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Sample records for trait loci predicting

  1. Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

    Science.gov (United States)

    Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

    2015-04-01

    Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

  2. Quantitative trait loci for behavioural traits in chicken

    NARCIS (Netherlands)

    Buitenhuis, A.J.; Rodenburg, T.B.; Siwek, M.Z.; Cornelissen, S.J.B.; Nieuwland, M.G.B.; Crooijmans, R.P.M.A.; Groenen, M.A.M.; Koene, P.; Bovenhuis, H.; Poel, van der J.J.

    2005-01-01

    The detection of quantitative trait loci (QTL) of behavioural traits has mainly been focussed on mouse and rat. With the rapid development of molecular genetics and the statistical tools, QTL mapping for behavioural traits in farm animals is developing. In chicken, a total of 30 QTL involved in

  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. 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 ...

  5. 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...

  6. Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

    DEFF Research Database (Denmark)

    Brøndum, Rasmus Froberg; Su, Guosheng; Janss, Luc

    2015-01-01

    This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected...... with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index...... itself. Depending on the trait’s economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage...

  7. Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits.

    Directory of Open Access Journals (Sweden)

    Ben J Hayes

    2010-09-01

    Full Text Available Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type", which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage than for a trait with no loci of large effect (overall type, provided the method of analysis takes advantage of the distribution of loci effects.

  8. 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...

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

    African Journals Online (AJOL)

    Lablab purpureus (L.) sweet is an ancient legume species whose immature pods serve as a vegetable in south and south-east Asia. The objective of this study is to identify quantitative trait loci (QTLs) associated with quantitative traits such as inflorescence length, peduncle length from branch to axil, peduncle length from ...

  10. Quantitative trait loci mapping for stomatal traits in interspecific ...

    Indian Academy of Sciences (India)

    M. Sumathi

    2018-02-23

    Feb 23, 2018 ... Journal of Genetics, Vol. ... QTL analysis was carried out to identify the chromosomal regions affecting ... Keywords. linkage map; quantitative trait loci; stomata; stress ..... of India for providing financial support for the project.

  11. Whole genome scan in chickens for quantitative trait loci affecting carcass traits

    NARCIS (Netherlands)

    Kaam, van J.B.C.H.M.; Groenen, M.A.M.; Bovenhuis, H.; Veenendaal, A.; Vereijken, A.L.J.; Arendonk, van J.A.M.

    1999-01-01

    An experiment was conducted to enable quantitative trait loci (QTL) mapping for carcass traits. The population consisted of 10 full-sib families originating from a cross between male and female founders chosen from two different outcross broiler lines. Founder animals, parents, offspring, and

  12. 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.

  13. Quantitative trait loci and metabolic pathways

    Science.gov (United States)

    McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

    1998-01-01

    The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

  14. Quantitative trait loci analysis of osteocondrosis traits in the elbow joint of pigs

    DEFF Research Database (Denmark)

    Christensen, O F; Busch, M E; Gregersen, V R

    2010-01-01

    Osteochondrosis is a growth disorder in the cartilage of young animals and is characterised by lesions found in the cartilage and bone. This study identified quantitative trait loci (QTLs) associated with six osteochondrosis lesion traits in the elbow joint of finishing pigs. The traits were: thi...

  15. Quantile-Based Permutation Thresholds for Quantitative Trait Loci Hotspots

    NARCIS (Netherlands)

    Neto, Elias Chaibub; Keller, Mark P.; Broman, Andrew F.; Attie, Alan D.; Jansen, Ritsert C.; Broman, Karl W.; Yandell, Brian S.; Borevitz, J.

    Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key

  16. Quantitative trait loci associated with seed and seedling traits in Lactuca.

    Science.gov (United States)

    Argyris, Jason; Truco, María José; Ochoa, Oswaldo; Knapp, Steven J; Still, David W; Lenssen, Ger M; Schut, Johan W; Michelmore, Richard W; Bradford, Kent J

    2005-11-01

    Seed and seedling traits related to germination and stand establishment are important in the production of cultivated lettuce (Lactuca sativa L.). Six seed and seedling traits segregating in a L. sativa cv. Salinas x L. serriola recombinant inbred line population consisting of 103 F8 families revealed a total of 17 significant quantitative trait loci (QTL) resulting from three seed production environments. Significant QTL were identified for germination in darkness, germination at 25 and 35 degrees C, median maximum temperature of germination, hypocotyl length at 72 h post-imbibition, and plant (seedling) quality. Some QTL for germination and early seedling growth characteristics were co-located, suggestive of pleiotropic loci regulating these traits. A single QTL (Htg6.1) described 25 and 23% of the total phenotypic variation for high temperature germination in California- and Netherlands-grown populations, respectively, and was significant between 33 and 37 degrees C. Additionally, Htg6.1 showed significant epistatic interactions with other Htg QTL and a consistent effect across all the three seed production environments. L. serriola alleles increased germination at these QTL. The estimate of narrow-sense heritability (h2) of Htg6.1 was 0.84, indicating potential for L. serriola as a source of germination thermotolerance for lettuce introgression programs.

  17. 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), ...

  18. Genomic value prediction for quantitative traits under the epistatic model

    Directory of Open Access Journals (Sweden)

    Xu Shizhong

    2011-01-01

    Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

  19. 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...

  20. Quantitative trait loci for fertility traits in Finnish Ayrshire cattle

    Directory of Open Access Journals (Sweden)

    Viitala Sirja M

    2008-03-01

    Full Text Available Abstract 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 were used as phenotypic data. In a granddaughter design, 171 markers were typed on all 29 bovine autosomes. Associations between markers and traits were analysed by multiple marker regression. Multi-trait analyses were carried out with a variance component based approach for the chromosomes and trait 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.

  1. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Science.gov (United States)

    Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

    2015-01-01

    The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  2. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Directory of Open Access Journals (Sweden)

    Ulrike Ober

    Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

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

    African Journals Online (AJOL)

    Mapping of quantitative trait loci controlling Orobanche foetida Poir. resistance in faba bean (Vicia faba L.) R Díaz-Ruiz, A Torres, MV Gutierrez, D Rubiales, JI Cubero, M Kharrat, Z Satovic, B Román ...

  4. 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.E. 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

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

    NARCIS (Netherlands)

    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 O; 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; Kivimäki, 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 F; 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

    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

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

    NARCIS (Netherlands)

    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, Asa; 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 O.; 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; Kivimäki, 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 F.; 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

    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

  7. 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 ...

  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. 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.

  10. Quantitative trait loci associated with anthracnose resistance in sorghum

    Science.gov (United States)

    With an aim to develop a durable resistance to the fungal disease anthracnose, two unique genetic sources of resistance were selected to create genetic mapping populations to identify regions of the sorghum genome that encode anthracnose resistance. A series of quantitative trait loci were identifi...

  11. 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.

  12. 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.

  13. 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.

  14. 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

    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...

  15. 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

    Quantitative trait loci (QTL) for Cadmium (Cd) tolerance and accumulation in wheat (Triticum aestivum L.) were identified, using 103 recombinant inbred lines (RILs) derived from a cross of Ch×Sh at germination and seedling stages. The traits of germination, growth and physiology were measured. Cd...

  16. 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.

  17. 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

  18. 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

  19. 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.;

  20. 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.

  1. A general mixture model for mapping quantitative trait loci by using molecular markers

    NARCIS (Netherlands)

    Jansen, R.C.

    1992-01-01

    In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers.

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

    NARCIS (Netherlands)

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

  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. Joint analysis of quantitative trait loci and majoreffect causative mutations affecting meat quality and carcass composition traits in pigs

    OpenAIRE

    Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Herault, Frédéric; Damon, Marie; Le Roy, Pascale

    2011-01-01

    Abstract Background Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effect...

  6. 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.

  7. Mapping Quantitative Trait Loci (QTL in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL

    Directory of Open Access Journals (Sweden)

    Thomson Peter C

    2010-09-01

    Full Text Available Abstract An (Awassi × Merino × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1 and 3.5 (cohort 2 years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3, 15 significant (LOD ≥ 2, and 11 suggestive QTL (1.7 ≤ LOD P P A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

  8. A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

    OpenAIRE

    Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.

    2006-01-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...

  9. Genotype-dependent participation of coat color gene loci in the behavioral traits of laboratory mice.

    Science.gov (United States)

    Yamamuro, Yutaka; Shiraishi, Aya

    2011-10-01

    To evaluate if loci responsible for coat color phenotypes contribute to behavioral characteristics, we specified novel gene loci associated with social exploratory behavior and examined the effects of the frequency of each allele at distinct loci on behavioral expression. We used the F2 generation, which arose from the mating of F1 mice obtained by interbreeding DBA/2 and ICR mice. Phenotypic analysis indicated that the agouti and albino loci affect behavioral traits. A genotype-based analysis revealed that novel exploratory activity was suppressed in a manner dependent on the frequency of the dominant wild-type allele at the agouti, but not albino, locus. The allele-dependent suppression was restricted to colored mice and was not seen in albino mice. The present results suggest that the agouti locus contributes to a particular behavioral trait in the presence of a wild-type allele at the albino locus, which encodes a structural gene for tyrosinase. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Interactions between Glu-1 and Glu-3 loci and associations of selected molecular markers with quality traits in winter wheat (Triticum aestivum L.) DH lines.

    Science.gov (United States)

    Krystkowiak, Karolina; Langner, Monika; Adamski, Tadeusz; Salmanowicz, Bolesław P; Kaczmarek, Zygmunt; Krajewski, Paweł; Surma, Maria

    2017-02-01

    The quality of wheat depends on a large complex of genes and environmental factors. The objective of this study was to identify quantitative trait loci controlling technological quality traits and their stability across environments, and to assess the impact of interaction between alleles at loci Glu-1 and Glu-3 on grain quality. DH lines were evaluated in field experiments over a period of 4 years, and genotyped using simple sequence repeat markers. Lines were analysed for grain yield (GY), thousand grain weight (TGW), protein content (PC), starch content (SC), wet gluten content (WG), Zeleny sedimentation value (ZS), alveograph parameter W (APW), hectolitre weight (HW), and grain hardness (GH). A number of QTLs for these traits were identified in all chromosome groups. The Glu-D1 locus influenced TGW, PC, SC, WG, ZS, APW, GH, while locus Glu-B1 affected only PC, ZS, and WG. Most important marker-trait associations were found on chromosomes 1D and 5D. Significant effects of interaction between Glu-1 and Glu-3 loci on technological properties were recorded, and in all types of this interaction positive effects of Glu-D1 locus on grain quality were observed, whereas effects of Glu-B1 locus depended on alleles at Glu-3 loci. Effects of Glu-A3 and Glu-D3 loci per se were not significant, while their interaction with alleles present at other loci encoding HMW and LMW were important. These results indicate that selection of wheat genotypes with predicted good bread-making properties should be based on the allelic composition both in Glu-1 and Glu-3 loci, and confirm the predominant effect of Glu-D1d allele on technological properties of wheat grains.

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

    Science.gov (United States)

    Ried, Janina S.; Jeff M., Janina; Chu, Audrey Y.; Bragg-Gresham, Jennifer L.; van Dongen, Jenny; Huffman, Jennifer E.; Ahluwalia, Tarunveer S.; Cadby, Gemma; Eklund, Niina; Eriksson, Joel; Esko, Tõnu; Feitosa, Mary F.; Goel, Anuj; Gorski, Mathias; Hayward, Caroline; Heard-Costa, Nancy L.; Jackson, Anne U.; Jokinen, Eero; Kanoni, Stavroula; Kristiansson, Kati; Kutalik, Zoltán; Lahti, Jari; Luan, Jian'an; Mägi, Reedik; Mahajan, Anubha; Mangino, Massimo; Medina-Gomez, Carolina; Monda, Keri L.; Nolte, Ilja M.; Pérusse, Louis; Prokopenko, Inga; Qi, Lu; Rose, Lynda M.; Salvi, Erika; Smith, Megan T.; Snieder, Harold; Stančáková, Alena; Ju Sung, Yun; Tachmazidou, Ioanna; Teumer, Alexander; Thorleifsson, Gudmar; van der Harst, Pim; Walker, Ryan W.; Wang, Sophie R.; Wild, Sarah H.; Willems, Sara M.; Wong, Andrew; Zhang, Weihua; Albrecht, Eva; Couto Alves, Alexessander; Bakker, Stephan J. L.; Barlassina, Cristina; Bartz, Traci M.; Beilby, John; Bellis, Claire; Bergman, Richard N.; Bergmann, Sven; Blangero, John; Blüher, Matthias; Boerwinkle, Eric; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bruinenberg, Marcel; Campbell, Harry; Chen, Yii-Der Ida; Chiang, Charleston W. K.; Chines, Peter S.; Collins, Francis S; Cucca, Fracensco; Cupples, L Adrienne; D'Avila, Francesca; de Geus, Eco J .C.; Dedoussis, George; Dimitriou, Maria; Döring, Angela; Eriksson, Johan G.; Farmaki, Aliki-Eleni; Farrall, Martin; Ferreira, Teresa; Fischer, Krista; Forouhi, Nita G.; Friedrich, Nele; Gjesing, Anette Prior; Glorioso, Nicola; Graff, Mariaelisa; Grallert, Harald; Grarup, Niels; Gräßler, Jürgen; Grewal, Jagvir; Hamsten, Anders; Harder, Marie Neergaard; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas; Hattersley, Andrew Tym; Havulinna, Aki S.; Heliövaara, Markku; Hillege, Hans; Hofman, Albert; Holmen, Oddgeir; Homuth, Georg; Hottenga, Jouke-Jan; Hui, Jennie; Husemoen, Lise Lotte; Hysi, Pirro G.; Isaacs, Aaron; Ittermann, Till; Jalilzadeh, Shapour; James, Alan L.; Jørgensen, Torben; Jousilahti, Pekka; Jula, Antti; Marie Justesen, Johanne; Justice, Anne E.; Kähönen, Mika; Karaleftheri, Maria; Tee Khaw, Kay; Keinanen-Kiukaanniemi, Sirkka M.; Kinnunen, Leena; Knekt, Paul B.; Koistinen, Heikki A.; Kolcic, Ivana; Kooner, Ishminder K.; Koskinen, Seppo; Kovacs, Peter; Kyriakou, Theodosios; Laitinen, Tomi; Langenberg, Claudia; Lewin, Alexandra M.; Lichtner, Peter; Lindgren, Cecilia M.; Lindström, Jaana; Linneberg, Allan; Lorbeer, Roberto; Lorentzon, Mattias; Luben, Robert; Lyssenko, Valeriya; Männistö, Satu; Manunta, Paolo; Leach, Irene Mateo; McArdle, Wendy L.; Mcknight, Barbara; Mohlke, Karen L.; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Montasser, May E.; Morris, Andrew P.; Müller, Gabriele; Musk, Arthur W.; Narisu, Narisu; Ong, Ken K.; Oostra, Ben A.; Osmond, Clive; Palotie, Aarno; Pankow, James S.; Paternoster, Lavinia; Penninx, Brenda W.; Pichler, Irene; Pilia, Maria G.; Polašek, Ozren; Pramstaller, Peter P.; Raitakari, Olli T; Rankinen, Tuomo; Rao, D. C.; Rayner, Nigel W.; Ribel-Madsen, Rasmus; Rice, Treva K.; Richards, Marcus; Ridker, Paul M.; Rivadeneira, Fernando; Ryan, Kathy A.; Sanna, Serena; Sarzynski, Mark A.; Scholtens, Salome; Scott, Robert A.; Sebert, Sylvain; Southam, Lorraine; Sparsø, Thomas Hempel; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stolk, Ronald P.; Strauch, Konstantin; Stringham, Heather M.; Swertz, Morris A.; Swift, Amy J.; Tönjes, Anke; Tsafantakis, Emmanouil; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Vartiainen, Erkki; Venturini, Cristina; Verweij, Niek; Viikari, Jorma S.; Vitart, Veronique; Vohl, Marie-Claude; Vonk, Judith M.; Waeber, Gérard; Widén, Elisabeth; Willemsen, Gonneke; Wilsgaard, Tom; Winkler, Thomas W.; Wright, Alan F.; Yerges-Armstrong, Laura M.; Hua Zhao, Jing; Carola Zillikens, M.; Boomsma, Dorret I.; Bouchard, Claude; Chambers, John C.; Chasman, Daniel I.; Cusi, Daniele; Gansevoort, Ron T.; Gieger, Christian; Hansen, Torben; Hicks, Andrew A.; Hu, Frank; Hveem, Kristian; Jarvelin, Marjo-Riitta; Kajantie, Eero; Kooner, Jaspal S.; Kuh, Diana; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A.; Lehtimäki, Terho; Metspalu, Andres; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Palmer, Lyle J.; Pedersen, Oluf; Perola, Markus; Peters, Annette; Psaty, Bruce M.; Puolijoki, Hannu; Rauramaa, Rainer; Rudan, Igor; Salomaa, Veikko; Schwarz, Peter E. H.; Shudiner, Alan R.; Smit, Jan H.; Sørensen, Thorkild I. A.; Spector, Timothy D.; Stefansson, Kari; Stumvoll, Michael; Tremblay, Angelo; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; Völker, Uwe; Vollenweider, Peter; Wareham, Nicholas J.; Watkins, Hugh; Wilson, James F.; Zeggini, Eleftheria; Abecasis, Goncalo R.; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; van Duijn, Cornelia M.; Fox, Caroline; Groop, Leif C.; Heid, Iris M.; Hunter, David J.; Kaplan, Robert C.; McCarthy, Mark I.; North, Kari E.; O'Connell, Jeffrey R.; Schlessinger, David; Thorsteinsdottir, Unnur; Strachan, David P.; Frayling, Timothy; Hirschhorn, Joel N.; Müller-Nurasyid, Martina; Loos, Ruth 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 averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways. PMID:27876822

  12. Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

    DEFF Research Database (Denmark)

    Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

    2017-01-01

    Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

  13. Detection of Quantitative Trait Loci Affecting Fat Deposition Traits in Pigs

    Directory of Open Access Journals (Sweden)

    B. H. Choi

    2012-11-01

    Full Text Available Quantitative trait loci (QTL associated with fat deposition traits in pigs are important gene positions in a chromosome that influence meat quality of pork. For QTL study, a three generation resource population was constructed from a cross between Korean native boars and Landrace sows. A total of 240 F2 animals from intercross of F1 were produced. 80 microsatellite markers covering chromosomes 1 to 10 were selected to genotype the resource population. Intervals between adjacent markers were approximately 19 cM. Linkage analysis was performed using CRIMAP software version 2.4 with a FIXED option to obtain the map distances. For QTL analysis, the public web-based software, QTL express (http://www.qtl.cap.ed.ac.uk was used. Two significant and two suggestive QTL were identified on SSC 6, 7, and 8 as affecting body fat and IMF traits. For QTL affecting IMF, the most significant association was detected between marker sw71 and sw1881 on SSC 6, and a suggestive QTL was identified between sw268 and sw205 on SSC8. These QTL accounted for 26.58% and 12.31% of the phenotypic variance, respectively. A significant QTL affecting IMF was detected at position 105 cM between markers sw71 and sw1881 on SSC 6.

  14. Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

    Science.gov (United States)

    Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

    2018-02-02

    Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

  15. Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower

    Directory of Open Access Journals (Sweden)

    Patrick Thorwarth

    2018-02-01

    Full Text Available Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower (Brassica oleracea var. botrytis by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding.

  16. Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

    Science.gov (United States)

    Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

    2018-05-15

    A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

  17. Dominant Epistasis Between Two Quantitative Trait Loci Governing Sporulation Efficiency in Yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Bergman, Juraj; Mitrikeski, Petar T.

    2015-01-01

    Summary Sporulation efficiency in the yeast Saccharomyces cerevisiae is a well-established model for studying quantitative traits. A variety of genes and nucleotides causing different sporulation efficiencies in laboratory, as well as in wild strains, has already been extensively characterised (mainly by reciprocal hemizygosity analysis and nucleotide exchange methods). We applied a different strategy in order to analyze the variation in sporulation efficiency of laboratory yeast strains. Coupling classical quantitative genetic analysis with simulations of phenotypic distributions (a method we call phenotype modelling) enabled us to obtain a detailed picture of the quantitative trait loci (QTLs) relationships underlying the phenotypic variation of this trait. Using this approach, we were able to uncover a dominant epistatic inheritance of loci governing the phenotype. Moreover, a molecular analysis of known causative quantitative trait genes and nucleotides allowed for the detection of novel alleles, potentially responsible for the observed phenotypic variation. Based on the molecular data, we hypothesise that the observed dominant epistatic relationship could be caused by the interaction of multiple quantitative trait nucleotides distributed across a 60--kb QTL region located on chromosome XIV and the RME1 locus on chromosome VII. Furthermore, we propose a model of molecular pathways which possibly underlie the phenotypic variation of this trait. PMID:27904371

  18. 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...

  19. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng

    2016-07-06

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  20. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

    Directory of Open Access Journals (Sweden)

    Guozheng Liu

    Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  1. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  2. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    Science.gov (United States)

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

  3. Quantitative trait loci mapping of heat tolerance in broccoli (Brassica oleracea var. italica) using genotyping-by-sequencing.

    Science.gov (United States)

    Branham, Sandra E; Stansell, Zachary J; Couillard, David M; Farnham, Mark W

    2017-03-01

    Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials. Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

  4. 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.

  5. 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.

  6. 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...

  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. 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...

  9. Quantile-based permutation thresholds for quantitative trait loci hotspots.

    Science.gov (United States)

    Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

    2012-08-01

    Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

  10. 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...

  11. Quantitative Trait Loci Mapping Problem: An Extinction-Based Multi-Objective Evolutionary Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Nicholas S. Flann

    2013-09-01

    Full Text Available The Quantitative Trait Loci (QTL mapping problem aims to identify regions in the genome that are linked to phenotypic features of the developed organism that vary in degree. It is a principle step in determining targets for further genetic analysis and is key in decoding the role of specific genes that control quantitative traits within species. Applications include identifying genetic causes of disease, optimization of cross-breeding for desired traits and understanding trait diversity in populations. In this paper a new multi-objective evolutionary algorithm (MOEA method is introduced and is shown to increase the accuracy of QTL mapping identification for both independent and epistatic loci interactions. The MOEA method optimizes over the space of possible partial least squares (PLS regression QTL models and considers the conflicting objectives of model simplicity versus model accuracy. By optimizing for minimal model complexity, MOEA has the advantage of solving the over-fitting problem of conventional PLS models. The effectiveness of the method is confirmed by comparing the new method with Bayesian Interval Mapping approaches over a series of test cases where the optimal solutions are known. This approach can be applied to many problems that arise in analysis of genomic data sets where the number of features far exceeds the number of observations and where features can be highly correlated.

  12. Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

    Science.gov (United States)

    Cavanagh, Colin R; Jonas, Elisabeth; Hobbs, Matthew; Thomson, Peter C; Tammen, Imke; Raadsma, Herman W

    2010-09-16

    An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

  13. Mapping quantitative trait loci (QTL in sheep. II. Meta-assembly and identification of novel QTL for milk production traits in sheep

    Directory of Open Access Journals (Sweden)

    Lam Mary K

    2009-10-01

    Full Text Available Abstract An (Awassi × Merino × Merino backcross family of 172 ewes was used to map quantitative trait loci (QTL for different milk production traits on a framework map of 200 loci across all autosomes. From five previously proposed mathematical models describing lactation curves, the Wood model was considered the most appropriate due to its simplicity and its ability to determine ovine lactation curve characteristics. Derived milk traits for milk, fat, protein and lactose yield, as well as percentage composition and somatic cell score were used for single and two-QTL approaches using maximum likelihood estimation and regression analysis. A total of 15 significant (P P http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_genome/. Many of the QTL for milk production traits have been reported on chromosomes 1, 3, 6, 16 and 20. Those on chromosomes 3 and 20 are in strong agreement with the results reported here. In addition, novel QTL were found on chromosomes 7, 8, 9, 14, 22 and 24. In a cross-species comparison, we extended the meta-assembly by comparing QTL regions of sheep and cattle, which provided strong evidence for synteny conservation of QTL regions for milk, fat, protein and somatic cell score data between cattle and sheep.

  14. An optimal strategy for functional mapping of dynamic trait loci.

    Science.gov (United States)

    Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

    2010-02-01

    As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

  15. 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.

  16. 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…

  17. 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.

  18. 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.

  19. 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

  20. High Resolution of Quantitative Traits Into Multiple Loci via Interval Mapping

    OpenAIRE

    Jansen, Ritsert C.; Stam, Piet

    1994-01-01

    A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F1 data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection...

  1. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  2. 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.

  3. Mapping quantitative trait loci in a selectively genotyped outbred population using a mixture model approach

    NARCIS (Netherlands)

    Johnson, David L.; Jansen, Ritsert C.; Arendonk, Johan A.M. van

    1999-01-01

    A mixture model approach is employed for the mapping of quantitative trait loci (QTL) for the situation where individuals, in an outbred population, are selectively genotyped. Maximum likelihood estimation of model parameters is obtained from an Expectation-Maximization (EM) algorithm facilitated by

  4. 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

  5. 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.

  6. Metabolomic Quantitative Trait Loci (mQTL Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.

    Directory of Open Access Journals (Sweden)

    William E Kraus

    2015-11-01

    Full Text Available Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA, long-chain dicarboxylacylcarnitine (LCDA and medium chain acylcarnitine (MCA metabolites are heritable and predict cardiovascular disease (CVD events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490, we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1 These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10. Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2. Expression quantitative trait loci (eQTL pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

  7. Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

    Science.gov (United States)

    Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

    2010-04-01

    Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

  8. Quantitative Trait Loci Analysis of Seed Quality Characteristics in Lentil using Single Nucleotide Polymorphism Markers

    Directory of Open Access Journals (Sweden)

    Michael J. Fedoruk

    2013-11-01

    Full Text Available Seed shape, color, and pattern of lentil ( Medik. subsp. are important quality traits as they determine market class and possible end uses. A recombinant inbred line population was phenotyped for seed dimensions over multiple site–years and classified according to cotyledon and seed coat color and pattern. The objectives were to determine the heritability of seed dimensions, identify genomic regions controlling these dimensions, and map seed coat and cotyledon color genes. A genetic linkage map consisting of 563 single nucleotide polymorphisms, 10 simple sequence repeats, and four seed color loci was developed for quantitative trait loci (QTL analysis. Loci for seed coat color and pattern mapped to linkage groups 2 (, 3 (, and 6 ( while the cotyledon color locus ( mapped to linkage group 1. The broad sense heritability estimates were high for seed diameter (broad-sense heritability [] = 0.92 and seed plumpness ( = 0.94 while seed thickness ( = 0.60 and days to flowering ( = 0.45 were more moderate. There were significant seed dimension QTL on six of the seven linkage groups. The most significant QTL for diameter and plumpness was found at the cotyledon color locus (. The markers identified in this study can be used to help enrich breeding populations for desired seed quality characteristics, thereby increasing efficiency in the lentil breeding program.

  9. 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...

  10. 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.

  11. Genome scan for nonadditive heterotic trait loci reveals mainly underdominant effects in Saccharomyces cerevisiae.

    Science.gov (United States)

    Laiba, Efrat; Glikaite, Ilana; Levy, Yael; Pasternak, Zohar; Fridman, Eyal

    2016-04-01

    The overdominant model of heterosis explains the superior phenotype of hybrids by synergistic allelic interaction within heterozygous loci. To map such genetic variation in yeast, we used a population doubling time dataset of Saccharomyces cerevisiae 16 × 16 diallel and searched for major contributing heterotic trait loci (HTL). Heterosis was observed for the majority of hybrids, as they surpassed their best parent growth rate. However, most of the local heterozygous loci identified by genome scan were surprisingly underdominant, i.e., reduced growth. We speculated that in these loci adverse effects on growth resulted from incompatible allelic interactions. To test this assumption, we eliminated these allelic interactions by creating hybrids with local hemizygosity for the underdominant HTLs, as well as for control random loci. Growth of hybrids was indeed elevated for most hemizygous to HTL genes but not for control genes, hence validating the results of our genome scan. Assessing the consequences of local heterozygosity by reciprocal hemizygosity and allele replacement assays revealed the influence of genetic background on the underdominant effects of HTLs. Overall, this genome-wide study on a multi-parental hybrid population provides a strong argument against single gene overdominance as a major contributor to heterosis, and favors the dominance complementation model.

  12. Quantitative Trait Loci Analysis of Allelopathy in Rice

    DEFF Research Database (Denmark)

    Jensen, L B; Courtois, B; Olofsdotter, M

    2008-01-01

    The allelopathic potential of rice (Oryza sativa L.) against Echinochloa crus-galli (L.) Beauv. was investigated under both laboratory and greenhouse conditions. A population of 150 recombinant inbred lines (RILs) was derived through single-seed descent from a cross between the indica cultivar AC...... the population phenotype was normally distributed. Two quantitative trait loci (QTLs) were located on chromosomes 4 and 7, explaining 20% of the phenotypic variation. A second relay seeding experiment was set up, this time including charcoal in the perlite. This screening showed that the allelopathic rice...... varieties did not have any effect on the weed species when grown with charcoal, the charcoal reversing the effect of any potential allelochemicals exuded from the rice roots. The second phenotypic experiment was conducted under greenhouse conditions in pots. Thirteen QTLs were detected for four different...

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

    Science.gov (United States)

    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, Tönu; 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 raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control. PMID:22885924

  14. A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

    Science.gov (United States)

    Anderson, Carl A; McRae, Allan F; Visscher, Peter M

    2006-07-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

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

    Science.gov (United States)

    Horikoshi, Momoko; Mӓgi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S; Winkler, Thomas W; Willems, Sara M; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K E; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R; Groves, Christopher J; Bennett, Amanda J; Lehtimӓki, Terho; Viikari, Jorma S; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M; Karssen, Lennart C; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J; de Craen, Anton J M; Deelen, Joris; Havulinna, Aki S; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D; Samani, Nilesh J; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M; Slagboom, P Eline; Metspalu, Andres; van Duijn, Cornelia M; Eriksson, Johan G; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T; Power, Chris; Penninx, Brenda W J H; de Geus, Eco; Smit, Johannes H; Boomsma, Dorret I; Pedersen, Nancy L; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I; Morris, Andrew P

    2015-07-01

    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.

  16. Analysis of genetic variants of coat colour loci and their influence on the coat colour phenotype and quantitative performance traits in the pig

    OpenAIRE

    Siebel, Krista

    2010-01-01

    The influence of four single coat colour loci (KIT, MC1R, TYR, ASP) on the coat colour phenotype and performance traits in the pig have been investigated in a resource population. The research revealed an unknown genotype for the white phenotype in the pig. The influence of the Agouti locus on the coat colour phenotype has been suggested. An influence of the coat colour loci KIT on growth performance traits and MC1R on body fatness could be demonstrated.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Physiognomy: Personality Traits Prediction by Learning

    Institute of Scientific and Technical Information of China (English)

    Ting Zhang; Ri-Zhen Qin; Qiu-Lei Dong; Wei Gao; Hua-Rong Xu; Zhan-Yi Hu

    2017-01-01

    Evaluating individuals' personality traits and intelligence from their faces plays a crucial role in interpersonal relationship and important social events such as elections and court sentences.To assess the possible correlations between personality traits (also measured intelligence) and face images,we first construct a dataset consisting of face photographs,personality measurements,and intelligence measurements.Then,we build an end-to-end convolutional neural network for prediction of personality traits and intelligence to investigate whether self-reported personality traits and intelligence can be predicted reliably from a face image.To our knowledge,it is the first work where deep learning is applied to this problem.Experimental results show the following three points:1)"Rule-consciousness" and "Tension" can be reliably predicted from face images.2) It is difficult,if not impossible,to predict intelligence from face images,a finding in accord with previous studies.3) Convolutional neural network (CNN) features outperform traditional handcrafted features in predicting traits.

  2. 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.

  3. Targeted introgression of cotton fibre quality quantitative trait loci using molecular markers

    International Nuclear Information System (INIS)

    Lacape, J.M.; Trung-Bieu Nguyen; Hau, B.; Giband, M.

    2007-01-01

    Within the framework of a cotton breeding programme, molecular markers are used to improve the efficiency of the introgression of fibre quality traits of Gossypium barbadense into G. hirsutum. A saturated genetic map was developed based on genotyping data obtained from the BC 1 (75 plants) and BC 2 (200 plants) generations. Phenotypic measurements conducted over three generations (BC 1 , BC 2 and BC 2 S 1 ) allowed 80 quantitative trait loci (QTL) to be detected for fibre length, uniformity, strength, elongation, fineness and colour. Positive QTL, i.e. those for which favourable alleles came from the G. barbadense parent, were harboured by 19 QTL-rich regions on 15 'carrier' chromosomes. In subsequent generations (BC 3 and BC 4 ), markers framing the QTL-rich regions were used to select about 10 percent of over 400 plants analysed in each generation. Although BC plants selected through the marker-assisted selection (MAS) process show promising fibre quality, only their full field evaluation will allow validation of the procedure. (author)

  4. Quantitative trait loci for maysin synthesis in maize (Zea mays L.) lines selected for high silk maysin content.

    Science.gov (United States)

    Meyer, J D F; Snook, M E; Houchins, K E; Rector, B G; Widstrom, N W; McMullen, M D

    2007-06-01

    Maysin is a naturally occurring C-glycosyl flavone found in maize (Zea mays L.) silk tissue that confers resistance to corn earworm (Helicoverpa zea, Boddie). Recently, two new maize populations were derived for high silk maysin. The two populations were named the exotic populations of maize (EPM) and the southern inbreds of maize (SIM). Quantitative trait locus (QTL) analysis was employed to determine which loci were responsible for elevated maysin levels in inbred lines derived from the EPM and SIM populations. The candidate genes consistent with QTL position included the p (pericarp color), c2 (colorless2), whp1 (white pollen1) and in1 (intensifier1) loci. The role of these loci in controlling high maysin levels in silks was tested by expression analysis and use of the loci as genetic markers onto the QTL populations. These studies support p, c2 and whp1, but not in1, as loci controlling maysin. Through this study, we determined that the p locus regulates whp1 transcription and that increased maysin in these inbred lines was primarily due to alleles at both structural and regulatory loci promoting increased flux through the flavone pathway by increasing chalcone synthase activity.

  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; 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

  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. Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function.

    Science.gov (United States)

    Smeland, Olav B; Frei, Oleksandr; Kauppi, Karolina; Hill, W David; Li, Wen; Wang, Yunpeng; Krull, Florian; Bettella, Francesco; Eriksen, Jon A; Witoelar, Aree; Davies, Gail; Fan, Chun C; Thompson, Wesley K; Lam, Max; Lencz, Todd; Chen, Chi-Hua; Ueland, Torill; Jönsson, Erik G; Djurovic, Srdjan; Deary, Ian J; Dale, Anders M; Andreassen, Ole A

    2017-10-01

    Schizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction. To identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains. Combining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79 757 [cases, 34 486; controls, 45 271]); verbal-numerical reasoning (n = 36 035) and reaction time (n = 111 483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53 949) and COGENT (Cognitive Genomics Consortium) (n = 27 888). Genetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined. Among the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and

  8. Simultaneous discovery, estimation and prediction analysis of complex traits using a bayesian mixture model.

    Directory of Open Access Journals (Sweden)

    Gerhard Moser

    2015-04-01

    Full Text Available Gene discovery, estimation of heritability captured by SNP arrays, inference on genetic architecture and prediction analyses of complex traits are usually performed using different statistical models and methods, leading to inefficiency and loss of power. Here we use a Bayesian mixture model that simultaneously allows variant discovery, estimation of genetic variance explained by all variants and prediction of unobserved phenotypes in new samples. We apply the method to simulated data of quantitative traits and Welcome Trust Case Control Consortium (WTCCC data on disease and show that it provides accurate estimates of SNP-based heritability, produces unbiased estimators of risk in new samples, and that it can estimate genetic architecture by partitioning variation across hundreds to thousands of SNPs. We estimated that, depending on the trait, 2,633 to 9,411 SNPs explain all of the SNP-based heritability in the WTCCC diseases. The majority of those SNPs (>96% had small effects, confirming a substantial polygenic component to common diseases. The proportion of the SNP-based variance explained by large effects (each SNP explaining 1% of the variance varied markedly between diseases, ranging from almost zero for bipolar disorder to 72% for type 1 diabetes. Prediction analyses demonstrate that for diseases with major loci, such as type 1 diabetes and rheumatoid arthritis, Bayesian methods outperform profile scoring or mixed model approaches.

  9. Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

    Science.gov (United States)

    Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

    2017-04-01

    Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

  10. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  11. Mapping of quantitative trait loci for resistance to fall armyworm and southwestern corn borer leaf-feeding damage in maize.

    Science.gov (United States)

    Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), and southwestern corn borer (SWCB), Diatraea grandiosella Dyar are damaging insect pests of maize resulting in significant yield and economic losses. A previous study identified quantitative trait loci (QTL) that contribute to reduced leaf-fe...

  12. Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

    Directory of Open Access Journals (Sweden)

    Nina Melzer

    Full Text Available In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach. To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317 SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype.

  13. 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

  14. 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

  15. 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.

  16. Quantitative trait loci for magnitude of the plasma cortisol response to confinement in rainbow trout.

    Science.gov (United States)

    Quillet, E; Krieg, F; Dechamp, N; Hervet, C; Bérard, A; Le Roy, P; Guyomard, R; Prunet, P; Pottinger, T G

    2014-04-01

    Better understanding of the mechanisms underlying interindividual variation in stress responses and their links with production traits is a key issue for sustainable animal breeding. In this study, we searched for quantitative trait loci (QTL) controlling the magnitude of the plasma cortisol stress response and compared them to body size traits in five F2 full-sib families issued from two rainbow trout lines divergently selected for high or low post-confinement plasma cortisol level. Approximately 1000 F2 individuals were individually tagged and exposed to two successive acute confinement challenges (1 month interval). Post-stress plasma cortisol concentrations were determined for each fish. A medium density genome scan was carried out (268 markers, overall marker spacing less than 10 cM). QTL detection was performed using qtlmap software, based on an interval mapping method (http://www.inra.fr/qtlmap). Overall, QTL of medium individual effects on cortisol responsiveness (confinement stressor are distinct traits sharing only part of their genetic control. Chromosomal location of the steroidogenic acute regulatory protein (STAR) makes it a good potential candidate gene for one of the QTL. Finally, comparison of body size traits QTL (weight, length and body conformation) with cortisol-associated QTL did not support evidence for negative genetic relationships between the two types of traits. © 2014 Stichting International Foundation for Animal Genetics.

  17. Evolution of branched regulatory genetic pathways: directional selection on pleiotropic loci accelerates developmental system drift.

    Science.gov (United States)

    Johnson, Norman A; Porter, Adam H

    2007-01-01

    Developmental systems are regulated by a web of interacting loci. One common and useful approach in studying the evolution of development is to focus on classes of interacting elements within these systems. Here, we use individual-based simulations to study the evolution of traits controlled by branched developmental pathways involving three loci, where one locus regulates two different traits. We examined the system under a variety of selective regimes. In the case where one branch was under stabilizing selection and the other under directional selection, we observed "developmental system drift": the trait under stabilizing selection showed little phenotypic change even though the loci underlying that trait showed considerable evolutionary divergence. This occurs because the pleiotropic locus responds to directional selection and compensatory mutants are then favored in the pathway under stabilizing selection. Though developmental system drift may be caused by other mechanisms, it seems likely that it is accelerated by the same underlying genetic mechanism as that producing the Dobzhansky-Muller incompatibilities that lead to speciation in both linear and branched pathways. We also discuss predictions of our model for developmental system drift and how different selective regimes affect probabilities of speciation in the branched pathway system.

  18. 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

    The aim of this study was to 1) detect QTL across the cattle genome that influence the incidence of clinical mastitis and somatic cell score (SCS) in Danish Holsteins, and 2) characterize these QTL for pleiotropy versus multiple linked quantitative trait loci (QTL) when chromosomal regions...... affecting clinical mastitis were also affecting other traits in the Danish udder health index or milk production traits. The chromosomes were scanned using a granddaughter design where markers were typed for 19 to 34 grandsire families and 1,373 to 2,042 sons. A total of 356 microsatellites covering all 29...... autosomes were used in the scan. Among the across-family regression analyses, 16 showed chromosome-wide significance for the primary traits incidence of clinical mastitis in first (CM1), second (CM2), and third (CM3) lactations, and SCS. Regions of chromosomes 5, 6, 9, 11, 15, and 26 were found to affect CM...

  19. Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs.

    Science.gov (United States)

    Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Hérault, Frédéric; Damon, Marie; Le Roy, Pascale

    2011-08-29

    Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected

  20. Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

    Directory of Open Access Journals (Sweden)

    Iannuccelli Nathalie

    2011-08-01

    Full Text Available Abstract Background Detection of quantitative trait loci (QTLs affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08, with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Results Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Conclusions Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the

  1. SplicePlot: a utility for visualizing splicing quantitative trait loci.

    Science.gov (United States)

    Wu, Eric; Nance, Tracy; Montgomery, Stephen B

    2014-04-01

    RNA sequencing has provided unprecedented resolution of alternative splicing and splicing quantitative trait loci (sQTL). However, there are few tools available for visualizing the genotype-dependent effects of splicing at a population level. SplicePlot is a simple command line utility that produces intuitive visualization of sQTLs and their effects. SplicePlot takes mapped RNA sequencing reads in BAM format and genotype data in VCF format as input and outputs publication-quality Sashimi plots, hive plots and structure plots, enabling better investigation and understanding of the role of genetics on alternative splicing and transcript structure. Source code and detailed documentation are available at http://montgomerylab.stanford.edu/spliceplot/index.html under Resources and at Github. SplicePlot is implemented in Python and is supported on Linux and Mac OS. A VirtualBox virtual machine running Ubuntu with SplicePlot already installed is also available.

  2. Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice

    Science.gov (United States)

    Kelly, Scott A.; Hua, Kunjie; Pomp, Daniel

    2012-01-01

    Driven by the recent obesity epidemic, interest in understanding the complex genetic and environmental basis of body weight and composition is great. We investigated this by searching for quantitative trait loci (QTLs) affecting a number of weight and adiposity traits in a G10 advanced intercross population produced from crosses of mice in inbred strain C57BL/6J with those in a strain selected for high voluntary wheel running. The mice in this population were fed either a high-fat or a control diet throughout the study and also measured for four exercise traits prior to death, allowing us to test for pre- and postexercise QTLs as well as QTL-by-diet and QTL-by-exercise interactions. Our genome scan uncovered a number of QTLs, of which 40% replicated QTLs previously found for similar traits in an earlier (G4) generation. For those replicated QTLs, the confidence intervals were reduced from an average of 19 Mb in the G4 to 8 Mb in the G10. Four QTLs on chromosomes 3, 8, 13, and 18 were especially prominent in affecting the percentage of fat in the mice. About of all QTLs showed interactions with diet, exercise, or both, their genotypic effects on the traits showing a variety of patterns depending on the diet or level of exercise. It was concluded that the indirect effects of these QTLs provide an underlying genetic basis for the considerable variability in weight or fat loss typically found among individuals on the same diet and/or exercise regimen. PMID:23048196

  3. Localization of quantitative trait loci associated with radiation induced pulmonary fibrosis in the mouse

    International Nuclear Information System (INIS)

    Oas, L.G.; Haston, C.K.; Travis, E.L.

    1997-01-01

    Purpose/Objective: Pulmonary fibrosis is often a limiting factor in the planning of radiotherapy for thoracic neoplasms. Differences in the propensity to develop radiation induced pulmonary fibrosis have been noted between C3Hf/Kam (resistant) and C57BL/6J (susceptible) mouse strains. Bleomycin and radiation induced pulmonary fibrosis have been shown to be heritable traits in mice with significant linkage to the major histocompatibility complex on chromosome 17. The heritability of radiation induced damage was estimated to be 38%±11% with 1-2 genetic factors influencing expression. Only 6.6% of the phenotypic variance could be attributed to chromosome 17. A search of the genome was undertaken to identify loci which may be responsible for the remaining phenotypic variance. Materials and Methods: C3Hf/Kam and C57BL/6J mice were crosbred to yield F1 and F2 (F1 intercross) generations. Two hundred sixty eight males and females of the F2 generation were treated with orthovoltage radiation, 14 or 16 Gy, to the whole thorax. The mice were sacrificed after development of respiratory distress or at 33 weeks. Histologic sections were assessed with quantified image analysis to determine the percentage of fibrosis in both lungs. Genotyping was done on the pooled DNA of the mice who developed respiratory distress with 44 32 P labeled microsatellite markers having an average spacing of 24.5 cM. Correlation of the quantitative trait loci (QTLs) with the highest quartile of fibrosis revealed 10 out of 44 regions showing possible linkage. Individual DNA from 54 mice with the least fibrosis and 40 with the most fibrosis were probed using these markers. PCR and gel electrophoresis were performed and the results analysed. Results: Of the 10 markers analysed, one locus on chromosome 1 meets the criterion of suggestion of linkage. Conclusion: These findings point to regions on the mouse genome for which further investigation of fibrosis associated loci may be warranted

  4. Quantitative Trait Loci Associated with Drought Tolerance in Brachypodium distachyon

    Directory of Open Access Journals (Sweden)

    Yiwei Jiang

    2017-05-01

    Full Text Available The temperate wild grass Brachypodium distachyon (Brachypodium serves as model system for studying turf and forage grasses. Brachypodium collections show diverse responses to drought stress, but little is known about the genetic mechanisms of drought tolerance of this species. The objective of this study was to identify quantitative trait loci (QTLs associated with drought tolerance traits in Brachypodium. We assessed leaf fresh weight (LFW, leaf dry weight (LDW, leaf water content (LWC, leaf wilting (WT, and chlorophyll fluorescence (Fv/Fm under well-watered and drought conditions on a recombinant inbred line (RIL population from two parents (Bd3-1 and Bd1-1 known to differ in their drought adaptation. A linkage map of the RIL population was constructed using 467 single nucleotide polymorphism (SNP markers obtained from genotyping-by-sequencing. The Bd3-1/Bd1-1 map spanned 1,618 cM and had an average distance of 3.5 cM between adjacent single nucleotide polymorphisms (SNPs. Twenty-six QTLs were identified in chromosome 1, 2, and 3 in two experiments, with 14 of the QTLs under well-watered conditions and 12 QTLs under drought stress. In Experiment 1, a QTL located on chromosome 2 with a peak at 182 cM appeared to simultaneously control WT, LWC, and Fv/Fm under drought stress, accounting for 11–18.7% of the phenotypic variation. Allelic diversity of candidate genes DREB2B, MYB, and SPK, which reside in one multi-QTL region, may play a role in the natural variation in whole plant drought tolerance in Brachypodium. Co-localization of QTLs for multiple drought-related traits suggest that the gene(s involved are important regulators of drought tolerance in Brachypodium.

  5. 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...

  6. 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

    at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m(2...

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

    Directory of Open Access Journals (Sweden)

    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

  8. Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects

    NARCIS (Netherlands)

    Korstanje, Ron; Desai, Jigar; Lazar, Gloria; King, Benjamin; Rollins, Jarod; Spurr, Melissa; Joseph, Jamie; Kadambi, Sindhuja; Li, Yang; Cherry, Allison; Matteson, Paul G.; Paigen, Beverly; Millonig, James H.

    Korstanje R, Desai J, Lazar G, King B, Rollins J, Spurr M, Joseph J, Kadambi S, Li Y, Cherry A, Matteson PG, Paigen B, Millonig JH. Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects. Physiol Genomics 35:

  9. Genomic selection: genome-wide prediction in plant improvement.

    Science.gov (United States)

    Desta, Zeratsion Abera; Ortiz, Rodomiro

    2014-09-01

    Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Genomic prediction of reproduction traits for Merino sheep.

    Science.gov (United States)

    Bolormaa, S; Brown, D J; Swan, A A; van der Werf, J H J; Hayes, B J; Daetwyler, H D

    2017-06-01

    Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy

  11. Genetic susceptibility to obesity and related traits in childhood and adolescence

    DEFF Research Database (Denmark)

    den Hoed, Marcel; Ekelund, Ulf; Brage, Søren

    2010-01-01

    Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.......Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents....

  12. Multi-ethnic fine-mapping of 14 central adiposity loci

    NARCIS (Netherlands)

    Liu, C.T.; Buchkovich, M.L.; Winkler, T.W.; Heid, I.M.; Hottenga, J.J.; Boomsma, D.I.; de Geus, E.J.C.; Willemsen, G.; Borecki, I.B.; Fox, C.S.; Mohlke, K.L.; North, K.E.; Cupples, L.A.

    2014-01-01

    The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowingthe signalsremains necessary. Twelve of 14 loci identified inGIANTEA

  13. Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross.

    Science.gov (United States)

    Brand, Bodo; Scheinhardt, Markus O; Friedrich, Juliane; Zimmer, Daisy; Reinsch, Norbert; Ponsuksili, Siriluck; Schwerin, Manfred; Ziegler, Andreas

    2016-10-06

    The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing

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

    Science.gov (United States)

    Iqbal, Asif; Kim, You-Sam; Kang, Jun-Mo; Lee, Yun-Mi; Rai, Rajani; Jung, Jong-Hyun; Oh, Dong-Yup; Nam, Ki-Chang; Lee, Hak-Kyo; Kim, Jong-Joo

    2015-01-01

    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. PMID:26580276

  15. 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.

  16. 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.

  17. Discovery of quantitative trait loci for crossability from a synthetic wheat genotype

    Institute of Scientific and Technical Information of China (English)

    Li Zhang; Jin Wang; Ronghua Zhou; Jizeng Jia

    2011-01-01

    Crossability between wheat and rye is an important trait for wheat improvement.No quantitative trait loci (QTLs) were detected from wheat ancestors previously.The objectives of this study were to dissect the QTLs for crossability using 111 introgression lines (ILs) derived from synthetic hexaploid wheat.A total of 1275 SSR markers were screened for polymorphism between the two parents,and 552 markers of them displayed polymorphism,of which 64 were selected for genotyping the 111 BC5F6 ILs.Field trials were performed in a Latinized α-lattice design in Luoyang and Jiaozuo of Henan Province of China in 2007-2008 and 2008-2009 cropping seasons.One-way ANOVA and interval mapping (IM) analysis were used to detect QTL for crossability between wheat and rye.A total of 13 putative QTLs were detected.Five of them,QCa.caas.1A,QCa.caas.2D,QCa.caas.4B,QCa.caas.5B and QCa.caas.6A,were detected in both trials and three of them,QCa.caas.2D,QCa.caas.4B and QCa.caas.6A,were novel.The positive effect allele of the four QTLs came from the donor parent Am3 except QCa.caas.6A that came from the recurrent parent Laizhou953.ILs with both higher positive effect alleles and favorable agronomic traits developed in present study are elite germplasm for wide crossing in wheat.Results from the current study suggest that wheat ancestors can be rich in new sources of crossability genes.

  18. 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.

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

    DEFF Research Database (Denmark)

    Drag, Markus; Hansen, Mathias B.; Kadarmideen, Haja N.

    2018-01-01

    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 similar to 100 kg. Gene...... monitoring of other overlapping QTL traits should be performed to avoid any negative consequences of selection....

  20. Predicting Risk-Mitigating Behaviors From Indecisiveness and Trait Anxiety

    DEFF Research Database (Denmark)

    Mcneill, Ilona M.; Dunlop, Patrick D.; Skinner, Timothy C.

    2016-01-01

    Past research suggests that indecisiveness and trait anxiety may both decrease the likelihood of performing risk-mitigating preparatory behaviors (e.g., preparing for natural hazards) and suggests two cognitive processes (perceived control and worrying) as potential mediators. However, no single...... control over wildfire-related outcomes. Trait anxiety did not uniquely predict preparedness or perceived control, but it did uniquely predict worry, with higher trait anxiety predicting more worrying. Also, worry trended toward uniquely predicting preparedness, albeit in an unpredicted positive direction...

  1. Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

    Science.gov (United States)

    Jackson, Anne U.; Monda, Keri L.; Kilpeläinen, Tuomas O.; Esko, Tõnu; Mägi, Reedik; Li, Shengxu; Workalemahu, Tsegaselassie; Feitosa, Mary F.; Croteau-Chonka, Damien C.; Day, Felix R.; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Locke, Adam E.; Mathieson, Iain; Scherag, Andre; Vedantam, Sailaja; Wood, Andrew R.; Liang, Liming; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Dermitzakis, Emmanouil T.; Dimas, Antigone S.; Karpe, Fredrik; Min, Josine L.; Nicholson, George; Clegg, Deborah J.; Person, Thomas; Krohn, Jon P.; Bauer, Sabrina; Buechler, Christa; Eisinger, Kristina; Bonnefond, Amélie; Froguel, Philippe; Hottenga, Jouke-Jan; Prokopenko, Inga; Waite, Lindsay L.; Harris, Tamara B.; Smith, Albert Vernon; Shuldiner, Alan R.; McArdle, Wendy L.; Caulfield, Mark J.; Munroe, Patricia B.; Grönberg, Henrik; Chen, Yii-Der Ida; Li, Guo; Beckmann, Jacques S.; Johnson, Toby; Thorsteinsdottir, Unnur; Teder-Laving, Maris; Khaw, Kay-Tee; Wareham, Nicholas J.; Zhao, Jing Hua; Amin, Najaf; Oostra, Ben A.; Kraja, Aldi T.; Province, Michael A.; Cupples, L. Adrienne; Heard-Costa, Nancy L.; Kaprio, Jaakko; Ripatti, Samuli; Surakka, Ida; Collins, Francis S.; Saramies, Jouko; Tuomilehto, Jaakko; Jula, Antti; Salomaa, Veikko; Erdmann, Jeanette; Hengstenberg, Christian; Loley, Christina; Schunkert, Heribert; Lamina, Claudia; Wichmann, H. Erich; Albrecht, Eva; Gieger, Christian; Hicks, Andrew A.; Johansson, Åsa; Pramstaller, Peter P.; Kathiresan, Sekar; Speliotes, Elizabeth K.; Penninx, Brenda; Hartikainen, Anna-Liisa; Jarvelin, Marjo-Riitta; Gyllensten, Ulf; Boomsma, Dorret I.; Campbell, Harry; Wilson, James F.; Chanock, Stephen J.; Farrall, Martin; Goel, Anuj; Medina-Gomez, Carolina; Rivadeneira, Fernando; Estrada, Karol; Uitterlinden, André G.; Hofman, Albert; Zillikens, M. Carola; den Heijer, Martin; Kiemeney, Lambertus A.; Maschio, Andrea; Hall, Per; Tyrer, Jonathan; Teumer, Alexander; Völzke, Henry; Kovacs, Peter; Tönjes, Anke; Mangino, Massimo; Spector, Tim D.; Hayward, Caroline; Rudan, Igor; Hall, Alistair S.; Samani, Nilesh J.; Attwood, Antony Paul; Sambrook, Jennifer G.; Hung, Joseph; Palmer, Lyle J.; Lokki, Marja-Liisa; Sinisalo, Juha; Boucher, Gabrielle; Huikuri, Heikki; Lorentzon, Mattias; Ohlsson, Claes; Eklund, Niina; Eriksson, Johan G.; Barlassina, Cristina; Rivolta, Carlo; Nolte, Ilja M.; Snieder, Harold; Van der Klauw, Melanie M.; Van Vliet-Ostaptchouk, Jana V.; Gejman, Pablo V.; Shi, Jianxin; Jacobs, Kevin B.; Wang, Zhaoming; Bakker, Stephan J. L.; Mateo Leach, Irene; Navis, Gerjan; van der Harst, Pim; Martin, Nicholas G.; Medland, Sarah E.; Montgomery, Grant W.; Yang, Jian; Chasman, Daniel I.; Ridker, Paul M.; Rose, Lynda M.; Lehtimäki, Terho; Raitakari, Olli; Absher, Devin; Iribarren, Carlos; Basart, Hanneke; Hovingh, Kees G.; Hyppönen, Elina; Power, Chris; Anderson, Denise; Beilby, John P.; Hui, Jennie; Jolley, Jennifer; Sager, Hendrik; Bornstein, Stefan R.; Schwarz, Peter E. H.; Kristiansson, Kati; Perola, Markus; Lindström, Jaana; Swift, Amy J.; Uusitupa, Matti; Atalay, Mustafa; Lakka, Timo A.; Rauramaa, Rainer; Bolton, Jennifer L.; Fowkes, Gerry; Fraser, Ross M.; Price, Jackie F.; Fischer, Krista; KrjutÅ¡kov, Kaarel; Metspalu, Andres; Mihailov, Evelin; Langenberg, Claudia; Luan, Jian'an; Ong, Ken K.; Chines, Peter S.; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Edkins, Sarah; Franks, Paul W.; Hallmans, Göran; Shungin, Dmitry; Morris, Andrew David; Palmer, Colin N. A.; Erbel, Raimund; Moebus, Susanne; Nöthen, Markus M.; Pechlivanis, Sonali; Hveem, Kristian; Narisu, Narisu; Hamsten, Anders; Humphries, Steve E.; Strawbridge, Rona J.; Tremoli, Elena; Grallert, Harald; Thorand, Barbara; Illig, Thomas; Koenig, Wolfgang; Müller-Nurasyid, Martina; Peters, Annette; Boehm, Bernhard O.; Kleber, Marcus E.; März, Winfried; Winkelmann, Bernhard R.; Kuusisto, Johanna; Laakso, Markku; Arveiler, Dominique; Cesana, Giancarlo; Kuulasmaa, Kari; Virtamo, Jarmo; Yarnell, John W. G.; Kuh, Diana; Wong, Andrew; Lind, Lars; de Faire, Ulf; Gigante, Bruna; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Dedoussis, George; Dimitriou, Maria; Kolovou, Genovefa; Kanoni, Stavroula; Stirrups, Kathleen; Bonnycastle, Lori L.; Njølstad, Inger; Wilsgaard, Tom; Ganna, Andrea; Rehnberg, Emil; Hingorani, Aroon; Kivimaki, Mika; Kumari, Meena; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunians, Talin; Hunter, David; Ingelsson, Erik; Kaplan, Robert; Mohlke, Karen L.; O'Connell, Jeffrey R.; Schlessinger, David; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Abecasis, Gonçalo R.; McCarthy, Mark I.; Hirschhorn, Joel N.; Qi, Lu; Loos, Ruth J. F.; Lindgren, Cecilia M.; North, Kari E.; Heid, Iris M.

    2013-01-01

    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. PMID:23754948

  2. 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.

  3. Association and Genetic Identification of Loci for Four Fruit Traits in Tomato Using InDel Markers

    Directory of Open Access Journals (Sweden)

    Xiaoxi Liu

    2017-07-01

    Full Text Available Tomato (Solanum lycopersicum fruit weight (FW, soluble solid content (SSC, fruit shape and fruit color are crucial for yield, quality and consumer acceptability. In this study, a 192 accessions tomato association panel comprising a mixture of wild species, cherry tomato, landraces, and modern varieties collected worldwide was genotyped with 547 InDel markers evenly distributed on 12 chromosomes and scored for FW, SSC, fruit shape index (FSI, and color parameters over 2 years with three replications each year. The association panel was sorted into two subpopulations. Linkage disequilibrium ranged from 3.0 to 47.2 Mb across 12 chromosomes. A set of 102 markers significantly (p < 1.19–1.30 × 10−4 associated with SSC, FW, fruit shape, and fruit color was identified on 11 of the 12 chromosomes using a mixed linear model. The associations were compared with the known gene/QTLs for the same traits. Genetic analysis using F2 populations detected 14 and 4 markers significantly (p < 0.05 associated with SSC and FW, respectively. Some loci were commonly detected by both association and linkage analysis. Particularly, one novel locus for FW on chromosome 4 detected by association analysis was also identified in F2 populations. The results demonstrated that association mapping using limited number of InDel markers and a relatively small population could not only complement and enhance previous QTL information, but also identify novel loci for marker-assisted selection of fruit traits in tomato.

  4. Identification of Quantitative Trait Loci for Resistance to RSIVD in Red Sea Bream (Pagrus major).

    Science.gov (United States)

    Sawayama, Eitaro; Tanizawa, Shiho; Kitamura, Shin-Ichi; Nakayama, Kei; Ohta, Kohei; Ozaki, Akiyuki; Takagi, Motohiro

    2017-12-01

    Red sea bream iridoviral disease (RSIVD) is a major viral disease in red sea bream farming in Japan. Previously, we identified one candidate male individual of red sea bream that was significantly associated with convalescent individuals after RSIVD. The purpose of this study is to identify the quantitative trait loci (QTL) linked to the RSIVD-resistant trait for future marker-assisted selection (MAS). Two test families were developed using the candidate male in 2014 (Fam-2014) and 2015 (Fam-2015). These test families were challenged with RSIV, and phenotypes were evaluated. Then, de novo genome sequences of red sea bream were obtained through next-generation sequencing, and microsatellite markers were searched and selected for linkage map construction. One immune-related gene, MHC class IIβ, was also used for linkage map construction. Of the microsatellite markers searched, 148 and 197 were mapped on 23 and 27 linkage groups in the female and male linkage maps, respectively, covering approximately 65% of genomes in both sexes. One QTL linked to an RSIVD-resistant trait was found in linkage group 2 of the candidate male in Fam-2014, and the phenotypic variance of the QTL was 31.1%. The QTL was closely linked to MHC class IIβ. Moreover, the QTL observed in Fam-2014 was also significantly linked to an RSIVD-resistant trait in the candidate male of Fam-2015. Our results suggest that the RSIVD-resistant trait in the candidate male was controlled by one major QTL closely linked to the MHC class IIβ gene and could be useful for MAS of red sea bream.

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

    OpenAIRE

    Dastani, Z.; Hivert, M. F.; Timpson, N.; Perry, J. R.; Yuan, X.; Scott, R. A.; Henneman, P.; Heid, I. M.; Kizer, J. R.; Lyytikäinen, L. P.; Fuchsberger, C.; Tanaka, T.; Morris, A. P.; Small, K.; Isaacs, A.

    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...

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

    OpenAIRE

    Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas; Perry, John Richard; Yuan, Xin; Scott, Robert; Henneman, Peter; Heid, Iris M; Kizer, Jorge R; Lyytikäinen, Leo-Pekka; Fuchsberger, Christian; Tanaka, Toshiko; Morris, Andrew P; Small, Kerrin; Isaacs, Aaron

    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}\\)). U...

  7. Association Mapping of Malting Quality Quantitative Trait Loci in Winter Barley: Positive Signals from Small Germplasm Arrays

    Directory of Open Access Journals (Sweden)

    Lucía Gutiérrez

    2011-11-01

    Full Text Available Malting quality comprises one of the most economically relevant set of traits in barley ( L.. It is a complex phenotype, expensive and difficult to measure, that would benefit from a marker-assisted selection strategy. Malting quality is a target of the U.S. Barley Coordinated Agricultural Project (CAP and development of winter habit malting barley varieties is a key objective of the U.S. barley research community. The objective of this work was to detect quantitative trait loci (QTL for malting quality traits in a winter breeding program that is a component of the U.S. Barley CAP. We studied the association between five malting quality traits and 3072 single nucleotide polymorphisms (SNPs from the barley oligonucleotide pool assay (BOPA 1 and 2, assayed in advanced inbred lines from the Oregon State University (OSU breeding program from three germplasm arrays (CAP I, CAP II, and CAP III. After comparing 16 models we selected a structured association model with posterior probabilities inferred from software STRUCTURE (QK approach to use on all germplasm arrays. Most of the marker-trait associations are germplasm- and environment-specific and close to previously mapped genes and QTL relevant for malt and beer quality. We found alleles fixed by random genetic drift, novel unmasked alleles, and genetic-background interaction. In a relatively small population size study we provide strong evidence for detecting true QTL.

  8. 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.

  9. Whole-genome modeling accurately predicts quantitative traits, as revealed in plants.

    OpenAIRE

    Tatarinova, Tatiana; Shin, Min-Gyoung; Marjoram, Paul; Nuzhdin, Sergey; Triska, Martin; Rickauer, Martina; Nikolsky, Yuri; Mazurier, Melanie; Gentzbittel, Laurent; Ben, Cecile

    2016-01-01

    Many adaptive events in natural populations, as well as response to artificial selection, are caused by polygenic action. Under selective pressure, the adaptive traits can quickly respond via small allele frequency shifts spread across numerous loci. We hypothesize that a large proportion of current phenotypic variation between individuals may be best explained by population admixture. We thus consider the complete, genome-wide universe of genetic variability, spread across several ancestral ...

  10. Plants with useful traits and related methods

    Science.gov (United States)

    Mackenzie, Sally Ann; De la Rosa Santamaria, Roberto

    2016-10-25

    The present invention provides methods for obtaining plants that exhibit useful traits by transient suppression of the MSH1 gene of the plants. Methods for identifying genetic loci that provide for useful traits in plants and plants produced with those loci are also provided. In addition, plants that exhibit the useful traits, parts of the plants including seeds, and products of the plants are provided as well as methods of using the plants.

  11. Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

    Science.gov (United States)

    Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

    2009-12-01

    Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

  12. Plant functional traits predict green roof ecosystem services.

    Science.gov (United States)

    Lundholm, Jeremy; Tran, Stephanie; Gebert, Luke

    2015-02-17

    Plants make important contributions to the services provided by engineered ecosystems such as green roofs. Ecologists use plant species traits as generic predictors of geographical distribution, interactions with other species, and ecosystem functioning, but this approach has been little used to optimize engineered ecosystems. Four plant species traits (height, individual leaf area, specific leaf area, and leaf dry matter content) were evaluated as predictors of ecosystem properties and services in a modular green roof system planted with 21 species. Six indicators of ecosystem services, incorporating thermal, hydrological, water quality, and carbon sequestration functions, were predicted by the four plant traits directly or indirectly via their effects on aggregate ecosystem properties, including canopy density and albedo. Species average height and specific leaf area were the most useful traits, predicting several services via effects on canopy density or growth rate. This study demonstrates that easily measured plant traits can be used to select species to optimize green roof performance across multiple key services.

  13. Two developmentally temporal quantitative trait loci underlie convergent evolution of increased branchial bone length in sticklebacks

    Science.gov (United States)

    Erickson, Priscilla A.; Glazer, Andrew M.; Cleves, Phillip A.; Smith, Alyson S.; Miller, Craig T.

    2014-01-01

    In convergent evolution, similar phenotypes evolve repeatedly in independent populations, often reflecting adaptation to similar environments. Understanding whether convergent evolution proceeds via similar or different genetic and developmental mechanisms offers insight towards the repeatability and predictability of evolution. Oceanic populations of threespine stickleback fish, Gasterosteus aculeatus, have repeatedly colonized countless freshwater lakes and streams, where new diets lead to morphological adaptations related to feeding. Here, we show that heritable increases in branchial bone length have convergently evolved in two independently derived freshwater stickleback populations. In both populations, an increased bone growth rate in juveniles underlies the convergent adult phenotype, and one population also has a longer cartilage template. Using F2 crosses from these two freshwater populations, we show that two quantitative trait loci (QTL) control branchial bone length at distinct points in development. In both populations, a QTL on chromosome 21 controls bone length throughout juvenile development, and a QTL on chromosome 4 controls bone length only in adults. In addition to these similar developmental profiles, these QTL show similar chromosomal locations in both populations. Our results suggest that sticklebacks have convergently evolved longer branchial bones using similar genetic and developmental programmes in two independently derived populations. PMID:24966315

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

    DEFF Research Database (Denmark)

    Drag, Markus; Hansen, Mathias B.; Kadarmideen, Haja N.

    2018-01-01

    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 similar to 100 kg. Gene...... 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...

  15. Empirical and deterministic accuracies of across-population genomic prediction

    NARCIS (Netherlands)

    Wientjes, Y.C.J.; Veerkamp, R.F.; Bijma, P.; Bovenhuis, H.; Schrooten, C.; Calus, M.P.L.

    2015-01-01

    Background: Differences in linkage disequilibrium and in allele substitution effects of QTL (quantitative trait loci) may hinder genomic prediction across populations. Our objective was to develop a deterministic formula to estimate the accuracy of across-population genomic prediction, for which

  16. 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.

  17. Biological, clinical and population relevance of 95 loci for blood lipids

    DEFF Research Database (Denmark)

    Teslovich, Tanya M; Musunuru, Kiran; Smith, Albert V

    2010-01-01

    polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits...... in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken...

  18. Genome-Wide Association Study Identifies Two Novel Loci with Sex-Specific Effects for Type 2 Diabetes Mellitus and Glycemic Traits in a Korean Population

    Directory of Open Access Journals (Sweden)

    Min Jin Go

    2014-10-01

    Full Text Available BackgroundUntil recently, genome-wide association study (GWAS-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population.MethodsWe performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842. The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500. A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively.ResultsA combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356 loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study.ConclusionOur study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

  19. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

    Science.gov (United States)

    Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

    2017-08-24

    Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

  20. Exploring alternative models for sex-linked quantitative trait loci in outbred populations: application to an iberian x landrace pig intercross.

    OpenAIRE

    Pérez-Enciso, Miguel; Clop, Alex; Folch, Josep M; Sánchez, Armand; Oliver, Maria A; Ovilo, Cristina; Barragán, C; Varona, Luis; Noguera, José L

    2002-01-01

    We present a very flexible method that allows us to analyze X-linked quantitative trait loci (QTL) in crosses between outbred lines. The dosage compensation phenomenon is modeled explicitly in an identity-by-descent approach. A variety of models can be fitted, ranging from considering alternative fixed alleles within the founder breeds to a model where the only genetic variation is within breeds, as well as mixed models. Different genetic variances within each founder breed can be estimated. ...

  1. Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

    Science.gov (United States)

    Jia, Yi; Jannink, Jean-Luc

    2012-01-01

    Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

  2. 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...

  3. Automatic prediction of facial trait judgments: appearance vs. structural models.

    Directory of Open Access Journals (Sweden)

    Mario Rojas

    Full Text Available Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a derive a facial trait judgment model from training data and b predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations and classification rules (4 rules suggest that a prediction of perception of facial traits is learnable by both holistic and structural approaches; b the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

  4. Genetic Diversity and Elite Allele Mining for Grain Traits in Rice (Oryza sativa L.) by Association Mapping.

    Science.gov (United States)

    Edzesi, Wisdom M; Dang, Xiaojing; Liang, Lijun; Liu, Erbao; Zaid, Imdad U; Hong, Delin

    2016-01-01

    Mining elite alleles for grain size and weight is of importance for the improvement of cultivated rice and selection for market demand. In this study, association mapping for grain traits was performed on a selected sample of 628 rice cultivars using 262 SSRs. Grain traits were evaluated by grain length (GL), grain width (GW), grain thickness (GT), grain length to width ratio (GL/GW), and 1000-grain weight (TGW) in 2013 and 2014. Our result showed abundant phenotypic and genetic diversities found in the studied population. In total, 2953 alleles were detected with an average of 11.3 alleles per locus. The population was divided into seven subpopulations and the levels of linkage disequilibrium (LD) ranged from 34 to 84 cM. Genome-wide association mapping detected 10 marker trait association (MTAs) loci for GL, 1MTAs locus for GW, 7 MTAs loci for GT, 3 MTAs loci for GL/GW, and 1 MTAs locus for TGW. Twenty-nine, 2, 10, 5, and 3 elite alleles were found for the GL, GW, GT, GL/GW, and TGW, respectively. Optimal cross designs were predicted for improving the target traits. The accessions containing elite alleles for grain traits mined in this study could be used for breeding rice cultivars and cloning the candidate genes.

  5. 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.

  6. A family-based joint test for mean and variance heterogeneity for quantitative traits.

    Science.gov (United States)

    Cao, Ying; Maxwell, Taylor J; Wei, Peng

    2015-01-01

    Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.

  7. Predicting personality traits related to consumer behavior using SNS analysis

    Science.gov (United States)

    Baik, Jongbum; Lee, Kangbok; Lee, Soowon; Kim, Yongbum; Choi, Jayoung

    2016-07-01

    Modeling a user profile is one of the important factors for devising a personalized recommendation. The traditional approach for modeling a user profile in computer science is to collect and generalize the user's buying behavior or preference history, generated from the user's interactions with recommender systems. According to consumer behavior research, however, internal factors such as personality traits influence a consumer's buying behavior. Existing studies have tried to adapt the Big 5 personality traits to personalized recommendations. However, although studies have shown that these traits can be useful to some extent for personalized recommendation, the causal relationship between the Big 5 personality traits and the buying behaviors of actual consumers has not been validated. In this paper, we propose a novel method for predicting the four personality traits-Extroversion, Public Self-consciousness, Desire for Uniqueness, and Self-esteem-that correlate with buying behaviors. The proposed method automatically constructs a user-personality-traits prediction model for each user by analyzing the user behavior on a social networking service. The experimental results from an analysis of the collected Facebook data show that the proposed method can predict user-personality traits with greater precision than methods that use the variables proposed in previous studies.

  8. A journey from a SSR-based low density map to a SNP-based high density map for identification of disease resistance quantitative trait loci in peanut

    Science.gov (United States)

    Mapping and identification of quantitative trait loci (QTLs) are important for efficient marker-assisted breeding. Diseases such as leaf spots and Tomato spotted wilt virus (TSWV) cause significant loses to peanut growers. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to...

  9. 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.

  10. Phylogeny and species traits predict bird detectability

    Science.gov (United States)

    Solymos, Peter; Matsuoka, Steven M.; Stralberg, Diana; Barker, Nicole K. S.; Bayne, Erin M.

    2018-01-01

    Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.

  11. A three-component system incorporating Ppd-D1, copy number variation at Ppd-B1, and numerous small-effect quantitative trait loci facilitates adaptation of heading time in winter wheat cultivars of worldwide origin.

    Science.gov (United States)

    Würschum, Tobias; Langer, Simon M; Longin, C Friedrich H; Tucker, Matthew R; Leiser, Willmar L

    2018-06-01

    The broad adaptability of heading time has contributed to the global success of wheat in a diverse array of climatic conditions. Here, we investigated the genetic architecture underlying heading time in a large panel of 1,110 winter wheat cultivars of worldwide origin. Genome-wide association mapping, in combination with the analysis of major phenology loci, revealed a three-component system that facilitates the adaptation of heading time in winter wheat. The photoperiod sensitivity locus Ppd-D1 was found to account for almost half of the genotypic variance in this panel and can advance or delay heading by many days. In addition, copy number variation at Ppd-B1 was the second most important source of variation in heading, explaining 8.3% of the genotypic variance. Results from association mapping and genomic prediction indicated that the remaining variation is attributed to numerous small-effect quantitative trait loci that facilitate fine-tuning of heading to the local climatic conditions. Collectively, our results underpin the importance of the two Ppd-1 loci for the adaptation of heading time in winter wheat and illustrate how the three components have been exploited for wheat breeding globally. © 2018 John Wiley & Sons Ltd.

  12. Genetic and Physiological Characterization of Two Clusters of Quantitative Trait Loci Associated With Seed Dormancy and Plant Height in Rice

    OpenAIRE

    Ye, Heng; Beighley, Donn H.; Feng, Jiuhuan; Gu, Xing-You

    2013-01-01

    Seed dormancy and plant height have been well-studied in plant genetics, but their relatedness and shared regulatory mechanisms in natural variants remain unclear. The introgression of chromosomal segments from weedy into cultivated rice (Oryza sativa) prompted the detection of two clusters (qSD1-2/qPH1 and qSD7-2/qPH7) of quantitative trait loci both associated with seed dormancy and plant height. Together, these two clusters accounted for >96% of the variances for plant height and ~71% of t...

  13. Quantitative trait loci mapping for stomatal traits in interspecific ...

    Indian Academy of Sciences (India)

    Dr.YASODHA

    seedling raising, field planting and maintenance of the mapping population. ... tereticornis and production of interspecific hybrids displaying hybrid vigour in terms of .... A total of 114, 115 and 129 SSR, ISSR and SRAP markers were generated .... stomatal traits with yield and adaptability would help to improve productivity of ...

  14. Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

    Science.gov (United States)

    He, Dan; Kuhn, David; Parida, Laxmi

    2016-06-15

    Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

  15. 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

  16. 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

  17. Predicting early academic achievement: The role of higher-versus lower-order personality traits

    Directory of Open Access Journals (Sweden)

    Zupančič Maja

    2011-01-01

    Full Text Available The study explored the role of children’s (N = 193 individual differences and parental characteristics at the beginning of the first year of schooling in predicting students’ attainment of academic standards at the end of the year. Special attention was paid to children’s personality as perceived by the teachers’ assistants. Along with parents’ education, parenting practices and first-graders’ cognitive ability, the incremental predictive power of children’s higher-order (robust personality traits was compared to the contribution of lower-order (specific traits in explaining academic achievement. The specific traits provided a somewhat more accurate prediction than the robust traits. Unique contributions of maternal authoritative parenting, children’s cognitive ability, and personality to academic achievement were established. The ratings of first-graders’ conscientiousness (a higher-order trait improved the prediction of academic achievement based on parenting and cognitive ability by 12%, whereas assistant teacher’s perceived children’s intelligence and low antagonism (lower-order traits improved the prediction by 17%.

  18. 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).

  19. Uncovering the genetic landscape for multiple sleep-wake traits.

    Directory of Open Access Journals (Sweden)

    Christopher J Winrow

    Full Text Available Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28 QTL affected a particular sleep-wake trait (e.g., amount of wake across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts, as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency. Construction of a Bayesian network for sleep-wake traits and loci led to the identification of sub-networks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits

  20. 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.

  1. A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

    Directory of Open Access Journals (Sweden)

    Hayashi Takeshi

    2013-01-01

    Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero

  2. Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize.

    Directory of Open Access Journals (Sweden)

    Lu Jiang

    Full Text Available Kernel shape related traits (KSRTs have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL and kernel width (KW lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17, 82 intermated B73 × Mo17 (IBM individuals, and the corresponding triple testcross (TTC populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL for six KSRTs: KL, KW, length to width ratio (LWR, perimeter length (PL, kernel area (KA, and circularity (CS. The results showed that the mid-parent heterosis (MPH for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson's R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW. 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total R2 for KW (78.8%, and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total R2 (55.3%. Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.

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

    Science.gov (United States)

    2011-01-01

    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 observed for this trait in

  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. Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

    Science.gov (United States)

    Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

    2017-03-01

    Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

  6. Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

    Science.gov (United States)

    Amare, Azmeraw T.; Schubert, Klaus Oliver; Tekola-Ayele, Fasil; Hsu, Yi-Hsiang; Sangkuhl, Katrin; Jenkins, Gregory; Whaley, Ryan M.; Barman, Poulami; Batzler, Anthony; Altman, Russ B.; Arolt, Volker; Brockmöller, Jürgen; Chen, Chia-Hui; Domschke, Katharina; Hall-Flavin, Daniel K.; Hong, Chen-Jee; Illi, Ari; Ji, Yuan; Kampman, Olli; Kinoshita, Toshihiko; Leinonen, Esa; Liou, Ying-Jay; Mushiroda, Taisei; Nonen, Shinpei; Skime, Michelle K.; Wang, Liewei; Kato, Masaki; Liu, Yu-Li; Praphanphoj, Verayuth; Stingl, Julia C.; Bobo, William V.; Tsai, Shih-Jen; Kubo, Michiaki; Klein, Teri E.; Weinshilboum, Richard M.; Biernacka, Joanna M.; Baune, Bernhard T.

    2018-01-01

    Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs. PMID:29559929

  7. Narcissism and Callous-Unemotional Traits Prospectively Predict Child Conduct Problems.

    Science.gov (United States)

    Jezior, Kristen L; McKenzie, Meghan E; Lee, Steve S

    2016-01-01

    Although narcissism and callous-unemotional (CU) traits are separable facets of psychopathy, their independent prediction of conduct problems (CP) among young children is not well known. In addition, above-average IQ was central to the original conceptualization of psychopathy, yet IQ is typically inversely associated with youth CP. We examined narcissism and CU traits as independent and prospective predictors of oppositional defiant disorder (ODD), conduct disorder (CD), and youth self-reported antisocial behavior, as well as their moderation by IQ. At baseline, parents and teachers separately rated narcissism and CU traits in 188 6-to-10-year-old children (47.9% non-White; 69.1% male; M = 7.34 years, SD = 1.09) with (n = 99) and without (n = 89) attention-deficit/hyperactivity disorder (ADHD). Approximately 2 years later, parents and teachers separately rated youth ODD and CD symptoms, and youth self-reported antisocial behavior. With control of baseline ADHD and ODD/CD symptoms, narcissism and CU traits independently and positively predicted ODD and CD symptoms at follow-up. IQ did not moderate any CP predictions from baseline narcissism or CU traits. These preliminary findings suggest that individual differences in narcissism and CU traits, even relatively early in development, are uniquely associated with emergent CP. Findings are considered within a developmental framework and the multiple pathways underlying the heterogeneity of CP are discussed.

  8. Predicting College Students' Positive Psychology Associated Traits with Executive Functioning Dimensions

    Science.gov (United States)

    Marshall, Seth

    2016-01-01

    More research is needed that investigates how positive psychology-associated traits are predicted by neurocognitive processes. Correspondingly, the purpose of this study was to ascertain how, and to what extent, four traits, namely, grit, optimism, positive affect, and life satisfaction were predicted by the executive functioning (EF) dimensions…

  9. 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.

  10. Psychopathic Traits and Moral Disengagement Interact to Predict Bullying and Cyberbullying Among Adolescents.

    Science.gov (United States)

    Orue, Izaskun; Calvete, Esther

    2016-07-01

    The aim of this study was to test a model in which psychopathic traits (callous-unemotional, grandiose-manipulative, and impulsive-irresponsible) and moral disengagement individually and interactively predict two types of bullying (traditional and cyberbullying) in a community sample of adolescents. A total of 765 adolescents (464 girls and 301 boys) completed measures of moral disengagement and psychopathic traits at Time 1, and measures of bullying and cyberbullying at Time 1 and 1 year later, at Time 2. The results showed that callous-unemotional traits predicted both traditional bullying and cyberbullying, grandiose-manipulative and impulsive-irresponsible traits only predicted traditional bullying, and moral disengagement only predicted cyberbullying. Callous-Unemotional Traits × Moral Disengagement and Grandiose-Manipulative × Moral Disengagement were significantly correlated with the residual change in cyberbullying. Callous-unemotional traits were positively related to cyberbullying at high levels of moral disengagement but not when moral disengagement was low. In contrast, grandiose-manipulative traits were positively related to cyberbullying at low levels of moral disengagement but not when moral disengagement was high. These findings have implications for both prevention and intervention. Integrative approaches that promote moral growth are needed, including a deeper understanding of why bullying is morally wrong and ways to stimulate personality traits that counteract psychopathic traits.

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

    Indian Academy of Sciences (India)

    QIANG YI

    2018-03-15

    Mar 15, 2018 ... in maize have evaluated flowering-related traits (Li et al. ... with Upadyayula et al. (2006). The measurements taken were TTL, the length (cm) of the tassel ...... M. Banziger, H. R. Mickelson and C. B. Penã–Valdivia), pp.

  12. Can personality traits predict increases in manic and depressive symptoms?

    Science.gov (United States)

    Lozano, B E; Johnson, S L

    2001-03-01

    There has been limited research investigating personality traits as predictors of manic and depressive symptoms in bipolar individuals. The present study investigated the relation between personality traits and the course of bipolar disorder. The purpose of this study was to identify specific personality traits that predict the course of manic and depressive symptoms experienced by bipolar individuals. The sample consisted of 39 participants with bipolar I disorder assessed by the Structured Clinical Interview for DSM-IV. Personality was assessed using the NEO Five-Factor Inventory. The Modified Hamilton Rating Scale for Depression and the Bech-Rafaelsen Mania Rating Scale were used to assess symptom severity on a monthly basis. Consistent with previous research on unipolar depression, high Neuroticism predicted increases in depressive symptoms across time while controlling for baseline symptoms. Additionally, high Conscientiousness, particularly the Achievement Striving facet, predicted increases in manic symptoms across time. The current study was limited by the small number of participants, the reliance on a shortened version of a self-report personality measure, and the potential state-dependency of the personality measures. Specific personality traits may assist in predicting bipolar symptoms across time. Further studies are needed to tease apart the state-dependency of personality.

  13. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding.

    Science.gov (United States)

    Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

    2017-01-01

    Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

  14. Prediction of Performance Facets using Specific Personality Traits in the Chinese Context.

    Science.gov (United States)

    Kwong, Jessica Y. Y.; Cheung, Fanny M.

    2003-01-01

    Data from the Chinese Personality Assessment Inventory for 187 Hong Kong supervisors showed that personality traits related to interpersonal orientation better predicted interpersonal versus personal contextual behaviors. Traits associated with moral obligation and group loyalty predicted personal but not interpersonal contextual behaviors.…

  15. 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

  16. Detection of quantitative trait loci for carcass composition traits in pigs

    Directory of Open Access Journals (Sweden)

    Renard Christine

    2002-11-01

    Full Text Available Abstract A quantitative trait locus (QTL analysis of carcass composition data from a three-generation experimental cross between Meishan (MS and Large White (LW pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.

  17. 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.

  18. 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

    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...... for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across...... 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...

  19. 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.

  20. Can Leaf Spectroscopy Predict Leaf and Forest Traits Along a Peruvian Tropical Forest Elevation Gradient?

    Science.gov (United States)

    Doughty, Christopher E.; Santos-Andrade, P. E.; Goldsmith, G. R.; Blonder, B.; Shenkin, A.; Bentley, L. P.; Chavana-Bryant, C.; Huaraca-Huasco, W.; Díaz, S.; Salinas, N.; Enquist, B. J.; Martin, R.; Asner, G. P.; Malhi, Y.

    2017-11-01

    High-resolution spectroscopy can be used to measure leaf chemical and structural traits. Such leaf traits are often highly correlated to other traits, such as photosynthesis, through the leaf economics spectrum. We measured VNIR (visible-near infrared) leaf reflectance (400-1,075 nm) of sunlit and shaded leaves in 150 dominant species across ten, 1 ha plots along a 3,300 m elevation gradient in Peru (on 4,284 individual leaves). We used partial least squares (PLS) regression to compare leaf reflectance to chemical traits, such as nitrogen and phosphorus, structural traits, including leaf mass per area (LMA), branch wood density and leaf venation, and "higher-level" traits such as leaf photosynthetic capacity, leaf water repellency, and woody growth rates. Empirical models using leaf reflectance predicted leaf N and LMA (r2 > 30% and %RMSE < 30%), weakly predicted leaf venation, photosynthesis, and branch density (r2 between 10 and 35% and %RMSE between 10% and 65%), and did not predict leaf water repellency or woody growth rates (r2<5%). Prediction of higher-level traits such as photosynthesis and branch density is likely due to these traits correlations with LMA, a trait readily predicted with leaf spectroscopy.

  1. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

    Directory of Open Access Journals (Sweden)

    Yong-Bi Fu

    2017-07-01

    Full Text Available Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

  2. Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

    Science.gov (United States)

    Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

    2017-01-01

    Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

  3. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

    NARCIS (Netherlands)

    Webb, Thomas R.; Erdmann, Jeanette; Stirrups, Kathleen E.; Stitziel, Nathan O.; Masca, Nicholas G. D.; Jansen, Henning; Kanoni, Stavroula; Nelson, Christopher P.; Ferrario, Paola G.; König, Inke R.; Eicher, John D.; Johnson, Andrew D.; Hamby, Stephen E.; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E.; Björkegren, Johan L. M.; Weeke, Peter E.; Auer, Paul L.; Schick, Ursula M.; Lu, Yingchang; Zhang, He; Dube, Marie-Pierre; Goel, Anuj; Farrall, Martin; Peloso, Gina M.; Won, Hong-Hee; Do, Ron; van Iperen, Erik; Kruppa, Jochen; Mahajan, Anubha; Scott, Robert A.; Willenborg, Christina; Braund, Peter S.; van Capelleveen, Julian C.; Doney, Alex S. F.; Donnelly, Louise A.; Asselta, Rosanna; Merlini, Pier A.; Duga, Stefano; Marziliano, Nicola; Denny, Josh C.; Shaffer, Christian; El-Mokhtari, Nour Eddine; Franke, Andre; Heilmann, Stefanie; Hengstenberg, Christian; Hoffmann, Per; Holmen, Oddgeir L.; Hveem, Kristian; Jansson, Jan-Håkan; Jöckel, Karl-Heinz; Kessler, Thorsten; Kriebel, Jennifer; Laugwitz, Karl L.; Marouli, Eirini; Martinelli, Nicola; McCarthy, Mark I.; van Zuydam, Natalie R.; Meisinger, Christa; Esko, Tõnu; Mihailov, Evelin; Escher, Stefan A.; Alver, Maris; Moebus, Susanne; Morris, Andrew D.; Virtamo, Jarma; Nikpay, Majid; Olivieri, Oliviero; Provost, Sylvie; AlQarawi, Alaa; Robertson, Neil R.; Akinsansya, Karen O.; Reilly, Dermot F.; Vogt, Thomas F.; Yin, Wu; Asselbergs, Folkert W.; Kooperberg, Charles; Jackson, Rebecca D.; Stahl, Eli; Müller-Nurasyid, Martina; Strauch, Konstantin; Varga, Tibor V.; Waldenberger, Melanie; Zeng, Lingyao; Chowdhury, Rajiv; Salomaa, Veikko; Ford, Ian; Jukema, J. Wouter; Amouyel, Philippe; Kontto, Jukka; Nordestgaard, Børge G.; Ferrières, Jean; Saleheen, Danish; Sattar, Naveed; Surendran, Praveen; Wagner, Aline; Young, Robin; Howson, Joanna M. M.; Butterworth, Adam S.; Danesh, John; Ardissino, Diego; Bottinger, Erwin P.; Erbel, Raimund; Franks, Paul W.; Girelli, Domenico; Hall, Alistair S.; Hovingh, G. Kees; Kastrati, Adnan; Lieb, Wolfgang; Meitinger, Thomas; Kraus, William E.; Shah, Svati H.; McPherson, Ruth; Orho-Melander, Marju; Melander, Olle; Metspalu, Andres; Palmer, Colin N. A.; Peters, Annette; Rader, Daniel J.; Reilly, Muredach P.; Loos, Ruth J. F.; Reiner, Alex P.; Roden, Dan M.; Tardif, Jean-Claude; Thompson, John R.; Wareham, Nicholas J.; Watkins, Hugh; Willer, Cristen J.; Samani, Nilesh J.; Schunkert, Heribert; Deloukas, Panos; Kathiresan, Sekar

    2017-01-01

    Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. This study sought to systematically test if genetic variants identified for non-CAD

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

    African Journals Online (AJOL)

    User

    2011-05-02

    May 2, 2011 ... character affected by ecological surroundings, growth ... developed from each F2 by bud self-pollination for QTL analysis. ... Quantitative traits measured for the each individual plant in F2 the population and F3 families ..... sex and parental interactions (Liu et al., 1996). ... evolution of solanaceous species.

  5. Genome-enabled predictions for binomial traits in sugar beet populations.

    Science.gov (United States)

    Biscarini, Filippo; Stevanato, Piergiorgio; Broccanello, Chiara; Stella, Alessandra; Saccomani, Massimo

    2014-07-22

    Genomic information can be used to predict not only continuous but also categorical (e.g. binomial) traits. Several traits of interest in human medicine and agriculture present a discrete distribution of phenotypes (e.g. disease status). Root vigor in sugar beet (B. vulgaris) is an example of binomial trait of agronomic importance. In this paper, a panel of 192 SNPs (single nucleotide polymorphisms) was used to genotype 124 sugar beet individual plants from 18 lines, and to classify them as showing "high" or "low" root vigor. A threshold model was used to fit the relationship between binomial root vigor and SNP genotypes, through the matrix of genomic relationships between individuals in a genomic BLUP (G-BLUP) approach. From a 5-fold cross-validation scheme, 500 testing subsets were generated. The estimated average cross-validation error rate was 0.000731 (0.073%). Only 9 out of 12326 test observations (500 replicates for an average test set size of 24.65) were misclassified. The estimated prediction accuracy was quite high. Such accurate predictions may be related to the high estimated heritability for root vigor (0.783) and to the few genes with large effect underlying the trait. Despite the sparse SNP panel, there was sufficient within-scaffold LD where SNPs with large effect on root vigor were located to allow for genome-enabled predictions to work.

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

    African Journals Online (AJOL)

    VANITHA

    2014-02-05

    Feb 5, 2014 ... improvement, plant breeders deal with several qualitative traits. However, the most ... Table 1. Characteristics of parental lines. Character ..... Sunflower, an agronomic crop, adapted to fundamental and applied biotechnology.

  7. 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.

  8. A genetic risk score combining ten psoriasis risk loci improves disease prediction.

    Directory of Open Access Journals (Sweden)

    Haoyan Chen

    2011-04-01

    Full Text Available Psoriasis is a chronic, immune-mediated skin disease affecting 2-3% of Caucasians. Recent genetic association studies have identified multiple psoriasis risk loci; however, most of these loci contribute only modestly to disease risk. In this study, we investigated whether a genetic risk score (GRS combining multiple loci could improve psoriasis prediction. Two approaches were used: a simple risk alleles count (cGRS and a weighted (wGRS approach. Ten psoriasis risk SNPs were genotyped in 2815 case-control samples and 858 family samples. We found that the total number of risk alleles in the cases was significantly higher than in controls, mean 13.16 (SD 1.7 versus 12.09 (SD 1.8, p = 4.577×10(-40. The wGRS captured considerably more risk than any SNP considered alone, with a psoriasis OR for high-low wGRS quartiles of 10.55 (95% CI 7.63-14.57, p = 2.010×10(-65. To compare the discriminatory ability of the GRS models, receiver operating characteristic curves were used to calculate the area under the curve (AUC. The AUC for wGRS was significantly greater than for cGRS (72.0% versus 66.5%, p = 2.13×10(-8. Additionally, the AUC for HLA-C alone (rs10484554 was equivalent to the AUC for all nine other risk loci combined (66.2% versus 63.8%, p = 0.18, highlighting the dominance of HLA-C as a risk locus. Logistic regression revealed that the wGRS was significantly associated with two subphenotypes of psoriasis, age of onset (p = 4.91×10(-6 and family history (p = 0.020. Using a liability threshold model, we estimated that the 10 risk loci account for only 11.6% of the genetic variance in psoriasis. In summary, we found that a GRS combining 10 psoriasis risk loci captured significantly more risk than any individual SNP and was associated with early onset of disease and a positive family history. Notably, only a small fraction of psoriasis heritability is captured by the common risk variants identified to date.

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

    KAUST Repository

    Marondedze, Claudius; Thomas, Ludivine

    2013-01-01

    , 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

  10. Whole Genome Scan to Detect Chromosomal Regions Affecting Multiple Traits in Dairy Cattle

    NARCIS (Netherlands)

    Schrooten, C.; Bink, M.C.A.M.; Bovenhuis, H.

    2004-01-01

    Chromosomal regions affecting multiple traits ( multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait

  11. Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

    NARCIS (Netherlands)

    Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.; Acha, Moshe Ray; Newton-Cheh, Christopher; Pfeufer, Arne; Lyneh, Stacey N.; Olesen, Soren-Peter; Brunak, Soren; Ellinor, Patrick T.; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark J.; Asselbergs, Ikea W.; van der Harst, Pim; Milan, David J.; de Bakker, Paul I. W.; Lage, Kasper; Olsen, Jesper V.

    Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes

  12. 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...

  13. 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

  14. cis-Acting Complex-Trait-Associated lincRNA Expression Correlates with Modulation of Chromosomal Architecture

    Directory of Open Access Journals (Sweden)

    Jennifer Yihong Tan

    2017-02-01

    Full Text Available Summary: Intergenic long noncoding RNAs (lincRNAs are the largest class of transcripts in the human genome. Although many have recently been linked to complex human traits, the underlying mechanisms for most of these transcripts remain undetermined. We investigated the regulatory roles of a high-confidence and reproducible set of 69 trait-relevant lincRNAs (TR-lincRNAs in human lymphoblastoid cells whose biological relevance is supported by their evolutionary conservation during recent human history and genetic interactions with other trait-associated loci. Their enrichment in enhancer-like chromatin signatures, interactions with nearby trait-relevant protein-coding loci, and preferential location at topologically associated domain (TAD boundaries provide evidence that TR-lincRNAs likely regulate proximal trait-relevant gene expression in cis by modulating local chromosomal architecture. This is consistent with the positive and significant correlation found between TR-lincRNA abundance and intra-TAD DNA-DNA contacts. Our results provide insights into the molecular mode of action by which TR-lincRNAs contribute to complex human traits. : Tan et al. identify and characterize 69 human complex trait/disease-associated lincRNAs in LCLs. They show that these loci are often associated with cis-regulation of gene expression and tend to be localized at TAD boundaries, suggesting that these lincRNAs may influence chromosomal architecture. Keywords: intergenic long noncoding RNA, lincRNA, GWAS, expression quantitative trait loci, eQTL, complex trait and disease, enhancer, cis-regulation, topologically associated domains, TAD

  15. Linkage Map Construction and Quantitative Trait Locus Analysis of Agronomic and Fiber Quality Traits in Cotton

    Directory of Open Access Journals (Sweden)

    Michael A. Gore

    2014-03-01

    Full Text Available The superior fiber properties of L. serve as a source of novel variation for improving fiber quality in Upland cotton ( L., but introgression from has been largely unsuccessful due to hybrid breakdown and a lack of genetic and genomic resources. In an effort to overcome these limitations, we constructed a linkage map and conducted a quantitative trait locus (QTL analysis of 10 agronomic and fiber quality traits in a recombinant inbred mapping population derived from a cross between TM-1, an Upland cotton line, and NM24016, an elite line with stabilized introgression from . The linkage map consisted of 429 simple-sequence repeat (SSR and 412 genotyping-by-sequencing (GBS-based single-nucleotide polymorphism (SNP marker loci that covered half of the tetraploid cotton genome. Notably, the 841 marker loci were unevenly distributed among the 26 chromosomes of tetraploid cotton. The 10 traits evaluated on the TM-1 × NM24016 population in a multienvironment trial were highly heritable, and most of the fiber traits showed considerable transgressive variation. Through the QTL analysis, we identified a total of 28 QTLs associated with the 10 traits. Our study provides a novel resource that can be used by breeders and geneticists for the genetic improvement of agronomic and fiber quality traits in Upland cotton.

  16. Determination of gene action for some biometrical traits in Lens ...

    Indian Academy of Sciences (India)

    RESEARCH NOTE. Determination ... limitation of this design is that if the testers do not differ at all loci for ... the traits under study indicating the presence of epistasis for these traits ... Quantitative genetic analysis for yield traits in lentil. Table 1.

  17. A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

    Science.gov (United States)

    Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

    2011-05-01

    Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. 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. de 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

  19. 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; Zhao, Jing Hua; Chen, Constance

    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

  20. Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

    Science.gov (United States)

    Gauguier, Dominique; Behmoaras, Jacques; Argoud, Karène; Wilder, Steven P; Pradines, Christelle; Bihoreau, Marie Thérèse; Osborne-Pellegrin, Mary; Jacob, Marie Paule

    2005-03-01

    Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

  1. Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

    Directory of Open Access Journals (Sweden)

    Azmeraw T. Amare

    2018-03-01

    Full Text Available Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD. Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs. In addition, we performed meta-analyses of genome-wide association studies (GWASs on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529 and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865. The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a SSRIs response and conscientiousness near YEATS4 gene and (b SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.

  2. Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

    DEFF Research Database (Denmark)

    Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.

    2014-01-01

    Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes...... involved in the Mendelian disorder long QT syndrome (LOTS). We integrated the LOTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LOTS protein...... network to filter weak GWAS signals by identifying single-nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy...

  3. Pathogen-specific effects of quantitative trait loci affecting clinical mastitis and somatic cell count in danish holstein cattle

    DEFF Research Database (Denmark)

    Sørensen, Lars Peter; Guldbrandtsen, Bernt; Thomasen, J.R.

    2008-01-01

    The aim of this study was to investigate whether quantitative trait loci (QTL) affecting the risk of clinical mastitis (CM) and QTL affecting somatic cell score (SCS) exhibit pathogen-specific effects on the incidence of mastitis. Bacteriological data on mastitis pathogens were used to investigate...... pathogen specificity of QTL affecting treatments of mastitis in first parity (CM1), second parity (CM2), and third parity (CM3), and QTL affecting SCS. The 5 most common mastitis pathogens in the Danish dairy population were analyzed: Streptococcus dysgalactiae, Escherichia coli, coagulase...... against coagulase-negative staphylococci and Strep. uberis. Our results show that particular mastitis QTL are highly likely to exhibit pathogen-specificity. However, the results should be interpreted carefully because the results are sensitive to the sampling method and method of analysis. Field data were...

  4. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

    NARCIS (Netherlands)

    Webb, Thomas R; Erdmann, Jeanette; Stirrups, Kathleen E; Stitziel, Nathan O; Masca, Nicholas G D; Jansen, Henning; Kanoni, Stavroula; Nelson, Christopher P; Ferrario, Paola G; König, Inke R; Eicher, John D; Johnson, Andrew D; Hamby, Stephen E; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E; Björkegren, Johan L M; Weeke, Peter E; Auer, Paul L; Schick, Ursula M; Lu, Yingchang; Zhang, He; Dube, Marie-Pierre; Goel, Anuj; Farrall, Martin; Peloso, Gina M; Won, Hong-Hee; Do, Ron; van Iperen, Erik; Kruppa, Jochen; Mahajan, Anubha; Scott, Robert A; Willenborg, Christina; Braund, Peter S; van Capelleveen, Julian C; Doney, Alex S F; Donnelly, Louise A; Asselta, Rosanna; Merlini, Pier A; Duga, Stefano; Marziliano, Nicola; Denny, Josh C; Shaffer, Christian; El-Mokhtari, Nour Eddine; Franke, Andre; Heilmann, Stefanie; Hengstenberg, Christian; Hoffmann, Per; Holmen, Oddgeir L; Hveem, Kristian; Jansson, Jan-Håkan; Jöckel, Karl-Heinz; Kessler, Thorsten; Kriebel, Jennifer; Laugwitz, Karl L; Marouli, Eirini; Martinelli, Nicola; McCarthy, Mark I; Van Zuydam, Natalie R; Meisinger, Christa; Esko, Tõnu; Mihailov, Evelin; Escher, Stefan A; Alver, Maris; Moebus, Susanne; Morris, Andrew D; Virtamo, Jarma; Nikpay, Majid; Olivieri, Oliviero; Provost, Sylvie; AlQarawi, Alaa; Robertson, Neil R; Akinsansya, Karen O; Reilly, Dermot F; Vogt, Thomas F; Yin, Wu; Asselbergs, Folkert W; Kooperberg, Charles; Jackson, Rebecca D; Stahl, Eli; Müller-Nurasyid, Martina; Strauch, Konstantin; Varga, Tibor V; Waldenberger, Melanie; Zeng, Lingyao; Chowdhury, Rajiv; Salomaa, Veikko; Ford, Ian; Jukema, J Wouter; Amouyel, Philippe; Kontto, Jukka; Nordestgaard, Børge G; Ferrières, Jean; Saleheen, Danish; Sattar, Naveed; Surendran, Praveen; Wagner, Aline; Young, Robin; Howson, Joanna M M; Butterworth, Adam S; Danesh, John; Ardissino, Diego; Bottinger, Erwin P; Erbel, Raimund; Franks, Paul W; Girelli, Domenico; Hall, Alistair S; Hovingh, G Kees; Kastrati, Adnan; Lieb, Wolfgang; Meitinger, Thomas; Kraus, William E; Shah, Svati H; McPherson, Ruth; Orho-Melander, Marju; Melander, Olle; Metspalu, Andres; Palmer, Colin N A; Peters, Annette; Rader, Daniel J; Reilly, Muredach P; Loos, Ruth J F; Reiner, Alex P; Roden, Dan M; Tardif, Jean-Claude; Thompson, John R; Wareham, Nicholas J; Watkins, Hugh; Willer, Cristen J; Samani, Nilesh J; Schunkert, Heribert; Deloukas, Panos; Kathiresan, Sekar

    2017-01-01

    BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES: This study sought to systematically test if genetic variants

  5. Quantitative trait loci associated with the immune response to a bovine respiratory syncytial virus vaccine.

    Directory of Open Access Journals (Sweden)

    Richard J Leach

    Full Text Available Infectious disease is an important problem for animal breeders, farmers and governments worldwide. One approach to reducing disease is to breed for resistance. This linkage study used a Charolais-Holstein F2 cattle cross population (n = 501 which was genotyped for 165 microsatellite markers (covering all autosomes to search for associations with phenotypes for Bovine Respiratory Syncytial Virus (BRSV specific total-IgG, IgG1 and IgG2 concentrations at several time-points pre- and post-BRSV vaccination. Regions of the bovine genome which influenced the immune response induced by BRSV vaccination were identified, as well as regions associated with the clearance of maternally derived BRSV specific antibodies. Significant positive correlations were detected within traits across time, with negative correlations between the pre- and post-vaccination time points. The whole genome scan identified 27 Quantitative Trait Loci (QTL on 13 autosomes. Many QTL were associated with the Thymus Helper 1 linked IgG2 response, especially at week 2 following vaccination. However the most significant QTL, which reached 5% genome-wide significance, was on BTA 17 for IgG1, also 2 weeks following vaccination. All animals had declining maternally derived BRSV specific antibodies prior to vaccination and the levels of BRSV specific antibody prior to vaccination were found to be under polygenic control with several QTL detected.Heifers from the same population (n = 195 were subsequently immunised with a 40-mer Foot-and-Mouth Disease Virus peptide (FMDV in a previous publication. Several of these QTL associated with the FMDV traits had overlapping peak positions with QTL in the current study, including the QTL on BTA23 which included the bovine Major Histocompatibility Complex (BoLA, and QTL on BTA9 and BTA24, suggesting that the genes underlying these QTL may control responses to multiple antigens. These results lay the groundwork for future investigations to identify the

  6. Integrative analysis of a cross-loci regulation network identifies App as a gene regulating insulin secretion from pancreatic islets.

    Directory of Open Access Journals (Sweden)

    Zhidong Tu

    Full Text Available Complex diseases result from molecular changes induced by multiple genetic factors and the environment. To derive a systems view of how genetic loci interact in the context of tissue-specific molecular networks, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant (B6 and diabetes-susceptible (BTBR mouse strains made genetically obese by the Leptin(ob/ob mutation (Lep(ob. High-density genotypes, diabetes-related clinical traits, and whole-transcriptome expression profiling in five tissues (white adipose, liver, pancreatic islets, hypothalamus, and gastrocnemius muscle were determined for all mice. We performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait. Among five tissues under study, there are extensive protein-protein interactions between genes responding to different loci in adipose and pancreatic islets that potentially jointly participated in the regulation of plasma insulin. We developed a novel ranking scheme based on cross-loci protein-protein network topology and gene expression to assess each gene's potential to regulate plasma insulin. Unique candidate genes were identified in adipose tissue and islets. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose or a membrane-permeant cAMP analog, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes.

  7. 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.

  8. A population genetic interpretation of GWAS findings for human quantitative traits

    Science.gov (United States)

    Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

    2018-01-01

    Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID

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

    Directory of Open Access Journals (Sweden)

    John L Norelli

    Full Text Available 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 (PI613981. 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

  10. 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 ...

  11. Genome-wide prediction of discrete traits using bayesian regressions and machine learning

    Directory of Open Access Journals (Sweden)

    Forni Selma

    2011-02-01

    Full Text Available Abstract Background Genomic selection has gained much attention and the main goal is to increase the predictive accuracy and the genetic gain in livestock using dense marker information. Most methods dealing with the large p (number of covariates small n (number of observations problem have dealt only with continuous traits, but there are many important traits in livestock that are recorded in a discrete fashion (e.g. pregnancy outcome, disease resistance. It is necessary to evaluate alternatives to analyze discrete traits in a genome-wide prediction context. Methods This study shows two threshold versions of Bayesian regressions (Bayes A and Bayesian LASSO and two machine learning algorithms (boosting and random forest to analyze discrete traits in a genome-wide prediction context. These methods were evaluated using simulated and field data to predict yet-to-be observed records. Performances were compared based on the models' predictive ability. Results The simulation showed that machine learning had some advantages over Bayesian regressions when a small number of QTL regulated the trait under pure additivity. However, differences were small and disappeared with a large number of QTL. Bayesian threshold LASSO and boosting achieved the highest accuracies, whereas Random Forest presented the highest classification performance. Random Forest was the most consistent method in detecting resistant and susceptible animals, phi correlation was up to 81% greater than Bayesian regressions. Random Forest outperformed other methods in correctly classifying resistant and susceptible animals in the two pure swine lines evaluated. Boosting and Bayes A were more accurate with crossbred data. Conclusions The results of this study suggest that the best method for genome-wide prediction may depend on the genetic basis of the population analyzed. All methods were less accurate at correctly classifying intermediate animals than extreme animals. Among the different

  12. 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

    . Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching PFTO....... Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown...

  13. 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...... autosome 9. In the present study, we induced experimental E. coli mastitis in Danish HF cows to investigate the effect of 2 E. coli mastitis-associated QTL haplotypes on the cows' disease phenotypes and recovery in early lactation. Thirty-two cows were divided in 2 groups bearing haplotypes with either low...... 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...

  14. Trait Impressions as Heuristics for Predicting Future Behavior.

    Science.gov (United States)

    Newman, Leonard S.

    1996-01-01

    The dispositionist bias manifests itself when behavior is overattributed to dispositions, and when contextual factors are underused when predicting behavior. Psychological processes underlying the former bias have been most thoroughly examined. Three studies support the hypothesis that trait implications of past behavior function as heuristics…

  15. Bilaterally Asymmetric Effects of Quantitative Trait Loci (QTLs): QTLs That Affect Laxity in the Right Versus Left Coxofemoral (Hip) Joints of the Dog (Canis familiaris)

    OpenAIRE

    Chase, Kevin; Lawler, Dennis F.; Adler, Fred R.; Ostrander, Elaine A.; Lark, Karl G.

    2004-01-01

    In dogs hip joint laxity that can lead to degenerative joint disease (DJD) is frequent and heritable, providing a genetic model for some aspects of the human disease. We have used Portuguese water dogs (PWDs) to identify Quantitative trait loci (QTLs) that regulate laxity in the hip joint.A population of 286 PWDs, each characterized by ca. 500 molecular genetic markers, was analyzed for subluxation of the hip joint as measured by the Norberg angle, a quantitative radiographic measure of laxit...

  16. 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

  17. Contribution of Large Region Joint Associations to Complex Traits Genetics

    Science.gov (United States)

    Paré, Guillaume; Asma, Senay; Deng, Wei Q.

    2015-01-01

    A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs. PMID:25856144

  18. Comparison of first quadrant yield loci for Ti--6Al--4V with those predicted by Knoop hardness measurements

    International Nuclear Information System (INIS)

    Amateau, M.F.; Hanna, W.D.

    1975-01-01

    Knoop hardness impressions were used to construct biaxial yield loci in Ti--6A l--4V for a variety of textures. These results were compared with partial yield loci in the first quadrant, determined from flow stress measurements at three stress ratios. In each case, the Knoop hardness technique was not sufficiently sensitive to predict the shape of the yield locus, the largest discrepancy occurring for the most anisotropic sample. (U.S.)

  19. Emotional intelligence predicts peer-rated social competence above and beyond personality traits

    OpenAIRE

    Dorota Szczygieł; Joanna Weber

    2016-01-01

    Background This study investigated the relationship between trait emotional intelligence (EI) and social competences (SC), which determine effective functioning in three types of social situations: intimate situations, situations of social exposure and situations requiring self-assertion. Social competences were assessed using a peer nomination method. It was hypothesized that trait EI predicts SC above and beyond personality traits. Participants and procedure Data were co...

  20. 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.

  1. Predicting chromosomal locations of genetically mapped loci in maize using the Morgan2McClintock Translator.

    Science.gov (United States)

    Lawrence, Carolyn J; Seigfried, Trent E; Bass, Hank W; Anderson, Lorinda K

    2006-03-01

    The Morgan2McClintock Translator permits prediction of meiotic pachytene chromosome map positions from recombination-based linkage data using recombination nodule frequency distributions. Its outputs permit estimation of DNA content between mapped loci and help to create an integrated overview of the maize nuclear genome structure.

  2. Trait-based prediction of extinction risk of small-bodied freshwater fishes.

    Science.gov (United States)

    Kopf, R Keller; Shaw, Casey; Humphries, Paul

    2017-06-01

    Small body size is generally correlated with r-selected life-history traits, including early maturation, short-generation times, and rapid growth rates, that result in high population turnover and a reduced risk of extinction. Unlike other classes of vertebrates, however, small freshwater fishes appear to have an equal or greater risk of extinction than large fishes. We explored whether particular traits explain the International Union for Conservation of Nature (IUCN) Red List conservation status of small-bodied freshwater fishes from 4 temperate river basins: Murray-Darling, Australia; Danube, Europe; Mississippi-Missouri, North America; and the Rio Grande, North America. Twenty-three ecological and life-history traits were collated for all 171 freshwater fishes of ≤120 mm total length. We used generalized linear mixed-effects models to assess which combination of the 23 traits best explained whether a species was threatened or not threatened. We used the best models to predict the probability of 29 unclassified species being listed as threatened. With and without controlling for phylogeny at the family level, small body size-among small-bodied species-was the most influential trait correlated with threatened species listings. The k-folds cross-validation demonstrated that body size and a random effect structure that included family predicted the threat status with an accuracy of 78% (SE 0.5). We identified 10 species likely to be threatened that are not listed as such on the IUCN Red List. Small body size is not a trait that provides universal resistance to extinction, particularly for vertebrates inhabiting environments affected by extreme habitat loss and fragmentation. We hypothesize that this is because small-bodied species have smaller home ranges, lower dispersal capabilities, and heightened ecological specialization relative to larger vertebrates. Trait data and further model development are needed to predict the IUCN conservation status of the over 11

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Low trait self-control predicts self-handicapping.

    Science.gov (United States)

    Uysal, Ahmet; Knee, C Raymond

    2012-02-01

    Past research has shown that self-handicapping stems from uncertainty about one's ability and self-presentational concerns. The present studies suggest that low dispositional self-control is also associated with self-handicapping. In 3 studies (N = 289), the association between self-control and self-handicapping was tested. Self-control was operationalized as trait self-control, whereas self-handicapping was operationalized as trait self-handicapping in Study 1 (N = 160), self-reported self-handicapping in Study 2 (N = 74), and behavioral self-handicapping in Study 3 (N = 55). In all 3 studies, hierarchical regression analyses revealed that low self-control predicts self-handicapping, independent of self-esteem, self-doubt, social desirability, and gender. © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.

  9. Trait-based representation of biological nitrification: Model development, testing, and predicted community composition

    Directory of Open Access Journals (Sweden)

    Nick eBouskill

    2012-10-01

    Full Text Available Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an ‘organism’ in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait focused on nitrification (MicroTrait-N that represents the ammonia-oxidizing bacteria (AOB and ammonia-oxidizing archaea (AOA and nitrite oxidizing bacteria (NOB using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3 oxidation rates and nitrous oxide (N2O production across pH, temperature and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over six month simulations is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

  10. Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

    Science.gov (United States)

    Montesinos-López, Osval A.; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C.; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

    2018-01-01

    In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. PMID:29097376

  11. Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems.

    Science.gov (United States)

    Montesinos-López, Osval A; Montesinos-López, Abelardo; Crossa, José; Montesinos-López, José C; Mota-Sanchez, David; Estrada-González, Fermín; Gillberg, Jussi; Singh, Ravi; Mondal, Suchismita; Juliana, Philomin

    2018-01-04

    In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF) and the matrix factorization algorithm (MF) in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment-trait combinations) and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets. Copyright © 2018 Montesinos-Lopez et al.

  12. Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems

    Directory of Open Access Journals (Sweden)

    Osval A. Montesinos-López

    2018-01-01

    Full Text Available In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. In current genomic selection, although researchers have a large amount of information and appropriate statistical models to process it, there is still limited computing efficiency to do so. Although some statistical models are usually mathematically elegant, many of them are also computationally inefficient, and they are impractical for many traits, lines, environments, and years because they need to sample from huge normal multivariate distributions. For these reasons, this study explores two recommender systems: item-based collaborative filtering (IBCF and the matrix factorization algorithm (MF in the context of multiple traits and multiple environments. The IBCF and MF methods were compared with two conventional methods on simulated and real data. Results of the simulated and real data sets show that the IBCF technique was slightly better in terms of prediction accuracy than the two conventional methods and the MF method when the correlation was moderately high. The IBCF technique is very attractive because it produces good predictions when there is high correlation between items (environment–trait combinations and its implementation is computationally feasible, which can be useful for plant breeders who deal with very large data sets.

  13. Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

    Science.gov (United States)

    Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

    2016-09-13

    Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

  14. Mapping of shoot fly tolerance loci in sorghum using SSR markers

    Indian Academy of Sciences (India)

    Identification of the genomic regions containing quantitative trait loci (QTLs) for ... Journal of Genetics, Vol. .... gant analysis were utilized further for genotyping of the ran- ..... Financial support to PLK in the form of research grants from Indian.

  15. Online Social Network Users’ Attitudes toward Personality Traits Predict Behaviour of their Friends

    Directory of Open Access Journals (Sweden)

    Sergei A. Shchebetenko

    2016-12-01

    Full Text Available The research considers attitudes toward personality traits in online social network (OSN Vkontakte users’ behaviour. Users’ friends’ activity on a given user’s profile was supposed to be affected by attitudes toward traits of the latter. Within a broader context, the role of metacognitive type of characteristic adaptations as a key element of the five-factor theory of personality is studied. Accordingly, along with attitudes toward traits, other metacognitive characteristic adaptations are examined (e.g. dispositional efficiency, reflected trait, and reflected attitude toward a trait. 1030 undergraduates participated in the study. The research results confirm that extraversion is the most important predictor of OSN behavior among other personality traits. The information presented in this research is obtained using behavioural data instead of more convenient self-reports. Moreover, these behavioural data characterise other users’ (friends’ behaviour while addressing a certain user’s profile. Positive attitudes toward each Big Five traits (extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience separately affected the number of “Likes” of the avatars representing users’ photographs. Furthermore, revealed correlations between traits and “Likes” were subsequently eliminated by the attitudes toward respective traits. Positive attitudes toward conscientiousness predicted the increase of friends’ number unlike trait conscientiousness. Positive attitude toward agreeableness predicted the increase of the number of posts written by friends on user’s wall unlike trait agreeableness. Attitudes toward traits are argued to affect social environment governed by an individual: one may select those social relationships and partners that fit better one’s attitudes toward traits. This, in turn, may affect actions of other people towards the given individual including those of online behaviour.

  16. Genome-wide meta-analysis identifies new susceptibility loci for migraine.

    Science.gov (United States)

    Anttila, Verneri; Winsvold, Bendik S; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E; Todt, Unda; McArdle, Wendy L; Quaye, Lydia; Koiranen, Markku; Ikram, M Arfan; Lehtimäki, Terho; Stam, Anine H; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin M; Palta, Priit; Hamalainen, Eija; Schürks, Markus; Rose, Lynda M; Buring, Julie E; Ridker, Paul M; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A; Evans, David M; Ring, Susan M; Färkkilä, Markus; Artto, Ville; Kaunisto, Mari A; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R; Pelzer, Nadine; Weller, Claudia M; Zielman, Ronald; Heath, Andrew C; Madden, Pamela A F; Montgomery, Grant W; Martin, Nicholas G; Borck, Guntram; Göbel, Hartmut; Heinze, Axel; Heinze-Kuhn, Katja; Williams, Frances M K; Hartikainen, Anna-Liisa; Pouta, Anneli; van den Ende, Joyce; Uitterlinden, Andre G; Hofman, Albert; Amin, Najaf; Hottenga, Jouke-Jan; Vink, Jacqueline M; Heikkilä, Kauko; Alexander, Michael; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Wichmann, Heinz Erich; Aromaa, Arpo; Eriksson, Johan G; Traynor, Bryan; Trabzuni, Daniah; Rossin, Elizabeth; Lage, Kasper; Jacobs, Suzanne B R; Gibbs, J Raphael; Birney, Ewan; Kaprio, Jaakko; Penninx, Brenda W; Boomsma, Dorret I; van Duijn, Cornelia; Raitakari, Olli; Jarvelin, Marjo-Riitta; Zwart, John-Anker; Cherkas, Lynn; Strachan, David P; Kubisch, Christian; Ferrari, Michel D; van den Maagdenberg, Arn M J M; Dichgans, Martin; Wessman, Maija; Smith, George Davey; Stefansson, Kari; Daly, Mark J; Nyholt, Dale R; Chasman, Daniel; Palotie, Aarno

    2013-08-01

    Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P<5×10(-8)). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

  17. 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

  18. Discovery of novel heart rate-associated loci using the Exome Chip

    DEFF Research Database (Denmark)

    van den Berg, Marten E; Warren, Helen R; Cabrera, Claudia P

    2017-01-01

    Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to di......) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies....

  19. 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.

  20. Genes and quality trait loci (QTLs) associated with firmness in Malus ...

    African Journals Online (AJOL)

    ctm

    2013-03-06

    Mar 6, 2013 ... Fruit firmness is affected by the inheritance of alleles at multiple loci and their possible interactions ... influences the sensory perception of fruits by consumers. (Harker et al. ..... direct comparisons between studies are difficult.

  1. Quantitative trait loci controlling leaf appearance and curd initiation of cauliflower in relation to temperature.

    Science.gov (United States)

    Hasan, Yaser; Briggs, William; Matschegewski, Claudia; Ordon, Frank; Stützel, Hartmut; Zetzsche, Holger; Groen, Simon; Uptmoor, Ralf

    2016-07-01

    QTL regions on chromosomes C06 and C09 are involved in temperature dependent time to curd induction in cauliflower. Temperature is the main environmental factor influencing curding time of cauliflower (Brassica oleracea var. botrytis). Temperatures above 20-22 °C inhibit development towards curding even in many summer cultivars. To identify quantitative trait loci (QTL) controlling curding time and its related traits in a wide range of different temperature regimes from 12 to 27 °C, a doubled haploid (DH) mapping population segregating for curding time was developed and days to curd initiation (DCI), leaf appearance rate (LAR), and final leaf number (FLN) were measured. The population was genotyped with 176 single nucleotide polymorphism (SNP) markers. Composite interval mapping (CIM) revealed repeatedly detected QTL for DCI on C06 and C09. The estimated additive effect increased at high temperatures. Significant QTL × environment interactions (Q × E) for FLN and DCI on C06 and C09 suggest that these hotspot regions have major influences on temperature mediated curd induction. 25 % of the DH lines did not induce curds at temperatures higher than 22 °C. Applying a binary model revealed a QTL with LOD >15 on C06. Nearly all lines carrying the allele of the reliable early maturing parental line (PL) on that locus induced curds at high temperatures while only half of the DH lines carrying the allele of the unreliable PL reached the generative phase during the experiment. Large variation in LAR was observed. QTL for LAR were detected repeatedly in several environments on C01, C04 and C06. Negative correlations between LAR and DCI and QTL co-localizations on C04 and C06 suggest that LAR has also effects on development towards curd induction.

  2. A meta-analysis of thyroid-related traits reveals novel loci and gender-specific differences in the regulation of thyroid function.

    Directory of Open Access Journals (Sweden)

    Eleonora Porcu

    Full Text Available Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3 and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2. Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2 show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism.

  3. A Meta-Analysis of Thyroid-Related Traits Reveals Novel Loci and Gender-Specific Differences in the Regulation of Thyroid Function

    Science.gov (United States)

    Volpato, Claudia B.; Wilson, Scott G.; Cappola, Anne R.; Bos, Steffan D.; Deelen, Joris; den Heijer, Martin; Freathy, Rachel M.; Lahti, Jari; Liu, Chunyu; Lopez, Lorna M.; Nolte, Ilja M.; O'Connell, Jeffrey R.; Tanaka, Toshiko; Trompet, Stella; Arnold, Alice; Bandinelli, Stefania; Beekman, Marian; Böhringer, Stefan; Brown, Suzanne J.; Buckley, Brendan M.; Camaschella, Clara; de Craen, Anton J. M.; Davies, Gail; de Visser, Marieke C. H.; Ford, Ian; Forsen, Tom; Frayling, Timothy M.; Fugazzola, Laura; Gögele, Martin; Hattersley, Andrew T.; Hermus, Ad R.; Hofman, Albert; Houwing-Duistermaat, Jeanine J.; Jensen, Richard A.; Kajantie, Eero; Kloppenburg, Margreet; Lim, Ee M.; Masciullo, Corrado; Mariotti, Stefano; Minelli, Cosetta; Mitchell, Braxton D.; Nagaraja, Ramaiah; Netea-Maier, Romana T.; Palotie, Aarno; Persani, Luca; Piras, Maria G.; Psaty, Bruce M.; Räikkönen, Katri; Richards, J. Brent; Rivadeneira, Fernando; Sala, Cinzia; Sabra, Mona M.; Sattar, Naveed; Shields, Beverley M.; Soranzo, Nicole; Starr, John M.; Stott, David J.; Sweep, Fred C. G. J.; Usala, Gianluca; van der Klauw, Melanie M.; van Heemst, Diana; van Mullem, Alies; H.Vermeulen, Sita; Visser, W. Edward; Walsh, John P.; Westendorp, Rudi G. J.; Widen, Elisabeth; Zhai, Guangju; Cucca, Francesco; Deary, Ian J.; Eriksson, Johan G.; Ferrucci, Luigi; Fox, Caroline S.; Jukema, J. Wouter; Kiemeney, Lambertus A.; Pramstaller, Peter P.; Schlessinger, David; Shuldiner, Alan R.; Slagboom, Eline P.; Uitterlinden, André G.; Vaidya, Bijay; Visser, Theo J.; Wolffenbuttel, Bruce H. R.; Meulenbelt, Ingrid; Rotter, Jerome I.; Spector, Tim D.; Hicks, Andrew A.; Toniolo, Daniela; Sanna, Serena; Peeters, Robin P.; Naitza, Silvia

    2013-01-01

    Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism. PMID:23408906

  4. The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits.

    Directory of Open Access Journals (Sweden)

    Benjamin F Voight

    Full Text Available Genome-wide association studies have identified hundreds of loci for type 2 diabetes, coronary artery disease and myocardial infarction, as well as for related traits such as body mass index, glucose and insulin levels, lipid levels, and blood pressure. These studies also have pointed to thousands of loci with promising but not yet compelling association evidence. To establish association at additional loci and to characterize the genome-wide significant loci by fine-mapping, we designed the "Metabochip," a custom genotyping array that assays nearly 200,000 SNP markers. Here, we describe the Metabochip and its component SNP sets, evaluate its performance in capturing variation across the allele-frequency spectrum, describe solutions to methodological challenges commonly encountered in its analysis, and evaluate its performance as a platform for genotype imputation. The metabochip achieves dramatic cost efficiencies compared to designing single-trait follow-up reagents, and provides the opportunity to compare results across a range of related traits. The metabochip and similar custom genotyping arrays offer a powerful and cost-effective approach to follow-up large-scale genotyping and sequencing studies and advance our understanding of the genetic basis of complex human diseases and traits.

  5. Identification of Major Quantitative Trait Loci for Seed Oil Content in Soybeans by Combining Linkage and Genome-Wide Association Mapping.

    Science.gov (United States)

    Cao, Yongce; Li, Shuguang; Wang, Zili; Chang, Fangguo; Kong, Jiejie; Gai, Junyi; Zhao, Tuanjie

    2017-01-01

    Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2 , was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F 2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1 , and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F 2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.

  6. Statistical correction of the Winner's Curse explains replication variability in quantitative trait genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Cameron Palmer

    2017-07-01

    Full Text Available Genome-wide association studies (GWAS have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10-14, even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner's Curse (p < 10-16. We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94. In contrast, ancestry differences between replication and discovery (13 studies, 385 loci cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium.

  7. Responsiveness of performance and morphological traits to experimental submergence predicts field distribution pattern of wetland plants

    NARCIS (Netherlands)

    Luo, Fang-Li; Huang, Lin; Lei, Ting; Xue, Wei; Li, Hong-Li; Yu, Fei-Hai; Cornelissen, J.H.C.

    2016-01-01

    Question: Plant trait mean values and trait responsiveness to different environmental regimes are both important determinants of plant field distribution, but the degree to which plant trait means vs trait responsiveness predict plant distribution has rarely been compared quantitatively. Because

  8. Minding Your Matters: Predicting Satisfaction, Commitment, and Conflict Strategies From Trait Mindfulness

    Directory of Open Access Journals (Sweden)

    Jacquelyn Harvey Knowles

    2015-06-01

    Full Text Available This exploratory study sought to uncover whether trait mindfulness, an individual’s aptitude for focusing on the present moment while refraining from passing negative judgments or processing external cues in a habitual manner, is predictive of more constructive and less destructive approaches to relational conflict. In addition, we looked at its predictive role in relational satisfaction and commitment. Ninety-one participants completed self-report measures on trait mindfulness, relational satisfaction, commitment, and conflict strategies. Results revealed that aspects of mindfulness predict the type of conflict strategy in which people reportedly engage. Mindfulness subscales were also related positively to satisfaction and commitment. In concluding, we discuss limitations and potential avenues for future inquiry in this area.

  9. Quantitative genetic analysis of life-history traits of Caenorhabditis elegans in stressful environments

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    Shorto Alison

    2008-01-01

    Full Text Available Abstract Background Organisms live in environments that vary. For life-history traits that vary across environments, fitness will be maximised when the phenotype is appropriately matched to the environmental conditions. For the free-living nematode Caenorhabditis elegans, we have investigated how two major life-history traits, (i the development of environmentally resistant dauer larvae and (ii reproduction, respond to environmental stress (high population density and low food availability, and how these traits vary between lines and the genetic basis of this variation. Results We found that lines of C. elegans vary in their phenotypic plasticity of dauer larva development, i.e. there is variation in the likelihood of developing into a dauer larva for the same environmental change. There was also variation in how lifetime fecundity and the rate of reproduction changed under conditions of environmental stress. These traits were related, such that lines that are highly plastic for dauer larva development also maintain a high population growth rate when stressed. We identified quantitative trait loci (QTL on two chromosomes that control the dauer larva development and population size phenotypes. The QTLs affecting the dauer larva development and population size phenotypes on chromosome II are closely linked, but are genetically separable. This chromosome II QTL controlling dauer larva development does not encompass any loci previously identified to control dauer larva development. This chromosome II region contains many predicted 7-transmembrane receptors. Such proteins are often involved in information transduction, which is clearly relevant to the control of dauer larva development. Conclusion C. elegans alters both its larval development and adult reproductive strategy in response to environmental stress. Together the phenotypic and genotypic data suggest that these two major life-history traits are co-ordinated responses to environmental stress

  10. Replication and Characterization of Association between ABO SNPs and Red Blood Cell Traits by Meta-Analysis in Europeans.

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    Stela McLachlan

    Full Text Available Red blood cell (RBC traits are routinely measured in clinical practice as important markers of health. Deviations from the physiological ranges are usually a sign of disease, although variation between healthy individuals also occurs, at least partly due to genetic factors. Recent large scale genetic studies identified loci associated with one or more of these traits; further characterization of known loci and identification of new loci is necessary to better understand their role in health and disease and to identify potential molecular mechanisms. We performed meta-analysis of Metabochip association results for six RBC traits-hemoglobin concentration (Hb, hematocrit (Hct, mean corpuscular hemoglobin (MCH, mean corpuscular hemoglobin concentration (MCHC, mean corpuscular volume (MCV and red blood cell count (RCC-in 11 093 Europeans from seven studies of the UCL-LSHTM-Edinburgh-Bristol (UCLEB Consortium. We identified 394 non-overlapping SNPs in five loci at genome-wide significance: 6p22.1-6p21.33 (with HFE among others, 6q23.2 (with HBS1L among others, 6q23.3 (contains no genes, 9q34.3 (only ABO gene and 22q13.1 (with TMPRSS6 among others, replicating previous findings of association with RBC traits at these loci and extending them by imputation to 1000 Genomes. We further characterized associations between ABO SNPs and three traits: hemoglobin, hematocrit and red blood cell count, replicating them in an independent cohort. Conditional analyses indicated the independent association of each of these traits with ABO SNPs and a role for blood group O in mediating the association. The 15 most significant RBC-associated ABO SNPs were also associated with five cardiometabolic traits, with discordance in the direction of effect between groups of traits, suggesting that ABO may act through more than one mechanism to influence cardiometabolic risk.

  11. Relationship of the Interaction Between Two Quantitative Trait Loci with γ-Globin Expression in β-Thalassemia Intermedia Patients.

    Science.gov (United States)

    NickAria, Shiva; Haghpanah, Sezaneh; Ramzi, Mani; Karimi, Mehran

    2018-05-10

    Globin switching is a significant factor on blood hemoglobin (Hb) level but its molecular mechanisms have not yet been identified, however, several quantitative trait loci (QTL) and polymorphisms involved regions on chromosomes 2p, 6q, 8q and X account for variation in the γ-globin expression level. We studied the effect of interaction between a region on intron six of the TOX gene, chromosome 8q (chr8q) and XmnI locus on the γ-globin promoter, chr11p on γ-globin expression in 150 β-thalassemia intermedia (β-TI) patients, evaluated by statistical interaction analysis. Our results showed a significant interaction between one QTL on intron six of the TOX gene (rs9693712) and XmnI locus that effect γ-globin expression. Interchromosomal interaction mediates through transcriptional machanisms to preserve true genome architectural features, chromosomes localization and DNA bending. This interaction can be a part of the unknown molecular mechanism of globin switching and regulation of gene expression.

  12. Validation of genomic predictions for wellness traits in US Holstein cows.

    Science.gov (United States)

    McNeel, Anthony K; Reiter, Brenda C; Weigel, Dan; Osterstock, Jason; Di Croce, Fernando A

    2017-11-01

    The objective of this study was to evaluate the efficacy of wellness trait genetic predictions in commercial herds of US Holstein cows from herds that do not contribute phenotypic information to the evaluation. Tissue samples for DNA extraction were collected from more than 3,400 randomly selected pregnant Holstein females in 11 herds and 2 age groups (69% nulliparous, 31% primiparous) approximately 30 to 60 d before their expected calving date. Lactation records from cows that calved between September 1, 2015, and December 31, 2015, were included in the analysis. Genomically enhanced predicted transmitting abilities for the wellness traits of retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness were estimated by the Zoetis genetic evaluation and converted into standardized transmitting abilities. Mean reliabilities of the animals in the study ranged between 45 and 47% for each of the 6 traits. Animals were ranked by their standardized transmitting abilities within herd and age group then assigned to 1 of 4 groups of percentile-based genetic groups of equal size. Adverse health events, including retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness, were collected from on-farm herd management software, and animal phenotype was coded as either healthy (0), diseased (1), or excluded for each of the 6 outcomes of interest. Statistical analysis was performed using a generalized linear mixed model with genetic group, age group, and lactation as fixed effects, whereas herd and animal nested within herd were set as random effects. Results of the analysis indicated that the wellness trait predictions were associated with differences in phenotypic disease incidence between the worst and best genetic groups. The difference between the worst and best genetic groups in recorded disease incidence was 2.9% for retained placenta, 10.8% for metritis, 1.1% for displaced abomasum, 1.7% for ketosis, 7.4% for mastitis, and 3

  13. Predicting Undergraduate Leadership Student Goal Orientation Using Personality Traits

    Science.gov (United States)

    Lamm, Kevan W.; Sheikh, Emana; Carter, Hannah S.; Lamm, Alexa J.

    2017-01-01

    Finding strategies to increase the motivation of students, their connection with the material, and retention of the content, has been very important within leadership education. Previous research studies have shown that personality traits can predict desired outcomes, including goal orientation or motivational disposition. However, there have not…

  14. Neutral mutation as the source of genetic variation in life history traits.

    Science.gov (United States)

    Brcić-Kostić, Krunoslav

    2005-08-01

    The mechanism underlying the maintenance of adaptive genetic variation is a long-standing question in evolutionary genetics. There are two concepts (mutation-selection balance and balancing selection) which are based on the phenotypic differences between alleles. Mutation - selection balance and balancing selection cannot properly explain the process of gene substitution, i.e. the molecular evolution of quantitative trait loci affecting fitness. I assume that such loci have non-essential functions (small effects on fitness), and that they have the potential to evolve into new functions and acquire new adaptations. Here I show that a high amount of neutral polymorphism at these loci can exist in real populations. Consistent with this, I propose a hypothesis for the maintenance of genetic variation in life history traits which can be efficient for the fixation of alleles with very small selective advantage. The hypothesis is based on neutral polymorphism at quantitative trait loci and both neutral and adaptive gene substitutions. The model of neutral - adaptive conversion (NAC) assumes that neutral alleles are not neutral indefinitely, and that in specific and very rare situations phenotypic (relative fitness) differences between them can appear. In this paper I focus on NAC due to phenotypic plasticity of neutral alleles. The important evolutionary consequence of NAC could be the increased adaptive potential of a population. Loci responsible for adaptation should be fast evolving genes with minimally discernible phenotypic effects, and the recent discovery of genes with such characteristics implicates them as suitable candidates for loci involved in adaptation.

  15. How well can spectroscopy predict leaf morphological traits in the seasonal neotropical savannas?

    Science.gov (United States)

    Streher, A. S.; McGill, B.; Morellato, P.; Silva, T. S. F.

    2017-12-01

    Variations in foliar morphological traits, quantified as leaf mass per area (LMA, g m-2) and leaf dry matter content (LDMC, g g-1), correspond to a tradeoff between investments in leaf construction costs and leaf life span. Leaf spectroscopy, the acquisition of reflected radiation along contiguous narrow spectral bands from leaves, has shown the potential to link leaf optical properties with a range of foliar traits. However, our knowledge is still limited on how well leaf traits from plants with different life forms and deciduousness strategies can be predicted from spectroscopy. To understand the relationships between leaf traits and optical properties, we investigated: 1) What are the spectral regions associated with leaf morphological traits? 2) How generalizable an optical trait model is across different life forms and leaf strategies? Five locations across cerrado and campo rupestre vegetation in Brazil were sampled during the growing season in 2017. Triplicate mature sun leaves were harvested from plants encompassing different life forms (grasses, perennial herbs, shrubs and trees), comprising 1650 individuals growing over a wide range of environmental conditions. For each individual, we determined LDMC and LMA, and took 30 spectral leaf measurements from 400 to 2500nm, using a spectrometer. We used the Random Forests (RF) algorithm to predict both morphological traits from leaf reflectance, and performed feature selection with a backward stepwise method, progressively removing variables with small importance at each iteration. Model performance was evaluated by using 10-fold cross-validation. LDMC values ranged from 0.12 to 0.67 g g-1, while LMA varied between 41.78 and 562 g m-2. The spectral bands that best explained trait variation were found within the SWIR, around 1397 nm for LDMC, and 2279 nm for LMA. Our general model explained 55.28% of LDMC variance and 55.64% of LMA variation, and the mean RMSE for the predicted values were 0.004 g g-1 and 36.99 g

  16. When should we expect microbial phenotypic traits to predict microbial abundances?

    Directory of Open Access Journals (Sweden)

    Jeremy W. Fox

    2012-08-01

    Full Text Available Species’ phenotypic traits may predict their relative abundances. Intuitively, this is because locally-abundant species have traits making them well adapted to local abiotic and biotic conditions, while locally-rare species are not as well-adapted. But this intuition may not be valid. If competing species vary in how well-adapted they are to local conditions, why doesn’t the best-adapted species simply exclude the others entirely? But conversely, if species exhibit niche differences that allow them to coexist, then by definition there is no single best adapted species. Rather, demographic rates depend on species’ relative abundances, so that phenotypic traits conferring high adaptedness do not necessarily confer high abundance. I illustrate these points using a simple theoretical model incorporating adjustable levels of "adaptedness" and "niche differences". Even very small niche differences can weaken or even reverse the expected correlation between adaptive traits and abundance. Conversely, adaptive traits confer high abundance when niche differences are very strong. Future work should be directed towards understanding the link between phenotypic traits and frequency-dependence of demographic rates.

  17. When should we expect microbial phenotypic traits to predict microbial abundances?

    Science.gov (United States)

    Fox, Jeremy W

    2012-01-01

    Species' phenotypic traits may predict their relative abundances. Intuitively, this is because locally abundant species have traits making them well-adapted to local abiotic and biotic conditions, while locally rare species are not as well-adapted. But this intuition may not be valid. If competing species vary in how well-adapted they are to local conditions, why doesn't the best-adapted species simply exclude the others entirely? But conversely, if species exhibit niche differences that allow them to coexist, then by definition there is no single best adapted species. Rather, demographic rates depend on species' relative abundances, so that phenotypic traits conferring high adaptedness do not necessarily confer high abundance. I illustrate these points using a simple theoretical model incorporating adjustable levels of "adaptedness" and "niche differences." Even very small niche differences can weaken or even reverse the expected correlation between adaptive traits and abundance. Conversely, adaptive traits confer high abundance when niche differences are very strong. Future work should be directed toward understanding the link between phenotypic traits and frequency-dependence of demographic rates.

  18. Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

    Directory of Open Access Journals (Sweden)

    Benjamin Stich

    2018-03-01

    Full Text Available Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP, BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY, and tuber yield (TY of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

  19. Estimation of loci involved in non-shattering of seeds in early rice domestication.

    Science.gov (United States)

    Ishikawa, Ryo; Nishimura, Akinori; Htun, Than Myint; Nishioka, Ryo; Oka, Yumi; Tsujimura, Yuki; Inoue, Chizuru; Ishii, Takashige

    2017-04-01

    Rice (Oryza sativa L.) is widely cultivated around the world and is known to be domesticated from its wild form, O. rufipogon. A loss of seed shattering is one of the most obvious phenotypic changes selected for during rice domestication. Previously, three seed-shattering loci, qSH1, sh4, and qSH3 were reported to be involved in non-shattering of seeds of Japonica-type cultivated rice, O. sativa cv. Nipponbare. In this study, we focused on non-shattering characteristics of O. sativa Indica cv. IR36 having functional allele at qSH1. We produced backcross recombinant inbred lines having chromosomal segments from IR36 in the genetic background of wild rice, O. rufipogon W630. Histological and quantitative trait loci analyses of abscission layer formation were conducted. In the analysis of quantitative trait loci, a strong peak was observed close to sh4. We, nevertheless, found that some lines showed complete abscission layer formation despite carrying the IR36 allele at sh4, implying that non-shattering of seeds of IR36 could be regulated by the combination of mutations at sh4 and other seed-shattering loci. We also genotyped qSH3, a recently identified seed-shattering locus. Lines that have the IR36 alleles at sh4 and qSH3 showed inhibition of abscission layer formation but the degree of seed shattering was different from that of IR36. On the basis of these results, we estimated that non-shattering of seeds in early rice domestication involved mutations in at least three loci, and these genetic materials produced in this study may help to identify novel seed-shattering loci.

  20. Modularization and epistatic hierarchy determine homeostatic actions of multiple blood pressure quantitative trait loci.

    Science.gov (United States)

    Chauvet, Cristina; Crespo, Kimberley; Ménard, Annie; Roy, Julie; Deng, Alan Y

    2013-11-15

    Hypertension, the most frequently diagnosed clinical condition world-wide, predisposes individuals to morbidity and mortality, yet its underlying pathological etiologies are poorly understood. So far, a large number of quantitative trait loci (QTLs) have been identified in both humans and animal models, but how they function together in determining overall blood pressure (BP) in physiological settings is unknown. Here, we systematically and comprehensively performed pair-wise comparisons of individual QTLs to create a global picture of their functionality in an inbred rat model. Rather than each of numerous QTLs contributing to infinitesimal BP increments, a modularized pattern arises: two epistatic 'blocks' constitute basic functional 'units' for nearly all QTLs, designated as epistatic module 1 (EM1) and EM2. This modularization dictates the magnitude and scope of BP effects. Any EM1 member can contribute to BP additively to that of EM2, but not to those of the same module. Members of each EM display epistatic hierarchy, which seems to reflect a related functional pathway. Rat homologues of 11 human BP QTLs belong to either EM1 or EM2. Unique insights emerge into the novel genetic mechanism and hierarchy determining BP in the Dahl salt-sensitive SS/Jr (DSS) rat model that implicate a portion of human QTLs. Elucidating the pathways underlying EM1 and EM2 may reveal the genetic regulation of BP.

  1. Combining a weed traits database with a population dynamics model predicts shifts in weed communities

    DEFF Research Database (Denmark)

    Storkey, Jonathan; Holst, Niels; Bøjer, Ole Mission

    2015-01-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, po...

  2. Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

    Science.gov (United States)

    Nazarian, Alireza; Gezan, Salvador A

    2016-03-01

    The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. A Novel Adaptive Conditional Probability-Based Predicting Model for User’s Personality Traits

    Directory of Open Access Journals (Sweden)

    Mengmeng Wang

    2015-01-01

    Full Text Available With the pervasive increase in social media use, the explosion of users’ generated data provides a potentially very rich source of information, which plays an important role in helping online researchers understand user’s behaviors deeply. Since user’s personality traits are the driving force of user’s behaviors, hence, in this paper, along with social network features, we first extract linguistic features, emotional statistical features, and topic features from user’s Facebook status updates, followed by quantifying importance of features via Kendall correlation coefficient. And then, on the basis of weighted features and dynamic updated thresholds of personality traits, we deploy a novel adaptive conditional probability-based predicting model which considers prior knowledge of correlations between user’s personality traits to predict user’s Big Five personality traits. In the experimental work, we explore the existence of correlations between user’s personality traits which provides a better theoretical support for our proposed method. Moreover, on the same Facebook dataset, compared to other methods, our method can achieve an F1-measure of 80.6% when taking into account correlations between user’s personality traits, and there is an impressive improvement of 5.8% over other approaches.

  4. Quantitative trait loci identified for blood chemistry components of an advanced intercross line of chickens under heat stress.

    Science.gov (United States)

    Van Goor, Angelica; Ashwell, Christopher M; Persia, Michael E; Rothschild, Max F; Schmidt, Carl J; Lamont, Susan J

    2016-04-14

    Heat stress in poultry results in considerable economic losses and is a concern for both animal health and welfare. Physiological changes occur during periods of heat stress, including changes in blood chemistry components. A highly advanced intercross line, created from a broiler (heat susceptible) by Fayoumi (heat resistant) cross, was exposed to daily heat cycles for seven days starting at 22 days of age. Blood components measured pre-heat treatment and on the seventh day of heat treatment included pH, pCO2, pO2, base excess, HCO3, TCO2, K, Na, ionized Ca, hematocrit, hemoglobin, sO2, and glucose. A genome-wide association study (GWAS) for these traits and their calculated changes was conducted to identify quantitative trait loci (QTL) using a 600 K SNP panel. There were significant increases in pH, base excess, HCO3, TCO2, ionized Ca, hematocrit, hemoglobin, and sO2, and significant decreases in pCO2 and glucose after 7 days of heat treatment. Heritabilities ranged from 0.01-0.21 for pre-heat measurements, 0.01-0.23 for measurements taken during heat, and 0.00-0.10 for the calculated change due to heat treatment. All blood components were highly correlated within measurement days, but not correlated between measurement days. The GWAS revealed 61 QTL for all traits, located on GGA (Gallus gallus chromosome) 1, 3, 6, 9, 10, 12-14, 17, 18, 21-28, and Z. A functional analysis of the genes in these QTL regions identified the Angiopoietin pathway as significant. The QTL that co-localized for three or more traits were on GGA10, 22, 26, 28, and Z and revealed candidate genes for birds' response to heat stress. The results of this study contribute to our knowledge of levels and heritabilities of several blood components of chickens under thermoneutral and heat stress conditions. Most components responded to heat treatment. Mapped QTL may serve as markers for genomic selection to enhance heat tolerance in poultry. The Angiopoietin pathway is likely involved in the

  5. Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

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    Zhengbin Liu

    2016-08-01

    Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.

  6. Comparative Mapping of Seed Dormancy Loci Between Tropical and Temperate Ecotypes of Weedy Rice (Oryza sativa L.

    Directory of Open Access Journals (Sweden)

    Lihua Zhang

    2017-08-01

    Full Text Available Genotypic variation at multiple loci for seed dormancy (SD contributes to plant adaptation to diverse ecosystems. Weedy rice (Oryza sativa was used as a model to address the similarity of SD genes between distinct ecotypes. A total of 12 quantitative trait loci (QTL for SD were identified in one primary and two advanced backcross (BC populations derived from a temperate ecotype of weedy rice (34.3°N Lat.. Nine (75% of the 12 loci were mapped to the same positions as those identified from a tropical ecotype of weedy rice (7.1°N Lat.. The high similarity suggested that the majority of SD genes were conserved during the ecotype differentiation. These common loci are largely those collocated/linked with the awn, hull color, pericarp color, or plant height loci. Phenotypic correlations observed in the populations support the notion that indirect selections for the wild-type morphological characteristics, together with direct selections for germination time, were major factors influencing allelic distributions of SD genes across ecotypes. Indirect selections for crop-mimic traits (e.g., plant height and flowering time could also alter allelic frequencies for some SD genes in agroecosystems. In addition, 3 of the 12 loci were collocated with segregation distortion loci, indicating that some gametophyte development genes could also influence the genetic equilibria of SD loci in hybrid populations. The SD genes with a major effect on germination across ecotypes could be used as silencing targets to develop transgene mitigation (TM strategies to reduce the risk of gene flow from genetically modified crops into weed/wild relatives.

  7. Eye Movements During Everyday Behavior Predict Personality Traits.

    Science.gov (United States)

    Hoppe, Sabrina; Loetscher, Tobias; Morey, Stephanie A; Bulling, Andreas

    2018-01-01

    Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness) as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human-computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

  8. Eye Movements During Everyday Behavior Predict Personality Traits

    Directory of Open Access Journals (Sweden)

    Sabrina Hoppe

    2018-04-01

    Full Text Available Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human–computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

  9. 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

    2017-01-01

    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.

  10. Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L. Using SLAF-seq

    Directory of Open Access Journals (Sweden)

    Dongwei Xie

    2018-01-01

    Full Text Available 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.

  11. Detection and characterization of quantitative trait loci for meat quality traits in pigs

    NARCIS (Netherlands)

    Koning, de D.J.; Harlizius, B.; Rattink, A.P.; Groenen, M.A.M.; Brascamp, E.W.; Arendonk, van J.A.M.

    2001-01-01

    In an experimental cross between Meishan and Dutch Large White and Landrace lines, 785 F2 animals with carcass information and their parents were typed for molecular markers covering the entire porcine genome. Linkage was studied between these markers and eight meat quality traits. Quantitative

  12. 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.

  13. Analysis of natural allelic variation of Arabidopsis seed germination and seed longevity traits between the accessions Landberg erecta and Shakdara, using a new recombinant inbred line population

    NARCIS (Netherlands)

    Clerkx, E.J.M.; El-Lithy, M.E.M.; Vierling, E.; Ruijs, G.J.; Vries, de M.H.C.; Groot, S.P.C.; Vreugdenhil, D.; Koornneef, M.

    2004-01-01

    Quantitative trait loci (QTL) mapping was used to identify loci controlling various aspects of seed longevity during storage and germination. Similar locations for QTLs controlling different traits might be an indication for a common genetic control of such traits. For this analysis we used a new

  14. 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.

  15. Does trait affectivity predict work-to-family conflict and enrichment beyond job characteristics?

    Science.gov (United States)

    Tement, Sara; Korunka, Christian

    2013-01-01

    The present study examines whether negative and positive affectivity (NA and PA, respectively) predict different forms of work-to-family conflict (WFC-time, WFC-strain, WFC-behavior) and enrichment (WFE-development, WFE-affect, WFE-capital) beyond job characteristics (workload, autonomy, variety, workplace support). Furthermore, interactions between job characteristics and trait affectivity while predicting WFC and WFE were examined. Using a large sample of Slovenian employees (N = 738), NA and PA were found to explain variance in WFC as well as in WFE above and beyond job characteristics. More precisely, NA significantly predicted WFC, whereas PA significantly predicted WFE. In addition, several interactive effects were found to predict forms of WFC and WFE. These results highlight the importance of trait affectivity in work-family research. They provide further support for the crucial impact of job characteristics as well.

  16. Meta-analysis of loci associated with age at natural menopause in African-American women

    Science.gov (United States)

    Chen, Christina T.L.; Liu, Ching-Ti; Chen, Gary K.; Andrews, Jeanette S.; Arnold, Alice M.; Dreyfus, Jill; Franceschini, Nora; Garcia, Melissa E.; Kerr, Kathleen F.; Li, Guo; Lohman, Kurt K.; Musani, Solomon K.; Nalls, Michael A.; Raffel, Leslie J.; Smith, Jennifer; Ambrosone, Christine B.; Bandera, Elisa V.; Bernstein, Leslie; Britton, Angela; Brzyski, Robert G.; Cappola, Anne; Carlson, Christopher S.; Couper, David; Deming, Sandra L.; Goodarzi, Mark O.; Heiss, Gerardo; John, Esther M.; Lu, Xiaoning; Le Marchand, Loic; Marciante, Kristin; Mcknight, Barbara; Millikan, Robert; Nock, Nora L.; Olshan, Andrew F.; Press, Michael F.; Vaiyda, Dhananjay; Woods, Nancy F.; Taylor, Herman A.; Zhao, Wei; Zheng, Wei; Evans, Michele K.; Harris, Tamara B.; Henderson, Brian E.; Kardia, Sharon L.R.; Kooperberg, Charles; Liu, Yongmei; Mosley, Thomas H.; Psaty, Bruce; Wellons, Melissa; Windham, Beverly G.; Zonderman, Alan B.; Cupples, L. Adrienne; Demerath, Ellen W.; Haiman, Christopher; Murabito, Joanne M.; Rajkovic, Aleksandar

    2014-01-01

    Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA. PMID:24493794

  17. Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

    Science.gov (United States)

    Zhang, Jiaoping; Song, Qijian; Cregan, Perry B; Jiang, Guo-Liang

    2016-01-01

    Twenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations. Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4% of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75-0.87 and 0.62-0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.

  18. Nine Loci for Ocular Axial Length Identified through Genome-wide Association Studies, Including Shared Loci with Refractive Error

    Science.gov (United States)

    Cheng, Ching-Yu; Schache, Maria; Ikram, M. Kamran; Young, Terri L.; Guggenheim, Jeremy A.; Vitart, Veronique; MacGregor, Stuart; Verhoeven, Virginie J.M.; Barathi, Veluchamy A.; Liao, Jiemin; Hysi, Pirro G.; Bailey-Wilson, Joan E.; St. Pourcain, Beate; Kemp, John P.; McMahon, George; Timpson, Nicholas J.; Evans, David M.; Montgomery, Grant W.; Mishra, Aniket; Wang, Ya Xing; Wang, Jie Jin; Rochtchina, Elena; Polasek, Ozren; Wright, Alan F.; Amin, Najaf; van Leeuwen, Elisabeth M.; Wilson, James F.; Pennell, Craig E.; van Duijn, Cornelia M.; de Jong, Paulus T.V.M.; Vingerling, Johannes R.; Zhou, Xin; Chen, Peng; Li, Ruoying; Tay, Wan-Ting; Zheng, Yingfeng; Chew, Merwyn; Rahi, Jugnoo S.; Hysi, Pirro G.; Yoshimura, Nagahisa; Yamashiro, Kenji; Miyake, Masahiro; Delcourt, Cécile; Maubaret, Cecilia; Williams, Cathy; Guggenheim, Jeremy A.; Northstone, Kate; Ring, Susan M.; Davey-Smith, George; Craig, Jamie E.; Burdon, Kathryn P.; Fogarty, Rhys D.; Iyengar, Sudha K.; Igo, Robert P.; Chew, Emily; Janmahasathian, Sarayut; Iyengar, Sudha K.; Igo, Robert P.; Chew, Emily; Janmahasathian, Sarayut; Stambolian, Dwight; Wilson, Joan E. Bailey; MacGregor, Stuart; Lu, Yi; Jonas, Jost B.; Xu, Liang; Saw, Seang-Mei; Baird, Paul N.; Rochtchina, Elena; Mitchell, Paul; Wang, Jie Jin; Jonas, Jost B.; Nangia, Vinay; Hayward, Caroline; Wright, Alan F.; Vitart, Veronique; Polasek, Ozren; Campbell, Harry; Vitart, Veronique; Rudan, Igor; Vatavuk, Zoran; Vitart, Veronique; Paterson, Andrew D.; Hosseini, S. Mohsen; Iyengar, Sudha K.; Igo, Robert P.; Fondran, Jeremy R.; Young, Terri L.; Feng, Sheng; Verhoeven, Virginie J.M.; Klaver, Caroline C.; van Duijn, Cornelia M.; Metspalu, Andres; Haller, Toomas; Mihailov, Evelin; Pärssinen, Olavi; Wedenoja, Juho; Wilson, Joan E. Bailey; Wojciechowski, Robert; Baird, Paul N.; Schache, Maria; Pfeiffer, Norbert; Höhn, René; Pang, Chi Pui; Chen, Peng; Meitinger, Thomas; Oexle, Konrad; Wegner, Aharon; Yoshimura, Nagahisa; Yamashiro, Kenji; Miyake, Masahiro; Pärssinen, Olavi; Yip, Shea Ping; Ho, Daniel W.H.; Pirastu, Mario; Murgia, Federico; Portas, Laura; Biino, Genevra; Wilson, James F.; Fleck, Brian; Vitart, Veronique; Stambolian, Dwight; Wilson, Joan E. Bailey; Hewitt, Alex W.; Ang, Wei; Verhoeven, Virginie J.M.; Klaver, Caroline C.; van Duijn, Cornelia M.; Saw, Seang-Mei; Wong, Tien-Yin; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Saw, Seang-Mei; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Saw, Seang-Mei; Wong, Tien-Yin; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Saw, Seang-Mei; Wong, Tien-Yin; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Saw, Seang-Mei; Tai, E-Shyong; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Saw, Seang-Mei; Teo, Yik-Ying; Fan, Qiao; Cheng, Ching-Yu; Zhou, Xin; Ikram, M. Kamran; Mackey, David A.; MacGregor, Stuart; Hammond, Christopher J.; Hysi, Pirro G.; Deangelis, Margaret M.; Morrison, Margaux; Zhou, Xiangtian; Chen, Wei; Paterson, Andrew D.; Hosseini, S. Mohsen; Mizuki, Nobuhisa; Meguro, Akira; Lehtimäki, Terho; Mäkelä, Kari-Matti; Raitakari, Olli; Kähönen, Mika; Burdon, Kathryn P.; Craig, Jamie E.; Iyengar, Sudha K.; Igo, Robert P.; Lass, Jonathan H.; Reinhart, William; Belin, Michael W.; Schultze, Robert L.; Morason, Todd; Sugar, Alan; Mian, Shahzad; Soong, Hunson Kaz; Colby, Kathryn; Jurkunas, Ula; Yee, Richard; Vital, Mark; Alfonso, Eduardo; Karp, Carol; Lee, Yunhee; Yoo, Sonia; Hammersmith, Kristin; Cohen, Elisabeth; Laibson, Peter; Rapuano, Christopher; Ayres, Brandon; Croasdale, Christopher; Caudill, James; Patel, Sanjay; Baratz, Keith; Bourne, William; Maguire, Leo; Sugar, Joel; Tu, Elmer; Djalilian, Ali; Mootha, Vinod; McCulley, James; Bowman, Wayne; Cavanaugh, H. Dwight; Verity, Steven; Verdier, David; Renucci, Ann; Oliva, Matt; Rotkis, Walter; Hardten, David R.; Fahmy, Ahmad; Brown, Marlene; Reeves, Sherman; Davis, Elizabeth A.; Lindstrom, Richard; Hauswirth, Scott; Hamilton, Stephen; Lee, W. Barry; Price, Francis; Price, Marianne; Kelly, Kathleen; Peters, Faye; Shaughnessy, Michael; Steinemann, Thomas; Dupps, B.J.; Meisler, David M.; Mifflin, Mark; Olson, Randal; Aldave, Anthony; Holland, Gary; Mondino, Bartly J.; Rosenwasser, George; Gorovoy, Mark; Dunn, Steven P.; Heidemann, David G.; Terry, Mark; Shamie, Neda; Rosenfeld, Steven I.; Suedekum, Brandon; Hwang, David; Stone, Donald; Chodosh, James; Galentine, Paul G.; Bardenstein, David; Goddard, Katrina; Chin, Hemin; Mannis, Mark; Varma, Rohit; Borecki, Ingrid; Chew, Emily Y.; Haller, Toomas; Mihailov, Evelin; Metspalu, Andres; Wedenoja, Juho; Simpson, Claire L.; Wojciechowski, Robert; Höhn, René; Mirshahi, Alireza; Zeller, Tanja; Pfeiffer, Norbert; Lackner, Karl J.; Donnelly, Peter; Barroso, Ines; Blackwell, Jenefer M.; Bramon, Elvira; Brown, Matthew A.; Casas, Juan P.; Corvin, Aiden; Deloukas, Panos; Duncanson, Audrey; Jankowski, Janusz; Markus, Hugh S.; Mathew, Christopher G.; Palmer, Colin N.A.; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J.; Trembath, Richard C.; Viswanathan, Ananth C.; Wood, Nicholas W.; Spencer, Chris C.A.; Band, Gavin; Bellenguez, Céline; Freeman, Colin; Hellenthal, Garrett; Giannoulatou, Eleni; Pirinen, Matti; Pearson, Richard; Strange, Amy; Su, Zhan; Vukcevic, Damjan; Donnelly, Peter; Langford, Cordelia; Hunt, Sarah E.; Edkins, Sarah; Gwilliam, Rhian; Blackburn, Hannah; Bumpstead, Suzannah J.; Dronov, Serge; Gillman, Matthew; Gray, Emma; Hammond, Naomi; Jayakumar, Alagurevathi; McCann, Owen T.; Liddle, Jennifer; Potter, Simon C.; Ravindrarajah, Radhi; Ricketts, Michelle; Waller, Matthew; Weston, Paul; Widaa, Sara; Whittaker, Pamela; Barroso, Ines; Deloukas, Panos; Mathew, Christopher G.; Blackwell, Jenefer M.; Brown, Matthew A.; Corvin, Aiden; Spencer, Chris C.A.; Bettecken, Thomas; Meitinger, Thomas; Oexle, Konrad; Pirastu, Mario; Portas, Laura; Nag, Abhishek; Williams, Katie M.; Yonova-Doing, Ekaterina; Klein, Ronald; Klein, Barbara E.; Hosseini, S. Mohsen; Paterson, Andrew D.; Genuth, S.; Nathan, D.M.; Zinman, B.; Crofford, O.; Crandall, J.; Reid, M.; Brown-Friday, J.; Engel, S.; Sheindlin, J.; Martinez, H.; Shamoon, H.; Engel, H.; Phillips, M.; Gubitosi-Klug, R.; Mayer, L.; Pendegast, S.; Zegarra, H.; Miller, D.; Singerman, L.; Smith-Brewer, S.; Novak, M.; Quin, J.; Dahms, W.; Genuth, Saul; Palmert, M.; Brillon, D.; Lackaye, M.E.; Kiss, S.; Chan, R.; Reppucci, V.; Lee, T.; Heinemann, M.; Whitehouse, F.; Kruger, D.; Jones, J.K.; McLellan, M.; Carey, J.D.; Angus, E.; Thomas, A.; Galprin, A.; Bergenstal, R.; Johnson, M.; Spencer, M.; Morgan, K.; Etzwiler, D.; Kendall, D.; Aiello, Lloyd Paul; Golden, E.; Jacobson, A.; Beaser, R.; Ganda, O.; Hamdy, O.; Wolpert, H.; Sharuk, G.; Arrigg, P.; Schlossman, D.; Rosenzwieg, J.; Rand, L.; Nathan, D.M.; Larkin, M.; Ong, M.; Godine, J.; Cagliero, E.; Lou, P.; Folino, K.; Fritz, S.; Crowell, S.; Hansen, K.; Gauthier-Kelly, C.; Service, J.; Ziegler, G.; Luttrell, L.; Caulder, S.; Lopes-Virella, M.; Colwell, J.; Soule, J.; Fernandes, J.; Hermayer, K.; Kwon, S.; Brabham, M.; Blevins, A.; Parker, J.; Lee, D.; Patel, N.; Pittman, C.; Lindsey, P.; Bracey, M.; Lee, K.; Nutaitis, M.; Farr, A.; Elsing, S.; Thompson, T.; Selby, J.; Lyons, T.; Yacoub-Wasef, S.; Szpiech, M.; Wood, D.; Mayfield, R.; Molitch, M.; Schaefer, B.; Jampol, L.; Lyon, A.; Gill, M.; Strugula, Z.; Kaminski, L.; Mirza, R.; Simjanoski, E.; Ryan, D.; Kolterman, O.; Lorenzi, G.; Goldbaum, M.; Sivitz, W.; Bayless, M.; Counts, D.; Johnsonbaugh, S.; Hebdon, M.; Salemi, P.; Liss, R.; Donner, T.; Gordon, J.; Hemady, R.; Kowarski, A.; Ostrowski, D.; Steidl, S.; Jones, B.; Herman, W.H.; Martin, C.L.; Pop-Busui, R.; Sarma, A.; Albers, J.; Feldman, E.; Kim, K.; Elner, S.; Comer, G.; Gardner, T.; Hackel, R.; Prusak, R.; Goings, L.; Smith, A.; Gothrup, J.; Titus, P.; Lee, J.; Brandle, M.; Prosser, L.; Greene, D.A.; Stevens, M.J.; Vine, A.K.; Bantle, J.; Wimmergren, N.; Cochrane, A.; Olsen, T.; Steuer, E.; Rath, P.; Rogness, B.; Hainsworth, D.; Goldstein, D.; Hitt, S.; Giangiacomo, J.; Schade, D.S.; Canady, J.L.; Chapin, J.E.; Ketai, L.H.; Braunstein, C.S.; Bourne, P.A.; Schwartz, S.; Brucker, A.; Maschak-Carey, B.J.; Baker, L.; Orchard, T.; Silvers, N.; Ryan, C.; Songer, T.; Doft, B.; Olson, S.; Bergren, R.L.; Lobes, L.; Rath, P. Paczan; Becker, D.; Rubinstein, D.; Conrad, P.W.; Yalamanchi, S.; Drash, A.; Morrison, A.; Bernal, M.L.; Vaccaro-Kish, J.; Malone, J.; Pavan, P.R.; Grove, N.; Iyer, M.N.; Burrows, A.F.; Tanaka, E.A.; Gstalder, R.; Dagogo-Jack, S.; Wigley, C.; Ricks, H.; Kitabchi, A.; Murphy, M.B.; Moser, S.; Meyer, D.; Iannacone, A.; Chaum, E.; Yoser, S.; Bryer-Ash, M.; Schussler, S.; Lambeth, H.; Raskin, P.; Strowig, S.; Zinman, B.; Barnie, A.; Devenyi, R.; Mandelcorn, M.; Brent, M.; Rogers, S.; Gordon, A.; Palmer, J.; Catton, S.; Brunzell, J.; Wessells, H.; de Boer, I.H.; Hokanson, J.; Purnell, J.; Ginsberg, J.; Kinyoun, J.; Deeb, S.; Weiss, M.; Meekins, G.; Distad, J.; Van Ottingham, L.; Dupre, J.; Harth, J.; Nicolle, D.; Driscoll, M.; Mahon, J.; Canny, C.; May, M.; Lipps, J.; Agarwal, A.; Adkins, T.; Survant, L.; Pate, R.L.; Munn, G.E.; Lorenz, R.; Feman, S.; White, N.; Levandoski, L.; Boniuk, I.; Grand, G.; Thomas, M.; Joseph, D.D.; Blinder, K.; Shah, G.; Boniuk; Burgess; Santiago, J.; Tamborlane, W.; Gatcomb, P.; Stoessel, K.; Taylor, K.; Goldstein, J.; Novella, S.; Mojibian, H.; Cornfeld, D.; Lima, J.; Bluemke, D.; Turkbey, E.; van der Geest, R.J.; Liu, C.; Malayeri, A.; Jain, A.; Miao, C.; Chahal, H.; Jarboe, R.; Maynard, J.; Gubitosi-Klug, R.; Quin, J.; Gaston, P.; Palmert, M.; Trail, R.; Dahms, W.; Lachin, J.; Cleary, P.; Backlund, J.; Sun, W.; Braffett, B.; Klumpp, K.; Chan, K.; Diminick, L.; Rosenberg, D.; Petty, B.; Determan, A.; Kenny, D.; Rutledge, B.; Younes, Naji; Dews, L.; Hawkins, M.; Cowie, C.; Fradkin, J.; Siebert, C.; Eastman, R.; Danis, R.; Gangaputra, S.; Neill, S.; Davis, M.; Hubbard, L.; Wabers, H.; Burger, M.; Dingledine, J.; Gama, V.; Sussman, R.; Steffes, M.; Bucksa, J.; Nowicki, M.; Chavers, B.; O’Leary, D.; Polak, J.; Harrington, A.; Funk, L.; Crow, R.; Gloeb, B.; Thomas, S.; O’Donnell, C.; Soliman, E.; Zhang, Z.M.; Prineas, R.; Campbell, C.; Ryan, C.; Sandstrom, D.; Williams, T.; Geckle, M.; Cupelli, E.; Thoma, F.; Burzuk, B.; Woodfill, T.; Low, P.; Sommer, C.; Nickander, K.; Budoff, M.; Detrano, R.; Wong, N.; Fox, M.; Kim, L.; Oudiz, R.; Weir, G.; Espeland, M.; Manolio, T.; Rand, L.; Singer, D.; Stern, M.; Boulton, A.E.; Clark, C.; D’Agostino, R.; Lopes-Virella, M.; Garvey, W.T.; Lyons, T.J.; Jenkins, A.; Virella, G.; Jaffa, A.; Carter, Rickey; Lackland, D.; Brabham, M.; McGee, D.; Zheng, D.; Mayfield, R.K.; Boright, A.; Bull, S.; Sun, L.; Scherer, S.; Zinman, B.; Natarajan, R.; Miao, F.; Zhang, L.; Chen;, Z.; Nathan, D.M.; Makela, Kari-Matti; Lehtimaki, Terho; Kahonen, Mika; Raitakari, Olli; Yoshimura, Nagahisa; Matsuda, Fumihiko; Chen, Li Jia; Pang, Chi Pui; Yip, Shea Ping; Yap, Maurice K.H.; Meguro, Akira; Mizuki, Nobuhisa; Inoko, Hidetoshi; Foster, Paul J.; Zhao, Jing Hua; Vithana, Eranga; Tai, E-Shyong; Fan, Qiao; Xu, Liang; Campbell, Harry; Fleck, Brian; Rudan, Igor; Aung, Tin; Hofman, Albert; Uitterlinden, André G.; Bencic, Goran; Khor, Chiea-Chuen; Forward, Hannah; Pärssinen, Olavi; Mitchell, Paul; Rivadeneira, Fernando; Hewitt, Alex W.; Williams, Cathy; Oostra, Ben A.; Teo, Yik-Ying; Hammond, Christopher J.; Stambolian, Dwight; Mackey, David A.; Klaver, Caroline C.W.; Wong, Tien-Yin; Saw, Seang-Mei; Baird, Paul N.

    2013-01-01

    Refractive errors are common eye disorders of public health importance worldwide. Ocular axial length (AL) is the major determinant of refraction and thus of myopia and hyperopia. We conducted a meta-analysis of genome-wide association studies for AL, combining 12,531 Europeans and 8,216 Asians. We identified eight genome-wide significant loci for AL (RSPO1, C3orf26, LAMA2, GJD2, ZNRF3, CD55, MIP, and ALPPL2) and confirmed one previously reported AL locus (ZC3H11B). Of the nine loci, five (LAMA2, GJD2, CD55, ALPPL2, and ZC3H11B) were associated with refraction in 18 independent cohorts (n = 23,591). Differential gene expression was observed for these loci in minus-lens-induced myopia mouse experiments and human ocular tissues. Two of the AL genes, RSPO1 and ZNRF3, are involved in Wnt signaling, a pathway playing a major role in the regulation of eyeball size. This study provides evidence of shared genes between AL and refraction, but importantly also suggests that these traits may have unique pathways. PMID:24144296

  19. Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

    Science.gov (United States)

    Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

    2009-11-01

    Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

  20. Functional traits help predict post-disturbance demography of tropical trees.

    Science.gov (United States)

    Flores, Olivier; Hérault, Bruno; Delcamp, Matthieu; Garnier, Éric; Gourlet-Fleury, Sylvie

    2014-01-01

    How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.

  1. An international collaborative family-based whole genome quantitative trait linkage scan for myopic refractive error

    DEFF Research Database (Denmark)

    Abbott, Diana; Li, Yi-Ju; Guggenheim, Jeremy A

    2012-01-01

    To investigate quantitative trait loci linked to refractive error, we performed a genome-wide quantitative trait linkage analysis using single nucleotide polymorphism markers and family data from five international sites....

  2. Kernel-based whole-genome prediction of complex traits: a review.

    Science.gov (United States)

    Morota, Gota; Gianola, Daniel

    2014-01-01

    Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  3. Kernel-based whole-genome prediction of complex traits: a review

    Directory of Open Access Journals (Sweden)

    Gota eMorota

    2014-10-01

    Full Text Available Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways, thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  4. Basic traits predict the prevalence of personality disorder across the life span: the example of psychopathy.

    Science.gov (United States)

    Vachon, David D; Lynam, Donald R; Widiger, Thomas A; Miller, Joshua D; McCrae, Robert R; Costa, Paul T

    2013-05-01

    Personality disorders (PDs) may be better understood in terms of dimensions of general personality functioning rather than as discrete categorical conditions. Personality-trait descriptions of PDs are robust across methods and settings, and PD assessments based on trait measures show good construct validity. The study reported here extends research showing that basic traits (e.g., impulsiveness, warmth, straightforwardness, modesty, and deliberation) can re-create the epidemiological characteristics associated with PDs. Specifically, we used normative changes in absolute trait levels to simulate age-related differences in the prevalence of psychopathy in a forensic setting. Results demonstrated that trait information predicts the rate of decline for psychopathy over the life span; discriminates the decline of psychopathy from that of a similar disorder, antisocial PD; and accurately predicts the differential decline of subfactors of psychopathy. These findings suggest that basic traits provide a parsimonious account of PD prevalence across the life span.

  5. Combining a weed traits database with a population dynamics model predicts shifts in weed communities.

    Science.gov (United States)

    Storkey, J; Holst, N; Bøjer, O Q; Bigongiali, F; Bocci, G; Colbach, N; Dorner, Z; Riemens, M M; Sartorato, I; Sønderskov, M; Verschwele, A

    2015-04-01

    A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated 'fitness contours' (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

  6. Mapping Quantitative Trait Loci (QTL for Resistance to Late Blight in Tomato

    Directory of Open Access Journals (Sweden)

    Dilip R. Panthee

    2017-07-01

    Full Text Available Late blight caused by Phytophthora infestans (Montagne, Bary is a devastating disease of tomato worldwide. There are three known major genes, Ph-1, Ph-2, and Ph-3, conferring resistance to late blight. In addition to these three genes, it is also believed that there are additional factors or quantitative trait loci (QTL conferring resistance to late blight. Precise molecular mapping of all those major genes and potential QTL is important in the development of suitable molecular markers and hence, marker-assisted selection (MAS. The objective of the present study was to map the genes and QTL associated with late blight resistance in a tomato population derived from intra-specific crosses. To achieve this objective, a population, derived from the crossings of NC 1CELBR × Fla. 7775, consisting of 250 individuals at F2 and F2-derived families, were evaluated in replicated trials. These were conducted at Mountain Horticultural Crops Reseach & Extension Center (MHCREC at Mills River, NC, and Mountain Research Staion (MRS at Waynesville, NC in 2011, 2014, and 2015. There were two major QTL associated with late blight resistance located on chromosomes 9 and 10 with likelihood of odd (LOD scores of more than 42 and 6, explaining 67% and 14% of the total phenotypic variation, respectively. The major QTLs are probably caused by the Ph-2 and Ph-3 genes. Furthermore, there was a minor QTL on chromosomes 12, which has not been reported before. This minor QTL may be novel and may be worth investigating further. Source of resistance to Ph-2, Ph-3, and this minor QTL traces back to line L3707, or Richter’s Wild Tomato. The combination of major genes and minor QTL may provide a durable resistance to late blight in tomato.

  7. 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.

  8. Predicting Risky Sexual Behavior: the Unique and Interactive Roles of Childhood Conduct Disorder Symptoms and Callous-Unemotional Traits.

    Science.gov (United States)

    Anderson, Sarah L; Zheng, Yao; McMahon, Robert J

    2017-08-01

    Conduct disorder (CD) symptoms and callous-unemotional (CU) traits have been shown to be uniquely associated with risky sexual behavior (RSB) in adolescence and early adulthood, yet their interactive role in predicting RSB remains largely unknown. This study aimed to investigate the predictive value of CD symptoms and CU traits, as well as their interaction, on several RSB outcomes in adolescence and early adulthood. A total of 683 participants (41.7 % female, 47.4 % African American) were followed annually and self-reported age of first sexual intercourse, frequency of condom use, pregnancy, contraction of sexually transmitted infections, and engagement in sexual solicitation from grade 7 to 2-years post-high school. CD symptoms predicted age of first sexual intercourse, condom use, and sexual solicitation. CU traits predicted age of first sexual intercourse and pregnancy. Their interaction predicted a composite score of these RSBs such that CD symptoms positively predicted the composite score among those with high levels of CU traits but not among those with low levels of CU traits. The current findings provide information regarding the importance of both CD symptoms and CU traits in understanding adolescent and early adulthood RSB, as well as the benefits of examining multiple RSB outcomes during this developmental period. These findings have implications for the development and implementation of preventive efforts to target these risky behaviors among adolescents and young adults.

  9. 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

  10. Emotional intelligence predicts peer-rated social competence above and beyond personality traits

    Directory of Open Access Journals (Sweden)

    Dorota Szczygieł

    2016-12-01

    Full Text Available Background This study investigated the relationship between trait emotional intelligence (EI and social competences (SC, which determine effective functioning in three types of social situations: intimate situations, situations of social exposure and situations requiring self-assertion. Social competences were assessed using a peer nomination method. It was hypothesized that trait EI predicts SC above and beyond personality traits. Participants and procedure Data were collected from among 111 adolescents (46.95% girls. The study was conducted among five classes from three public high schools. Participants first completed the Personality Inventory NEO-FFI and the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF. Subsequently, the descriptions of three different persons were presented to the participants. Each description concerned one of the SC: intimate competence, social exposure competence and assertive competence. Participants were asked to nominate three classmates who suited each description best. Results A series of hierarchical regression analyses was performed. Personality traits and trait EI were regressed on each competence. Analyses involved two-step hierarchical regressions, entering personality traits at step 1 and adding trait EI at step 2. The results demonstrated that personality traits explained a substantial portion of the variance in each SC. Beyond these variables, trait EI was significant as a predictor of nominations for each SC, explaining an additional amount of the unique variance. Conclusions The results complement existing evidence that trait EI contributes to successful social functioning. The relationships between trait EI and SC remained statistically significant even after controlling for Big Five variance. The results demonstrate incremental validity of trait EI over and above personality traits.

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

    Indian Academy of Sciences (India)

    2014-08-19

    Aug 19, 2014 ... 2Seed Management Station of Jilin Province, Changchun 130062, Jilin, ... daidzein (DC), genistein (GeC), glycitein (GlC) and total isoflavone contents (TIC) in ..... ing and height) and quality (oil and protein content) traits.

  12. Inter-simple sequence repeat (ISSR) loci mapping in the genome of perennial ryegrass

    DEFF Research Database (Denmark)

    Pivorienė, O; Pašakinskienė, I; Brazauskas, G

    2008-01-01

    The aim of this study was to identify and characterize new ISSR markers and their loci in the genome of perennial ryegrass. A subsample of the VrnA F2 mapping family of perennial ryegrass comprising 92 individuals was used to develop a linkage map including inter-simple sequence repeat markers...... demonstrated a 70% similarity to the Hordeum vulgare germin gene GerA. Inter-SSR mapping will provide useful information for gene targeting, quantitative trait loci mapping and marker-assisted selection in perennial ryegrass....

  13. QTL detection and elite alleles mining for stigma traits in Oryza sativa by association mapping

    Directory of Open Access Journals (Sweden)

    Xiaojing Dang

    2016-08-01

    Full Text Available Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR markers. By combining phenotypic and genotypic data, a genome-wide association (GWA map was generated. Large phenotypic variations in stigma length (STL, stigma brush-shaped part length (SBPL and stigma non-brush-shaped part length (SNBPL were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future.

  14. 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.

  15. Does genetic diversity predict health in humans?

    Directory of Open Access Journals (Sweden)

    Hanne C Lie

    2009-07-01

    Full Text Available Genetic diversity, especially at genes important for immune functioning within the Major Histocompatibility Complex (MHC, has been associated with fitness-related traits, including disease resistance, in many species. Recently, genetic diversity has been associated with mate preferences in humans. Here we asked whether these preferences are adaptive in terms of obtaining healthier mates. We investigated whether genetic diversity (heterozygosity and standardized mean d(2 at MHC and nonMHC microsatellite loci, predicted health in 153 individuals. Individuals with greater allelic diversity (d(2 at nonMHC loci and at one MHC locus, linked to HLA-DRB1, reported fewer symptoms over a four-month period than individuals with lower d(2. In contrast, there were no associations between MHC or nonMHC heterozygosity and health. NonMHC-d(2 has previously been found to predict male preferences for female faces. Thus, the current findings suggest that nonMHC diversity may play a role in both natural and sexual selection acting on human populations.

  16. Identifying QTL for fur quality traits in mink (Neovison vison)

    DEFF Research Database (Denmark)

    Thirstrup, Janne Pia; Anistoroaei, Razvan Marian; Guldbrandtsen, Bernt

    2012-01-01

    Mapping of quantitative trait loci (QTL) affecting fur quality traits (guard hair length, guard hair thikness, and density of woll) was performed in a 3-generation population (F2-design). In the parental generation, Nordic wild mink were crossed reciprocally with American short nap mink. Twenty o...

  17. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

    DEFF Research Database (Denmark)

    Webb, Thomas R; Erdmann, Jeanette; Stirrups, Kathleen E

    2017-01-01

    %) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control...... subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study...

  18. 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.

  19. An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity

    Directory of Open Access Journals (Sweden)

    Struchalin Maksim V

    2012-01-01

    Full Text Available Abstract Background Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010 developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. Results In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. Conclusions Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.

  20. Predicting human height by Victorian and genomic methods.

    Science.gov (United States)

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-08-01

    In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.

  1. 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

  2. Interactions Between SNP Alleles at Multiple Loci and Variation in Skin Pigmentation in 122 Caucasians

    Directory of Open Access Journals (Sweden)

    Sumiko Anno

    2007-01-01

    Full Text Available This study was undertaken to clarify the molecular basis for human skin color variation and the environmental adaptability to ultraviolet irradiation, with the ultimate goal of predicting the impact of changes in future environments on human health risk. One hundred twenty-two Caucasians living in Toledo, Ohio participated. Back and cheek skin were assayed for melanin as a quantitative trait marker. Buccal cell samples were collected and used for DNA extraction. DNA was used for SNP genotyping using the Masscode™ system, which entails two-step PCR amplification and a platform chemistry which allows cleavable mass spectrometry tags. The results show gene-gene interaction between SNP alleles at multiple loci (not necessarily on the same chromosome contributes to inter-individual skin color variation while suggesting a high probability of linkage disequilibrium. Confirmation of these findings requires further study with other ethic groups to analyze the associations between SNP alleles at multiple loci and human skin color variation. Our overarching goal is to use remote sensing data to clarify the interaction between atmospheric environments and SNP allelic frequency and investigate human adaptability to ultraviolet irradiation. Such information should greatly assist in the prediction of the health effects of future environmental changes such as ozone depletion and increased ultraviolet exposure. If such health effects are to some extent predictable, it might be possible to prepare for such changes in advance and thus reduce the extent of their impact.

  3. Confronting species distribution model predictions with species functional traits.

    Science.gov (United States)

    Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M

    2016-02-01

    Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.

  4. A meta-analytic investigation of conscientiousness in the prediction of job performance: examining the intercorrelations and the incremental validity of narrow traits.

    Science.gov (United States)

    Dudley, Nicole M; Orvis, Karin A; Lebiecki, Justin E; Cortina, José M

    2006-01-01

    Researchers of broad and narrow traits have debated whether narrow traits are important to consider in the prediction of job performance. Because personality-performance relationship meta-analyses have focused almost exclusively on the Big Five, the predictive power of narrow traits has not been adequately examined. In this study, the authors address this question by meta-analytically examining the degree to which the narrow traits of conscientiousness predict above and beyond global conscientiousness. Results suggest that narrow traits do incrementally predict performance above and beyond global conscientiousness, yet the degree to which they contribute depends on the particular performance criterion and occupation in question. Overall, the results of this study suggest that there are benefits to considering the narrow traits of conscientiousness in the prediction of performance. (c) 2006 APA, all rights reserved.

  5. Species’ traits help predict small mammal responses to habitat homogenization by an invasive grass

    Science.gov (United States)

    Ceradini, Joseph P.; Chalfoun, Anna D.

    2017-01-01

    Invasive plants can negatively affect native species, however, the strength, direction, and shape of responses may vary depending on the type of habitat alteration and the natural history of native species. To prioritize conservation of vulnerable species, it is therefore critical to effectively predict species’ responses to invasive plants, which may be facilitated by a framework based on species’ traits. We studied the population and community responses of small mammals and changes in habitat heterogeneity across a gradient of cheatgrass (Bromus tectorum) cover, a widespread invasive plant in North America. We live-trapped small mammals over two summers and assessed the effect of cheatgrass on native small mammal abundance, richness, and species-specific and trait-based occupancy, while accounting for detection probability and other key habitat elements. Abundance was only estimated for the most common species, deer mice (Peromyscus maniculatus). All species were pooled for the trait-based occupancy analysis to quantify the ability of small mammal traits (habitat association, mode of locomotion, and diet) to predict responses to cheatgrass invasion. Habitat heterogeneity decreased with cheatgrass cover. Deer mouse abundance increased marginally with cheatgrass. Species richness did not vary with cheatgrass, however, pocket mouse (Perognathus spp.) and harvest mouse (Reithrodontomys spp.) occupancy tended to decrease and increase, respectively, with cheatgrass cover, suggesting a shift in community composition. Cheatgrass had little effect on occupancy for deer mice, 13-lined ground squirrels (Spermophilus tridecemlineatus), and Ord's kangaroo rat (Dipodomys ordii). Species’ responses to cheatgrass primarily corresponded with our a priori predictions based on species’ traits. The probability of occupancy varied significantly with a species’ habitat association but not with diet or mode of locomotion. When considered within the context of a rapid

  6. Synaptic Transmission Optimization Predicts Expression Loci of Long-Term Plasticity.

    Science.gov (United States)

    Costa, Rui Ponte; Padamsey, Zahid; D'Amour, James A; Emptage, Nigel J; Froemke, Robert C; Vogels, Tim P

    2017-09-27

    Long-term modifications of neuronal connections are critical for reliable memory storage in the brain. However, their locus of expression-pre- or postsynaptic-is highly variable. Here we introduce a theoretical framework in which long-term plasticity performs an optimization of the postsynaptic response statistics toward a given mean with minimal variance. Consequently, the state of the synapse at the time of plasticity induction determines the ratio of pre- and postsynaptic modifications. Our theory explains the experimentally observed expression loci of the hippocampal and neocortical synaptic potentiation studies we examined. Moreover, the theory predicts presynaptic expression of long-term depression, consistent with experimental observations. At inhibitory synapses, the theory suggests a statistically efficient excitatory-inhibitory balance in which changes in inhibitory postsynaptic response statistics specifically target the mean excitation. Our results provide a unifying theory for understanding the expression mechanisms and functions of long-term synaptic transmission plasticity. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Do personality traits predict first onset in depressive and bipolar disorder?

    DEFF Research Database (Denmark)

    Christensen, Maj Vinberg; Kessing, Lars Vedel

    2006-01-01

    The aim was to investigate whether personality traits predict onset of the first depressive or manic episode (the vulnerability hypothesis) and whether personality might be altered by the mood disorder (the scar hypothesis). A systematic review of population-based and high-risk studies concerning...... personality traits and affective disorder in adults was conducted. Nine cross-sectional high-risk studies, seven longitudinal high-risk studies and nine longitudinal population-based studies were found. Most studies support the vulnerability hypothesis and there is evidence that neuroticism is a premorbid...... risk factor for developing depressive disorder. The evidence for the scar hypothesis is sparse, but the studies with the strongest design showed evidence for both hypotheses. Only few studies of bipolar disorder were found and the association between personality traits and bipolar disorder is unclear...

  8. Predicting effects of noncoding variants with deep learning-based sequence model.

    Science.gov (United States)

    Zhou, Jian; Troyanskaya, Olga G

    2015-10-01

    Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

  9. Personality traits predict job stress, depression and anxiety among junior physicians.

    Science.gov (United States)

    Gramstad, Thomas Olsen; Gjestad, Rolf; Haver, Brit

    2013-11-09

    High levels of stress and deteriorating mental health among medical students are commonly reported. In Bergen, Norway, we explored the impact of personality traits measured early in their curriculum on stress reactions and levels of depression and anxiety symptoms as junior physicians following graduation. Medical students (n = 201) from two classes participated in a study on personality traits and mental health early in the curriculum. A questionnaire measuring personality traits (Basic Character Inventory (BCI)) was used during their third undergraduate year. BCI assesses four personality traits: neuroticism, extroversion, conscientiousness and reality weakness. Questionnaires measuring mental health (Hospital Anxiety and Depression Scale (HADS) and Symptom Checklist 25 (SCL-25)), and stress (Perceived Medical School Stress (PMSS)) were used during their third and sixth undergraduate year. During postgraduate internship, Cooper's Job Stress Questionnaire (CJSQ) was used to measure perceived job stress, while mental health and stress reactions were reassessed using HADS and SCL-25. Extroversion had the highest mean value (5.11) among the total group of participants, while reality weakness had the lowest (1.51). Neuroticism and reality weakness were related to high levels of perceived job stress (neuroticism r = .19, reality weakness r = .17) as well as higher levels of anxiety symptoms (neuroticism r = .23, reality weakness r = .33) and symptoms of depression (neuroticism r = .21, reality weakness r = .36) during internship. Neuroticism indirectly predicted stress reactions and levels of depression and anxiety symptoms. These relations were mediated by perceived job stress, while reality weakness predicted these mental health measures directly. Extroversion, on the other hand, protected against symptoms of depression (r = -.20). Furthermore, females reported higher levels of job stress than males (difference = 7.52). Certain personality traits measured early in

  10. Understanding reproducibility of human IVF traits to predict next IVF cycle outcome.

    Science.gov (United States)

    Wu, Bin; Shi, Juanzi; Zhao, Wanqiu; Lu, Suzhen; Silva, Marta; Gelety, Timothy J

    2014-10-01

    Evaluating the failed IVF cycle often provides useful prognostic information. Before undergoing another attempt, patients experiencing an unsuccessful IVF cycle frequently request information about the probability of future success. Here, we introduced the concept of reproducibility and formulae to predict the next IVF cycle outcome. The experimental design was based on the retrospective review of IVF cycle data from 2006 to 2013 in two different IVF centers and statistical analysis. The reproducibility coefficients (r) of IVF traits including number of oocytes retrieved, oocyte maturity, fertilization, embryo quality and pregnancy were estimated using the interclass correlation coefficient between the repeated IVF cycle measurements for the same patient by variance component analysis. The formulae were designed to predict next IVF cycle outcome. The number of oocytes retrieved from patients and their fertilization rate had the highest reproducibility coefficients (r = 0.81 ~ 0.84), which indicated a very close correlation between the first retrieval cycle and subsequent IVF cycles. Oocyte maturity and number of top quality embryos had middle level reproducibility (r = 0.38 ~ 0.76) and pregnancy rate had a relative lower reproducibility (r = 0.23 ~ 0.27). Based on these parameters, the next outcome for these IVF traits might be accurately predicted by the designed formulae. The introduction of the concept of reproducibility to our human IVF program allows us to predict future IVF cycle outcomes. The traits of oocyte numbers retrieved, oocyte maturity, fertilization, and top quality embryos had higher or middle reproducibility, which provides a basis for accurate prediction of future IVF outcomes. Based on this prediction, physicians may counsel their patients or change patient's stimulation plans, and laboratory embryologists may improve their IVF techniques accordingly.

  11. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

    DEFF Research Database (Denmark)

    Dupuis, Josée; Langenberg, Claudia; Prokopenko, Inga

    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...... to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA......2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell...

  12. Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs.

    Science.gov (United States)

    Camarinha-Silva, Amelia; Maushammer, Maria; Wellmann, Robin; Vital, Marius; Preuss, Siegfried; Bennewitz, Jörn

    2017-07-01

    The aim of the present study was to analyze the interplay between gastrointestinal tract (GIT) microbiota, host genetics, and complex traits in pigs using extended quantitative-genetic methods. The study design consisted of 207 pigs that were housed and slaughtered under standardized conditions, and phenotyped for daily gain, feed intake, and feed conversion rate. The pigs were genotyped with a standard 60 K SNP chip. The GIT microbiota composition was analyzed by 16S rRNA gene amplicon sequencing technology. Eight from 49 investigated bacteria genera showed a significant narrow sense host heritability, ranging from 0.32 to 0.57. Microbial mixed linear models were applied to estimate the microbiota variance for each complex trait. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota composition were used to predict the complex traits using genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods, respectively. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, in addition to SNP data, microbiota abundances are an informative source of complex trait predictions. Since the pig is a well-suited animal for modeling the human digestive tract, M-BLUP, in addition to G-BLUP, might be beneficial for predicting human predispositions to some diseases, and, consequently, for preventative and personalized medicine. Copyright © 2017 by the Genetics Society of America.

  13. A recoding scheme for X-linked and pseudoautosomal loci to be used with computer programs for autosomal LOD-score analysis.

    Science.gov (United States)

    Strauch, Konstantin; Baur, Max P; Wienker, Thomas F

    2004-01-01

    We present a recoding scheme that allows for a parametric multipoint X-chromosomal linkage analysis of dichotomous traits in the context of a computer program for autosomes that can use trait models with imprinting. Furthermore, with this scheme, it is possible to perform a joint multipoint analysis of X-linked and pseudoautosomal loci. It is required that (1) the marker genotypes of all female nonfounders are available and that (2) there are no male nonfounders who have daughters in the pedigree. The second requirement does not apply if the trait locus is pseudoautosomal. The X-linked marker loci are recorded by adding a dummy allele to the males' hemizygous genotypes. For modelling an X-linked trait locus, five different liability classes are defined, in conjunction with a paternal imprinting model for male nonfounders. The formulation aims at the mapping of a diallelic trait locus relative to an arbitrary number of codominant markers with known genetic distances, in cases where a program for a genuine X-chromosomal analysis is not available. 2004 S. Karger AG, Basel.

  14. Fine mapping and candidate gene prediction of a pleiotropic quantitative trait locus for yield-related trait in Zea mays.

    Directory of Open Access Journals (Sweden)

    Ruixiang Liu

    Full Text Available The yield of maize grain is a highly complex quantitative trait that is controlled by multiple quantitative trait loci (QTLs with small effects, and is frequently influenced by multiple genetic and environmental factors. Thus, it is challenging to clone a QTL for grain yield in the maize genome. Previously, we identified a major QTL, qKNPR6, for kernel number per row (KNPR across multiple environments, and developed two nearly isogenic lines, SL57-6 and Ye478, which differ only in the allelic constitution at the short segment harboring the QTL. Recently, qKNPR6 was re-evaluated in segregating populations derived from SL57-6×Ye478, and was narrowed down to a 2.8 cM interval, which explained 56.3% of the phenotypic variance of KNPR in 201 F(2∶3 families. The QTL simultaneously affected ear length, kernel weight and grain yield. Furthermore, a large F(2 population with more than 12,800 plants, 191 recombinant chromosomes and 10 overlapping recombinant lines placed qKNPR6 into a 0.91 cM interval corresponding to 198Kb of the B73 reference genome. In this region, six genes with expressed sequence tag (EST evidence were annotated. The expression pattern and DNA diversity of the six genes were assayed in Ye478 and SL57-6. The possible candidate gene and the pathway involved in inflorescence development were discussed.

  15. Trait Anticipatory Pleasure Predicts Effort Expenditure for Reward.

    Directory of Open Access Journals (Sweden)

    Joachim T Geaney

    Full Text Available Research in motivation and emotion has been increasingly influenced by the perspective that processes underpinning the motivated approach of rewarding goals are distinct from those underpinning enjoyment during reward consummation. This distinction recently inspired the construction of the Temporal Experience of Pleasure Scale (TEPS, a self-report measure that distinguishes trait anticipatory pleasure (pre-reward feelings of desire from consummatory pleasure (feelings of enjoyment and gratification upon reward attainment. In a university community sample (N = 97, we examined the TEPS subscales as predictors of (1 the willingness to expend effort for monetary rewards, and (2 affective responses to a pleasant mood induction procedure. Results showed that both anticipatory pleasure and a well-known trait measure of reward motivation predicted effort-expenditure for rewards when the probability of being rewarded was relatively low. Against expectations, consummatory pleasure was unrelated to induced pleasant affect. Taken together, our findings provide support for the validity of the TEPS anticipatory pleasure scale, but not the consummatory pleasure scale.

  16. Prosocial Personality Traits Differentially Predict Egalitarianism, Generosity, and Reciprocity in Economic Games.

    Science.gov (United States)

    Zhao, Kun; Ferguson, Eamonn; Smillie, Luke D

    2016-01-01

    Recent research has highlighted the role of prosocial personality traits-agreeableness and honesty-humility-in egalitarian distributions of wealth in the dictator game. Expanding on these findings, we ran two studies to examine individual differences in two other forms of prosociality-generosity and reciprocity-with respect to two major models of personality, the Big Five and the HEXACO. Participants (combined N = 560) completed a series of economic games in which allocations in the dictator game were compared with those in the generosity game, a non-constant-sum wealth distribution task where proposers with fixed payoffs selected the size of their partner's payoff ("generosity"). We further examined positive and negative reciprocity by manipulating a partner's previous move ("reciprocity"). Results showed clear evidence of both generosity and positive reciprocity in social preferences, with allocations to a partner greater in the generosity game than in the dictator game, and greater still when a player had been previously assisted by their partner. There was also a consistent interaction with gender, whereby men were more generous when this was costless and women were more egalitarian overall. Furthermore, these distinct forms of prosociality were differentially predicted by personality traits, in line with the core features of these traits and the theoretical distinctions between them. HEXACO honesty-humility predicted dictator, but not generosity allocations, while traits capturing tendencies toward irritability and anger predicted lower generosity, but not dictator allocations. In contrast, the politeness-but not compassion-aspect of Big Five agreeableness was uniquely and broadly associated with prosociality across all games. These findings support the discriminant validity between related prosocial constructs, and have important implications for understanding the motives and mechanisms taking place within economic games.

  17. Personality traits and individual differences predict threat-induced changes in postural control.

    Science.gov (United States)

    Zaback, Martin; Cleworth, Taylor W; Carpenter, Mark G; Adkin, Allan L

    2015-04-01

    This study explored whether specific personality traits and individual differences could predict changes in postural control when presented with a height-induced postural threat. Eighty-two healthy young adults completed questionnaires to assess trait anxiety, trait movement reinvestment (conscious motor processing, movement self-consciousness), physical risk-taking, and previous experience with height-related activities. Tests of static (quiet standing) and anticipatory (rise to toes) postural control were completed under low and high postural threat conditions. Personality traits and individual differences significantly predicted height-induced changes in static, but not anticipatory postural control. Individuals less prone to taking physical risks were more likely to lean further away from the platform edge and sway at higher frequencies and smaller amplitudes. Individuals more prone to conscious motor processing were more likely to lean further away from the platform edge and sway at larger amplitudes. Individuals more self-conscious about their movement appearance were more likely to sway at smaller amplitudes. Evidence is also provided that relationships between physical risk-taking and changes in static postural control are mediated through changes in fear of falling and physiological arousal. Results from this study may have indirect implications for balance assessment and treatment; however, further work exploring these factors in patient populations is necessary. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. 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

  19. 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.

  20. Panic disorder and health-related quality of life: the predictive roles of anxiety sensitivity and trait anxiety.

    Science.gov (United States)

    Kang, Eun-Ho; Kim, Borah; Choe, Ah Young; Lee, Jun-Yeob; Choi, Tai Kiu; Lee, Sang-Hyuk

    2015-01-30

    Panic disorder (PD) is a very common anxiety disorder and is often a chronic disabling condition. However, little is known about the factors that predict health-related quality of life (HRQOL) other than sociodemographic factors and illness-related symptomatology that explain HRQOL in only small to modest degrees. This study explored whether anxiety-related individual traits including anxiety sensitivity and trait anxiety can predict independently HRQOL in panic patients. Patients with panic disorder with or without agoraphobia (N=230) who met the diagnostic criteria in the Structured Clinical Interview for DSM-IV were recruited. Stepwise regression analysis was performed to determine the factors that predict HRQOL in panic disorder. HRQOL was assessed by the 36-item Short-Form Health Survey (SF-36). Anxiety sensitivity was an independent predictor of bodily pain and social functioning whereas trait anxiety independently predicted all of the eight domains of the SF-36. Our data suggests that the assessment of symptomatology as well as individual anxiety-related trait should be included in the evaluation of HRQOL in panic patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

    Science.gov (United States)

    Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

    2018-03-01

    Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

  2. Spontaneous eye movements and trait empathy predict vicarious learning of fear.

    Science.gov (United States)

    Kleberg, Johan L; Selbing, Ida; Lundqvist, Daniel; Hofvander, Björn; Olsson, Andreas

    2015-12-01

    Learning to predict dangerous outcomes is important to survival. In humans, this kind of learning is often transmitted through the observation of others' emotional responses. We analyzed eye movements during an observational/vicarious fear learning procedure, in which healthy participants (N=33) watched another individual ('learning model') receiving aversive treatment (shocks) paired with a predictive conditioned stimulus (CS+), but not a control stimulus (CS-). Participants' gaze pattern towards the model differentiated as a function of whether the CS was predictive or not of a shock to the model. Consistent with our hypothesis that the face of a conspecific in distress can act as an unconditioned stimulus (US), we found that the total fixation time at a learning model's face increased when the CS+ was shown. Furthermore, we found that the total fixation time at the CS+ during learning predicted participants' conditioned responses (CRs) at a later test in the absence of the model. We also demonstrated that trait empathy was associated with stronger CRs, and that autistic traits were positively related to autonomic reactions to watching the model receiving the aversive treatment. Our results have implications for both healthy and dysfunctional socio-emotional learning. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality.

    Directory of Open Access Journals (Sweden)

    Johannes Raffler

    2015-09-01

    Full Text Available Genome-wide association studies with metabolic traits (mGWAS uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3. Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13, pulmonary hypertension (CPS1, and ischemic stroke (XYLB. By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular

  4. Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

    Directory of Open Access Journals (Sweden)

    Jinliang Yang

    2017-09-01

    Full Text Available Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

  5. Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize.

    Science.gov (United States)

    Yang, Jinliang; Mezmouk, Sofiane; Baumgarten, Andy; Buckler, Edward S; Guill, Katherine E; McMullen, Michael D; Mumm, Rita H; Ross-Ibarra, Jeffrey

    2017-09-01

    Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

  6. 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.

  7. Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

    Institute of Scientific and Technical Information of China (English)

    熊敏; 王石平; 张启发

    2002-01-01

    Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.

  8. Genome-wide Association Study for Calving Traits in Danish and Swedish Holstein Cattle

    DEFF Research Database (Denmark)

    Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø

    2011-01-01

    A total of 22 quantitative trait loci (QTL) were detected on 19 chromosomes for direct and maternal calving traits in cattle using a genome-wide association study. Calving performance is affected by the genotypes of both the calf (direct effect) and dam (maternal effect). To identify the QTL cont...

  9. Genome-wide association genetics of an adaptive trait in lodgepole pine.

    Science.gov (United States)

    Parchman, Thomas L; Gompert, Zachariah; Mudge, Joann; Schilkey, Faye D; Benkman, Craig W; Buerkle, C Alex

    2012-06-01

    Pine cones that remain closed and retain seeds until fire causes the cones to open (cone serotiny) represent a key adaptive trait in a variety of pine species. In lodgepole pine, there is substantial geographical variation in serotiny across the Rocky Mountain region. This variation in serotiny has evolved as a result of geographically divergent selection, with consequences that extend to forest communities and ecosystems. An understanding of the genetic architecture of this trait is of interest owing to the wide-reaching ecological consequences of serotiny and also because of the repeated evolution of the trait across the genus. Here, we present and utilize an inexpensive and time-effective method for generating population genomic data. The method uses restriction enzymes and PCR amplification to generate a library of fragments that can be sequenced with a high level of multiplexing. We obtained data for more than 95,000 single nucleotide polymorphisms across 98 serotinous and nonserotinous lodgepole pines from three populations. We used a Bayesian generalized linear model (GLM) to test for an association between genotypic variation at these loci and serotiny. The probability of serotiny varied by genotype at 11 loci, and the association between genotype and serotiny at these loci was consistent in each of the three populations of pines. Genetic variation across these 11 loci explained 50% of the phenotypic variation in serotiny. Our results provide a first genome-wide association map of serotiny in pines and demonstrate an inexpensive and efficient method for generating population genomic data. © 2012 Blackwell Publishing Ltd.

  10. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47

    DEFF Research Database (Denmark)

    Anderson, Carl A; Boucher, Gabrielle; Lees, Charlie W

    2011-01-01

    Genome-wide association studies and candidate gene studies in ulcerative colitis have identified 18 susceptibility loci. We conducted a meta-analysis of six ulcerative colitis genome-wide association study datasets, comprising 6,687 cases and 19,718 controls, and followed up the top association...... signals in 9,628 cases and 12,917 controls. We identified 29 additional risk loci (P associated loci to 47. After annotating associated regions using GRAIL, expression quantitative trait loci data and correlations with non-synonymous SNPs, we...... identified many candidate genes that provide potentially important insights into disease pathogenesis, including IL1R2, IL8RA-IL8RB, IL7R, IL12B, DAP, PRDM1, JAK2, IRF5, GNA12 and LSP1. The total number of confirmed inflammatory bowel disease risk loci is now 99, including a minimum of 28 shared association...

  11. 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

  12. A computational approach for functional mapping of quantitative trait loci that regulate thermal performance curves.

    Directory of Open Access Journals (Sweden)

    John Stephen Yap

    2007-06-01

    Full Text Available Whether and how thermal reaction norm is under genetic control is fundamental to understand the mechanistic basis of adaptation to novel thermal environments. However, the genetic study of thermal reaction norm is difficult because it is often expressed as a continuous function or curve. Here we derive a statistical model for dissecting thermal performance curves into individual quantitative trait loci (QTL with the aid of a genetic linkage map. The model is constructed within the maximum likelihood context and implemented with the EM algorithm. It integrates the biological principle of responses to temperature into a framework for genetic mapping through rigorous mathematical functions established to describe the pattern and shape of thermal reaction norms. The biological advantages of the model lie in the decomposition of the genetic causes for thermal reaction norm into its biologically interpretable modes, such as hotter-colder, faster-slower and generalist-specialist, as well as the formulation of a series of hypotheses at the interface between genetic actions/interactions and temperature-dependent sensitivity. The model is also meritorious in statistics because the precision of parameter estimation and power of QTLdetection can be increased by modeling the mean-covariance structure with a small set of parameters. The results from simulation studies suggest that the model displays favorable statistical properties and can be robust in practical genetic applications. The model provides a conceptual platform for testing many ecologically relevant hypotheses regarding organismic adaptation within the Eco-Devo paradigm.

  13. 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

  14. Predicting treatable traits for long-acting bronchodilators in patients with stable COPD

    Directory of Open Access Journals (Sweden)

    Kang J

    2017-12-01

    Full Text Available Jieun Kang,1,* Ki Tae Kim,2,* Ji-Hyun Lee,3 Eun Kyung Kim,3 Tae-Hyung Kim,4 Kwang Ha Yoo,5 Jae Seung Lee,1 Woo Jin Kim,6 Ju Han Kim,2 Yeon-Mok Oh1 1Department of Pulmonology and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 2Seoul National University Biomedical Informatics and Systems Biomedical Informatics Research Center, Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, 3Department of Internal Medicine, CHA Bundang Medical Center, CHA University, Seongnam, 4Division of Pulmonology, Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, 5Department of Internal Medicine, Konkuk University Hospital, Konkuk University School of Medicine, Seoul, 6Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, School of Medicine, Kangwon National University, Chuncheon, South Korea *These authors contributed equally to this work Purpose: There is currently no measure to predict a treatability of long-acting β-2 agonist (LABA or long-acting muscarinic antagonist (LAMA in patients with chronic obstructive pulmonary disease (COPD. We aimed to build prediction models for the treatment response to these bronchodilators, in order to determine the most responsive medication for patients with COPD.Methods: We performed a prospective open-label crossover study, in which each long-acting bronchodilator was given in a random order to 65 patients with stable COPD for 4 weeks, with a 4-week washout period in between. We analyzed 14 baseline clinical traits, expression profiles of 31,426 gene transcripts, and damaged-gene scores of 6,464 genes acquired from leukocytes. The gene expression profiles were measured by RNA microarray and the damaged-gene scores were obtained after DNA exome sequencing. Linear regression analyses were performed to build prediction models after using

  15. Predictability of bee community composition after floral removals differs by floral trait group.

    Science.gov (United States)

    Urban-Mead, Katherine R

    2017-11-01

    Plant-bee visitor communities are complex networks. While studies show that deleting nodes alters network topology, predicting these changes in the field remains difficult. Here, a simple trait-based approach is tested for predicting bee community composition following disturbance. I selected six fields with mixed cover of flower species with shallow (open) and deep (tube) nectar access, and removed all flowers or flower heads of species of each trait in different plots paired with controls, then observed bee foraging and composition. I compared the bee community in each manipulated plot with bees on the same flower species in control plots. The bee morphospecies composition in manipulations with only tube flowers remaining was the same as that in the control plots, while the bee morphospecies on only open flowers were dissimilar from those in control plots. However, the proportion of short- and long-tongued bees on focal flowers did not differ between control and manipulated plots for either manipulation. So, bees within some functional groups are more strongly linked to their floral trait partners than others. And, it may be more fruitful to describe expected bee community compositions in terms of relative proportions of relevant ecological traits than species, particularly in species-diverse communities. © 2017 The Author(s).

  16. Personality traits and types predict medical school stress: a six-year longitudinal and nationwide study.

    Science.gov (United States)

    Tyssen, Reidar; Dolatowski, Filip C; Røvik, Jan Ole; Thorkildsen, Ruth F; Ekeberg, Oivind; Hem, Erlend; Gude, Tore; Grønvold, Nina T; Vaglum, Per

    2007-08-01

    Personality types (combinations of traits) that take into account the interplay between traits give a more detailed picture of an individual's character than do single traits. This study examines whether both personality types and traits predict stress during medical school training. We surveyed Norwegian medical students (n = 421) 1 month after they began medical school (T1), at the mid-point of undergraduate Year 3 (T2), and at the end of undergraduate Year 6 (T3). A total of 236 medical students (56%) responded at all time-points. They were categorised according to Torgersen's personality typology by their combination of high and low scores on the 'Big Three' personality traits of extroversion, neuroticism and conscientiousness. We studied the effects of both personality types (spectator, insecure, sceptic, brooder, hedonist, impulsive, entrepreneur and complicated) and traits on stress during medical school. There was a higher level of stress among female students. The traits of neuroticism (P = 0.002) and conscientiousness (P = 0.03) were independent predictors of stress, whereas female gender was absorbed by neuroticism in the multivariate model. When controlled for age and gender, 'brooders' (low extroversion, high neuroticism, high conscientiousness) were at risk of experiencing more stress (P = 0.02), whereas 'hedonists' (high extroversion, low neuroticism, low conscientiousness) were more protected against stress (P = 0.001). This is the first study to show that a specific combination of personality traits can predict medical school stress. The combination of high neuroticism and high conscientiousness is considered to be particularly high risk.

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

    Science.gov (United States)

    Kitomi, Yuka; Nakao, Emari; Kawai, Sawako; Kanno, Noriko; Ando, Tsuyu; Fukuoka, Shuichi; Irie, Kenji; Uga, Yusaku

    2018-02-02

    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 BC 4 F 2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC 4 F 3 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. Copyright © 2018 Kitomi et al.

  18. 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.

  19. Identification and validation of quantitative trait loci (QTL for canine hip dysplasia (CHD in German Shepherd Dogs.

    Directory of Open Access Journals (Sweden)

    Lena Fels

    Full Text Available Canine hip dysplasia (CHD is the most common hereditary skeletal disorder in dogs. To identify common alleles associated with CHD, we genotyped 96 German Shepherd Dogs affected by mild, moderate and severe CHD and 96 breed, sex, age and birth year matched controls using the Affymetrix canine high density SNP chip. A mixed linear model analysis identified five SNPs associated with CHD scores on dog chromosomes (CFA 19, 24, 26 and 34. These five SNPs were validated in a by sex, age, birth year and coancestry stratified sample of 843 German Shepherd Dogs including 277 unaffected dogs and 566 CHD-affected dogs. Mean coancestry coefficients among and within cases and controls were <0.1%. Genotype effects of these SNPs explained 20-32% of the phenotypic variance of CHD in German Shepherd Dogs employed for validation. Genome-wide significance in the validation data set could be shown for each one CHD-associated SNP on CFA24, 26 and 34. These SNPs are located within or in close proximity of genes involved in bone formation and related through a joint network. The present study validated positional candidate genes within two previously known quantitative trait loci (QTL and a novel QTL for CHD in German Shepherd Dogs.

  20. Trait-based diet selection: prey behaviour and morphology predict vulnerability to predation in reef fish communities.

    Science.gov (United States)

    Green, Stephanie J; Côté, Isabelle M

    2014-11-01

    Understanding how predators select their prey can provide important insights into community structure and dynamics. However, the suite of prey species available to a predator is often spatially and temporally variable. As a result, species-specific selectivity data are of limited use for predicting novel predator-prey interactions because they are assemblage specific. We present a method for predicting diet selection that is applicable across prey assemblages, based on identifying general morphological and behavioural traits of prey that confer vulnerability to predation independent of species identity. We apply this trait-based approach to examining prey selection by Indo-Pacific lionfish (Pterois volitans and Pterois miles), invasive predators that prey upon species-rich reef fish communities and are rapidly spreading across the western Atlantic. We first generate hypotheses about morphological and behavioural traits recurring across fish species that could facilitate or deter predation by lionfish. Constructing generalized linear mixed-effects models that account for relatedness among prey taxa, we test whether these traits predict patterns of diet selection by lionfish within two independent data sets collected at different spatial scales: (i) in situ visual observations of prey consumption and availability for individual lionfish and (ii) comparisons of prey abundance in lionfish stomach contents to availability on invaded reefs at large. Both analyses reveal that a number of traits predicted to affect vulnerability to predation, including body size, body shape, position in the water column and aggregation behaviour, are important determinants of diet selection by lionfish. Small, shallow-bodied, solitary fishes found resting on or just above reefs are the most vulnerable. Fishes that exhibit parasite cleaning behaviour experience a significantly lower risk of predation than non-cleaning fishes, and fishes that are nocturnally active are at significantly

  1. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    Science.gov (United States)

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

  2. High-precision genetic mapping of behavioral traits in the diversity outbred mouse population

    Science.gov (United States)

    Logan, R W; Robledo, R F; Recla, J M; Philip, V M; Bubier, J A; Jay, J J; Harwood, C; Wilcox, T; Gatti, D M; Bult, C J; Churchill, G A; Chesler, E J

    2013-01-01

    Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light–dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics PMID:23433259

  3. Extensions of Island Biogeography Theory predict the scaling of functional trait composition with habitat area and isolation.

    Science.gov (United States)

    Jacquet, Claire; Mouillot, David; Kulbicki, Michel; Gravel, Dominique

    2017-02-01

    The Theory of Island Biogeography (TIB) predicts how area and isolation influence species richness equilibrium on insular habitats. However, the TIB remains silent about functional trait composition and provides no information on the scaling of functional diversity with area, an observation that is now documented in many systems. To fill this gap, we develop a probabilistic approach to predict the distribution of a trait as a function of habitat area and isolation, extending the TIB beyond the traditional species-area relationship. We compare model predictions to the body-size distribution of piscivorous and herbivorous fishes found on tropical reefs worldwide. We find that small and isolated reefs have a higher proportion of large-sized species than large and connected reefs. We also find that knowledge of species body-size and trophic position improves the predictions of fish occupancy on tropical reefs, supporting both the allometric and trophic theory of island biogeography. The integration of functional ecology to island biogeography is broadly applicable to any functional traits and provides a general probabilistic approach to study the scaling of trait distribution with habitat area and isolation. © 2016 John Wiley & Sons Ltd/CNRS.

  4. Do the big-five personality traits predict empathic listening and assertive communication?

    OpenAIRE

    Sims, Ceri M.

    2016-01-01

    As personality traits can influence important social outcomes, the current research investigated whether the Big-Five had predictive influences on communication competences of active-empathic listening (AEL) and assertiveness. A sample of 245 adults of various ages completed the self-report scales. Both Agreeableness and Openness uniquely predicted AEL. Extraversion had the biggest influence onassertiveness but did not uniquely explain AEL variance. Conscientiousness and Neuroticism had small...

  5. Predictive validity of callous-unemotional traits measured in early adolescence with respect to multiple antisocial outcomes.

    Science.gov (United States)

    McMahon, Robert J; Witkiewitz, Katie; Kotler, Julie S

    2010-11-01

    This study investigated the predictive validity of youth callous-unemotional (CU) traits, as measured in early adolescence (Grade 7) by the Antisocial Process Screening Device (APSD; Frick & Hare, 2001), in a longitudinal sample (N = 754). Antisocial outcomes, assessed in adolescence and early adulthood, included self-reported general delinquency from 7th grade through 2 years post-high school, self-reported serious crimes through 2 years post-high school, juvenile and adult arrest records through 1 year post-high school, and antisocial personality disorder symptoms and diagnosis at 2 years post-high school. CU traits measured in 7th grade were highly predictive of 5 of the 6 antisocial outcomes-general delinquency, juvenile and adult arrests, and early adult antisocial personality disorder criterion count and diagnosis-over and above prior and concurrent conduct problem behavior (i.e., criterion counts of oppositional defiant disorder and conduct disorder) and attention-deficit/hyperactivity disorder (criterion count). Incorporating a CU traits specifier for those with a diagnosis of conduct disorder improved the positive prediction of antisocial outcomes, with a very low false-positive rate. There was minimal evidence of moderation by sex, race, or urban/rural status. Urban/rural status moderated one finding, with being from an urban area associated with stronger relations between CU traits and adult arrests. Findings clearly support the inclusion of CU traits as a specifier for the diagnosis of conduct disorder, at least with respect to predictive validity. PsycINFO Database Record (c) 2010 APA, all rights reserved

  6. Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

    Science.gov (United States)

    Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

    2007-09-01

    Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

  7. Personality traits predict treatment outcome with an antidepressant in patients with functional gastrointestinal disorder.

    Science.gov (United States)

    Tanum, L; Malt, U F

    2000-09-01

    We investigated the relationship between personality traits and response to treatment with the tetracyclic antidepressant mianserin or placebo in patients with functional gastrointestinal disorder (FGD) without psychopathology. Forty-eight patients completed the Buss-Durkee Hostility Inventory, Neuroticism Extroversion Openness -Personality Inventory (NEO-PI), and Eysenck Personality Questionnaire (EPQ), neuroticism + lie subscales, before they were consecutively allocated to a 7-week double-blind treatment study with mianserin or placebo. Treatment response to pain and target symptoms were recorded daily with the Visual Analogue Scale and Clinical Global Improvement Scale at every visit. A low level of neuroticism and little concealed aggressiveness predicted treatment outcome with the antidepressant drug mianserin in non-psychiatric patients with FGD. Inversely, moderate to high neuroticism and marked concealed aggressiveness predicted poor response to treatment. These findings were most prominent in women. Personality traits were better predictors of treatment outcome than serotonergic sensitivity assessed with the fenfluramine test. Assessment of the personality traits negativism, irritability, aggression, and neuroticism may predict response to drug treatment of FGD even when serotonergic sensitivity is controlled for. If confirmed in future studies, the findings point towards a more differential psychopharmacologic treatment of FGD.

  8. Confirmation of dyslexia susceptibility loci on chromosomes 1p and 2p, but not 6p in a Dutch sib-pair collection.

    NARCIS (Netherlands)

    Kovel, C.G.F. de; Franke, B.; Hol, F.A.; Lebrec, J.J.; Maassen, B.A.M.; Brunner, H.G.; Padberg, G.W.A.M.; Platko, J.; Pauls, D.

    2008-01-01

    In this study, we attempted to confirm genetic linkage to developmental dyslexia and reading-related quantitative traits of loci that have been shown to be associated with dyslexia in previous studies. In our sample of 108 Dutch nuclear families, the categorical trait showed strongest linkage to

  9. Who Punishes? Personality Traits Predict Individual Variation in Punitive Sentiment

    Directory of Open Access Journals (Sweden)

    S. Craig Roberts

    2013-01-01

    Full Text Available Cross-culturally, participants in public goods games reward participants and punish defectors to a degree beyond that warranted by rational, profit-maximizing considerations. Costly punishment, where individuals impose costs on defectors at a cost to themselves, is thought to promote the maintenance of cooperation. However, despite substantial variation in the extent to which people punish, little is known about why some individuals, and not others, choose to pay these costs. Here, we test whether personality traits might contribute to variation in helping and punishment behavior. We first replicate a previous study using public goods scenarios to investigate effects of sex, relatedness and likelihood of future interaction on willingness to help a group member or to punish a transgressor. As in the previous study, we find that individuals are more willing to help related than unrelated needy others and that women are more likely to express desire to help than men. Desire to help was higher if the probability of future interaction is high, at least among women. In contrast, among these variables, only participant sex predicted some measures of punitive sentiment. Extending the replication, we found that punitive sentiment, but not willingness to help, was predicted by personality traits. Most notably, participants scoring lower on Agreeableness expressed more anger towards and greater desire to punish a transgressor, and were more willing to engage in costly punishment, at least in our scenario. Our results suggest that some personality traits may contribute to underpinning individual variation in social enforcement of cooperation.

  10. 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

  11. Private traits and attributes are predictable from digital records of human behavior.

    Science.gov (United States)

    Kosinski, Michal; Stillwell, David; Graepel, Thore

    2013-04-09

    We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

  12. Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds.

    Science.gov (United States)

    Panthee, D R; Pantalone, V R; Sams, C E; Saxton, A M; West, D R; Orf, J H; Killam, A S

    2006-02-01

    Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, a major limitation of soy proteins is their deficiency in sulfur-containing amino acids, methionine (Met) and cysteine (Cys). The objective of this study was to identify quantitative trait loci (QTL) associated with Met and Cys concentration in soybean seed. To achieve this objective, 101 F(6)-derived recombinant inbred lines (RIL) from a population developed from a cross of N87-984-16 x TN93-99 were used. Ground soybean seed samples were analyzed for Met and Cys concentration using a near infrared spectroscopy instrument. Data were analyzed using SAS software and QTL Cartographer. RIL differed (Pseed dry weight) for Cys and 4.4-8.8 (g kg(-1) seed dry weight) for Met. Heritability estimates on an entry mean basis were 0.14 and 0.57 for Cys and Met, respectively. A total of 94 polymorphic simple sequence repeat molecular genetic markers were screened in the RIL. Single factor ANOVA was used to identify candidate QTL, which were confirmed by composite interval mapping using QTL Cartographer. Four QTL linked to molecular markers Satt235, Satt252, Satt427 and Satt436 distributed on three molecular linkage groups (MLG) D1a, F and G were associated with Cys and three QTL linked to molecular markers Satt252, Satt564 and Satt590 distributed on MLG F, G and M were associated with Met concentration in soybean seed. QTL associated with Met and Cys in soybean seed will provide important information to breeders targeting improvements in the nutritional quality of soybean.

  13. 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.

  14. Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure.

    Science.gov (United States)

    Iancu, Ovidiu D; Darakjian, Priscila; Kawane, Sunita; Bottomly, Daniel; Hitzemann, Robert; McWeeney, Shannon

    2012-01-01

    Complex Mus musculus crosses, e.g., heterogeneous stock (HS), provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, HS populations have complex genetic architectures not fully captured by the whole genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F(2) intercross, a HS formed by crossing four inbred strains (HS4), and a HS (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome specific relatedness can result in improved eQTL detection.

  15. 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.

  16. Leaf and life history traits predict plant growth in a green roof ecosystem.

    Directory of Open Access Journals (Sweden)

    Jeremy Lundholm

    Full Text Available Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that

  17. Leaf and life history traits predict plant growth in a green roof ecosystem.

    Science.gov (United States)

    Lundholm, Jeremy; Heim, Amy; Tran, Stephanie; Smith, Tyler

    2014-01-01

    Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth) to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies) for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that favor less

  18. Lack of predictive power of trait fear and anxiety for conditioned pain modulation (CPM).

    Science.gov (United States)

    Horn-Hofmann, Claudia; Priebe, Janosch A; Schaller, Jörg; Görlitz, Rüdiger; Lautenbacher, Stefan

    2016-12-01

    In recent years the association of conditioned pain modulation (CPM) with trait fear and anxiety has become a hot topic in pain research due to the assumption that such variables may explain the low CPM efficiency in some individuals. However, empirical evidence concerning this association is still equivocal. Our study is the first to investigate the predictive power of fear and anxiety for CPM by using a well-established psycho-physiological measure of trait fear, i.e. startle potentiation, in addition to two self-report measures of pain-related trait anxiety. Forty healthy, pain-free participants (female: N = 20; age: M = 23.62 years) underwent two experimental blocks in counter-balanced order: (1) a startle paradigm with affective picture presentation and (2) a CPM procedure with hot water as conditioning stimulus (CS) and contact heat as test stimulus (TS). At the end of the experimental session, pain catastrophizing (PCS) and pain anxiety (PASS) were assessed. PCS score, PASS score and startle potentiation to threatening pictures were entered as predictors in a linear regression model with CPM magnitude as criterion. We were able to show an inhibitory CPM effect in our sample: pain ratings of the heat stimuli were significantly reduced during hot water immersion. However, CPM was neither predicted by self-report of pain-related anxiety nor by startle potentiation as psycho-physiological measure of trait fear. These results corroborate previous negative findings concerning the association between trait fear/anxiety and CPM efficiency and suggest that shifting the focus from trait to state measures might be promising.

  19. Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations.

    Directory of Open Access Journals (Sweden)

    Heather A Lawson

    2011-09-01

    Full Text Available Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS components (obesity, dyslipidemia, and diabetes-related traits. MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL in an F(16 advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002. Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

  20. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

    Science.gov (United States)

    McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

    2017-01-01

    Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730

  1. Meta-analysis of rare and common exome chip variants identifies S1PR4 and other loci influencing blood cell traits

    DEFF Research Database (Denmark)

    Pankratz, Nathan; Schick, Ursula M; Zhou, Yi

    2016-01-01

    with Illumina HumanExome BeadChip genotypes. We then performed replication analyses of new discoveries in 18,018 European-American women and 5,261 Han Chinese. We identified and replicated four new erythrocyte trait-locus associations (CEP89, SHROOM3, FADS2, and APOE) and six new WBC loci for neutrophil count...... (S1PR4), monocyte count (BTBD8, NLRP12, and IL17RA), eosinophil count (IRF1), and total WBC count (MYB). The association of a rare missense variant in S1PR4 supports the role of sphingosine-1-phosphate signaling in leukocyte trafficking and circulating neutrophil counts. Loss-of-function experiments...... for S1pr4 in mouse and s1pr4 in zebrafish demonstrated phenotypes consistent with the association observed in humans and altered kinetics of neutrophil recruitment and resolution in response to tissue injury....

  2. Effect of Polymorphism of some Candidate Genes from Growth Hormone Axis on Egg Production Traits in Mazandaran Native Fowls

    Directory of Open Access Journals (Sweden)

    B Enayati

    2012-02-01

    Full Text Available In the present study the allelic polymorphisms of GH, GHR and TGFβ3 genes and its association with egg production traits were investigated. Blood samples randomly were collected from breeder hens of Mazandaran native fowls breeding station and transported to the laboratory in cold chain condition. DNA was extracted using modified salting out method and the desired loci were amplified by specific primers. All samples genotyping were carried out by RFLP-PCR method. The frequency of each (+ and (- alleles was estimated at 0.7981 and 0.2019 for GH, 0.9937 and 0.0063 for GHR and 0.8037 and 0.1961 for TGFβ3 loci, respectively. The heterozygote genotype was detected in both GH and TGFβ3 loci but all individuals showed homozygote genotype in GHR marker site. The chi-squared test showed that all individuals in both GH and TGFβ3 loci were in HW equilibrium. Statistical analysis of showed that GH marker site had a significant effect on both phenotypic and breeding values of egg weight at puberty (EWM and age at first laying egg (AFE, respectively. The mean comparison showed that individuals with -/- genotype in GH marker site had higher phenotypic values for EWM but lower breeding values for AFE trait. The GHR and TGFβ3 loci and also the interaction between GH×TGFβ3 loci were not statistically significant on phenotypic and breeding values of mentioned traits..

  3. Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

    Directory of Open Access Journals (Sweden)

    Sjur Reppe

    Full Text Available Bone Mineral Density (BMD is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR method to identify single nucleotide polymorphisms (SNPs associated with BMD by leveraging cardiovascular disease (CVD associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity.

  4. Predicting Changes in Macrophyte Community Structure from Functional Traits in a Freshwater Lake: A Test of Maximum Entropy Model

    Science.gov (United States)

    Fu, Hui; Zhong, Jiayou; Yuan, Guixiang; Guo, Chunjing; Lou, Qian; Zhang, Wei; Xu, Jun; Ni, Leyi; Xie, Ping; Cao, Te

    2015-01-01

    Trait-based approaches have been widely applied to investigate how community dynamics respond to environmental gradients. In this study, we applied a series of maximum entropy (maxent) models incorporating functional traits to unravel the processes governing macrophyte community structure along water depth gradient in a freshwater lake. We sampled 42 plots and 1513 individual plants, and measured 16 functional traits and abundance of 17 macrophyte species. Study results showed that maxent model can be highly robust (99.8%) in predicting the species relative abundance of macrophytes with observed community-weighted mean (CWM) traits as the constraints, while relative low (about 30%) with CWM traits fitted from water depth gradient as the constraints. The measured traits showed notably distinct importance in predicting species abundances, with lowest for perennial growth form and highest for leaf dry mass content. For tuber and leaf nitrogen content, there were significant shifts in their effects on species relative abundance from positive in shallow water to negative in deep water. This result suggests that macrophyte species with tuber organ and greater leaf nitrogen content would become more abundant in shallow water, but would become less abundant in deep water. Our study highlights how functional traits distributed across gradients provide a robust path towards predictive community ecology. PMID:26167856

  5. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

    Science.gov (United States)

    Lorenz, Aaron J

    2013-03-01

    Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

  6. Do Core Interpersonal and Affective Traits of PCL-R Psychopathy Interact with Antisocial Behavior and Disinhibition to Predict Violence?

    Science.gov (United States)

    Kennealy, Patrick J.; Skeem, Jennifer L.; Walters, Glenn D.; Camp, Jacqueline

    2010-01-01

    The utility of psychopathy measures in predicting violence is largely explained by their assessment of social deviance (e.g., antisocial behavior; disinhibition). A key question is whether social deviance "interacts" with the core interpersonal-affective traits of psychopathy to predict violence. Do core psychopathic traits multiply the (already…

  7. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

    Science.gov (United States)

    McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

    2017-07-01

    Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

  8. 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

  9. Prediction and Cross-Situational Consistency of Daily Behavior across Cultures: Testing Trait and Cultural Psychology Perspectives

    Science.gov (United States)

    Church, A. Timothy; Katigbak, Marcia S.; Reyes, Jose Alberto S.; Salanga, Maria Guadalupe C.; Miramontes, Lilia A.; Adams, Nerissa B.

    2008-01-01

    Trait and cultural psychology perspectives on the cross-situational consistency of behavior, and the predictive validity of traits, were tested in a daily process study in the United States (N = 68), an individualistic culture, and the Philippines (N = 80), a collectivistic culture. Participants completed the Revised NEO Personality Inventory (Costa & McCrae, 1992) and a measure of self-monitoring, then reported their daily behaviors and associated situational contexts for approximately 30 days. Consistent with trait perspectives, the Big Five traits predicted daily behaviors in both cultures, and relative (interindividual) consistency was observed across many, although not all, situational contexts. The frequency of various Big Five behaviors varied across relevant situational contexts in both cultures and, consistent with cultural psychology perspectives, there was a tendency for Filipinos to exhibit greater situational variability than Americans. Self-monitoring showed some ability to account for individual differences in situational variability in the American sample, but not the Filipino sample. PMID:22146866

  10. Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs

    Directory of Open Access Journals (Sweden)

    Liang Kung-Yee

    2010-07-01

    Full Text Available Abstract Background Many dichotomous traits for complex diseases are often involved more than one locus and/or associated with quantitative biomarkers or environmental factors. Incorporating these quantitative variables into linkage analysis as well as localizing two linked disease loci simultaneously could therefore improve the efficiency in mapping genes. We extended the robust multipoint Identity-by-Descent (IBD approach with incorporation of covariates developed previously to simultaneously estimate two linked loci using different types of affected relative pairs (ARPs. Results We showed that the efficiency was enhanced by incorporating a quantitative covariate parametrically or non-parametrically while localizing two disease loci using ARPs. In addition to its help in identifying factors associated with the disease and in improving the efficiency in estimating disease loci, this extension also allows investigators to account for heterogeneity in risk-ratios for different ARPs. Data released from the collaborative study on the genetics of alcoholism (COGA for Genetic Analysis Workshop 14 (GAW 14 were used to illustrate the application of this extended method. Conclusions The simulation studies and example illustrated that the efficiency in estimating disease loci was demonstratively enhanced by incorporating a quantitative covariate and by using all relative pairs while mapping two linked loci simultaneously.

  11. The bovine QTL viewer: a web accessible database of bovine Quantitative Trait Loci

    Directory of Open Access Journals (Sweden)

    Xavier Suresh R

    2006-06-01

    Full Text Available Abstract Background Many important agricultural traits such as weight gain, milk fat content and intramuscular fat (marbling in cattle are quantitative traits. Most of the information on these traits has not previously been integrated into a genomic context. Without such integration application of these data to agricultural enterprises will remain slow and inefficient. Our goal was to populate a genomic database with data mined from the bovine quantitative trait literature and to make these data available in a genomic context to researchers via a user friendly query interface. Description The QTL (Quantitative Trait Locus data and related information for bovine QTL are gathered from published work and from existing databases. An integrated database schema was designed and the database (MySQL populated with the gathered data. The bovine QTL Viewer was developed for the integration of QTL data available for cattle. The tool consists of an integrated database of bovine QTL and the QTL viewer to display QTL and their chromosomal position. Conclusion We present a web accessible, integrated database of bovine (dairy and beef cattle QTL for use by animal geneticists. The viewer and database are of general applicability to any livestock species for which there are public QTL data. The viewer can be accessed at http://bovineqtl.tamu.edu.

  12. Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

    Science.gov (United States)

    Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

    2017-08-10

    A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of

  13. 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

  14. 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.

  15. Predicting the establishment success of introduced target species in grassland restoration by functional traits.

    Science.gov (United States)

    Engst, Karina; Baasch, Annett; Bruelheide, Helge

    2017-09-01

    potential of functional trait analysis to predict success in restoration projects.

  16. 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

  17. 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

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

    Indian Academy of Sciences (India)

    reviewer

    Sari, P.O. Box -578, Iran .... (2015) identified one SNP with genome wide significance effect within SYNE1 gene on ..... analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. ... Problems involved in breeding for efficiency of food utilization. Proc .... 131, 210-216.

  19. Quantitative trait loci for live animal and carcass composition traits in Jersey and Limousin back-cross cattle finished on pasture or feedlot.

    Science.gov (United States)

    Morris, C A; Pitchford, W S; Cullen, N G; Esmailizadeh, A K; Hickey, S M; Hyndman, D; Dodds, K G; Afolayan, R A; Crawford, A M; Bottema, C D K

    2009-10-01

    A quantitative trait locus (QTL) study was carried out in two countries, recording live animal and carcass composition traits. Back-cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin breed backgrounds. The New Zealand cattle were reared on pasture to carcass weights averaging 229 kg, whilst the Australian cattle were reared on grass and finished on grain (for at least 180 days) to carcass weights averaging 335 kg. From 11 live animal traits and 31 carcass composition traits respectively, 5 and 22 QTL were detected in combined-sire analyses, which were significant (P < 0.05) on a genome-wise basis. Fourteen significant traits for carcass composition QTL were on chromosome 2 and these were traits associated with muscling and fatness. This chromosome carried a variant myostatin allele (F94L), segregating from the Limousin ancestry. Despite very different cattle management systems between the two countries, the two populations had a large number of QTL in common. Of the 18 traits which were common to both countries, and which had significant QTL at the genome-wise level, eight were significant in both countries.

  20. Genome-wide meta-analysis of myopia and hyperopia provides evidence for replication of 11 loci.

    Directory of Open Access Journals (Sweden)

    Claire L Simpson

    Full Text Available Refractive error (RE is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness and hyperopia (farsightedness, which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10(-8, which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10(-11 and 8q12 (minimum p value 1.82×10(-11 previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al. and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. "Replication-level" association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of

  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. Evaluation of seven common lipid associated loci in a large Indian sib pair study.

    Science.gov (United States)

    Rafiq, Sajjad; Venkata, Kranthi Kumar M; Gupta, Vipin; Vinay, D G; Spurgeon, Charles J; Parameshwaran, Smitha; Madana, Sandeep N; Kinra, Sanjay; Bowen, Liza; Timpson, Nicholas J; Smith, George Davey; Dudbridge, Frank; Prabhakaran, Dorairaj; Ben-Shlomo, Yoav; Reddy, K Srinath; Ebrahim, Shah; Chandak, Giriraj R

    2012-11-14

    Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations.

  3. Divergence at neutral and non-neutral loci in Drosophila buzzatii populations and their hybrids

    DEFF Research Database (Denmark)

    Andersen, Ditte Holm; Pertoldi, Cino; Loeschcke, Volker

    2008-01-01

    The impact of intraspecific hybridisation on fitness and morphological traits depends on the history of natural selection and genetic drift, which may have led to differently coadapted gene-complexes in the parental populations. The divergence at neutral and non-neutral loci between populations can...... populations of Drosophila buzzatii, one between populations from Argentina and the Canary Islands (separated for 200 years), and the other between populations from Argentina and Australia (separated for 80 years). We observed the highest divergence at neutral loci between the Argentinean and Canary Island...

  4. Do the Big-Five Personality Traits Predict Empathic Listening and Assertive Communication?

    Science.gov (United States)

    Sims, Ceri M.

    2017-01-01

    As personality traits can influence important social outcomes, the current research investigated whether the Big-Five had predictive influences on communication competences of active-empathic listening (AEL) and assertiveness. A sample of 245 adults of various ages completed the self-report scales. Both Agreeableness and Openness uniquely…

  5. The Prediction of Item Parameters Based on Classical Test Theory and Latent Trait Theory

    Science.gov (United States)

    Anil, Duygu

    2008-01-01

    In this study, the prediction power of the item characteristics based on the experts' predictions on conditions try-out practices cannot be applied was examined for item characteristics computed depending on classical test theory and two-parameters logistic model of latent trait theory. The study was carried out on 9914 randomly selected students…

  6. Biallelic and Genome Wide Association Mapping of Germanium Tolerant Loci in Rice (Oryza sativa L..

    Directory of Open Access Journals (Sweden)

    Partha Talukdar

    Full Text Available Rice plants accumulate high concentrations of silicon. Silicon has been shown to be involved in plant growth, high yield, and mitigating biotic and abiotic stresses. However, it has been demonstrated that inorganic arsenic is taken up by rice through silicon transporters under anaerobic conditions, thus the ability to efficiently take up silicon may be considered either a positive or a negative trait in rice. Germanium is an analogue of silicon that produces brown lesions in shoots and leaves, and germanium toxicity has been used to identify mutants in silicon and arsenic transport. In this study, two different genetic mapping methods were performed to determine the loci involved in germanium sensitivity in rice. Genetic mapping in the biparental cross of Bala × Azucena (an F6 population and a genome wide association (GWA study with 350 accessions from the Rice Diversity Panel 1 were conducted using 15 μM of germanic acid. This identified a number of germanium sensitive loci: some co-localised with previously identified quantitative trait loci (QTL for tissue silicon or arsenic concentration, none co-localised with Lsi1 or Lsi6, while one single nucleotide polymorphism (SNP was detected within 200 kb of Lsi2 (these are genes known to transport silicon, whose identity was discovered using germanium toxicity. However, examining candidate genes that are within the genomic region of the loci detected above reveals genes homologous to both Lsi1 and Lsi2, as well as a number of other candidate genes, which are discussed.

  7. QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley.

    Science.gov (United States)

    Gong, Xue; McDonald, Glenn

    2017-09-01

    Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency. Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE GY ) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE GY . A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

  8. Expression quantitative trait loci for PAX8 contributes to the prognosis of hepatocellular carcinoma.

    Directory of Open Access Journals (Sweden)

    Shijie Ma

    Full Text Available Paired-box family member PAX8 encodes a transcription factor that has a role in cell differentiation and cell growth and may participate in the prognosis of hepatocellular carcinoma (HCC. By bioinformatics analysis, we identified several single nucleotide polymorphisms (SNPs within a newly identified long non-coding RNA (lncRNA AC016683.6 as expression quantitative trait loci (eQTLs for PAX8. Hence, we hypothesized that PAX8eQTLs in lncRNA AC016683.6 may influence the HCC prognosis. We then performed a case-only study to assess the association between the two SNPs as well as the prognosis of HCC in 331 HBV-positive HCC patients without surgical treatment. Cox proportional hazard models were used for survival analysis with adjustments for the age, gender, smoking status, drinking status, Barcelona-Clinic Liver Cancer (BCLC stage, and chemotherapy or TACE (transcatheter hepatic arterial chemoembolization status. We found that the G allele of rs1110839 and the T allele of rs4848320 in PAX8was significantly associated with a better prognosis compared with the T allele of rs1110839 and the C allele of rs4848320 (adjusted HR = 0.74, 95% CI = 0.61-0.91, P = 0.004 for rs1110839 and adjusted HR = 0.71, 95% CI = 0.54-0.94, P = 0.015 for rs4848320 in the additive model. Furthermore, the combined effect of the variant genotypes for these two SNPs was more prominent in patients with the BCLC-C stage orpatients with chemotherapy or TACE. Although the exact biological function remains to be explored, our findings suggest a possible association of PAX8eQTLs in lncRNA AC016683.6 with the HCC prognosis inthe Chinese population. Further large and functional studies are needed to confirm our findings.

  9. Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines

    Directory of Open Access Journals (Sweden)

    Riedelsheimer Christian

    2012-09-01

    Full Text Available Abstract Background There is increasing empirical evidence that whole-genome prediction (WGP is a powerful tool for predicting line and hybrid performance in maize. However, there is a lack of knowledge about the sensitivity of WGP models towards the genetic architecture of the trait. Whereas previous studies exclusively focused on highly polygenic traits, important agronomic traits such as disease resistances, nutrifunctional or climate adaptational traits have a genetic architecture which is either much less complex or unknown. For such cases, information about model robustness and guidelines for model selection are lacking. Here, we compared five WGP models with different assumptions about the distribution of the underlying genetic effects. As contrasting model traits, we chose three highly polygenic agronomic traits and three metabolites each with a major QTL explaining 22 to 30% of the genetic variance in a panel of 289 diverse maize inbred lines genotyped with 56,110 SNPs. Results We found the five WGP models to be remarkable robust towards trait architecture with the largest differences in prediction accuracies ranging between 0.05 and 0.14 for the same trait, most likely as the result of the high level of linkage disequilibrium prevailing in elite maize germplasm. Whereas RR-BLUP performed best for the agronomic traits, it was inferior to LASSO or elastic net for the three metabolites. We found the approach of genome partitioning of genetic variance, first applied in human genetics, as useful in guiding the breeder which model to choose, if prior knowledge of the trait architecture is lacking. Conclusions Our results suggest that in diverse germplasm of elite maize inbred lines with a high level of LD, WGP models differ only slightly in their accuracies, irrespective of the number and effects of QTL found in previous linkage or association mapping studies. However, small gains in prediction accuracies can be achieved if the WGP model is

  10. 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

  11. Genome-wide association mapping of root traits in a japonica rice panel.

    Directory of Open Access Journals (Sweden)

    Brigitte Courtois

    Full Text Available Rice is a crop prone to drought stress in upland and rainfed lowland ecosystems. A deep root system is recognized as the best drought avoidance mechanism. Genome-wide association mapping offers higher resolution for locating quantitative trait loci (QTLs than QTL mapping in biparental populations. We performed an association mapping study for root traits using a panel of 167 japonica accessions, mostly of tropical origin. The panel was genotyped at an average density of one marker per 22.5 kb using genotyping by sequencing technology. The linkage disequilibrium in the panel was high (r(2>0.6, on average, for 20 kb mean distances between markers. The plants were grown in transparent 50 cm × 20 cm × 2 cm Plexiglas nailboard sandwiches filled with 1.5 mm glass beads through which a nutrient solution was circulated. Root system architecture and biomass traits were measured in 30-day-old plants. The panel showed a moderate to high diversity in the various traits, particularly for deep (below 30 cm depth root mass and the number of deep roots. Association analyses were conducted using a mixed model involving both population structure and kinship to control for false positives. Nineteen associations were significant at P<1e-05, and 78 were significant at P<1e-04. The greatest numbers of significant associations were detected for deep root mass and the number of deep roots, whereas no significant associations were found for total root biomass or deep root proportion. Because several QTLs for different traits were co-localized, 51 unique loci were detected; several co-localized with meta-QTLs for root traits, but none co-localized with rice genes known to be involved in root growth. Several likely candidate genes were found in close proximity to these loci. Additional work is necessary to assess whether these markers are relevant in other backgrounds and whether the genes identified are robust candidates.

  12. 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.

  13. Can a mathematical model predict an individual's trait-like response to both total and partial sleep loss?

    Science.gov (United States)

    Ramakrishnan, Sridhar; Lu, Wei; Laxminarayan, Srinivas; Wesensten, Nancy J; Rupp, Tracy L; Balkin, Thomas J; Reifman, Jaques

    2015-06-01

    Humans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance (UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation (TSD) and (ii) chronic sleep restriction (CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over non-individualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions. © 2014 European Sleep Research Society.

  14. Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

    DEFF Research Database (Denmark)

    Wu, Yili; Duan, Haiping; Tian, Xiaocao

    2018-01-01

    Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....

  15. Genetic parameters for the prediction of abdominal fat traits using blood biochemical indicators in broilers.

    Science.gov (United States)

    Zhang, H L; Xu, Z Q; Yang, L L; Wang, Y X; Li, Y M; Dong, J Q; Zhang, X Y; Jiang, X Y; Jiang, X F; Li, H; Zhang, D X; Zhang, H

    2018-02-01

    1. Excessive deposition of body fat, especially abdominal fat, is detrimental in chickens and the prevention of excessive fat accumulation is an important problem. The aim of this study was to identify blood biochemical indicators that could be used as criteria to select lean Yellow-feathered chicken lines. 2. Levels of blood biochemical indicators in the fed and fasted states and the abdominal fat traits were measured in 332 Guangxi Yellow chickens. In the fed state, the genetic correlations (r g ) of triglycerides and very low density lipoprotein levels were positive for the abdominal fat traits (0.47 ≤ r g  ≤ 0.67), whereas total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) showed higher negative correlations with abdominal fat traits (-0.59 ≤ r g  ≤ -0.33). Heritabilities of these blood biochemical parameters were high, varying from 0.26 to 0.60. 3. In the fasted state, HDL-C:LDL-C level was positively correlated with abdominal fat traits (0.35 ≤ r g  ≤ 0.38), but triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin, aspartate transaminase, uric acid and creatinine levels were negatively correlated with abdominal fat traits (-0.79 ≤ r g  ≤ -0.35). The heritabilities of these 10 blood biochemical parameters were high (0.22 ≤ h 2  ≤ 0.59). 4. In the fed state, optimal multiple regression models were constructed to predict abdominal fat traits by using triglycerides and LDL-C. In the fasted state, triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin and uric acid could be used to predict abdominal fat content. 5. It was concluded that these models in both nutritional states could be used to predict abdominal fat content in Guangxi Yellow broiler chickens.

  16. Identification, replication, and fine-mapping of Loci associated with adult height in individuals of african ancestry.

    Directory of Open Access Journals (Sweden)

    Amidou N'Diaye

    2011-10-01

    Full Text Available Adult height is a classic polygenic trait of high heritability (h(2 approximately 0.8. More than 180 single nucleotide polymorphisms (SNPs, identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12 and 2p14-rs4315565, P = 1.2×10(-8. As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4 for overall replication. Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01. Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.

  17. 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.

  18. Identification of Gene Loci That Overlap Between Schizophrenia and Educational Attainment

    DEFF Research Database (Denmark)

    Le Hellard, Stéphanie; Wang, Yunpeng; Witoelar, Aree

    2017-01-01

    . Here we investigated the shared genetic architecture between SCZ and educational attainment, which is regarded as a "proxy phenotype" for cognitive abilities, but may also reflect other traits. We applied a conditional false discovery rate (condFDR) method to GWAS of SCZ (n = 82 315), college...... completion ("College," n = 95 427), and years of education ("EduYears," n = 101 069). Variants associated with College or EduYears showed enrichment of association with SCZ, demonstrating polygenic overlap. This was confirmed by an increased replication rate in SCZ. By applying a condFDR threshold ... of these loci had effects in opposite directions. Our results provide evidence for polygenic overlap between SCZ and educational attainment, and identify novel pleiotropic loci. Other studies have reported genetic overlap between SCZ and cognition, or SCZ and educational attainment, with negative correlation...

  19. An integrative genetic study of rice metabolism, growth and stochastic variation reveals potential C/N partitioning loci

    DEFF Research Database (Denmark)

    Li, Baohua; Zhang, Yuanyuan; Mohammadi, Seyed Abolghasem

    2016-01-01

    metabolites suggesting that they may influence carbon and nitrogen partitioning, with one locus co-localizing with SUSIBA2 (WRKY78). Comparing QTLs for metabolomic and a variety of growth related traits identified few overlaps. Interestingly, the rice population displayed fewer loci controlling stochastic...

  20. Genomic Prediction of Testcross Performance in Canola (Brassica napus)

    Science.gov (United States)

    Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (