars have been bred for especially weak dormancy to optimize their use in malt production. Here, we analyzed the genetic mechanism of this difference in seed dormancy, using recombinant inbred lines (RILs derived from a cross between the wild barley accession ‘H602’ and the malting barley cultivar ‘Kanto Nakate Gold (KNG’. Grains of H602 and KNG harvested at physiological maturity and dried at 30°C for 7 days had germination of approximately 0 and 100%, respectively. Analysis of quantitative trait loci (QTL affecting grain dormancy identified the well-known major dormancy QTL SD1 and SD2 (located near the centromeric region and at the distal end of the long arm of chromosome 5H, respectively, and QTL at the end of the long arm of chromosome 4H and in the middle of the long arm of chromosome 5H. We designated these four QTL Qsd1-OK, Qsd2-OK, Qsdw-4H, and Qsdw-5H, and they explained approximately 6, 38, 3, and 13% of the total phenotypic variation, respectively. RILs carrying H602 alleles showed increased dormancy levels for all QTL. The QTL acted additively and did not show epistasis or QTL–environment interactions. Comparison of QTL locations indicated that all QTL except Qsdw-5H are likely the same as the QTL previously detected in the doubled haploid population from a cross between the malting cultivar ‘Haruna Nijo’ and ‘H602.’ We further examined Qsd2-OK and Qsdw-5H by analyzing the segregation of phenotypes and genotypes of F2 progenies derived from crosses between RILs carrying specific segments of chromosome 5H from H602 in the KNG background. This analysis confirmed that the two genomic regions corresponding to these QTL are involved in

  15. Quantitative Trait Loci and Maternal Effects Affecting the Strong Grain Dormancy of Wild Barley (Hordeum vulgaressp.spontaneum).

    Science.gov (United States)

    Nakamura, Shingo; Pourkheirandish, Mohammad; Morishige, Hiromi; Sameri, Mohammad; Sato, Kazuhiro; Komatsuda, Takao

    2017-01-01

    Wild barley ( Hordeum vulgare ssp. spontaneum ) has strong grain dormancy, a trait that may enhance its survival in non-cultivated environments; by contrast, cultivated barley ( Hordeum vulgare ssp. vulgare ) has weaker dormancy, allowing uniform germination in cultivation. Malting barley cultivars have been bred for especially weak dormancy to optimize their use in malt production. Here, we analyzed the genetic mechanism of this difference in seed dormancy, using recombinant inbred lines (RILs) derived from a cross between the wild barley accession 'H602' and the malting barley cultivar 'Kanto Nakate Gold (KNG)'. Grains of H602 and KNG harvested at physiological maturity and dried at 30°C for 7 days had germination of approximately 0 and 100%, respectively. Analysis of quantitative trait loci (QTL) affecting grain dormancy identified the well-known major dormancy QTL SD1 and SD2 (located near the centromeric region and at the distal end of the long arm of chromosome 5H, respectively), and QTL at the end of the long arm of chromosome 4H and in the middle of the long arm of chromosome 5H. We designated these four QTL Qsd1-OK , Qsd2-OK , Qsdw-4H , and Qsdw-5H , and they explained approximately 6, 38, 3, and 13% of the total phenotypic variation, respectively. RILs carrying H602 alleles showed increased dormancy levels for all QTL. The QTL acted additively and did not show epistasis or QTL-environment interactions. Comparison of QTL locations indicated that all QTL except Qsdw-5H are likely the same as the QTL previously detected in the doubled haploid population from a cross between the malting cultivar 'Haruna Nijo' and 'H602.' We further examined Qsd2-OK and Qsdw-5H by analyzing the segregation of phenotypes and genotypes of F 2 progenies derived from crosses between RILs carrying specific segments of chromosome 5H from H602 in the KNG background. This analysis confirmed that the two genomic regions corresponding to these QTL are involved in the regulation of

  16. Identifying Quantitative Trait Loci (QTLs and Developing Diagnostic Markers Linked to Orange Rust Resistance in Sugarcane (Saccharum spp.

    Directory of Open Access Journals (Sweden)

    Xiping Yang

    2018-03-01

    Full Text Available Sugarcane (Saccharum spp. is an important economic crop, contributing up to 80% of table sugar used in the world and has become a promising feedstock for biofuel production. Sugarcane production has been threatened by many diseases, and fungicide applications for disease control have been opted out for sustainable agriculture. Orange rust is one of the major diseases impacting sugarcane production worldwide. Identifying quantitative trait loci (QTLs and developing diagnostic markers are valuable for breeding programs to expedite release of superior sugarcane cultivars for disease control. In this study, an F1 segregating population derived from a cross between two hybrid sugarcane clones, CP95-1039 and CP88-1762, was evaluated for orange rust resistance in replicated trails. Three QTLs controlling orange rust resistance in sugarcane (qORR109, qORR4 and qORR102 were identified for the first time ever, which can explain 58, 12 and 8% of the phenotypic variation, separately. We also characterized 1,574 sugarcane putative resistance (R genes. These sugarcane putative R genes and simple sequence repeats in the QTL intervals were further used to develop diagnostic markers for marker-assisted selection of orange rust resistance. A PCR-based Resistance gene-derived maker, G1 was developed, which showed significant association with orange rust resistance. The putative QTLs and marker developed in this study can be effectively utilized in sugarcane breeding programs to facilitate the selection process, thus contributing to the sustainable agriculture for orange rust disease control.

  17. The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.

    Science.gov (United States)

    Fischer, Daniel

    2017-11-01

    We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (exploratory) Quantitative Trait Loci analysis that overcomes some of the limitations of other popular (e)QTL approaches. Popular (e)QTL approaches that use linear models or ANOVA are often based on over-simplified models that have weak statistical properties and which are not robust against outlying observations. The algorithm to calculate the MDR is well established. To speed up its calculation in R, we implemented it in C++. Further, our implementation also supports the combination of several MDR results to an MDR ensemble classifier. The (e)QTL test procedure is based on a generalized Mann-Whitney test that is tailored for directional alternatives, as they are present in an (e)QTL analysis. Our package GenomicTools provides functions to determine SNP combinations that have the highest accuracy for a MDR classification problem. It also provides functions to combine the best MDR results to a joined ensemble classifier for improved classification results. Further, the (e)QTL analysis is based on a solid statistical theory. In addition, informative visualizations of the results are provided. The here presented new class of tests and methods have an easy to apply syntax, so that also researchers inexperienced in R are able to apply our proposed methods and implementations. The package creates publication ready Figures and hence could be a valuable tool for genomic data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Towards positional isolation of three quantitative trait loci conferring resistance to powdery mildew in two Spanish barley landraces.

    Directory of Open Access Journals (Sweden)

    Cristina Silvar

    Full Text Available Three quantitative trait loci (QTL conferring broad spectrum resistance to powdery mildew, caused by the fungus Blumeria graminis f. sp. hordei, were previously identified on chromosomes 7HS, 7HL and 6HL in the Spanish barley landrace-derived lines SBCC097 and SBCC145. In the present work, a genome-wide putative linear gene index of barley (Genome Zipper and the first draft of the physical, genetic and functional sequence of the barley genome were used to go one step further in the shortening and explicit demarcation on the barley genome of these regions conferring resistance to powdery mildew as well as in the identification of candidate genes. First, a comparative analysis of the target regions to the barley Genome Zippers of chromosomes 7H and 6H allowed the development of 25 new gene-based molecular markers, which slightly better delimit the QTL intervals. These new markers provided the framework for anchoring of genetic and physical maps, figuring out the outline of the barley genome at the target regions in SBCC097 and SBCC145. The outermost flanking markers of QTLs on 7HS, 7HL and 6HL defined a physical area of 4 Mb, 3.7 Mb and 3.2 Mb, respectively. In total, 21, 10 and 16 genes on 7HS, 7HL and 6HL, respectively, could be interpreted as potential candidates to explain the resistance to powdery mildew, as they encode proteins of related functions with respect to the known pathogen defense-related processes. The majority of these were annotated as belonging to the NBS-LRR class or protein kinase family.

  19. Joint Analysis of Near-Isogenic and Recombinant Inbred Line Populations Yields Precise Positional Estimates for Quantitative Trait Loci

    Directory of Open Access Journals (Sweden)

    Kristen L. Kump

    2010-11-01

    Full Text Available Data generated for initial quantitative trait loci (QTL mapping using recombinant inbred line (RIL populations are usually ignored during subsequent fine-mapping using near-isogenic lines (NILs. Combining both datasets would increase the number of recombination events sampled and generate better position and effect estimates. Previously, several QTL for resistance to southern leaf blight of maize were mapped in two RIL populations, each independently derived from a cross between the lines B73 and Mo17. In each case the largest QTL was in bin 3.04. Here, two NIL pairs differing for this QTL were derived and used to create two distinct F family populations that were assessed for southern leaf blight (SLB resistance. By accounting for segregation of the other QTL in the original RIL data, we were able to combine these data with the new genotypic and phenotypic data from the F families. Joint analysis yielded a narrower QTL support interval compared to that derived from analysis of any one of the data sets alone, resulting in the localization of the QTL to a less than 0.5 cM interval. Candidate genes identified within this interval are discussed. This methodology allows combined QTL analysis in which data from RIL populations is combined with data derived from NIL populations segregating for the same pair of alleles. It improves mapping resolution over the conventional approach with virtually no additional resources. Because data sets of this type are commonly produced, this approach is likely to prove widely applicable.

  20. Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

    Directory of Open Access Journals (Sweden)

    Cecilia M Lindgren

    2009-06-01

    Full Text Available To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580 informative for adult waist circumference (WC and waist-hip ratio (WHR. We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11 and MSRA (WC, P = 8.9x10(-9. A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8. The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

  1. Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution

    Science.gov (United States)

    Qi, Lu; Speliotes, Elizabeth K.; Thorleifsson, Gudmar; Willer, Cristen J.; Herrera, Blanca M.; Jackson, Anne U.; Lim, Noha; Scheet, Paul; Soranzo, Nicole; Amin, Najaf; Aulchenko, Yurii S.; Chambers, John C.; Drong, Alexander; Luan, Jian'an; Lyon, Helen N.; Rivadeneira, Fernando; Sanna, Serena; Timpson, Nicholas J.; Zillikens, M. Carola; Zhao, Jing Hua; Almgren, Peter; Bandinelli, Stefania; Bennett, Amanda J.; Bergman, Richard N.; Bonnycastle, Lori L.; Bumpstead, Suzannah J.; Chanock, Stephen J.; Cherkas, Lynn; Chines, Peter; Coin, Lachlan; Cooper, Cyrus; Crawford, Gabriel; Doering, Angela; Dominiczak, Anna; Doney, Alex S. F.; Ebrahim, Shah; Elliott, Paul; Erdos, Michael R.; Estrada, Karol; Ferrucci, Luigi; Fischer, Guido; Forouhi, Nita G.; Gieger, Christian; Grallert, Harald; Groves, Christopher J.; Grundy, Scott; Guiducci, Candace; Hadley, David; Hamsten, Anders; Havulinna, Aki S.; Hofman, Albert; Holle, Rolf; Holloway, John W.; Illig, Thomas; Isomaa, Bo; Jacobs, Leonie C.; Jameson, Karen; Jousilahti, Pekka; Karpe, Fredrik; Kuusisto, Johanna; Laitinen, Jaana; Lathrop, G. Mark; Lawlor, Debbie A.; Mangino, Massimo; McArdle, Wendy L.; Meitinger, Thomas; Morken, Mario A.; Morris, Andrew P.; Munroe, Patricia; Narisu, Narisu; Nordström, Anna; Nordström, Peter; Oostra, Ben A.; Palmer, Colin N. A.; Payne, Felicity; Peden, John F.; Prokopenko, Inga; Renström, Frida; Ruokonen, Aimo; Salomaa, Veikko; Sandhu, Manjinder S.; Scott, Laura J.; Scuteri, Angelo; Silander, Kaisa; Song, Kijoung; Yuan, Xin; Stringham, Heather M.; Swift, Amy J.; Tuomi, Tiinamaija; Uda, Manuela; Vollenweider, Peter; Waeber, Gerard; Wallace, Chris; Walters, G. Bragi; Weedon, Michael N.; Witteman, Jacqueline C. M.; Zhang, Cuilin; Zhang, Weihua; Caulfield, Mark J.; Collins, Francis S.; Davey Smith, George; Day, Ian N. M.; Franks, Paul W.; Hattersley, Andrew T.; Hu, Frank B.; Jarvelin, Marjo-Riitta; Kong, Augustine; Kooner, Jaspal S.; Laakso, Markku; Lakatta, Edward; Mooser, Vincent; Morris, Andrew D.; Peltonen, Leena; Samani, Nilesh J.; Spector, Timothy D.; Strachan, David P.; Tanaka, Toshiko; Tuomilehto, Jaakko; Uitterlinden, André G.; van Duijn, Cornelia M.; Wareham, Nicholas J.; Watkins for the PROCARDIS consortia, Hugh; Waterworth, Dawn M.; Boehnke, Michael; Deloukas, Panos; Groop, Leif; Hunter, David J.; Thorsteinsdottir, Unnur; Schlessinger, David; Wichmann, H.-Erich; Frayling, Timothy M.; Abecasis, Gonçalo R.; Hirschhorn, Joel N.; Loos, Ruth J. F.; Stefansson, Kari; Mohlke, Karen L.; Barroso, Inês; McCarthy for the GIANT consortium, Mark I.

    2009-01-01

    To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10−11) and MSRA (WC, P = 8.9×10−9). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10−8). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity. PMID:19557161

  2. Genetic Influences on Growth Traits of BMI

    DEFF Research Database (Denmark)

    Hjelmborg, Jacob V B; Fagnani, Corrado; Silventoinen, Karri

    2008-01-01

    Objective:To investigate the interplay between genetic factors influencing baseline level and changes in BMI in adulthood.Methods and Procedures:A longitudinal twin study of the cohort of Finnish twins (N = 10,556 twin individuals) aged 20-46 years at baseline was conducted and followed up 15 years....... Data on weight and height were obtained from mailed surveys in 1975, 1981, and 1990.Results:Latent growth models revealed a substantial genetic influence on BMI level at baseline in males and females (heritability (h(2)) 80% (95% confidence interval 0.79-0.80) for males and h(2) = 82% (0.81, 0.......84) for females) and a moderate-to-high influence on rate of change in BMI (h(2) = 58% (0.50, 0.69) for males and h(2) = 64% (0.58, 0.69) for females). Only very weak evidence for genetic pleiotropy was observed; the genetic correlation between baseline and rate of change in BMI was very modest (-0.070 (-0.13, -0...

  3. Consumer trait variation influences tritrophic interactions in salt marsh communities.

    Science.gov (United States)

    Hughes, Anne Randall; Hanley, Torrance C; Orozco, Nohelia P; Zerebecki, Robyn A

    2015-07-01

    The importance of intraspecific variation has emerged as a key question in community ecology, helping to bridge the gap between ecology and evolution. Although much of this work has focused on plant species, recent syntheses have highlighted the prevalence and potential importance of morphological, behavioral, and life history variation within animals for ecological and evolutionary processes. Many small-bodied consumers live on the plant that they consume, often resulting in host plant-associated trait variation within and across consumer species. Given the central position of consumer species within tritrophic food webs, such consumer trait variation may play a particularly important role in mediating trophic dynamics, including trophic cascades. In this study, we used a series of field surveys and laboratory experiments to document intraspecific trait variation in a key consumer species, the marsh periwinkle Littoraria irrorata, based on its host plant species (Spartina alterniflora or Juncus roemerianus) in a mixed species assemblage. We then conducted a 12-week mesocosm experiment to examine the effects of Littoraria trait variation on plant community structure and dynamics in a tritrophic salt marsh food web. Littoraria from different host plant species varied across a suite of morphological and behavioral traits. These consumer trait differences interacted with plant community composition and predator presence to affect overall plant stem height, as well as differentially alter the density and biomass of the two key plant species in this system. Whether due to genetic differences or phenotypic plasticity, trait differences between consumer types had significant ecological consequences for the tritrophic marsh food web over seasonal time scales. By altering the cascading effects of the top predator on plant community structure and dynamics, consumer differences may generate a feedback over longer time scales, which in turn influences the degree of trait

  4. A genome-wide scan for loci influencing adolescent cannabis dependence symptoms: evidence for linkage on chromosomes 3 and 9.

    Science.gov (United States)

    Hopfer, Christian J; Lessem, Jeffrey M; Hartman, Christie A; Stallings, Michael C; Cherny, Stacey S; Corley, Robin P; Hewitt, John K; Krauter, Kenneth S; Mikulich-Gilbertson, Susan K; Rhee, Soo Hyun; Smolen, Andrew; Young, Susan E; Crowley, Thomas J

    2007-06-15

    Cannabis is the most frequently abused illicit substance among adolescents and young adults. Genetic risk factors account for part of the variation in the development of cannabis dependence symptoms; however, no linkage studies have been performed for cannabis dependence symptoms. This study aimed to identify such loci. Three hundred and twenty-four sibling pairs from 192 families were assessed for cannabis dependence symptoms. Probands (13-19 years of age) were recruited from consecutive admissions to substance abuse treatment facilities. The siblings of the probands ranged in age from 12 to 25 years. A community-based sample of 4843 adolescents and young adults was utilized to define an age- and sex-corrected index of cannabis dependence vulnerability. DSM-IV cannabis dependence symptoms were assessed in youth and their family members with the Composite International Diagnostic Instrument-Substance Abuse Module. Siblings and parents were genotyped for 374 microsatellite markers distributed across the 22 autosomes (average inter-marker distance=9.2cM). Cannabis dependence symptoms were analyzed using Merlin-regress, a regression-based method that is robust to sample selection. Evidence for suggestive linkage was found on chromosome 3q21 near marker D3S1267 (LOD=2.61), and on chromosome 9q34 near marker D9S1826 (LOD=2.57). This is the first reported linkage study of cannabis dependence symptoms. Other reports of linkage regions for illicit substance dependence have been reported near 3q21, suggesting that this region may contain a quantitative trait loci influencing cannabis dependence and other substance use disorders.

  5. Genome-wide association study reveals constant and specific loci for hematological traits at three time stages in a White Duroc × Erhualian F2 resource population.

    Directory of Open Access Journals (Sweden)

    Zhiyan Zhang

    Full Text Available Hematological traits are important indicators of immune function and have been commonly examined as biomarkers of disease and disease severity in humans. Pig is an ideal biomedical model for human diseases due to its high degree of similarity with human physiological characteristics. Here, we conducted genome-wide association studies (GWAS for 18 hematological traits at three growth stages (days 18, 46 and 240 in a White Duroc × Erhualian F2 intercross. In total, we identified 38 genome-wide significant regions containing 185 genome-wide significant SNPs by single-marker GWAS or LONG-GWAS. The significant regions are distributed on pig chromosomes (SSC 1, 4, 5, 7, 8, 10, 11, 12, 13, 17 and 18, and most of significant SNPs reside on SSC7 and SSC8. Of the 38 significant regions, 7 show constant effects on hematological traits across the whole life stages, and 6 regions have time-specific effects on the measured traits at early or late stages. The most prominent locus is the genomic region between 32.36 and 84.49 Mb on SSC8 that is associated with multiple erythroid traits. The KIT gene in this region appears to be a promising candidate gene. The findings improve our understanding of the genetic architecture of hematological traits in pigs. Further investigations are warranted to characterize the responsible gene(s and causal variant(s especially for the major loci on SSC7 and SSC8.

  6. Association mapping for phenology and plant architecture in maize shows higher power for developmental traits compared with growth influenced traits.

    Science.gov (United States)

    Bouchet, S; Bertin, P; Presterl, T; Jamin, P; Coubriche, D; Gouesnard, B; Laborde, J; Charcosset, A

    2017-03-01

    Plant architecture, phenology and yield components of cultivated plants have repeatedly been shaped by selection to meet human needs and adaptation to different environments. Here we assessed the genetic architecture of 24 correlated maize traits that interact during plant cycle. Overall, 336 lines were phenotyped in a network of 9 trials and genotyped with 50K single-nucleotide polymorphisms. Phenology was the main factor of differentiation between genetic groups. Then yield components distinguished dents from lower yielding genetic groups. However, most of trait variation occurred within group and we observed similar overall and within group correlations, suggesting a major effect of pleiotropy and/or linkage. We found 34 quantitative trait loci (QTLs) for individual traits and six for trait combinations corresponding to PCA coordinates. Among them, only five were pleiotropic. We found a cluster of QTLs in a 5 Mb region around Tb1 associated with tiller number, ear row number and the first PCA axis, the latter being positively correlated to flowering time and negatively correlated to yield. Kn1 and ZmNIP1 were candidate genes for tillering, ZCN8 for leaf number and Rubisco Activase 1 for kernel weight. Experimental repeatabilities, numbers of QTLs and proportion of explained variation were higher for traits related to plant development such as tillering, leaf number and flowering time, than for traits affected by growth such as yield components. This suggests a simpler genetic determinism with larger individual QTL effects for the first category.

  7. Detection of quantitative trait loci in Danish Holstein cattle affecting clinical mastitis, somatic cell score, udder conformation traits, and assessment of associated effects on milk yield

    DEFF Research Database (Denmark)

    Lund, M S; Guldbrandtsen, B; Buitenhuis, A J

    2008-01-01

    either a pleiotropic QTL affecting 2 traits or 2 QTL each affecting 1 trait gave some evidence to distinguish between these models. For Bos taurus autosome 5, the most likely models were a pleiotropic QTL affecting CM2, CM3, and SCS, and a linked QTL affecting fat yield index. For Bos taurus autosome 9...

  8. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.

    Directory of Open Access Journals (Sweden)

    Joshua C Randall

    2013-06-01

    Full Text Available Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals and took forward 348 SNPs into follow-up (additional 137,052 individuals in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%, including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9 and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG, all of which were genome-wide significant in women (P<5×10(-8, but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

  9. A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize.

    Science.gov (United States)

    Welcker, Claude; Sadok, Walid; Dignat, Grégoire; Renault, Morgan; Salvi, Silvio; Charcosset, Alain; Tardieu, François

    2011-10-01

    Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material.

  10. Do gender and personality traits influence use of deal sites?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek; Pavlicek, Antonin

    2017-01-01

    There is a growing body of literature on impact of personality traits on technology adoption. But majority of these studies are never replicated and, therefore, it is hard to estimate how general are their findings. The focus of this paper is adoption of deal sites, and its aim to replicate...... in the Czech Republic a research of deal sites use originally conducted in Denmark. While in Denmark, agreeableness, neuroticism, and gender significantly influenced use of deal sites, in the Czech Republic, it was the remaining traits - extraversion, conscientiousness, and openness to experience, and gender....... In both surveys, women used deal sites more than men. If usage is defined as at least one purchase within last six months, then only gender and extraversion are significant and conscientiousness is borderline significant....

  11. Identification of Loci Associated with Drought Resistance Traits in Heterozygous Autotetraploid Alfalfa (Medicago sativa L.) Using Genome-Wide Association Studies with Genotyping by Sequencing.

    Science.gov (United States)

    Zhang, Tiejun; Yu, Long-Xi; Zheng, Ping; Li, Yajun; Rivera, Martha; Main, Dorrie; Greene, Stephanie L

    2015-01-01

    Drought resistance is an important breeding target for enhancing alfalfa productivity in arid and semi-arid regions. Identification of genes involved in drought tolerance will facilitate breeding for improving drought resistance and water use efficiency in alfalfa. Our objective was to use a diversity panel of alfalfa accessions comprised of 198 cultivars and landraces to identify genes involved in drought tolerance. The panel was selected from the USDA-ARS National Plant Germplasm System alfalfa collection and genotyped using genotyping by sequencing. A greenhouse procedure was used for phenotyping two important traits associated with drought tolerance: drought resistance index (DRI) and relative leaf water content (RWC). Marker-trait association identified nineteen and fifteen loci associated with DRI and RWC, respectively. Alignments of target sequences flanking to the resistance loci against the reference genome of M. truncatula revealed multiple chromosomal locations. Markers associated with DRI are located on all chromosomes while markers associated with RWC are located on chromosomes 1, 2, 3, 4, 5, 6 and 7. Co-localizations of significant markers between DRI and RWC were found on chromosomes 3, 5 and 7. Most loci associated with DRI in this work overlap with the reported QTLs associated with biomass under drought in alfalfa. Additional significant markers were targeted to several contigs with unknown chromosomal locations. BLAST search using their flanking sequences revealed homology to several annotated genes with functions in stress tolerance. With further validation, these markers may be used for marker-assisted breeding new alfalfa varieties with drought resistance and enhanced water use efficiency.

  12. CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

    DEFF Research Database (Denmark)

    Macé, Aurélien; Tuke, Marcus A; Deelen, Patrick

    2017-01-01

    There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations ...

  13. Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis.

    Science.gov (United States)

    Aulchenko, Yurii S; de Koning, Dirk-Jan; Haley, Chris

    2007-09-01

    For pedigree-based quantitative trait loci (QTL) association analysis, a range of methods utilizing within-family variation such as transmission-disequilibrium test (TDT)-based methods have been developed. In scenarios where stratification is not a concern, methods exploiting between-family variation in addition to within-family variation, such as the measured genotype (MG) approach, have greater power. Application of MG methods can be computationally demanding (especially for large pedigrees), making genomewide scans practically infeasible. Here we suggest a novel approach for genomewide pedigree-based quantitative trait loci (QTL) association analysis: genomewide rapid association using mixed model and regression (GRAMMAR). The method first obtains residuals adjusted for family effects and subsequently analyzes the association between these residuals and genetic polymorphisms using rapid least-squares methods. At the final step, the selected polymorphisms may be followed up with the full measured genotype (MG) analysis. In a simulation study, we compared type 1 error, power, and operational characteristics of the proposed method with those of MG and TDT-based approaches. For moderately heritable (30%) traits in human pedigrees the power of the GRAMMAR and the MG approaches is similar and is much higher than that of TDT-based approaches. When using tabulated thresholds, the proposed method is less powerful than MG for very high heritabilities and pedigrees including large sibships like those observed in livestock pedigrees. However, there is little or no difference in empirical power of MG and the proposed method. In any scenario, GRAMMAR is much faster than MG and enables rapid analysis of hundreds of thousands of markers.

  14. Cultural influences on social feedback processing of character traits

    Directory of Open Access Journals (Sweden)

    Christoph W Korn

    2014-04-01

    Full Text Available Cultural differences are generally explained by how people see themselves in relation to social interaction partners. While Western culture emphasizes independence, East Asian culture emphasizes interdependence. Despite this focus on social interactions, it remains elusive how people from different cultures process feedback on their own (and on others' character traits. Here, participants of either German or Chinese origin engaged in a face-to-face interaction. Consequently, they updated their self- and other-ratings of 80 character traits (e.g., polite, pedantic after receiving feedback from their interaction partners. To exclude potential confounds, we obtained data from German and Chinese participants in Berlin (functional magnetic resonance imaging and in Beijing (behavior. We tested cultural influences on social conformity, positivity biases, and self-related neural activity. First, Chinese conformed more to social feedback than Germans (i.e., Chinese updated their trait ratings more. Second, regardless of culture, participants processed self- and other-related feedback in a positively biased way (i.e., they updated more toward desirable than toward undesirable feedback. Third, changes in self-related medial prefrontal cortex activity were greater in Germans than in Chinese during feedback processing. By investigating conformity, positivity biases, and self-related activity in relation to feedback obtained in a real-life interaction, we provide an essential step towards a unifying framework for understanding the diversity of human culture.

  15. Cultural influences on social feedback processing of character traits

    Science.gov (United States)

    Korn, Christoph W.; Fan, Yan; Zhang, Kai; Wang, Chenbo; Han, Shihui; Heekeren, Hauke R.

    2014-01-01

    Cultural differences are generally explained by how people see themselves in relation to social interaction partners. While Western culture emphasizes independence, East Asian culture emphasizes interdependence. Despite this focus on social interactions, it remains elusive how people from different cultures process feedback on their own (and on others') character traits. Here, participants of either German or Chinese origin engaged in a face-to-face interaction. Consequently, they updated their self- and other-ratings of 80 character traits (e.g., polite, pedantic) after receiving feedback from their interaction partners. To exclude potential confounds, we obtained data from German and Chinese participants in Berlin [functional magnetic resonance imaging (fMRI)] and in Beijing (behavior). We tested cultural influences on social conformity, positivity biases, and self-related neural activity. First, Chinese conformed more to social feedback than Germans (i.e., Chinese updated their trait ratings more). Second, regardless of culture, participants processed self- and other-related feedback in a positively biased way (i.e., they updated more toward desirable than toward undesirable feedback). Third, changes in self-related medial prefrontal cortex activity were greater in Germans than in Chinese during feedback processing. By investigating conformity, positivity biases, and self-related activity in relation to feedback obtained in a real-life interaction, we provide an essential step toward a unifying framework for understanding the diversity of human culture. PMID:24772075

  16. Identification and mapping of leaf, stem and stripe rust resistance quantitative trait loci and their interactions in durum wheat

    OpenAIRE

    Singh, A.; Pandey, M. P.; Singh, A. K.; Knox, R. E.; Ammar, K.; Clarke, J. M.; Clarke, F. R.; Singh, R. P.; Pozniak, C. J.; DePauw, R. M.; McCallum, B. D.; Cuthbert, R. D.; Randhawa, H. S.; Fetch, T. G.

    2012-01-01

    Leaf rust (Puccinia triticina Eriks.), stripe rust (Puccinia striiformis f. tritici Eriks.) and stem rust (Puccinia graminis f. sp. tritici) cause major production losses in durum wheat (Triticum turgidum L. var. durum). The objective of this research was to identify and map leaf, stripe and stem rust resistance loci from the French cultivar Sachem and Canadian cultivar Strongfield. A doubled haploid population from Sachem/Strongfield and parents were phenotyped for seedling reaction to leaf ...

  17. Identification of Quantitative Trait Loci Conditioning the Main Biomass Yield Components and Resistance to Melampsora spp. in Salix viminalis × Salix schwerinii Hybrids.

    Science.gov (United States)

    Sulima, Paweł; Przyborowski, Jerzy A; Kuszewska, Anna; Załuski, Dariusz; Jędryczka, Małgorzata; Irzykowski, Witold

    2017-03-22

    The biomass of Salix viminalis is the most highly valued source of green energy, followed by S. schwerinii , S. dasyclados and other species. Significant variability in productivity and leaf rust resistance are noted both within and among willow species, which creates new opportunities for improving willow yield parameters through selection of desirable recombinants supported with molecular markers. The aim of this study was to identify quantitative trait loci (QTLs) linked with biomass yield-related traits and the resistance/susceptibility of Salix mapping population to leaf rust. The experimental material comprised a mapping population developed based on S. viminalis × S. schwerinii hybrids. Phenotyping was performed on plants grown in a field experiment that had a balanced incomplete block design with 10 replications. Based on a genetic map, 11 QTLs were identified for plant height, 9 for shoot diameter, 3 for number of shoots and 11 for resistance/susceptibility to leaf rust. The QTLs identified in our study explained 3%-16% of variability in the analyzed traits. Our findings make significant contributions to the development of willow breeding programs and research into shrubby willow crops grown for energy.

  18. High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L..

    Directory of Open Access Journals (Sweden)

    Zhen Zhang

    Full Text Available Cotton (Gossypium hirsutum L. is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

  19. High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L.).

    Science.gov (United States)

    Zhang, Zhen; Li, Junwen; Muhammad, Jamshed; Cai, Juan; Jia, Fei; Shi, Yuzhen; Gong, Juwu; Shang, Haihong; Liu, Aiying; Chen, Tingting; Ge, Qun; Palanga, Koffi Kibalou; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Li, Wei; Sun, Linyang; Gong, Wankui; Yuan, Youlu

    2015-01-01

    Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

  20. Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

    Directory of Open Access Journals (Sweden)

    Silvano O Assanga

    Full Text Available Stable quantitative trait loci (QTL are important for deployment in marker assisted selection in wheat (Triticum aestivum L. and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading and yield related traits (test weight, thousand kernel weight, harvest index. The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1

  1. A genome-wide association study using international breeding-evaluation data identifies major loci affecting production traits and stature in the Brown Swiss cattle breed

    Directory of Open Access Journals (Sweden)

    Guo Jiazhong

    2012-10-01

    Full Text Available Abstract Background The genome-wide association study (GWAS is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program. Result GWASs were performed using 50 k SNP chip data and deregressed estimated breeding values (DEBVs for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY, fat yield (FY, protein yield (PY, lactating cow’s ability to recycle after calving (CRC, angularity (ANG, body depth (BDE, stature (STA, milk somatic cell score (SCS and milk speed (MSP. Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations. Conclusions Our study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other

  2. Genetic variability and population structure in loci related to milk production traits in native Argentine Creole and commercial Argentine Holstein cattle

    Directory of Open Access Journals (Sweden)

    Golijow C.D.

    1999-01-01

    Full Text Available Many cattle breeds have been subjected to high selection pressure for production traits. Consequently, population genetic structure and allelic distribution could differ in breeds under high selection pressure compared to unselected breeds. Analysis of k-casein, aS1-casein and prolactin gene frequencies was made for Argentine Creole (AC and Argentine Holstein (AH cattle herds. The calculated FST values measured the degree of genetic differentiation of subpopulations, depending on the variances of gene frequencies.The AC breed had considerably more variation among herds at the aS1-casein and k-casein loci. Conservation strategies should consider the entire AC population in order to maintain the genetic variability found in this native breed.

  3. Genome-wide association and meta-analysis in populations from Starr County, Texas, and Mexico City identify type 2 diabetes susceptibility loci and enrichment for expression quantitative trait loci in top signals

    Science.gov (United States)

    Below, J. E.; Gamazon, E. R.; Morrison, J. V.; Konkashbaev, A.; Pluzhnikov, A.; McKeigue, P. M.; Parra, E. J.; Elbein, S. C.; Hallman, D. M.; Nicolae, D. L.; Bell, G. I.; Cruz, M.

    2013-01-01

    Aims/hypothesis We conducted genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) analyses to identify and characterise risk loci for type 2 diabetes in Mexican-Americans from Starr County, TX, USA. Method Using 1.8 million directly interrogated and imputed genotypes in 837 unrelated type 2 diabetes cases and 436 normoglycaemic controls, we conducted Armitage trend tests. To improve power in this population with high disease rates, we also performed ordinal regression including an intermediate class with impaired fasting glucose and/or glucose tolerance. These analyses were followed by meta-analysis with a study of 967 type 2 diabetes cases and 343 normoglycaemic controls from Mexico City, Mexico. Result The top signals (unadjusted p value <1×10−5) included 49 single nucleotide polymorphisms (SNPs) in eight gene regions (PER3, PARD3B, EPHA4, TOMM7, PTPRD, HNT [also known as RREB1], LOC729993 and IL34) and six intergenic regions. Among these was a missense polymorphism (rs10462020; Gly639Val) in the clock gene PER3, a system recently implicated in diabetes. We also report a second signal (minimum p value 1.52× 10−6) within PTPRD, independent of the previously implicated SNP, in a population of Han Chinese. Top meta-analysis signals included known regions HNF1A and KCNQ1. Annotation of top association signals in both studies revealed a marked excess of trans-acting eQTL in both adipose and muscle tissues. Conclusions/Interpretation In the largest study of type 2 diabetes in Mexican populations to date, we identified modest associations of novel and previously reported SNPs. In addition, in our top signals we report significant excess of SNPs that predict transcript levels in muscle and adipose tissues. PMID:21647700

  4. Quantitative trait loci underlying resistance to sudden death syndrome (SDS) in MD96-5722 by 'Spencer' recombinant inbred line population of soybean.

    Science.gov (United States)

    Anderson, J; Akond, M; Kassem, M A; Meksem, K; Kantartzi, S K

    2015-04-01

    The best way to protect yield loss of soybean [Glycine max (L.) Merr.] due to sudden death syndrome (SDS), caused by Fusarium virguliforme (Aoki, O'Donnel, Homma & Lattanzi), is the development and use of resistant lines. Mapping quantitative trait loci (QTL) linked to SDS help developing resistant soybean germplasm through molecular marker-assisted selection strategy. QTL for SDS presented herein are from a high-density SNP-based genetic linkage map of MD 96-5722 (a.k.a 'Monocacy') by 'Spencer' recombinant inbred line using SoySNP6K Illumina Infinium BeadChip genotyping array. Ninety-four F 5:7 lines were evaluated for 2 years (2010 and 2011) at two locations (Carbondale and Valmeyer) in southern Illinois, USA to identify QTL controlling SDS resistance using disease index (DX). Composite interval mapping identified 19 SDS controlling QTL which were mapped on 11 separate linkage group (LG) or chromosomes (Chr) out of 20 LG or Chr of soybean genome. Many of these significant QTL identified in one environment/year were confirmed in another year or environment, which suggests a common genetic effects and modes of the pathogen. These new QTL are useful sources for SDS resistance studies in soybean breeding, complementing previously reported loci.

  5. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

    NARCIS (Netherlands)

    C.J. Willer (Cristen); E.K. Speliotes (Elizabeth); R.J.F. Loos (Ruth); S. Li (Shengxu); C.M. Lindgren (Cecilia); I.M. Heid (Iris); S.I. Berndt (Sonja); A.L. Elliott (Amanda); A.U. Jackson (Anne); C. Lamina (Claudia); G. Lettre (Guillaume); N. Lim (Noha); H.N. Lyon (Helen); S.A. McCarroll (Steven); K. Papadakis (Konstantinos); L. Qi (Lu); J.C. Randall (Joshua); R.M. Roccasecca; S. Sanna (Serena); P. Scheet (Paul); M.N. Weedon (Michael); E. Wheeler (Eleanor); J.H. Zhao (Jing Hua); L.C. Jacobs (Leonie); I. Prokopenko (Inga); N. Soranzo (Nicole); T. Tanaka (Toshiko); N.J. Timpson (Nicholas); P. Almgren (Peter); A.J. Bennett (Amanda); R.N. Bergman (Richard); S. Bingham (Sheila); L.L. Bonnycastle (Lori); M.J. Brown (Morris); N.P. Burtt (Noël); P.S. Chines (Peter); L. Coin (Lachlan); F.S. Collins (Francis); J. Connell (John); C. Cooper (Charles); G.D. Smith; E.M. Dennison (Elaine); P. Deodhar (Parimal); M.R. Erdos (Michael); K. Estrada Gil (Karol); D.M. Evans (David); L. Gianniny (Lauren); C. Gieger (Christian); C.J. Gillson (Christopher); C. Guiducci (Candace); R. Hackett (Rachel); D. Hadley (David); A.S. Hall (Alistair); A.S. Havulinna (Aki); J. Hebebrand (Johannes); A. Hofman (Albert); B. Isomaa (Bo); T. Johnson (Toby); P. Jousilahti (Pekka); Z. Jovanovic (Zorica); K-T. Khaw (Kay-Tee); P. Kraft (Peter); M. Kuokkanen (Mikko); J. Kuusisto (Johanna); J. Laitinen (Jaana); E. Lakatta (Edward); J. Luan; R.N. Luben (Robert); M. Mangino (Massimo); W.L. McArdle (Wendy); T. Meitinger (Thomas); A. Mulas (Antonella); P. Munroe (Patricia); N. Narisu (Narisu); A.R. Ness (Andrew); K. Northstone (Kate); S. O'Rahilly (Stephen); C. Purmann (Carolin); M.G. Rees (Matthew); M. Ridderstråle (Martin); S.M. Ring (Susan); F. Rivadeneira Ramirez (Fernando); A. Ruokonen (Aimo); M.S. Sandhu (Manjinder); J. Saramies (Jouko); L.J. Scott (Laura); A. Scuteri (Angelo); K. Silander (Kaisa); M.A. Sims (Matthew); K. Song (Kijoung); J. Stephens (Jonathan); S. Stevens (Suzanne); H.M. Stringham (Heather); Y.C.L. Tung (Loraine); T.T. Valle (Timo); P. Tikka-Kleemola (Päivi); K.S. Vimaleswaran (Karani); P. Vollenweider (Peter); G. Waeber (Gérard); C. Wallace (Chris); R.M. Watanabe (Richard); D. Waterworth (Dawn); N. Watkins (Nicholas); J.C.M. Witteman (Jacqueline); E. Zeggini (Eleftheria); G. Zhai (Guangju); M.C. Zillikens (Carola); D. Altshuler (David); M. Caulfield (Mark); S.J. Chanock (Stephen); I.S. Farooqi (Sadaf); L. Ferrucci (Luigi); J.M. Guralnik (Jack); A.T. Hattersley (Andrew); F.B. Hu (Frank); M.-R. Jarvelin (Marjo-Riitta); M. Laakso (Markku); V. Mooser (Vincent); K.K. Ong (Ken); W.H. Ouwehand (Willem); V. Salomaa (Veikko); N.J. Samani (Nilesh); T.D. Spector (Timothy); T. Tuomi (Tiinamaija); J. Tuomilehto (Jaakko); M. Uda (Manuela); A.G. Uitterlinden (André); P. Deloukas (Panagiotis); N.J. Wareham (Nick); T.M. Frayling (Timothy); L. Groop (Leif); R.B. Hayes (Richard); D. Hunter (David); K.L. Mohlke (Karen); L. Peltonen (Leena Johanna); D. Schlessinger (David); D.P. Strachan (David); H.E. Wichmann (Erich); M.I. McCarthy (Mark); M. Boehnke (Michael); I. Barroso (Inês); G.R. Abecasis (Gonçalo); J.N. Hirschhorn (Joel)

    2009-01-01

    textabstractCommon variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts

  6. Quantitative trait loci for resistance to stripe rust of wheat revealed using global field nurseries and opportunities for stacking resistance genes.

    Science.gov (United States)

    Bokore, Firdissa E; Cuthbert, Richard D; Knox, Ron E; Randhawa, Harpinder S; Hiebert, Colin W; DePauw, Ron M; Singh, Asheesh K; Singh, Arti; Sharpe, Andrew G; N'Diaye, Amidou; Pozniak, Curtis J; McCartney, Curt; Ruan, Yuefeng; Berraies, Samia; Meyer, Brad; Munro, Catherine; Hay, Andy; Ammar, Karim; Huerta-Espino, Julio; Bhavani, Sridhar

    2017-12-01

    Quantitative trait loci controlling stripe rust resistance were identified in adapted Canadian spring wheat cultivars providing opportunity for breeders to stack loci using marker-assisted breeding. Stripe rust or yellow rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss., is a devastating disease of common wheat (Triticum aestivum L.) in many regions of the world. The objectives of this research were to identify and map quantitative trait loci (QTL) associated with stripe rust resistance in adapted Canadian spring wheat cultivars that are effective globally, and investigate opportunities for stacking resistance. Doubled haploid (DH) populations from the crosses Vesper/Lillian, Vesper/Stettler, Carberry/Vesper, Stettler/Red Fife and Carberry/AC Cadillac were phenotyped for stripe rust severity and infection response in field nurseries in Canada (Lethbridge and Swift Current), New Zealand (Lincoln), Mexico (Toluca) and Kenya (Njoro), and genotyped with SNP markers. Six QTL for stripe rust resistance in the population of Vesper/Lillian, five in Vesper/Stettler, seven in Stettler/Red Fife, four in Carberry/Vesper and nine in Carberry/AC Cadillac were identified. Lillian contributed stripe rust resistance QTL on chromosomes 4B, 5A, 6B and 7D, AC Cadillac on 2A, 2B, 3B and 5B, Carberry on 1A, 1B, 4A, 4B, 7A and 7D, Stettler on 1A, 2A, 3D, 4A, 5B and 6A, Red Fife on 2D, 3B and 4B, and Vesper on 1B, 2B and 7A. QTL on 1A, 1B, 2A, 2B, 3B, 4A, 4B, 5B, 7A and 7D were observed in multiple parents. The populations are compelling sources of recombination of many stripe rust resistance QTL for stacking disease resistance. Gene pyramiding should be possible with little chance of linkage drag of detrimental genes as the source parents were mostly adapted cultivars widely grown in Canada.

  7. Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations.

    Science.gov (United States)

    Yoneyama, Sachiko; Guo, Yiran; Lanktree, Matthew B; Barnes, Michael R; Elbers, Clara C; Karczewski, Konrad J; Padmanabhan, Sandosh; Bauer, Florianne; Baumert, Jens; Beitelshees, Amber; Berenson, Gerald S; Boer, Jolanda M A; Burke, Gregory; Cade, Brian; Chen, Wei; Cooper-Dehoff, Rhonda M; Gaunt, Tom R; Gieger, Christian; Gong, Yan; Gorski, Mathias; Heard-Costa, Nancy; Johnson, Toby; Lamonte, Michael J; McDonough, Caitrin; Monda, Keri L; Onland-Moret, N Charlotte; Nelson, Christopher P; O'Connell, Jeffrey R; Ordovas, Jose; Peter, Inga; Peters, Annette; Shaffer, Jonathan; Shen, Haiqinq; Smith, Erin; Speilotes, Liz; Thomas, Fridtjof; Thorand, Barbara; Monique Verschuren, W M; Anand, Sonia S; Dominiczak, Anna; Davidson, Karina W; Hegele, Robert A; Heid, Iris; Hofker, Marten H; Huggins, Gordon S; Illig, Thomas; Johnson, Julie A; Kirkland, Susan; König, Wolfgang; Langaee, Taimour Y; McCaffery, Jeanne; Melander, Olle; Mitchell, Braxton D; Munroe, Patricia; Murray, Sarah S; Papanicolaou, George; Redline, Susan; Reilly, Muredach; Samani, Nilesh J; Schork, Nicholas J; Van Der Schouw, Yvonne T; Shimbo, Daichi; Shuldiner, Alan R; Tobin, Martin D; Wijmenga, Cisca; Yusuf, Salim; Hakonarson, Hakon; Lange, Leslie A; Demerath, Ellen W; Fox, Caroline S; North, Kari E; Reiner, Alex P; Keating, Brendan; Taylor, Kira C

    2014-05-01

    Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to date. We assessed the association between SNPs and BMI-adjusted WC and WHR and unadjusted WC in up to 57 412 individuals of European descent from 22 cohorts collaborating with the NHLBI's Candidate Gene Association Resource (CARe) project. The study population consisted of women and men aged 20-80 years. Study participants were genotyped using the ITMAT/Broad/CARE array, which includes ∼50 000 cosmopolitan tagged SNPs across ∼2100 cardiovascular-related genes. Each trait was modeled as a function of age, study site and principal components to control for population stratification, and we conducted a fixed-effects meta-analysis. No new loci for WC were observed. For WHR analyses, three novel loci were significantly associated (P < 2.4 × 10(-6)). Previously unreported rs2811337-G near TMCC1 was associated with increased WHR (β ± SE, 0.048 ± 0.008, P = 7.7 × 10(-9)) as was rs7302703-G in HOXC10 (β = 0.044 ± 0.008, P = 2.9 × 10(-7)) and rs936108-C in PEMT (β = 0.035 ± 0.007, P = 1.9 × 10(-6)). Sex-stratified analyses revealed two additional novel signals among females only, rs12076073-A in SHC1 (β = 0.10 ± 0.02, P = 1.9 × 10(-6)) and rs1037575-A in ATBDB4 (β = 0.046 ± 0.01, P = 2.2 × 10(-6)), supporting an already established sexual dimorphism of central adiposity-related genetic variants. Functional analysis using ENCODE and eQTL databases revealed that several of these loci are in regulatory regions or regions with differential expression in adipose tissue.

  8. Influence of Different Yield Loci on Failure Prediction with Damage Models

    Science.gov (United States)

    Heibel, S.; Nester, W.; Clausmeyer, T.; Tekkaya, A. E.

    2017-09-01

    Advanced high strength steels are widely used in the automotive industry to simultaneously improve crash performance and reduce the car body weight. A drawback of these multiphase steels is their sensitivity to damage effects and thus the reduction of ductility. For that reason the Forming Limit Curve is only partially suitable for this class of steels. An improvement in failure prediction can be obtained by using damage mechanics. The objective of this paper is to comparatively review the phenomenological damage model GISSMO and the Enhanced Lemaitre Damage Model. GISSMO is combined with three different yield loci, namely von Mises, Hill48 and Barlat2000 to investigate the influence of the choice of the plasticity description on damage modelling. The Enhanced Lemaitre Model is used with Hill48. An inverse parameter identification strategy for a DP1000 based on stress-strain curves and optical strain measurements of shear, uniaxial, notch and (equi-)biaxial tension tests is applied to calibrate the models. A strong dependency of fracture strains on the choice of yield locus can be observed. The identified models are validated on a cross-die cup showing ductile fracture with slight necking.

  9. Mapping quantitative trait loci affecting fatness and breast muscle weight in meat-type chicken lines divergently selected on abdominal fatness

    Directory of Open Access Journals (Sweden)

    Neau André

    2006-01-01

    Full Text Available Abstract Quantitative trait loci (QTL for abdominal fatness and breast muscle weight were investigated in a three-generation design performed by inter-crossing two experimental meat-type chicken lines that were divergently selected on abdominal fatness. A total of 585 F2 male offspring from 5 F1 sires and 38 F1 dams were recorded at 8 weeks of age for live body, abdominal fat and breast muscle weights. One hundred-twenty nine microsatellite markers, evenly located throughout the genome and heterozygous for most of the F1 sires, were used for genotyping the F2 birds. In each sire family, those offspring exhibiting the most extreme values for each trait were genotyped. Multipoint QTL analyses using maximum likelihood methods were performed for abdominal fat and breast muscle weights, which were corrected for the effects of 8-week body weight, dam and hatching group. Isolated markers were assessed by analyses of variance. Two significant QTL were identified on chromosomes 1 and 5 with effects of about one within-family residual standard deviation. One breast muscle QTL was identified on GGA1 with an effect of 2.0 within-family residual standard deviation.

  10. Quantitative trait loci for tibial bone strength in C57BL/6J and C3H ...

    Indian Academy of Sciences (India)

    in C57BL/6J and C3H/HeJ inbred strains of mice. J. Genet. 89, 21–27]. Introduction. In the last decade, mouse model has increasingly been used in the identification of genetic factors that regulate osteo- porosis related traits such as bone mineral density (BMD). A F2 population derived from the cross between C57BL/6J.

  11. Construction of a dense genetic linkage map and mapping quantitative trait loci for economic traits of a doubled haploid population of Pyropia haitanensis (Bangiales, Rhodophyta).

    Science.gov (United States)

    Xu, Yan; Huang, Long; Ji, Dehua; Chen, Changsheng; Zheng, Hongkun; Xie, Chaotian

    2015-09-21

    Pyropia haitanensis is one of the most economically important mariculture crops in China. A high-density genetic map has not been published yet and quantitative trait locus (QTL) mapping has not been undertaken for P. haitanensis because of a lack of sufficient molecular markers. Specific length amplified fragment sequencing (SLAF-seq) was developed recently for large-scale, high resolution de novo marker discovery and genotyping. In this study, SLAF-seq was used to obtain mass length polymorphic markers to construct a high-density genetic map for P. haitanensis. In total, 120.33 Gb of data containing 75.21 M pair-end reads was obtained after sequencing. The average coverage for each SLAF marker was 75.50-fold in the male parent, 74.02-fold in the female parent, and 6.14-fold average in each double haploid individual. In total, 188,982 SLAFs were detected, of which 6731 were length polymorphic SLAFs that could be used to construct a genetic map. The final map included 4550 length polymorphic markers that were combined into 740 bins on five linkage groups, with a length of 874.33 cM and an average distance of 1.18 cM between adjacent bins. This map was used for QTL mapping to identify chromosomal regions associated with six economically important traits: frond length, width, thickness, fresh weight, growth rates of frond length and growth rates of fresh weight. Fifteen QTLs were identified for these traits. The value of phenotypic variance explained by an individual QTL ranged from 9.59 to 16.61 %, and the confidence interval of each QTL ranged from 0.97 cM to 16.51 cM. The first high-density genetic linkage map for P. haitanensis was constructed, and fifteen QTLs associated with six economically important traits were identified. The results of this study not only provide a platform for gene and QTL fine mapping, map-based gene isolation, and molecular breeding for P. haitanensis, but will also serve as a reference for positioning sequence scaffolds on a physical

  12. A genome-wide SNP scan reveals novel loci for egg production and quality traits in white leghorn and brown-egg dwarf layers.

    Science.gov (United States)

    Liu, Wenbo; Li, Dongfeng; Liu, Jianfeng; Chen, Sirui; Qu, Lujiang; Zheng, Jiangxia; Xu, Guiyun; Yang, Ning

    2011-01-01

    Availability of the complete genome sequence as well as high-density SNP genotyping platforms allows genome-wide association studies (GWAS) in chickens. A high-density SNP array containing 57,636 markers was employed herein to identify associated variants underlying egg production and quality traits within two lines of chickens, i.e., White Leghorn and brown-egg dwarf layers. For each individual, age at first egg (AFE), first egg weight (FEW), and number of eggs (EN) from 21 to 56 weeks of age were recorded, and egg quality traits including egg weight (EW), eggshell weight (ESW), yolk weight (YW), eggshell thickness (EST), eggshell strength (ESS), albumen height(AH) and Haugh unit(HU) were measured at 40 and 60 weeks of age. A total of 385 White Leghorn females and 361 brown-egg dwarf dams were selected to be genotyped. The genome-wide scan revealed 8 SNPs showing genome-wise significant (Pegg production and quality traits under the Fisher's combined probability method. Some significant SNPs are located in known genes including GRB14 and GALNT1 that can impact development and function of ovary, but more are located in genes with unclear functions in layers, and need to be studied further. Many chromosome-wise significant SNPs were also detected in this study and some of them are located in previously reported QTL regions. Most of loci detected in this study are novel and the follow-up replication studies may be needed to further confirm the functional significance for these newly identified SNPs.

  13. Quantitative trait loci (QTL study identifies novel genomic regions associated to Chiari-like malformation in Griffon Bruxellois dogs.

    Directory of Open Access Journals (Sweden)

    Philippe Lemay

    Full Text Available Chiari-like malformation (CM is a developmental abnormality of the craniocervical junction that is common in the Griffon Bruxellois (GB breed with an estimated prevalence of 65%. This disease is characterized by overcrowding of the neural parenchyma at the craniocervical junction and disturbance of cerebrospinal fluid (CSF flow. The most common clinical sign is pain either as a direct consequence of CM or neuropathic pain as a consequence of secondary syringomyelia. The etiology of CM remains unknown but genetic factors play an important role. To investigate the genetic complexity of the disease, a quantitative trait locus (QTL approach was adopted. A total of 14 quantitative skull and atlas measurements were taken and were tested for association to CM. Six traits were found to be associated to CM and were subjected to a whole-genome association study using the Illumina canine high density bead chip in 74 GB dogs (50 affected and 24 controls. Linear and mixed regression analyses identified associated single nucleotide polymorphisms (SNPs on 5 Canis Familiaris Autosomes (CFAs: CFA2, CFA9, CFA12, CFA14 and CFA24. A reconstructed haplotype of 0.53 Mb on CFA2 strongly associated to the height of the cranial fossa (diameter F and an haplotype of 2.5 Mb on CFA14 associated to both the height of the rostral part of the caudal cranial fossa (AE and the height of the brain (FG were significantly associated to CM after 10 000 permutations strengthening their candidacy for this disease (P = 0.0421, P = 0.0094 respectively. The CFA2 QTL harbours the Sall-1 gene which is an excellent candidate since its orthologue in humans is mutated in Townes-Brocks syndrome which has previously been associated to Chiari malformation I. Our study demonstrates the implication of multiple traits in the etiology of CM and has successfully identified two new QTL associated to CM and a potential candidate gene.

  14. Influencing agent group behavior by adjusting cultural trait values.

    Science.gov (United States)

    Tuli, Gaurav; Hexmoor, Henry

    2010-10-01

    Social reasoning and norms among individuals that share cultural traits are largely fashioned by those traits. We have explored predominant sociological and cultural traits. We offer a methodology for parametrically adjusting relevant traits. This exploratory study heralds a capability to deliberately tune cultural group traits in order to produce a desired group behavior. To validate our methodology, we implemented a prototypical-agent-based simulated test bed for demonstrating an exemplar from intelligence, surveillance, and reconnaissance scenario. A group of simulated agents traverses a hostile territory while a user adjusts their cultural group trait settings. Group and individual utilities are dynamically observed against parametric values for the selected traits. Uncertainty avoidance index and individualism are the cultural traits we examined in depth. Upon the user's training of the correspondence between cultural values and system utilities, users deliberately produce the desired system utilities by issuing changes to trait. Specific cultural traits are without meaning outside of their context. Efficacy and timely application of traits in a given context do yield desirable results. This paper heralds a path for the control of large systems via parametric cultural adjustments.

  15. Hundreds of variants clustered in genomic loci and biological pathways affect human height

    NARCIS (Netherlands)

    H.L. Allen; K. Estrada Gil (Karol); G. Lettre (Guillaume); S.I. Berndt (Sonja); F. Rivadeneira Ramirez (Fernando); C.J. Willer (Cristen); A.U. Jackson (Anne); S. Vedantam (Sailaja); S. Raychaudhuri (Soumya); T. Ferreira (Teresa); A.R. Wood (Andrew); R.J. Weyant (Robert); A.V. Segrè (Ayellet); E.K. Speliotes (Elizabeth); E. Wheeler (Eleanor); N. Soranzo (Nicole); J.H. Park; J. Yang (Joanna); D.F. Gudbjartsson (Daniel); N.L. Heard-Costa (Nancy); J.C. Randall (Joshua); L. Qi (Lu); A.V. Smith (Albert Vernon); R. Mägi (Reedik); T. Pastinen (Tomi); L. Liang (Liming); I.M. Heid (Iris); J. Luan; G. Thorleifsson (Gudmar); T.W. Winkler (Thomas); M.E. Goddard (Michael); K.S. Lo; C. Palmer (Cameron); T. Workalemahu (Tsegaselassie); Y.S. Aulchenko (Yurii); A. Johansson (Åsa); M.C. Zillikens (Carola); M.F. Feitosa (Mary Furlan); T. Esko (Tõnu); T. Johnson (Toby); S. Ketkar (Shamika); P. Kraft (Peter); M. Mangino (Massimo); I. Prokopenko (Inga); D. Absher (Devin); E. Albrecht (Eva); F.D.J. Ernst (Florian); N.L. Glazer (Nicole); C. Hayward (Caroline); J.J. Hottenga (Jouke Jan); K.B. Jacobs (Kevin); J.W. Knowles (Joshua); Z. Kutalik (Zoltán); K.L. Monda (Keri); O. Polasek (Ozren); M. Preuss (Michael); N.W. Rayner (Nigel William); N.R. Robertson (Neil); V. Steinthorsdottir (Valgerdur); J.P. Tyrer (Jonathan); B.F. Voight (Benjamin); F. Wiklund (Fredrik); J. Xu (Jianfeng); J.H. Zhao (Jing Hua); D.R. Nyholt (Dale); N. Pellikka (Niina); M. Perola (Markus); J.R.B. Perry (John); I. Surakka (Ida); M.L. Tammesoo; E.L. Altmaier (Elizabeth); N. Amin (Najaf); T. Aspelund (Thor); T. Bhangale (Tushar); G. Boucher (Gabrielle); D.I. Chasman (Daniel); C. Chen (Constance); L. Coin (Lachlan); M.N. Cooper (Matthew); A.L. Dixon (Anna); Q. Gibson (Quince); E. Grundberg (Elin); K. Hao (Ke); M.J. Junttila (Juhani); R.C. Kaplan (Robert); J. Kettunen (Johannes); I.R. König (Inke); T. Kwan (Tony); R.W. Lawrence (Robert); D.F. Levinson (Douglas); M. Lorentzon (Mattias); B. McKnight (Barbara); A.D. Morris (Andrew); M. Müller (Martina); J.S. Ngwa; S. Purcell (Shaun); S. Rafelt (Suzanne); R.M. Salem (Rany); E. Salvi (Erika); S. Sanna (Serena); J. Shi (Jianxin); U. Sovio (Ulla); J.R. Thompson (John); M.C. Turchin (Michael); L. Vandenput (Liesbeth); D.J. Verlaan (Dominique); V. Vitart (Veronique); C.C. White (Charles); A. Ziegler (Andreas); P. Almgren (Peter); A.J. Balmforth (Anthony); H. Campbell (Harry); L. Citterio (Lorena); A. de Grandi (Alessandro); A. Dominiczak (Anna); J. Duan (Jubao); P. Elliott (Paul); R. Elosua (Roberto); J.G. Eriksson (Johan); N.B. Freimer (Nelson); E.J.C. Geus (Eco); N. Glorioso (Nicola); S. Haiqing (Shen); A.L. Hartikainen; A.S. Havulinna (Aki); A.A. Hicks (Andrew); J. Hui (Jennie); W. Igl (Wilmar); T. Illig (Thomas); A. Jula (Antti); E. Kajantie (Eero); T.O. Kilpeläinen (Tuomas); M. Koiranen (Markku); I. Kolcic (Ivana); S. Koskinen (Seppo); P. Kovacs (Peter); J. Laitinen (Jaana); J. Liu (Jianjun); M.L. Lokki; A. Marusic (Ana); A. Maschio; T. Meitinger (Thomas); A. Mulas (Antonella); G. Paré (Guillaume); A.N. Parker (Alex); J. Peden (John); A. Petersmann (Astrid); I. Pichler (Irene); K.H. Pietilainen (Kirsi Hannele); A. Pouta (Anneli); M. Ridderstråle (Martin); J.I. Rotter (Jerome); J.G. Sambrook (Jennifer); A.R. Sanders (Alan); C.O. Schmidt (Carsten Oliver); J. Sinisalo (Juha); J.H. Smit (Jan); H.M. Stringham (Heather); G.B. Walters (Bragi); E. Widen (Elisabeth); S.H. Wild (Sarah); G.A.H.M. Willemsen (Gonneke); L. Zagato (Laura); L. Zgaga (Lina); P. Zitting (Paavo); H. Alavere (Helene); M. Farrall (Martin); W.L. McArdle (Wendy); M. Nelis (Mari); M.J. Peters (Marjolein); S. Ripatti (Samuli); J.B.J. van Meurs (Joyce); K.K.H. Aben (Katja); J.S. Beckmann (Jacques); J.P. Beilby (John); R.N. Bergman (Richard); S.M. Bergmann (Sven); F.S. Collins (Francis); D. Cusi (Daniele); M. den Heijer (Martin); G. Eiriksdottir (Gudny); P.V. Gejman (Pablo); A.S. Hall (Alistair); A. Hamsten (Anders); H.V. Huikuri (Heikki); C. Iribarren (Carlos); M. Kähönen (Mika); J. Kaprio (Jaakko); S. Kathiresan (Sekar); L.A.L.M. Kiemeney (Bart); T. Kocher (Thomas); L.J. Launer (Lenore); T. Lehtimäki (Terho); O. Melander (Olle); T.H. Mosley (Thomas); A.W. Musk (Arthur); M.S. Nieminen (Markku); C.J. O'Donnell (Christopher); C. Ohlsson (Claes); B.A. Oostra (Ben); O. Raitakari (Olli); P.M. Ridker (Paul); J.D. Rioux (John); A. Rissanen (Aila); C. Rivolta (Carlo); H. Schunkert (Heribert); A.R. Shuldiner (Alan); D.S. Siscovick (David); M. Stumvoll (Michael); A. Tönjes (Anke); J. Tuomilehto (Jaakko); G.J. van Ommen (Gert); J. Viikari (Jorma); A.C. Heath (Andrew); N.G. Martin (Nicholas); G.W. Montgomery (Grant); M.A. Province (Mike); M.H. Kayser (Manfred); A.M. Arnold (Alice); L.D. Atwood (Larry); E.A. Boerwinkle (Eric); S.J. Chanock (Stephen); P. Deloukas (Panagiotis); C. Gieger (Christian); H. Grönberg (Henrik); A.T. Hattersley (Andrew); C. Hengstenberg (Christian); W. Hoffman (Wolfgang); G.M. Lathrop (Mark); V. Salomaa (Veikko); S. Schreiber (Stefan); M. Uda (Manuela); D. Waterworth (Dawn); A.F. Wright (Alan); T.L. Assimes (Themistocles); I.E. Barroso (Inês); A. Hofman (Albert); K.L. Mohlke (Karen); D.I. Boomsma (Dorret); M. Caulfield (Mark); L.A. Cupples (Adrienne); C.S. Fox (Caroline); V. Gudnason (Vilmundur); U. Gyllensten (Ulf); T.B. Harris (Tamara); R.B. Hayes (Richard); M.R. Järvelin; V. Mooser (Vincent); P. Munroe (Patricia); W.H. Ouwehand (Willem); B.W.J.H. Penninx (Brenda); P.P. Pramstaller (Peter Paul); T. Quertermous (Thomas); I. Rudan (Igor); N.J. Samani (Nilesh); T.D. Spector (Timothy); H. Völzke (Henry); H. Watkins (Hugh); J.F. Wilson (James); L. Groop (Leif); T. Haritunians (Talin); F.B. Hu (Frank); A. Metspalu (Andres); K.E. North (Kari); D. Schlessinger; N.J. Wareham (Nick); D.J. Hunter (David); J.R. O´Connell; D.P. Strachan (David); H.E. Wichmann (Heinz Erich); I.B. Borecki (Ingrid); C.M. van Duijn (Cornelia); E.E. Schadt (Eric); U. Thorsteinsdottir (Unnur); L. Peltonen (Leena Johanna); A.G. Uitterlinden (André); P.M. Visscher (Peter); N. Chatterjee (Nilanjan); J. Erdmann (Jeanette); R.J.F. Loos (Ruth); M. Boehnke (Michael); M.I. McCarthy (Mark); E. Ingelsson (Erik); C.M. Lindgren (Cecilia); G.R. Abecasis (Gonçalo); K. Stefansson (Kari); T.M. Frayling (Timothy); J.N. Hirschhorn (Joel); K.G. Ardlie (Kristin); M.N. Weedon (Michael)

    2010-01-01

    textabstractMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small

  16. Hundreds of variants clustered in genomic loci and biological pathways affect human height

    NARCIS (Netherlands)

    Allen, Hana Lango; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segre, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Maegi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Asa; Zillikens, M. Carola; Feitosa, Mary F.; Esko, Tonu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltan; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R. B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; Koenig, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Mueller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J. C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpelaeinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Pare, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietilainen, Kirsi H.; Pouta, Anneli; Riddertrale, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G. Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; vVan Meurs, Joyce B. J.; Aben, Katja K.; Ardlie, Kristin G.; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kahonen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimaki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Toenjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Gronberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G. Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Ines; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L. Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Ritta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Voelzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Schadt, H. -Erich; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, Andre G.; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J. F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Goncalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N.

    2010-01-01

    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions

  17. Hundreds of variants clustered in genomic loci and biological pathways affect human height

    DEFF Research Database (Denmark)

    Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume

    2010-01-01

    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions...

  18. Quantitative Trait Loci Associated with Photoperiodic Response and Stage of Diapause in the Pitcher-Plant Mosquito, Wyeomyia smithii

    Science.gov (United States)

    Mathias, Derrick; Jacky, Lucien; Bradshaw, William E.; Holzapfel, Christina M.

    2007-01-01

    A wide variety of temperate animals rely on length of day (photoperiodism) to anticipate and prepare for changing seasons by regulating the timing of development, reproduction, dormancy, and migration. Although the molecular basis of circadian rhythms regulating daily activities is well defined, the molecular basis for the photoperiodic regulation of seasonal activities is largely unknown. We use geographic variation in the photoperiodic control of diapause in the pitcher-plant mosquito Wyeomyia smithii to create the first QTL map of photoperiodism in any animal. For critical photoperiod (CPP), we detect QTL that are unique, a QTL that is sex linked, QTL that overlap with QTL for stage of diapause (SOD), and a QTL that interacts epistatically with the circadian rhythm gene, timeless. Results presented here confirm earlier studies concluding that CPP is under directional selection over the climatic gradient of North America and that the evolution of CPP is genetically correlated with SOD. Despite epistasis between timeless and a QTL for CPP, timeless is not located within any detectable QTL, indicating that it plays an ancillary role in the evolution of photoperiodism in W. smithii. Finally, we highlight one region of the genome that includes loci contributing to CPP, SOD, and hormonal regulation of development. PMID:17339202

  19. Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice.

    Directory of Open Access Journals (Sweden)

    Ryo Ishikawa

    Full Text Available Zinc (Zn is one of the essential mineral elements for both plants and humans. Zn deficiency in human is one of the major causes of hidden hunger, a serious health problem observed in many developing countries. Therefore, increasing Zn concentration in edible part is an important issue for improving human Zn nutrition. Here, we found that an Australian wild rice O. meridionalis showed higher grain Zn concentrations compared with cultivated and other wild rice species. The quantitative trait loci (QTL analysis was then performed to identify the genomic regions controlling grain Zn levels using backcross recombinant inbred lines derived from O. sativa 'Nipponbare' and O. meridionalis W1627. Four QTLs responsible for high grain Zn were detected on chromosomes 2, 9, and 10. The QTL on the chromosome 9 (named qGZn9, which showed the largest effect on grain Zn concentration was confirmed with the introgression line, which had a W1627 chromosomal segment covering the qGZn9 region in the genetic background of O. sativa 'Nipponbare'. Fine mapping of this QTL resulted in identification of two tightly linked loci, qGZn9a and qGZn9b. The candidate regions of qGZn9a and qGZn9b were estimated to be 190 and 950 kb, respectively. Furthermore, we also found that plants having a wild chromosomal segment covering qGZn9a, but not qGZn9b, is associated with fertility reduction. qGZn9b, therefore, provides a valuable allele for breeding rice with high Zn in the grains.

  20. A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans

    Science.gov (United States)

    Liu, Fan; van der Lijn, Fedde; Schurmann, Claudia; Zhu, Gu; Chakravarty, M. Mallar; Hysi, Pirro G.; Wollstein, Andreas; Lao, Oscar; de Bruijne, Marleen; Ikram, M. Arfan; van der Lugt, Aad; Rivadeneira, Fernando; Uitterlinden, André G.; Hofman, Albert; Niessen, Wiro J.; Homuth, Georg; de Zubicaray, Greig; McMahon, Katie L.; Thompson, Paul M.; Daboul, Amro; Puls, Ralf; Hegenscheid, Katrin; Bevan, Liisa; Pausova, Zdenka; Medland, Sarah E.; Montgomery, Grant W.; Wright, Margaret J.; Wicking, Carol; Boehringer, Stefan; Spector, Timothy D.; Paus, Tomáš; Martin, Nicholas G.; Biffar, Reiner; Kayser, Manfred

    2012-01-01

    Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes—PRDM16, PAX3, TP63, C5orf50, and COL17A1—in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications. PMID:23028347

  1. A genome-wide association study identifies five loci influencing facial morphology in Europeans.

    Directory of Open Access Journals (Sweden)

    Fan Liu

    2012-09-01

    Full Text Available Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

  2. Trait emotional intelligence influences on academic achievement and school behaviour.

    Science.gov (United States)

    Mavroveli, Stella; Sánchez-Ruiz, María José

    2011-03-01

    BACKGROUND. Trait emotional intelligence (trait EI or trait emotional self-efficacy) refers to individuals' emotion-related self-perceptions (Petrides, Furnham, & Mavroveli, 2007). The children's trait EI sampling domain provides comprehensive coverage of their affective personality. Preliminary evidence shows that the construct has important implications for children's psychological and behavioural adjustment. AIMS. This study investigates the associations between trait EI and school outcomes, such as performance in reading, writing, and maths, peer-rated behaviour and social competence, and self-reported bullying behaviours in a sample of primary school children. It also examines whether trait EI scores differentiate between children with and without special educational needs (SEN). SAMPLE. The sample comprised 565 children (274 boys and 286 girls) between the ages of 7 and 12 (M((age)) = 9.12 years, SD= 1.27 years) attending three English state primary schools. METHOD. Pupils completed the Trait Emotional Intelligence Questionnaire-Child Form (TEIQue-CF), the Guess Who peer assessment, the Peer-Victimization Scale, and the Bullying Behaviour Scale. Additional data on achievement and SEN were collected from the school archives. RESULTS. As predicted by trait EI theory, associations between trait EI and academic achievement were modest and limited to Year 3 children. Higher trait EI scores were related to more nominations from peers for prosocial behaviours and fewer nominations for antisocial behaviour as well as lower scores on self-reported bulling behaviours. Furthermore, SEN students scored lower on trait EI compared to students without SEN. CONCLUSIONS. Trait EI holds important and multifaceted implications for the socialization of primary schoolchildren. ©2010 The British Psychological Society.

  3. R/qtlcharts: Interactive Graphics for Quantitative Trait Locus Mapping

    OpenAIRE

    Broman, Karl W.

    2014-01-01

    Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL) (genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl?s static graphs, as well as additional interactive graphs for the explor...

  4. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

    Science.gov (United States)

    Willer, Cristen J; Speliotes, Elizabeth K; Loos, Ruth J F; Li, Shengxu; Lindgren, Cecilia M; Heid, Iris M; Berndt, Sonja I; Elliott, Amanda L; Jackson, Anne U; Lamina, Claudia; Lettre, Guillaume; Lim, Noha; Lyon, Helen N; McCarroll, Steven A; Papadakis, Konstantinos; Qi, Lu; Randall, Joshua C; Roccasecca, Rosa Maria; Sanna, Serena; Scheet, Paul; Weedon, Michael N; Wheeler, Eleanor; Zhao, Jing Hua; Jacobs, Leonie C; Prokopenko, Inga; Soranzo, Nicole; Tanaka, Toshiko; Timpson, Nicholas J; Almgren, Peter; Bennett, Amanda; Bergman, Richard N; Bingham, Sheila A; Bonnycastle, Lori L; Brown, Morris; Burtt, Noël P; Chines, Peter; Coin, Lachlan; Collins, Francis S; Connell, John M; Cooper, Cyrus; Smith, George Davey; Dennison, Elaine M; Deodhar, Parimal; Elliott, Paul; Erdos, Michael R; Estrada, Karol; Evans, David M; Gianniny, Lauren; Gieger, Christian; Gillson, Christopher J; Guiducci, Candace; Hackett, Rachel; Hadley, David; Hall, Alistair S; Havulinna, Aki S; Hebebrand, Johannes; Hofman, Albert; Isomaa, Bo; Jacobs, Kevin B; Johnson, Toby; Jousilahti, Pekka; Jovanovic, Zorica; Khaw, Kay-Tee; Kraft, Peter; Kuokkanen, Mikko; Kuusisto, Johanna; Laitinen, Jaana; Lakatta, Edward G; Luan, Jian'an; Luben, Robert N; Mangino, Massimo; McArdle, Wendy L; Meitinger, Thomas; Mulas, Antonella; Munroe, Patricia B; Narisu, Narisu; Ness, Andrew R; Northstone, Kate; O'Rahilly, Stephen; Purmann, Carolin; Rees, Matthew G; Ridderstråle, Martin; Ring, Susan M; Rivadeneira, Fernando; Ruokonen, Aimo; Sandhu, Manjinder S; Saramies, Jouko; Scott, Laura J; Scuteri, Angelo; Silander, Kaisa; Sims, Matthew A; Song, Kijoung; Stephens, Jonathan; Stevens, Suzanne; Stringham, Heather M; Tung, Y C Loraine; Valle, Timo T; Van Duijn, Cornelia M; Vimaleswaran, Karani S; Vollenweider, Peter; Waeber, Gerard; Wallace, Chris; Watanabe, Richard M; Waterworth, Dawn M; Watkins, Nicholas; Witteman, Jacqueline C M; Zeggini, Eleftheria; Zhai, Guangju; Zillikens, M Carola; Altshuler, David; Caulfield, Mark J; Chanock, Stephen J; Farooqi, I Sadaf; Ferrucci, Luigi; Guralnik, Jack M; Hattersley, Andrew T; Hu, Frank B; Jarvelin, Marjo-Riitta; Laakso, Markku; Mooser, Vincent; Ong, Ken K; Ouwehand, Willem H; Salomaa, Veikko; Samani, Nilesh J; Spector, Timothy D; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Uda, Manuela; Uitterlinden, André G; Wareham, Nicholas J; Deloukas, Panagiotis; Frayling, Timothy M; Groop, Leif C; Hayes, Richard B; Hunter, David J; Mohlke, Karen L; Peltonen, Leena; Schlessinger, David; Strachan, David P; Wichmann, H-Erich; McCarthy, Mark I; Boehnke, Michael; Barroso, Inês; Abecasis, Gonçalo R; Hirschhorn, Joel N

    2009-01-01

    Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10−8): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity. PMID:19079261

  5. Personality traits in bipolar disorder and influence on outcome.

    Science.gov (United States)

    Sparding, Timea; Pålsson, Erik; Joas, Erik; Hansen, Stefan; Landén, Mikael

    2017-05-03

    The aim was to investigate the personality profile of bipolar disorder I and II, and healthy controls, and to study whether personality influences the course of bipolar disorder. One hundred ten patients with bipolar disorder I, 85 patients with bipolar disorder II, and 86 healthy individuals had their personality profile assessed using the Swedish universities Scales of Personality (SSP), an instrument developed to explore personality-related vulnerabilities and correlates of psychiatric disorders. Patients were followed prospectively for 2 years. To assess the impact of Neuroticism, Aggressiveness, and Disinhibition on illness course, we performed logistic regressions with the outcome variables mood episodes (depressive, hypo/manic, mixed), suicide attempts, violence, and the number of sick leave days. Bipolar disorder I and II demonstrated higher global measures of Neuroticism, Aggressiveness, and Disinhibition as compared with healthy controls. A third of the patients scored ≥1 SD above the population-based normative mean on the global neuroticism measure. The two subtypes of bipolar disorder were, however, undistinguishable on all of the personality traits. In the unadjusted model, higher neuroticism at baseline predicted future depressive episodes and suicide attempts/violent behavior, but this association disappeared when adjusting for baseline depressive symptoms as assessed with MADRS. A significant minority of the patients scored ≥1 SD above the population mean on the global measures of Neuroticism, Aggressiveness and Disinhibition; scores this high are usually evident clinically. Yet, the personality profile does not seem to have prognostic value over a 2-year period.

  6. Mapping and validation of quantitative trait loci for resistance to Cercospora zeae-maydis infection in tropical maize (Zea mays L.).

    Science.gov (United States)

    Pozar, Gilberto; Butruille, David; Silva, Heyder Diniz; McCuddin, Zoe Patterson; Penna, Julio Cesar Viglioni

    2009-02-01

    Breeding for resistance to gray leaf spot, caused by Cercospora zeae-maydis (Cz) is paramount for many maize environments, in particular under warm and humid growing conditions. In this study, we mapped and characterized quantitative trait loci (QTL) involved in the resistance of maize against Cz. We confirmed the impact of the QTL on disease severity using near-isogenic lines (NILs), and estimated their effects on three major agronomic traits using their respective near isogenic hybrids (NIHs), which we obtained by crossing the NILs with an inbred from a complementary heterotic pool. We further validated three of the four QTL that were mapped using the Multiple Interval Mapping approach and showed LOD values>2.5. NILs genotype included all combinations between favorable alleles of the two QTL located in chromosome 1 (Q1 in bin 1.05 and Q2 in bin 1.07), and the allele in chromosome 3 (Q3 in bin 3.07). Each of the three QTL separately significantly reduced the severity of Cz. However, we found an unfavorable epistatic interaction between Q1 and Q2: presence of the favorable allele at one of the QTL allele effectively nullified the effect of the favorable allele at the other. In contrast, the interaction between Q2 and Q3 was additive, promoting the reduction of the severity to a greater extent than the sum of their individual effects. When evaluating the NIH we found significant individual effects for Q1 and Q3 on gray leaf spot severity, for Q2 on stalk lodging and grain yield, and for Q3 on grain moisture and stalk lodging. We detected significant epitasis between Q1 and Q2 for grain moisture and between Q1 and Q3 for stalk lodging. These results suggest that the combination of QTL impacts the effectiveness of marker-assisted selection procedures in commercial product development programs.

  7. Do gender and personality traits (BFI-10) influence self-perceived innovativeness?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2016-01-01

    's own opinion. Big Five Inventory-10 is used to measure personality traits. Findings are that conscientiousness influences self-perceived innovativeness in the eyes of others, and openness to experience influences self-perceived innovativeness in one's own opinion. Conscientiousness also influences......Innovativeness is a useful trait in many walks of life. The aim of this paper is to investigate if gender and personality traits influence rating of self-perceived innovativeness. There are two versions of the dependent variable used - innovativeness in the eyes of others, and innovativeness in one...

  8. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

    DEFF Research Database (Denmark)

    Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F

    2017-01-01

    direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting...

  9. A genome-wide meta-analysis of rice blast resistance genes and quantitative trait loci provides new insights into partial and complete resistance.

    Science.gov (United States)

    Ballini, Elsa; Morel, Jean-Benoît; Droc, Gaétan; Price, Adam; Courtois, Brigitte; Notteghem, Jean-Loup; Tharreau, Didier

    2008-07-01

    The completion of the genome sequences of both rice and Magnaporthe oryzae has strengthened the position of rice blast disease as a model to study plant-pathogen interactions in monocotyledons. Genetic studies of blast resistance in rice were established in Japan as early as 1917. Despite such long-term study, examples of cultivars with durable resistance are rare, partly due to our limited knowledge of resistance mechanisms. A rising number of blast resistance genes and quantitative trait loci (QTL) have been genetically described, and some have been characterized during the last 20 years. Using the rice genome sequence, can we now go a step further toward a better understanding of the genetics of blast resistance by combining all these results? Is such knowledge appropriate and sufficient to improve breeding for durable resistance? A review of bibliographic references identified 85 blast resistance genes and approximately 350 QTL, which we mapped on the rice genome. These data provide a useful update on blast resistance genes as well as new insights to help formulate hypotheses about the molecular function of blast QTL, with special emphasis on QTL for partial resistance. All these data are available from the OrygenesDB database.

  10. Assessing the feasibility of linkage disequilibrium methods for mapping complex traits: an initial screen for bipolar disorder loci on chromosome 18.

    Science.gov (United States)

    Escamilla, M A; McInnes, L A; Spesny, M; Reus, V I; Service, S K; Shimayoshi, N; Tyler, D J; Silva, S; Molina, J; Gallegos, A; Meza, L; Cruz, M L; Batki, S; Vinogradov, S; Neylan, T; Nguyen, J B; Fournier, E; Araya, C; Barondes, S H; Leon, P; Sandkuijl, L A; Freimer, N B

    1999-06-01

    Linkage disequilibrium (LD) analysis has been promoted as a method of mapping disease genes, particularly in isolated populations, but has not yet been used for genome-screening studies of complex disorders. We present results of a study to investigate the feasibility of LD methods for genome screening using a sample of individuals affected with severe bipolar mood disorder (BP-I), from an isolated population of the Costa Rican central valley. Forty-eight patients with BP-I were genotyped for markers spaced at approximately 6-cM intervals across chromosome 18. Chromosome 18 was chosen because a previous genome-screening linkage study of two Costa Rican families had suggested a BP-I locus on this chromosome. Results of the current study suggest that LD methods will be useful for mapping BP-I in a larger sample. The results also support previously reported possible localizations (obtained from a separate collection of patients) of BP-I-susceptibility genes at two distinct sites on this chromosome. Current limitations of LD screening for identifying loci for complex traits are discussed, and recommendations are made for future research with these methods.

  11. Mapping of quantitative trait loci for partial resistance to Mycosphaerella pinodes in pea (Pisum sativum L.), at the seedling and adult plant stages.

    Science.gov (United States)

    Prioul, S; Frankewitz, A; Deniot, G; Morin, G; Baranger, A

    2004-05-01

    The inheritance of resistance to Ascochyta blight, an economically important foliar disease of field pea ( Pisum sativum L.) worldwide, was investigated. Breeding resistant pea varieties to this disease, caused by Mycosphaerella pinodes, is difficult due to the availability of only partial resistance. We mapped and characterized quantitative trait loci (QTLs) for resistance to M. pinodes in pea. A population of 135 recombinant inbred lines (RILs), derived from the cross between DP (partially resistant) and JI296 (susceptible), was genotyped with morphological, RAPD, SSR and STS markers. A genetic map was elaborated, comprising 206 markers distributed over eight linkage groups and covering 1,061 cM. The RILs were assessed under growth chamber and field conditions at the seedling and adult plant stages, respectively. Six QTLs were detected at the seedling stage, which together explained up to 74% of the variance. Ten QTLs were identified at the adult plant stage in the field, and together these explained 56.6-67.1% of the variance, depending on the resistance criteria and the organ considered. Four QTLs were detected under both growth chamber and field conditions, suggesting they were not plant-stage dependent. Three QTLs for flowering date and three QTLs for plant height were also identified in the RIL population, some of which co-located with QTLs for resistance. The relationship between QTLs for resistance to M. pinodes, plant height and flowering date is discussed.

  12. Growth performance, meat quality traits, and genetic mapping of quantitative trait loci in 3 generations of Japanese quail populations (Coturnix japonica).

    Science.gov (United States)

    Tavaniello, S; Maiorano, G; Siwek, M; Knaga, S; Witkowski, A; Di Memmo, D; Bednarczyk, M

    2014-08-01

    The current research was conducted to compare growth, carcass traits, pH, intramuscular collagen (IMC) properties, and genetic bases of IMC and carcasses (breast-muscle weight) of different lines and generations of adult males and females of Japanese quail (Coturnix japonica). Forty-four quails (generation F0), 22 Pharaoh (F-33) meat-type males and 22 Standard (S-22) laying-type females, were crossed to produce the F1 hybrids generation. The F2 generation was created by mating one F1 male with one F1 female, full siblings. The birds, randomly chosen from F0 (22 males and 22 females), F1 (22 males and 22 females), and F2 (84 males and 152 females) were raised to 20 wk of age in collective cages. Quails were fed ad libitum commercial diets. At slaughter, all birds were individually weighed (after a fasting period of 12 h) and dressing yield (without giblets) was calculated. The carcasses were then dissected. Genomic DNA was extracted from all of the blood, and 30 microsatellite markers located on 2 quail chromosomes were genotyped. The F -: 33 quails had higher in vivo and postmortem performances and a higher abdominal fat percentage than those of the egg line. Meat from S -: 22 quails had a slower collagen maturation (hydroxylysylpyridinoline crosslink/collagen) and a higher ultimate pH. The F1 and F2 generations showed an evident sexual dimorphism, and an additional effect could be due to hybrid heterosis evident in F2. Meat from quails of F1 and F2 generations had a lower IMC amount with a higher degree of collagen maturation compared with parental lines. Two statistically significant QTL have been detected on quail chromosome 2 (CJA02): a QTL with an additive effect (0.50) for IMC in the marker bracket GUJ0037 and GUJ0093; a second QTL with additive (1.32) and dominant (1.91) effects for breast-muscle weight in the marker bracket GUJ0084 and GUJ0073. To our knowledge, this is the first report of a QTL associated with breast-muscle weight and IMC in quail and

  13. Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

    NARCIS (Netherlands)

    Barban, N.; Jansen, R.; de Vlaming, Ronald; Vaez, A.; Mandemakers, J.J.; Tropf, F.C.; Shen, X.; Wilson, J.F.; Chasman, D.I.; Nolte, I.M.; Mbarek, H.; Boomsma, D.I.; de Geus, E.J.C.; Penninx, B.W.J.H.; Willemsen, G.; Zondervan, K.T.; Stefansson, K.; Krueger, R.F.; Lee, J.J.; Benjamin, D.J.; Cesarini, D.; Koellinger, P.D.; den Hoed, M.A.H.; Snieder, H.; Mills, M.C.

    2016-01-01

    The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the

  14. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma

    NARCIS (Netherlands)

    Chambers, John C.; Zhang, Weihua; Sehmi, Joban; Li, Xinzhong; Wass, Mark N.; van der Harst, Pim; Holm, Hilma; Sanna, Serena; Kavousi, Maryam; Baumeister, Sebastian E.; Coin, Lachlan J.; Deng, Guohong; Gieger, Christian; Heard-Costa, Nancy L.; Hottenga, Jouke-Jan; Kühnel, Brigitte; Kumar, Vinod; Lagou, Vasiliki; Liang, Liming; Luan, Jian'an; Vidal, Pedro Marques; Mateo Leach, Irene; O'Reilly, Paul F.; Peden, John F.; Rahmioglu, Nilufer; Soininen, Pasi; Speliotes, Elizabeth K.; Yuan, Xin; Thorleifsson, Gudmar; Alizadeh, Behrooz Z.; Atwood, Larry D.; Borecki, Ingrid B.; Brown, Morris J.; Charoen, Pimphen; Cucca, Francesco; Das, Debashish; de Geus, Eco J. C.; Dixon, Anna L.; Döring, Angela; Ehret, Georg; Eyjolfsson, Gudmundur I.; Farrall, Martin; Forouhi, Nita G.; Friedrich, Nele; Goessling, Wolfram; Gudbjartsson, Daniel F.; Harris, Tamara B.; Hartikainen, Anna-Liisa; Heath, Simon; Hirschfield, Gideon M.; Hofman, Albert; Homuth, Georg; Hyppönen, Elina; Janssen, Harry L. A.; Johnson, Toby; Kangas, Antti J.; Kema, Ido P.; Kühn, Jens P.; Lai, Sandra; Lathrop, Mark; Lerch, Markus M.; Li, Yun; Liang, T. Jake; Lin, Jing-Ping; Loos, Ruth J. F.; Martin, Nicholas G.; Moffatt, Miriam F.; Montgomery, Grant W.; Munroe, Patricia B.; Musunuru, Kiran; Nakamura, Yusuke; O'Donnell, Christopher J.; Olafsson, Isleifur; Penninx, Brenda W.; Pouta, Anneli; Prins, Bram P.; Prokopenko, Inga; Puls, Ralf; Ruokonen, Aimo; Savolainen, Markku J.; Schlessinger, David; Schouten, Jeoffrey N. L.; Seedorf, Udo; Sen-Chowdhry, Srijita; Siminovitch, Katherine A.; Smit, Johannes H.; Spector, Timothy D.; Tan, Wenting; Teslovich, Tanya M.; Tukiainen, Taru; Uitterlinden, Andre G.; van der Klauw, Melanie M.; Vasan, Ramachandran S.; Wallace, Chris; Wallaschofski, Henri; Wichmann, H.-Erich; Willemsen, Gonneke; Würtz, Peter; Xu, Chun; Yerges-Armstrong, Laura M.; Abecasis, Goncalo R.; Ahmadi, Kourosh R.; Boomsma, Dorret I.; Caulfield, Mark; Cookson, William O.; van Duijn, Cornelia M.; Froguel, Philippe; Matsuda, Koichi; McCarthy, Mark I.; Meisinger, Christa; Mooser, Vincent; Pietiläinen, Kirsi H.; Schumann, Gunter; Snieder, Harold; Sternberg, Michael J. E.; Stolk, Ronald P.; Thomas, Howard C.; Thorsteinsdottir, Unnur; Uda, Manuela; Waeber, Gérard; Wareham, Nicholas J.; Waterworth, Dawn M.; Watkins, Hugh; Whitfield, John B.; Witteman, Jacqueline C. M.; Wolffenbuttel, Bruce H. R.; Fox, Caroline S.; Ala-Korpela, Mika; Stefansson, Kari; Vollenweider, Peter; Völzke, Henry; Schadt, Eric E.; Scott, James; Järvelin, Marjo-Riitta; Elliott, Paul; Kooner, Jaspal S.; Voight, Benjamin F.; Scott, Laura J.; Steinthorsdottir, Valgerdur; Morris, Andrew P.; Dina, Christian; Welch, Ryan P.; Zeggini, Eleftheria; Huth, Cornelia; Aulchenko, Yurii S.; Mcculloch, Laura J.; Ferreira, Teresa; Grallert, Harald; Amin, Najaf; Wu, Guanming; Willer, Cristen J.; Raychaudhuri, Soumya; Mccarroll, Steve A.; Langenberg, Claudia; Hofmann, Oliver M.; Dupuis, Josée; Qi, Lu; Segrè, Ayellet V.; van Hoek, Mandy; Navarro, Pau; Ardlie, Kristin; Balkau, Beverley; Benediktsson, Rafn; Bennett, Amanda J.; Blagieva, Roza; Boerwinkle, Eric; Bonnycastle, Lori L.; Bengtsson Boström, Kristina; Bravenboer, Bert; Bumpstead, Suzannah; Burtt, Noël P.; Charpentier, Guillaume; Chines, Peter S.; Cornelis, Marilyn; Couper, David J.; Crawford, Gabe; Doney, Alex S. F.; Elliott, Katherine S.; Elliott, Amanda L.; Erdos, Michael R.; Franklin, Christopher S.; Ganser, Martha; Grarup, Niels; Green, Todd; Griffin, Simon; Groves, Christopher J.; Guiducci, Candace; Hadjadj, Samy; Hassanali, Neelam; Herder, Christian; Isomaa, Bo; Jackson, Anne U.; Johnson, Paul R. V.; Jørgensen, Torben; Kao, Wen H. L.; Klopp, Norman; Kong, Augustine; Kraft, Peter; Kuusisto, Johanna; Lauritzen, Torsten; Li, Man; Lieverse, Aloysius; Lindgren, Cecilia M.; Lyssenko, Valeriya; Marre, Michel; Meitinger, Thomas; Midthjell, Kristian; Morken, Mario A.; Narisu, Narisu; Nilsson, Peter; Owen, Katharine R.; Payne, Felicity; Perry, John R. B.; Petersen, Ann-Kristin; Platou, Carl; Proença, Christine; Rathmann, Wolfgang; William Rayner, N.; Robertson, Neil R.; Rocheleau, Ghislain; Roden, Michael; Sampson, Michael J.; Saxena, Richa; Shields, Beverley M.; Shrader, Peter; Sigurdsson, Gunnar; Sparsø, Thomas; Strassburger, Klaus; Stringham, Heather M.; Sun, Qi; Swift, Amy J.; Thorand, Barbara; Tichet, Jean; Tuomi, Tiinamaija; van Dam, Rob M.; van Haeften, Timon W.; van Herpt, Thijs; van Vliet-Ostaptchouk, Jana V.; Walters, G. Bragi; Weedon, Michael N.; Wijmenga, Cisca; Witteman, Jacqueline; Bergman, Richard N.; Cauchi, Stephane; Collins, Francis S.; Gloyn, Anna L.; Gyllensten, Ulf; Hansen, Torben; Hide, Winston A.; Hitman, Graham A.; Hunter, David J.; Hveem, Kristian; Laakso, Markku; Mohlke, Karen L.; Morris, Andrew D.; Palmer, Colin N. A.; Pramstaller, Peter P.; Rudan, Igor; Sijbrands, Eric; Stein, Lincoln D.; Tuomilehto, Jaakko; Uitterlinden, Andre; Walker, Mark; Watanabe, Richard M.; Boehm, Bernhard O.; Campbell, Harry; Daly, Mark J.; Hattersley, Andrew T.; Hu, Frank B.; Meigs, James B.; Pankow, James S.; Pedersen, Oluf; Barroso, Inês; Florez, Jose C.; Frayling, Timothy M.; Groop, Leif; Sladek, Rob; Wilson, James F.; Illig, Thomas; Altshuler, David; Boehnke, Michael; Lango Allen, H.; Estrada, K.; Lettre, G.; Berndt, S. I.; Weedon, M. N.; Rivadeneira, F.; Willer, C. J.; Jackson, A. U.; Vedantam, S.; Raychaudhuri, S.; Ferreira, T.; Wood, A. R.; Weyant, R. J.; Segrè, A. V.; Speliotes, E. K.; Wheeler, E.; Soranzo, N.; Park, J. H.; Yang, J.; Gudbjartsson, D.; Heard-Costa, N. L.; Randall, J. C.; Qi, L.; Smith, A. Vernon; Mägi, R.; Pastinen, T.; Liang, L.; Heid, I. M.; Luan, J.; Thorleifsson, G.; Winkler, T. W.; Goddard, M. E.; Sin Lo, K.; Palmer, C.; Workalemahu, T.; Aulchenko, Y. S.; Johansson, A.; Zillikens, M. C.; Feitosa, M. F.; Esko, T.; Johnson, T.; Ketkar, S.; Kraft, P.; Mangino, M.; Prokopenko, I.; Absher, D.; Albrecht, E.; Ernst, F.; Glazer, N. L.; Hayward, C.; Hottenga, J. J.; Jacobs, K. B.; Knowles, J. W.; Kutalik, Z.; Monda, K. L.; Polasek, O.; Preuss, M.; Rayner, N. W.; Robertson, N. R.; Steinthorsdottir, V.; Tyrer, J. P.; Voight, B. F.; Wiklund, F.; Xu, J.; Zhao, J. Hua; Nyholt, D. R.; Pellikka, N.; Perola, M.; Perry, J. R.; Surakka, I.; Tammesoo, M. L.; Altmaier, E. L.; Amin, N.; Aspelund, T.; Bhangale, T.; Boucher, G.; Chasman, D. I.; Chen, C.; Coin, L.; Cooper, M. N.; Dixon, A. L.; Gibson, Q.; Grundberg, E.; Hao, K.; Juhani Junttila, M.; Kaplan, L. M.; Kettunen, J.; König, I. R.; Kwan, T.; Lawrence, R. W.; Levinson, D. F.; Lorentzon, M.; McKnight, B.; Morris, A. P.; Müller, M.; Suh Ngwa, J.; Purcell, S.; Rafelt, S.; Salem, R. M.; Salvi, E.; Sanna, S.; Shi, J.; Sovio, U.; Thompson, J. R.; Turchin, M. C.; Vandenput, L.; Verlaan, D. J.; Vitart, V.; White, C. C.; Ziegler, A.; Almgren, P.; Balmforth, A. J.; Campbell, H.; Citterio, L.; de Grandi, A.; Dominiczak, A.; Duan, J.; Elliott, P.; Elosua, R.; Eriksson, J. G.; Freimer, N. B.; Geus, E. J.; Glorioso, N.; Haiqing, S.; Hartikainen, A. L.; Havulinna, A. S.; Hicks, A. A.; Hui, J.; Igl, W.; Illig, T.; Jula, A.; Kajantie, E.; Kilpeläinen, T. O.; Koiranen, M.; Kolcic, I.; Koskinen, S.; Kovacs, P.; Laitinen, J.; Liu, J.; Lokki, M. L.; Marusic, A.; Maschio, A.; Meitinger, T.; Mulas, A.; Paré, G.; Parker, A. N.; Peden, J. F.; Petersmann, A.; Pichler, I.; Pietiläinen, K. H.; Pouta, A.; Ridderstråle, M.; Rotter, J. I.; Sambrook, J. G.; Sanders, A. R.; Schmidt, C. Oliver; Sinisalo, J.; Smit, J. H.; Stringham, H. M.; Widen, E.; Wild, S. H.; Willemsen, G.; Zagato, L.; Zgaga, L.; Zitting, P.; Alavere, H.; Farrall, M.; McArdle, W. L.; Nelis, M.; Peters, M. J.; Ripatti, S.; van Meurs, J. B.; Aben, K. K.; Ardlie, K. G.; Beckmann, J. S.; Beilby, J. P.; Bergman, R. N.; Bergmann, S.; Collins, F. S.; Cusi, D.; den Heijer, M.; Eiriksdottir, G.; Gejman, P. V.; Hamsten, A.; Huikuri, H. V.; Iribarren, C.; Kähönen, M.; Kaprio, J.; Kathiresan, S.; Kiemeney, L.; Kocher, T.; Launer, L. J.; Lehtimäki, T.; Melander, O.; Mosley, T. H.; Musk, A. W.; Nieminen, M. S.; O'Donnell, C. J.; Ohlsson, C.; Oostra, B.; Palmer, L. J.; Raitakari, O.; Ridker, P. M.; Rioux, J. D.; Rissanen, A.; Rivolta, C.; Schunkert, H.; Shuldiner, A. R.; Siscovick, D. S.; Stumvoll, M.; Tönjes, A.; Tuomilehto, J.; van Ommen, G. J.; Viikari, J.; Heath, A. C.; Martin, N. G.; Montgomery, G. W.; Province, M. A.; Kayser, M.; Arnold, A. M.; Atwood, L. D.; Boerwinkle, E.; Chanock, S. J.; Deloukas, P.; Gieger, C.; Grönberg, H.; Hall, P.; Hattersley, A. T.; Hengstenberg, C.; Hoffman, W.; Lathrop, G. Mark; Salomaa, V.; Schreiber, S.; Uda, M.; Waterworth, D.; Wright, A. F.; Assimes, T. L.; Barroso, I.; Hofman, A.; Mohlke, K. L.; Boomsma, D. I.; Caulfield, M. J.; Cupples, L. Adrienne; Erdmann, J.; Fox, C. S.; Gudnason, V.; Gyllensten, U.; Harris, T. B.; Hayes, R. B.; Jarvelin, M. R.; Mooser, V.; Munroe, P. B.; Ouwehand, W. H.; Penninx, B. W.; Pramstaller, P. P.; Quertermous, T.; Rudan, I.; Samani, N. J.; Spector, T. D.; Völzke, H.; Watkins, H.; Wilson, J. F.; Groop, L. C.; Haritunians, T.; Hu, F. B.; Kaplan, R. C.; Metspalu, A.; North, K. E.; Schlessinger, D.; Wareham, N. J.; Hunter, D. J.; O'Connell, J. R.; Strachan, D. P.; Wichmann, H. E.; Borecki, I. B.; van Duijn, C. M.; Schadt, E. E.; Thorsteinsdottir, U.; Peltonen, L.; Uitterlinden, A. G.; Visscher, P. M.; Chatterjee, N.; Loos, R. J.; Boehnke, M.; McCarthy, M. I.; Ingelsson, E.; Lindgren, C. M.; Abecasis, G. R.; Stefansson, K.; Frayling, T. M.; Hirschhorn, J. N.; Teslovich, T. M.; Musunuru, K.; Smith, A. V.; Edmondson, A. C.; Stylianou, I. M.; Koseki, M.; Pirruccello, J. P.; Johansen, C. T.; Fouchier, S. W.; Isaacs, A.; Peloso, G. M.; Barbalic, M.; Ricketts, S. L.; Bis, J. C.; Chambers, J.; Orho-Melander, M.; Li, X.; Guo, X.; Li, M.; Cho, Y. Shin; Go, M. Jin; Kim, Y. Jin; Lee, J. Y.; Park, T.; Kim, K.; Sim, X.; Ong, R. Twee-Hee; Croteau-Chonka, D. C.; Lange, L. A.; Smith, J. D.; Song, K.; Yuan, X.; Lamina, C.; Zhang, W.; Zee, R. Y.; Witteman, J. C.; Whitfield, J. B.; Waterworth, D. M.; Waeber, G.; Vollenweider, P.; Tanaka, T.; Silander, K.; Sijbrands, E. J.; Scuteri, A.; Scott, J.; Salomaa, J.; Sabatti, C.; Ruokonen, A.; Rose, L. M.; Roberts, R.; Rieder, M.; Psaty, B. M.; Pedersen, N. L.; Pattaro, C.; Pare, G.; Oostra, B. A.; Nickerson, D. A.; McPherson, R.; McArdle, W.; Masson, D.; Marroni, F.; Magnusson, P. K.; Lucas, G.; Luben, R.; Langenberg, C.; Lakatta, E. G.; Laaksonen, R.; Kyvik, K. O.; Kronenberg, F.; Khaw, K. T.; Janssens, A. C.; Hovingh, G. Kees; Hastie, N. D.; Hall, A. S.; Guiducci, C.; Gonzalez, E.; Gieger, N. B.; Ferrucci, L.; Ejebe, K. G.; Döring, A.; Dominiczak, A. F.; Demissie, S.; de Geus, E. J.; de Faire, U.; Crawford, G.; Chen, Y. D.; Burtt, N. P.; Bonnycastle, L. L.; Boekholdt, S. M.; Bandinelli, S.; Ballantyne, C. M.; Ballantyne, T. L.; Altshuler, D.; Seielstad, M.; Wong, T. Y.; Tai, E. S.; Feranil, A. B.; Kuzawa, C. W.; Adair, L. S.; Taylor, H. A.; Gabriel, S. B.; Wilson, J. G.; Holm, H.; Krauss, R. M.; Ordovas, J. M.; Kooner, J. S.; Tall, A. R.; Hegele, R. A.; Kastelein, J. J.; Reilly, M. P.; Cupples, L. A.; Sandhu, M. S.; Rader, D. J.; Hernaez, Ruben; Kim, Lauren J.; Palmer, Cameron D.; Gudnason, Vilmundur; Eiriksdottir, Gudny; Garcia, Melissa E.; Launer, Lenore J.; Nalls, Michael A.; Clark, Jeanne M.; Mitchell, Braxton D.; Shuldiner, Alan R.; Butler, Johannah L.; Tomas, Marta; Hoffmann, Udo; Hwang, Shih-Jen; Massaro, Joseph M.; Sahani, Dushyant V.; Salomaa, Veikko; Schwartz, Stephen M.; Siscovick, David S.; Carr, J. Jeffrey; Feitosa, Mary F.; Smith, Albert V.; Kao, W. H. Linda; Hirschhorn, Joel N.; Ehret, Georg B.; Rice, Kenneth M.; Bochud, Murielle; Johnson, Andrew D.; Chasman, Daniel I.; Tobin, Martin D.; Verwoert, Germaine C.; Pihur, Vasyl; Bragg-Gresham, Jennifer L.; Teumer, Alexander; Glazer, Nicole L.; Launer, Lenore; Zhao, Jing Hua; Aulchenko, Yurii; Sober, Siim; Parsa, Afshin; Arora, Pankaj; Dehghan, Abbas; Zhang, Feng; Lucas, Gavin; Hicks, Andrew A.; Tanaka, Toshiko; Wild, Sarah H.; Igl, Wilmar; Milaneschi, Yuri; Parker, Alex N.; Fava, Cristiano; Fox, Ervin R.; Kumari, Meena; Go, Min Jin; Kao, Wen Hong Linda; Sjogren, Marketa; Vinay, D. G.; Alexander, Myriam; Tabara, Yasuharu; Shaw-Hawkins, Sue; Whincup, Peter H.; Liu, Yongmei; Shi, Gang; Tayo, Bamidele; Seielstad, Mark; Sim, Xueling; Nguyen, Khanh-Dung Hoang; Lehtimaki, Terho; Matullo, Giuseppe; Wu, Ying; Gaunt, Tom R.; Onland-Moret, N. Charlotte; Cooper, Matthew N.; Platou, Carl G. P.; Org, Elin; Hardy, Rebecca; Dahgam, Santosh; Palmen, Jutta; Vitart, Veronique; Braund, Peter S.; Kuznetsova, Tatiana; Uiterwaal, Cuno S. P. M.; Adeyemo, Adebowale; Palmas, Walter; Ludwig, Barbara; Tomaszewski, Maciej; Tzoulaki, Ioanna; Palmer, Nicholette D.; Aspelund, Thor; Garcia, Melissa; Chang, Yen-Pei C.; O'Connell, Jeffrey R.; Steinle, Nanette I.; Grobbee, Diederick E.; Arking, Dan E.; Kardia, Sharon L.; Morrison, Alanna C.; Hernandez, Dena; Najjar, Samer; McArdle, Wendy L.; Hadley, David; Connell, John M.; Hingorani, Aroon D.; Day, Ian N. M.; Lawlor, Debbie A.; Beilby, John P.; Lawrence, Robert W.; Clarke, Robert; Collins, Rory; Hopewell, Jemma C.; Ongen, Halit; Dreisbach, Albert W.; Li, Yali; Young, J. H.; Bis, Joshua C.; Kahonen, Mika; Viikari, Jorma; Adair, Linda S.; Lee, Nanette R.; Chen, Ming-Huei; Olden, Matthias; Pattaro, Cristian; Bolton, Judith A. Hoffman; Kottgen, Anna; Bergmann, Sven; Chaturvedi, Nish R.; Islam, Muhammad; Jafar, Tazeen H.; Erdmann, Jeanette; Kulkarni, Smita R.; Bornstein, Stefan R.; Grassler, Jurgen; Kettunen, Johannes; Howard, Philip; Taylor, Andrew; Guarrera, Simonetta; Ricceri, Fulvio; Emilsson, Valur; Plump, Andrew; Barroso, Ines; Khaw, Kay-Tee; Weder, Alan B.; Hunt, Steven C.; Sun, Yan V.; Peltonen, Leena; Perola, Markus; Vartiainen, Erkki; Brand, Stefan-Martin; Staessen, Jan A.; Wang, Thomas J.; Burton, Paul R.; Artigas, Maria Soler; Dong, Yanbin; Wang, Xiaoling; Zhu, Haidong; Lohman, Kurt K.; Rudock, Megan E.; Heckbert, Susan R.; Smith, Nicholas L.; Wiggins, Kerri L.; Doumatey, Ayo; Shriner, Daniel; Veldre, Gudrun; Viigimaa, Margus; Kinra, Sanjay; Prabhakaran, Dorairajan; Tripathy, Vikal; Langefeld, Carl D.; Rosengren, Annika; Thelle, Dag S.; Corsi, Anna Maria; Singleton, Andrew; Forrester, Terrence; Hilton, Gina; McKenzie, Colin A.; Salako, Tunde; Iwai, Naoharu; Kita, Yoshikuni; Ogihara, Toshio; Ohkubo, Takayoshi; Okamura, Tomonori; Ueshima, Hirotsugu; Umemura, Satoshi; Eyheramendy, Susana; Cho, Yoon Shin; Kim, Hyung-Lae; Lee, Jong-Young; Sehmi, Joban S.; Hedblad, Bo; Smith, George Davey; Wong, Andrew; Stančakova, Alena; Raffel, Leslie J.; Yao, Jie; Kathiresan, Sekar; O'Donnell, Chris; Schwartz, Steven M.; Ikram, M. Arfan; Longstreth, Will T.; Mosley, Thomas H.; Seshadri, Sudha; Shrine, Nick R. G.; Wain, Louise V.; Laitinen, Jaana; Zitting, Paavo; Cooper, Jackie A.; Humphries, Steve E.; Danesh, John; Rasheed, Asif; Goel, Anuj; Hamsten, Anders; Bakker, Stephan J. L.; van Gilst, Wiek H.; Janipalli, Charles S.; Mani, K. Radha; Yajnik, Chittaranjan S.; Mattace-Raso, Francesco U. S.; Oostra, Ben A.; Demirkan, Ayse; Isaacs, Aaron; Rivadeneira, Fernando; Lakatta, Edward G.; Orru, Marco; Scuteri, Angelo; Lyytikainen, Leo-Pekka; Wurz, Peter; Ong, Rick Twee-Hee; Dorr, Marcus; Kroemer, Heyo K.; Volker, Uwe; Volzke, Henry; Galan, Pilar; Hercberg, Serge; Zelenika, Diana; Deloukas, Panos; Mangino, Massimo; Spector, Tim D.; Zhai, Guangju; Meschia, James F.; Sharma, Pankaj; Terzic, Janos; Kumar, M. J. Kranthi; Denniff, Matthew; Zukowska-Szczechowska, Ewa; Wagenknecht, Lynne E.; Fowkes, F. Gerald R.; Charchar, Fadi J.; Schwarz, Peter E. H.; Hayward, Caroline; Guo, Xiuqing; Rotimi, Charles; Bots, Michiel L.; Brand, Eva; Samani, Nilesh J.; Polasek, Ozren; Talmud, Philippa J.; Nyberg, Fredrik; Kuh, Diana; Laan, Maris; Palmer, Lyle J.; van der Schouw, Yvonne T.; Casas, Juan P.; Vineis, Paolo; Raitakari, Olli; Ganesh, Santhi K.; Wong, Tien Y.; Tai, E. Shyong; Cooper, Richard S.; Rao, Dabeeru C.; Morris, Richard W.; Dominiczak, Anna F.; Kivimaki, Mika; Marmot, Michael G.; Miki, Tetsuro; Saleheen, Danish; Chandak, Giriraj R.; Coresh, Josef; Navis, Gerjan; Han, Bok-Ghee; Zhu, Xiaofeng; Melander, Olle; Ridker, Paul M.; Bandinelli, Stefania; Gyllensten, Ulf B.; Wright, Alan F.; Ferrucci, Luigi; Elosua, Roberto; Soranzo, Nicole; Sijbrands, Eric J. G.; Meneton, Pierre; Rotter, Jerome I.; Rettig, Rainer; Strachan, David P.; Beckmann, Jacques S.; Larson, Martin G.; Jarvelin, Marjo-Riitta; Psaty, Bruce M.; Chakravarti, Aravinda; Newton-Cheh, Christopher; Levy, Daniel; Caulfield, Mark J.; Dupuis, J.; Saxena, R.; Bouatia-Naji, N.; Gloyn, A. L.; Randall, J.; Rybin, D.; Henneman, P.; Grallert, H.; Dehghan, A.; Franklin, C. S.; Navarro, P.; Goel, A.; Egan, J. M.; Lajunen, T.; Grarup, N.; Sparsø, T.; Doney, A.; Kanoni, S.; Shrader, P.; Cavalcanti-Proença, C.; Kumari, M.; Timpson, N. J.; Zabena, C.; Rocheleau, G.; An, P.; O'Connell, J.; Elliott, A.; McCarroll, S. A.; Payne, F.; Roccasecca, R. M.; Pattou, F.; Sethupathy, P.; Ardlie, K.; Ariyurek, Y.; Balkau, B.; Barter, P.; Ben-Shlomo, Y.; Benediktsson, R.; Bennett, A. J.; Bochud, M.; Bonnefond, A.; Borch-Johnsen, K.; Böttcher, Y.; Brunner, E.; Bumpstead, S. J.; Charpentier, G.; Chines, P.; Clarke, R.; Coin, L. J.; Cornelis, M.; Crisponi, L.; Day, I. N.; Delplanque, J.; Dina, C.; Erdos, M. R.; Fedson, A. C.; Fischer-Rosinsky, A.; Forouhi, N. G.; Frants, R.; Franzosi, M. G.; Galan, P.; Goodarzi, M. O.; Graessler, J.; Groves, C. J.; Grundy, S.; Gwilliam, R.; Hadjadj, S.; Hallmans, G.; Hammond, N.; Han, X.; Hassanali, N.; Heath, S. C.; Hercberg, S.; Herder, C.; Hillman, D. R.; Hingorani, A. D.; Hung, J.; Isomaa, B.; Johnson, P. R.; Jørgensen, T.; Kaakinen, M.; Kesaniemi, Y. A.; Kivimaki, M.; Knight, B.; Lathrop, G. M.; Lawlor, D. A.; Le Bacquer, O.; Lecoeur, C.; Li, Y.; Lyssenko, V.; Mahley, R.; Manning, A. K.; Martínez-Larrad, M. T.; McAteer, J. B.; McCulloch, L. J.; Meisinger, C.; Melzer, D.; Meyre, D.; Mitchell, B. D.; Morken, M. A.; Mukherjee, S.; Naitza, S.; Narisu, N.; Neville, M. J.; Orrù, M.; Pakyz, R.; Palmer, C. N.; Paolisso, G.; Pearson, D.; Pfeiffer, A. F.; Posthuma, D.; Potter, S. C.; Rathmann, W.; Rice, K.; Roden, M.; Rolandsson, O.; Sandbaek, A.; Sandhu, M.; Sayer, A. A.; Scheet, P.; Scott, L. J.; Seedorf, U.; Sharp, S. J.; Shields, B.; Sigurethsson, G.; Silveira, A.; Simpson, L.; Singleton, A.; Smith, N. L.; Swift, A.; Syddall, H.; Syvänen, A. C.; Thorand, B.; Tichet, J.; Tuomi, T.; van Dijk, K. W.; van Hoek, M.; Varma, D.; Visvikis-Siest, S.; Vogelzangs, N.; Wagner, P. J.; Walley, A.; Walters, G. B.; Ward, K. L.; Yarnell, J. W.; Zeggini, E.; Zelenika, D.; Zethelius, B.; Zhai, G.; Zhao, J. H.; Meneton, P.; Nathan, D. M.; Williams, G. H.; Smith, G. D.; Bornstein, S. R.; Schwarz, P.; Spranger, J.; Karpe, F.; Cooper, C.; Dedoussis, G. V.; Serrano-Ríos, M.; Morris, A. D.; Lind, L.; Franks, P. W.; Ebrahim, S.; Marmot, M.; Kao, W. H.; Pankow, J. S.; Sampson, M. J.; Kuusisto, J.; Laakso, M.; Hansen, T.; Pedersen, O.; Buchanan, T. A.; Valle, T. T.; Kong, A.; Cao, A.; Sladek, R.; Froguel, P.; Watanabe, R. M.; Meigs, J. B.; Groop, L.; Florez, J. C.

    2011-01-01

    Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P =

  15. Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure

    NARCIS (Netherlands)

    Wain, Louise V.; Verwoert, Germaine C.; O'Reilly, Paul F.; Shi, Gang; Johnson, Toby; Johnson, Andrew D.; Bochud, Murielle; Rice, Kenneth M.; Henneman, Peter; Smith, Albert V.; Ehret, Georg B.; Amin, Najaf; Larson, Martin G.; Mooser, Vincent; Hadley, David; Doerr, Marcus; Bis, Joshua C.; Aspelund, Thor; Esko, Tonu; Janssens, A. Cecile J. W.; Zhao, Jing Hua; Heath, Simon; Laan, Maris; Fu, Jingyuan; Pistis, Giorgio; Luan, Jian'an; Arora, Pankaj; Lucas, Gavin; Pirastu, Nicola; Pichler, Irene; Jackson, Anne U.; Webster, Rebecca J.; Zhang, Feng; Peden, John F.; Schmidt, Helena; Tanaka, Toshiko; Campbell, Harry; Igl, Wilmar; Milaneschi, Yuri; Hottenga, Jouke-Jan; Vitart, Veronique; Chasman, Daniel I.; Trompet, Stella; Bragg-Gresham, Jennifer L.; Alizadeh, Behrooz Z.; Chambers, John C.; Guo, Xiuqing; Lehtimaki, Terho; Kuehnel, Brigitte; Lopez, Lorna M.; Polasek, Ozren; Boban, Mladen; Nelson, Christopher P.; Morrison, Alanna C.; Pihur, Vasyl; Ganesh, Santhi K.; Hofman, Albert; Kundu, Suman; Mattace-Raso, Francesco U. S.; Rivadeneira, Fernando; Sijbrands, Eric J. G.; Uitterlinden, Andre G.; Hwang, Shih-Jen; Vasan, Ramachandran S.; Wang, Thomas J.; Bergmann, Sven; Vollenweider, Peter; Waeber, Gerard; Laitinen, Jaana; Pouta, Anneli; Zitting, Paavo; McArdle, Wendy L.; Kroemer, Heyo K.; Voelker, Uwe; Voelzke, Henry; Glazer, Nicole L.; Taylor, Kent D.; Harris, Tamara B.; Alavere, Helene; Haller, Toomas; Keis, Aime; Tammesoo, Mari-Liis; Aulchenko, Yurii; Barroso, Ines; Khaw, Kay-Tee; Galan, Pilar; Hercberg, Serge; Lathrop, Mark; Eyheramendy, Susana; Org, Elin; Sober, Siim; Lu, Xiaowen; Nolte, Ilja M.; Penninx, Brenda W.; Corre, Tanguy; Masciullo, Corrado; Sala, Cinzia; Groop, Leif; Voight, Benjamin F.; Melander, Olle; O'Donnell, Christopher J.; Salomaa, Veikko; d'Adamo, Adamo Pio; Fabretto, Antonella; Faletra, Flavio; Ulivi, Sheila; Del Greco, Fabiola M.; Facheris, Maurizio; Collins, Francis S.; Bergman, Richard N.; Beilby, John P.; Hung, Joseph; Musk, A. William; Mangino, Massimo; Shin, So-Youn; Soranzo, Nicole; Watkins, Hugh; Goel, Anuj; Hamsten, Anders; Gider, Pierre; Loitfelder, Marisa; Zeginigg, Marion; Hernandez, Dena; Najjar, Samer S.; Navarro, Pau; Wild, Sarah H.; Corsi, Anna Maria; Singleton, Andrew; de Geus, Eco J. C.; Willemsen, Gonneke; Parker, Alex N.; Rose, Lynda M.; Buckley, Brendan; Stott, David; Orru, Marco; Uda, Manuela; van der Klauw, Melanie M.; Zhang, Weihua; Li, Xinzhong; Scott, James; Chen, Yii-Der Ida; Burke, Gregory L.; Kahonen, Mika; Viikari, Jorma; Doering, Angela; Meitinger, Thomas; Davies, Gail; Starr, John M.; Emilsson, Valur; Plump, Andrew; Lindeman, Jan H.; 't Hoen, Peter A. C.; Koenig, Inke R.; Felix, Janine F.; Clarke, Robert; Hopewell, Jemma C.; Ongen, Halit; Breteler, Monique; Debette, Stephanie; DeStefano, Anita L.; Fornage, Myriam; Mitchell, Gary F.; Smith, Nicholas L.; Holm, Hilma; Stefansson, Kari; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Samani, Nilesh J.; Preuss, Michael; Rudan, Igor; Hayward, Caroline; Deary, Ian J.; Wichmann, H-Erich; Raitakari, Olli T.; Palmas, Walter; Kooner, Jaspal S.; Stolk, Ronald P.; Jukema, J. Wouter; Wright, Alan F.; Boomsma, Dorret I.; Bandinelli, Stefania; Gyllensten, Ulf B.; Wilson, James F.; Ferrucci, Luigi; Schmidt, Reinhold; Farrall, Martin; Spector, Tim D.; Palmer, Lyle J.; Tuomilehto, Jaakko; Pfeufer, Arne; Gasparini, Paolo; Siscovick, David; Altshuler, David; Loos, Ruth J. F.; Toniolo, Daniela; Snieder, Harold; Gieger, Christian; Meneton, Pierre; Wareham, Nicholas J.; Oostra, Ben A.; Metspalu, Andres; Launer, Lenore; Rettig, Rainer; Strachan, David P.; Beckmann, Jacques S.; Witteman, Jacqueline C. M.; Erdmann, Jeanette; van Dijk, Ko Willems; Boerwinkle, Eric; Boehnke, Michael; Ridker, Paul M.; Jarvelin, Marjo-Riitta; Chakravarti, Aravinda; Abecasis, Goncalo R.; Gudnason, Vilmundur; Newton-Cheh, Christopher; Levy, Daniel; Munroe, Patricia B.; Psaty, Bruce M.; Caulfield, Mark J.; Rao, Dabeeru C.; Tobin, Martin D.; Elliott, Paul; van Duijn, Cornelia M.

    2011-01-01

    Numerous genetic loci have been associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans(1-3). We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N = 74,064) and follow-up studies (N = 48,607), we

  16. Genome-wide analysis identifies 12 loci influencing human reproductive behavior

    NARCIS (Netherlands)

    Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J; Tropf, Felix C; Shen, Xia; Wilson, James F; Chasman, Daniel I; Nolte, Ilja M; Tragante, Vinicius; van der Laan, Sander W; Perry, John R B; Kong, Augustine; Ahluwalia, Tarunveer S; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J; Gieger, Christian; Gunderson, Erica P; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F; McMahon, George; Meddens, S Fleur W; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A; Monnereau, Claire; van der Most, Peter J; Myhre, Ronny; Nalls, Mike A; Nutile, Teresa; Kalafati, Ioanna Panagiota; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B; Rich-Edwards, Janet; Rietveld, Cornelius A; Robino, Antonietta; Rose, Lynda M; Rueedi, Rico; Ryan, Kathleen A; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A; Stolk, Lisette; Streeten, Elizabeth; Tönjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I; Buring, Julie E; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R; Cucca, Francesco; Toniolo, Daniela; Davey-Smith, George; Deary, Ian J; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M; de Geus, Eco J C; Eriksson, Johan G; Evans, Denis A; Faul, Jessica D; Sala, Cinzia Felicita; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J F; de Haan, Hugoline G; Haerting, Johannes; Harris, Tamara B; Heath, Andrew C; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hyppönen, Elina; Jacobsson, Bo; Jaddoe, Vincent W V; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L R; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William G; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia M; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; McQuillan, Ruth; Medland, Sarah E; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Traglia, Michela; Milani, Lili; Mitchell, Paul; Montgomery, Grant W; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W J H; Perola, Markus; Peyser, Patricia A; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M; Ring, Susan M; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D; Starr, John M; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tung, Joyce Y; Uitterlinden, André G; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G; Wang, Jie Jin; Wareham, Nicholas J; Weir, David R; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F; Zondervan, Krina T; Stefansson, Kari; Krueger, Robert F; Lee, James J; Benjamin, Daniel J; Cesarini, David; Koellinger, Philipp D; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C

    2016-01-01

    The genetic architecture of human reproductive behavior age at first birth (AFB) and number of children ever born (NEB) has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the

  17. Genome-wide analysis identifies 12 loci influencing human reproductive behavior

    NARCIS (Netherlands)

    Barban, Nicola; Jansen, Rick; De Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; Van Der Laan, Sander W.; Perry, John R B; Kong, Augustine; Ahluwalia, Tarunveer S.; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E.; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; Van Der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Kalafati, Ioanna Panagiota; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathleen A.; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tönjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Toniolo, Daniela; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; Van Duijn, Cornelia M.; De Geus, Eco J C; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Sala, Cinzia Felicita; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans Jörgen; Greiser, Karin Halina; Groenen, Patrick J F; De Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G.; Hopper, John; Hyppönen, Elina; Jacobsson, Bo; Jaddoe, Vincent W V; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L R; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William G.; Lai, Sandra; Lehtimäki, Terho; Liewald, David C.; Lindgren, Cecilia M.; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrikke; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Traglia, Michela; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; De Mutsert, Renée; Nohr, Ellen A.; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W J H; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Roy Thurik, A.; Timpson, Nicholas J.; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; Den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.

    2016-01-01

    The genetic architecture of human reproductive behavior - age at first birth (AFB) and number of children ever born (NEB) - has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the

  18. Genome-wide analysis identifies 12 loci influencing human reproductive behavior

    NARCIS (Netherlands)

    Barban, Nicola; Jansen, Rick; Vlaming, de Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; Laan, van der Sander W.; Perry, John R.B.; Kong, Augustine; Ahluwalia, Tarunveer S.; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E.; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S.F.W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; Most, van der Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Kalafati, Ioanna Panagiota; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathleen A.; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tönjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Toniolo, Daniela; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; Duijn, van Cornelia M.; Geus, de Eco J.C.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Sala, Cinzia Felicita; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; Haan, de Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G.; Hopper, John; Hyppönen, Elina; Jacobsson, Bo; Jaddoe, Vincent W.V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; Bianca, la Martina; Lachance, Genevieve; Iacono, William G.; Lai, Sandra; Lehtimäki, Terho; Liewald, David C.; Lindgren, Cecilia M.; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Traglia, Michela; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; Mutsert, de Renée; Nohr, Ellen A.; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda W.J.H.; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A.R.; Timpson, Nicholas J.; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; Hoed, den Marcel; Snieder, Harold; Mills, Melinda C.

    2016-01-01

    The genetic architecture of human reproductive behavior—age at first birth (AFB) and number of children ever born (NEB)—has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the

  19. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels

    DEFF Research Database (Denmark)

    Kilpeläinen, Tuomas O; Carli, Jayne F Martin; Skowronski, Alicja A

    2016-01-01

    Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered...

  20. The influence of genetic drift and selection on quantitative traits in a plant pathogenic fungus.

    Science.gov (United States)

    Stefansson, Tryggvi S; McDonald, Bruce A; Willi, Yvonne

    2014-01-01

    Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55-0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.

  1. Round fruit shape in WI7239 cucumber is controlled by two interacting quantitative trait loci with one putatively encoding a tomato SUN homolog.

    Science.gov (United States)

    Pan, Yupeng; Liang, Xinjing; Gao, Meiling; Liu, Hanqiang; Meng, Huanwen; Weng, Yiqun; Cheng, Zhihui

    2017-03-01

    QTL analysis revealed two interacting loci, FS1.2 and FS2.1, underlying round fruit shape in WI7239 cucumber; CsSUN , a homolog of tomato fruit shape gene SUN , was a candidate for FS1.2. Fruit size is an important quality and yield trait in cucumber, but its genetic basis remains poorly understood. Here we reported QTL mapping results on fruit size with segregating populations derived from the cross between WI7238 (long fruit) and WI7239 (round fruit) inbred cucumber lines. Phenotypic data of fruit length and diameter were collected at anthesis, immature and mature fruit stages in four environments. Ten major-effect QTL were detected for six traits; synthesis of information from these QTL supported two genes, FS1.2 and FS2.1, underlying fruit size variation in the examined populations. Under the two-gene model, deviation from expected segregation ratio in fruit length and diameter among segregating populations was observed, which could be explained mainly by the interactions between FS1.2 and FS2.1, and segregation distortion in the FS2.1 region. Genome-wide candidate gene search identified CsSUN, a homolog of the tomato fruit shape gene SUN, as the candidate for FS1.2. The round-fruited WI7239 had a 161-bp deletion in the first exon of CsSUN, and its expression in WI7239 was significantly lower than that in WI7238. A marker derived from this deletion was mapped at the peak location of FS1.2 in QTL analysis. Comparative analysis suggested the melon gene CmSUN-14, a homolog of CsSUN as a candidate of the fl2/fd2/fw2 QTL in melon. This study revealed the unique genetic architecture of round fruit shape in WI7239 cucumber. It also highlights the power of QTL analysis for traits with a simple genetic basis but their expression is complicated by other factors.

  2. Eggplant Resistance to the Ralstonia solanacearum Species Complex Involves Both Broad-Spectrum and Strain-Specific Quantitative Trait Loci

    Directory of Open Access Journals (Sweden)

    Sylvia Salgon

    2017-05-01

    Full Text Available Bacterial wilt (BW is a major disease of solanaceous crops caused by the Ralstonia solanacearum species complex (RSSC. Strains are grouped into five phylotypes (I, IIA, IIB, III, and IV. Varietal resistance is the most sustainable strategy for managing BW. Nevertheless, breeding to improve cultivar resistance has been limited by the pathogen’s extensive genetic diversity. Identifying the genetic bases of specific and non-specific resistance is a prerequisite to breed improvement. A major gene (ERs1 was previously mapped in eggplant (Solanum melongena L. using an intraspecific population of recombinant inbred lines derived from the cross of susceptible MM738 (S × resistant AG91-25 (R. ERs1 was originally found to control three strains from phylotype I, while being totally ineffective against a virulent strain from the same phylotype. We tested this population against four additional RSSC strains, representing phylotypes I, IIA, IIB, and III in order to clarify the action spectrum of ERs1. We recorded wilting symptoms and bacterial stem colonization under controlled artificial inoculation. We constructed a high-density genetic map of the population using single nucleotide polymorphisms (SNPs developed from genotyping-by-sequencing and added 168 molecular markers [amplified fragment length polymorphisms (AFLPs, simple sequence repeats (SSRs, and sequence-related amplified polymorphisms (SRAPs] developed previously. The new linkage map based on a total of 1,035 markers was anchored on eggplant, tomato, and potato genomes. Quantitative trait locus (QTL mapping for resistance against a total of eight RSSC strains resulted in the detection of one major phylotype-specific QTL and two broad-spectrum QTLs. The major QTL, which specifically controls three phylotype I strains, was located at the bottom of chromosome 9 and corresponded to the previously identified major gene ERs1. Five candidate R-genes were underlying this QTL, with different alleles

  3. The Influence of Personality Traits on the Use of Memory English Language Learning Strategies

    Science.gov (United States)

    Fazeli, Seyed Hossein

    2012-01-01

    The present study aims to find out the influence of personality traits on the choice and use of Memory English Language Learning Strategies (MELLSs) for learners of English as a foreign language, and the role of personality traits in the prediction of use of such Strategies. Four instruments were used, which were Adapted Inventory for Memory…

  4. Herd characteristics influence farmers’ preferences for trait improvements in Danish Red and Danish Jersey cows

    DEFF Research Database (Denmark)

    Slagboom, Margot; Kargo, Morten; Edwards, David

    2016-01-01

    of a cluster analysis, three distinct clusters of farmers were identified per breed. Comparisons of herd characteristics between clusters suggest that farmers choose to improve traits that are problematic in their herds. This study shows that heterogeneity exists in farmers’ preferences for trait improvements...... and that herd characteristics influence these preferences in DR and DJ....

  5. Interaction of Induced Anxiety and Verbal Working Memory: Influence of Trait Anxiety

    Science.gov (United States)

    Patel, Nilam; Stoodley, Catherine; Pine, Daniel S.; Grillon, Christian; Ernst, Monique

    2017-01-01

    This study examines the influence of trait anxiety on working memory (WM) in safety and threat. Interactions between experimentally induced anxiety and WM performance (on different cognitive loads) have been reported in healthy, nonanxious subjects. Differences in trait anxiety may moderate these interactions. Accordingly, these interactions may…

  6. Hepatitis B virus genotypes, expression quantitative trait loci for ZNRD1-AS1 and their interactions in hepatocellular carcinoma

    Science.gov (United States)

    Wen, Juan; Xu, Lu; Liu, Yao; Zhu, Jian; Zhu, Liguo; Hu, Zhibin; Ma, Hongxia; Liu, Li

    2016-01-01

    Genetic variants in zinc ribbon domain-containing 1 antisense RNA 1 (ZNRD1-AS1) have been reported to be associated with development of hepatocellular carcinoma (HCC). We sought to determine the influences of ZNRD1-AS1 polymorphisms and their interactions with Hepatitis B virus (HBV) genotypes on the risk of HCC. In this study, we conducted a large population case-control study with 1,507 HBV-related HCC cases and 1,560 HBV persistent carriers. Three single-nucleotide polymorphisms (SNPs) in ZNRD1-AS1 (rs3757328, rs6940552 and rs9261204) were genotyped using a TaqMan allelic discrimination assay, and the HBV genotypes were identified by multiplex PCR. We found consistently significant associations between the ZNRD1-AS1 rs6940552 and rs9261204 SNPs with an increased risk of HCC (additive genetic model: adjusted OR = 1.16, 95% CI = 1.03-1.32 for rs6940552; adjusted OR =1.20, 95% CI = 1.06-1.35 for rs9261204) and found a borderline association between rs3757328 and HCC risk. Besides, we observed a dose-dependent relationship between increasing numbers of variant alleles of the SNPs and HCC risk (P for trend <0.001). Moreover, we observed a stronger combined effect of the three SNPs on HCC risk among the subjects infected with non-B genotype HBV (adjusted OR = 1.26, 95% CI = 1.05-1.50) compared with HBV B-related genotypes (adjusted OR = 0.89, 95% CI = 0.69-1.15; P= 0.029 for heterogeneity test). We also found that a multiplicative interaction between the variant alleles and the HBV genotype significantly affected HCC susceptibility (P = 0.030). Together, these results indicate that ZNRD1-AS1 may influence HCC risk accompanied by HBV genotypes. PMID:27286450

  7. Loci at chromosomes 13, 19 and 20 influence age at natural menopause

    NARCIS (Netherlands)

    L. Stolk (Lisette); G. Zhai (Guangju); J.B.J. van Meurs (Joyce); M.M.P.J. Verbiest (Michael); J.A. Visser (Jenny); K. Estrada Gil (Karol); F. Rivadeneira Ramirez (Fernando); F.M. Williams (Frances); L. Cherkas (Lynn); P. Deloukas (Panagiotis); N. Soranzo (Nicole); J.J. de Keyzer (Jules); V.J.M. Pop (Victor); P. Lips (Paul); C.E.I. Lebrun (Corinne); Y.T. van der Schouw (Yvonne); D.E. Grobbee (Diederick); J.C.M. Witteman (Jacqueline); A. Hofman (Albert); H.A.P. Pols (Huib); J.S.E. Laven (Joop); T.D. Spector (Tim); A.G. Uitterlinden (André)

    2009-01-01

    textabstractWe conducted a genome-wide association study for age at natural menopause in 2,979 European women and identified six SNPs in three loci associated with age at natural menopause: chromosome 19q13.4 (rs1172822; -0.4 year per T allele (39%); P = 6.3 × 10 11), chromosome 20p12.3 (rs236114;

  8. Loci at chromosomes 13, 19 and 20 influence age at natural menopause

    NARCIS (Netherlands)

    Stolk, L.; Zhai, G.; van Meurs, J.B.J.; Verbiest, M.M.P.J.; Visser, J.A.; Estrada, K.; Rivadeneira, F.; Williams, F.M.; Cherkas, L.; Deloukas, P.; Soranzo, N.; de Keyzer, J.J.; Pop, V.J.M.; Lips, P.T.A.M.; Lebrun, C.E.I.; van der Schouw, Y.T.; Grobbee, D.E.; Witteman, J.; Hofman, A.; Pols, H.A.P.; Laven, J.S.E.; Spector, T.D.; Uitterlinden, A.G.

    2009-01-01

    We conducted a genome-wide association study for age at natural menopause in 2,979 European women and identified six SNPs in three loci associated with age at natural menopause: chromosome 19q13.4 (rs1172822; -0.4 year per T allele (39%); P = 6.3 × 10 11), chromosome 20p12.3 (rs236114; +0.5 year per

  9. Interaction of the GCKR and A1CF loci with alcohol consumption to influence the risk of gout.

    Science.gov (United States)

    Rasheed, Humaira; Stamp, Lisa K; Dalbeth, Nicola; Merriman, Tony R

    2017-07-05

    Some gout-associated loci interact with dietary exposures to influence outcome. The aim of this study was to systematically investigate interactions between alcohol exposure and urate-associated loci in gout. A total of 2792 New Zealand European and Polynesian (Māori or Pacific) people with or without gout were genotyped for 29 urate-associated genetic variants and tested for a departure from multiplicative interaction with alcohol exposure in the risk of gout. Publicly available data from 6892 European subjects were used to test for a departure from multiplicative interaction between specific loci and alcohol exposure for the risk of hyperuricemia (HU). Multivariate adjusted logistic and linear regression was done, including an interaction term. Interaction of any alcohol exposure with GCKR (rs780094) and A1CF (rs10821905) influenced the risk of gout in Europeans (interaction term 0.28, P = 1.5 × 10 -4 ; interaction term 0.29, P = 1.4 × 10 -4 , respectively). At A1CF, alcohol exposure suppressed the gout risk conferred by the A-positive genotype. At GCKR, alcohol exposure eliminated the genetic effect on gout. In the Polynesian sample set, there was no experiment-wide evidence for interaction with alcohol in the risk of gout (all P > 8.6 × 10 -4 ). However, at GCKR, there was nominal evidence for an interaction in a direction consistent the European observation (interaction term 0.62, P = 0.05). There was no evidence for an interaction of A1CF or GCKR with alcohol exposure in determining HU. These data support the hypothesis that alcohol influences the risk of gout via glucose and apolipoprotein metabolism. In the absence of alcohol exposure, genetic variants in the GCKR and A1CF genes have a stronger role in gout.

  10. Violent peer influence: The roles of self-esteem and psychopathic traits.

    Science.gov (United States)

    Van Zalk, Maarten Herman Walter; Van Zalk, Nejra

    2015-11-01

    Evidence for the risks of psychopathic personality traits for adolescent antisocial behavior are well documented in the literature. Little is known, however, about who the peers of adolescents with these traits are and to what extent they influence one another. In the current study, three dimensions of psychopathic traits were distinguished: grandiose-manipulative traits, callous-unemotional traits, and impulsive-irresponsible traits. A dynamic social network approach was used with three waves of longitudinal data from 1,772 adolescents (51.1% girls, M age = 13.03 at first measurement). Results showed that adolescents with grandiose-manipulative and callous-unemotional traits formed peer relationships with adolescents who had low self-esteem. Furthermore, peers' violence predicted stronger increases in violence for adolescents with low self-esteem than for other adolescents, and peers' violence predicted stronger increases in adolescent violence for peers with high psychopathic traits than for other peers. Thus, findings indicate that adolescents with low self-esteem are vulnerable to deviant peer influence from peers with psychopathic traits.

  11. Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss).

    Science.gov (United States)

    Gonzalez-Pena, Dianelys; Gao, Guangtu; Baranski, Matthew; Moen, Thomas; Cleveland, Beth M; Kenney, P Brett; Vallejo, Roger L; Palti, Yniv; Leeds, Timothy D

    2016-01-01

    Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0-1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a

  12. Transcriptomic characterization of two major Fusarium resistance quantitative trait loci (QTLs), Fhb1 and Qfhs.ifa-5A, identifies novel candidate genes

    Science.gov (United States)

    Schweiger, Wolfgang; Steiner, Barbara; Ametz, Christian; Siegwart, Gerald; Wiesenberger, Gerlinde; Berthiller, Franz; Lemmens, Marc; Jia, Haiyan; Adam, Gerhard; Muehlbauer, Gary J; Kreil, David P; Buerstmayr, Hermann

    2013-01-01

    Fusarium head blight, caused by Fusarium graminearum, is a devastating disease of wheat. We developed near-isogenic lines (NILs) differing in the two strongest known F. graminearum resistance quantitative trait loci (QTLs), Qfhs.ndsu-3BS (also known as resistance gene Fhb1) and Qfhs.ifa-5A, which are located on the short arm of chromosome 3B and on chromosome 5A, respectively. These NILs showing different levels of resistance were used to identify transcripts that are changed significantly in a QTL-specific manner in response to the pathogen and between mock-inoculated samples. After inoculation with F. graminearum spores, 16 transcripts showed a significantly different response for Fhb1 and 352 for Qfhs.ifa-5A. Notably, we identified a lipid transfer protein which is constitutively at least 50-fold more abundant in plants carrying the resistant allele of Qfhs.ifa-5A. In addition to this candidate gene associated with Qfhs.ifa-5A, we identified a uridine diphosphate (UDP)-glycosyltransferase gene, designated TaUGT12887, exhibiting a positive difference in response to the pathogen in lines harbouring both QTLs relative to lines carrying only the Qfhs.ifa-5A resistance allele, suggesting Fhb1 dependence of this transcript. Yet, this dependence was observed only in the NIL with already higher basal resistance. The complete cDNA of TaUGT12887 was reconstituted from available wheat genomic sequences, and a synthetic recoded gene was expressed in a toxin-sensitive strain of Saccharomyces cerevisiae. This gene conferred deoxynivalenol resistance, albeit much weaker than that observed with the previously characterized barley HvUGT13248. PMID:23738863

  13. Identification of distinct quantitative trait loci associated with defence against the closely related aphids Acyrthosiphon pisum and A. kondoi in Medicago truncatula

    KAUST Repository

    Guo, Su-Min

    2012-03-21

    Aphids are a major family of plant insect pests. Medicago truncatula and Acyrthosiphon pisum (pea aphid, PA) are model species with a suite of resources available to help dissect the mechanism underlying plant-aphid interactions. A previous study focused on monogenic and relatively strong resistance in M. truncatula to PA and other aphid species. In this study a moderate resistance to PA was characterized in detail in the M. truncatula line A17 and compared with the highly susceptible line A20 and the more resistant line Jester. The results show that PA resistance in A17 involves both antibiosis and tolerance, and that resistance is phloem based. Quantitative trait locus (QTL) analysis using a recombinant inbred line (RIL) population (n=114) from a cross between A17 and A20 revealed that one locus, which co-segregated with AIN (Acyrthosiphon-induced necrosis) on chromosome 3, is responsible for the reduction of aphid biomass (indicator of antibiosis) for both PA and bluegreen aphid (BGA, A. kondoi), albeit to a lesser degree for PA than BGA. Interestingly, two independent loci on chromosomes 5 and 3 were identified for the plant biomass reduction (indicator of plant tolerance) by PA and BGA, respectively, demonstrating that the plant\\'s tolerance response to these two closely related aphid species is distinct. Together with previously identified major resistant (R) genes, the QTLs identified in this study are powerful tools to understand fully the spectrum of plant defence against sap-sucking insects and provide opportunities for breeders to generate effective and sustainable strategies for aphid control. 2012 The Author.

  14. Detection of parent-of-origin specific expression quantitative trait loci by cis-association analysis of gene expression in trios.

    Science.gov (United States)

    Garg, Paras; Borel, Christelle; Sharp, Andrew J

    2012-01-01

    Parent-of-origin (PofO) effects, such as imprinting are a phenomenon in which homologous chromosomes exhibit differential gene expression and epigenetic modifications according to their parental origin. Such non-Mendelian inheritance patterns are generally ignored by conventional association studies, as these tests consider the maternal and paternal alleles as equivalent. To identify regulatory regions that show PofO effects on gene expression (imprinted expression Quantitative Trait Loci, ieQTLs), here we have developed a novel method in which we associate SNP genotypes of defined parental origin with gene expression levels. We applied this method to study 59 HapMap phase II parent-offspring trios. By analyzing mother/father/child trios, rules of Mendelian inheritance allowed the parental origin to be defined for ~95% of SNPs in each child. We used 680,475 informative SNPs and corresponding expression data for 92,167 probe sets from Affymetrix GeneChip Human Exon 1.0 ST arrays and performed four independent cis-association analyses with the expression level of RefSeq genes within 1 Mb using PLINK. Independent analyses of maternal and paternal genotypes identified two significant cis-ieQTLs (pgenes SFT2D2 and SRRT associated exclusively with maternally inherited SNPs rs3753292 and rs6945374, respectively. 28 additional suggestive cis-associations with only maternal or paternal SNPs were found at a lower stringency threshold of pgenes PEG10 and TRAPPC9, demonstrating the efficacy of our method. Furthermore, comparison of our method that utilizes independent analyses of maternal and paternal genotypes with the Likelihood Ratio Test (LRT) showed it to be more effective for detecting imprinting effects than the LRT. Our method represents a novel approach that can identify imprinted regulatory elements that control gene expression, suggesting novel PofO effects in the human genome.

  15. Quantitative trait loci for blood glucose confirm diabetes predisposing and protective genes, Iddm4 and Iddm5r, in the spontaneously diabetic BB/OK rat.

    Science.gov (United States)

    Klöting, I; Van Den Brandt, J; Kovács, P

    1998-11-01

    Several crossing studies using diabetic BB/OK and diabetes-resistant rat strains have clearly shown that the MHC class-II-genes of the RT1u haplotype (Iddm1) and the lymphopenia (Iddm2) are essential but not sufficient for type 1 diabetes development. The search for additional diabetogenic genes revealed predisposing non-MHC genes, Iddm3 and Iddm4, and a diabetes protective gene, Iddm5r, cosegregating with diabetes in the BB/OK rat subline. These findings were based on cosegregation studies comparing allele frequencies between diabetic and non-diabetic cross hybrids. Since, type 1 diabetes is characterised by hyperglycaemia we analysed 22 diabetic and 43 non-diabetic [(BB x SHR)FI x BB] backcross hybrids (28M:37F) which were already homozygous for Iddml and Iddm2 to search for quantitative trait loci (QTLs) affecting blood glucose in BB/OK rats. The QTL analysis using 117 microsatellite markers located on 19 autosomal chromosomes and the X chromosome, revealed suggestive linkage for blood glucose at the same position for diabetics (lod score 3.1) and non-diabetics at an age of 16 weeks at locus D6Mgh2 on chromosome 6 (lod score 1.9). In contrast, the peak for nondiabetics at an age of 28 weeks (lod score 3.1) was located in the region on chromosome 1 flanked by D1Mgh12 and D1Mit14, whereas the peak for diabetics (lod score 1.9) was found between Sa and Igf2. The distance between two peaks is ca. 50 cM. These findings are consistent with previously described results and provide strong evidence on the relevance of the described region for the development of diabetes not only in the rat, but, regarding the chromosomal homology also in human.

  16. Quantitative Trait Loci Mapping of Western Corn Rootworm (Coleoptera: Chrysomelidae) Host Plant Resistance in Two Populations of Doubled Haploid Lines in Maize (Zea mays L.).

    Science.gov (United States)

    Bohn, Martin O; Marroquin, Juan J; Flint-Garcia, Sherry; Dashiell, Kenton; Willmot, David B; Hibbard, Bruce E

    2018-02-09

    Over the last 70 yr, more than 12,000 maize accessions have been screened for their level of resistance to western corn rootworm, Diabrotica virgifera virgifera (LeConte; Coleoptera: Chrysomelidae), larval feeding. Less than 1% of this germplasm was selected for initiating recurrent selection or other breeding programs. Selected genotypes were mostly characterized by large root systems and superior root regrowth after root damage caused by western corn rootworm larvae. However, no hybrids claiming native (i.e., host plant) resistance to western corn rootworm larval feeding are currently commercially available. We investigated the genetic basis of western corn rootworm resistance in maize materials with improved levels of resistance using linkage disequilibrium mapping approaches. Two populations of topcrossed doubled haploid maize lines (DHLs) derived from crosses between resistant and susceptible maize lines were evaluated for their level of resistance in three to four different environments. For each DHL topcross an average root damage score was estimated and used for quantitative trait loci (QTL) analysis. We found genomic regions contributing to western corn rootworm resistance on all maize chromosomes, except for chromosome 4. Models fitting all QTL simultaneously explained about 30 to 50% of the genotypic variance for root damage scores in both mapping populations. Our findings confirm the complex genetic structure of host plant resistance against western corn rootworm larval feeding in maize. Interestingly, three of these QTL regions also carry genes involved in ascorbate biosynthesis, a key compound we hypothesize is involved in the expression of western corn rootworm resistance. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Major Quantitative Trait Loci and Putative Candidate Genes for Powdery Mildew Resistance and Fruit-Related Traits Revealed by an Intraspecific Genetic Map for Watermelon (Citrullus lanatus var. lanatus).

    Science.gov (United States)

    Kim, Kwang-Hwan; Hwang, Ji-Hyun; Han, Dong-Yeup; Park, Minkyu; Kim, Seungill; Choi, Doil; Kim, Yongjae; Lee, Gung Pyo; Kim, Sun-Tae; Park, Young-Hoon

    2015-01-01

    An intraspecific genetic map for watermelon was constructed using an F2 population derived from 'Arka Manik' × 'TS34' and transcript sequence variants and quantitative trait loci (QTL) for resistance to powdery mildew (PMR), seed size (SS), and fruit shape (FS) were analyzed. The map consists of 14 linkage groups (LGs) defined by 174 cleaved amplified polymorphic sequences (CAPS), 2 derived-cleaved amplified polymorphic sequence markers, 20 sequence-characterized amplified regions, and 8 expressed sequence tag-simple sequence repeat markers spanning 1,404.3 cM, with a mean marker interval of 6.9 cM and an average of 14.6 markers per LG. Genetic inheritance and QTL analyses indicated that each of the PMR, SS, and FS traits is controlled by an incompletely dominant effect of major QTLs designated as pmr2.1, ss2.1, and fsi3.1, respectively. The pmr2.1, detected on chromosome 2 (Chr02), explained 80.0% of the phenotypic variation (LOD = 30.76). This QTL was flanked by two CAPS markers, wsb2-24 (4.00 cM) and wsb2-39 (13.97 cM). The ss2.1, located close to pmr2.1 and CAPS marker wsb2-13 (1.00 cM) on Chr02, explained 92.3% of the phenotypic variation (LOD = 68.78). The fsi3.1, detected on Chr03, explained 79.7% of the phenotypic variation (LOD = 31.37) and was flanked by two CAPS, wsb3-24 (1.91 cM) and wsb3-9 (7.00 cM). Candidate gene-based CAPS markers were developed from the disease resistance and fruit shape gene homologs located on Chr.02 and Chr03 and were mapped on the intraspecific map. Colocalization of these markers with the major QTLs indicated that watermelon orthologs of a nucleotide-binding site-leucine-rich repeat class gene containing an RPW8 domain and a member of SUN containing the IQ67 domain are candidate genes for pmr2.1 and fsi3.1, respectively. The results presented herein provide useful information for marker-assisted breeding and gene cloning for PMR and fruit-related traits.

  18. Major Quantitative Trait Loci and Putative Candidate Genes for Powdery Mildew Resistance and Fruit-Related Traits Revealed by an Intraspecific Genetic Map for Watermelon (Citrullus lanatus var. lanatus)

    Science.gov (United States)

    Kim, Kwang-Hwan; Hwang, Ji-Hyun; Han, Dong-Yeup; Park, Minkyu; Kim, Seungill; Choi, Doil; Kim, Yongjae; Lee, Gung Pyo; Kim, Sun-Tae; Park, Young-Hoon

    2015-01-01

    An intraspecific genetic map for watermelon was constructed using an F2 population derived from ‘Arka Manik’ × ‘TS34’ and transcript sequence variants and quantitative trait loci (QTL) for resistance to powdery mildew (PMR), seed size (SS), and fruit shape (FS) were analyzed. The map consists of 14 linkage groups (LGs) defined by 174 cleaved amplified polymorphic sequences (CAPS), 2 derived-cleaved amplified polymorphic sequence markers, 20 sequence-characterized amplified regions, and 8 expressed sequence tag-simple sequence repeat markers spanning 1,404.3 cM, with a mean marker interval of 6.9 cM and an average of 14.6 markers per LG. Genetic inheritance and QTL analyses indicated that each of the PMR, SS, and FS traits is controlled by an incompletely dominant effect of major QTLs designated as pmr2.1, ss2.1, and fsi3.1, respectively. The pmr2.1, detected on chromosome 2 (Chr02), explained 80.0% of the phenotypic variation (LOD = 30.76). This QTL was flanked by two CAPS markers, wsb2-24 (4.00 cM) and wsb2-39 (13.97 cM). The ss2.1, located close to pmr2.1 and CAPS marker wsb2-13 (1.00 cM) on Chr02, explained 92.3% of the phenotypic variation (LOD = 68.78). The fsi3.1, detected on Chr03, explained 79.7% of the phenotypic variation (LOD = 31.37) and was flanked by two CAPS, wsb3-24 (1.91 cM) and wsb3-9 (7.00 cM). Candidate gene-based CAPS markers were developed from the disease resistance and fruit shape gene homologs located on Chr.02 and Chr03 and were mapped on the intraspecific map. Colocalization of these markers with the major QTLs indicated that watermelon orthologs of a nucleotide-binding site-leucine-rich repeat class gene containing an RPW8 domain and a member of SUN containing the IQ67 domain are candidate genes for pmr2.1 and fsi3.1, respectively. The results presented herein provide useful information for marker-assisted breeding and gene cloning for PMR and fruit-related traits. PMID:26700647

  19. Retrospectively evaluated preinjury personality traits influence postconcussion symptoms.

    Science.gov (United States)

    Yuen, Kit-Man; Tsai, Yi-Hsin; Lin, Wei-Chi; Yang, Chi-Cheng; Huang, Sheng-Jean

    2016-01-01

    Postconcussion symptoms (PCS) are not uncommon following mild traumatic brain injury (mTBI). Personality traits have always been viewed as one of the most important explanations for persistent postconcussion symptoms (PPCS). Unfortunately, studies on the association between preinjury personality traits and the PPCS are still limited. This study thus aimed to examine the relationship between the preinjury personality and PCS in patients with mTBI. A total of 106 participants including 53 healthy participants were recruited. All participants complete the modified Checklist of Postconcussion Symptoms and the Health, Personality, & Habit Scale. Participants were evaluated within 4 weeks and at 4 months, respectively, after injury. The results showed patients reported significantly more PCS than healthy participants did within 4 weeks postinjury. A significant positive association between PCS and retrospectively evaluated preinjury personality was found. Specifically, patients who reported that their preinjury personality was depressive or anxious-related presented more PCS. This study might be the first to directly demonstrate that preinjury personality traits are closely linked to PCS reporting in patients with mTBI. Importantly, PCS reporting might be associated with different personality traits at different periods after injuries, and thus, a careful evaluation for personality characteristics is merited after mTBI.

  20. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts

    DEFF Research Database (Denmark)

    Aulchenko, Yurii S; Ripatti, Samuli; Lindqvist, Ida

    2008-01-01

    Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) .......8% of variation in lipids and were also associated with increased intima media thickness (P = 0.001) and coronary heart disease incidence (P = 0.04). The genetic risk score improves the screening of high-risk groups of dyslipidemia over classical risk factors.......Recent genome-wide association (GWA) studies of lipids have been conducted in samples ascertained for other phenotypes, particularly diabetes. Here we report the first GWA analysis of loci affecting total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL......) cholesterol and triglycerides sampled randomly from 16 population-based cohorts and genotyped using mainly the Illumina HumanHap300-Duo platform. Our study included a total of 17,797-22,562 persons, aged 18-104 years and from geographic regions spanning from the Nordic countries to Southern Europe. We...

  1. Genetic Dissection of Quantitative Trait Loci for Hemostasis and Thrombosis on Mouse Chromosomes 11 and 5 Using Congenic and Subcongenic Strains

    Science.gov (United States)

    Hoover-Plow, Jane; Sa, Qila; Huang, Menggui; Grondolsky, Jessica

    2013-01-01

    Susceptibility to thrombosis varies in human populations as well as many inbred mouse strains. Only a small portion of this variation has been identified, suggesting that there are unknown modifier genes. The objective of this study was to narrow the quantitative trait locus (QTL) intervals previously identified for hemostasis and thrombosis on mouse distal chromosome 11 (Hmtb6) and on chromosome 5 (Hmtb4 and Hmtb5). In a tail bleeding/rebleeding assay, a reporter assay for hemostasis and thrombosis, subcongenic strain (6A-2) had longer clot stability time than did C57BL/6J (B6) mice but a similar time to the B6-Chr11A/J consomic mice, confirming the Hmtb6 phenotype. Six congenic and subcongenic strains were constructed for chromosome 5, and the congenic strain, 2A-1, containing the shortest A/J interval (16.6 cM, 26.6 Mbp) in the Hmtb4 region, had prolonged clot stability time compared to B6 mice. In the 3A-2 and CSS-5 mice bleeding time was shorter than for B6, mice confirming the Hmtb5 QTL. An increase in bleeding time was identified in another congenic strain (3A-1) with A/J interval (24.8 cM, 32.9 Mbp) in the proximal region of chromosome 5, confirming a QTL for bleeding previously mapped to that region and designated as Hmtb10. The subcongenic strain 4A-2 with the A/J fragment in the proximal region had a long occlusion time of the carotid artery after ferric chloride injury and reduced dilation after injury to the abdominal aorta compared to B6 mice, suggesting an additional locus in the proximal region, which was designated Hmtb11 (5 cM, 21.4 Mbp). CSS-17 mice crossed with congenic strains, 3A-1 and 3A-2, modified tail bleeding. Using congenic and subcongenic analysis, candidate genes previously identified and novel genes were identified as modifiers of hemostasis and thrombosis in each of the loci Hmtb6, Hmtb4, Hmtb10, and Hmtb11. PMID:24147020

  2. Quantitative Trait Loci for Salinity Tolerance Identified under Drained and Waterlogged Conditions and Their Association with Flowering Time in Barley (Hordeum vulgare. L.

    Directory of Open Access Journals (Sweden)

    Yanling Ma

    Full Text Available Salinity is one of the major abiotic stresses affecting crop production via adverse effects of osmotic stress, specific ion toxicity, and stress-related nutritional disorders. Detrimental effects of salinity are also often exacerbated by low oxygen availability when plants are grown under waterlogged conditions. Developing salinity-tolerant varieties is critical to overcome these problems, and molecular marker assisted selection can make breeding programs more effective.In this study, a double haploid (DH population consisting of 175 lines, derived from a cross between a Chinese barley variety Yangsimai 1 (YSM1 and an Australian malting barley variety Gairdner, was used to construct a high density molecular map which contained more than 8,000 Diversity Arrays Technology (DArT markers and single nucleotide polymorphism (SNP markers. Salinity tolerance of parental and DH lines was evaluated under drained (SalinityD and waterlogged (SalinityW conditions at two different sowing times.Three quantitative trait loci (QTL located on chromosome 1H, single QTL located on chromosomes 1H, 2H, 4H, 5H and 7H, were identified to be responsible for salinity tolerance under different environments. Waterlogging stress, daylight length and temperature showed significant effects on barley salinity tolerance. The QTL for salinity tolerance mapped on chromosomes 4H and 7H, QSlwd.YG.4H, QSlwd.YG.7H and QSlww.YG.7H were only identified in winter trials, while the QTL on chromosome 2H QSlsd.YG.2H and QSlsw.YG.2H were only detected in summer trials. Genes associated with flowering time were found to pose significant effects on the salinity QTL mapped on chromosomes 2H and 5H in summer trials. Given the fact that the QTL for salinity tolerance QSlsd.YG.1H and QSlww.YG.1H-1 reported here have never been considered in the literature, this warrants further investigation and evaluation for suitability to be used in breeding programs.

  3. Do gender and personality traits (BFI-10) influence trust? A replication

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2016-01-01

    of this article is to investigate if gender and personality traits influence rating of these two statement. And if so, if it is possible to account for these factors and to create a robust trust indicator from these two statements after all. Big Five Inventory-10 is used to measure personality traits. Findings...... with adding personality traits into the equation. This article is a replication of a previous study. This study uses 1-5 Likert scales while the previous used 1-7 Likert scales, while all the questions/statements stayed the same. The difference is that both measures (not only the first measure) of trust were...

  4. Trait and Social Influences in the Links among Adolescent Attachment, Depressive Symptoms, and Coping

    Science.gov (United States)

    Merlo, Lisa J.; Lakey, Brian

    2007-01-01

    Attachment insecurity and maladaptive coping are associated with depression in adolescence; however, it is unclear whether these links primarily reflect stable individual differences among teens (trait influences), experiential differences in their interactions with relationship partners (social influences) or both. In this study, teens (ages…

  5. Coping with early stage breast cancer: examining the influence of personality traits and interpersonal closeness

    OpenAIRE

    Saita, Emanuela; Acquati, Chiara; Kayser, Karen

    2015-01-01

    The study examines the influence of personality traits and close relationships on the coping style of women with breast cancer. A sample of seventy-two Italian patients receiving treatment for early stage breast cancer was recruited. Participants completed questionnaires measuring personality traits (Interpersonal Adaptation Questionnaire), interpersonal closeness (Inclusion of the Other in the Self Scale), and adjustment to cancer (Mini-Mental Adjustment to Cancer Scale). We hypothesized tha...

  6. BDNF val66met genotype and schizotypal personality traits interact to influence probabilistic association learning.

    Science.gov (United States)

    Skilleter, Ashley Jayne; Weickert, Cynthia Shannon; Moustafa, Ahmed Abdelhalim; Gendy, Rasha; Chan, Mico; Arifin, Nur; Mitchell, Philip Bowden; Weickert, Thomas Wesley

    2014-11-01

    The brain derived neurotrophic factor (BDNF) val66met polymorphism rs6265 influences learning and may represent a risk factor for schizophrenia. Healthy people with high schizotypal personality traits display cognitive deficits that are similar to but not as severe as those observed in schizophrenia and they can be studied without confounds of antipsychotics or chronic illness. How genetic variation in BDNF may impact learning in individuals falling along the schizophrenia spectrum is unknown. We predicted that schizotypal personality traits would influence learning and that schizotypal personality-based differences in learning would vary depending on the BDNF val66met genotype. Eighty-nine healthy adults completed the Schizotypal Personality Questionnaire (SPQ) and a probabilistic association learning test. Blood samples were genotyped for the BDNF val66met polymorphism. An ANOVA was performed with BDNF genotype (val homozygotes and met-carriers) and SPQ score (high/low) as grouping variables and probabilistic association learning as the dependent variable. Participants with low SPQ scores (fewer schizotypal personality traits) showed significantly better learning than those with high SPQ scores. BDNF met-carriers displaying few schizotypal personality traits performed best, whereas BDNF met-carriers displaying high schizotypal personality traits performed worst. Thus, the BDNF val66met polymorphism appears to influence probabilistic association learning differently depending on the extent of schizotypal personality traits displayed. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

  7. CHOOSING TEACHING AS A PROFESSION: INFLUENCE OF BIG FIVE PERSONALITY TRAITS ON FALLBACK CAREER

    Directory of Open Access Journals (Sweden)

    Robert Tomšik

    2018-02-01

    Full Text Available Personality plays a significant role in influencing motivation for choosing a perspective profession. As empirical evidence confirmed, personality traits conscientiousness, openness to experience, extraversion are in positive correlation with intrinsic motives for choosing teaching as a profession (in negative with personality trait neuroticism, and in negative correlation with extrinsic motivation and fallback career (in positive with personality trait neuroticism. The primary aim of research is to point out the importance of personality traits in career choices via detecting which personality traits are predictors of fallback career. In the research first grade university students (teacher trainees; N = 402 completed the Five Factor Inventory and SMVUP-4-S scale. As results show, Big Five personality traits are in correlation with fallback career and are a significant predictor of fallback career. The Big Five model together explained 17.4% of the variance in fallback career, where personality traits agreeableness, conscientiousness, openness to experience and neuroticism has been shown as a statistically significant predictor of fallback career of teacher trainees.

  8. Influence of personality traits in coping skills in individuals with bipolar disorder

    Directory of Open Access Journals (Sweden)

    Érika Leonardo de Souza

    2014-08-01

    Full Text Available Background : Bipolar disorder is marked by alterations in coping skills which in turn impacts the disease course. Personality traits are associated with coping skills and for this reason it has been suggested that personality traits of patients with BD may have influence over their coping skills. Objective : To investigate possible associations between coping skills and personality in individuals with bipolar disorder (BD. Methods : Thirty-five euthymic subjects with BD were compared with 40 healthy controls. Coping skills were evaluated using Ways of Coping Checklist Revised and Brief-COPE. Personality traits were assessed by Neo Personality Inventory. MANCOVA was used for between groups comparison. Results : Regarding coping, individuals with BD reported more frequent use of emotion-focused strategies than problem-focused strategies, and high levels of neuroticism and low levels of extroversion and conscientiousness on personality measures. Neuroticism influenced negatively the use of problem-focused strategies, and positively emotion-focused coping. Conscientiousness influenced the use of problem-focused strategies in both groups. There was a significant difference between emotion focused coping and personality traits between BD and control groups. Discussion : Personality traits seem to modulate coping skills and strategies in BD which may be took into account for further interventions.

  9. Genome-Wide Association Study Singles Out SCD and LEPR as the Two Main Loci Influencing Intramuscular Fat Content and Fatty Acid Composition in Duroc Pigs.

    Science.gov (United States)

    Ros-Freixedes, Roger; Gol, Sofia; Pena, Ramona N; Tor, Marc; Ibáñez-Escriche, Noelia; Dekkers, Jack C M; Estany, Joan

    2016-01-01

    Intramuscular fat (IMF) content and fatty acid composition affect the organoleptic quality and nutritional value of pork. A genome-wide association study was performed on 138 Duroc pigs genotyped with a 60k SNP chip to detect biologically relevant genomic variants influencing fat content and composition. Despite the limited sample size, the genome-wide association study was powerful enough to detect the association between fatty acid composition and a known haplotypic variant in SCD (SSC14) and to reveal an association of IMF and fatty acid composition in the LEPR region (SSC6). The association of LEPR was later validated with an independent set of 853 pigs using a candidate quantitative trait nucleotide. The SCD gene is responsible for the biosynthesis of oleic acid (C18:1) from stearic acid. This locus affected the stearic to oleic desaturation index (C18:1/C18:0), C18:1, and saturated (SFA) and monounsaturated (MUFA) fatty acids content. These effects were consistently detected in gluteus medius, longissimus dorsi, and subcutaneous fat. The association of LEPR with fatty acid composition was detected only in muscle and was, at least in part, a consequence of its effect on IMF content, with increased IMF resulting in more SFA, less polyunsaturated fatty acids (PUFA), and greater SFA/PUFA ratio. Marker substitution effects estimated with a subset of 65 animals were used to predict the genomic estimated breeding values of 70 animals born 7 years later. Although predictions with the whole SNP chip information were in relatively high correlation with observed SFA, MUFA, and C18:1/C18:0 (0.48-0.60), IMF content and composition were in general better predicted by using only SNPs at the SCD and LEPR loci, in which case the correlation between predicted and observed values was in the range of 0.36 to 0.54 for all traits. Results indicate that markers in the SCD and LEPR genes can be useful to select for optimum fatty acid profiles of pork.

  10. Genome-Wide Association Study Singles Out SCD and LEPR as the Two Main Loci Influencing Intramuscular Fat Content and Fatty Acid Composition in Duroc Pigs.

    Directory of Open Access Journals (Sweden)

    Roger Ros-Freixedes

    Full Text Available Intramuscular fat (IMF content and fatty acid composition affect the organoleptic quality and nutritional value of pork. A genome-wide association study was performed on 138 Duroc pigs genotyped with a 60k SNP chip to detect biologically relevant genomic variants influencing fat content and composition. Despite the limited sample size, the genome-wide association study was powerful enough to detect the association between fatty acid composition and a known haplotypic variant in SCD (SSC14 and to reveal an association of IMF and fatty acid composition in the LEPR region (SSC6. The association of LEPR was later validated with an independent set of 853 pigs using a candidate quantitative trait nucleotide. The SCD gene is responsible for the biosynthesis of oleic acid (C18:1 from stearic acid. This locus affected the stearic to oleic desaturation index (C18:1/C18:0, C18:1, and saturated (SFA and monounsaturated (MUFA fatty acids content. These effects were consistently detected in gluteus medius, longissimus dorsi, and subcutaneous fat. The association of LEPR with fatty acid composition was detected only in muscle and was, at least in part, a consequence of its effect on IMF content, with increased IMF resulting in more SFA, less polyunsaturated fatty acids (PUFA, and greater SFA/PUFA ratio. Marker substitution effects estimated with a subset of 65 animals were used to predict the genomic estimated breeding values of 70 animals born 7 years later. Although predictions with the whole SNP chip information were in relatively high correlation with observed SFA, MUFA, and C18:1/C18:0 (0.48-0.60, IMF content and composition were in general better predicted by using only SNPs at the SCD and LEPR loci, in which case the correlation between predicted and observed values was in the range of 0.36 to 0.54 for all traits. Results indicate that markers in the SCD and LEPR genes can be useful to select for optimum fatty acid profiles of pork.

  11. Conservation and synteny of SSR loci and QTLs for vegetative propagation in four Eucalyptus species.

    Science.gov (United States)

    Marques, M.; Brondani, V.; Grattapaglia, D.; Sederoff, R.

    2002-08-01

    Conservation of microsatellite loci, heterozygous in Eucalyptus grandis, Eucalyptus urophylla, Eucalyptus tereticornis and Eucalyptus globulus, allowed us to propose homeologies among genetic linkage groups in these species, supported by at least three SSR loci in two different linkage groups. Marker-trait associations for sprouting and adventitious rooting ability were also compared in the four species. Putative quantitative trait loci (QTLs) influencing vegetative propagation traits were located on homeologous linkage groups. Our findings indicate high transferability of microsatellite markers between Eucalyptus species of the Symphyomyrtus subgenus and establish foundations for the use of synteny in the genetic analysis of this genus. Microsatellite markers should help integrate eucalypt genetic linkage maps from various sources. The availability of comparative linkage maps provides a basis of more-efficient use of genetic information for molecular breeding and evolutionary studies in Eucalyptus.

  12. Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

    DEFF Research Database (Denmark)

    Teumer, Alexander; Qi, Qibin; Nethander, Maria

    2016-01-01

    . Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF-I and IGFBP-3 concentrations (IGF1, IGFBP3, GCKR, TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2......). Significant sex interactions, which were characterized by different genotype-phenotype associations between men and women, were found only for associations of IGFBP-3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between...

  13. Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle.

    Science.gov (United States)

    Nkrumah, J D; Sherman, E L; Li, C; Marques, E; Crews, D H; Bartusiak, R; Murdoch, B; Wang, Z; Basarab, J A; Moore, S S

    2007-12-01

    Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is

  14. Seventy-five genetic loci influencing the human red blood cell

    NARCIS (Netherlands)

    van der Harst, P.; Zhang, W.; Mateo Leach, I.; Rendon, A.; Verweij, N.; Sehmi, J.; Paul, D.S.; Elling, U.; Allayee, H.; Li, X.; Radhakrishnan, A.; Tan, S.T.; Voss, K.; Weichenberger, C.X.; Albers, C.A.; Al-Hussani, A.; Asselbergs, F.W.; Ciullo, M.; Danjou, F.; Dina, C.; Esko, T.; Evans, D.M.; Franke, L.; Gogele, M.; Hartiala, J.; Hersch, M.; Holm, H.; Hottenga, J.J.; Kanoni, S.; Kleber, M.E.; Lagou, V.; Langenberg, C.; Lopez, L.M.; Lyytikainen, L.P.; Melander, O.; Murgia, F.; Nolte, I.M.; O'Reilly, P.F.; Padmanabhan, S.; Parsa, A.; Pirastu, N.; Porcu, E.; Portas, L.; Prokopenko, I.; Ried, J.S.; Shin, S.Y.; Tang, C.S.; Teumer, A.; Traglia, M.; Ulivi, S.; Westra, H.J.; Yang, J.; Zhao, J.H.; Anni, F.; Abdellaoui, A.; Attwood, A.; Balkau, B.; Bandinelli, S.; Bastardot, F.; Benyamin, B.; Boehm, B.O.; Cookson, W.O.; Das, D; de Bakker, P.I.; de Boer, R.A.; de Geus, E.J.; de Moor, M.H.; Dimitriou, M.; Domingues, F.S.; Doring, A.; Engstrom, G.; Eyjolfsson, G.I.; Ferrucci, L.; Fischer, K.; Galanello, R.; Garner, S.F.; Genser, B.; Gibson, Q.D.; Girotto, G.; Gudbjartsson, D.F.; Harris, S.E.; Hartikainen, A.L.; Hastie, C.E.; Hedblad, B.; Illig, T.; Jolley, J.; Kahonen, M.; Kema, I.P.; Kemp, J.P.; Liang, L.; Lloyd-Jones, H.; Loos, R.J.; Meacham, S.; Medland, S.E.; Meisinger, C.; Memari, Y.; Mihailov, E.; Miller, K.; Moffatt, M.F.; Nauck, M., et al.

    2012-01-01

    Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related

  15. Genome-wide association study identifies candidate loci underlying seven agronomic traits in Middle American diversity panel in common bean (Phaseolus vulgaris L.)

    Science.gov (United States)

    Common bean (Phaseolus vulgaris L.) breeding programs aim to improve both agronomic and seed characteristics traits. However, the genetic architecture of the many traits that affect common bean production are not completely understood. Genome-wide associate studies (GWAS) provide an experimental ap...

  16. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

    NARCIS (Netherlands)

    Justice, A.E.; Winkler, T.W.; Feitosa, M.F.; Graff, M.; Fisher, V.A.; Young, K.; Vink, J.M.; North, K.E.; Cupples, L.A.

    2017-01-01

    Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87%

  17. Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

    NARCIS (Netherlands)

    Santure, Anna W.; Poissant, Jocelyn; Cauwer, De Isabelle; Oers, Van Kees; Robinson, Matthew R.; Quinn, John L.; Groenen, M.A.M.; Visser, M.E.; Sheldon, Ben C.; Slate, Jon

    2015-01-01

    Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar

  18. Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

    NARCIS (Netherlands)

    Santure, Anna W; Poissant, Jocelyn; De Cauwer, Isabelle; van Oers, Kees; Robinson, Matthew R; Quinn, John L; Groenen, Martien A M; Visser, Marcel E; Sheldon, Ben C; Slate, Jon

    2015-01-01

    Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic

  19. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

    NARCIS (Netherlands)

    J. Dupuis (Josée); C. Langenberg (Claudia); I. Prokopenko (Inga); R. Saxena (Richa); N. Soranzo (Nicole); A.U. Jackson (Anne); E. Wheeler (Eleanor); N.L. Glazer (Nicole); N. Bouatia-Naji (Nabila); A.L. Gloyn (Anna); C.M. Lindgren (Cecilia); R. Mägi (Reedik); A.P. Morris (Andrew); J.C. Randall (Joshua); T. Johnson (Toby); P. Elliott (Paul); D. Rybin (Denis); G. Thorleifsson (Gudmar); V. Steinthorsdottir (Valgerdur); P. Henneman (Peter); H. Grallert (Harald); A. Dehghan (Abbas); J. JanHottenga (Jouke); C.S. Franklin (Christopher); P. Navarro (Pau); K. Song (Kijoung); A. Goel (Anuj); J.R.B. Perry (John); J.M. Egan (Josephine); T. Lajunen (Taina); N. Grarup (Niels); T. Sparsø (Thomas); A.S.F. Doney (Alex); B.F. Voight (Benjamin); H.M. Stringham (Heather); M. Li (Man); S. Kanoni (Stavroula); P. Shrader (Peter); C. Cavalcanti-Proença (Christine); M. Kumari (Meena); L. Qi (Lu); N.J. Timpson (Nicholas); C. Gieger (Christian); C. Zabena (Carina); G. Rocheleau (Ghislain); E. Ingelsson (Erik); P. An (Ping); J.R. O´Connell; J. Luan; S.A. McCarroll (Steven); F. Payne (Felicity); R.M. Roccasecca; F. Pattou (François); P. Sethupathy (Praveen); K.G. Ardlie (Kristin); Y. Ariyurek (Yavuz); B. Balkau (Beverley); P. Barter (Phil); J.P. Beilby (John); Y. Ben-Shlomo; R. Benediktsson (Rafn); A.J. Bennett (Amanda); S.M. Bergmann (Sven); M. Bochud (Murielle); E.A. Boerwinkle (Eric); A. Bonnefond (Amélie); L.L. Bonnycastle (Lori); K. Borch-Johnsen; Y. Böttcher (Yvonne); E. Brunner (Eric); S. Bumpstead (Suzannah); G. Charpentier (Guillaume); Y. der IdaChen (Yii); P.S. Chines (Peter); R. Clarke; L.J. McOin (Lachlan); M.N. Cooper (Matthew); M. Cornelis (Marilyn); G. Crawford (Gabe); L. Crisponi (Laura); I.N.M. Day (Ian); E.J.C. de Geus (Eco); J. Delplanque (Jerome); C. Dina (Christian); M.R. Erdos (Michael); A.C. Fedson (Annette); A. Fischer-Rosinsky (Antje); N.G. Forouhi (Nita); C.S. Fox (Caroline); R.R. Frants (Rune); M. GraziaFranzosi (Maria); P. Galan (Pilar); M. Goodarzi (Mark); J. Graessler (Jürgen); C.J. Groves (Christopher); S.M. Grundy (Scott); R. Gwilliam (Rhian); U. Gyllensten (Ulf); S. Hadjadj (Samy); G. Hallmans (Göran); N. Hammond (Naomi); X. Han (Xijing); A.-L. Hartikainen (Anna-Liisa); N. Hassanali (Neelam); C. Hayward (Caroline); S.C. Heath (Simon); S. Hercberg (Serge); C. Herder (Christian); A.A. Hicks (Andrew); D.R. Hillman (David); A. Hingorani (Aroon); A. Hofman (Albert); J. Hui (Jennie); J. Hung (Judy); B. Isomaa (Bo); T. Jørgensen (Torben); A. Jula (Antti); M. Kaakinen (Marika); J. Kaprio (Jaakko); Y. AnteroKesaniemi; M. Kivimaki (Mika); B. Knight (Beatrice); S. Koskinen (Seppo); P. Kovacs (Peter); K.O. Kyvik (Kirsten Ohm); G.M. Lathrop (Mark); D.A. Lawlor (Debbie); O.L. Bacquer (Olivier); C. Lecoeur (Cécile); V. Lyssenko (Valeriya); R. Mahley (Robert); M. Mangino (Massimo); A.K. Manning (Alisa); M. TeresaMartínez-Larrad (María); J.B. McAteer (Jarred); L.J. McCulloch (Laura); R. McPherson (Ruth); C. Meisinger (Christa); D. Melzer (David); D. Meyre (David); B.D. Mitchell (Braxton); M.A. Morken (Mario); S. Mukherjee (Sutapa); S. Naitza (Silvia); N. Narisu (Narisu); M.J. Neville (Matthew); B.A. Oostra (Ben); M. Orrù (Marco); R. Pakyz (Ruth); C.N.A. Palmer (Colin); G. Paolisso (Giuseppe); C. Pattaro (Cristian); D. Pearson (Daniel); J. Peden (John); N.L. Pedersen (Nancy); M. Perola (Markus); A.F.H. Pfeiffer (Andreas); I. Pichler (Irene); O. Polasek (Ozren); D. Posthuma (Danielle); S.C. Potter (Simon); A. Pouta (Anneli); M.A. Province (Mike); B.M. Psaty (Bruce); W. Rathmann (Wolfgang); N.W. Rayner (Nigel William); K. Rice (Kenneth); S. Ripatti (Samuli); F. Rivadeneira Ramirez (Fernando); M. Roden (Michael); O. Rolandsson (Olov); A. Sandbaek (Annelli); M.S. Sandhu (Manjinder); S. Sanna (Serena); A.A. Sayer; P. Scheet (Paul); L.J. Scott (Laura); U. Seedorf (Udo); S.J. Sharp (Stephen); B.M. Shields (Beverley); G. Sigursson (Gunnar); E.J.G. Sijbrands (Eric); A. Silveira (Angela); L. Simpson (Laila); A. Singleton (Andrew); N.L. Smith (Nicholas); U. Sovio (Ulla); A.J. Swift (Amy); H. Syddall (Holly); A.-C. Syvänen (Ann-Christine); T. Tanaka (Toshiko); B. Thorand (Barbara); J. Tichet (Jean); A. Tönjes (Anke); T. Tuomi (Tiinamaija); A.G. Uitterlinden (André); J.A.P. Willems van Dijk (Ko); M.V. Hoek; D. Varma (Dhiraj); S. Visvikis-Siest (Sophie); V. Vitart (Veronique); N. Vogelzangs (Nicole); G. Waeber (Gérard); P.J. Wagner (Peter); A. Walley (Andrew); G. BragiWalters; K.L. Ward (Kim); H. Watkins (Hugh); M.N. Weedon (Michael); S.H. Wild (Sarah); G.A.H.M. Willemsen (Gonneke); J.C.M. Witteman (Jacqueline); J.W. GYarnell (John); E. Zeggini (Eleftheria); D. Zelenika (Diana); B. Zethelius (Björn); G. Zhai (Guangju); J.H. Zhao (Jing Hua); M.C. Zillikens (Carola); I.B. Borecki (Ingrid); R.J.F. Loos (Ruth); P. Meneton (Pierre); P.K. Magnusson (Patrik); D.M. Nathan (David); G.H. Williams (Gordon); A.T. Hattersley (Andrew); K. Silander (Kaisa); V. Salomaa (Veikko); S.R. Bornstein (Stefan); P. Schwarz (Peter); J. Spranger (Jürgen); F. Karpe (Fredrik); A.R. Shuldiner (Alan); G.V. Dedoussis (George); M. Serrano-Ríos (Manuel); L. Lind (Lars); C. Palmer (Cameron); F.B. Hu (Frank); P.W. Franks (Paul); S. Ebrahim (Shanil); M. Marmot (Michael); W.H. Linda Kao; J.S. Pankow (James); M.J. Sampson (Michael); J. Kuusisto (Johanna); M. Laakso (Markku); T. Hansen (Torben); P.P. Pramstaller (Peter Paul); H.E. Wichmann (Erich); T. Illig (Thomas); I. Rudan (Igor); A.F. Wright (Alan); M. Stumvoll (Michael); H. Campbell (Harry); J.F. Wilson (James); R.N. Bergman (Richard); T.A. Buchanan (Thomas); F.S. Collins (Francis); K.L. Mohlke (Karen); J. Tuomilehto (Jaakko); T.T. Valle (Timo); D. Altshuler (David); J.I. Rotter (Jerome); D.S. Siscovick (David); B.W.J.H. Penninx (Brenda); D.I. Boomsma (Dorret); P. Deloukas (Panagiotis); T.D. Spector (Timothy); T.M. Frayling (Timothy); L. Ferrucci (Luigi); A. Kong (Augustine); U. Thorsteinsdottir (Unnur); J-A. Zwart (John-Anker); P. Tikka-Kleemola (Päivi); Y.S. Aulchenko (Yurii); A. Cao (Antonio); A. Scuteri (Angelo); D. Schlessinger (David); M. Uda (Manuela); A. Ruokonen (Aimo); M.-R. Jarvelin (Marjo-Riitta); D. Waterworth (Dawn); P. Vollenweider (Peter); L. Peltonen (Leena Johanna); V. Mooser (Vincent); G.R. Abecasis (Gonçalo); N.J. Wareham (Nick); R. Sladek (Rob); P. Froguel (Philippe); J.B. Meigs (James); L. Groop (Leif); R.M. Watanabe (Richard); M. Boehnke (Michael); M.I. McCarthy (Mark); J.C. Florez (Jose); I. Barroso (Inês)

    2010-01-01

    textabstractLevels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance

  20. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

    NARCIS (Netherlands)

    Dupuis, J.; Langenberg, C.; Prokopenko, I.; Saxena, R.; Soranzo, N.; Jackson, A.U.; Wheeler, E.; Glazer, N.L.; Bouatia-Naji, N.; Gloyn, A.L.; Lindgren, C.M.; Mägi, R.; Morris, A.P.; Randall, J.; Johnson, T.; Hottenga, J.J.; de Geus, E.J.C.; Kaprio, J.; Kyvik, K.O.; Pedersen, N.L.; Perola, M.; Posthuma, D.; Rivadeneira, F.; Uitterlinden, A.G.; Willems van Dijk, K.; van Hoek, M.; Vogelzangs, N.; Willemsen, G.; Witteman, J.C.M.; Zillikens, M.C.; Penninx, B.W.J.H.; Boomsma, D.I.; van Duijn, C.M.; Aulchenko, Y.S.; Waterworth, D.; Vollenweider, P.; Peltonen, L.; Mooser, V.; Abecasis, G.R.; Wareham, N.J.; Sladek, R.; Froguel, P.; Watanabe, R.M.; Meigs, J.B.; Groop, L.C.; Boehnke, M.; McCarthy, M.I.; Florez, J.C.; Barroso, I.

    2010-01-01

    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up

  1. Genetic variation in functional traits influences arthropod community composition in aspen (Populus tremula L..

    Directory of Open Access Journals (Sweden)

    Kathryn M Robinson

    Full Text Available We conducted a study of natural variation in functional leaf traits and herbivory in 116 clones of European aspen, Populus tremula L., the Swedish Aspen (SwAsp collection, originating from ten degrees of latitude across Sweden and grown in a common garden. In surveys of phytophagous arthropods over two years, we found the aspen canopy supports nearly 100 morphospecies. We identified significant broad-sense heritability of plant functional traits, basic plant defence chemistry, and arthropod community traits. The majority of arthropods were specialists, those coevolved with P. tremula to tolerate and even utilize leaf defence compounds. Arthropod abundance and richness were more closely related to plant growth rates than general chemical defences and relationships were identified between the arthropod community and stem growth, leaf and petiole morphology, anthocyanins, and condensed tannins. Heritable genetic variation in plant traits in young aspen was found to structure arthropod community; however no single trait drives the preferences of arthropod folivores among young aspen genotypes. The influence of natural variation in plant traits on the arthropod community indicates the importance of maintaining genetic variation in wild trees as keystone species for biodiversity. It further suggests that aspen can be a resource for the study of mechanisms of natural resistance to herbivores.

  2. Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations

    NARCIS (Netherlands)

    Yoneyama, Sachiko; Guo, Yiran; Lanktree, Matthew B.; Barnes, Michael R.; Elbers, Clara C.; Karczewski, Konrad J.; Padmanabhan, Sandosh; Bauer, Florianne; Baumert, Jens; Beitelshees, Amber; Berenson, Gerald S.; Boer, Jolanda M. A.; Burke, Gregory; Cade, Brian; Chen, Wei; Cooper-Dehoff, Rhonda M.; Gaunt, Tom R.; Gieger, Christian; Gong, Yan; Gorski, Mathias; Heard-Costa, Nancy; Johnson, Toby; Lamonte, Michael J.; Mcdonough, Caitrin; Monda, Keri L.; Onland-Moret, N. Charlotte; Nelson, Christopher P.; O'Connell, Jeffrey R.; Ordovas, Jose; Peter, Inga; Peters, Annette; Shaffer, Jonathan; Shen, Haiqinq; Smith, Erin; Speilotes, Liz; Thomas, Fridtjof; Thorand, Barbara; Verschuren, W. M. Monique; Anand, Sonia S.; Dominiczak, Anna; Davidson, Karina W.; Hegele, Robert A.; Heid, Iris; Hofker, Marten H.; Huggins, Gordon S.; Illig, Thomas; Johnson, Julie A.; Kirkland, Susan; Koenig, Wolfgang; Langaee, Taimour Y.; Mccaffery, Jeanne; Melander, Olle; Mitchell, Braxton D.; Munroe, Patricia; Murray, Sarah S.; Papanicolaou, George; Redline, Susan; Reilly, Muredach; Samani, Nilesh J.; Schork, Nicholas J.; Van der Schouw, Yvonne T.; Shimbo, Daichi; Shuldiner, Alan R.; Tobin, Martin D.; Wijmenga, Cisca; Yusuf, Salim; Hakonarson, Hakon; Lange, Leslie A.; Demerath, Ellen W.; Fox, Caroline S.; North, Kari E.; Reiner, Alex P.; Keating, Brendan; Taylor, Kira C.

    2014-01-01

    Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to

  3. Do gender and personality traits (BFI-10) influence self-perceived tech savviness?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2015-01-01

    Nowadays, it is necessary to use technology in various everyday activities. A certain level of what used to be called high-tech savviness is needed to access certain services. The aim of this paper is to analyze if gender and personality traits (Big Five Inventory-10) influence self-perceived tech...

  4. Personality Traits and Second Language Acquisition: The Influence of the Enneagram on Adult ESOL Students

    Science.gov (United States)

    Coker, Crystal; Mihai, Florin

    2017-01-01

    In this qualitative study, researchers focused on providing explicit knowledge of personality traits via the Enneagram profile to a group of 10 adult advanced students of English for speakers of other languages. Through the Enneagram and two surveys, researchers gained insight into how students perceived the influence of their personality type on…

  5. Do gender and personality traits influence visits of and purchases at deal sites?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek; Pavlicek, Antonin

    2017-01-01

    As deal sites became widespread, there are multiple international and local players in the Czech market. The research presented in the paper investigates if gender and personality traits influence frequency of visits of deal sites and the number of coupon purchases. Big Five Inventory-10 is used ...

  6. Do gender and personality traits influence visits of and purchases at deal sites?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek; Pavlicek, Antonin

    2017-01-01

    As deal sites became widespread, there are multiple international and local players in the Czech market. The research presented in the paper investigates if gender and personality traits influence frequency of visits of deal sites and the number of coupon purchases. Big Five Inventory-10 is used...

  7. Fertilization but not irrigation influences hydraulic traits in plantation-grown loblolly pine

    Science.gov (United States)

    Lisa J. Samuelson; Marianne G. Farris; Tom A. Stokes; Mark D. Coleman

    2008-01-01

    The goal of the study was to explore hydraulic traits in a 4-year-old loblolly pine (Pinus taeda L.) plantation to better understand plasticity of this species to resource availability. The influence of a factorial combination of irrigation (130 mm year-1 versus 494 mm year-1) and fertilization (0 kg N ha...

  8. Genetic and environmental influences on Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) maladaptive personality traits and their connections with normative personality traits.

    Science.gov (United States)

    Wright, Zara E; Pahlen, Shandell; Krueger, Robert F

    2017-05-01

    The Diagnostic and Statistical Manual for Mental Disorders-Fifth Edition (DSM-5) proposes an alternative model for personality disorders, which includes maladaptive-level personality traits. These traits can be operationalized by the Personality Inventory for the DSM-5 (PID-5). Although there has been extensive research on genetic and environmental influences on normative level personality, the heritability of the DSM-5 traits remains understudied. The present study addresses this gap in the literature by assessing traits indexed by the PID-5 and the International Personality Item Pool NEO (IPIP-NEO) in adult twins (N = 1,812 individuals). Research aims include (a) replicating past findings of the heritability of normative level personality as measured by the IPIP-NEO as a benchmark for studying maladaptive level traits, (b) ascertaining univariate heritability estimates of maladaptive level traits as measured by the PID-5, (c) establishing how much variation in personality pathology can be attributed to the same genetic components affecting variation in normative level personality, and (d) determining residual variance in personality pathology domains after variance attributable to genetic and environmental components of general personality has been removed. Results revealed that PID-5 traits reflect similar levels of heritability to that of IPIP-NEO traits. Further, maladaptive and normative level traits that correlate at the phenotypic level also correlate at the genotypic level, indicating overlapping genetic components contribute to variance in both. Nevertheless, we also found evidence for genetic and environmental components unique to maladaptive level personality traits, not shared with normative level traits. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. The Influence of State and Trait Anxiety on the Memory of Pain.

    Science.gov (United States)

    Babel, Przemyslaw

    2017-12-01

    The study aimed to assess the accuracy of memories of both pain and the state anxiety that accompanies experimentally induced pain and to investigate the factors that influence the memory of experimental pain. Forty-nine healthy female volunteers participated in the study. The participants received three electrocutaneous pain stimuli during the first phase of the study and rated the pain intensity, pain unpleasantness, and state anxiety they felt at that moment. Trait pain anxiety was measured by the Pain Anxiety Symptoms Scale and the Fear of Pain Questionnaire. During the second phase of the study, three or six months later (depending on the experimental group), the participants were asked to rate the pain intensity, pain unpleasantness, and state anxiety they had felt during the first phase of the study. Recalled pain intensity and unpleasantness and the state anxiety that accompanied the pain experience were remembered accurately, regardless of the recall delay. Both recalled pain intensity and unpleasantness were predicted by experienced pain, experienced and recalled state anxiety, and trait pain anxiety, that is, scores for physiological anxiety, cognitive anxiety, escape/avoidance, and severe pain. The present study demonstrates that a specific type of trait anxiety (pain anxiety) influences the memory of pain. The study is not only the first to investigate the influence of trait anxiety on the memory of experimental pain, it also is the first study to determine the effect of a specific form of anxiety (pain anxiety) on the memory of experimentally induced pain.

  10. The influence of trait-emotional intelligence on authentic leadership

    Directory of Open Access Journals (Sweden)

    Martina Kotzé

    2015-11-01

    Full Text Available Orientation: Authentic leadership is a relatively new construct that has recently gained increasing attention resulting from challenges faced by organisations relating to ethical meltdowns, corruption and fraud. Research purpose: This study seeks to explore the relationship between components of emotional intelligence and authentic leadership. Motivation for the study: Several authors called for more empirical investigations into the antecedents of authentic leadership. Despite the important role that emotions play in leadership, empirical studies were lacking about the influence of different components of emotional intelligence to authentic leadership. Research design, approach and method: Data were collected, using questionnaires obtained from 341 full-time employed applicants to MBA and leadership programmes in a South African Business School. Relationships between variables were analysed, using Pearson product-moment correlations and stepwise multiple regression. Main findings: The results indicated that emotional intelligence has positive statistically significant associations with authentic leadership. Specifically, those who scored high on all the emotional intelligence components also scored high on authentic leadership. In addition, the emotional intelligence component of empathy was a statistically significant predictor of authentic leadership. Practical/managerial implications: Initial findings suggest the potential value of recognising and developing the emotional intelligence of leaders to enable them to lead their organisations authentically to desired, successful outcomes. As empathy has been shown to be the most important emotional intelligence predictor of authentic leadership, leaders need to understand when subordinates perceive a leader as displaying empathic emotion. Contribution: This study contributes to the literature and empirical research on the antecedents of authentic leadership.

  11. Personality traits influencing somatization symptoms and social inhibition in the elderly

    Directory of Open Access Journals (Sweden)

    Wongpakaran T

    2014-01-01

    Full Text Available Tinakon Wongpakaran, Nahathai WongpakaranFaculty of Medicine, Chiang Mai University, Chiang Mai, ThailandPurpose: Somatization is a common symptom among the elderly, and even though personality disorders have been found to be associated with somatization, personality traits have not yet been explored with regard to this symptom. The aim of this study is to investigate the relationship between personality traits and somatization, and social inhibition.Patients and methods: As part of a cross-sectional study of a community sample, 126 elderly Thais aged 60 years or over completed self-reporting questionnaires related to somatization and personality traits. Somatization was elicited from the somatization subscale when using the Symptom Checklist SCL-90 instrument. Personality traits were drawn from the 16 Personality Factor Questionnaire and social inhibition was identified when using the inventory of interpersonal problems. In addition, path analysis was used to establish the influence of personality traits on somatization and social inhibition.Results: Of the 126 participants, 51% were male, 55% were married, and 25% were retired. The average number of years in education was 7.6 (standard deviation =5.2. “Emotional stability” and “dominance” were found to have a direct effect on somatization, as were age and number of years in education, but not sex. Also, 35% of the total variance could be explained by the model, with excellent fit statistics. Dominance was found to have an indirect effect, via vigilance, on social inhibition, which was also influenced by number of years in education and emotional stability. Social inhibition was not found to have any effect on somatization, although hypothetically it should.Conclusion: “Emotional stability”, “dominance”, and “vigilance”, as well as age and the number of years in education, were found to have an effect on somatization. Attention should be paid to these factors in the elderly

  12. Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides) Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq).

    Science.gov (United States)

    Yu, Hui; You, Xinxin; Li, Jia; Liu, Hankui; Meng, Zining; Xiao, Ling; Zhang, Haifa; Lin, Hao-Ran; Zhang, Yong; Shi, Qiong

    2016-04-06

    Mapping of quantitative trait loci (QTL) is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms) by double digest restriction site associated DNA sequencing (ddRADseq), and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides) using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs) spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1) including three (tert, ftz-f1 and notch1) that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS) efforts to improve growth-related traits in this economically important fish.

  13. Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq

    Directory of Open Access Journals (Sweden)

    Hui Yu

    2016-04-01

    Full Text Available Mapping of quantitative trait loci (QTL is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms by double digest restriction site associated DNA sequencing (ddRADseq, and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1 including three (tert, ftz-f1 and notch1 that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS efforts to improve growth-related traits in this economically important fish.

  14. Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides) Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq)

    Science.gov (United States)

    Yu, Hui; You, Xinxin; Li, Jia; Liu, Hankui; Meng, Zining; Xiao, Ling; Zhang, Haifa; Lin, Hao-Ran; Zhang, Yong; Shi, Qiong

    2016-01-01

    Mapping of quantitative trait loci (QTL) is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms) by double digest restriction site associated DNA sequencing (ddRADseq), and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides) using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs) spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1) including three (tert, ftz-f1 and notch1) that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS) efforts to improve growth-related traits in this economically important fish. PMID:27058532

  15. Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

    Science.gov (United States)

    Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

    2018-01-01

    Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

  16. Genetic and environmental influences on psychological traits and eating attitudes in a sample of Spanish schoolchildren.

    Science.gov (United States)

    Rojo-Moreno, Luis; Iranzo-Tatay, Carmen; Gimeno-Clemente, Natalia; Barberá-Fons, Maria Antonia; Rojo-Bofill, Luis Miguel; Livianos-Aldana, Lorenzo

    The heritability of eating disorders has been estimated to range from 22% to over 62%.The aim of this study is to determine the relative influence of genetics and environment that contribute to the drive for thinness, body dissatisfaction, perfectionism, and ineffectiveness, by evaluating sex differences in a sample of adolescent twins from Valencia, Spain. Five hundred eighty-four pairs of adolescent twins between 13 and 18 years of age completed the study. To determine zygosity, teachers responded to a questionnaire on physical similarity. Psychological traits of eating disorders were assessed with four sub-scales of the Eating Disorder Inventory (EDI); drive for thinness, body dissatisfaction, perfectionism, and ineffectiveness. Twin models were used to assess genetic and environmental (common and unique) factors affecting these four psychological traits. All four traits showed significant genetic contributions among girls, with heritability estimates of 37.7% for ineffectiveness, 42.8% for perfectionism, 56.9% for drive for thinness, and 65.5% for body dissatisfaction. Among boys, body dissatisfaction showed no additive genetic contributions, indicating significant shared and individual specific environment effects. The three other traits in boys showed significant additive genetic contributions, but were lower than in girls. With the exception of body dissatisfaction in boys, psychological traits of eating disorders show heritability patterns that differ according to sex. Copyright © 2014 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. Ethnic influences on body awareness, trait anxiety, perceived risk, and breast and gynecologic cancer screening practices.

    Science.gov (United States)

    Foxall, M J; Barron, C R; Houfek, J F

    2001-05-01

    To examine ethnic influences on body awareness, trait anxiety, perceived risk, and breast and gynecologic cancer screening practices. Descriptive, correlational secondary analysis. Urban and rural home and community populations. 233 women: 138 (59%) Caucasian, 37 (17%) African American, 29 (12%) Hispanic, and 29 (12%) American Indian women (X = 46.86 years) were recruited through mailings, churches, and community organizations. Structured questionnaires. Body awareness, trait anxiety, perceived risk, and breast and gynecologic cancer screening practices. Ethnicity predicted breast and gynecologic cancer screening practices (except clinical breast examination), body awareness, trait anxiety, and perceived risk. Hispanic and American Indian women reported greater breast self-examination frequency than Caucasian and African American women. Caucasian and African American women reported more mammogram use than Hispanic and American Indian women. Increased body awareness was related to fewer gynecologic exams for American Indian women. Women of different ethnic backgrounds respond differently to breast and gynecologic cancer screening practices. The influence of psychosocial variables on these practices varied with different groups. Nursing interventions to increase breast and gynecologic cancer screening should be ethnic-specific, with particular attention to the meaning of body awareness to American Indian women and trait anxiety and perceived risk to African American women.

  18. Dissection of genetically complex traits with extremely large pools of yeast segregants.

    Science.gov (United States)

    Ehrenreich, Ian M; Torabi, Noorossadat; Jia, Yue; Kent, Jonathan; Martis, Stephen; Shapiro, Joshua A; Gresham, David; Caudy, Amy A; Kruglyak, Leonid

    2010-04-15

    Most heritable traits, including many human diseases, are caused by multiple loci. Studies in both humans and model organisms, such as yeast, have failed to detect a large fraction of the loci that underlie such complex traits. A lack of statistical power to identify multiple loci with small effects is undoubtedly one of the primary reasons for this problem. We have developed a method in yeast that allows the use of much larger sample sizes than previously possible and hence permits the detection of multiple loci with small effects. The method involves generating very large numbers of progeny from a cross between two Saccharomyces cerevisiae strains and then phenotyping and genotyping pools of these offspring. We applied the method to 17 chemical resistance traits and mitochondrial function, and identified loci for each of these phenotypes. We show that the level of genetic complexity underlying these quantitative traits is highly variable, with some traits influenced by one major locus and others by at least 20 loci. Our results provide an empirical demonstration of the genetic complexity of a number of traits and show that it is possible to identify many of the underlying factors using straightforward techniques. Our method should have broad applications in yeast and can be extended to other organisms.

  19. Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

    Science.gov (United States)

    Mahajan, Anubha; Sim, Xueling; Ng, Hui Jin; Manning, Alisa; Rivas, Manuel A.; Highland, Heather M.; Locke, Adam E.; Grarup, Niels; Im, Hae Kyung; Cingolani, Pablo; Flannick, Jason; Fontanillas, Pierre; Fuchsberger, Christian; Gaulton, Kyle J.; Teslovich, Tanya M.; Rayner, N. William; Robertson, Neil R.; Beer, Nicola L.; Rundle, Jana K.; Bork-Jensen, Jette; Ladenvall, Claes; Blancher, Christine; Buck, David; Buck, Gemma; Burtt, Noël P.; Gabriel, Stacey; Gjesing, Anette P.; Groves, Christopher J.; Hollensted, Mette; Huyghe, Jeroen R.; Jackson, Anne U.; Jun, Goo; Justesen, Johanne Marie; Mangino, Massimo; Murphy, Jacquelyn; Neville, Matt; Onofrio, Robert; Small, Kerrin S.; Stringham, Heather M.; Syvänen, Ann-Christine; Trakalo, Joseph; Abecasis, Goncalo; Bell, Graeme I.; Blangero, John; Cox, Nancy J.; Duggirala, Ravindranath; Hanis, Craig L.; Seielstad, Mark; Wilson, James G.; Christensen, Cramer; Brandslund, Ivan; Rauramaa, Rainer; Surdulescu, Gabriela L.; Doney, Alex S. F.; Lannfelt, Lars; Linneberg, Allan; Isomaa, Bo; Tuomi, Tiinamaija; Jørgensen, Marit E.; Jørgensen, Torben; Kuusisto, Johanna; Uusitupa, Matti; Salomaa, Veikko; Spector, Timothy D.; Morris, Andrew D.; Palmer, Colin N. A.; Collins, Francis S.; Mohlke, Karen L.; Bergman, Richard N.; Ingelsson, Erik; Lind, Lars; Tuomilehto, Jaakko; Hansen, Torben; Watanabe, Richard M.; Prokopenko, Inga; Dupuis, Josee; Karpe, Fredrik; Groop, Leif; Laakso, Markku; Pedersen, Oluf; Florez, Jose C.; Morris, Andrew P.; Altshuler, David; Meigs, James B.; Boehnke, Michael; McCarthy, Mark I.; Lindgren, Cecilia M.; Gloyn, Anna L.

    2015-01-01

    Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights. PMID:25625282

  20. Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

    Directory of Open Access Journals (Sweden)

    Anubha Mahajan

    2015-01-01

    Full Text Available Genome wide association studies (GWAS for fasting glucose (FG and insulin (FI have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7 evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF=1.5% influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1% influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D, the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

  1. R/qtlcharts: interactive graphics for quantitative trait locus mapping.

    Science.gov (United States)

    Broman, Karl W

    2015-02-01

    Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL) (genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl's static graphs, as well as additional interactive graphs for the exploration of high-dimensional genotype and phenotype data. Copyright © 2015 by the Genetics Society of America.

  2. Differential Influences of Depression and Personality Traits on the Use of Facebook

    Directory of Open Access Journals (Sweden)

    Sebastian Scherr

    2017-03-01

    Full Text Available Depressive symptoms are highly prevalent among younger populations and have been clearly associated with lowered activity in general. Focusing on Facebook use as an extremely popular leisure activity, this study examines the influence of depressive tendencies on the intensity of using Facebook by considering the moderating effects of relevant personality traits and different motivations associated with social network site (SNS use. Based on an online survey among 510 young Facebook users, this study shows that increasing depressive tendencies are associated with an increased frequency of posting status updates—most likely for negative reasons. Moderated mediation models show that the personality traits of neuroticism and extraversion only influence the motivations behind using Facebook and not the time spent on the SNS. Findings are also discussed with regard to novel digital help offers for Facebook users with depressive tendencies.

  3. A Common Genetic Determinism for Sensitivities to Soil Water Deficit and Evaporative Demand: Meta-Analysis of Quantitative Trait Loci and Introgression Lines of Maize1[W][OA

    Science.gov (United States)

    Welcker, Claude; Sadok, Walid; Dignat, Grégoire; Renault, Morgan; Salvi, Silvio; Charcosset, Alain; Tardieu, François

    2011-01-01

    Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material. PMID:21795581

  4. Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on enzymatic mastitis indicators of milk from dairy cows experimentally inoculated with Escherichia coli

    DEFF Research Database (Denmark)

    Sørensen, Lars Peter; Engberg, Ricarda Greuel; Løvendahl, Peter

    2015-01-01

    The aim of this study was to investigate the effect of a quantitative trait locus associated with mastitis caused by Escherichia coli, with one haplotype being more susceptible (HH) and another being more resistant (HL) to E. coli mastitis, on the activity of 4 inflammatory related milk enzymes. ...

  5. Genetic mapping of semi-polar metabolites in pepper fruits (Capsicum sp.): towards unravelling the molecular regulation of flavonoid quantitative trait loci

    NARCIS (Netherlands)

    Wahyuni, Y.; Stahl-Hermes, V.; Ballester, A.R.; Vos, de C.H.; Voorrips, R.E.; Maharijaya, A.; Molthoff, J.W.; Víquez Zamora, A.M.; Sudarmonowati, E.; Arisi, A.C.M.; Bino, R.J.; Bovy, A.G.

    2014-01-01

    Untargeted LCMS profiling of semi-polar metabolites followed by metabolite quantitative trait locus (mQTL) analysis was performed in ripe pepper fruits of 113 F2 plants derived from a cross between Capsicum annuum AC1979 (no. 19) and Capsicum chinense No. 4661 Selection (no. 18). The parental

  6. Round fruit shape in WI7239 cucumber is controlled by two interacting quantitative trait loci with one putatively encoding a tomato SUN homolog

    Science.gov (United States)

    Fruit size and shape is an important quality trait in cucumber breeding, yet its genetic basis remains poorly understood. In the present study, we conducted QTL mapping on round fruit shape in cucumber with F2 and F2:3 segregating populations from the cross between WI7238 (long fruit) and WI7239 (ro...

  7. Introgressed chromosome 2 quantitative trait loci restores aldosterone regulation and reduces response to salt in the stroke-prone spontaneously hypertensive rat

    NARCIS (Netherlands)

    Sampson, Amanda K.; Mohammed, Dashti; Beattie, Wendy; Graham, Delyth; Kenyon, Christopher J.; Al-Dujaili, Emad A. S.; Guryev, Victor; Mcbride, Martin W.; Dominiczak, Anna F.

    2014-01-01

    Background: The genetic contribution to salt-sensitivity in hypertension remains unclear. We have previously identified a quantitative trait locus on chromosome 2 in stroke-prone spontaneously hypertensive rats (SHRSPs) responsible for an increase in SBP in response to a salt challenge. This

  8. Genome-wide association study for identifying loci that affect fillet yield, carcass, and body weight traits in rainbow trout (Oncorhynchus mykiss)

    Science.gov (United States)

    Fillet yield (FY, %) is an economically important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has not received much attention in breeding programs because it is difficult to measure on a large number of fish and it cannot be directly measured on breeding c...

  9. Individual Differences in Subjective Utility and Risk Preferences: The Influence of Hedonic Capacity and Trait Anxiety

    Directory of Open Access Journals (Sweden)

    Jonathon R. Howlett

    2017-05-01

    Full Text Available Individual differences in decision-making are important in both normal populations and psychiatric conditions. Variability in decision-making could be mediated by different subjective utilities or by other processes. For example, while traditional economic accounts attribute risk aversion to a concave subjective utility curve, in practice other factors could affect risk behavior. This distinction may have important implications for understanding the biological basis of variability in decision-making and for developing interventions to improve decision-making. Another aspect of decision-making that may vary between individuals is the sensitivity of subjective utility to counterfactual outcomes (outcomes that could have occurred, but did not. We investigated decision-making in relation to hedonic capacity and trait anxiety, two traits that relate to psychiatric conditions but also vary in the general population. Subjects performed a decision-making task, in which they chose between low- and high-risk gambles to win 0, 20, or 40 points on each trial. Subjects then rated satisfaction after each outcome on a visual analog scale, indicating subjective utility. Hedonic capacity was positively associated with the subjective utility of winning 20 points but was not associated with the concavity of the subjective utility curve (constructed using the mean subjective utility of winning 0, 20, or 40 points. Consistent with economic theory, concavity of the subjective utility curve was associated with risk aversion. Hedonic capacity was independently associated with risk seeking (i.e., not mediated by the shape of the subjective utility curve, while trait anxiety was unrelated to risk preferences. Contrary to our expectations, counterfactual sensitivity was unrelated to hedonic capacity and trait anxiety. Nevertheless, trait anxiety was associated with a self-report measure of regret-proneness, suggesting that counterfactual influences may occur via a pathway

  10. Analysis of Non-Genetic Factors Influencing Reproductive Traits of Japanese Black Heifer

    Science.gov (United States)

    Setiaji, A.; Oikawa, T.

    2018-02-01

    This study aimed was to identify non-genetic factors strongly associated with reproductive traits on Japanese Black heifer. Artificial insemination and calving records were analyzed to investigate non-genetic effect on reproductive performances. A total of 2220 records of heifer raised between 2005 and 2016 were utilized in this study. Studied traits were first service non return rate to 56 days (NRR), first service pregnancy rate (FPR), days from first to successful insemination (FSI), number of services per conception (NSC), age at first calving (AFC), and gestation length (GL). Test of significance for effects in the statistical model was performed using GLM procedure of SAS 9.3. The yearling trend was plotted on the adjusted mean of parameters, by the least square mean procedure. Means of NRR, FPR, FSI, NSC, AFC and GL were 72%, 53%, 52.71 days, 1.76, 760.71 days and 288.26 days, respectively. The effect of farm was significant (P<0.001) for FSI, AFC, and GL. The effects of age of heifer at first insemination was significant (P<0.001) for AFC. Month of insemination and sex of calf were significant (P<0.001) for GL. Compared with average value of reproductive traits, NSC and GL were generally within standard values for Japanese Black cattle, while AFC was slightly earlier. The result indicated that different management of farms strongly influenced reproductive traits of Japanese Black heifer.

  11. Coping with Early Stage Breast Cancer:Examining the Influence of Personality Traits and Interpersonal Closeness

    Directory of Open Access Journals (Sweden)

    Emanuela eSaita

    2015-02-01

    Full Text Available The study examines the influence of personality traits and close relationships on the coping style of women with breast cancer. A sample of seventy-two Italian patients receiving treatment for early stage breast cancer was recruited. Participants completed questionnaires measuring personality traits (Interpersonal Adaptation Questionnaire, interpersonal closeness (Inclusion of the Other in the Self Scale, and adjustment to cancer (Mini-Mental Adjustment to Cancer Scale. We hypothesized that diverse personality traits and degrees of closeness contribute to determine the coping styles shown by participants. Multiple regression analyses were conducted for each of the five coping styles (Helplessness/Hopelessness, Anxious Preoccupation, Avoidance, Fatalism, and Fighting Spirit using personality traits and interpersonal closeness variables (Strength of Support Relations, and Number of Support Relations as predictors. Women who rated high on assertiveness and social anxiety were more likely to utilize active coping strategies (Fighting Spirit. Perceived strength of relationships was predictive of using an active coping style while the number of supportive relationships did not correlate with any of the coping styles. Implications for assessment of breast cancer patients at risk for negative adaptation to the illness and the development of psychosocial interventions are discussed.

  12. Identical genetic influences underpin behavior problems in adolescence and basic traits of personality.

    Science.gov (United States)

    Lewis, Gary J; Haworth, Claire M A; Plomin, Robert

    2014-08-01

    Understanding the etiology of adolescent problem behavior has been of enduring interest. Only relatively recently, however, has this issue been examined within a normal personality trait framework. Research suggests that problem behaviors in adolescence and beyond may be adequately explained by the taxonomy provided by the basic dimensions of normal personality: Such problem behaviors are suggested to be extreme points on a distribution of the full range of the underlying traits. We extend work in this field examining the extent to which genetic factors underlying the five-factor model of personality are common with genetic influences on adolescent behavior problems (namely, anxiety, peer problems, conduct, hyperactivity, and low prosociality). A nationally representative twin sample (Twins Early Development Study) from the general population of England and Wales, including 2031 pairs of twins aged 16 years old, was used to decompose variation into genetic and environmental components. Behavioral problems in adolescence were assessed by self-report with the Strengths and Difficulties Questionnaire. Adolescent behavior problems were moderately associated with normal personality: Specifically, a fifth to a third of phenotypic variance in problem behaviors was accounted for by five-factor model personality traits. Of central importance here, genetic influences underpinning personality were entirely overlapping with those genetic factors underlying adolescent behavior problems. These findings suggest that adolescent behavior problems can be understood, at least in part, within a model of normal personality trait variation, with the genetic bases of these behavior problems the same as those genetic influences underpinning normal personality. © 2013 The Authors. Journal of Child Psychology and Psychiatry. © 2013 Association for Child and Adolescent Mental Health.

  13. Association analysis using USDA diverse rice (Oryza sativa L.) germplasm collections to identify loci influencing grain quality traits

    Science.gov (United States)

    he USDA rice (Oryza sativa L.) core subset (RCS) was assembled to represent the genetic diversity of the entire USDA-ARS National Small Grains Collection and consists of 1,794 accessions from 114 countries. The USDA rice mini-core (MC) is a subset of 217 accessions from the RCS and was selected to ...

  14. Quantitative Trait Loci Influencing Hb F Levels in Southern Thai Hb E (HBB: c.79G>A) Heterozygotes.

    Science.gov (United States)

    Kesornsit, Aumpika; Jeenduang, Nutjaree; Horpet, Dararat; Plyduang, Thunyaluk; Nuinoon, Manit

    2018-01-01

    Variation of fetal hemoglobin (Hb F) expression in heterozygous Hb E (HBB: c.79G>A) individuals is associated with several genetic modifiers and not well understood. This study was undertaken in order to determine the effect of single nucleotide polymorphisms (SNPs), including XmnI G γ (rs7482144), rs766432 on the BCL11A gene and rs9376074 on the HBS1L gene, on Hb F levels in Southern Thai heterozygous Hb E individuals. A total of 97 Southern Thai subjects carrying heterozygous Hb E were selected for the hematological study. After excluding the samples with α-thalassemia (α-thal) interaction or moderate anemia, because both conditions can affect the hematological parameters, the remaining 74 samples were submitted to SNP analysis. Hematological parameters were measured using an automated hematology analyzer and high performance liquid chromatography (HPLC). The results show that rs766432 was strongly associated with increased Hb F levels and rs7482144 was associated with Hb F levels in each subgroup (genotype) of rs766432. This study suggested that the BCL11A locus has a major effect on Hb F levels compared with the XmnI polymorphism in Hb E heterozygotes. This association of Hb F levels with SNPs is useful for the interpretation of hemoglobin (Hb) typing in heterozygous Hb E samples with high Hb F levels. Future research will need to address the better understanding of the mechanisms of the SNPs that regulate Hb F production without stress erythropoiesis in Hb E heterozygotes.

  15. Trait procrastination among dental students in India and its influence on academic performance.

    Science.gov (United States)

    Madhan, Balasubramanian; Kumar, Cholleti Sudheer; Naik, Eslavath Seena; Panda, Sujit; Gayathri, Haritheertham; Barik, Ashish Kumar

    2012-10-01

    Trait procrastination is believed to be highly prevalent among college students and detrimental to their educational performance. As the scenario among dental students is virtually unknown, this study was conducted to evaluate the prevalence of trait procrastination among dental students and to analyze its influence on their academic performance. A total of 174 fourth-year dental students from three dental colleges in India voluntarily completed the Lay's Procrastination Scale-student version (LPS). The mean percentage marks scored in the subsequent final university examinations were used as a measure of academic performance. The descriptive statistics were computed to evaluate the prevalence of significant procrastination (LPS score ≥60). Mann-Whitney U test and multiple linear regressions were used to assess the influence of age and gender on procrastination severity, and the latter was again used to analyze the association between procrastination severity and academic performance. The results indicated that 27 percent (n=47) of the students exhibited a significant extent of trait procrastination; neither age nor gender affected its severity (pProcrastination had a significant and negative impact on the academic performance of the student (beta=-0.150, p=0.039). These findings highlight the need for active measures to reduce the causes and consequences of procrastination in dental education.

  16. Personality and music preferences: the influence of personality traits on preferences regarding musical elements.

    Science.gov (United States)

    Kopacz, Malgorzata

    2005-01-01

    The purpose of this scientific study was to determine how personality traits, as classified by Cattell, influence preferences regarding musical elements. The subject group consisted of 145 students, male and female, chosen at random from different Polish universities. For the purpose of determining their personality traits the participants completed the 16PF Questionnaire (Cattell, Saunders, & Stice, 1957; Russel & Karol, 1993), in its Polish adaptation by Choynowski (Nowakowska, 1970). The participants' musical preferences were determined by their completing a Questionnaire of Musical Preferences (specifically created for the purposes of this research), in which respondents indicated their favorite piece of music. Next, on the basis of the Questionnaire of Musical Preferences, a list of the works of music chosen by the participants was compiled. All pieces were collected on CDs and analyzed to separate out their basic musical elements. The statistical analysis shows that some personality traits: Liveliness (Factor F), Social Boldness (Factor H), Vigilance (Factor L), Openness to Change (Factor Q1), Extraversion (a general factor) have an influence on preferences regarding musical elements. Important in the subjects' musical preferences were found to be those musical elements having stimulative value and the ability to regulate the need for stimulation. These are: tempo, rhythm in relation to metrical basis, number of melodic themes, sound voluminosity, and meter.

  17. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

    Science.gov (United States)

    Dupuis, Josée; Langenberg, Claudia; Prokopenko, Inga; Saxena, Richa; Soranzo, Nicole; Jackson, Anne U; Wheeler, Eleanor; Glazer, Nicole L; Bouatia-Naji, Nabila; Gloyn, Anna L; Lindgren, Cecilia M; Mägi, Reedik; Morris, Andrew P; Randall, Joshua; Johnson, Toby; Elliott, Paul; Rybin, Denis; Thorleifsson, Gudmar; Steinthorsdottir, Valgerdur; Henneman, Peter; Grallert, Harald; Dehghan, Abbas; Hottenga, Jouke Jan; Franklin, Christopher S; Navarro, Pau; Song, Kijoung; Goel, Anuj; Perry, John R B; Egan, Josephine M; Lajunen, Taina; Grarup, Niels; Sparsø, Thomas; Doney, Alex; Voight, Benjamin F; Stringham, Heather M; Li, Man; Kanoni, Stavroula; Shrader, Peter; Cavalcanti-Proença, Christine; Kumari, Meena; Qi, Lu; Timpson, Nicholas J; Gieger, Christian; Zabena, Carina; Rocheleau, Ghislain; Ingelsson, Erik; An, Ping; O’Connell, Jeffrey; Luan, Jian'an; Elliott, Amanda; McCarroll, Steven A; Payne, Felicity; Roccasecca, Rosa Maria; Pattou, François; Sethupathy, Praveen; Ardlie, Kristin; Ariyurek, Yavuz; Balkau, Beverley; Barter, Philip; Beilby, John P; Ben-Shlomo, Yoav; Benediktsson, Rafn; Bennett, Amanda J; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bonnefond, Amélie; Bonnycastle, Lori L; Borch-Johnsen, Knut; Böttcher, Yvonne; Brunner, Eric; Bumpstead, Suzannah J; Charpentier, Guillaume; Chen, Yii-Der Ida; Chines, Peter; Clarke, Robert; Coin, Lachlan J M; Cooper, Matthew N; Cornelis, Marilyn; Crawford, Gabe; Crisponi, Laura; Day, Ian N M; de Geus, Eco; Delplanque, Jerome; Dina, Christian; Erdos, Michael R; Fedson, Annette C; Fischer-Rosinsky, Antje; Forouhi, Nita G; Fox, Caroline S; Frants, Rune; Franzosi, Maria Grazia; Galan, Pilar; Goodarzi, Mark O; Graessler, Jürgen; Groves, Christopher J; Grundy, Scott; Gwilliam, Rhian; Gyllensten, Ulf; Hadjadj, Samy; Hallmans, Göran; Hammond, Naomi; Han, Xijing; Hartikainen, Anna-Liisa; Hassanali, Neelam; Hayward, Caroline; Heath, Simon C; Hercberg, Serge; Herder, Christian; Hicks, Andrew A; Hillman, David R; Hingorani, Aroon D; Hofman, Albert; Hui, Jennie; Hung, Joe; Isomaa, Bo; Johnson, Paul R V; Jørgensen, Torben; Jula, Antti; Kaakinen, Marika; Kaprio, Jaakko; Kesaniemi, Y Antero; Kivimaki, Mika; Knight, Beatrice; Koskinen, Seppo; Kovacs, Peter; Kyvik, Kirsten Ohm; Lathrop, G Mark; Lawlor, Debbie A; Le Bacquer, Olivier; Lecoeur, Cécile; Li, Yun; Lyssenko, Valeriya; Mahley, Robert; Mangino, Massimo; Manning, Alisa K; Martínez-Larrad, María Teresa; McAteer, Jarred B; McCulloch, Laura J; McPherson, Ruth; Meisinger, Christa; Melzer, David; Meyre, David; Mitchell, Braxton D; Morken, Mario A; Mukherjee, Sutapa; Naitza, Silvia; Narisu, Narisu; Neville, Matthew J; Oostra, Ben A; Orrù, Marco; Pakyz, Ruth; Palmer, Colin N A; Paolisso, Giuseppe; Pattaro, Cristian; Pearson, Daniel; Peden, John F; Pedersen, Nancy L.; Perola, Markus; Pfeiffer, Andreas F H; Pichler, Irene; Polasek, Ozren; Posthuma, Danielle; Potter, Simon C; Pouta, Anneli; Province, Michael A; Psaty, Bruce M; Rathmann, Wolfgang; Rayner, Nigel W; Rice, Kenneth; Ripatti, Samuli; Rivadeneira, Fernando; Roden, Michael; Rolandsson, Olov; Sandbaek, Annelli; Sandhu, Manjinder; Sanna, Serena; Sayer, Avan Aihie; Scheet, Paul; Scott, Laura J; Seedorf, Udo; Sharp, Stephen J; Shields, Beverley; Sigurðsson, Gunnar; Sijbrands, Erik J G; Silveira, Angela; Simpson, Laila; Singleton, Andrew; Smith, Nicholas L; Sovio, Ulla; Swift, Amy; Syddall, Holly; Syvänen, Ann-Christine; Tanaka, Toshiko; Thorand, Barbara; Tichet, Jean; Tönjes, Anke; Tuomi, Tiinamaija; Uitterlinden, André G; van Dijk, Ko Willems; van Hoek, Mandy; Varma, Dhiraj; Visvikis-Siest, Sophie; Vitart, Veronique; Vogelzangs, Nicole; Waeber, Gérard; Wagner, Peter J; Walley, Andrew; Walters, G Bragi; Ward, Kim L; Watkins, Hugh; Weedon, Michael N; Wild, Sarah H; Willemsen, Gonneke; Witteman, Jaqueline C M; Yarnell, John W G; Zeggini, Eleftheria; Zelenika, Diana; Zethelius, Björn; Zhai, Guangju; Zhao, Jing Hua; Zillikens, M Carola; Borecki, Ingrid B; Loos, Ruth J F; Meneton, Pierre; Magnusson, Patrik K E; Nathan, David M; Williams, Gordon H; Hattersley, Andrew T; Silander, Kaisa; Salomaa, Veikko; Smith, George Davey; Bornstein, Stefan R; Schwarz, Peter; Spranger, Joachim; Karpe, Fredrik; Shuldiner, Alan R; Cooper, Cyrus; Dedoussis, George V; Serrano-Ríos, Manuel; Morris, Andrew D; Lind, Lars; Palmer, Lyle J; Hu, Frank B.; Franks, Paul W; Ebrahim, Shah; Marmot, Michael; Kao, W H Linda; Pankow, James S; Sampson, Michael J; Kuusisto, Johanna; Laakso, Markku; Hansen, Torben; Pedersen, Oluf; Pramstaller, Peter Paul; Wichmann, H Erich; Illig, Thomas; Rudan, Igor; Wright, Alan F; Stumvoll, Michael; Campbell, Harry; Wilson, James F; Hamsten, Anders; Bergman, Richard N; Buchanan, Thomas A; Collins, Francis S; Mohlke, Karen L; Tuomilehto, Jaakko; Valle, Timo T; Altshuler, David; Rotter, Jerome I; Siscovick, David S; Penninx, Brenda W J H; Boomsma, Dorret; Deloukas, Panos; Spector, Timothy D; Frayling, Timothy M; Ferrucci, Luigi; Kong, Augustine; Thorsteinsdottir, Unnur; Stefansson, Kari; van Duijn, Cornelia M; Aulchenko, Yurii S; Cao, Antonio; Scuteri, Angelo; Schlessinger, David; Uda, Manuela; Ruokonen, Aimo; Jarvelin, Marjo-Riitta; Waterworth, Dawn M; Vollenweider, Peter; Peltonen, Leena; Mooser, Vincent; Abecasis, Goncalo R; Wareham, Nicholas J; Sladek, Robert; Froguel, Philippe; Watanabe, Richard M; Meigs, James B; Groop, Leif; Boehnke, Michael; McCarthy, Mark I; Florez, Jose C; Barroso, Inês

    2010-01-01

    Circulating glucose levels are tightly regulated. To identify novel glycemic loci, we performed meta-analyses of 21 genome-wide associations studies informative for fasting glucose (FG), fasting insulin (FI) and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with FG/HOMA-B and two associated with FI/HOMA-IR. These include nine new FG loci (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and FAM148B) and one influencing FI/HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB/TMEM195 with type 2 diabetes (T2D). Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify T2D risk loci, as well as loci that elevate FG modestly, but do not cause overt diabetes. PMID:20081858

  18. Do gender and personality traits (BFI-10) influence self-perceived opinion leadership?

    DEFF Research Database (Denmark)

    Sudzina, Frantisek

    2016-01-01

    and it uses fewer items to measure relevant constructs. The Big Five Inventory is measured using a 10-question instrument as opposed to a 21-question one. Opinion leadership is measured using one question instead of nine; moreover, it is investigated separately as self-perceived in the eyes of others...... trait closest related to opinion leadership regardless whether it is self-perceived in the eyes of others or in one's own opinion. Opinion leadership in one's own opinion can be predicted even using neuroticism, and conscientiousness. The three traits are consistent with previous findings. Unlike....... Conclusions: From six investigated factors, extraversion has the highest influence on self-perceived opinion leadership. Since extraversion can be identified also through observation, the finding has also a practical implication....

  19. Multiple genetic loci influence serum urate levels and their relationship with gout and cardiovascular disease risk factors

    NARCIS (Netherlands)

    Q. Yang (Qiong Fang); A. Köttgen (Anna); A. Dehghan (Abbas); A.V. Smith (Albert Vernon); N.L. Glazer (Nicole); M-H. Chen (Ming-Huei); D.I. Chasman (Daniel); T. Aspelund (Thor); G. Eiriksdottir (Gudny); T.B. Harris (Tamara); L.J. Launer (Lenore); M.A. Nalls (Michael); D.G. Hernandez (Dena); D.E. Arking (Dan); E.A. Boerwinkle (Eric); M.L. Grove (Megan); M. Li (Man); W.H. Linda Kao; M. Chonchol (Michel); T. Haritunians (Talin); T. Lumley (Thomas); B.M. Psaty (Bruce); M.G. Shlipak (Michael); S.J. Hwang; M.G. Larson (Martin); C.J. O'Donnell (Christopher); A. Upadhyay (Ashish); P. Tikka-Kleemola (Päivi); A. Hofman (Albert); F. Rivadeneira Ramirez (Fernando); B.H.Ch. Stricker (Bruno); A.G. Uitterlinden (André); G. Paré (Guillaume); A.N. Parker (Alex); P.M. Ridker (Paul); D.S. Siscovick (David); V. Gudnason (Vilmundur); J.C.M. Witteman (Jacqueline); C.S. Fox (Caroline); J. Coresh (Josef)

    2010-01-01

    textabstractBackground - Elevated serum urate levels can lead to gout and are associated with cardiovascular risk factors. We performed a genome-wide association study to search for genetic susceptibility loci for serum urate and gout and investigated the causal nature of the associations of serum

  20. Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations.

    Directory of Open Access Journals (Sweden)

    Melanie Kolz

    2009-06-01

    Full Text Available Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201, ABCG2 (p = 3.1x10(-26, SLC17A1 (p = 3.0x10(-14, SLC22A11 (p = 6.7x10(-14, SLC22A12 (p = 2.0x10(-9, SLC16A9 (p = 1.1x10(-8, GCKR (p = 1.4x10(-9, LRRC16A (p = 8.5x10(-9, and near PDZK1 (p = 2.7x10(-9. Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26 and propionyl-L-carnitine (p = 5.0x10(-8 concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57 and p = 8.1x10(-54, respectively, forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.

  1. Genetic influences on type 2 diabetes and metabolic syndrome related quantitative traits in Mauritius.

    Science.gov (United States)

    Jowett, Jeremy B; Diego, Vincent P; Kotea, Navaratnam; Kowlessur, Sudhir; Chitson, Pierrot; Dyer, Thomas D; Zimmet, Paul; Blangero, John

    2009-02-01

    Epidemiological studies report a high prevalence of type 2 diabetes and metabolic syndrome in the