Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001
Full Text Available Recent genome-wide association (GWA studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA data from 18 population-based cohorts with European ancestry (maximum N = 32,225. We collected 8 further cohorts (N = 17,102 for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR on total cholesterol (TC with a combined P-value of 4.79×10(-9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P
Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of
Surakka, I.; Isaacs, A.; Karssen, L. C.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain similar to 25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened......, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79 x 10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes...
Surakka, Ida; Isaacs, Aaron; Karssen, Lennart C.; Laurila, Pirkka-Pekka P.; Middelberg, Rita P. S.; Tikkanen, Emmi; Ried, Janina S.; Lamina, Claudia; Mangino, Massimo; Igl, Wilmar; Hottenga, Jouke-Jan; Lagou, Vasiliki; van der Harst, Pim; Mateo Leach, Irene; Esko, Tonu; Kutalik, Zoltan; Wainwright, Nicholas W.; Struchalin, Maksim V.; Sarin, Antti-Pekka; Kangas, Antti J.; Viikari, Jorma S.; Perola, Markus; Rantanen, Taina; Petersen, Ann-Kristin; Soininen, Pasi; Johansson, Asa; Soranzo, Nicole; Heath, Andrew C.; Papamarkou, Theodore; Prokopenko, Inga; Toenjes, Anke; Kronenberg, Florian; Doering, Angela; Rivadeneira, Fernando; Montgomery, Grant W.; Whitfield, John B.; Kahonen, Mika; Lehtimaki, Terho; Freimer, Nelson B.; Willemsen, Gonneke; de Geus, Eco J. C.; Palotie, Aarno; Sandhu, Manj S.; Waterworth, Dawn M.; Metspalu, Andres; Stumvoll, Michael; Uitterlinden, Andre G.; Navis, Gerjan; Wijmenga, Cisca; Wolffenbuttel, Bruce H. R.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain similar to 25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for
Surakka, I.; Isaacs, A.; Karssen, L.C.; Laurila, P.P.P.; Middelberg, R.P.S.; Tikkanen, E.; Ried, J.S.; Lamina, C.; Mangino, M.; Igl, W.; Hottenga, J.J.; Lagou, V.; van der Harst, P.; Mateo Leach, I.; Esko, T.; Kutalik, Z.; Wainwright, N.W.; Struchalin, M.V.; Sarin, A.P.; Kangas, A.J.; Viikari, J.S.; Perola, M.; Rantanen, T.; Petersen, A.K.; Soininen, P.; Johansson, Å.; Soranzo, N.; Heath, A.C.; Papamarkou, T.; Prokopenko, I.; Tönjes, A.; Kronenberg, F.; Döring, A.; Rivadeneira, F.; Montgomery, GW; Whitfield, J.B.; Kähönen, M.; Lehtimäki, T.; Freimer, N.B.; Willemsen, G.; de Geus, E.J.C.; Palotie, A.; Sandhu, M.S.; Waterworth, D.; Metspalu, A.; Stumvoll, M.; Uitterlinden, A.G.; Navis, G.; Wijmenga, C.; Wolffenbuttel, B.H.R.; Taskinen, M.R.; Ala-Korpela, M.; Kaprio, J.; Kyvik, K.O.; Boomsma, D.I.; Pedersen, N.L.; Gyllensten, U.; Wilson, J.F.; Rudan, I.; Campbell, H.; Pramstaller, P.P.; Spector, T.D.; Witteman, J.C.M.; Eriksson, J.G.; Salomaa, V.; Oostra, B.A.; Raitakari, O.T.; Wichmann, H.E.; Gieger, C.; Järvelin, M.J.; Martin, N.G.; Hofman, A.; McCarthy, M.I.; Peltonen, L.; van Duijn, C.M.; Aulchenko, Y.S.; Ripatti, S.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ~25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants
I. Surakka (Ida); A.J. Isaacs (Aaron); L.C. Karssen (Lennart); P.-P.P. Laurila; R.P.S. Middelberg (Rita); E. Tikkanen (Emmi); J.S. Ried (Janina); C. Lamina (Claudia); M. Mangino (Massimo); W. Igl (Wilmar); J.J. Hottenga (Jouke Jan); V. Lagou (Vasiliki); P. van der Harst (Pim); I.M. Leach (Irene Mateo); T. Esko (Tõnu); Z. Kutalik (Zoltán); N.W. Wainwright (Nicholas); M.V. Struchalin (Maksim); A.-P. Sarin; A.J. Kangas (Antti); J. Viikari (Jorma); M. Perola (Markus); T. Rantanen (Taina); A.K. Petersen; P. Soininen (Pasi); A. Johansson (Åsa); N. Soranzo (Nicole); A.C. Heath (Andrew); T. Papamarkou (Theodore); I. Prokopenko (Inga); A. Tönjes (Anke); F. Kronenberg (Florian); A. Döring (Angela); F. Rivadeneira Ramirez (Fernando); G.W. Montgomery (Grant); J.B. Whitfield (John); M. Kähönen (Mika); T. Lehtimäki (Terho); N.B. Freimer (Nelson); G.A.H.M. Willemsen (Gonneke); E.J.C. de Geus (Eco); A. Palotie (Aarno); M.S. Sandhu (Manj); D. Waterworth (Dawn); A. Metspalu (Andres); M. Stumvoll (Michael); A.G. Uitterlinden (André); A. Jula (Antti); G. Navis (Gerjan); C. Wijmenga (Cisca); B.H.R. Wolffenbuttel (Bruce); M.-R. Taskinen; M. Ala-Korpela (Mika); J. Kaprio (Jaakko); K.O. Kyvik (Kirsten Ohm); D.I. Boomsma (Dorret); N.L. Pedersen (Nancy); U. Gyllensten (Ulf); J.F. Wilson (James); I. Rudan (Igor); H. Campbell (Harry); P.P. Pramstaller (Peter Paul); T.D. Spector (Timothy); J.C.M. Witteman (Jacqueline); J.G. Eriksson (Johan); V. Salomaa (Veikko); B.A. Oostra (Ben); O. Raitakari (Olli); H.E. Wichmann (Heinz Erich); C. Gieger (Christian); M.R. Järvelin; N.G. Martin (Nicholas); A. Hofman (Albert); M.I. McCarthy (Mark); Y.S. Aulchenko (Yurii); L. Peltonen (Leena Johanna); P. Tikka-Kleemola (Päivi); S. Ripatti (Samuli)
textabstractRecent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ~25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for
Dogan, Meeshanthini V; Beach, Steven R H; Philibert, Robert A
Smoking is the leading cause of death in the United States. It exerts its effects by increasing susceptibility to a variety of complex disorders among those who smoke, and if pregnant, to their unborn children. In prior efforts to understand the epigenetic mechanisms through which this increased vulnerability is conveyed, a number of investigators have conducted genome wide methylation analyses. Unfortunately, secondary to methodological limitations, these studies were unable to examine methylation in gene regions with significant amounts of genetic variation. Using genome wide genetic and epigenetic data from the Framingham Heart Study, we re-examined the relationship of smoking status to genome wide methylation status. When only methylation status is considered, smoking was significantly associated with differential methylation in 310 genes that map to a variety of biological process and cellular differentiation pathways. However, when SNP effects on the magnitude of smoking associated methylation changes are also considered, cis and trans-interaction effects were noted at a total of 266 and 4353 genes with no marked enrichment for any biological pathways. Furthermore, the SNP variation participating in the significant interaction effects is enriched for loci previously associated with complex medical illnesses. The enlarged scope of the methylome shown to be affected by smoking may better explicate the mediational pathways linking smoking with a myriad of smoking related complex syndromes. Additionally, these results strongly suggest that combined epigenetic and genetic data analyses may be critical for a more complete understanding of the relationship between environmental variables, such as smoking, and pathophysiological outcomes. © 2017 Wiley Periodicals, Inc.
Dunn, Erin C.; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M.; Gogarten, Stephanie M.; Sofer, Tamar; Faul, Jessica D.; Kardia, Sharon L.R.; Smith, Jennifer A.; Weir, David R.; Zhao, Wei; Soare, Thomas W.; Mirza, Saira S.; Hek, Karin; Tiemeier, Henning W.; Goveas, Joseph S.; Sarto, Gloria E.; Snively, Beverly M.; Cornelis, Marilyn; Koenen, Karestan C.; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J.; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W.
Background Genome-wide association studies (GWAS) have been unable to identify variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (G×E) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide environment interaction study (GWEIS) of depressive symptoms. Methods Using data from the SHARe cohort of the Women’s Health Initiative, comprising African Americans (n=7179) and Hispanics/Latinas (n=3138), we examined genetic main effects and G×E with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. Results No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20kb from GPR139, p=5.75×10−8) and rs75407252 (intronic to CACNA2D3, p=6.99×10−7). In Hispanics/Latinas, the top signals were rs2532087 (located 27kb from CD38, p=2.44×10−7) and rs4542757 (intronic to DCC, p=7.31×10−7). In the GWEIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; p=4.10×10−10; located 14kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG=0.95), suggesting that common variation underlying depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Conclusions Our results underscore the need for larger samples, more GWEIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. PMID:27038408
Full Text Available The identification of statistical SNP-SNP interactions may help explain the genetic etiology of many human diseases, but exhaustive genome-wide searches for these interactions have been difficult, due to a lack of power in most datasets. We aimed to use data from the Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA study to search for SNP-SNP interactions associated with 10 common diseases. FastEpistasis and BOOST were used to evaluate all pairwise interactions among approximately N = 300,000 single nucleotide polymorphisms (SNPs with minor allele frequency (MAF ≥ 0.15, for the dichotomous outcomes of allergic rhinitis, asthma, cardiac disease, depression, dermatophytosis, type 2 diabetes, dyslipidemia, hemorrhoids, hypertensive disease, and osteoarthritis. A total of N = 45,171 subjects were included after quality control steps were applied. These data were divided into discovery and replication subsets; the discovery subset had > 80% power, under selected models, to detect genome-wide significant interactions (P < 10−12. Interactions were also evaluated for enrichment in particular SNP features, including functionality, prior disease relevancy, and marginal effects. No interaction in any disease was significant in both the discovery and replication subsets. Enrichment analysis suggested that, for some outcomes, interactions involving SNPs with marginal effects were more likely to be nominally replicated, compared to interactions without marginal effects. If SNP-SNP interactions play a role in the etiology of the studied conditions, they likely have weak effect sizes, involve lower-frequency variants, and/or involve complex models of interaction that are not captured well by the methods that were utilized.
Graff, Mariaelisa; Scott, Robert A; Justice, Anne E; Young, Kristin L; Feitosa, Mary F; Barata, Llilda; Winkler, Thomas W; Chu, Audrey Y; Mahajan, Anubha; Hadley, David; Xue, Luting; Workalemahu, Tsegaselassie; Heard-Costa, Nancy L; den Hoed, Marcel; Ahluwalia, Tarunveer S; Qi, Qibin; Ngwa, Julius S; Renström, Frida; Quaye, Lydia; Eicher, John D; Hayes, James E; Cornelis, Marilyn; Kutalik, Zoltan; Lim, Elise; Luan, Jian'an; Huffman, Jennifer E; Zhang, Weihua; Zhao, Wei; Griffin, Paula J; Haller, Toomas; Ahmad, Shafqat; Marques-Vidal, Pedro M; Bien, Stephanie; Yengo, Loic; Teumer, Alexander; Smith, Albert Vernon; Kumari, Meena; Harder, Marie Neergaard; Justesen, Johanne Marie; Kleber, Marcus E; Hollensted, Mette; Lohman, Kurt; Rivera, Natalia V; Whitfield, John B; Zhao, Jing Hua; Stringham, Heather M; Lyytikäinen, Leo-Pekka; Huppertz, Charlotte; Willemsen, Gonneke; Peyrot, Wouter J; Wu, Ying; Kristiansson, Kati; Demirkan, Ayse; Fornage, Myriam; Hassinen, Maija; Bielak, Lawrence F; Cadby, Gemma; Tanaka, Toshiko; Mägi, Reedik; van der Most, Peter J; Jackson, Anne U; Bragg-Gresham, Jennifer L; Vitart, Veronique; Marten, Jonathan; Navarro, Pau; Bellis, Claire; Pasko, Dorota; Johansson, Åsa; Snitker, Søren; Cheng, Ching-Yu; Eriksson, Joel; Lim, Unhee; Aadahl, Mette; Adair, Linda S; Amin, Najaf; Balkau, Beverley; Auvinen, Juha; Beilby, John; Bergman, Richard N; Bergmann, Sven; Bertoni, Alain G; Blangero, John; Bonnefond, Amélie; Bonnycastle, Lori L; Borja, Judith B; Brage, Søren; Busonero, Fabio; Buyske, Steve; Campbell, Harry; Chines, Peter S; Collins, Francis S; Corre, Tanguy; Smith, George Davey; Delgado, Graciela E; Dueker, Nicole; Dörr, Marcus; Ebeling, Tapani; Eiriksdottir, Gudny; Esko, Tõnu; Faul, Jessica D; Fu, Mao; Færch, Kristine; Gieger, Christian; Gläser, Sven; Gong, Jian; Gordon-Larsen, Penny; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; van Grootheest, Gerard; Harald, Kennet; Hastie, Nicholas D; Havulinna, Aki S; Hernandez, Dena G; Hindorff, Lucia; Hocking, Lynne J; Holmens, Oddgeir L; Holzapfel, Christina; Hottenga, Jouke Jan; Huang, Jie; Huang, Tao; Hui, Jennie; Huth, Cornelia; Hutri-Kähönen, Nina; James, Alan L; Jansson, John-Olov; Jhun, Min A; Juonala, Markus; Kinnunen, Leena; Koistinen, Heikki A; Kolcic, Ivana; Komulainen, Pirjo; Kuusisto, Johanna; Kvaløy, Kirsti; Kähönen, Mika; Lakka, Timo A; Launer, Lenore J; Lehne, Benjamin; Lindgren, Cecilia M; Lorentzon, Mattias; Luben, Robert; Marre, Michel; Milaneschi, Yuri; Monda, Keri L; Montgomery, Grant W; De Moor, Marleen H M; Mulas, Antonella; Müller-Nurasyid, Martina; Musk, A.W.; Männikkö, Reija; Männistö, Satu; Narisu, Narisu; Nauck, Matthias; Nettleton, Jennifer A; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Paternoster, Lavinia; Perez, Jeremiah; Perola, Markus; Peters, Annette; Peters, Ulrike; Peyser, Patricia A; Prokopenko, Inga; Puolijoki, Hannu; Raitakari, Olli T; Rankinen, Tuomo; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Ridker, Paul M; Rose, Lynda M; Rudan, Igor; Sarti, Cinzia; Sarzynski, Mark A; Savonen, Kai; Scott, William R; Sanna, Serena; Shuldiner, Alan R; Sidney, Steve; Silbernagel, Günther; Smith, Blair H; Smith, Jennifer A; Snieder, Harold; Stančáková, Alena; Sternfeld, Barbara; Swift, Amy J; Tammelin, Tuija; Tan, Sian-Tsung; Thorand, Barbara; Thuillier, Dorothée; Vandenput, Liesbeth; Vestergaard, Henrik; van Vliet-Ostaptchouk, Jana V; Vohl, Marie-Claude; Völker, Uwe; Waeber, Gérard; Walker, Mark; Wild, Sarah; Wong, Andrew; Wright, Alan F; Zillikens, M Carola; Zubair, Niha; Haiman, Christopher A; Lemarchand, Loic; Gyllensten, Ulf; Ohlsson, Claes; Hofman, Albert; Rivadeneira, Fernando; Uitterlinden, André G; Pérusse, Louis; Wilson, James F; Hayward, Caroline; Polasek, Ozren; Cucca, Francesco; Hveem, Kristian; Hartman, Catharina A; Tönjes, Anke; Bandinelli, Stefania; Palmer, Lyle J; Kardia, Sharon L R; Rauramaa, Rainer; Sørensen, Thorkild I A; Tuomilehto, Jaakko; Salomaa, Veikko; Penninx, Brenda W J H; de Geus, Eco J C; Boomsma, Dorret I; Lehtimäki, Terho; Mangino, Massimo; Laakso, Markku; Bouchard, Claude; Martin, Nicholas G; Kuh, Diana; Liu, YongMei; Linneberg, Allan; März, Winfried; Strauch, Konstantin; Kivimäki, Mika; Harris, Tamara B; Gudnason, Vilmundur; Völzke, Henry; Qi, Lu; Järvelin, Marjo-Riitta; Chambers, John C; Kooner, Jaspal S; Froguel, Philippe; Kooperberg, Charles; Vollenweider, Peter; Hallmans, Göran; Hansen, Torben; Pedersen, Oluf; Metspalu, Andres; Wareham, Nicholas J; Langenberg, Claudia; Weir, David R; Porteous, David J; Boerwinkle, Eric; Chasman, Daniel I; Abecasis, Gonçalo R; Barroso, Inês; McCarthy, Mark I; Frayling, Timothy M; O'Connell, Jeffrey R; van Duijn, Cornelia M; Boehnke, Michael; Heid, Iris M; Mohlke, Karen L; Strachan, David P; Fox, Caroline S; Liu, Ching-Ti; Hirschhorn, Joel N; Klein, Robert J; Johnson, Andrew D; Borecki, Ingrid B; Franks, Paul W; North, Kari E; Cupples, L Adrienne; Loos, Ruth J F; Kilpeläinen, Tuomas O
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults
Graff, Mariaelisa; Scott, Robert A.; Justice, Anne E.
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adu...
Aschard, Hugues; Lutz, Sharon; Maus, Bärbel; Duell, Eric J.; Fingerlin, Tasha; Chatterjee, Nilanjan; Kraft, Peter; Van Steen, Kristel
The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes. PMID:22760307
Full Text Available Genome-wide association studies (GWAS have identified many genetic susceptibility loci for colorectal cancer (CRC. However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO. Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10-8; permuted p-value 3.51x10-8 region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74-0.91]; P = 2.1×10-4 and TT genotypes (OR,0.62 [95% CI, 0.51-0.75]; P = 1.3×10-6 but not associated among those with the CC genotype (p = 0.059. No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk.
Newcomb, Polly A.; Campbell, Peter T.; Baron, John A.; Berndt, Sonja I.; Bezieau, Stephane; Brenner, Hermann; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Du, Mengmeng; Figueiredo, Jane C.; Gallinger, Steven; Giovannucci, Edward L.; Haile, Robert W.; Harrison, Tabitha A.; Hayes, Richard B.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jeon, Jihyoun; Jenkins, Mark A.; Küry, Sébastien; Le Marchand, Loic; Lin, Yi; Lindor, Noralane M.; Nishihara, Reiko; Ogino, Shuji; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Thibodeau, Stephen N.; Thornquist, Mark; Toth, Reka; Wallace, Robert; White, Emily; Jiao, Shuo; Lemire, Mathieu; Hsu, Li; Peters, Ulrike
Genome-wide association studies (GWAS) have identified many genetic susceptibility loci for colorectal cancer (CRC). However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10−8; permuted p-value 3.51x10-8) region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74–0.91]; P = 2.1×10−4) and TT genotypes (OR,0.62 [95% CI, 0.51–0.75]; P = 1.3×10−6) but not associated among those with the CC genotype (p = 0.059). No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk. PMID:27723779
Smith, Caren E; Follis, Jack L; Dashti, Hassan S
SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption. METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variati...
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
A.D. Børglum; D. Demontis; J. Grove (Jakob); J. Pallesen (J.); M.V. Hollegaard (Mads V); C.B. Pedersen (C.); A. Hedemand (A.); M. Mattheisen (Manuel); A.G. Uitterlinden (André); M. Nyegaard (M.); T.F. Orntoft (Torben); C. Wiuf (Carsten); M. Didriksen (Michael); M. Nordentoft (M.); M.M. Nö then (M.); M. Rietschel (Marcella); R.A. Ophoff (Roel); S. Cichon (Sven); R.H. Yolken (Robert); D.M. Hougaard (David); P.B. Mortensen; O. Mors
textabstractGenetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all
Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung
Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Full Text Available Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations.
Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer
Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318
Kathryn M Tsang
Full Text Available Effects of parental genotype or parent-offspring genetic interaction are well established in model organisms for a variety of traits. However, these transgenerational genetic models are rarely studied in humans. We have utilized an autism case-control study with 735 mother-child pairs to perform genome-wide screening for maternal genetic effects and maternal-offspring genetic interaction. We used simple models of single locus parent-child interaction and identified suggestive results (P<10(-4 that cannot be explained by main effects, but no genome-wide significant signals. Some of these maternal and maternal-child associations were in or adjacent to autism candidate genes including: PCDH9, FOXP1, GABRB3, NRXN1, RELN, MACROD2, FHIT, RORA, CNTN4, CNTNAP2, FAM135B, LAMA1, NFIA, NLGN4X, RAPGEF4, and SDK1. We attempted validation of potential autism association under maternal-specific models using maternal-paternal comparison in family-based GWAS datasets. Our results suggest that further study of parental genetic effects and parent-child interaction in autism is warranted.
Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.
Børglum, A D; Demontis, D; Grove, J
Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals...... born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases...... was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies....
Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.
Joanna L Davies
Full Text Available Genome-wide association study (GWAS data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into "ancestry groups" and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions.
Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.
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...
Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong
With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.
Sonuga-Barke, E.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.; Gill, M.; Anney, R.J.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Steinhausen, H.C.; Thompson, M.; Asherson, P.; Faraone, S.V.
Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid
Sonuga-Barke, E.J.S.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.P.; Gill, M.; Anney, R.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.; Sergeant, J.A.; Steinhausen, H.C.; Thompson, M.; Asherson, P.; Faraone, S.V.
Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid
Børglum, A D; Demontis, D; Grove, J; Pallesen, J; Hollegaard, M V; Pedersen, C B; Hedemand, A; Mattheisen, M; Uitterlinden, A; Nyegaard, M; Ørntoft, T; Wiuf, C; Didriksen, M; Nordentoft, M; Nöthen, M M; Rietschel, M; Ophoff, R A; Cichon, S; Yolken, R H; Hougaard, D M; Mortensen, P B; Mors, O
Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies.
Cardinale, S; Cambray, G
The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content
Beaty, Terri H; Ruczinski, Ingo; Murray, Jeffrey C
Nonsyndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome-wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international...... consortium. Family-based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption, and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G × E) interaction simultaneously, plus...... multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G × E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G × E interaction when...
Beaty, Terri H.; Ruczinski, Ingo; Murray, Jeffrey C.; Marazita, Mary L.; Munger, Ronald G.; Hetmanski, Jacqueline B.; Murray, Tanda; Redett, Richard J.; Fallin, M. Daniele; Liang, Kung Yee; Wu, Tao; Patel, Poorav J.; Jin, Sheng C.; Zhang, Tian Xiao; Schwender, Holger; Wu-Chou, Yah Huei; Chen, Philip K; Chong, Samuel S; Cheah, Felicia; Yeow, Vincent; Ye, Xiaoqian; Wang, Hong; Huang, Shangzhi; Jabs, Ethylin W.; Shi, Bing; Wilcox, Allen J.; Lie, Rolv T.; Jee, Sun Ha; Christensen, Kaare; Doheny, Kimberley F.; Pugh, Elizabeth W.; Ling, Hua; Scott, Alan F.
Non-syndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international consortium. Family based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G×E) interaction simultaneously, plus a separate 1 df test for G×E interaction alone. Conditional logistic regression models were used to estimate effects on risk to exposed and unexposed children. While no SNP achieved genome wide significance when considered alone, markers in several genes attained or approached genome wide significance when G×E interaction was included. Among these, MLLT3 and SMC2 on chromosome 9 showed multiple SNPs resulting in increased risk if the mother consumed alcohol during the peri-conceptual period (3 months prior to conception through the first trimester). TBK1 on chr. 12 and ZNF236 on chr. 18 showed multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G×E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G×E interaction when searching for genes influencing risk to complex and heterogeneous disorders, such as non-syndromic CP. PMID:21618603
Gref, Anna; Merid, Simon K; Gruzieva, Olena; Ballereau, Stéphane; Becker, Allan; Bellander, Tom; Bergström, Anna; Bossé, Yohan; Bottai, Matteo; Chan-Yeung, Moira; Fuertes, Elaine; Ierodiakonou, Despo; Jiang, Ruiwei; Joly, Stéphane; Jones, Meaghan; Kobor, Michael S; Korek, Michal; Kozyrskyj, Anita L; Kumar, Ashish; Lemonnier, Nathanaël; MacIntyre, Elaina; Ménard, Camille; Nickle, David; Obeidat, Ma'en; Pellet, Johann; Standl, Marie; Sääf, Annika; Söderhäll, Cilla; Tiesler, Carla M T; van den Berge, Maarten; Vonk, Judith M; Vora, Hita; Xu, Cheng-Jian; Antó, Josep M; Auffray, Charles; Brauer, Michael; Bousquet, Jean; Brunekreef, Bert; Gauderman, W James; Heinrich, Joachim; Kere, Juha; Koppelman, Gerard H; Postma, Dirkje; Carlsten, Christopher; Pershagen, Göran; Melén, Erik
The evidence supporting an association between traffic-related air pollution exposure and incident childhood asthma is inconsistent and may depend on genetic factors. To identify gene-environment interaction effects on childhood asthma using genome-wide single-nucleotide polymorphism (SNP) data and air pollution exposure. Identified loci were further analyzed at epigenetic and transcriptomic levels. We used land use regression models to estimate individual air pollution exposure (represented by outdoor NO 2 levels) at the birth address and performed a genome-wide interaction study for doctors' diagnoses of asthma up to 8 years in three European birth cohorts (n = 1,534) with look-up for interaction in two separate North American cohorts, CHS (Children's Health Study) and CAPPS/SAGE (Canadian Asthma Primary Prevention Study/Study of Asthma, Genetics and Environment) (n = 1,602 and 186 subjects, respectively). We assessed expression quantitative trait locus effects in human lung specimens and blood, as well as associations among air pollution exposure, methylation, and transcriptomic patterns. In the European cohorts, 186 SNPs had an interaction P asthma development and provided supportive evidence for interaction with air pollution for ADCY2, B4GALT5, and DLG2.
Feitosa, Mary F.; Barata, Llilda; Chu, Audrey Y.; Mahajan, Anubha; Hadley, David; Xue, Luting; Workalemahu, Tsegaselassie; den Hoed, Marcel; Ahluwalia, Tarunveer S.; Qi, Qibin; Ngwa, Julius S.; Quaye, Lydia; Eicher, John D.; Hayes, James E.; Cornelis, Marilyn; Kutalik, Zoltan; Lim, Elise; Luan, Jian’an; Huffman, Jennifer E.; Zhang, Weihua; Zhao, Wei; Griffin, Paula J.; Haller, Toomas; Ahmad, Shafqat; Marques-Vidal, Pedro M.; Bien, Stephanie; Yengo, Loic; Teumer, Alexander; Smith, Albert Vernon; Kumari, Meena; Harder, Marie Neergaard; Justesen, Johanne Marie; Kleber, Marcus E.; Hollensted, Mette; Lohman, Kurt; Rivera, Natalia V.; Whitfield, John B.; Zhao, Jing Hua; Stringham, Heather M.; Lyytikäinen, Leo-Pekka; Huppertz, Charlotte; Willemsen, Gonneke; Peyrot, Wouter J.; Wu, Ying; Kristiansson, Kati; Demirkan, Ayse; Fornage, Myriam; Hassinen, Maija; Bielak, Lawrence F.; Cadby, Gemma; Tanaka, Toshiko; Mägi, Reedik; van der Most, Peter J.; Jackson, Anne U.; Bragg-Gresham, Jennifer L.; Vitart, Veronique; Marten, Jonathan; Navarro, Pau; Bellis, Claire; Pasko, Dorota; Johansson, Åsa; Snitker, Søren; Cheng, Yu-Ching; Eriksson, Joel; Lim, Unhee; Aadahl, Mette; Adair, Linda S.; Amin, Najaf; Balkau, Beverley; Auvinen, Juha; Beilby, John; Bergman, Richard N.; Bergmann, Sven; Bertoni, Alain G.; Blangero, John; Bonnefond, Amélie; Bonnycastle, Lori L.; Borja, Judith B.; Brage, Søren; Busonero, Fabio; Buyske, Steve; Campbell, Harry; Chines, Peter S.; Collins, Francis S.; Corre, Tanguy; Smith, George Davey; Delgado, Graciela E.; Dueker, Nicole; Dörr, Marcus; Ebeling, Tapani; Eiriksdottir, Gudny; Esko, Tõnu; Faul, Jessica D.; Fu, Mao; Færch, Kristine; Gieger, Christian; Gläser, Sven; Gong, Jian; Gordon-Larsen, Penny; Grallert, Harald; Grammer, Tanja B.; Grarup, Niels; van Grootheest, Gerard; Harald, Kennet; Hastie, Nicholas D.; Havulinna, Aki S.; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J.; Holmens, Oddgeir L.; Holzapfel, Christina; Hottenga, Jouke Jan; Huang, Jie; Huang, Tao; Hui, Jennie; Huth, Cornelia; Hutri-Kähönen, Nina; James, Alan L.; Jansson, John-Olov; Jhun, Min A.; Juonala, Markus; Kinnunen, Leena; Koistinen, Heikki A.; Kolcic, Ivana; Komulainen, Pirjo; Kuusisto, Johanna; Kvaløy, Kirsti; Kähönen, Mika; Lakka, Timo A.; Launer, Lenore J.; Lehne, Benjamin; Lindgren, Cecilia M.; Lorentzon, Mattias; Luben, Robert; Marre, Michel; Milaneschi, Yuri; Monda, Keri L.; Montgomery, Grant W.; De Moor, Marleen H. M.; Mulas, Antonella; Müller-Nurasyid, Martina; Musk, A. W.; Männikkö, Reija; Männistö, Satu; Narisu, Narisu; Nauck, Matthias; Nettleton, Jennifer A.; Nolte, Ilja M.; Oldehinkel, Albertine J.; Olden, Matthias; Ong, Ken K.; Padmanabhan, Sandosh; Paternoster, Lavinia; Perez, Jeremiah; Perola, Markus; Peters, Annette; Peters, Ulrike; Peyser, Patricia A.; Prokopenko, Inga; Puolijoki, Hannu; Raitakari, Olli T.; Rankinen, Tuomo; Rasmussen-Torvik, Laura J.; Rawal, Rajesh; Ridker, Paul M.; Rose, Lynda M.; Rudan, Igor; Sarti, Cinzia; Sarzynski, Mark A.; Savonen, Kai; Scott, William R.; Sanna, Serena; Shuldiner, Alan R.; Sidney, Steve; Silbernagel, Günther; Smith, Blair H.; Smith, Jennifer A.; Snieder, Harold; Stančáková, Alena; Sternfeld, Barbara; Swift, Amy J.; Tammelin, Tuija; Tan, Sian-Tsung; Thorand, Barbara; Thuillier, Dorothée; Vandenput, Liesbeth; Vestergaard, Henrik; van Vliet-Ostaptchouk, Jana V.; Vohl, Marie-Claude; Völker, Uwe; Waeber, Gérard; Walker, Mark; Wild, Sarah; Wong, Andrew; Wright, Alan F.; Zillikens, M. Carola; Zubair, Niha; Haiman, Christopher A.; Lemarchand, Loic; Gyllensten, Ulf; Ohlsson, Claes; Hofman, Albert; Rivadeneira, Fernando; Uitterlinden, André G.; Pérusse, Louis; Wilson, James F.; Hayward, Caroline; Polasek, Ozren; Cucca, Francesco; Hveem, Kristian; Hartman, Catharina A.; Tönjes, Anke; Bandinelli, Stefania; Palmer, Lyle J.; Kardia, Sharon L. R.; Rauramaa, Rainer; Sørensen, Thorkild I. A.; Tuomilehto, Jaakko; Salomaa, Veikko; Penninx, Brenda W. J. H.; de Geus, Eco J. C.; Boomsma, Dorret I.; Lehtimäki, Terho; Mangino, Massimo; Laakso, Markku; Bouchard, Claude; Martin, Nicholas G.; Kuh, Diana; Liu, Yongmei; Linneberg, Allan; März, Winfried; Strauch, Konstantin; Kivimäki, Mika; Harris, Tamara B.; Gudnason, Vilmundur; Völzke, Henry; Qi, Lu; Järvelin, Marjo-Riitta; Chambers, John C.; Kooner, Jaspal S.; Froguel, Philippe; Kooperberg, Charles; Vollenweider, Peter; Hallmans, Göran; Hansen, Torben; Pedersen, Oluf; Metspalu, Andres; Wareham, Nicholas J.; Langenberg, Claudia; Weir, David R.; Porteous, David J.; Boerwinkle, Eric; Chasman, Daniel I.; Abecasis, Gonçalo R.; McCarthy, Mark I.; Frayling, Timothy M.; O’Connell, Jeffrey R.; van Duijn, Cornelia M.; Boehnke, Michael; Heid, Iris M.; Mohlke, Karen L.; Fox, Caroline S.; Hirschhorn, Joel N.; Johnson, Andrew D.; Borecki, Ingrid B.; Franks, Paul W.; North, Kari E.; Cupples, L. Adrienne; Loos, Ruth J. F.; Kilpeläinen, Tuomas O.
Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery. PMID:28448500
Full Text Available Physical activity (PA may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423 or other ancestry (n = 20,029. We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.
Taye H Hamza; Honglei Chen; Erin M Hill-Burns; Shannon L Rhodes; Jennifer Montimurro; Denise M Kay; Albert Tenesa; Victoria I Kusel; Patricia Sheehan; Muthukrishnan Eaaswarkhanth; Dora Yearout; Ali Samii; John W Roberts; Pinky Agarwal; Yvette Bordelon
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal compo...
Hong, Joon Ki; Jeong, Yong Dae; Cho, Eun Seok; Choi, Tae Jeong; Kim, Yong Min; Cho, Kyu Ho; Lee, Jae Bong; Lim, Hyun Tae; Lee, Deuk Hwan
The genetic effects of an individual on the phenotypes of its social partners, such as its pen mates, are known as social genetic effects. This study aims to identify the candidate genes for social (pen-mates') average daily gain (ADG) in pigs by using the genome-wide association approach. Social ADG (sADG) was the average ADG of unrelated pen-mates (strangers). We used the phenotype data (16,802 records) after correcting for batch (week), sex, pen, number of strangers (1 to 7 pigs) in the pen, full-sib rate (0% to 80%) within pen, and age at the end of the test. A total of 1,041 pigs from Landrace breeds were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel, which comprised 61,565 single nucleotide polymorphism (SNP) markers. After quality control, 909 individuals and 39,837 markers remained for sADG in genome-wide association study. We detected five new SNPs, all on chromosome 6, which have not been associated with social ADG or other growth traits to date. One SNP was inside the prostaglandin F2α receptor ( PTGFR ) gene, another SNP was located 22 kb upstream of gene interferon-induced protein 44 ( IFI44 ), and the last three SNPs were between 161 kb and 191 kb upstream of the EGF latrophilin and seven transmembrane domain-containing protein 1 ( ELTD1 ) gene. PTGFR, IFI44, and ELTD1 were never associated with social interaction and social genetic effects in any of the previous studies. The identification of several genomic regions, and candidate genes associated with social genetic effects reported here, could contribute to a better understanding of the genetic basis of interaction traits for ADG. In conclusion, we suggest that the PTGFR, IFI44, and ELTD1 may be used as a molecular marker for sADG, although their functional effect was not defined yet. Thus, it will be of interest to execute association studies in those genes.
Full Text Available Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI. Genome-wide association studies (GWAS have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2 × 10(-8. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.
Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V
Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits. PMID:27436263
Nivard, Michel G.; Middeldorp, Christel M.; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I.; Dolan, Conor V.
Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include
Adkins, D E; Clark, S L; Åberg, K; Hettema, J M; Bukszár, J; McClay, J L; Souza, R P; van den Oord, E J C G
Affecting about 1 in 12 Americans annually, depression is a leading cause of the global disease burden. While a range of effective antidepressants are now available, failure and relapse rates remain substantial, with intolerable side effect burden the most commonly cited reason for discontinuation. Thus, understanding individual differences in susceptibility to antidepressant therapy side effects will be essential to optimize depression treatment. Here we perform genome-wide association studies (GWAS) to identify genetic variation influencing susceptibility to citalopram-induced side effects. The analysis sample consisted of 1762 depression patients, successfully genotyped for 421K single-nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study. Outcomes included five indicators of citalopram side effects: general side effect burden, overall tolerability, sexual side effects, dizziness and vision/hearing side effects. Two SNPs met our genome-wide significance criterion (qeffects of citalopram on vision/hearing side effects (P=3.27 × 10(-8), q=0.026). The second genome-wide significant finding, representing a haplotype spanning ∼30 kb and eight genotyped SNPs in a gene desert on chromosome 13, was associated with general side effect burden (P=3.22 × 10(-7), q=0.096). Suggestive findings were also found for SNPs at LAMA1, AOX2P, EGFLAM, FHIT and RTP2. Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antidepressant medications.
Struchalin Maksim V
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.
Full Text Available Abstract Background Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases. A recent study in automatic detection of epistatic interactions shows that Markov Blanket-based methods are capable of finding genetic variants strongly associated with common diseases and reducing false positives when the number of instances is large. Unfortunately, a typical dataset from genome-wide association studies consists of very limited number of examples, where current methods including Markov Blanket-based method may perform poorly. Results To address small sample problems, we propose a Bayesian network-based approach (bNEAT to detect epistatic interactions. The proposed method also employs a Branch-and-Bound technique for learning. We apply the proposed method to simulated datasets based on four disease models and a real dataset. Experimental results show that our method outperforms Markov Blanket-based methods and other commonly-used methods, especially when the number of samples is small. Conclusions Our results show bNEAT can obtain a strong power regardless of the number of samples and is especially suitable for detecting epistatic interactions with slight or no marginal effects. The merits of the proposed approach lie in two aspects: a suitable score for Bayesian network structure learning that can reflect higher-order epistatic interactions and a heuristic Bayesian network structure learning method.
Sonuga-Barke, E.; Lasky-Su, J.; Neale, B.; Oades, R.D.; Chen, W.; Franke, B.; Buitelaar, J.K.; Banaschewski, T.; Ebstein, R.; Gill, M.; Anney, R.J.; Miranda, A.; Mulas, F.; Roeyers, H.; Rothenberger, A.
Studies of gene x environment (G x E) interaction in ADHD have previously focused on known risk genes for ADHD and environmentally mediated biological risk. Here we use G x E analysis in the context of a genome-wide association scan to identify novel genes whose effects on ADHD symptoms and comorbid conduct disorder are moderated by high maternal expressed emotion (EE). SNPs (600,000) were genotyped in 958 ADHD proband-parent trios. After applying data cleaning procedures we examined 429,981 ...
Shi, Min; Murray, Jeffrey C; Marazita, Mary L; Munger, Ronald G; Ruczinski, Ingo; Hetmanski, Jacqueline B; Wu, Tao; Murray, Tanda; Redett, Richard J; Wilcox, Allen J; Lie, Rolv T; Jabs, Ethylin Wang; Wu-Chou, Yah Huei; Chen, Philip K; Wang, Hong; Ye, Xiaoqian; Yeow, Vincent; Chong, Samuel S; Shi, Bing; Christensen, Kaare; Scott, Alan F; Patel, Poorav; Cheah, Felicia; Beaty, Terri H
We performed a genome wide association analysis of maternally-mediated genetic effects and parent-of-origin effects on risk of orofacial clefting using over 2,000 case-parent triads collected through an international cleft consortium. We used log-linear regression models to test individual SNPs. For SNPs with a p-value <10−5 for maternal genotypic effects, we also applied a haplotype-based method, TRIMM, to extract potential information from clusters of correlated SNPs. None of the SNPs were significant at the genome wide level. Our results suggest neither maternal genome nor parent of origin effects play major roles in the etiology of orofacial clefting in our sample. This finding is consistent with previous genetic studies and recent population-based cohort studies in Norway and Denmark, which showed no apparent difference between mother-to-offspring and father-to-offspring recurrence of clefting. We, however, cannot completely rule out maternal genome or parent of origin effects as risk factors because very small effects might not be detectable with our sample size, they may influence risk through interactions with environmental exposures or may act through a more complex network of interacting genes. Thus the most promising SNPs identified by this study may still be worth further investigation. PMID:22419666
Full Text Available To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac interfered with establishment of cell polarity, cyproheptadine (Periactin targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol and pimozide (Orap. Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.
Martínez, C A; Khare, K; Rahman, S; Elzo, M A
Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.
Jensen, Majken Karoline; Pers, Tune Hannes; Dworzynski, Piotr
in genes associated with risk of coronary heart disease (CHD). Methods and Results-Genome-wide association analyses of approximately approximate to 700 000 single-nucleotide polymorphisms in 899 incident CHD cases and 1823 age-and sex-matched controls within the Nurses' Health and the Health Professionals...... complex. Conclusions-The integration of a GWA study with PPI data successfully identifies a set of candidate susceptibility genes for incident CHD that would have been missed in single-marker GWA analysis. (Circ Cardiovasc Genet. 2011; 4:549-556.)...
Yuan, Han; Dougherty, Joseph D.
Lay Abstract Autism spectrum disorders (ASDs) are pervasive developmental disorders which have both a genetic and environmental component. One source of the environmental component is the in utero (prenatal) environment. The maternal genome can potentially contribute to the risk of autism in children by altering this prenatal environment. In this study, the possibility of maternal genotype effects was explored by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. We performed a case/control genome-wide association study (GWAS) using mothers of probands as cases and either fathers of probands or normal females as controls, using two collections of families with autism. We did not identify any SNP that reached significance and thus a common variant of large effect is unlikely. However, there was evidence for the possibility of a large number of alleles each carrying a small effect. This suggested that if there is a contribution to autism risk through common-variant maternal genetic effects, it may be the result of multiple loci of small effects. We did not investigate rare variants in this study. Scientific Abstract Like most psychiatric disorders, autism spectrum disorders have both a genetic and an environmental component. While previous studies have clearly demonstrated the contribution of in utero (prenatal) environment on autism risk, most of them focused on transient environmental factors. Based on a recent sibling study, we hypothesized that environmental factors could also come from the maternal genome, which would result in persistent effects across siblings. In this study, the possibility of maternal genotype effects was examined by looking for common variants (single nucleotide polymorphisms, or SNPs) in the maternal genome associated with increased risk of autism in children. A case/control genome-wide association study (GWAS) was performed using mothers of
Karlas, Alexander; Berre, Stefano; Couderc, Thérèse; Varjak, Margus; Braun, Peter; Meyer, Michael; Gangneux, Nicolas; Karo-Astover, Liis; Weege, Friderike; Raftery, Martin; Schönrich, Günther; Klemm, Uwe; Wurzlbauer, Anne; Bracher, Franz; Merits, Andres; Meyer, Thomas F; Lecuit, Marc
Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents.
Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous gene expression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous gene expression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in gene expression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on gene expression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.
Elisabeth M van Leeuwen
Full Text Available Genome-wide association studies (GWAS have revealed 74 single nucleotide polymorphisms (SNPs associated with high-density lipoprotein cholesterol (HDL blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS cohort I (RS-I using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III, we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011 when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098 and rs12442098 in SPATA8 (ENSG00000185594 being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.
Full Text Available Abstract Background MiRNA are about 22nt long small noncoding RNAs that post transcriptionally regulate gene expression in animals, plants and protozoa. Confident identification of MiRNA-Target Interactions (MTI is vital to understand their function. Currently, several integrated computational programs and databases are available for animal miRNAs, the mechanisms of which are significantly different from plant miRNAs. Methods Here we present an integrated MTI prediction and analysis toolkit (imiRTP for Arabidopsis thaliana. It features two important functions: (i combination of several effective plant miRNA target prediction methods provides a sufficiently large MTI candidate set, and (ii different filters allow for an efficient selection of potential targets. The modularity of imiRTP enables the prediction of high quality targets on genome-wide scale. Moreover, predicted MTIs can be presented in various ways, which allows for browsing through the putative target sites as well as conducting simple and advanced analyses. Results Results show that imiRTP could always find high quality candidates compared with single method by choosing appropriate filter and parameter. And we also reveal that a portion of plant miRNA could bind target genes out of coding region. Based on our results, imiRTP could facilitate the further study of Arabidopsis miRNAs in real use. All materials of imiRTP are freely available under a GNU license at (http://admis.fudan.edu.cn/projects/imiRTP.htm.
Full Text Available The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS, for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X
The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
Wesley K Thompson
Full Text Available Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD and the other for schizophrenia (SZ. A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the
Thompson, Wesley K; Wang, Yunpeng; Schork, Andrew J; Witoelar, Aree; Zuber, Verena; Xu, Shujing; Werge, Thomas; Holland, Dominic; Andreassen, Ole A; Dale, Anders M
Characterizing the distribution of effects from genome-wide genotyping data is crucial for understanding important aspects of the genetic architecture of complex traits, such as number or proportion of non-null loci, average proportion of phenotypic variance explained per non-null effect, power for discovery, and polygenic risk prediction. To this end, previous work has used effect-size models based on various distributions, including the normal and normal mixture distributions, among others. In this paper we propose a scale mixture of two normals model for effect size distributions of genome-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local false discovery rate, and power for discovery of a specified proportion of phenotypic variance explained from additive effects of loci surpassing a given significance threshold. We also examine the crucial issue of the impact of linkage disequilibrium (LD) on effect sizes and parameter estimates, both analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn's disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While capturing the general behavior of the data, this mixture model underestimates the tails of the CD effect size distribution. We discuss the implications of
Full Text Available Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.
Jane C Figueiredo
Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.
The single-nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains-1 (CSMD1) gene on 8p23.2, was recently identified as genome-wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non-carriers of the risk \\'A\\' allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk \\'A\\' allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified \\'A\\' risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.
Xi, Zhiyong; Gavotte, Laurent; Xie, Yan; Dobson, Stephen L
Background Intracellular Wolbachia bacteria are obligate, maternally-inherited, endosymbionts found frequently in insects and other invertebrates. The success of Wolbachia can be attributed in part to an ability to alter host reproduction via mechanisms including cytoplasmic incompatibility (CI), parthenogenesis, feminization and male killing. Despite substantial scientific effort, the molecular mechanisms underlying the Wolbachia/host interaction are unknown. Results Here, an in vitro Wolbachia infection was generated in the Drosophila S2 cell line, and transcription profiles of infected and uninfected cells were compared by microarray. Differentially-expressed patterns related to reproduction, immune response and heat stress response are observed, including multiple genes that have been previously reported to be involved in the Wolbachia/host interaction. Subsequent in vivo characterization of differentially-expressed products in gonads demonstrates that Angiotensin Converting Enzyme (Ance) varies between Wolbachia infected and uninfected flies and that the variation occurs in a sex-specific manner. Consistent with expectations for the conserved CI mechanism, the observed Ance expression pattern is repeatable in different Drosophila species and with different Wolbachia types. To examine Ance involvement in the CI phenotype, compatible and incompatible crosses of Ance mutant flies were conducted. Significant differences are observed in the egg hatch rate resulting from incompatible crosses, providing support for additional experiments examining for an interaction of Ance with the CI mechanism. Conclusion Wolbachia infection is shown to affect the expression of multiple host genes, including Ance. Evidence for potential Ance involvement in the CI mechanism is described, including the prior report of Ance in spermatid differentiation, Wolbachia-induced sex-specific effects on Ance expression and an Ance mutation effect on CI levels. The results support the use of
Xi, Zhiyong; Gavotte, Laurent; Xie, Yan; Dobson, Stephen L
Intracellular Wolbachia bacteria are obligate, maternally-inherited, endosymbionts found frequently in insects and other invertebrates. The success of Wolbachia can be attributed in part to an ability to alter host reproduction via mechanisms including cytoplasmic incompatibility (CI), parthenogenesis, feminization and male killing. Despite substantial scientific effort, the molecular mechanisms underlying the Wolbachia/host interaction are unknown. Here, an in vitro Wolbachia infection was generated in the Drosophila S2 cell line, and transcription profiles of infected and uninfected cells were compared by microarray. Differentially-expressed patterns related to reproduction, immune response and heat stress response are observed, including multiple genes that have been previously reported to be involved in the Wolbachia/host interaction. Subsequent in vivo characterization of differentially-expressed products in gonads demonstrates that Angiotensin Converting Enzyme (Ance) varies between Wolbachia infected and uninfected flies and that the variation occurs in a sex-specific manner. Consistent with expectations for the conserved CI mechanism, the observed Ance expression pattern is repeatable in different Drosophila species and with different Wolbachia types. To examine Ance involvement in the CI phenotype, compatible and incompatible crosses of Ance mutant flies were conducted. Significant differences are observed in the egg hatch rate resulting from incompatible crosses, providing support for additional experiments examining for an interaction of Ance with the CI mechanism. Wolbachia infection is shown to affect the expression of multiple host genes, including Ance. Evidence for potential Ance involvement in the CI mechanism is described, including the prior report of Ance in spermatid differentiation, Wolbachia-induced sex-specific effects on Ance expression and an Ance mutation effect on CI levels. The results support the use of Wolbachia infected cell cultures
Rose, Emma J
The single nucleotide polymorphism rs10503253 within the CUB and Sushi multiple domains-1 (CSMD1) gene on 8p23.2 has been identified as genome-wide significant for schizophrenia (SZ). This gene is of unknown function but has been implicated in multiple neurodevelopmental disorders that impact upon cognition, leading us to hypothesize that an effect on brain structure and function underlying cognitive processes may be part of the mechanism by which CMSD1 increases illness risk. To test this hypothesis, we investigated this CSMD1 variant in vivo in healthy participants in a magnetic resonance imaging (MRI) study comprised of both fMRI of spatial working memory (N = 50) and a voxel-based morphometry investigation of grey and white matter (WM) volume (N = 150). Analyses of these data indicated that the risk "A" allele was associated with comparatively reduced cortical activations in BA18, that is, middle occipital gyrus and cuneus; posterior brain regions that support maintenance processes during performance of a spatial working memory task. Conversely, there was an absence of significant structural differences in brain volume (i.e., grey or WM). In accordance with previous evidence, these data suggest that CSMD1 may mediate brain function related to cognitive processes (i.e., executive function); with the relatively deleterious effects of the identified "A" risk allele on brain activity possibly constituting part of the mechanism by which CSMD1 increases schizophrenia risk.
Zhu, Xuefeng; Wirén, Marianna; Sinha, Indranil
Mediator exists in a free form containing the Med12, Med13, CDK8, and CycC subunits (the Srb8-11 module) and a smaller form, which lacks these four subunits and associates with RNA polymerase II (Pol II), forming a holoenzyme. We use chromatin immunoprecipitation (ChIP) and DNA microarrays...... to investigate genome-wide localization of Mediator and the Srb8-11 module in fission yeast. Mediator and the Srb8-11 module display similar binding patterns, and interactions with promoters and upstream activating sequences correlate with increased transcription activity. Unexpectedly, Mediator also interacts...... with the downstream coding region of many genes. These interactions display a negative bias for positions closer to the 5' ends of open reading frames (ORFs) and appear functionally important, because downregulation of transcription in a temperature-sensitive med17 mutant strain correlates with increased Mediator...
Shi, Min; Murray, Jeff; Marazita, Mary L
We performed a genome wide association analysis of maternally-mediated genetic effects and parent-of-origin (POO) effects on risk of orofacial clefting (OC) using over 2,000 case-parent triads collected through an international cleft consortium. We used log-linear regression models to test indivi...... individual SNPs. For SNPs with a P-value...
Luciano, Michelle; Huffman, Jennifer E.; Arias-Vásquez, Alejandro; Vinkhuyzen, Anna A. E.; Middeldorp, Christel M.; Giegling, Ina; Payton, Antony; Davies, Gail; Zgaga, Lina; Janzing, Joost; Ke, Xiayi; Galesloot, Tessel; Hartmann, Annette M.; Ollier, William; Tenesa, Albert; Hayward, Caroline; Verhagen, Maaike; Montgomery, Grant W.; Hottenga, Jouke-Jan; Konte, Bettina; Starr, John M.; Vitart, Veronique; Vos, Pieter E.; Madden, Pamela A. F.; Willemsen, Gonneke; Konnerth, Heike; Horan, Michael A.; Porteous, David J.; Campbell, Harry; Vermeulen, Sita H.; Heath, Andrew C.; Wright, Alan; Polasek, Ozren; Kovacevic, Sanja B.; Hastie, Nicholas D.; Franke, Barbara; Boomsma, Dorret I.; Martin, Nicholas G.; Rujescu, Dan; Wilson, James F.; Buitelaar, Jan; Pendleton, Neil; Rudan, Igor; Deary, Ian J.
Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (similar to 2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of
Loo, Sandra K.; Shtir, Corina; Doyle, Alysa E.; Mick, Eric; McGough, James J.; McCracken, James; Biederman, Joseph; Smalley, Susan L.; Cantor, Rita M.; Faraone, Stephen V.; Nelson, Stanley F.
Objective: The purpose of the present study was to identify common genetic variants that are associated with human intelligence or general cognitive ability. Method: We performed a genome-wide association analysis with a dense set of 1 million single-nucleotide polymorphisms (SNPs) and quantitative intelligence scores within an ancestrally…
Winham, Stacey J.; Biernacka, Joanna M.
Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…
Lee, Myoungsook; Kwon, Dae Young; Kim, Myung-Sunny; Choi, Chong Ran; Park, Mi-Young; Kim, Ae-Jung
This is the first study to identify common genetic factors associated with the basal metabolic rate (BMR) and body mass index (BMI) in obese Korean women including overweight. This will be a basic study for future research of obese gene-BMR interaction. The experimental design was 2 by 2 with variables of BMR and BMI. A genome-wide association study (GWAS) of single nucleotide polymorphisms (SNPs) was conducted in the overweight and obesity (BMI > 23 kg/m(2)) compared to the normality, and in women with low BMR (BMR. A total of 140 SNPs reached formal genome-wide statistical significance in this study (P BMR (rs10786764; P = 8.0 × 10(-7), rs1040675; 2.3 × 10(-6)) and BMI (rs10786764; P = 2.5 × 10(-5), rs10786764; 6.57 × 10(-5)). The other genes related to BMI (HSD52, TMA16, MARCH1, NRG1, NRXN3, and STK4) yielded P BMR and BMI, including NRG3, OR8U8, BCL2L2-PABPN1, PABPN1, and SLC22A17 were identified in obese Korean women (P BMR- and BMI-related genes using GWAS. Although most of these newly established loci were not previously associated with obesity, they may provide new insights into body weight regulation. Our findings of five common genes associated with BMR and BMI in Koreans will serve as a reference for replication and validation of future studies on the metabolic rate.
Full Text Available Abstract Background Genome-wide association studies (GWAS do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD. Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci. This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci.
Full Text Available Analyses of viral protein-protein interactions are an important step to understand viral protein functions and their underlying molecular mechanisms. In this study, we adopted a mammalian two-hybrid system to screen the genome-wide intraviral protein-protein interactions of SARS coronavirus (SARS-CoV and therefrom revealed a number of novel interactions which could be partly confirmed by in vitro biochemical assays. Three pairs of the interactions identified were detected in both directions: non-structural protein (nsp 10 and nsp14, nsp10 and nsp16, and nsp7 and nsp8. The interactions between the multifunctional nsp10 and nsp14 or nsp16, which are the unique proteins found in the members of Nidovirales with large RNA genomes including coronaviruses and toroviruses, may have important implication for the mechanisms of replication/transcription complex assembly and functions of these viruses. Using a SARS-CoV replicon expressing a luciferase reporter under the control of a transcription regulating sequence, it has been shown that several viral proteins (N, X and SUD domains of nsp3, and nsp12 provided in trans stimulated the replicon reporter activity, indicating that these proteins may regulate coronavirus replication and transcription. Collectively, our findings provide a basis and platform for further characterization of the functions and mechanisms of coronavirus proteins.
Croteau-Chonka, Damien C; Marvelle, Amanda F; Lange, Ethan M; Lee, Nanette R; Adair, Linda S; Lange, Leslie A; Mohlke, Karen L
Increased values of multiple adiposity-related anthropometric traits are important risk factors for many common complex diseases. We performed a genome-wide association (GWA) study for four quantitative traits related to body size and adiposity (BMI, weight, waist circumference, and height) in a cohort of 1,792 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). This is the first GWA study of anthropometric traits in Filipinos, a population experiencing a rapid transition into a more obesogenic environment. In addition to identifying suggestive evidence of additional single-nucleotide polymorphism (SNP) association signals (P Filipinos and provide further insight into the effects of BDNF, FTO, and MC4R on BMI.
In high-dimensional studies such as genome-wide association studies, the correction for multiple testing in order to control total type I error results in decreased power to detect modest effects. We present a new analytical approach based on the higher criticism statistic that allows identification of the presence of modest effects. We apply our method to the genome-wide study of rheumatoid arthritis provided in the Genetic Analysis Workshop 16 Problem 1 data set. There is evidence for unknown bias in this study that could be explained by the presence of undetected modest effects. We compared the asymptotic and empirical thresholds for the higher criticism statistic. Using the asymptotic threshold we detected the presence of modest effects genome-wide. We also detected modest effects using 90th percentile of the empirical null distribution as a threshold; however, there is no such evidence when the 95th and 99th percentiles were used. While the higher criticism method suggests that there is some evidence for modest effects, interpreting individual single-nucleotide polymorphisms with significant higher criticism statistics is of undermined value. The goal of higher criticism is to alert the researcher that genetic effects remain to be discovered and to promote the use of more targeted and powerful studies to detect the remaining effects. PMID:20018032
Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan
Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.
Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias
Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.
Full Text Available Genome-wide insight into insect pest response to the infection of Beauveria bassiana (fungal insect pathogen is critical for genetic improvement of fungal insecticides but has been poorly explored. We constructed three pairs of transcriptomes of Plutella xylostella larvae at 24, 36 and 48 hours post treatment of infection (hptI and of control (hptC for insight into the host-pathogen interaction at genomic level. There were 2143, 3200 and 2967 host genes differentially expressed at 24, 36 and 48 hptI/hptC respectively. These infection-responsive genes (~15% of the host genome were enriched in various immune processes, such as complement and coagulation cascades, protein digestion and absorption, and drug metabolism-cytochrome P450. Fungal penetration into cuticle and host defense reaction began at 24 hptI, followed by most intensive host immune response at 36 hptI and attenuated immunity at 48 hptI. Contrastingly, 44% of fungal genes were differentially expressed in the infection course and enriched in several biological processes, such as antioxidant activity, peroxidase activity and proteolysis. There were 1636 fungal genes co-expressed during 24-48 hptI, including 116 encoding putative secretion proteins. Our results provide novel insights into the insect-pathogen interaction and help to probe molecular mechanisms involved in the fungal infection to the global pest.
Umeyama, Taichi; Ito, Takashi
Protein-DNA interactions provide the basis for chromatin structure and gene regulation. Comprehensive identification of protein-occupied sites is thus vital to an in-depth understanding of genome function. Dimethyl sulfate (DMS) is a chemical probe that has long been used to detect footprints of DNA-bound proteins in vitro and in vivo. Here, we describe a genomic footprinting method, dimethyl sulfate sequencing (DMS-seq), which exploits the cell-permeable nature of DMS to obviate the need for nuclear isolation. This feature makes DMS-seq simple in practice and removes the potential risk of protein re-localization during nuclear isolation. DMS-seq successfully detects transcription factors bound to cis-regulatory elements and non-canonical chromatin particles in nucleosome-free regions. Furthermore, an unexpected preference of DMS confers on DMS-seq a unique potential to directly detect nucleosome centers without using genetic manipulation. We expect that DMS-seq will serve as a characteristic method for genome-wide interrogation of in vivo protein-DNA interactions. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Raviram, Ramya; Rocha, Pedro P; Müller, Christian L; Miraldi, Emily R; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina; Bonneau, Richard; Skok, Jane A
4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.
van Haaften, Gijs; Vastenhouw, Nadine L; Nollen, Ellen A A; Plasterk, Ronald H A; Tijsterman, Marcel
Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect
Speliotes, Elizabeth K; Yerges-Armstrong, Laura M; Wu, Jun
steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (~26%-27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n¿=¿880 to 3,070). By carrying out a fixed-effects meta......-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ~2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome......Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic...
Thomas W Winkler
Full Text Available Genome-wide association studies (GWAS have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI, a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE, sex-specific effects (G x SEX or age-specific effects that differed between men and women (G x AGE x SEX. For BMI, we identified 15 loci (11 previously established for main effects, four novel that showed significant (FDR<5% age-specific effects, of which 11 had larger effects in younger (<50y than in older adults (≥50y. No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
Full Text Available Autism is a common heritable neurodevelopmental disorder with complex etiology. Several genome-wide linkage and association scans have been carried out to identify regions harboring genes related to autism or autism spectrum disorders, with mixed results. Given the overlap in autism features with genetic abnormalities known to be associated with imprinting, one possible reason for lack of consistency would be the influence of parent-of-origin effects that may mask the ability to detect linkage and association.We have performed a genome-wide linkage scan that accounts for potential parent-of-origin effects using 16,311 SNPs among families from the Autism Genetic Resource Exchange (AGRE and the National Institute of Mental Health (NIMH autism repository. We report parametric (GH, Genehunter and allele-sharing linkage (Aspex results using a broad spectrum disorder case definition. Paternal-origin genome-wide statistically significant linkage was observed on chromosomes 4 (LOD(GH = 3.79, empirical p<0.005 and LOD(Aspex = 2.96, p = 0.008, 15 (LOD(GH = 3.09, empirical p<0.005 and LOD(Aspex = 3.62, empirical p = 0.003 and 20 (LOD(GH = 3.36, empirical p<0.005 and LOD(Aspex = 3.38, empirical p = 0.006.These regions may harbor imprinted sites associated with the development of autism and offer fruitful domains for molecular investigation into the role of epigenetic mechanisms in autism.
Dana B Hancock
Full Text Available Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1, and its ratio to forced vital capacity (FEV(1/FVC. Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA of single nucleotide polymorphism (SNP and SNP-by-smoking (ever-smoking or pack-years associations on FEV(1 and FEV(1/FVC across 19 studies (total N = 50,047. We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = 5.00×10(-11, HLA-DQB1 and HLA-DQA2 (smallest P(JMA = 4.35×10(-9, and KCNJ2 and SOX9 (smallest P(JMA = 1.28×10(-8 were associated with FEV(1/FVC or FEV(1 in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.
Full Text Available 4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait" that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.
Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2dfcoffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that
Hamza, Taye H; Chen, Honglei; Hill-Burns, Erin M; Rhodes, Shannon L; Montimurro, Jennifer; Kay, Denise M; Tenesa, Albert; Kusel, Victoria I; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M; Kendler, Kenneth S; Bacanu, Silviu-Alin; Scott, William K; Ritz, Beate; Nutt, John; Factor, Stewart A; Zabetian, Cyrus P; Payami, Haydeh
Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df) = 10(-6), GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7)) but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication) = 0.59, P(Replication) = 10(-3); OR(Pooled) = 0.51, P(Pooled) = 7×10(-8). Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3)), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13)). Imputation revealed a block of SNPs that achieved P(2df)coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify
Taye H Hamza
Full Text Available Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD. We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC, and we performed a genome-wide association and interaction study (GWAIS, testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df = 10(-6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7 but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication = 0.59, P(Replication = 10(-3; OR(Pooled = 0.51, P(Pooled = 7×10(-8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3, whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13. Imputation revealed a block of SNPs that achieved P(2df<5×10(-8 in GWAIS, and OR = 0.41, P = 3×10(-8 in heavy coffee-drinkers. This study is proof of
Ramasamy, Adaikalavan; Curjuric, Ivan; Coin, Lachlan J; Kumar, Ashish; McArdle, Wendy L; Imboden, Medea; Leynaert, Benedicte; Kogevinas, Manolis; Schmid-Grendelmeier, Peter; Pekkanen, Juha; Wjst, Matthias; Bircher, Andreas J; Sovio, Ulla; Rochat, Thierry; Hartikainen, Anna-Liisa; Balding, David J; Jarvelin, Marjo-Riitta; Probst-Hensch, Nicole; Strachan, David P; Jarvis, Deborah L
Hay fever or seasonal allergic rhinitis (AR) is a chronic disorder associated with IgE sensitization to grass. The underlying genetic variants have not been studied comprehensively. There is overwhelming evidence that those who have older siblings have less AR, although the mechanism for this remains unclear. We sought to identify common genetic variant associations with prevalent AR and grass sensitization using existing genome-wide association study (GWAS) data and to determine whether genetic variants modify the protective effect of older siblings. Approximately 2.2 million genotyped or imputed single nucleotide polymorphisms were investigated in 4 large European adult cohorts for AR (3,933 self-reported cases vs 8,965 control subjects) and grass sensitization (2,315 cases vs 10,032 control subjects). Three loci reached genome-wide significance for either phenotype. The HLA variant rs7775228, which cis-regulates HLA-DRB4, was strongly associated with grass sensitization and weakly with AR (P(grass) = 1.6 × 10(-9); P(AR) = 8.0 × 10(-3)). Variants in a locus near chromosome 11 open reading frame 30 (C11orf30) and leucine-rich repeat containing 32 (LRRC32), which was previously associated with atopic dermatitis and eczema, were also strongly associated with both phenotypes (rs2155219; P(grass) = 9.4 × 10(-9); P(AR) = 3.8 × 10(-8)). The third genome-wide significant variant was rs17513503 (P(grass) = 1.2 × 10(-8); PAR = 7.4 × 10(-7)) which was located near transmembrane protein 232 (TMEM232) and solute carrier family 25, member 46 (SLC25A46). Twelve further loci with suggestive associations were also identified. Using a candidate gene approach, where we considered variants within 164 genes previously thought to be important, we found variants in 3 further genes that may be of interest: thymic stromal lymphopoietin (TSLP), Toll-like receptor 6 (TLR6) and nucleotide-binding oligomerization domain containing 1 (NOD1/CARD4). We found no evidence for variants
Full Text Available Abstract Background Overlapping genes (OGs in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest. Description BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ and Unweighted Pair-Group Method using Arithmetic averages (UPGMA. Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint. Conclusion BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by
Weidinger, Stephan; Willis-Owen, Saffron A G; Kamatani, Yoichiro; Baurecht, Hansjörg; Morar, Nilesh; Liang, Liming; Edser, Pauline; Street, Teresa; Rodriguez, Elke; O'Regan, Grainne M; Beattie, Paula; Fölster-Holst, Regina; Franke, Andre; Novak, Natalija; Fahy, Caoimhe M; Winge, Mårten C G; Kabesch, Michael; Illig, Thomas; Heath, Simon; Söderhäll, Cilla; Melén, Erik; Pershagen, Göran; Kere, Juha; Bradley, Maria; Lieden, Agne; Nordenskjold, Magnus; Harper, John I; McLean, W H Irwin; Brown, Sara J; Cookson, William O C; Lathrop, G Mark; Irvine, Alan D; Moffatt, Miriam F
Atopic dermatitis (AD) is the most common dermatological disease of childhood. Many children with AD have asthma and AD shares regions of genetic linkage with psoriasis, another chronic inflammatory skin disease. We present here a genome-wide association study (GWAS) of childhood-onset AD in 1563 European cases with known asthma status and 4054 European controls. Using Illumina genotyping followed by imputation, we generated 268 034 consensus genotypes and in excess of 2 million single nucleotide polymorphisms (SNPs) for analysis. Association signals were assessed for replication in a second panel of 2286 European cases and 3160 European controls. Four loci achieved genome-wide significance for AD and replicated consistently across all cohorts. These included the epidermal differentiation complex (EDC) on chromosome 1, the genomic region proximal to LRRC32 on chromosome 11, the RAD50/IL13 locus on chromosome 5 and the major histocompatibility complex (MHC) on chromosome 6; reflecting action of classical HLA alleles. We observed variation in the contribution towards co-morbid asthma for these regions of association. We further explored the genetic relationship between AD, asthma and psoriasis by examining previously identified susceptibility SNPs for these diseases. We found considerable overlap between AD and psoriasis together with variable coincidence between allergic rhinitis (AR) and asthma. Our results indicate that the pathogenesis of AD incorporates immune and epidermal barrier defects with combinations of specific and overlapping effects at individual loci.
Pütz, B; Kam-Thong, T; Karbalai, N; Altmann, A; Müller-Myhsok, B
Until recently, genotype studies were limited to the investigation of single SNP effects due to the computational burden incurred when studying pairwise interactions of SNPs. However, some genetic effects as simple as coloring (in plants and animals) cannot be ascribed to a single locus but only understood when epistasis is taken into account . It is expected that such effects are also found in complex diseases where many genes contribute to the clinical outcome of affected individuals. Only recently have such problems become feasible computationally. The inherently parallel structure of the problem makes it a perfect candidate for massive parallelization on either grid or cloud architectures. Since we are also dealing with confidential patient data, we were not able to consider a cloud-based solution but had to find a way to process the data in-house and aimed to build a local GPU-based grid structure. Sequential epistatsis calculations were ported to GPU using CUDA at various levels. Parallelization on the CPU was compared to corresponding GPU counterparts with regards to performance and cost. A cost-effective solution was created by combining custom-built nodes equipped with relatively inexpensive consumer-level graphics cards with highly parallel GPUs in a local grid. The GPU method outperforms current cluster-based systems on a price/performance criterion, as a single GPU shows speed performance comparable up to 200 CPU cores. The outlined approach will work for problems that easily lend themselves to massive parallelization. Code for various tasks has been made available and ongoing development of tools will further ease the transition from sequential to parallel algorithms.
Binder, Alexandra M; Michels, Karin B
Investigation of the biological mechanism by which folate acts to affect fetal development can inform appraisal of expected benefits and risk management. This research is ethically imperative given the ubiquity of folic acid fortified products in the US. Considering that folate is an essential component in the one-carbon metabolism pathway that provides methyl groups for DNA methylation, epigenetic modifications provide a putative molecular mechanism mediating the effect of folic acid supplementation on neonatal and pediatric outcomes. In this study we use a Mendelian Randomization Unnecessary approach to assess the effect of red blood cell (RBC) folate on genome-wide DNA methylation in cord blood. Site-specific CpG methylation within the proximal promoter regions of approximately 14,500 genes was analyzed using the Illumina Infinium Human Methylation27 Bead Chip for 50 infants from the Epigenetic Birth Cohort at Brigham and Women's Hospital in Boston. Using methylenetetrahydrofolate reductase genotype as the instrument, the Mendelian Randomization approach identified 7 CpG loci with a significant (mostly positive) association between RBC folate and methylation level. Among the genes in closest proximity to this significant subset of CpG loci, several enriched biologic processes were involved in nucleic acid transport and metabolic processing. Compared to the standard ordinary least squares regression method, our estimates were demonstrated to be more robust to unmeasured confounding. To the authors' knowledge, this is the largest genome-wide analysis of the effects of folate on methylation pattern, and the first to employ Mendelian Randomization to assess the effects of an exposure on epigenetic modifications. These results can help guide future analyses of the causal effects of periconceptional folate levels on candidate pathways.
Wielen, van der Nikkie; Paulus, Givan; Avesaat, van Mark; Masclee, Ad; Meijerink, Jocelijn; Bouvy, Nicole
Background: Bariatric surgery is an effective intervention strategy in obesity, resulting in sustained weight loss and a reduction of comorbidities. Gastroplication, using the articulating circular endoscopic stapler, was recently introduced as a transoral bariatric technique. This procedure reduces
Pohjanvirta, Raimo; Boutros, Paul C.; Moffat, Ivy D.; Linden, Jere; Wendelin, Dominique; Okey, Allan B.
Acute progressive feed restriction (APFR) represents a specific form of caloric restriction in which feed availability is increasingly curtailed over a period of a few days to a few weeks. It is often used for control animals in toxicological and pharmacological studies on compounds causing body weight loss to equalize weight changes between experimental and control groups and thereby, intuitively, to also set their metabolic states to the same phase. However, scientific justification for this procedure is lacking. In the present study, we analyzed by microarrays the impact on hepatic gene expression in rats of two APFR regimens that caused identical diminution of body weight (19%) but differed slightly in duration (4 vs. 10 days). In addition, white adipose tissue (WAT) was also subjected to the transcriptomic analysis on day-4. The data revealed that the two regimens led to distinct patterns of differentially expressed genes in liver, albeit some major pathways of energy metabolism were similarly affected (particularly fatty acid and amino acid catabolism). The reason for the divergence appeared to be entrainment by the longer APFR protocol of peripheral oscillator genes, which resulted in derailment of circadian rhythms and consequent interaction of altered diurnal fluctuations with metabolic adjustments in gene expression activities. WAT proved to be highly unresponsive to the 4-day APFR as only 17 mRNA levels were influenced by the treatment. This study demonstrates that body weight is a poor proxy of metabolic state and that the customary protocols of feed restriction can lead to rhythm entrainment
Nan, Jia Nancy; Ververis, Katherine; Bollu, Sameera; Rodd, Annabelle L; Swarup, Oshi; Karagiannis, Tom C
Epidemiological and clinical studies have established the health benefits of the Mediterranean diet, an important component of which are olives and olive oil derived from the olive tree (Olea Europea). It is now well-established that not only the major fatty acid constituents, but also the minor phenolic components, in olives and olive oil have important health benefits. Emerging research over the past decade has highlighted the beneficial effects of a range of phenolic compounds from olives and olive oil, particularly for cardiovascular diseases, metabolic syndrome and inflammatory conditions. Mechanisms of action include potent antioxidant and anti-inflammatory effects. Further, accumulating evidence indicates the potential of the polyphenols and potent antioxidants, hydroxytyrosol and oleuropein in oncology. Numerous studies, both in vitro and in vivo, have demonstrated the anticancer effects of hydroxytyrosol which include chemopreventive and cell-specific cytotoxic and apoptotic effects. Indeed, the precise molecular mechanisms accounting for the antioxidant, anti-inflammatory and anticancer properties are now becoming clear and this is, at least in part, due to high through-put gene transcription profiling. Initially, we constructed phylogenetic trees to visualize the evolutionary relationship of members of the Oleaceae family and secondly, between plants producing hydroxytyrosol to make inferences of potential similarities or differences in their medicinal properties and to identify novel plant candidates for the treatment and prevention of disease. Furthermore, given the recent interest in hydroxytyrosol as a potential anticancer agent and chemopreventative we utilized transcriptome analysis in the erythroleukemic cell line K562, to investigate the effects of hydroxytyrosol on three gene pathways: the complement system, The Warburg effect and chromatin remodeling to ascertain relevant gene candidates in the prevention of cancer.
Thompson, Wesley K.; Wang, Yunpeng; Schork, Andrew J.
-wide association study (GWAS) test statistics. Test statistics corresponding to null associations are modeled as random draws from a normal distribution with zero mean; test statistics corresponding to non-null associations are also modeled as normal with zero mean, but with larger variance. The model is fit via...... analytically and in simulations. We apply this approach to meta-analysis test statistics from two large GWAS, one for Crohn’s disease (CD) and the other for schizophrenia (SZ). A scale mixture of two normals distribution provides an excellent fit to the SZ nonparametric replication effect size estimates. While...... minimizing discrepancies between the parametric mixture model and resampling-based nonparametric estimates of replication effect sizes and variances. We describe in detail the implications of this model for estimation of the non-null proportion, the probability of replication in de novo samples, the local...
Eduardo da Cruz Gouveia Pimentel
Full Text Available The aim of this study was to compare iterative and direct solvers for estimation of marker effects in genomic selection. One iterative and two direct methods were used: Gauss-Seidel with Residual Update, Cholesky Decomposition and Gentleman-Givens rotations. For resembling different scenarios with respect to number of markers and of genotyped animals, a simulated data set divided into 25 subsets was used. Number of markers ranged from 1,200 to 5,925 and number of animals ranged from 1,200 to 5,865. Methods were also applied to real data comprising 3081 individuals genotyped for 45181 SNPs. Results from simulated data showed that the iterative solver was substantially faster than direct methods for larger numbers of markers. Use of a direct solver may allow for computing (covariances of SNP effects. When applied to real data, performance of the iterative method varied substantially, depending on the level of ill-conditioning of the coefficient matrix. From results with real data, Gentleman-Givens rotations would be the method of choice in this particular application as it provided an exact solution within a fairly reasonable time frame (less than two hours. It would indeed be the preferred method whenever computer resources allow its use.
Reddy, Umesh K; Nimmakayala, Padma; Levi, Amnon; Abburi, Venkata Lakshmi; Saminathan, Thangasamy; Tomason, Yan R; Vajja, Gopinath; Reddy, Rishi; Abburi, Lavanya; Wehner, Todd C; Ronin, Yefim; Karol, Abraham
We used genotyping by sequencing to identify a set of 10,480 single nucleotide polymorphism (SNP) markers for constructing a high-resolution genetic map of 1096 cM for watermelon. We assessed the genome-wide variation in recombination rate (GWRR) across the map and found an association between GWRR and genome-wide nucleotide diversity. Collinearity between the map and the genome-wide reference sequence for watermelon was studied to identify inconsistency and chromosome rearrangements. We assessed genome-wide nucleotide diversity, linkage disequilibrium (LD), and selective sweep for wild, semi-wild, and domesticated accessions of Citrullus lanatus var. lanatus to track signals of domestication. Principal component analysis combined with chromosome-wide phylogenetic study based on 1563 SNPs obtained after LD pruning with minor allele frequency of 0.05 resolved the differences between semi-wild and wild accessions as well as relationships among worldwide sweet watermelon. Population structure analysis revealed predominant ancestries for wild, semi-wild, and domesticated watermelons as well as admixture of various ancestries that were important for domestication. Sliding window analysis of Tajima's D across various chromosomes was used to resolve selective sweep. LD decay was estimated for various chromosomes. We identified a strong selective sweep on chromosome 3 consisting of important genes that might have had a role in sweet watermelon domestication. Copyright © 2014 Reddy et al.
Winkler, Thomas W.; Heid, Iris M.; Gorski, Mathias
Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of Eur...
Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert
Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize...
Mohammadnejad, Afsaneh; Brasch-Andersen, Charlotte; Haagerup, Annette
-value = 2.8 × 10−5) sits in C5orf66 gene on 5q31. Poster abstract 2 Discussion: Our study was able to detect a significant SNP rs4251459 mapping to IRAK4 gene on 12q12 locus which appeared to increase the risk of AR in females than males. This gene has previously been reported to have a sex dependent effect...... on AR. C5orf66 loci might also be an interesting candidate for AR, but its role warrants further validations. Additionally, pathway analysis from GSEA identified a pathway related to immune system which is biologically meaningful and supportive. In conclusion, our study revealed the gene-sex interaction...
Zhao, Huiying; Nyholt, Dale R.; Yang, Yuanhao; Wang, Jihua; Yang, Yuedong
Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous...
Juan J. Pierella Karlusich
transduction, transcriptional regulation and hormone-based pathways. Remarkable interactions with proteasomal protein degradation were observed. The results provide the first genome-wide, comprehensive picture illustrating the relevance of chloroplast redox status in biotic stress responses.
Elijah R Behr
Full Text Available Marked prolongation of the QT interval on the electrocardiogram associated with the polymorphic ventricular tachycardia Torsades de Pointes is a serious adverse event during treatment with antiarrhythmic drugs and other culprit medications, and is a common cause for drug relabeling and withdrawal. Although clinical risk factors have been identified, the syndrome remains unpredictable in an individual patient. Here we used genome-wide association analysis to search for common predisposing genetic variants. Cases of drug-induced Torsades de Pointes (diTdP, treatment tolerant controls, and general population controls were ascertained across multiple sites using common definitions, and genotyped on the Illumina 610k or 1M-Duo BeadChips. Principal Components Analysis was used to select 216 Northwestern European diTdP cases and 771 ancestry-matched controls, including treatment-tolerant and general population subjects. With these sample sizes, there is 80% power to detect a variant at genome-wide significance with minor allele frequency of 10% and conferring an odds ratio of ≥2.7. Tests of association were carried out for each single nucleotide polymorphism (SNP by logistic regression adjusting for gender and population structure. No SNP reached genome wide-significance; the variant with the lowest P value was rs2276314, a non-synonymous coding variant in C18orf21 (p = 3×10(-7, odds ratio = 2, 95% confidence intervals: 1.5-2.6. The haplotype formed by rs2276314 and a second SNP, rs767531, was significantly more frequent in controls than cases (p = 3×10(-9. Expanding the number of controls and a gene-based analysis did not yield significant associations. This study argues that common genomic variants do not contribute importantly to risk for drug-induced Torsades de Pointes across multiple drugs.
Full Text Available Understanding how infected cells respond to Ebola virus (EBOV and how this response changes during the process of viral replication and transcription are very important for establishing effective antiviral strategies. In this study, we conducted a genome-wide screen to identify long non-coding RNAs (lncRNAs, circular RNAs (circRNAs, micro RNAs (miRNAs, and mRNAs differentially expressed during replication and transcription using a tetracistronic transcription and replication-competent virus-like particle (trVLP system that models the life cycle of EBOV in 293T cells. To characterize the expression patterns of these differentially expressed RNAs, we performed a series cluster analysis, and up- or down-regulated genes were selected to establish a gene co-expression network. Competing endogenous RNA (ceRNA networks based on the RNAs responsible for the effects induced by EBOV replication and transcription in human cells, including circRNAs, lncRNAs, miRNAs, and mRNAs, were constructed for the first time. Based on these networks, the interaction details of circRNA-chr19 were explored. Our results demonstrated that circRNA-chr19 targeting miR-30b-3p regulated CLDN18 expression by functioning as a ceRNA. These findings may have important implications for further studies of the mechanisms of EBOV replication and transcription. These RNAs potentially have important functions and may be promising targets for EBOV therapy.
Turner, Leslie M; Harr, Bettina
Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone.
Acikel, Cengizhan; Aydin Son, Yesim; Celik, Cemil; Gul, Husamettin
Multifactor dimensionality reduction (MDR) is a nonparametric approach that can be used to detect relevant interactions between single-nucleotide polymorphisms (SNPs). The aim of this study was to build the best genomic model based on SNP associations and to identify candidate polymorphisms that are the underlying molecular basis of the bipolar disorders. This study was performed on Whole-Genome Association Study of Bipolar Disorder (dbGaP [database of Genotypes and Phenotypes] study accession number: phs000017.v3.p1) data. After preprocessing of the genotyping data, three classification-based data mining methods (ie, random forest, naïve Bayes, and k-nearest neighbor) were performed. Additionally, as a nonparametric, model-free approach, the MDR method was used to evaluate the SNP profiles. The validity of these methods was evaluated using true classification rate, recall (sensitivity), precision (positive predictive value), and F-measure. Random forests, naïve Bayes, and k-nearest neighbors identified 16, 13, and ten candidate SNPs, respectively. Surprisingly, the top six SNPs were reported by all three methods. Random forests and k-nearest neighbors were more successful than naïve Bayes, with recall values >0.95. On the other hand, MDR generated a model with comparable predictive performance based on five SNPs. Although different SNP profiles were identified in MDR compared to the classification-based models, all models mapped SNPs to the DOCK10 gene. Three classification-based data mining approaches, random forests, naïve Bayes, and k-nearest neighbors, have prioritized similar SNP profiles as predictors of bipolar disorders, in contrast to MDR, which has found different SNPs through analysis of two-way and three-way interactions. The reduced number of associated SNPs discovered by MDR, without loss in the classification performance, would facilitate validation studies and decision support models, and would reduce the cost to develop predictive and
Full Text Available Large-scale proteomic analyses in Escherichia coli have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI screens can provide insights into the biological role(s of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in E. coli describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.
Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand
PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).
Jacobsen, S C; Brøns, Charlotte; Bork-Jensen, Jette
Energy-dense diets that are high in fat are associated with a risk of metabolic diseases. The underlying molecular mechanisms could involve epigenetics, as recent data show altered DNA methylation of putative type 2 diabetes candidate genes in response to high-fat diets. We examined the effect...... of a short-term high-fat overfeeding (HFO) diet on genome-wide DNA methylation patterns in human skeletal muscle....
Rebbeck, Timothy R.; Weber, Anita L.; Walker, Amy H.; Stefflova, Klara; Tran, Teo V.; Spangler, Elaine; Chang, Bao-Li; Zeigler-Johnson, Charnita M.
Background Disparities in cancer defined by race, age, or gender are well established. However, demographic metrics are surrogates for the complex contributions of genotypes, exposures, health care, socioeconomic and sociocultural environment, and many other factors. Macro-environmental factors represent novel surrogates for exposures, lifestyle and other factors that are difficult to measure but may influence cancer outcomes. Methods We applied a “multilevel molecular epidemiology” approach using a prospective cohort of 444 White prostate cancer cases who underwent prostatectomy and were followed until biochemical failure (BF) or censoring without BF. We applied Cox regression models to test for joint effects of 86 genome-wide association study-identified genotypes and macro-environmental contextual effects after geocoding all cases to their residential census tracts. All analyses were adjusted for age at diagnosis and tumor aggressiveness. Results Residents living in macroenvironments with a high proportion of older single heads of household, high rates of vacant housing, or high unemployment had shorter time until BF post-surgery after adjustment for patient age and tumor aggressiveness. After correction for multiple testing, genotypes alone did not predict time to BF, but interactions predicting time to BF were observed for MSMB (rs10993994) and percent of older single head of households (p=0.0004), and for HNF1B/TCF2 (rs4430796) and macroenvironment per capita income (p=0.0002). Conclusions Context-specific macro-environmental effects of genotype may improve the ability to identify groups that may experience poor prostate cancer outcomes. Impact Risk estimation and clinical translation of genotype information may require an understanding of both individual-level and macroenvironmental context. PMID:20826827
Rebbeck, Timothy R; Weber, Anita L; Walker, Amy H; Stefflova, Klara; Tran, Teo V; Spangler, Elaine; Chang, Bao-Li; Zeigler-Johnson, Charnita M
Disparities in cancer defined by race, age, or gender are well established. However, demographic metrics are surrogates for the complex contributions of genotypes, exposures, health care, socioeconomic and sociocultural environment, and many other factors. Macroenvironmental factors represent novel surrogates for exposures, lifestyle, and other factors that are difficult to measure but might influence cancer outcomes. We applied a "multilevel molecular epidemiology" approach using a prospective cohort of 444 White prostate cancer cases who underwent prostatectomy and were followed until biochemical failure (BF) or censoring without BF. We applied Cox regression models to test for joint effects of 86 genome-wide association study-identified genotypes and macroenvironment contextual effects after geocoding all cases to their residential census tracts. All analyses were adjusted for age at diagnosis and tumor aggressiveness. Residents living in census tracts with a high proportion of older single heads of household, high rates of vacant housing, or high unemployment had shorter time until BF postsurgery after adjustment for patient age and tumor aggressiveness. After correction for multiple testing, genotypes alone did not predict time to BF, but interactions predicting time to BF were observed for MSMB (rs10993994) and percentage of older single heads of households (P = 0.0004), and for HNF1B/TCF2 (rs4430796) and census tract per capita income (P = 0.0002). The context-specific macroenvironmental effects of genotype might improve the ability to identify groups that might experience poor prostate cancer outcomes. Risk estimation and clinical translation of genotype information might require an understanding of both individual- and macroenvironment-level context. (c) 2010 AACR.
Zhao, Huiying; Nyholt, Dale R; Yang, Yuanhao; Wang, Jihua; Yang, Yuedong
Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .
T.W. Winkler (Thomas W.); A.E. Justice (Anne); M.J. Graff (Maud J.L.); Barata, L. (Llilda); M.F. Feitosa (Mary Furlan); Chu, S. (Su); J. Czajkowski (Jacek); T. Esko (Tõnu); M. Fall (Magnus); T.O. Kilpeläinen (Tuomas); Y. Lu (Yingchang); R. Mägi (Reedik); E. Mihailov (Evelin); T.H. Pers (Tune); Rüeger, S. (Sina); A. Teumer (Alexander); G.B. Ehret (Georg); T. Ferreira (Teresa); N.L. Heard-Costa (Nancy); J. Karjalainen (Juha); V. Lagou (Vasiliki); A. Mahajan (Anubha); Neinast, M.D. (Michael D.); I. Prokopenko (Inga); J. Simino (Jeannette); T.M. Teslovich (Tanya M.); R. Jansen; H.J. Westra (Harm-Jan); C.C. White (Charles); D. Absher (Devin); T.S. Ahluwalia (Tarunveer Singh); S. Ahmad (Shafqat); E. Albrecht (Eva); A.C. Alves (Alexessander Couto); Bragg-Gresham, J.L. (Jennifer L.); A.J. de Craen (Anton); J.C. Bis (Joshua); A. Bonnefond (Amélie); G. Boucher (Gabrielle); G. Cadby (Gemma); Y.-C. Cheng (Yu-Ching); Chiang, C.W. (Charleston W K); G. Delgado; A. Demirkan (Ayşe); N. Dueker (Nicole); N. Eklund (Niina); G. Eiriksdottir (Gudny); J. Eriksson (Joel); B. Feenstra (Bjarke); K. Fischer (Krista); F. Frau (Francesca); T.E. Galesloot (Tessel); F. Geller (Frank); A. Goel (Anuj); M. Gorski (Mathias); T.B. Grammer (Tanja); S. Gustafsson (Stefan); Haitjema, S. (Saskia); J.J. Hottenga (Jouke Jan); J.E. Huffman (Jennifer); A.U. Jackson (Anne); K.B. Jacobs (Kevin); A. Johansson (Åsa); M. Kaakinen (Marika); M.E. Kleber (Marcus); J. Lahti (Jari); I.M. Leach (Irene Mateo); Lehne, B. (Benjamin); Liu, Y. (Youfang); K.S. Lo; M. Lorentzon (Mattias); J. Luan (Jian'An); P.A. Madden (Pamela); M. Mangino (Massimo); B. McKnight (Barbara); Medina-Gomez, C. (Carolina); K.L. Monda (Keri); M.E. Montasser (May E.); G. Müller (Gabriele); M. Müller-Nurasyid (Martina); I.M. Nolte (Ilja); Panoutsopoulou, K. (Kalliope); L. Pascoe (Laura); L. Paternoster (Lavinia); N.W. Rayner (Nigel William); F. Renström (Frida); Rizzi, F. (Federica); L.M. Rose (Lynda); Ryan, K.A. (Kathy A.); P. Salo (Perttu); S. Sanna (Serena); H. Scharnagl (Hubert); Shi, J. (Jianxin); A.V. Smith (Albert Vernon); L. Southam (Lorraine); A. Stancáková (Alena); V. Steinthorsdottir (Valgerdur); R.J. Strawbridge (Rona); Sung, Y.J. (Yun Ju); I. Tachmazidou (Ioanna); T. Tanaka (Toshiko); G. Thorleifsson (Gudmar); S. Trompet (Stella); N. Pervjakova (Natalia); J.P. Tyrer (Jonathan); L. Vandenput (Liesbeth); S.W. Van Der Laan (Sander W.); N. van der Velde (Nathalie); J. van Setten (Jessica); J.V. van Vliet-Ostaptchouk (Jana); N. Verweij (Niek); E. Vlachopoulou (Efthymia); L. Waite (Lindsay); S.R. Wang (Sophie); Z. Wang (Zhaoming); S.H. Wild (Sarah); C. Willenborg (Christina); J.F. Wilson (James); A. Wong (Andrew); Yang, J. (Jian); L. Yengo (Loic); L.M. Yerges-Armstrong (Laura); Yu, L. (Lei); W. Zhang (Weihua); Zhao, J.H. (Jing Hua); E.A. Andersson (Ehm Astrid); S.J.L. Bakker (Stephan); D. Baldassarre (Damiano); Banasik, K. (Karina); Barcella, M. (Matteo); Barlassina, C. (Cristina); C. Bellis (Claire); P. Benaglio (Paola); J. Blangero (John); M. Blüher (Matthias); Bonnet, F. (Fabrice); L.L. Bonnycastle (Lori); H.A. Boyd (Heather); M. Bruinenberg (M.); Buchman, A.S. (Aron S.); H. Campbell (Harry); Y.D. Chen (Y.); P.S. Chines (Peter); S. Claudi-Boehm (Simone); J.W. Cole (John W.); F.S. Collins (Francis); E.J.C. de Geus (Eco); L.C.P.G.M. de Groot (Lisette); M. Dimitriou (Maria); J. Duan (Jubao); S. Enroth (Stefan); E. Eury (Elodie); A.-E. Farmaki (Aliki-Eleni); N.G. Forouhi (Nita); N. Friedrich (Nele); P.V. Gejman (Pablo); B. Gigante (Bruna); N. Glorioso (Nicola); A. Go (Attie); R.F. Gottesman (Rebecca); J. Gräßler (Jürgen); H. Grallert (Harald); N. Grarup (Niels); Gu, Y.-M. (Yu-Mei); L. Broer (Linda); A.C. Ham (Annelies); T. Hansen (T.); T.B. Harris (Tamara); C.A. Hartman (Catharina A.); Hassinen, M. (Maija); N. Hastie (Nick); A.T. Hattersley (Andrew); A.C. Heath (Andrew); A.K. Henders (Anjali); D.G. Hernandez (Dena); H.L. Hillege (Hans); O.L. Holmen (Oddgeir); G.K. Hovingh (Kees); J. Hui (Jennie); Husemoen, L.L. (Lise L.); Hutri-Kähönen, N. (Nina); P.G. Hysi (Pirro); T. Illig (Thomas); P.L. de Jager (Philip); S. Jalilzadeh (Shapour); T. Jorgensen (Torben); J.W. Jukema (Jan Wouter); Juonala, M. (Markus); S. Kanoni (Stavroula); M. Karaleftheri (Maria); K.T. Khaw; L. Kinnunen (Leena); T. Kittner (Thomas); W. Koenig (Wolfgang); I. Kolcic (Ivana); P. Kovacs (Peter); Krarup, N.T. (Nikolaj T.); W. Kratzer (Wolfgang); Krüger, J. (Janine); Kuh, D. (Diana); M. Kumari (Meena); T. Kyriakou (Theodosios); C. Langenberg (Claudia); L. Lannfelt (Lars); C. Lanzani (Chiara); V. Lotay (Vaneet); L.J. Launer (Lenore); K. Leander (Karin); J. Lindström (Jaana); A. Linneberg (Allan); Liu, Y.-P. (Yan-Ping); S. Lobbens (Stéphane); R.N. Luben (Robert); V. Lyssenko (Valeriya); S. Männistö (Satu); P.K. Magnusson (Patrik); W.L. McArdle (Wendy); C. Menni (Cristina); S. Merger (Sigrun); L. Milani (Lili); Montgomery, G.W. (Grant W.); A.P. Morris (Andrew); N. Narisu (Narisu); M. Nelis (Mari); K.K. Ong (Ken); A. Palotie (Aarno); L. Perusse (Louis); I. Pichler (Irene); M.G. Pilia (Maria Grazia); A. Pouta (Anneli); Rheinberger, M. (Myriam); Ribel-Madsen, R. (Rasmus); Richards, M. (Marcus); K.M. Rice (Kenneth); T.K. Rice (Treva K.); C. Rivolta (Carlo); V. Salomaa (Veikko); A.R. Sanders (Alan); M.A. Sarzynski (Mark A.); S. Scholtens (Salome); R.A. Scott (Robert); W.R. Scott (William R.); S. Sebert (Sylvain); S. Sengupta (Sebanti); B. Sennblad (Bengt); T. Seufferlein (Thomas); A. Silveira (Angela); P.E. Slagboom (Eline); J.H. Smit (Jan); T. Sparsø (Thomas); K. Stirrups (Kathy); R.P. Stolk (Ronald); H.M. Stringham (Heather); Swertz, M.A. (Morris A.); A.J. Swift (Amy); A.C. Syvänen; S.-T. Tan (Sian-Tsung); B. Thorand (Barbara); A. Tönjes (Anke); Tremblay, A. (Angelo); E. Tsafantakis (Emmanouil); P.J. van der Most (Peter); U. Völker (Uwe); M.-C. Vohl (Marie-Claude); J.M. Vonk (Judith); M. Waldenberger (Melanie); Walker, R.W. (Ryan W.); R. Wennauer (Roman); E. Widen; G.A.H.M. Willemsen (Gonneke); T. Wilsgaard (Tom); A.F. Wright (Alan); M.C. Zillikens (Carola); S. Van Dijk (Suzanne); N.M. van Schoor (Natasja); F.W. Asselbergs (Folkert); P.I.W. de Bakker (Paul); J.S. Beckmann (Jacques); J.P. Beilby (John); D.A. Bennett (David A.); R.N. Bergman (Richard); S.M. Bergmann (Sven); C.A. Böger (Carsten); B.O. Boehm (Bernhard); E.A. Boerwinkle (Eric); D.I. Boomsma (Dorret); S.R. Bornstein (Stefan); E.P. Bottinger (Erwin); C. Bouchard (Claude); J.C. Chambers (John); S.J. Chanock (Stephen); D.I. Chasman (Daniel); F. Cucca (Francesco); D. Cusi (Daniele); G.V. Dedoussis (George); J. Erdmann (Jeanette); K. Hagen (Knut); D. Evans; U. de Faire (Ulf); M. Farrall (Martin); L. Ferrucci (Luigi); I. Ford (Ian); L. Franke (Lude); P.W. Franks (Paul); P. Froguel (Philippe); R.T. Gansevoort (Ron); C. Gieger (Christian); H. Grönberg (Henrik); V. Gudnason (Vilmundur); U. Gyllensten (Ulf); P. Hall (Per); A. Hamsten (Anders); P. van der Harst (Pim); C. Hayward (Caroline); M. Heliovaara (Markku); C. Hengstenberg (Christian); A.A. Hicks (Andrew); A. Hingorani (Aroon); A. Hofman (Albert); Hu, F. (Frank); H.V. Huikuri (Heikki); K. Hveem (Kristian); A. James (Alan); Jordan, J.M. (Joanne M.); A. Jula (Antti); M. Kähönen (Mika); E. Kajantie (Eero); S. Kathiresan (Sekar); L.A.L.M. Kiemeney (Bart); M. Kivimaki (Mika); P. Knekt; H. Koistinen (Heikki); J.S. Kooner (Jaspal S.); S. Koskinen (Seppo); J. Kuusisto (Johanna); W. Maerz (Winfried); N.G. Martin (Nicholas); M. Laakso (Markku); T.A. Lakka (Timo); T. Lehtimäki (Terho); G. Lettre (Guillaume); D.F. Levinson (Douglas); W.H.L. Kao (Wen); M.L. Lokki; Mäntyselkä, P. (Pekka); M. Melbye (Mads); A. Metspalu (Andres); B.D. Mitchell (Braxton); F.L. Moll (Frans); J.C. Murray (Jeffrey); A.W. Musk (Arthur); M.S. Nieminen (Markku); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); B.A. Oostra (Ben); C. Palmer (Cameron); J.S. Pankow (James); G. Pasterkamp (Gerard); N.L. Pedersen (Nancy); O. Pedersen (Oluf); B.W.J.H. Penninx (Brenda); M. Perola (Markus); A. Peters (Annette); O. Polasek (Ozren); P.P. Pramstaller (Peter Paul); Psaty, B.M. (Bruce M.); Qi, L. (Lu); T. Quertermous (Thomas); Raitakari, O.T. (Olli T.); T. Rankinen (Tuomo); R. Rauramaa (Rainer); P.M. Ridker (Paul); J.D. Rioux (John); F. Rivadeneira Ramirez (Fernando); J.I. Rotter (Jerome I.); I. Rudan (Igor); H.M. den Ruijter (Hester ); J. Saltevo (Juha); N. Sattar (Naveed); Schunkert, H. (Heribert); P.E.H. Schwarz (Peter); A.R. Shuldiner (Alan); J. Sinisalo (Juha); H. Snieder (Harold); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); Staessen, J.A. (Jan A.); Stefania, B. (Bandinelli); U. Thorsteinsdottir (Unnur); M. Stumvoll (Michael); J.-C. Tardif (Jean-Claude); E. Tremoli (Elena); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); M. Uusitupa (Matti); A.L.M. Verbeek; S.H.H.M. Vermeulen (Sita); J. Viikari (Jorma); Vitart, V. (Veronique); H. Völzke (Henry); P. Vollenweider (Peter); G. Waeber (Gérard); M. Walker (Mark); H. Wallaschofski (Henri); N.J. Wareham (Nick); H. Watkins (Hugh); E. Zeggini (Eleftheria); A. Chakravarti (Aravinda); Clegg, D.J. (Deborah J.); L.A. Cupples (Adrienne); P. Gordon-Larsen (Penny); C.E. Jaquish (Cashell); D.C. Rao (Dabeeru C.); Abecasis, G.R. (Goncalo R.); T.L. Assimes (Themistocles); I.E. Barroso (Inês); S.I. Berndt (Sonja); M. Boehnke (Michael); P. Deloukas (Panagiotis); C.S. Fox (Caroline); L. Groop (Leif); D. Hunter (David); E. Ingelsson (Erik); R.C. Kaplan (Robert); McCarthy, M.I. (Mark I.); K.L. Mohlke (Karen); J.R. O´Connell; Schlessinger, D. (David); D.P. Strachan (David); J-A. Zwart (John-Anker); C.M. van Duijn (Cornelia); J.N. Hirschhorn (Joel); C.M. Lindgren (Cecilia M.); I.M. Heid (Iris); K.E. North (Kari); I.B. Borecki (Ingrid); Z. Kutalik (Zoltán); R.J.F. Loos (Ruth)
textabstractGenome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ
Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions.
Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy
The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study
Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions
Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT
Full Text Available Abstract Background Social insects, such as honey bees, use molecular, physiological and behavioral responses to combat pathogens and parasites. The honey bee genome contains all of the canonical insect immune response pathways, and several studies have demonstrated that pathogens can activate expression of immune effectors. Honey bees also use behavioral responses, termed social immunity, to collectively defend their hives from pathogens and parasites. These responses include hygienic behavior (where workers remove diseased brood and allo-grooming (where workers remove ectoparasites from nestmates. We have previously demonstrated that immunostimulation causes changes in the cuticular hydrocarbon profiles of workers, which results in altered worker-worker social interactions. Thus, cuticular hydrocarbons may enable workers to identify sick nestmates, and adjust their behavior in response. Here, we test the specificity of behavioral, chemical and genomic responses to immunostimulation by challenging workers with a panel of different immune stimulants (saline, Sephadex beads and Gram-negative bacteria E. coli. Results While only bacteria-injected bees elicited altered behavioral responses from healthy nestmates compared to controls, all treatments resulted in significant changes in cuticular hydrocarbon profiles. Immunostimulation caused significant changes in expression of hundreds of genes, the majority of which have not been identified as members of the canonical immune response pathways. Furthermore, several new candidate genes that may play a role in cuticular hydrocarbon biosynthesis were identified. Effects of immune challenge expression of several genes involved in immune response, cuticular hydrocarbon biosynthesis, and the Notch signaling pathway were confirmed using quantitative real-time PCR. Finally, we identified common genes regulated by pathogen challenge in honey bees and other insects. Conclusions These results demonstrate that
De Smet, Lina; De Koker, Dieter; Hawley, Alyse K; Foster, Leonard J; De Vos, Paul; de Graaf, Dirk C
Paenibacillus larvae, the causal agent of American Foulbrood disease (AFB), affects honey bee health worldwide. The present study investigates the effect of bodily fluids from honey bee larvae on growth velocity and transcription for this Gram-positive, endospore-forming bacterium. It was observed that larval fluids accelerate the growth and lead to higher bacterial densities during stationary phase. The genome-wide transcriptional response of in vitro cultures of P. larvae to larval fluids was studied by microarray technology. Early responses of P. larvae to larval fluids are characterized by a general down-regulation of oligopeptide and sugar transporter genes, as well as by amino acid and carbohydrate metabolic genes, among others. Late responses are dominated by general down-regulation of sporulation genes and up-regulation of phage-related genes. A theoretical mechanism of carbon catabolite repression is discussed.
Rozman, Vita; Kunej, Tanja
Harnessing the genomics big data requires innovation in how we extract and interpret biologically relevant variants. Currently, there is no established catalog of prioritized missense variants associated with deleterious protein function phenotypes. We report in this study, to the best of our knowledge, the first genome-wide prioritization of sequence variants with the most deleterious effect on protein function (potentially deleterious variants [pDelVars]) in nine vertebrate species: human, cattle, horse, sheep, pig, dog, rat, mouse, and zebrafish. The analysis was conducted using the Ensembl/BioMart tool. Genes comprising pDelVars in the highest number of examined species were identified using a Python script. Multiple genomic alignments of the selected genes were built to identify interspecies orthologous potentially deleterious variants, which we defined as the "ortho-pDelVars." Genome-wide prioritization revealed that in humans, 0.12% of the known variants are predicted to be deleterious. In seven out of nine examined vertebrate species, the genes encoding the multiple PDZ domain crumbs cell polarity complex component (MPDZ) and the transforming acidic coiled-coil containing protein 2 (TACC2) comprise pDelVars. Five interspecies ortho-pDelVars were identified in three genes. These findings offer new ways to harness genomics big data by facilitating the identification of functional polymorphisms in humans and animal models and thus provide a future basis for optimization of protocols for whole genome prioritization of pDelVars and screening of orthologous sequence variants. The approach presented here can inform various postgenomic applications such as personalized medicine and multiomics study of health interventions (iatromics).
Smoller, J.W.; Craddock, N.; Kendler, K.; Lee, P.H.; Neale, B.M.; Nurnberger, J.I.; Ripke, S.; Santangelo, S.; Sullivan, P.F.; Buitelaar, J.K.; Franke, B.; et al.,
BACKGROUND: Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics
Min Jin Go
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.
Full Text Available Opioid analgesics are widely used for the treatment of moderate to severe pain. The analgesic effects of opioids are well known to vary among individuals. The present study focused on the genetic factors that are associated with interindividual differences in pain and opioid sensitivity. We conducted a multistage genome-wide association study in subjects who were scheduled to undergo mandibular sagittal split ramus osteotomy and were not medicated until they received fentanyl for the induction of anesthesia. We preoperatively conducted the cold pressor-induced pain test before and after fentanyl administration. The rs13093031 and rs12633508 single-nucleotide polymorphisms (SNPs near the LOC728432 gene region and rs6961071 SNP in the tcag7.1213 gene region were significantly associated with the analgesic effect of fentanyl, based on differences in pain perception latency before and after fentanyl administration. The associations of these three SNPs that were identified in our exploratory study have not been previously reported. The two polymorphic loci (rs13093031 and rs12633508 were shown to be in strong linkage disequilibrium. Subjects with the G/G genotype of the rs13093031 and rs6961071 SNPs presented lower fentanyl-induced analgesia. Our findings provide a basis for investigating genetics-based analgesic sensitivity and personalized pain control. Keywords: Opioid sensitivity, Analgesia, Fentanyl, Polymorphism, GWAS
Vrieze, S. I.; Iacono, W. G.; McGue, M.
This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations...
Quarto, Tiziana; Paparella, Isabella; De Tullio, Davide; Viscanti, Giovanna; Fazio, Leonardo; Taurisano, Paolo; Romano, Raffaella; Rampino, Antonio; Masellis, Rita; Popolizio, Teresa; Selvaggi, Pierluigi; Pergola, Giulio; Bertolino, Alessandro; Blasi, Giuseppe
The brain functional mechanisms translating genetic risk into emotional symptoms in schizophrenia (SCZ) may include abnormal functional integration between areas key for emotion processing, such as the amygdala and the lateral prefrontal cortex (LPFC). Indeed, investigation of these mechanisms is also complicated by emotion processing comprising different subcomponents and by disease-associated state variables. Here, our aim was to investigate the relationship between risk for SCZ and effective connectivity between the amygdala and the LPFC during different subcomponents of emotion processing. Thus, we first characterized with dynamic causal modeling (DCM) physiological patterns of LPFC-amygdala effective connectivity in healthy controls (HC) during implicit and explicit emotion processing. Then, we compared DCM patterns in a subsample of HC, in patients with SCZ and in healthy siblings of patients (SIB), matched for demographics. Finally, we investigated in HC association of LPFC-amygdala effective connectivity with a genome-wide supported variant increasing genetic risk for SCZ and possibly relevant to emotion processing (DRD2 rs2514218). In HC, we found that a "bottom-up" amygdala-to-LPFC pattern during implicit processing and a "top-down" LPFC-to-amygdala pattern during explicit processing were the most likely directional models of effective connectivity. Differently, implicit emotion processing in SIB, SCZ, and HC homozygous for the SCZ risk rs2514218 C allele was associated with decreased probability for the "bottom-up" as well as with increased probability for the "top-down" model. These findings suggest that task-specific anomaly in the directional flow of information or disconnection between the amygdala and the LPFC is a good candidate endophenotype of SCZ. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: email@example.com.
Beaumont, R.N. (Robin N.); N.M. Warrington (Nicole); A. Cavadino (Alana); A.W.R. Tyrrell; M. Nodzenski (Michael); M. Horikoshi (Momoko); F. Geller (Frank); R. Myhre (Ronny); R.C. Richmond (Rebecca C.); Paternoster, L. (Lavinia); J.P. Bradfield (Jonathan); E. Kreiner-Møller (Eskil); V. Huikari (Ville); S. Metrustry (Sarah); K.L. Lunetta (Kathryn); J.N. Painter (Jodie N.); J.J. Hottenga (Jouke Jan); C. Allard (Catherine); S.J. Barton (Sheila J.); Espinosa, A. (Ana); J.A. Marsh (Julie); C. Potter (Catherine); Zhang, G. (Ge); W.Q. Ang (Wei); D. Berry (Diane); L. Bouchard (Luigi); S. Das (Shikta); H. Hakonarson (Hakon); J. Heikkinen (Jani); Helgeland, Ø. (Øyvind); B. Hocher (Berthold); A. Hofman (Albert); H.M. Inskip (Hazel); S.E. Jones (Samuel E.); M. Kogevinas (Manolis); P.A. Lind (Penelope); L. Marullo (Letizia); S.E. Medland (Sarah Elizabeth); Murray, A. (Anna); Murray, J.C. (Jeffrey C.); Njølstad, P.R. (Pa l R.); C. Nohr (Christian); C. Reichetzeder (Christoph); S.M. Ring (Susan); K.S. Ruth (Katherine S.); L. Santa-Marina (Loreto); D.M. Scholtens (Denise M.); Sebert, S. (Sylvain); V. Sengpiel (Verena); Tuke, M.A. (Marcus A.); Vaudel, M. (Marc); M.N. Weedon (Michael); G.A.H.M. Willemsen (Gonneke); Wood, A.R. (Andrew R.); Yaghootkar, H. (Hanieh); Muglia, L.J. (Louis J.); M. Bartels (Meike); C.L. Relton (Caroline); C.E. Pennell (Craig); L. Chatzi (Leda); Estivill, X. (Xavier); Holloway, J.W. (John W.); D.I. Boomsma (Dorret); Montgomery, G.W. (Grant W.); J. Murabito (Joanne); T.D. Spector (Timothy); Power, C. (Christine); Järvelin, M.-R. (Marjo-Ritta); Bisgaard, H. (Hans); Grant, S.F.A. (Struan F.A.); Sørensen, T.I.A. (Thorkild I.A.); Jaddoe, V.W. (Vincent W.); B. Jacobsson (Bo); Melbye, M. (Mads); McCarthy, M.I. (Mark I.); A.T. Hattersley (Andrew); Hayes, M.G. (M. Geoffrey); T.M. Frayling (Timothy); M.-F. Hivert (Marie-France); J.F. Felix (Janine); Hyppönen, E. (Elina); Lowe, W.L. (William L.); Evans, D.M. (David M.); Lawlor, D.A. (Debbie A.); B. Feenstra (Bjarke); R.M. Freathy (Rachel)
textabstractGenome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal
J Stephen Dumler
Full Text Available Anaplasma phagocytophilum, an obligate intracellular prokaryote, infects neutrophils and alters cardinal functions via reprogrammed transcription. Large contiguous regions of neutrophil chromosomes are differentially expressed during infection. Secreted A. phagocytophilum effector AnkA transits into the neutrophil or granulocyte nucleus to complex with DNA in heterochromatin across all chromosomes. AnkA binds to gene promoters to dampen cis-transcription and also has features of matrix attachment region (MAR-binding proteins that regulate three-dimensional chromatin architecture and coordinate transcriptional programs encoded in topologically-associated chromatin domains. We hypothesize that identification of additional AnkA binding sites will better delineate how A. phagocytophilum infection results in reprogramming of the neutrophil genome. Using AnkA-binding ChIP-seq, we showed that AnkA binds broadly throughout all chromosomes in a reproducible pattern, especially at: i intergenic regions predicted to be matrix attachment regions (MARs; ii within predicted lamina-associated domains; and iii at promoters ≤3,000 bp upstream of transcriptional start sites. These findings provide genome-wide support for AnkA as a regulator of cis-gene transcription. Moreover, the dominant mark of AnkA in distal intergenic regions known to be AT-enriched, coupled with frequent enrichment in the nuclear lamina, provides strong support for its role as a MAR-binding protein and genome re-organizer. AnkA must be considered a prime candidate to promote neutrophil reprogramming and subsequent functional changes that belie improved microbial fitness and pathogenicity.
Murray, Gemma G R; Woolhouse, Mark E J; Tapio, Miika; Mbole-Kariuki, Mary N; Sonstegard, Tad S; Thumbi, Samuel M; Jennings, Amy E; van Wyk, Ilana Conradie; Chase-Topping, Margo; Kiara, Henry; Toye, Phil; Coetzer, Koos; deC Bronsvoort, Barend M; Hanotte, Olivier
Positive multi-locus heterozygosity-fitness correlations have been observed in a number of natural populations. They have been explained by the correlation between heterozygosity and inbreeding, and the negative effect of inbreeding on fitness (inbreeding depression). Exotic introgression in a locally adapted population has also been found to reduce fitness (outbreeding depression) through the breaking-up of co-adapted genes, or the introduction of non-locally adapted gene variants. In this study we examined the inter-relationships between genome-wide heterozygosity, introgression, and death or illness as a result of infectious disease in a sample of calves from an indigenous population of East African Shorthorn Zebu (crossbred Bos taurus x Bos indicus) in western Kenya. These calves were observed from birth to one year of age as part of the Infectious Disease in East African Livestock (IDEAL) project. Some of the calves were found to be genetic hybrids, resulting from the recent introgression of European cattle breed(s) into the indigenous population. European cattle are known to be less well adapted to the infectious diseases present in East Africa. If death and illness as a result of infectious disease have a genetic basis within the population, we would expect both a negative association of these outcomes with introgression and a positive association with heterozygosity. In this indigenous livestock population we observed negative associations between heterozygosity and both death and illness as a result of infectious disease and a positive association between European taurine introgression and episodes of clinical illness. We observe the effects of both inbreeding and outbreeding depression in the East African Shorthorn Zebu, and therefore find evidence of a genetic component to vulnerability to infectious disease. These results indicate that the significant burden of infectious disease in this population could, in principle, be reduced by altered breeding
Full Text Available Abstract Background Despite the recent success of genome-wide association studies in identifying novel loci contributing effects to complex human traits, such as type 2 diabetes and obesity, much of the genetic component of variation in these phenotypes remains unexplained. One way to improving power to detect further novel loci is through meta-analysis of studies from the same population, increasing the sample size over any individual study. Although statistical software analysis packages incorporate routines for meta-analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genome-wide association studies. Results We have developed flexible, open-source software for the meta-analysis of genome-wide association studies. The software incorporates a variety of error trapping facilities, and provides a range of meta-analysis summary statistics. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genome-wide meta-analysis results. Conclusions The GWAMA (Genome-Wide Association Meta-Analysis software has been developed to perform meta-analysis of summary statistics generated from genome-wide association studies of dichotomous phenotypes or quantitative traits. Software with source files, documentation and example data files are freely available online at http://www.well.ox.ac.uk/GWAMA.
Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.
Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A
It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.
Full Text Available Asperger Syndrome (AS is a neurodevelopmental condition characterized by impairments in social interaction and communication, alongside the presence of unusually repetitive, restricted interests and stereotyped behaviour. Individuals with AS have no delay in cognitive and language development. It is a subset of Autism Spectrum Conditions (ASC, which are highly heritable and has a population prevalence of approximately 1%. Few studies have investigated the genetic basis of AS. To address this gap in the literature, we performed a genome-wide pooled DNA association study to identify candidate loci in 612 individuals (294 cases and 318 controls of Caucasian ancestry, using the Affymetrix GeneChip Human Mapping version 6.0 array. We identified 11 SNPs that had a p-value below 1x10-5. These SNPs were independently genotyped in the same sample. Three of the SNPs (rs1268055, rs7785891 and rs2782448 were nominally significant, though none remained significant after Bonferroni correction. Two of our top three SNPs (rs7785891 and rs2782448 lie in loci previously implicated in ASC. However, investigation of the three SNPs in the ASC genome-wide association dataset from the Psychiatric Genomics Consortium indicated that these three SNPs were not significantly associated with ASC. The effect sizes of the variants were modest, indicating that our study was not sufficiently powered to identify causal variants with precision.
Lin, Tao; Gao, Lihui
population of mutants with different tags, after recovered from different tissues of infected mice and ticks, mutants from output pool and input pool are detected using high-throughput, semi-quantitative Luminex ® FLEXMAP™ or next-generation sequencing (Tn-seq) technologies. Thus far, we have created a high-density, sequence-defined transposon library of over 6600 STM mutants for the efficient genome-wide investigation of genes and gene products required for wild-type pathogenesis, host-pathogen interactions, in vitro growth, in vivo survival, physiology, morphology, chemotaxis, motility, structure, metabolism, gene regulation, plasmid maintenance and replication, etc. The insertion sites of 4480 transposon mutants have been determined. About 800 predicted protein-encoding genes in the genome were disrupted in the STM transposon library. The infectivity and some functions of 800 mutants in 500 genes have been determined. Analysis of these transposon mutants has yielded valuable information regarding the genes and gene products important in the pathogenesis and biology of B. burgdorferi and its tick vectors.
Nagano, Takashi; Lubling, Yaniv; Yaffe, Eitan; Wingett, Steven W; Dean, Wendy; Tanay, Amos; Fraser, Peter
Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C-ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.
Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20
Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A
Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.
Full Text Available The calcineurin B-like protein (CBL–CBL-interacting protein kinase (CIPK complex has been identified as a primary component in calcium sensors that perceives various stress signals. Turnip (Brassica rapa var. rapa has been widely cultivated in the Qinghai–Tibet Plateau for a century as a food crop of worldwide economic significance. These CBL–CIPK complexes have been demonstrated to play crucial roles in plant response to various environmental stresses. However, no report is available on the genome-wide characterization of these two gene families in turnip. In the present study, 19 and 51 members of the BrrCBL and BrrCIPK genes, respectively, are first identified in turnip and phylogenetically grouped into three and two distinct clusters, respectively. The expansion of these two gene families is mainly attributable to segmental duplication. Moreover, the differences in expression patterns in quantitative real-time PCR, as well as interaction profiles in the yeast two-hybrid assay, suggest the functional divergence of paralog genes during long-term evolution in turnip. Overexpressing and complement lines in Arabidopsis reveal that BrrCBL9.2 improves, but BrrCBL9.1 does not affect, salt tolerance in Arabidopsis. Thus, the expansion of the BrrCBL and BrrCIPK gene families enables the functional differentiation and evolution of some new gene functions of paralog genes. These paralog genes then play prominent roles in turnip's adaptation to the adverse environment of the Qinghai–Tibet Plateau. Overall, the study results contribute to our understanding of the functions of the CBL–CIPK complex and provide basis for selecting appropriate genes for the in-depth functional studies of BrrCBL–BrrCIPK in turnip.
Pritykin, Yuri; Ghersi, Dario; Singh, Mona
Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655
Genome-Wide Analyses of the NAC Transcription Factor Gene Family in Pepper (Capsicum annuum L.: Chromosome Location, Phylogeny, Structure, Expression Patterns, Cis-Elements in the Promoter, and Interaction Network
Full Text Available The NAM, ATAF1/2, and CUC2 (NAC transcription factors form a large plant-specific gene family, which is involved in the regulation of tissue development in response to biotic and abiotic stress. To date, there have been no comprehensive studies investigating chromosomal location, gene structure, gene phylogeny, conserved motifs, or gene expression of NAC in pepper (Capsicum annuum L.. The recent release of the complete genome sequence of pepper allowed us to perform a genome-wide investigation of Capsicum annuum L. NAC (CaNAC proteins. In the present study, a comprehensive analysis of the CaNAC gene family in pepper was performed, and a total of 104 CaNAC genes were identified. Genome mapping analysis revealed that CaNAC genes were enriched on four chromosomes (chromosomes 1, 2, 3, and 6. In addition, phylogenetic analysis of the NAC domains from pepper, potato, Arabidopsis, and rice showed that CaNAC genes could be clustered into three groups (I, II, and III. Group III, which contained 24 CaNAC genes, was exclusive to the Solanaceae plant family. Gene structure and protein motif analyses showed that these genes were relatively conserved within each subgroup. The number of introns in CaNAC genes varied from 0 to 8, with 83 (78.9% of CaNAC genes containing two or less introns. Promoter analysis confirmed that CaNAC genes are involved in pepper growth, development, and biotic or abiotic stress responses. Further, the expression of 22 selected CaNAC genes in response to seven different biotic and abiotic stresses [salt, heat shock, drought, Phytophthora capsici, abscisic acid, salicylic acid (SA, and methyl jasmonate (MeJA] was evaluated by quantitative RT-PCR to determine their stress-related expression patterns. Several putative stress-responsive CaNAC genes, including CaNAC72 and CaNAC27, which are orthologs of the known stress-responsive Arabidopsis gene ANAC055 and potato gene StNAC30, respectively, were highly regulated by treatment with
Jee, Sun Ha; Sull, Jae Woong; Lee, Jong-Eun; Shin, Chol; Park, Jongkeun; Kimm, Heejin; Cho, Eun-Young; Shin, Eun-Soon; Yun, Ji Eun; Park, Ji Wan; Kim, Sang Yeun; Lee, Sun Ju; Jee, Eun Jung; Baik, Inkyung; Kao, Linda; Yoon, Sungjoo Kim; Jang, Yangsoo; Beaty, Terri H.
Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP associated with mean log adiponectin was rs3865188 in CDH13 on chromosome 16 (p = 1.69 × 10−15 in the initial sample, p = 6.58 × 10−39 in the second genome-wide sample, and p = 2.12 × 10−32 in the replication sample). The meta-analysis p value for rs3865188 in all 6,305 individuals was 2.82 × 10−83. The association of rs3865188 with high-molecular-weight adiponectin (p = 7.36 × 10−58) was even stronger in the third sample. A reporter assay that evaluated the effects of a CDH13 promoter SNP in complete linkage disequilibrium with rs3865188 revealed that the major allele increased expression 2.2-fold. This study clearly shows that genetic variants in CDH13 influence adiponectin levels in Korean adults. PMID:20887962
Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu
Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.
to protein: through epigenetic modifications, transcription regulators or post-transcriptional controls. The following papers concern several layers of gene regulation with questions answered by different HTS approaches. Genome-wide screening of epigenetic changes by ChIP-seq allowed us to study both spatial...... and temporal alterations of histone modifications (Papers I and II). Coupling the data with machine learning approaches, we established a prediction framework to assess the most informative histone marks as well as their most influential nucleosome positions in predicting the promoter usages. (Papers I...... they regulated or if the sites had global elevated usage rates by multiple TFs. Using RNA-seq, 5’end-seq in combination with depletion of 5’exonuclease as well as nonsensemediated decay (NMD) factors, we systematically analyzed NMD substrates as well as their degradation intermediates in human cells (Paper V...
Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L
bone mineral density loci: WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5. Variants in the TOM1L2/SREBF1 locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that SREBF1 is expressed in murine and human osteoblasts, as well...
Medina-Gomez, Carolina; Kemp, John P; Dimou, Niki L
Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone...... as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass.Bone mineral density and lean skeletal mass are heritable traits. Here, Medina-Gomez and colleagues perform bivariate GWAS analyses of total...
Bulik-Sullivan, Brendan K.; Loh, Po-Ru; Finucane, Hilary K.
Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from...
Khan, Meraj A; Sengupta, Jayasree; Mittal, Suneeta; Ghosh, Debabrata
Abstract Background In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eu...
Beaumont, Robin N; Warrington, Nicole M; Cavadino, Alana; Tyrrell, Jessica; Nodzenski, Michael; Horikoshi, Momoko; Geller, Frank; Myhre, Ronny; Richmond, Rebecca C; Paternoster, Lavinia; Bradfield, Jonathan P; Kreiner-Møller, Eskil; Huikari, Ville; Metrustry, Sarah; Lunetta, Kathryn L; Painter, Jodie N; Hottenga, Jouke-Jan; Allard, Catherine; Barton, Sheila J; Espinosa, Ana; Marsh, Julie A; Potter, Catherine; Zhang, Ge; Ang, Wei; Berry, Diane J; Bouchard, Luigi; Das, Shikta; Hakonarson, Hakon; Heikkinen, Jani; Helgeland, Øyvind; Hocher, Berthold; Hofman, Albert; Inskip, Hazel M; Jones, Samuel E; Kogevinas, Manolis; Lind, Penelope A; Marullo, Letizia; Medland, Sarah E; Murray, Anna; Murray, Jeffrey C; Njølstad, Pål R; Nohr, Ellen A; Reichetzeder, Christoph; Ring, Susan M; Ruth, Katherine S; Santa-Marina, Loreto; Scholtens, Denise M; Sebert, Sylvain; Sengpiel, Verena; Tuke, Marcus A; Vaudel, Marc; Weedon, Michael N; Willemsen, Gonneke; Wood, Andrew R; Yaghootkar, Hanieh; Muglia, Louis J; Bartels, Meike; Relton, Caroline L; Pennell, Craig E; Chatzi, Leda; Estivill, Xavier; Holloway, John W; Boomsma, Dorret I; Montgomery, Grant W; Murabito, Joanne M; Spector, Tim D; Power, Christine; Järvelin, Marjo-Ritta; Bisgaard, Hans; Grant, Struan F A; Sørensen, Thorkild I A; Jaddoe, Vincent W; Jacobsson, Bo; Melbye, Mads; McCarthy, Mark I; Hattersley, Andrew T; Hayes, M Geoffrey; Frayling, Timothy M; Hivert, Marie-France; Felix, Janine F; Hyppönen, Elina; Lowe, William L; Evans, David M; Lawlor, Debbie A; Feenstra, Bjarke
Abstract Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10−8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights. PMID:29309628
Desta, Zeratsion Abera; Ortiz, Rodomiro
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.
Van Winkel, Ruud; Esquivel, Gabriel; Kenis, Gunter; Wichers, Marieke; Collip, Dina; Peerbooms, Odette; Rutten, Bart; Myin-Germeys, Inez; Van Os, Jim
The recent advent of genome-wide mass-marker technology has resulted in renewed optimism to unravel the genetic architecture of psychotic disorders. Genome-wide association studies have identified a number of common polymorphisms robustly associated with schizophrenia, in ZNF804A, transcription factor 4, major histocompatibility complex, and neurogranin. In addition, copy number variants (CNVs) in 1q21.1, 2p16.3, 15q11.2, 15q13.3, 16p11.2, and 22q11.2 were convincingly implicated in schizophrenia risk. Furthermore, these studies have suggested considerable genetic overlap with bipolar disorder (particularly for common polymorphisms) and neurodevelopmental disorders such as autism (particularly for CNVs). The influence of these risk variants on relevant intermediate phenotypes needs further study. In addition, there is a need for etiological models of psychosis integrating genetic risk with environmental factors associated with the disorder, focusing specifically on environmental impact on gene expression (epigenetics) and convergence of genes and environment on common biological pathways bringing about larger effects than those of genes or environment in isolation (gene-environment interaction). Collaborative efforts that bring together expertise in statistics, genetics, epidemiology, experimental psychiatry, brain imaging, and clinical psychiatry will be required to succeed in this challenging task. © 2010 Blackwell Publishing Ltd.
Lane, Jérôme; McLaren, Paul J.; Dorrell, Lucy; Shianna, Kevin V.; Stemke, Amanda; Pelak, Kimberly; Moore, Stephen; Oldenburg, Johannes; Alvarez-Roman, Maria Teresa; Angelillo-Scherrer, Anne; Boehlen, Francoise; Bolton-Maggs, Paula H.B.; Brand, Brigit; Brown, Deborah; Chiang, Elaine; Cid-Haro, Ana Rosa; Clotet, Bonaventura; Collins, Peter; Colombo, Sara; Dalmau, Judith; Fogarty, Patrick; Giangrande, Paul; Gringeri, Alessandro; Iyer, Rathi; Katsarou, Olga; Kempton, Christine; Kuriakose, Philip; Lin, Judith; Makris, Mike; Manco-Johnson, Marilyn; Tsakiris, Dimitrios A.; Martinez-Picado, Javier; Mauser-Bunschoten, Evelien; Neff, Anne; Oka, Shinichi; Oyesiku, Lara; Parra, Rafael; Peter-Salonen, Kristiina; Powell, Jerry; Recht, Michael; Shapiro, Amy; Stine, Kimo; Talks, Katherine; Telenti, Amalio; Wilde, Jonathan; Yee, Thynn Thynn; Wolinsky, Steven M.; Martinson, Jeremy; Hussain, Shehnaz K.; Bream, Jay H.; Jacobson, Lisa P.; Carrington, Mary; Goedert, James J.; Haynes, Barton F.; McMichael, Andrew J.; Goldstein, David B.; Fellay, Jacques
Human genetic variation contributes to differences in susceptibility to HIV-1 infection. To search for novel host resistance factors, we performed a genome-wide association study (GWAS) in hemophilia patients highly exposed to potentially contaminated factor VIII infusions. Individuals with hemophilia A and a documented history of factor VIII infusions before the introduction of viral inactivation procedures (1979–1984) were recruited from 36 hemophilia treatment centers (HTCs), and their genome-wide genetic variants were compared with those from matched HIV-infected individuals. Homozygous carriers of known CCR5 resistance mutations were excluded. Single nucleotide polymorphisms (SNPs) and inferred copy number variants (CNVs) were tested using logistic regression. In addition, we performed a pathway enrichment analysis, a heritability analysis, and a search for epistatic interactions with CCR5 Δ32 heterozygosity. A total of 560 HIV-uninfected cases were recruited: 36 (6.4%) were homozygous for CCR5 Δ32 or m303. After quality control and SNP imputation, we tested 1 081 435 SNPs and 3686 CNVs for association with HIV-1 serostatus in 431 cases and 765 HIV-infected controls. No SNP or CNV reached genome-wide significance. The additional analyses did not reveal any strong genetic effect. Highly exposed, yet uninfected hemophiliacs form an ideal study group to investigate host resistance factors. Using a genome-wide approach, we did not detect any significant associations between SNPs and HIV-1 susceptibility, indicating that common genetic variants of major effect are unlikely to explain the observed resistance phenotype in this population. PMID:23372042
Full Text Available BACKGROUND: The rs12807809 single-nucleotide polymorphism in NRGN is a genetic risk variant with genome-wide significance for schizophrenia. The frequency of the T allele of rs12807809 is higher in individuals with schizophrenia than in those without the disorder. Reduced immunoreactivity of NRGN, which is expressed exclusively in the brain, has been observed in Brodmann areas (BA 9 and 32 of the prefrontal cortex in postmortem brains from patients with schizophrenia compared with those in controls. METHODS: Genotype effects of rs12807809 were investigated on gray matter (GM and white matter (WM volumes using magnetic resonance imaging (MRI with a voxel-based morphometry (VBM technique in a sample of 99 Japanese patients with schizophrenia and 263 healthy controls. RESULTS: Although significant genotype-diagnosis interaction either on GM or WM volume was not observed, there was a trend of genotype-diagnosis interaction on GM volume in the left anterior cingulate cortex (ACC. Thus, the effects of NRGN genotype on GM volume of patients with schizophrenia and healthy controls were separately investigated. In patients with schizophrenia, carriers of the risk T allele had a smaller GM volume in the left ACC (BA32 than did carriers of the non-risk C allele. Significant genotype effect on other regions of the GM or WM was not observed for either the patients or controls. CONCLUSIONS: Our findings suggest that the genome-wide associated genetic risk variant in the NRGN gene may be related to a small GM volume in the ACC in the left hemisphere in patients with schizophrenia.
Debibakas, S; Rocher, S; Garsmeur, O; Toubi, L; Roques, D; D'Hont, A; Hoarau, J-Y; Daugrois, J H
Using GWAS approaches, we detected independent resistant markers in sugarcane towards a vectored virus disease. Based on comparative genomics, several candidate genes potentially involved in virus/aphid/plant interactions were pinpointed. Yellow leaf of sugarcane is an emerging viral disease whose causal agent is a Polerovirus, the Sugarcane yellow leaf virus (SCYLV) transmitted by aphids. To identify quantitative trait loci controlling resistance to yellow leaf which are of direct relevance for breeding, we undertook a genome-wide association study (GWAS) on a sugarcane cultivar panel (n = 189) representative of current breeding germplasm. This panel was fingerprinted with 3,949 polymorphic markers (DArT and AFLP). The panel was phenotyped for SCYLV infection in leaves and stalks in two trials for two crop cycles, under natural disease pressure prevalent in Guadeloupe. Mixed linear models including co-factors representing population structure fixed effects and pairwise kinship random effects provided an efficient control of the risk of inflated type-I error at a genome-wide level. Six independent markers were significantly detected in association with SCYLV resistance phenotype. These markers explained individually between 9 and 14 % of the disease variation of the cultivar panel. Their frequency in the panel was relatively low (8-20 %). Among them, two markers were detected repeatedly across the GWAS exercises based on the different disease resistance parameters. These two markers could be blasted on Sorghum bicolor genome and candidate genes potentially involved in plant-aphid or plant-virus interactions were localized in the vicinity of sorghum homologs of sugarcane markers. Our results illustrate the potential of GWAS approaches to prospect among sugarcane germplasm for accessions likely bearing resistance alleles of significant effect useful in breeding programs.
Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark
Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed
Levinson, Douglas F; Shi, Jianxin; Wang, Kai
The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs).......The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs)....
Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H
Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.......Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia....
SNPs from the African American breast cancer scan to COGs , a European collaborative study which is has designed a SNP array with that will be genotyped...Award Number: W81XWH-08-1-0383 TITLE: A Genome-wide Breast Cancer Scan in African Americans PRINCIPAL INVESTIGATOR: Christopher A...SUBTITLE A Genome-wide Breast Cancer Scan in African Americans 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0383 5c. PROGRAM
Tincher, Clayton; Long, Hongan; Behringer, Megan; Walker, Noah; Lynch, Michael
Mutations induced by pollutants may promote pathogen evolution, for example by accelerating mutations conferring antibiotic resistance. Generally, evaluating the genome-wide mutagenic effects of long-term sublethal pollutant exposure at single-nucleotide resolution is extremely difficult. To overcome this technical barrier, we use the mutation accumulation/whole-genome sequencing (MA/WGS) method as a mutagenicity test, to quantitatively evaluate genome-wide mutagenesis of Escherichia coli after long-term exposure to a wide gradient of the glyphosate-based herbicide (GBH) Roundup Concentrate Plus. The genome-wide mutation rate decreases as GBH concentration increases, suggesting that even long-term GBH exposure does not compromise the genome stability of bacteria. Copyright © 2017 Tincher et al.
Full Text Available Community samples suggest that approximately 1 in 20 children and adults exhibit clinically significant anger, hostility, and aggression. Individuals with dysregulated emotional control have a greater lifetime burden of psychiatric morbidity, severe impairment in role functioning, and premature mortality due to cardiovascular disease.With publically available data secured from dbGaP, we conducted a genome-wide association study of proneness to anger using the Spielberger State-Trait Anger Scale in the Atherosclerosis Risk in Communities (ARIC study (n = 8,747.Subjects were, on average, 54 (range 45-64 years old at baseline enrollment, 47% (n = 4,117 were male, and all were of European descent by self-report. The mean Angry Temperament and Angry Reaction scores were 5.8 ± 1.8 and 7.6 ± 2.2. We observed a nominally significant finding (p = 2.9E-08, λ = 1.027 - corrected pgc = 2.2E-07, λ = 1.0015 on chromosome 6q21 in the gene coding for the non-receptor protein-tyrosine kinase, Fyn.Fyn interacts with NDMA receptors and inositol-1,4,5-trisphosphate (IP3-gated channels to regulate calcium influx and intracellular release in the post-synaptic density. These results suggest that signaling pathways regulating intracellular calcium homeostasis, which are relevant to memory, learning, and neuronal survival, may in part underlie the expression of Angry Temperament.
Full Text Available The outcome of Genome-Wide Association Studies (GWAS has challenged the field of blood pressure (BP genetics as previous candidate genes have not been among the top loci in these scans. We used Affymetrix 500K genotyping data of KORA S3 cohort (n = 1,644; Southern-Germany to address (i SNP coverage in 160 BP candidate genes; (ii the evidence for associations with BP traits in genome-wide and replication data, and haplotype analysis. In total, 160 gene regions (genic region+/-10 kb covered 2,411 SNPs across 11.4 Mb. Marker densities in genes varied from 0 (n = 11 to 0.6 SNPs/kb. On average 52.5% of the HAPMAP SNPs per gene were captured. No evidence for association with BP was obtained for 1,449 tested SNPs. Considerable associations (P50% of HAPMAP SNPs were tagged. In general, genes with higher marker density (>0.2 SNPs/kb revealed a better chance to reach close to significance associations. Although, none of the detected P-values remained significant after Bonferroni correction (P<0.05/2319, P<2.15 x 10(-5, the strength of some detected associations was close to this level: rs10889553 (LEPR and systolic BP (SBP (P = 4.5 x 10(-5 as well as rs10954174 (LEP and diastolic BP (DBP (P = 5.20 x 10(-5. In total, 12 markers in 7 genes (ADRA2A, LEP, LEPR, PTGER3, SLC2A1, SLC4A2, SLC8A1 revealed considerable association (P<10(-3 either with SBP, DBP, and/or hypertension (HYP. None of these were confirmed in replication samples (KORA S4, HYPEST, BRIGHT. However, supportive evidence for the association of rs10889553 (LEPR and rs11195419 (ADRA2A with BP was obtained in meta-analysis across samples stratified either by body mass index, smoking or alcohol consumption. Haplotype analysis highlighted LEPR and PTGER3. In conclusion, the lack of associations in BP candidate genes may be attributed to inadequate marker coverage on the genome-wide arrays, small phenotypic effects of the loci and/or complex interaction with life-style and metabolic parameters.
Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø
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...
Frech, Christian; Chen, Nansheng
Correct classification of genes into gene families is important for understanding gene function and evolution. Although gene families of many species have been resolved both computationally and experimentally with high accuracy, gene family classification in most newly sequenced genomes has not been done with the same high standard. This project has been designed to develop a strategy to effectively and accurately classify gene families across genomes. We first examine and compare the performance of computer programs developed for automated gene family classification. We demonstrate that some programs, including the hierarchical average-linkage clustering algorithm MC-UPGMA and the popular Markov clustering algorithm TRIBE-MCL, can reconstruct manual curation of gene families accurately. However, their performance is highly sensitive to parameter setting, i.e. different gene families require different program parameters for correct resolution. To circumvent the problem of parameterization, we have developed a comparative strategy for gene family classification. This strategy takes advantage of existing curated gene families of reference species to find suitable parameters for classifying genes in related genomes. To demonstrate the effectiveness of this novel strategy, we use TRIBE-MCL to classify chemosensory and ABC transporter gene families in C. elegans and its four sister species. We conclude that fully automated programs can establish biologically accurate gene families if parameterized accordingly. Comparative gene family classification finds optimal parameters automatically, thus allowing rapid insights into gene families of newly sequenced species. PMID:20976221
Keurentjes, Joost J.B.; Fu, Jingyuan; Terpstra, Inez R.; Garcia, Juan M.; Ackerveken, Guido van den; Snoek, L. Basten; Peeters, Anton J.M.; Vreugdenhil, Dick; Koornneef, Maarten; Jansen, Ritsert C.
Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genome-wide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation
A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...
Karnes, Jason H; Cronin, Robert M; Rollin, Jerome
Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect of heparin treatment resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. No genome-wide evaluations have been performed to identify potential genetic influences on HIT. ...
Full Text Available Plant organ development and polarity establishment is mediated by the action of several transcription factors. Among these, the KANADI (KAN subclade of the GARP protein family plays important roles in polarity-associated processes during embryo, shoot and root patterning. In this study, we have identified a set of potential direct target genes of KAN1 through a combination of chromatin immunoprecipitation/DNA sequencing (ChIP-Seq and genome-wide transcriptional profiling using tiling arrays. Target genes are over-represented for genes involved in the regulation of organ development as well as in the response to auxin. KAN1 affects directly the expression of several genes previously shown to be important in the establishment of polarity during lateral organ and vascular tissue development. We also show that KAN1 controls through its target genes auxin effects on organ development at different levels: transport and its regulation, and signaling. In addition, KAN1 regulates genes involved in the response to abscisic acid, jasmonic acid, brassinosteroids, ethylene, cytokinins and gibberellins. The role of KAN1 in organ polarity is antagonized by HD-ZIPIII transcription factors, including REVOLUTA (REV. A comparison of their target genes reveals that the REV/KAN1 module acts in organ patterning through opposite regulation of shared targets. Evidence of mutual repression between closely related family members is also shown.
Emily R Davenport
Full Text Available The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both. These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%. For example, we identified an association between a taxon known to affect obesity (genus Akkermansia and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10-7. Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.
Jee, Sun Ha; Sull, Jae Woong; Lee, Jong-Eun; Shin, Chol; Park, Jongkeun; Kimm, Heejin; Cho, Eun-Young; Shin, Eun-Soon; Yun, Ji Eun; Park, Ji Wan; Kim, Sang Yeun; Lee, Sun Ju; Jee, Eun Jung; Baik, Inkyung; Kao, Linda
Adiponectin is associated with obesity and insulin resistance. To date, there has been no genome-wide association study (GWAS) of adiponectin levels in Asians. Here we present a GWAS of a cohort of Korean volunteers. A total of 4,001 subjects were genotyped by using a genome-wide marker panel in a two-stage design (979 subjects initially and 3,022 in a second stage). Another 2,304 subjects were used for follow-up replication studies with selected markers. In the discovery phase, the top SNP a...
Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Adan, R A H; Alfredsson, L; Ando, T; Andreassen, O A; Aschauer, H; Baker, J H; Barrett, J C; Bencko, V; Bergen, A W; Berrettini, W H; Birgegard, A; Boni, C; Boraska Perica, V; Brandt, H; Breen, G; Bulik, C M; Carlberg, L; Cassina, M; Cichon, S; Clementi, M; Cohen-Woods, S; Coleman, J; Cone, R D; Courtet, P; Crawford, S; Crow, S; Crowley, J; Danner, U N; Davis, O S P; de Zwaan, M; Dedoussis, G; Degortes, D; DeSocio, J E; Dick, D M; Dikeos, D; Dina, C; Ding, B; Dmitrzak-Weglarz, M; Docampo, E; Duncan, L; Egberts, K; Ehrlich, S; Escaramís, G; Esko, T; Espeseth, T; Estivill, X; Favaro, A; Fernández-Aranda, F; Fichter, M M; Finan, C; Fischer, K; Floyd, J A B; Foretova, L; Forzan, M; Franklin, C S; Gallinger, S; Gambaro, G; Gaspar, H A; Giegling, I; Gonidakis, F; Gorwood, P; Gratacos, M; Guillaume, S; Guo, Y; Hakonarson, H; Halmi, K A; Hatzikotoulas, K; Hauser, J; Hebebrand, J; Helder, S; Herms, S; Herpertz-Dahlmann, B; Herzog, W; Hilliard, C E; Hinney, A; Hübel, C; Huckins, L M; Hudson, J I; Huemer, J; Inoko, H; Janout, V; Jiménez-Murcia, S; Johnson, C; Julià, A; Juréus, A; Kalsi, G; Kaminska, D; Kaplan, A S; Kaprio, J; Karhunen, L; Karwautz, A; Kas, M J H; Kaye, W; Kennedy, J L; Keski-Rahkonen, A; Kiezebrink, K; Klareskog, L; Klump, K L; Knudsen, G P S; Koeleman, B P C; Koubek, D; La Via, M C; Landén, M; Le Hellard, S; Levitan, R D; Li, D; Lichtenstein, P; Lilenfeld, L; Lissowska, J; Lundervold, A; Magistretti, P; Maj, M; Mannik, K; Marsal, S; Martin, N; Mattingsdal, M; McDevitt, S; McGuffin, P; Merl, E; Metspalu, A; Meulenbelt, I; Micali, N; Mitchell, J; Mitchell, K; Monteleone, P; Monteleone, A M; Mortensen, P; Munn-Chernoff, M A; Navratilova, M; Nilsson, I; Norring, C; Ntalla, I; Ophoff, R A; O'Toole, J K; Palotie, A; Pante, J; Papezova, H; Pinto, D; Rabionet, R; Raevuori, A; Rajewski, A; Ramoz, N; Rayner, N W; Reichborn-Kjennerud, T; Ripatti, S; Roberts, M; Rotondo, A; Rujescu, D; Rybakowski, F; Santonastaso, P; Scherag, A; Scherer, S W; Schmidt, U; Schork, N J; Schosser, A; Slachtova, L; Sladek, R; Slagboom, P E; Slof-Op 't Landt, M C T; Slopien, A; Soranzo, N; Southam, L; Steen, V M; Strengman, E; Strober, M; Sullivan, P F; Szatkiewicz, J P; Szeszenia-Dabrowska, N; Tachmazidou, I; Tenconi, E; Thornton, L M; Tortorella, A; Tozzi, F; Treasure, J; Tsitsika, A; Tziouvas, K; van Elburg, A A; van Furth, E F; Wagner, G; Walton, E; Watson, H; Wichmann, H-E; Widen, E; Woodside, D B; Yanovski, J; Yao, S; Yilmaz, Z; Zeggini, E; Zerwas, S; Zipfel, S; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E
Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10−6), and rs7700147, an intergenic variant (P=2.93 × 10−5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes. PMID:29155802
Background The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post-translational modifications and to regulate viral cccDNA transcription and cellular gene expression. Aiming to identify genes and non-coding RNAs (ncRNAs) directly targeted by HBx, we performed a chromatin immunoprecipitation sequencing (ChIP-Seq) to analyse HBV recruitment on host cell chromatin in cells replicating HBV. Results ChIP-Seq high throughput sequencing of HBx-bound fragments was used to obtain a high-resolution, unbiased, mapping of HBx binding sites across the genome in HBV replicating cells. Protein-coding genes and ncRNAs involved in cell metabolism, chromatin dynamics and cancer were enriched among HBx targets together with genes/ncRNAs known to modulate HBV replication. The direct transcriptional activation of genes/miRNAs that potentiate endocytosis (Ras-related in brain (RAB) GTPase family) and autophagy (autophagy related (ATG) genes, beclin-1, miR-33a) and the transcriptional repression of microRNAs (miR-138, miR-224, miR-576, miR-596) that directly target the HBV pgRNA and would inhibit HBV replication, contribute to HBx-mediated increase of HBV replication. Conclusions Our ChIP-Seq analysis of HBx genome wide chromatin recruitment defined the repertoire of genes and ncRNAs directly targeted by HBx and led to the identification of new mechanisms by which HBx positively regulates cccDNA transcription and HBV replication.
Zhu, Yunye; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Yue, Junyang; Wang, Wenjie; Liu, Yongsheng
One hundred DDB1 (damaged DNA binding protein-1)-binding WD40-repeat domain (DWD) family genes were identified in the S. lycopersicum genome. The DWD genes encode proteins presumably functioning as the substrate recognition subunits of the cullin4-ring ubiquitin E3 ligase complex. These findings provide candidate genes and a research platform for further gene functionality and molecular breeding study. A subclass of DDB1 (damaged DNA binding protein-1)-binding WD40-repeat domain (DWD) family proteins has been demonstrated to function as the substrate recognition subunits of the cullin4-ring ubiquitin E3 ligase complex. However, little information is available about the cognate subfamily genes in tomato (S. lycopersicum). In this study, based on the recently released tomato genome sequences, 100 tomato genes encoding DWD proteins that potentially interact with DDB1 were identified and characterized, including analyses of the detailed annotations, chromosome locations and compositions of conserved amino acid domains. In addition, a phylogenetic tree, which comprises of three main groups, of the subfamily genes was constructed. The physical interaction between tomato DDB1 and 14 representative DWD proteins was determined by yeast two-hybrid and co-immunoprecipitation assays. The subcellular localization of these 14 representative DWD proteins was determined. Six of them were localized in both nucleus and cytoplasm, seven proteins exclusively in cytoplasm, and one protein either in nucleus and cytoplasm, or exclusively in cytoplasm. Comparative genomic analysis demonstrated that the expansion of these subfamily members in tomato predominantly resulted from two whole-genome triplication events in the evolution history.
Apr 1, 2010 ... Genome-wide association studies (GWAS) examine the entire human genome with the goal of identifying genetic variants. (usually single nucleotide polymorphisms (SNPs)) that are associated with phenotypic traits such as disease status and drug response. The discordance of significantly associated ...
Ripke, S.; Sanders, A. R.; Kendler, K. S.; Levinson, D. F.; Sklar, P.; Holmans, P. A.; Lin, D. Y.; Duan, J.; Ophoff, R. A.; Andreassen, O. A.; Scolnick, E.; Cichon, S.; St Clair, D.; Corvin, A.; Gurling, H.; Werge, T.; Rujescu, D.; Blackwood, D. H.; Pato, C. N.; Malhotra, A. K.; Purcell, S.; Dudbridge, F.; Neale, B. M.; Rossin, L.; Visscher, P. M.; Posthuma, D.; Ruderfer, D. M.; Fanous, A.; Stefansson, H.; Steinberg, S.; Mowry, B. J.; Golimbet, V.; de Hert, M.; Jonsson, E. G.; Bitter, I.; Pietilainen, O. P.; Collier, D. A.; Tosato, S.; Agartz, I.; Albus, M.; Alexander, M.; Amdur, R. L.; Amin, F.; Bass, N.; Bergen, S. E.; Black, D. W.; Borglum, A. D.; Brown, M. A.; Bruggeman, R.; Buccola, N. G.; Byerley, W. F.; Cahn, W.; Cantor, R. M.; Carr, V. J.; Catts, S. V.; Choudhury, K.; Cloninger, C. R.; Cormican, P.; Craddock, N.; Danoy, P. A.; Datta, S.; de Haan, L.; Demontis, D.; Dikeos, D.; Djurovic, S.; Donnely, P.; Donohoe, G.; Duong, L.; Dwyer, S.; Fink-Jensen, A.; Freedman, R.; Freimer, N. B.; Friedl, M.; Georgieva, L.; Giegling, I.; Gill, M.; Glenthoj, B.; Godard, S.; Hamshere, M.; Hansen, M.; Hartmann, A. M.; Henskens, F. A.; Hougaard, D. M.; Hultman, C. M.; Ingason, A.; Jablensky, A. V.; Jakobsen, K. D.; Jay, M.; Jurgens, G.; Kahn, R. S.; Keller, M. C.; Kenis, G.; Kenny, E.; Kim, Y.; Kirov, G. K.; Konnerth, H.; Konte, B.; Krabbendam, L.; Krasucki, R.; Lasseter, V. K.; Laurent, C.; Lawrence, J.; Lencz, T.; Lerer, F. B.; Liang, K. Y.; Lichtenstein, P.; Lieberman, J. A.; Linszen, D. H.; Lonnqvist, J.; Loughland, C. M.; Maclean, A. W.; Maher, B. S.; Maier, W.; Mallet, J.; Malloy, P.; Mattheisen, M.; Mattingsdal, M.; McGhee, K. A.; McGrath, J. J.; McIntosh, A.; McLean, D. E.; McQuillin, A.; Melle, I.; Michie, P. T.; Milanova, V.; Morris, D. W.; Mors, O.; Mortensen, P. B.; Moskvina, V.; Muglia, P.; Myin-Germeys, I.; Nertney, D. A.; Nestadt, G.; Nielsen, J.; Nikolov, I.; Nordentoft, M.; Norton, N.; Nothen, M. M.; O'Dushlaine, C. T.; Olincy, A.; Olsen, L.; O'Neill, F. A.; Orntoft, T. F.; Owen, M. J.; Pantelis, C.; Papadimitriou, G.; Pato, M. T.; Peltonen, L.; Petursson, H.; Pickard, B.; Pimm, J.; Pulver, A. E.; Puri, V.; Quested, D.; Quinn, E. M.; Rasmussen, H. B.; Rethelyi, J. M.; Ribble, R.; Rietschel, M.; Riley, B. P.; Ruggeri, M.; Schall, U.; Schulze, T. G.; Schwab, S. G.; Scott, R. J.; Shi, J.; Sigurdsson, E.; Silvermann, J. M.; Spencer, C. C.; Stefansson, K.; Strange, A.; Strengman, E.; Stroup, T. S.; Suvisaari, J.; Terenius, L.; Thirumalai, S.; Thygesen, J. H.; Timm, S.; Toncheva, D.; van den Oord, E.; van Os, J.; van Winkel, R.; Veldink, J.; Walsh, D.; Wang, A. G.; Wiersma, D.; Wildenauer, D. B.; Williams, H. J.; Williams, N. M.; Wormley, B.; Zammit, S.; Sullivan, P. F.; O'Donovan, M. C.; Daly, M. J.; Gejman, P. V.
We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded
Beekman, Marian; Blanché, Hélène; Perola, Markus
Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian...
Scharf, J. M.; Yu, D.; Mathews, C. A.; Neale, B. M.; Stewart, S. E.; Fagerness, J. A.; Evans, P.; Gamazon, E.; Edlund, C. K.; Service, S. K.; Tikhomirov, A.; Osiecki, L.; Illmann, C.; Pluzhnikov, A.; Konkashbaev, A.; Davis, L. K.; Han, B.; Crane, J.; Moorjani, P.; Crenshaw, A. T.; Parkin, M. A.; Reus, V. I.; Lowe, T. L.; Rangel-Lugo, M.; Chouinard, S.; Dion, Y.; Girard, S.; Cath, D. C.; Smit, J. H.; King, R. A.; Fernandez, T. V.; Leckman, J. F.; Kidd, K. K.; Kidd, J. R.; Pakstis, A. J.; State, M. W.; Herrera, L. D.; Romero, R.; Fournier, E.; Sandor, P.; Barr, C. L.; Phan, N.; Gross-Tsur, V.; Benarroch, F.; Pollak, Y.; Budman, C. L.; Bruun, R. D.; Erenberg, G.; Naarden, A. L.; Hoekstra, P. J.
Tourette's syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association
We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10(-11)) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10(-9)), ANK3 (rs10994359, P = 2.5 × 10(-8)) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10(-9)).
Oskari Kilpeläinen, Tuomas; Ingelsson, Erik
Adiposity is strongly heritable and one of the leading risk factors for type 2 diabetes, cardiovascular disease, cancer, and premature death. In the past 8 years, genome-wide association studies (GWAS) have greatly increased our understanding of the genes and biological pathways that regulate...
Nilsson, Emil K.; Bostr?m, Adrian E.; Mwinyi, Jessica; Schi?th, Helgi B.
Abstract Despite an established link between sleep deprivation and epigenetic processes in humans, it remains unclear to what extent sleep deprivation modulates DNA methylation. We performed a within-subject randomized blinded study with 16 healthy subjects to examine the effect of one night of total sleep deprivation (TSD) on the genome-wide methylation profile in blood compared with that in normal sleep. Genome-wide differences in methylation between both conditions were assessed by applyin...
Carlberg, Carsten; Molnár, Ferdinand
Vitamin D3 is one of the few natural compounds that has, via its metabolite 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) and the transcription factor vitamin D receptor (VDR), a direct effect on gene regulation. For efficiently applying the therapeutic and disease-preventing potential of 1,25(OH)2D3 and its synthetic analogs, the key steps in vitamin D signaling need to be understood. These are the different types of molecular interactions with the VDR, such as (i) the complex formation of VDR with genomic DNA, (ii) the interaction of VDR with its partner transcription factors, (iii) the binding of 1,25(OH)2D3 or its synthetic analogs within the ligand-binding pocket of the VDR, and (iv) the resulting conformational change on the surface of the VDR leading to a change of the protein-protein interaction profile of the receptor with other proteins. This review will present the latest genome-wide insight into vitamin D signaling, and will discuss its therapeutic implications.
van Manen Daniëlle
Full Text Available Abstract Susceptibility to HIV-1 and the clinical course after infection show a substantial heterogeneity between individuals. Part of this variability can be attributed to host genetic variation. Initial candidate gene studies have revealed interesting host factors that influence HIV infection, replication and pathogenesis. Recently, genome-wide association studies (GWAS were utilized for unbiased searches at a genome-wide level to discover novel genetic factors and pathways involved in HIV-1 infection. This review gives an overview of findings from the GWAS performed on HIV infection, within different cohorts, with variable patient and phenotype selection. Furthermore, novel techniques and strategies in research that might contribute to the complete understanding of virus-host interactions and its role on the pathogenesis of HIV infection are discussed.
Li, Cheng-Wei; Chen, Bor-Sen
Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.
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
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.
SUMMARY The HIV genome encodes a small number of viral proteins (i.e., 16), invariably establishing cooperative associations among HIV proteins and between HIV and host proteins, to invade host cells and hijack their internal machineries. As a known example, the HIV envelope glycoprotein GP120 is closely associated with GP41 for viral entry. From a genome-wide perspective, a hypothesis can be worked out to determine whether 16 HIV proteins could develop 120 possible pairwise associations either by physical interactions or by functional associations mediated via HIV or host molecules. Here, we present the first systematic review of experimental evidence on HIV genome-wide protein associations using a large body of publications accumulated over the past 3 decades. Of 120 possible pairwise associations between 16 HIV proteins, at least 34 physical interactions and 17 functional associations have been identified. To achieve efficient viral replication and infection, HIV protein associations play essential roles (e.g., cleavage, inhibition, and activation) during the HIV life cycle. In either a dispensable or an indispensable manner, each HIV protein collaborates with another viral protein to accomplish specific activities that precisely take place at the proper stages of the HIV life cycle. In addition, HIV genome-wide protein associations have an impact on anti-HIV inhibitors due to the extensive cross talk between drug-inhibited proteins and other HIV proteins. Overall, this study presents for the first time a comprehensive overview of HIV genome-wide protein associations, highlighting meticulous collaborations between all viral proteins during the HIV life cycle. PMID:27357278
Oskari Kilpeläinen, Tuomas
Genome-wide association studies (GWASs) have revolutionized the search for genetic variants regulating resting heart rate. In the last 10 years, GWASs have led to the identification of at least 21 novel heart rate loci. These discoveries have provided valuable insights into the mechanisms...... and pathways that regulate heart rate and link heart rate to cardiovascular morbidity and mortality. GWASs capture majority of genetic variation in a population sample by utilizing high-throughput genotyping chips measuring genotypes for up to several millions of SNPs across the genome in thousands...... of individuals. This allows the identification of the strongest heart rate associated signals at genome-wide level. While GWASs provide robust statistical evidence of the association of a given genetic locus with heart rate, they are only the starting point for detailed follow-up studies to locate the causal...
Lang, M; Leménager, T; Streit, F; Fauth-Bühler, M; Frank, J; Juraeva, D; Witt, S H; Degenhardt, F; Hofmann, A; Heilmann-Heimbach, S; Kiefer, F; Brors, B; Grabe, H-J; John, U; Bischof, A; Bischof, G; Völker, U; Homuth, G; Beutel, M; Lind, P A; Medland, S E; Slutske, W S; Martin, N G; Völzke, H; Nöthen, M M; Meyer, C; Rumpf, H-J; Wurst, F M; Rietschel, M; Mann, K F
Pathological gambling is a behavioural addiction with negative economic, social, and psychological consequences. Identification of contributing genes and pathways may improve understanding of aetiology and facilitate therapy and prevention. Here, we report the first genome-wide association study of pathological gambling. Our aims were to identify pathways involved in pathological gambling, and examine whether there is a genetic overlap between pathological gambling and alcohol dependence. Four hundred and forty-five individuals with a diagnosis of pathological gambling according to the Diagnostic and Statistical Manual of Mental Disorders were recruited in Germany, and 986 controls were drawn from a German general population sample. A genome-wide association study of pathological gambling comprising single marker, gene-based, and pathway analyses, was performed. Polygenic risk scores were generated using data from a German genome-wide association study of alcohol dependence. No genome-wide significant association with pathological gambling was found for single markers or genes. Pathways for Huntington's disease (P-value=6.63×10(-3)); 5'-adenosine monophosphate-activated protein kinase signalling (P-value=9.57×10(-3)); and apoptosis (P-value=1.75×10(-2)) were significant. Polygenic risk score analysis of the alcohol dependence dataset yielded a one-sided nominal significant P-value in subjects with pathological gambling, irrespective of comorbid alcohol dependence status. The present results accord with previous quantitative formal genetic studies which showed genetic overlap between non-substance- and substance-related addictions. Furthermore, pathway analysis suggests shared pathology between Huntington's disease and pathological gambling. This finding is consistent with previous imaging studies. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Vilella Albert J
Full Text Available Abstract Background DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis. Results We have developed methods for the analysis of DNA sequence polymorphisms at the genome-wide scale. These methods, which have been tested on a coalescent-simulated and actual data files from mouse and human, have been implemented in the VariScan software package version 2.0. Additionally, we have also incorporated a graphical-user interface. The main features of this software are: i exhaustive population-genetic analyses including those based on the coalescent theory; ii analysis adapted to the shallow data generated by the high-throughput genome projects; iii use of genome annotations to conduct a comprehensive analyses separately for different functional regions; iv identification of relevant genomic regions by the sliding-window and wavelet-multiresolution approaches; v visualization of the results integrated with current genome annotations in commonly available genome browsers. Conclusion VariScan is a powerful and flexible suite of software for the analysis of DNA polymorphisms. The current version implements new algorithms, methods, and capabilities, providing an important tool for an exhaustive exploratory analysis of genome-wide DNA polymorphism data.
Power, Robert A; Cohen-Woods, Sarah; Ng, Mandy Y; Butler, Amy W; Craddock, Nick; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Zobel, Astrid; Mors, Ole; Placentino, Anna; Rietschel, Marcella; Aitchison, Katherine J; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Farmer, Anne E; McGuffin, Peter; Lewis, Cathryn M; Uher, Rudolf
Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between "true" cases and a "normal" response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case-control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis. Copyright © 2013 Wiley Periodicals, Inc.
Vrieze, Scott I; Iacono, William G; McGue, Matt
This article serves to outline a research paradigm to investigate main effects and interactions of genes, environment, and development on behavior and psychiatric illness. We provide a historical context for candidate gene studies and genome-wide association studies, including benefits, limitations, and expected payoffs. Using substance use and abuse as our driving example, we then turn to the importance of etiological psychological theory in guiding genetic, environmental, and developmental research, as well as the utility of refined phenotypic measures, such as endophenotypes, in the pursuit of etiological understanding and focused tests of genetic and environmental associations. Phenotypic measurement has received considerable attention in the history of psychology and is informed by psychometrics, whereas the environment remains relatively poorly measured and is often confounded with genetic effects (i.e., gene-environment correlation). Genetically informed designs, which are no longer limited to twin and adoption studies thanks to ever-cheaper genotyping, are required to understand environmental influences. Finally, we outline the vast amount of individual difference in structural genomic variation, most of which remains to be leveraged in genetic association tests. Although the genetic data can be massive and burdensome (tens of millions of variants per person), we argue that improved understanding of genomic structure and function will provide investigators with new tools to test specific a priori hypotheses derived from etiological psychological theory, much like current candidate gene research but with less confusion and more payoff than candidate gene research has to date.
Adam, Shelin; Friedman, Jan M
Genome-wide (exome or whole genome) sequencing with appropriate genetic counseling should be considered for any patient with a suspected Mendelian disease that has not been identified by conventional testing. Clinical genome-wide sequencing provides a powerful and effective means of identifying specific genetic causes of serious disease and improving clinical care. Copyright © 2017 Elsevier Inc. All rights reserved.
Clive J Hoggart
Full Text Available Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants, which is a plausible scenario for many complex diseases. We show that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods. We used a Bayesian-inspired penalised maximum likelihood approach in which every SNP can be considered for additive, dominant, and recessive contributions to disease risk. Posterior mode estimates were obtained for regression coefficients that were each assigned a prior with a sharp mode at zero. A non-zero coefficient estimate was interpreted as corresponding to a significant SNP. We investigated two prior distributions and show that the normal-exponential-gamma prior leads to improved SNP selection in comparison with single-SNP tests. We also derived an explicit approximation for type-I error that avoids the need to use permutation procedures. As well as genome-wide analyses, our method is well-suited to fine mapping with very dense SNP sets obtained from re-sequencing and/or imputation. It can accommodate quantitative as well as case-control phenotypes, covariate adjustment, and can be extended to search for interactions. Here, we demonstrate the power and empirical type-I error of our approach using simulated case-control data sets of up to 500 K SNPs, a real genome-wide data set of 300 K SNPs, and a sequence-based dataset, each of which can be analysed in a few hours on a desktop workstation.
Postmus, Iris; Warren, Helen R; Trompet, Stella
BACKGROUND: In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation. METHODS AND RESULTS: We performed...... a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p
Breithaupt, Lauren; Hubel, Christopher; Bulik, Cynthia M
Heterogeneity, frequent diagnostic fluctuation across presentations, and global concerns with the absence of effective treatments all encourage science that moves the field toward individualized or precision medicine in eating disorders. We review recent advances in psychiatric genetics focusing on genome-wide association studies (GWAS) in eating disorders and enumerate the prospects and challenges of a genomics-driven approach towards personalized intervention. Copyright© Bentham Science Publishers; For any queries, please email at firstname.lastname@example.org.
Full Text Available The aim of this study was to identify the evidence of recent selection based on estimation of the integrated Haplotype Score (iHS, population differentiation index (FST and characterize affected regions near QTL associated with traits under strong selection in Pinzgau cattle. In total 21 Austrian and 19 Slovak purebreed bulls genotyped with Illumina bovineHD and bovineSNP50 BeadChip were used to identify genomic regions under selection. Only autosomal loci with call rate higher than 90%, minor allele frequency higher than 0.01 and Hardy-Weinberg equlibrium limit of 0.001 were included in the subsequent analyses of selection sweeps presence. The final dataset was consisted from 30538 SNPs with 81.86 kb average adjacent SNPs spacing. The iHS score were averaged into non-overlapping 500 kb segments across the genome. The FST values were also plotted against genome position based on sliding windows approach and averaged over 8 consecutive SNPs. Based on integrated Haplotype Score evaluation only 7 regions with iHS score higher than 1.7 was found. The average iHS score observed for each adjacent syntenic regions indicated slight effect of recent selection in analysed group of Pinzgau bulls. The level of genetic differentiation between Austrian and Slovak bulls estimated based on FST index was low. Only 24% of FST values calculated for each SNP was greather than 0.01. By using sliding windows approach was found that 5% of analysed windows had higher value than 0.01. Our results indicated use of similar selection scheme in breeding programs of Slovak and Austrian Pinzgau bulls. The evidence for genome-wide association between signatures of selection and regions affecting complex traits such as milk production was insignificant, because the loci in segments identified as affected by selection were very distant from each other. Identification of genomic regions that may be under pressure of selection for phenotypic traits to better understanding of the
Yuan, Xiguo; Yu, Guoqiang; Hou, Xuchu; Shih, Ie-Ming; Clarke, Robert; Zhang, Junying; Hoffman, Eric P; Wang, Roger R; Zhang, Zhen; Wang, Yue
Somatic Copy Number Alterations (CNAs) in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC), a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1) exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2) performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3) iteratively detecting Significant Copy Number Aberrations (SCAs) and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS) on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma). When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC) or tumor suppressor genes (e.g., CDKN2A/B). Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes. Open-source and platform-independent SAIC software is
Full Text Available Abstract Background Somatic Copy Number Alterations (CNAs in human genomes are present in almost all human cancers. Systematic efforts to characterize such structural variants must effectively distinguish significant consensus events from random background aberrations. Here we introduce Significant Aberration in Cancer (SAIC, a new method for characterizing and assessing the statistical significance of recurrent CNA units. Three main features of SAIC include: (1 exploiting the intrinsic correlation among consecutive probes to assign a score to each CNA unit instead of single probes; (2 performing permutations on CNA units that preserve correlations inherent in the copy number data; and (3 iteratively detecting Significant Copy Number Aberrations (SCAs and estimating an unbiased null distribution by applying an SCA-exclusive permutation scheme. Results We test and compare the performance of SAIC against four peer methods (GISTIC, STAC, KC-SMART, CMDS on a large number of simulation datasets. Experimental results show that SAIC outperforms peer methods in terms of larger area under the Receiver Operating Characteristics curve and increased detection power. We then apply SAIC to analyze structural genomic aberrations acquired in four real cancer genome-wide copy number data sets (ovarian cancer, metastatic prostate cancer, lung adenocarcinoma, glioblastoma. When compared with previously reported results, SAIC successfully identifies most SCAs known to be of biological significance and associated with oncogenes (e.g., KRAS, CCNE1, and MYC or tumor suppressor genes (e.g., CDKN2A/B. Furthermore, SAIC identifies a number of novel SCAs in these copy number data that encompass tumor related genes and may warrant further studies. Conclusions Supported by a well-grounded theoretical framework, SAIC has been developed and used to identify SCAs in various cancer copy number data sets, providing useful information to study the landscape of cancer genomes
Background Classical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction. Results Here, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists. Conclusions These results appear to offer new insights into the genetic factors underlying drug addiction. PMID:21999673
Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike
The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300
Full Text Available The mechanistic and therapeutic differences in the cellular response to DNA-damaging compounds are not completely understood, despite intense study. To expand our knowledge of DNA damage, we assayed the effects of 12 closely related DNA-damaging agents on the complete pool of ~4,700 barcoded homozygous deletion strains of Saccharomyces cerevisiae. In our protocol, deletion strains are pooled together and grown competitively in the presence of compound. Relative strain sensitivity is determined by hybridization of PCR-amplified barcodes to an oligonucleotide array carrying the barcode complements. These screens identified genes in well-characterized DNA-damage-response pathways as well as genes whose role in the DNA-damage response had not been previously established. High-throughput individual growth analysis was used to independently confirm microarray results. Each compound produced a unique genome-wide profile. Analysis of these data allowed us to determine the relative importance of DNA-repair modules for resistance to each of the 12 profiled compounds. Clustering the data for 12 distinct compounds uncovered both known and novel functional interactions that comprise the DNA-damage response and allowed us to define the genetic determinants required for repair of interstrand cross-links. Further genetic analysis allowed determination of epistasis for one of these functional groups.
Full Text Available Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an in silico pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.
Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin
The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.
Morán, Tomás; Fontdevila, Antonio
To date, different studies about the genetic basis of hybrid male sterility (HMS), a postzygotic reproductive barrier thoroughly investigated using Drosophila species, have demonstrated that no single major gene can produce hybrid sterility without the cooperation of several genetic factors. Early work using hybrids between Drosophila koepferae (Dk) and Drosophila buzzatii (Db) was consistent with the idea that HMS requires the cooperation of several genetic factors, supporting a polygenic threshold (PT) model. Here we present a genome-wide mapping strategy to test the PT model, analyzing serially backcrossed fertile and sterile males in which the Dk genome was introgressed into the Db background. We identified 32 Dk-specific markers significantly associated with hybrid sterility. Our results demonstrate 1) a strong correlation between the number of segregated sterility markers and males' degree of sterility, 2) the exchangeability among markers, 3) their tendency to cluster into low-recombining chromosomal regions, and 4) the requirement for a minimum number (threshold) of markers to elicit sterility. Although our findings do not contradict a role for occasional major hybrid-sterility genes, they conform more to the view that HMS primarily evolves by the cumulative action of many interacting genes of minor effect in a complex PT architecture.
Mohammadnejad, Afsaneh; Brasch-Andersen, Charlotte; Haagerup, Annette
Background: Allergic Rhinitis (AR) is a complex disorder that affects many people around the world. There is a high genetic contribution to the development of the AR, as twins and family studies have estimated heritability of more than 33%. Due to the complex nature of the disease, single SNP...... analysis has limited power in identifying the genetic variations for AR. We combined genome-wide association analysis (GWAS) with polygenic risk score (PRS) in exploring the genetic basis underlying the disease. Methods: We collected clinical data on 631 Danish subjects with AR cases consisting of 434...... sibling pairs and unrelated individuals and control subjects of 197 unrelated individuals. SNP genotyping was done by Affymetrix Genome-Wide Human SNP Array 5.0. SNP imputation was performed using "IMPUTE2". Using additive effect model, GWAS was conducted in discovery sample, the genotypes...
Ji, Yuan; Schaid, Daniel J; Desta, Zeruesenay; Kubo, Michiaki; Batzler, Anthony J; Snyder, Karen; Mushiroda, Taisei; Kamatani, Naoyuki; Ogburn, Evan; Hall-Flavin, Daniel; Flockhart, David; Nakamura, Yusuke; Mrazek, David A; Weinshilboum, Richard M
Citalopram (CT) and escitalopram (S-CT) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder (MDD). We applied a genome-wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S-CT and their metabolites in MDD patients treated with CT or S-CT. Our genome-wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within-subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single-nucleotide polymorphisms (SNPs) were modelled as additive allelic effects. Genome-wide significant associations were observed for S-CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10(-9) ) and with S-didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10(-16) ), supporting the important role of these cytochrome P450 (CYP) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome-wide association study performed in MDD patients treated with CT or S-CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors. © 2014 The British Pharmacological Society.
Thorleifsson, Gudmar; Walters, G Bragi; Gudbjartsson, Daniel F
Obesity results from the interaction of genetic and environmental factors. To search for sequence variants that affect variation in two common measures of obesity, weight and body mass index (BMI), both of which are highly heritable, we performed a genome-wide association (GWA) study with 305......,846 SNPs typed in 25,344 Icelandic, 2,998 Dutch, 1,890 European Americans and 1,160 African American subjects and combined the results with previously published results from the Diabetes Genetics Initiative (DGI) on 3,024 Scandinavians. We selected 43 variants in 19 regions for follow-up in 5,586 Danish...... individuals and compared the results to a genome-wide study on obesity-related traits from the GIANT consortium. In total, 29 variants, some correlated, in 11 chromosomal regions reached a genome-wide significance threshold of P
Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J
The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53-3.14), P=1.9 × 10(-5)). Two polymorphisms at 6p21.2 LINC00951-LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37-1.85), P=1.6 × 10(-9)) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder.
Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.
Riechmann, J L; Heard, J; Martin, G; Reuber, L; Jiang, C; Keddie, J; Adam, L; Pineda, O; Ratcliffe, O J; Samaha, R R; Creelman, R; Pilgrim, M; Broun, P; Zhang, J Z; Ghandehari, D; Sherman, B K; Yu, G
The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.
Power, Robert A; Parkhill, Julian; de Oliveira, Tulio
The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.
Xu, Zhuofei; Zhou, Rui
As is well known, pathogenic microbes evolve rapidly to escape from the host immune system and antibiotics. Genetic variations among microbial populations occur frequently during the long-term pathogen–host evolutionary arms race, and individual mutation beneficial for the fitness can be fixed...... to scan genome-wide alignments for evidence of positive Darwinian selection, recombination, and other evolutionary forces operating on the coding regions. In this chapter, we describe an integrative analysis pipeline and its application to tracking featured evolutionary trajectories on the genome...
Ng, MYM; Levinson, DF; Faraone, SV; Suarez, BK; DeLisi, LE; Arinami, T; Riley, B; Paunio, T; Pulver, AE; Irmansyah; Holmans, PA; Escamilla, M; Wildenauer, DB; Williams, NM; Laurent, C; Mowry, BJ; Brzustowicz, LM; Maziade, M; Sklar, P; Garver, DL; Abecasis, GR; Lerer, B; Fallin, MD; Gurling, HMD; Gejman, PV; Lindholm, E; Moises, HW; Byerley, W; Wijsman, EM; Forabosco, P; Tsuang, MT; Hwu, H-G; Okazaki, Y; Kendler, KS; Wormley, B; Fanous, A; Walsh, D; O’Neill, FA; Peltonen, L; Nestadt, G; Lasseter, VK; Liang, KY; Papadimitriou, GM; Dikeos, DG; Schwab, SG; Owen, MJ; O’Donovan, MC; Norton, N; Hare, E; Raventos, H; Nicolini, H; Albus, M; Maier, W; Nimgaonkar, VL; Terenius, L; Mallet, J; Jay, M; Godard, S; Nertney, D; Alexander, M; Crowe, RR; Silverman, JM; Bassett, AS; Roy, M-A; Mérette, C; Pato, CN; Pato, MT; Roos, J Louw; Kohn, Y; Amann-Zalcenstein, D; Kalsi, G; McQuillin, A; Curtis, D; Brynjolfson, J; Sigmundsson, T; Petursson, H; Sanders, AR; Duan, J; Jazin, E; Myles-Worsley, M; Karayiorgou, M; Lewis, CM
A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (PSR) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for ‘aggregate’ genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies. PMID:19349958
Full Text Available Genome-wide association studies (GWAS aim to identify genetic variants related to diseases by examining the associations between phenotypes and hundreds of thousands of genotyped markers. Because many genes are potentially involved in common diseases and a large number of markers are analyzed, it is crucial to devise an effective strategy to identify truly associated variants that have individual and/or interactive effects, while controlling false positives at the desired level. Although a number of model selection methods have been proposed in the literature, including marginal search, exhaustive search, and forward search, their relative performance has only been evaluated through limited simulations due to the lack of an analytical approach to calculating the power of these methods. This article develops a novel statistical approach for power calculation, derives accurate formulas for the power of different model selection strategies, and then uses the formulas to evaluate and compare these strategies in genetic model spaces. In contrast to previous studies, our theoretical framework allows for random genotypes, correlations among test statistics, and a false-positive control based on GWAS practice. After the accuracy of our analytical results is validated through simulations, they are utilized to systematically evaluate and compare the performance of these strategies in a wide class of genetic models. For a specific genetic model, our results clearly reveal how different factors, such as effect size, allele frequency, and interaction, jointly affect the statistical power of each strategy. An example is provided for the application of our approach to empirical research. The statistical approach used in our derivations is general and can be employed to address the model selection problems in other random predictor settings. We have developed an R package markerSearchPower to implement our formulas, which can be downloaded from the
This chapter attempts to describe and compare some of the more important nucleon-nucleon interactions that have been used in nuclear structure calculations, and to relate them where possible to the real nucleon-nucleon interaction. Explains that different interactions have been used depending on whether one is fitting to total binding energies and densities with a Hartree Fock (HF) calculation or fitting to spectra and spectroscopic data in a shell model calculation. Examines both types of calculation after two preliminary sections concerned with notation and with the philosophy underlying the use of model spaces and effective interactions. Discusses Skyrme interactions, finite range interactions, small model space, large model space, and the Sussex potential matrix elements. Focuses on the more empirical approaches in which a simple form is chosen for the effective interaction in a given model space and the parameters are deduced from fitting many-body data
Fall, Tove; Ingelsson, Erik
Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Full Text Available Determination of cellular DNA damage has so far been limited to global assessment of genome integrity whereas nucleotide-level mapping has been restricted to specific loci by the use of specific primers. Therefore, only limited DNA sequences can be studied and novel regions of genomic instability can hardly be discovered. Using a well-characterized yeast model, we describe a straightforward strategy to map genome-wide DNA strand breaks without compromising nucleotide-level resolution. This technique, termed "damaged DNA immunoprecipitation" (dDIP, uses immunoprecipitation and the terminal deoxynucleotidyl transferase-mediated dUTP-biotin end-labeling (TUNEL to capture DNA at break sites. When used in combination with microarray or next-generation sequencing technologies, dDIP will allow researchers to map genome-wide DNA strand breaks as well as other types of DNA damage and to establish a clear profiling of altered genes and/or intergenic sequences in various experimental conditions. This mapping technique could find several applications for instance in the study of aging, genotoxic drug screening, cancer, meiosis, radiation and oxidative DNA damage.
Walter, Stefan; Atzmon, Gil; Demerath, Ellen W; Garcia, Melissa E; Kaplan, Robert C; Kumari, Meena; Lunetta, Kathryn L; Milaneschi, Yuri; Tanaka, Toshiko; Tranah, Gregory J; Völker, Uwe; Yu, Lei; Arnold, Alice; Benjamin, Emelia J; Biffar, Reiner; Buchman, Aron S; Boerwinkle, Eric; Couper, David; De Jager, Philip L; Evans, Denis A; Harris, Tamara B; Hoffmann, Wolfgang; Hofman, Albert; Karasik, David; Kiel, Douglas P; Kocher, Thomas; Kuningas, Maris; Launer, Lenore J; Lohman, Kurt K; Lutsey, Pamela L; Mackenbach, Johan; Marciante, Kristin; Psaty, Bruce M; Reiman, Eric M; Rotter, Jerome I; Seshadri, Sudha; Shardell, Michelle D; Smith, Albert V; van Duijn, Cornelia; Walston, Jeremy; Zillikens, M Carola; Bandinelli, Stefania; Baumeister, Sebastian E; Bennett, David A; Ferrucci, Luigi; Gudnason, Vilmundur; Kivimaki, Mika; Liu, Yongmei; Murabito, Joanne M; Newman, Anne B; Tiemeier, Henning; Franceschini, Nora
Human longevity and healthy aging show moderate heritability (20%-50%). We conducted a meta-analysis of genome-wide association studies from 9 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium for 2 outcomes: (1) all-cause mortality, and (2) survival free of major disease or death. No single nucleotide polymorphism (SNP) was a genome-wide significant predictor of either outcome (p < 5 × 10(-8)). We found 14 independent SNPs that predicted risk of death, and 8 SNPs that predicted event-free survival (p < 10(-5)). These SNPs are in or near genes that are highly expressed in the brain (HECW2, HIP1, BIN2, GRIA1), genes involved in neural development and function (KCNQ4, LMO4, GRIA1, NETO1) and autophagy (ATG4C), and genes that are associated with risk of various diseases including cancer and Alzheimer's disease. In addition to considerable overlap between the traits, pathway and network analysis corroborated these findings. These findings indicate that variation in genes involved in neurological processes may be an important factor in regulating aging free of major disease and achieving longevity. Copyright © 2011 Elsevier Inc. All rights reserved.
Jin, Eun-Heui; Zhang, Enji; Ko, Youngkwon; Sim, Woo Seog; Moon, Dong Eon; Yoon, Keon Jung; Hong, Jang Hee; Lee, Won Hyung
Complex regional pain syndrome (CRPS) is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II) and 5 controls (cut-off value: 1.5-fold change and pCRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10−4). The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression. PMID:24244504
M. Ilyas Kamboh
Full Text Available Background. The persistent presence of antiphospholipid antibodies (APA may lead to the development of primary or secondary antiphospholipid syndrome. Although the genetic basis of APA has been suggested, the identity of the underlying genes is largely unknown. In this study, we have performed a genome-wide association study (GWAS in an effort to identify susceptibility loci/genes for three main APA: anticardiolipin antibodies (ACL, lupus anticoagulant (LAC, and anti-β2 glycoprotein I antibodies (anti-β2GPI. Methods. DNA samples were genotyped using the Affymetrix 6.0 array containing 906,600 single-nucleotide polymorphisms (SNPs. Association of SNPs with the antibody status (positive/negative was tested using logistic regression under the additive model. Results. We have identified a number of suggestive novel loci with P
Scharf, Jeremiah M.; Yu, Dongmei; Mathews, Carol A.; Neale, Benjamin M.; Stewart, S. Evelyn; Fagerness, Jesen A; Evans, Patrick; Gamazon, Eric; Edlund, Christopher K.; Service, Susan; Tikhomirov, Anna; Osiecki, Lisa; Illmann, Cornelia; Pluzhnikov, Anna; Konkashbaev, Anuar; Davis, Lea K; Han, Buhm; Crane, Jacquelyn; Moorjani, Priya; Crenshaw, Andrew T.; Parkin, Melissa A.; Reus, Victor I.; Lowe, Thomas L.; Rangel-Lugo, Martha; Chouinard, Sylvain; Dion, Yves; Girard, Simon; Cath, Danielle C; Smit, Jan H; King, Robert A.; Fernandez, Thomas; Leckman, James F.; Kidd, Kenneth K.; Kidd, Judith R.; Pakstis, Andrew J.; State, Matthew; Herrera, Luis Diego; Romero, Roxana; Fournier, Eduardo; Sandor, Paul; Barr, Cathy L; Phan, Nam; Gross-Tsur, Varda; Benarroch, Fortu; Pollak, Yehuda; Budman, Cathy L.; Bruun, Ruth D.; Erenberg, Gerald; Naarden, Allan L; Lee, Paul C; Weiss, Nicholas; Kremeyer, Barbara; Berrío, Gabriel Bedoya; Campbell, Desmond; Silgado, Julio C. Cardona; Ochoa, William Cornejo; Restrepo, Sandra C. Mesa; Muller, Heike; Duarte, Ana V. Valencia; Lyon, Gholson J; Leppert, Mark; Morgan, Jubel; Weiss, Robert; Grados, Marco A.; Anderson, Kelley; Davarya, Sarah; Singer, Harvey; Walkup, John; Jankovic, Joseph; Tischfield, Jay A.; Heiman, Gary A.; Gilbert, Donald L.; Hoekstra, Pieter J.; Robertson, Mary M.; Kurlan, Roger; Liu, Chunyu; Gibbs, J. Raphael; Singleton, Andrew; Hardy, John; Strengman, Eric; Ophoff, Roel; Wagner, Michael; Moessner, Rainald; Mirel, Daniel B.; Posthuma, Danielle; Sabatti, Chiara; Eskin, Eleazar; Conti, David V.; Knowles, James A.; Ruiz-Linares, Andres; Rouleau, Guy A.; Purcell, Shaun; Heutink, Peter; Oostra, Ben A.; McMahon, William; Freimer, Nelson; Cox, Nancy J.; Pauls, David L.
Tourette Syndrome (TS) is a developmental disorder that has one of the highest familial recurrence rates among neuropsychiatric diseases with complex inheritance. However, the identification of definitive TS susceptibility genes remains elusive. Here, we report the first genome-wide association study (GWAS) of TS in 1285 cases and 4964 ancestry-matched controls of European ancestry, including two European-derived population isolates, Ashkenazi Jews from North America and Israel, and French Canadians from Quebec, Canada. In a primary meta-analysis of GWAS data from these European ancestry samples, no markers achieved a genome-wide threshold of significance (p<5 × 10−8); the top signal was found in rs7868992 on chromosome 9q32 within COL27A1 (p=1.85 × 10−6). A secondary analysis including an additional 211 cases and 285 controls from two closely-related Latin-American population isolates from the Central Valley of Costa Rica and Antioquia, Colombia also identified rs7868992 as the top signal (p=3.6 × 10−7 for the combined sample of 1496 cases and 5249 controls following imputation with 1000 Genomes data). This study lays the groundwork for the eventual identification of common TS susceptibility variants in larger cohorts and helps to provide a more complete understanding of the full genetic architecture of this disorder. PMID:22889924
Chen, Gary K; Zheng, Tian; Witte, John S; Goode, Ellen L; Gao, Lei; Hu, Pingzhao; Suh, Young Ju; Suktitipat, Bhoom; Szymczak, Silke; Woo, Jung Hoon; Zhang, Wei
A number of issues arise when analyzing the large amount of data from high-throughput genotype and expression microarray experiments, including design and interpretation of genome-wide association studies of expression phenotypes. These issues were considered by contributions submitted to Group 1 of the Genetic Analysis Workshop 15 (GAW15), which focused on the association of quantitative expression data. These contributions evaluated diverse hypotheses, including those relevant to cancer and obesity research, and used various analytic techniques, many of which were derived from information theory. Several observations from these reports stand out. First, one needs to consider the genetic model of the trait of interest and carefully select which single nucleotide polymorphisms and individuals are included early in the design stage of a study. Second, by targeting specific pathways when analyzing genome-wide data, one can generate more interpretable results than agnostic approaches. Finally, for datasets with small sample sizes but a large number of features like the Genetic Analysis Workshop 15 dataset, machine learning approaches may be more practical than traditional parametric approaches. (c) 2007 Wiley-Liss, Inc.
Harold T Bae
Full Text Available Personality traits have been shown to be associated with longevity and healthy aging. In order to discover novel genetic modifiers associated with personality traits as related with longevity, we performed a genome-wide association study (GWAS on personality factors assessed by NEO-FFI in individuals enrolled in the Long Life Family Study (LLFS, a study of 583 families (N up to 4595 with clustering for longevity in the United States and Denmark. Three SNPs, in almost perfect LD, associated with agreeableness reached genome-wide significance (p<10-8 and replicated in an additional sample of 1279 LLFS subjects, although one (rs9650241 failed to replicate and the other two were not available in two independent replication cohorts, the Baltimore Longitudinal Study of Aging and the New England Centenarian Study. Based on 10,000,000 permutations, the empirical p-value of 2X10-7 was observed for the genome-wide significant SNPs. Seventeen SNPs that reached marginal statistical significance in the two previous GWASs (p-value < 10-4 and 10-5, were also marginally significantly associated in this study (p-value < 0.05, although none of the associations passed the Bonferroni correction. In addition, we tested age-by-SNP interactions and found some significant associations. Since scores of personality traits in LLFS subjects change in the oldest ages, and genetic factors outweigh environmental factors to achieve extreme ages, these age-by-SNP interactions could be a proxy for complex gene-gene interactions affecting personality traits and longevity.
Evangelou, Evangelos; Fellay, Jacques; Colombo, Sara
Discussion on improving the power of genome-wide association studies to identify candidate variants and genes is generally centered on issues of maximizing sample size; less attention is given to the role of phenotype definition and ascertainment. The authors used genome-wide data from patients...... infected with human immunodeficiency virus type 1 (HIV-1) to assess whether differences in type of population (622 seroconverters vs. 636 seroprevalent subjects) or the number of measurements available for defining the phenotype resulted in differences in the effect sizes of associations between single...... available, particularly among seroconverters and for variants that achieved genome-wide significance. Differences in phenotype definition and ascertainment may affect the estimated magnitude of genetic effects and should be considered in optimizing power for discovering new associations....
Ahmed, Wareed; Sala, Claudia; Hegde, Shubhada R; Jha, Rajiv Kumar; Cole, Stewart T; Nagaraja, Valakunja
Movement of the transcription machinery along a template alters DNA topology resulting in the accumulation of supercoils in DNA. The positive supercoils generated ahead of transcribing RNA polymerase (RNAP) and the negative supercoils accumulating behind impose severe topological constraints impeding transcription process. Previous studies have implied the role of topoisomerases in the removal of torsional stress and the maintenance of template topology but the in vivo interaction of functionally distinct topoisomerases with heterogeneous chromosomal territories is not deciphered. Moreover, how the transcription-induced supercoils influence the genome-wide recruitment of DNA topoisomerases remains to be explored in bacteria. Using ChIP-Seq, we show the genome-wide occupancy profile of both topoisomerase I and DNA gyrase in conjunction with RNAP in Mycobacterium tuberculosis taking advantage of minimal topoisomerase representation in the organism. The study unveils the first in vivo genome-wide interaction of both the topoisomerases with the genomic regions and establishes that transcription-induced supercoils govern their recruitment at genomic sites. Distribution profiles revealed co-localization of RNAP and the two topoisomerases on the active transcriptional units (TUs). At a given locus, topoisomerase I and DNA gyrase were localized behind and ahead of RNAP, respectively, correlating with the twin-supercoiled domains generated. The recruitment of topoisomerases was higher at the genomic loci with higher transcriptional activity and/or at regions under high torsional stress compared to silent genomic loci. Importantly, the occupancy of DNA gyrase, sole type II topoisomerase in Mtb, near the Ter domain of the Mtb chromosome validates its function as a decatenase.
Rautiainen, M-R; Paunio, T; Repo-Tiihonen, E; Virkkunen, M; Ollila, H M; Sulkava, S; Jolanki, O; Palotie, A; Tiihonen, J
The pathophysiology of antisocial personality disorder (ASPD) remains unclear. Although the most consistent biological finding is reduced grey matter volume in the frontal cortex, about 50% of the total liability to developing ASPD has been attributed to genetic factors. The contributing genes remain largely unknown. Therefore, we sought to study the genetic background of ASPD. We conducted a genome-wide association study (GWAS) and a replication analysis of Finnish criminal offenders fulfilling DSM-IV criteria for ASPD (N=370, N=5850 for controls, GWAS; N=173, N=3766 for controls and replication sample). The GWAS resulted in suggestive associations of two clusters of single-nucleotide polymorphisms at 6p21.2 and at 6p21.32 at the human leukocyte antigen (HLA) region. Imputation of HLA alleles revealed an independent association with DRB1*01:01 (odds ratio (OR)=2.19 (1.53–3.14), P=1.9 × 10-5). Two polymorphisms at 6p21.2 LINC00951–LRFN2 gene region were replicated in a separate data set, and rs4714329 reached genome-wide significance (OR=1.59 (1.37–1.85), P=1.6 × 10−9) in the meta-analysis. The risk allele also associated with antisocial features in the general population conditioned for severe problems in childhood family (β=0.68, P=0.012). Functional analysis in brain tissue in open access GTEx and Braineac databases revealed eQTL associations of rs4714329 with LINC00951 and LRFN2 in cerebellum. In humans, LINC00951 and LRFN2 are both expressed in the brain, especially in the frontal cortex, which is intriguing considering the role of the frontal cortex in behavior and the neuroanatomical findings of reduced gray matter volume in ASPD. To our knowledge, this is the first study showing genome-wide significant and replicable findings on genetic variants associated with any personality disorder. PMID:27598967
Hsu, Yi-Hsiang; Liu, Youfang; Hannan, Marian T.; Maixner, William; Smith, Shad B.; Diatchenko, Luda; Golightly, Yvonne M.; Menz, Hylton B.; Kraus, Virginia B.; Doherty, Michael; Wilson, A.G.; Jordan, Joanne M.
Objective Hallux valgus (HV) affects ~36% of Caucasian adults. Although considered highly heritable, the underlying genetic determinants are unclear. We conducted the first genome-wide association study (GWAS) aimed to identify genetic variants associated with HV. Methods HV was assessed in 3 Caucasian cohorts (n=2,263, n=915, and n=1,231 participants, respectively). In each cohort, a GWAS was conducted using 2.5M imputed single nucleotide polymorphisms (SNPs). Mixed-effect regression with the additive genetic model adjusted for age, sex, weight and within-family correlations was used for both sex-specific and combined analyses. To combine GWAS results across cohorts, fixed-effect inverse-variance meta-analyses were used. Following meta-analyses, top-associated findings were also examined in an African American cohort (n=327). Results The proportion of HV variance explained by genome-wide genotyped SNPs was 50% in men and 48% in women. A higher proportion of genetic determinants of HV was sex-specific. The most significantly associated SNP in men was rs9675316 located on chr17q23-a24 near the AXIN2 gene (p=5.46×10−7); the most significantly associated SNP in women was rs7996797 located on chr13q14.1-q14.2 near the ESD gene (p=7.21×10−7). Genome-wide significant SNP-by-sex interaction was found for SNP rs1563374 located on chr11p15.1 near the MRGPRX3 gene (interaction p-value =4.1×10−9). The association signals diminished when combining men and women. Conclusion Findings suggest that the potential pathophysiological mechanisms of HV are complex and strongly underlined by sex-specific interactions. The identified genetic variants imply contribution of biological pathways observed in osteoarthritis as well as new pathways, influencing skeletal development and inflammation. PMID:26337638
Firnhaber Christopher B
Full Text Available Abstract Background The Notch signaling pathway regulates a diverse array of developmental processes, and aberrant Notch signaling can lead to diseases, including cancer. To obtain a more comprehensive understanding of the genetic network that integrates into Notch signaling, we performed a genome-wide RNAi screen in Drosophila cell culture to identify genes that modify Notch-dependent transcription. Results Employing complementary data analyses, we found 399 putative modifiers: 189 promoting and 210 antagonizing Notch activated transcription. These modifiers included several known Notch interactors, validating the robustness of the assay. Many novel modifiers were also identified, covering a range of cellular localizations from the extracellular matrix to the nucleus, as well as a large number of proteins with unknown function. Chromatin-modifying proteins represent a major class of genes identified, including histone deacetylase and demethylase complex components and other chromatin modifying, remodeling and replacement factors. A protein-protein interaction map of the Notch-dependent transcription modifiers revealed that a large number of the identified proteins interact physically with these core chromatin components. Conclusions The genome-wide RNAi screen identified many genes that can modulate Notch transcriptional output. A protein interaction map of the identified genes highlighted a network of chromatin-modifying enzymes and remodelers that regulate Notch transcription. Our results open new avenues to explore the mechanisms of Notch signal regulation and the integration of this pathway into diverse cellular processes.
Mohanty, Sujata; Khanna, Radhika
Comparative analysis of multiple genomes of closely or distantly related Drosophila species undoubtedly creates excitement among evolutionary biologists in exploring the genomic changes with an ecology and evolutionary perspective. We present herewith the de novo assembled whole genome sequences of four Drosophila species, D. bipectinata, D. takahashii, D. biarmipes and D. nasuta of Indian origin using Next Generation Sequencing technology on an Illumina platform along with their detailed assembly statistics. The comparative genomics analysis, e.g. gene predictions and annotations, functional and orthogroup analysis of coding sequences and genome wide SNP distribution were performed. The whole genome of Zaprionus indianus of Indian origin published earlier by us and the genome sequences of previously sequenced 12 Drosophila species available in the NCBI database were included in the analysis. The present work is a part of our ongoing genomics project of Indian Drosophila species.
Dijkstra, Akkelies E; Smolonska, Joanna; van den Berge, Maarten
by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years). Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism...... (SNP). RESULTS: A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10(-6), OR = 1.17), located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1) on chromosome 3. The risk allele (G) was associated with higher mRNA expression...... of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA) study of CMH in Caucasian populations. METHODS: GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed...
Gong, Jian; Hsu, Li; Harrison, Tabitha
Selenium is an essential trace element and circulating selenium concentrations have been associated with a wide range of diseases. Candidate gene studies suggest that circulating selenium concentrations may be impacted by genetic variation; however, no study has comprehensively investigated...... this hypothesis. Therefore, we conducted a two-stage genome-wide association study to identify genetic variants associated with serum selenium concentrations in 1203 European descents from two cohorts: the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening and the Women’s Health Initiative (WHI). We...... tested association between 2,474,333 single nucleotide polymorphisms (SNPs) and serum selenium concentrations using linear regression models. In the first stage (PLCO) 41 SNPs clustered in 15 regions had p
Soil water deficit is one of the major factors limiting plant productivity. Plants cope with this adverse environmental condition by coordinating the up- or downregulation of an array of stress responsive genes. Reprogramming the expression of these genes leads to rebalanced development and growth that are in concert with the reduced water availability and that ultimately confer enhanced stress tolerance. Currently, several techniques have been employed to monitor genome-wide transcriptional reprogramming under drought stress. The results from these high throughput studies indicate that drought stress-induced transcriptional reprogramming is dynamic, has temporal and spatial specificity, and is coupled with the circadian clock and phytohormone signaling pathways. © 2012 Springer-Verlag Berlin Heidelberg. All rights are reserved.
Lada Artem G
Full Text Available Abstract Clusters of localized hypermutation in human breast cancer genomes, named “kataegis” (from the Greek for thunderstorm, are hypothesized to result from multiple cytosine deaminations catalyzed by AID/APOBEC proteins. However, a direct link between APOBECs and kataegis is still lacking. We have sequenced the genomes of yeast mutants induced in diploids by expression of the gene for PmCDA1, a hypermutagenic deaminase from sea lamprey. Analysis of the distribution of 5,138 induced mutations revealed localized clusters very similar to those found in tumors. Our data provide evidence that unleashed cytosine deaminase activity is an evolutionary conserved, prominent source of genome-wide kataegis events. Reviewers This article was reviewed by: Professor Sandor Pongor, Professor Shamil R. Sunyaev, and Dr Vladimir Kuznetsov.
Galesloot, Tessel E; Van Steen, Kristel; Kiemeney, Lambertus A L M
Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six...... methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three...... for scenarios with an opposite sign of genetic and residual correlation. All multivariate analyses resulted in a higher power than univariate analyses, even when only one of the traits was associated with the QTL. Hence, use of multivariate GWAS methods can be recommended, even when genetic correlations between...
Full Text Available Genome-wide association study (GWAS aims to discover genetic factors underlying phenotypic traits. The large number of genetic factors poses both computational and statistical challenges. Various computational approaches have been developed for large scale GWAS. In this chapter, we will discuss several widely used computational approaches in GWAS. The following topics will be covered: (1 An introduction to the background of GWAS. (2 The existing computational approaches that are widely used in GWAS. This will cover single-locus, epistasis detection, and machine learning methods that have been recently developed in biology, statistic, and computer science communities. This part will be the main focus of this chapter. (3 The limitations of current approaches and future directions.
Full Text Available Genome-wide association studies (GWAS use high-throughput genotyping technology to relate hundreds of thousands of genetic markers (genotypes to clinical conditions and measurable traits (phenotypes. This review is intended to serve as an introduction to GWAS for clinicians, to allow them to better appreciate the value and limitations of GWAS for genotype-disease association studies. The input of clinicians is vital for GWAS, since disease heterogeneity is frequently a confounding factor that can only really be solved by clinicians. For diseases that are difficult to diagnose, clinicians should ensure that the cases do indeed have the disease; for common diseases, clinicians should ensure that the controls are truly disease-free.
Genetic studies have identified >60 loci associated with the risk of developing type 1 diabetes (T1D). The vast majority of these are identified by genome-wide association studies (GWAS) using large case-control cohorts of European ancestry. More than 80% of the heritability of T1D can be explained...... by GWAS data in this population group. However, with few exceptions, their individual contribution to T1D risk is low and understanding their function in disease biology remains a huge challenge. GWAS on its own does not inform us in detail on disease mechanisms, but the combination of GWAS data...... with other omics-data is beginning to advance our understanding of T1D etiology and pathogenesis. Current knowledge supports the notion that genetic variation in both pancreatic β cells and in immune cells is central in mediating T1D risk. Advances, perspectives and limitations of GWAS are discussed...
Caicedo, Ana L; Williamson, Scott H; Hernandez, Ryan D
Domesticated Asian rice (Oryza sativa) is one of the oldest domesticated crop species in the world, having fed more people than any other plant in human history. We report the patterns of DNA sequence variation in rice and its wild ancestor, O. rufipogon, across 111 randomly chosen gene fragments......, and use these to infer the evolutionary dynamics that led to the origins of rice. There is a genome-wide excess of high-frequency derived single nucleotide polymorphisms (SNPs) in O. sativa varieties, a pattern that has not been reported for other crop species. We developed several alternative models...... to explain contemporary patterns of polymorphisms in rice, including a (i) selectively neutral population bottleneck model, (ii) bottleneck plus migration model, (iii) multiple selective sweeps model, and (iv) bottleneck plus selective sweeps model. We find that a simple bottleneck model, which has been...
Full Text Available Complex regional pain syndrome (CRPS is a chronic, progressive, and devastating pain syndrome characterized by spontaneous pain, hyperalgesia, allodynia, altered skin temperature, and motor dysfunction. Although previous gene expression profiling studies have been conducted in animal pain models, there genome-wide expression profiling in the whole blood of CRPS patients has not been reported yet. Here, we successfully identified certain pain-related genes through genome-wide expression profiling in the blood from CRPS patients. We found that 80 genes were differentially expressed between 4 CRPS patients (2 CRPS I and 2 CRPS II and 5 controls (cut-off value: 1.5-fold change and p<0.05. Most of those genes were associated with signal transduction, developmental processes, cell structure and motility, and immunity and defense. The expression levels of major histocompatibility complex class I A subtype (HLA-A29.1, matrix metalloproteinase 9 (MMP9, alanine aminopeptidase N (ANPEP, l-histidine decarboxylase (HDC, granulocyte colony-stimulating factor 3 receptor (G-CSF3R, and signal transducer and activator of transcription 3 (STAT3 genes selected from the microarray were confirmed in 24 CRPS patients and 18 controls by quantitative reverse transcription-polymerase chain reaction (qRT-PCR. We focused on the MMP9 gene that, by qRT-PCR, showed a statistically significant difference in expression in CRPS patients compared to controls with the highest relative fold change (4.0±1.23 times and p = 1.4×10(-4. The up-regulation of MMP9 gene in the blood may be related to the pain progression in CRPS patients. Our findings, which offer a valuable contribution to the understanding of the differential gene expression in CRPS may help in the understanding of the pathophysiology of CRPS pain progression.
Willour, Virginia L.; Seifuddin, Fayaz; Mahon, Pamela B.; Jancic, Dubravka; Pirooznia, Mehdi; Steele, Jo; Schweizer, Barbara; Goes, Fernando S.; Mondimore, Francis M.; MacKinnon, Dean F.; Perlis, Roy H.; Lee, Phil Hyoun; Huang, Jie; Kelsoe, John R.; Shilling, Paul D.; Rietschel, Marcella; Nöthen, Markus; Cichon, Sven; Gurling, Hugh; Purcell, Shaun; Smoller, Jordan W.; Craddock, Nicholas; DePaulo, J. Raymond; Schulze, Thomas G.; McMahon, Francis J.; Zandi, Peter P.; Potash, James B.
The heritable component to attempted and completed suicide is partly related to psychiatric disorders and also partly independent of them. While attempted suicide linkage regions have been identified on 2p11–12 and 6q25–26, there are likely many more such loci, the discovery of which will require a much higher resolution approach, such as the genome-wide association study (GWAS). With this in mind, we conducted an attempted suicide GWAS that compared the single nucleotide polymorphism (SNP) genotypes of 1,201 bipolar (BP) subjects with a history of suicide attempts to the genotypes of 1,497 BP subjects without a history of suicide attempts. 2,507 SNPs with evidence for association at p<0.001 were identified. These associated SNPs were subsequently tested for association in a large and independent BP sample set. None of these SNPs were significantly associated in the replication sample after correcting for multiple testing, but the combined analysis of the two sample sets produced an association signal on 2p25 (rs300774) at the threshold of genome-wide significance (p= 5.07 × 10−8). The associated SNPs on 2p25 fall in a large linkage disequilibrium block containing the ACP1 gene, a gene whose expression is significantly elevated in BP subjects who have completed suicide. Furthermore, the ACP1 protein is a tyrosine phosphatase that influences Wnt signaling, a pathway regulated by lithium, making ACP1 a functional candidate for involvement in the phenotype. Larger GWAS sample sets will be required to confirm the signal on 2p25 and to identify additional genetic risk factors increasing susceptibility for attempted suicide. PMID:21423239
Full Text Available Michael E March,1 Patrick MA Sleiman,1,2 Hakon Hakonarson1,2 1Center for Applied Genomics, Children's Hospital of Philadelphia Research Institute, 2Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Abstract: Genetic studies of asthma have revealed that there is considerable heritability to the phenotype. An extensive history of candidate-gene studies has identified a long list of genes associated with immune function that are potentially involved in asthma pathogenesis. However, many of the results of candidate-gene studies have failed to be replicated, leaving in question the true impact of the implicated biological pathways on asthma. With the advent of genome-wide association studies, geneticists are able to examine the association of hundreds of thousands of genetic markers with a phenotype, allowing the hypothesis-free identification of variants associated with disease. Many such studies examining asthma or related phenotypes have been published, and several themes have begun to emerge regarding the biological pathways underpinning asthma. The results of many genome-wide association studies have currently not been replicated, and the large sample sizes required for this experimental strategy invoke difficulties with sample stratification and phenotypic heterogeneity. Recently, large collaborative groups of researchers have formed consortia focused on asthma, with the goals of sharing material and data and standardizing diagnosis and experimental methods. Additionally, research has begun to focus on genetic variants that affect the response to asthma medications and on the biology that generates the heterogeneity in the asthma phenotype. As this work progresses, it will move asthma patients closer to more specific, personalized medicine. Keywords: asthma, genetics, GWAS, pharmacogenetics, biomarkers
Jennifer K Lowe
Full Text Available It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining >/=5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.
Full Text Available Maintaining genetic variation and controlling the increase in inbreeding are crucial requirements in animal conservation programs. The most widely accepted strategy for achieving these objectives is to maximize the effective population size by minimizing the global coancestry obtained from a particular pedigree. However, for most natural or captive populations genealogical information is absent. In this situation, microsatellites have been traditionally the markers of choice to characterize genetic variation, and several estimators of genealogical coefficients have been developed using marker data, with unsatisfactory results. The development of high-throughput genotyping techniques states the necessity of reviewing the paradigm that genealogical coancestry is the best parameter for measuring genetic diversity. In this study, the Illumina PorcineSNP60 BeadChip was used to obtain genome-wide estimates of rates of coancestry and inbreeding and effective population size for an ancient strain of Iberian pigs that is now in serious danger of extinction and for which very accurate genealogical information is available (the Guadyerbas strain. Genome-wide estimates were compared with those obtained from microsatellite and from pedigree data. Estimates of coancestry and inbreeding computed from the SNP chip were strongly correlated with genealogical estimates and these correlations were substantially higher than those between microsatellite and genealogical coefficients. Also, molecular coancestry computed from SNP information was a better predictor of genealogical coancestry than coancestry computed from microsatellites. Rates of change in coancestry and inbreeding and effective population size estimated from molecular data were very similar to those estimated from genealogical data. However, estimates of effective population size obtained from changes in coancestry or inbreeding differed. Our results indicate that genome-wide information represents a
Wang, Jinglu; Qu, Susu; Wang, Weixiao; Guo, Liyuan; Zhang, Kunlin; Chang, Suhua; Wang, Jing
Numbers of gene expression profiling studies of bipolar disorder have been published. Besides different array chips and tissues, variety of the data processes in different cohorts aggravated the inconsistency of results of these genome-wide gene expression profiling studies. By searching the gene expression databases, we obtained six data sets for prefrontal cortex (PFC) of bipolar disorder with raw data and combinable platforms. We used standardized pre-processing and quality control procedures to analyze each data set separately and then combined them into a large gene expression matrix with 101 bipolar disorder subjects and 106 controls. A standard linear mixed-effects model was used to calculate the differentially expressed genes (DEGs). Multiple levels of sensitivity analyses and cross validation with genetic data were conducted. Functional and network analyses were carried out on basis of the DEGs. In the result, we identified 198 unique differentially expressed genes in the PFC of bipolar disorder and control. Among them, 115 DEGs were robust to at least three leave-one-out tests or different pre-processing methods; 51 DEGs were validated with genetic association signals. Pathway enrichment analysis showed these DEGs were related with regulation of neurological system, cell death and apoptosis, and several basic binding processes. Protein-protein interaction network further identified one key hub gene. We have contributed the most comprehensive integrated analysis of bipolar disorder expression profiling studies in PFC to date. The DEGs, especially those with multiple validations, may denote a common signature of bipolar disorder and contribute to the pathogenesis of disease. Copyright © 2016 Elsevier Ltd. All rights reserved.
Wang, Zhaoming; McGlynn, Katherine A.; Rajpert-De Meyts, Ewa
The international Testicular Cancer Consortium (TECAC) combined five published genome-wide association studies of testicular germ cell tumor (TGCT; 3,558 cases and 13,970 controls) to identify new susceptibility loci. We conducted a fixed-effects meta-analysis, including, to our knowledge, the fi...
Randall, J.C.; Winkler, T.W.; Kutalik, Z.; Berndt, S.I.; Jackson, A.U.; Monda, K.L.; Kilpeläinen, T.O.; Esko, T.; Mägi, R.; Li, S.; Workalemahu, T.; Feitosa, M.F.; Croteau-Chonka, D.C.; Day, F.R.; Fall, T.; Ferreira, T.; Gustafsson, S.; Locke, A.E.; Mathieson, I.; Scherag, A.; Vedantam, S.; Wood, A.R.; Liang, L.; Steinthorsdottir, V.; Thorleifsson, G.; Dermitzakis, E.T.; Dimas, A.S.; Karpe, F.; Min, J.L.; Nicholson, G.; Clegg, D.J.; Person, T.; Krohn, J.P.; Bauer, S.; Buechler, C.; Eisinger, K.; Bonnefond, A.; Froguel, P.; Hottenga, J.J.; Prokopenko, I.; Waite, L.L.; Harris, T.B.; Smith, A.V.; Shuldiner, A.R.; McArdle, W.L.; Caulfield, M.J.; Munroe, P.B.; Grönberg, H.; Chen, Y.D.; Li, G.; Beckmann, J.S.; Johnson, T.; Thorsteinsdottir, U.; Teder-Laving, M.; Khaw, K.T.; Wareham, N.J.; Zhao, J.H.; Amin, N.; Oostra, B.A.; Kraja, A.T.; Province, M.A.; Cupples, L.A.; Heard-Costa, N.L.; Kaprio, J.; Ripatti, S.; Surakka, I.; Collins, F.S.; Saramies, J.; Tuomilehto, J.; Jula, A.; Salomaa, V.; Erdmann, J.; Hengstenberg, C.; Loley, C.; Schunkert, H.; Lamina, C.; Wichmann, H.E.; Albrecht, E.; Gieger, C.; Hicks, A.A.; Johansson, A.; Pramstaller, P.P.; Kathiresan, S.; Speliotes, E.K.; Penninx, B.W.J.H.; Hartikainen, A.L.; Järvelin, M.R.; Gyllensten, U.; Boomsma, D.I.; Campbell, H.; Wilson, J.F.; Chanock, S.J.; Farrall, M.; Goel, A.; Medina-Gomez, C.; Rivadeneira, F.; Estrada, K.; Uitterlinden, A.G.; Hofman, A.; Zillikens, M.C.; den Heijer, M.; Kiemeney, L.A.; Maschio, A.; Hall, P.; Tyrer, J.; Teumer, A.; Völzke, H.; Kovacs, P.; Tönjes, A.; Mangino, M.; Spector, T.D.; Hayward, C.; Rudan, I.; Hall, A.S.; Samani, N.J.; Attwood, A.P.; Sambrook, J.G.; Hung, J.; Palmer, L.J.; Lokki, M.L.; Sinisalo, J.; Boucher, G.; Huikuri, H.V.; Lorentzon, M.; Ohlsson, C.; Eklund, N.; Eriksson, J.G.; Barlassina, C.; Rivolta, C.; Nolte, I.M.; Snieder, H.; van der Klauw, M.M.; van Vliet-Ostaptchouk, J.V.; Gejman, P.V.; Shi, J.; Jacobs, K.B.; Wang, Z.; Bakker, S.J.; Mateo Leach, I.; Navis, G.; van der Harst, P.; Martin, N.G.; Medland, S.E.; Montgomery, G.W.; Yang, J.; Chasman, D.I.; Ridker, P.M.; Rose, L.M.; Lehtimäki, T.; Raitakari, O.; Absher, D.; Iribarren, C.; Basart, H.; Hovingh, K.G.; Hyppönen, E.; Power, C.; Anderson, D.; Beilby, J.P.; Hui, J.; Jolley, J.; Sager, H.; Bornstein, S.R.; Schwarz, P.E.; Kristiansson, K.; Perola, M.; Lindström, J.; Swift, A.J.; Uusitupa, M.; Atalay, M.; Lakka, T.A.; Rauramaa, R.; Bolton, J.L.; Fowkes, G.; Fraser, R.M.; Price, J.F.; Fischer, K.; Krjuta Kov, K.; Metspalu, A.; Mihailov, E.; Langenberg, C.; Luan, J.; Ong, K.K.; Chines, P.S.; Keinanen-Kiukaanniemie, S.; Saaristo, T.E.; Edkins, S.; Franks, P.W.; Hallmans, G.; Shungin, D.; Morris, A.D.; Palmer, C.N.A.; Erbel, R.; Moebus, S.; Nöthen, M.M.; Pechlivanis, S.; Hveem, K.; Narisu, N.; Hamsten, A.; Humphries, S.E.; Strawbridge, R.J.; Tremoli, E.; Grallert, H.; Thorand, B.; Illig, T.; Koenig, W.; Müller-Nurasyid, M.; Peters, A.; Boehm, B.O.; Kleber, M.E.; März, W.; Winkelmann, B.R.; Kuusisto, J.; Laakso, M.; Arveiler, D.; Cesana, G.; Kuulasmaa, K.; Virtamo, J.; Yarnell, J.W.; Kuh, D; Wong, A.; Lind, L.; de Faire, U.; Gigante, B.; Magnusson, P.K.E.; Pedersen, N.L.; Dedoussis, G.; Dimitriou, M.; Kolovou, G.; Kanoni, S.; Stirrups, K.; Bonnycastle, L.L.; Njolstad, I.; Wilsgaard, T.; Ganna, A.; Rehnberg, E.; Hingorani, A.D.; Kivimaki, M.; Kumari, M.; Assimes, T.L.; Barroso, I.; Boehnke, M.; Borecki, I.B.; Deloukas, P.; Fox, C.S.; Frayling, T.M.; Groop, L.C.; Haritunians, T.; Hunter, D.; Ingelsson, E.; Kaplan, R.; Mohlke, K.L.; O'Connell, J.R.; Schlessinger, D.; Strachan, D.P.; Stefansson, K.; van Duijn, C.M.; Abecasis, G.R.; McCarthy, M.I.; Hirschhorn, J.N.; Qi, L.; Loos, R.J.; Lindgren, C.M.; North, K.E.; Heid, I.M.
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
Scott, Robert A; Scott, Laura J; Mägi, Reedik
To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promi...... secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology....
Dong, Jing; Yang, Jingyun; Tranah, Greg; Franceschini, Nora; Parimi, Neeta; Alkorta-Aranburu, Gorka; Xu, Zongli; Alonso, Alvaro; Cummings, Steven R; Fornage, Myriam; Huang, Xuemei; Kritchevsky, Stephen; Liu, Yongmei; London, Stephanie; Niu, Liang; Wilson, Robert S; De Jager, Philip L; Yu, Lei; Singleton, Andrew B; Harris, Tamara; Mosley, Thomas H; Pinto, Jayant M; Bennett, David A; Chen, Honglei
Olfactory dysfunction is common among older adults and affects their safety, nutrition, quality of life, and mortality. More importantly, the decreased sense of smell is an early symptom of neurodegenerative diseases such as Parkinson disease (PD) and Alzheimer disease. However, the genetic determinants for the sense of smell have been poorly investigated. We here performed the first genome-wide meta-analysis on the sense of smell among 6252 US older adults of European descent from the Atherosclerosis Risk in Communities (ARIC) study, the Health, Aging, and Body Composition (Health ABC) study, and the Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Genome-wide association study analysis was performed first by individual cohorts and then meta-analyzed using fixed-effect models with inverse variance weights. Although no SNPs reached genome-wide statistical significance, we identified 13 loci with suggestive evidence for an association with the sense of smell (Pmeta < 1 × 10). Of these, 2 SNPs at chromosome 17q21.31 (rs199443 in NSF, P = 3.02 × 10; and rs2732614 in KIAA1267-LRRC37A, P = 6.65 × 10) exhibited cis effects on the expression of microtubule-associated protein tau (MAPT, 17q21.31) in 447 frontal-cortex samples obtained postmortem and profiled by RNA-seq (P < 1 × 10). Gene-based and pathway-enrichment analyses further implicated MAPT in regulating the sense of smell in older adults. Similar results were obtained after excluding participants who reported a physician-diagnosed PD or use of PD medications. In conclusion, we provide preliminary evidence that the MAPT locus may play a role in regulating the sense of smell in older adults and therefore offer a potential genetic link between poor sense of smell and major neurodegenerative diseases.
Kasperaviciūte, Dalia; Catarino, Claudia B; Heinzen, Erin L; Depondt, Chantal; Cavalleri, Gianpiero L; Caboclo, Luis O; Tate, Sarah K; Jamnadas-Khoda, Jenny; Chinthapalli, Krishna; Clayton, Lisa M S; Shianna, Kevin V; Radtke, Rodney A; Mikati, Mohamad A; Gallentine, William B; Husain, Aatif M; Alhusaini, Saud; Leppert, David; Middleton, Lefkos T; Gibson, Rachel A; Johnson, Michael R; Matthews, Paul M; Hosford, David; Heuser, Kjell; Amos, Leslie; Ortega, Marcos; Zumsteg, Dominik; Wieser, Heinz-Gregor; Steinhoff, Bernhard J; Krämer, Günter; Hansen, Jörg; Dorn, Thomas; Kantanen, Anne-Mari; Gjerstad, Leif; Peuralinna, Terhi; Hernandez, Dena G; Eriksson, Kai J; Kälviäinen, Reetta K; Doherty, Colin P; Wood, Nicholas W; Pandolfo, Massimo; Duncan, John S; Sander, Josemir W; Delanty, Norman; Goldstein, David B; Sisodiya, Sanjay M
Partial epilepsies have a substantial heritability. However, the actual genetic causes are largely unknown. In contrast to many other common diseases for which genetic association-studies have successfully revealed common variants associated with disease risk, the role of common variation in partial epilepsies has not yet been explored in a well-powered study. We undertook a genome-wide association-study to identify common variants which influence risk for epilepsy shared amongst partial epilepsy syndromes, in 3445 patients and 6935 controls of European ancestry. We did not identify any genome-wide significant association. A few single nucleotide polymorphisms may warrant further investigation. We exclude common genetic variants with effect sizes above a modest 1.3 odds ratio for a single variant as contributors to genetic susceptibility shared across the partial epilepsies. We show that, at best, common genetic variation can only have a modest role in predisposition to the partial epilepsies when considered across syndromes in Europeans. The genetic architecture of the partial epilepsies is likely to be very complex, reflecting genotypic and phenotypic heterogeneity. Larger meta-analyses are required to identify variants of smaller effect sizes (odds ratio<1.3) or syndrome-specific variants. Further, our results suggest research efforts should also be directed towards identifying the multiple rare variants likely to account for at least part of the heritability of the partial epilepsies. Data emerging from genome-wide association-studies will be valuable during the next serious challenge of interpreting all the genetic variation emerging from whole-genome sequencing studies.
Hayden, Lystra P; Cho, Michael H; McDonald, Merry-Lynn N; Crapo, James D; Beaty, Terri H; Silverman, Edwin K; Hersh, Craig P
Previous studies have indicated that in adult smokers, a history of childhood pneumonia is associated with reduced lung function and chronic obstructive pulmonary disease. There have been few previous investigations using genome-wide association studies to investigate genetic predisposition to pneumonia. This study aims to identify the genetic variants associated with the development of pneumonia during childhood and over the course of the lifetime. Study subjects included current and former smokers with and without chronic obstructive pulmonary disease participating in the COPDGene Study. Pneumonia was defined by subject self-report, with childhood pneumonia categorized as having the first episode at pneumonia (843 cases, 9,091 control subjects) and lifetime pneumonia (3,766 cases, 5,659 control subjects) were performed separately in non-Hispanic whites and African Americans. Non-Hispanic white and African American populations were combined in the meta-analysis. Top genetic variants from childhood pneumonia were assessed in network analysis. No single-nucleotide polymorphisms reached genome-wide significance, although we identified potential regions of interest. In the childhood pneumonia analysis, this included variants in NGR1 (P = 6.3 × 10 -8 ), PAK6 (P = 3.3 × 10 -7 ), and near MATN1 (P = 2.8 × 10 -7 ). In the lifetime pneumonia analysis, this included variants in LOC339862 (P = 8.7 × 10 -7 ), RAPGEF2 (P = 8.4 × 10 -7 ), PHACTR1 (P = 6.1 × 10 -7 ), near PRR27 (P = 4.3 × 10 -7 ), and near MCPH1 (P = 2.7 × 10 -7 ). Network analysis of the genes associated with childhood pneumonia included top networks related to development, blood vessel morphogenesis, muscle contraction, WNT signaling, DNA damage, apoptosis, inflammation, and immune response (P ≤ 0.05). We have identified genes potentially associated with the risk of pneumonia. Further research will be required to confirm these
Johnson Andrew D
Full Text Available Abstract Background The number of genome-wide association studies (GWAS is growing rapidly leading to the discovery and replication of many new disease loci. Combining results from multiple GWAS datasets may potentially strengthen previous conclusions and suggest new disease loci, pathways or pleiotropic genes. However, no database or centralized resource currently exists that contains anywhere near the full scope of GWAS results. Methods We collected available results from 118 GWAS articles into a database of 56,411 significant SNP-phenotype associations and accompanying information, making this database freely available here. In doing so, we met and describe here a number of challenges to creating an open access database of GWAS results. Through preliminary analyses and characterization of available GWAS, we demonstrate the potential to gain new insights by querying a database across GWAS. Results Using a genomic bin-based density analysis to search for highly associated regions of the genome, positive control loci (e.g., MHC loci were detected with high sensitivity. Likewise, an analysis of highly repeated SNPs across GWAS identified replicated loci (e.g., APOE, LPL. At the same time we identified novel, highly suggestive loci for a variety of traits that did not meet genome-wide significant thresholds in prior analyses, in some cases with strong support from the primary medical genetics literature (SLC16A7, CSMD1, OAS1, suggesting these genes merit further study. Additional adjustment for linkage disequilibrium within most regions with a high density of GWAS associations did not materially alter our findings. Having a centralized database with standardized gene annotation also allowed us to examine the representation of functional gene categories (gene ontologies containing one or more associations among top GWAS results. Genes relating to cell adhesion functions were highly over-represented among significant associations (p -14, a finding
Zhang, Xiang-Yuan; He, Chao; Ye, Bing-Yu; Xie, De-Jian; Shi, Ming-Lei; Zhang, Yan; Shen, Wen-Long; Li, Ping; Zhao, Zhi-Hu
Highest-throughput chromosome conformation capture (Hi-C) is one of the key assays for genome- wide chromatin interaction studies. It is a time-consuming process that involves many steps and many different kinds of reagents, consumables, and equipments. At present, the reproducibility is unsatisfactory. By optimizing the key steps of the Hi-C experiment, such as crosslinking, pretreatment of digestion, inactivation of restriction enzyme, and in situ ligation etc., we established a robust Hi-C procedure and prepared two biological replicates of Hi-C libraries from the GM12878 cells. After preliminary quality control by Sanger sequencing, the two replicates were high-throughput sequenced. The bioinformatics analysis of the raw sequencing data revealed the mapping-ability and pair-mate rate of the raw data were around 90% and 72%, respectively. Additionally, after removal of self-circular ligations and dangling-end products, more than 96% of the valid pairs were reached. Genome-wide interactome profiling shows clear topological associated domains (TADs), which is consistent with previous reports. Further correlation analysis showed that the two biological replicates strongly correlate with each other in terms of both bin coverage and all bin pairs. All these results indicated that the optimized Hi-C procedure is robust and stable, which will be very helpful for the wide applications of the Hi-C assay.
Down Thomas A
Full Text Available Abstract Background DNA methylation can regulate gene expression by modulating the interaction between DNA and proteins or protein complexes. Conserved consensus motifs exist across the human genome ("predicted transcription factor binding sites": "predicted TFBS" but the large majority of these are proven by chromatin immunoprecipitation and high throughput sequencing (ChIP-seq not to be biological transcription factor binding sites ("empirical TFBS". We hypothesize that DNA methylation at conserved consensus motifs prevents promiscuous or disorderly transcription factor binding. Results Using genome-wide methylation maps of the human heart and sperm, we found that all conserved consensus motifs as well as the subset of those that reside outside CpG islands have an aggregate profile of hyper-methylation. In contrast, empirical TFBS with conserved consensus motifs have a profile of hypo-methylation. 40% of empirical TFBS with conserved consensus motifs resided in CpG islands whereas only 7% of all conserved consensus motifs were in CpG islands. Finally we further identified a minority subset of TF whose profiles are either hypo-methylated or neutral at their respective conserved consensus motifs implicating that these TF may be responsible for establishing or maintaining an un-methylated DNA state, or whose binding is not regulated by DNA methylation. Conclusions Our analysis supports the hypothesis that at least for a subset of TF, empirical binding to conserved consensus motifs genome-wide may be controlled by DNA methylation.
Reyes, Vincent C; Li, Minghua; Hoek, Eric M V; Mahendra, Shaily; Damoiseaux, Robert
The use of engineered nanomaterials (eNM) in consumer and industrial products is increasing exponentially. Our ability to rapidly assess their potential effects on human and environmental health is limited by our understanding of nanomediated toxicity. High-throughput screening (HTS) enables the investigation of nanomediated toxicity on a genome-wide level, thus uncovering their novel mechanisms and paradigms. Herein, we investigate the toxicity of zinc-containing nanomaterials (Zn-eNMs) using a time-resolved HTS methodology in an arrayed Escherichia coli genome-wide knockout (KO) library. The library was screened against nanoscale zerovalent zinc (nZn), nanoscale zinc oxide (nZnO), and zinc chloride (ZnCl(2)) salt as reference. Through sequential screening over 24 h, our method identified 173 sensitive clones from diverse biological pathways, which fell into two general groups: early and late responders. The overlap between these groups was small. Our results suggest that bacterial toxicity mechanisms change from pathways related to general metabolic function, transport, signaling, and metal ion homeostasis to membrane synthesis pathways over time. While all zinc sources shared pathways relating to membrane damage and metal ion homeostasis, Zn-eNMs and ZnCl(2) displayed differences in their sensitivity profiles. For example, ZnCl(2) and nZnO elicited unique responses in pathways related to two-component signaling and monosaccharide biosynthesis, respectively. Single isolated measurements, such as MIC or IC(50), are inadequate, and time-resolved approaches utilizing genome-wide assays are therefore needed to capture this crucial dimension and illuminate the dynamic interplay at the nano-bio interface.
Full Text Available Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed.We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality and EDAR (associated with hair thickness were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9 were associated with pre-weaning gain in our previous genome-wide association study.Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.
Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin
Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed. We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study. Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.
Full Text Available The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000-1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs. We estimate that the Roma harbor about 80% West Eurasian ancestry-derived from a combination of European and South Asian sources-and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe.
Bertram, Lars; Tanzi, Rudolph E
Genome-wide association studies (GWAS) have gained considerable momentum over the last couple of years for the identification of novel complex disease genes. In the field of Alzheimer's disease (AD), there are currently eight published and two provisionally reported GWAS, highlighting over two dozen novel potential susceptibility loci beyond the well-established APOE association. On the basis of the data available at the time of this writing, the most compelling novel GWAS signal has been observed in GAB2 (GRB2-associated binding protein 2), followed by less consistently replicated signals in galanin-like peptide (GALP), piggyBac transposable element derived 1 (PGBD1), tyrosine kinase, non-receptor 1 (TNK1). Furthermore, consistent replication has been recently announced for CLU (clusterin, also known as apolipoprotein J). Finally, there are at least three replicated loci in hitherto uncharacterized genomic intervals on chromosomes 14q32.13, 14q31.2 and 6q24.1 likely implicating the existence of novel AD genes in these regions. In this review, we will discuss the characteristics and potential relevance to pathogenesis of the outcomes of all currently available GWAS in AD. A particular emphasis will be laid on findings with independent data in favor of the original association.
Full Text Available Selenium is an essential trace element and circulating selenium concentrations have been associated with a wide range of diseases. Candidate gene studies suggest that circulating selenium concentrations may be impacted by genetic variation; however, no study has comprehensively investigated this hypothesis. Therefore, we conducted a two-stage genome-wide association study to identify genetic variants associated with serum selenium concentrations in 1203 European descents from two cohorts: the Prostate, Lung, Colorectal, and Ovarian (PLCO Cancer Screening and the Women’s Health Initiative (WHI. We tested association between 2,474,333 single nucleotide polymorphisms (SNPs and serum selenium concentrations using linear regression models. In the first stage (PLCO 41 SNPs clustered in 15 regions had p < 1 × 10−5. None of these 41 SNPs reached the significant threshold (p = 0.05/15 regions = 0.003 in the second stage (WHI. Three SNPs had p < 0.05 in the second stage (rs1395479 and rs1506807 in 4q34.3/AGA-NEIL3; and rs891684 in 17q24.3/SLC39A11 and had p between 2.62 × 10−7 and 4.04 × 10−7 in the combined analysis (PLCO + WHI. Additional studies are needed to replicate these findings. Identification of genetic variation that impacts selenium concentrations may contribute to a better understanding of which genes regulate circulating selenium concentrations.
Full Text Available Abstract Background With the availability of large-scale genome-wide association study (GWAS data, choosing an optimal set of SNPs for disease susceptibility prediction is a challenging task. This study aimed to use single nucleotide polymorphisms (SNPs to predict psoriasis from searching GWAS data. Methods Totally we had 2,798 samples and 451,724 SNPs. Process for searching a set of SNPs to predict susceptibility for psoriasis consisted of two steps. The first one was to search top 1,000 SNPs with high accuracy for prediction of psoriasis from GWAS dataset. The second one was to search for an optimal SNP subset for predicting psoriasis. The sequential information bottleneck (sIB method was compared with classical linear discriminant analysis(LDA for classification performance. Results The best test harmonic mean of sensitivity and specificity for predicting psoriasis by sIB was 0.674(95% CI: 0.650-0.698, while only 0.520(95% CI: 0.472-0.524 was reported for predicting disease by LDA. Our results indicate that the new classifier sIB performs better than LDA in the study. Conclusions The fact that a small set of SNPs can predict disease status with average accuracy of 68% makes it possible to use SNP data for psoriasis prediction.
Full Text Available Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr. We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set.
Xavier, Alencar; Muir, William M; Rainey, Katy Martin
Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. Copyright © 2016 Xavie et al.
Ripke, Stephan; Wray, Naomi R; Lewis, Cathryn M; Hamilton, Steven P; Weissman, Myrna M; Breen, Gerome; Byrne, Enda M; Blackwood, Douglas H R; Boomsma, Dorret I; Cichon, Sven; Heath, Andrew C; Holsboer, Florian; Lucae, Susanne; Madden, Pamela A F; Martin, Nicholas G; McGuffin, Peter; Muglia, Pierandrea; Noethen, Markus M; Penninx, Brenda P; Pergadia, Michele L; Potash, James B; Rietschel, Marcella; Lin, Danyu; Müller-Myhsok, Bertram; Shi, Jianxin; Steinberg, Stacy; Grabe, Hans J; Lichtenstein, Paul; Magnusson, Patrik; Perlis, Roy H; Preisig, Martin; Smoller, Jordan W; Stefansson, Kari; Uher, Rudolf; Kutalik, Zoltan; Tansey, Katherine E; Teumer, Alexander; Viktorin, Alexander; Barnes, Michael R; Bettecken, Thomas; Binder, Elisabeth B; Breuer, René; Castro, Victor M; Churchill, Susanne E; Coryell, William H; Craddock, Nick; Craig, Ian W; Czamara, Darina; De Geus, Eco J; Degenhardt, Franziska; Farmer, Anne E; Fava, Maurizio; Frank, Josef; Gainer, Vivian S; Gallagher, Patience J; Gordon, Scott D; Goryachev, Sergey; Gross, Magdalena; Guipponi, Michel; Henders, Anjali K; Herms, Stefan; Hickie, Ian B; Hoefels, Susanne; Hoogendijk, Witte; Hottenga, Jouke Jan; Iosifescu, Dan V; Ising, Marcus; Jones, Ian; Jones, Lisa; Jung-Ying, Tzeng; Knowles, James A; Kohane, Isaac S; Kohli, Martin A; Korszun, Ania; Landen, Mikael; Lawson, William B; Lewis, Glyn; Macintyre, Donald; Maier, Wolfgang; Mattheisen, Manuel; McGrath, Patrick J; McIntosh, Andrew; McLean, Alan; Middeldorp, Christel M; Middleton, Lefkos; Montgomery, Grant M; Murphy, Shawn N; Nauck, Matthias; Nolen, Willem A; Nyholt, Dale R; O'Donovan, Michael; Oskarsson, Högni; Pedersen, Nancy; Scheftner, William A; Schulz, Andrea; Schulze, Thomas G; Shyn, Stanley I; Sigurdsson, Engilbert; Slager, Susan L; Smit, Johannes H; Stefansson, Hreinn; Steffens, Michael; Thorgeirsson, Thorgeir; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; van den Oord, Edwin J C G; Van Grootheest, Gerard; Völzke, Henry; Weilburg, Jeffrey B; Willemsen, Gonneke; Zitman, Frans G; Neale, Benjamin; Daly, Mark; Levinson, Douglas F; Sullivan, Patrick F
Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.
Novel recurrent chromosomal aberrations detected in clonal plasma cells of light chain amyloidosis patients show potential adverse prognostic effect: first results from a genome-wide copy number array analysis.
Granzow, Martin; Hegenbart, Ute; Hinderhofer, Katrin; Hose, Dirk; Seckinger, Anja; Bochtler, Tilmann; Hemminki, Kari; Goldschmidt, Hartmut; Schönland, Stefan O; Jauch, Anna
Immunoglobulin light chain (AL) amyloidosis is a rare plasma cell dyscrasia characterized by the deposition of abnormal amyloid fibrils in multiple organs, thus impairing their function. In the largest cohort studied up to now of 118 CD138-purified plasma cell samples from previously untreated immunoglobulin light chain amyloidosis patients, we assessed in parallel copy number alterations using high-density copy number arrays and interphase fluorescence in situ hybridization (iFISH). We used fluorescence in situ hybridization probes for the IgH translocations t(11;14), t(4;14), and t(14;16) or any other IgH rearrangement as well as numerical aberrations of the chromosome loci 1q21, 8p21, 5p15/5q35, 11q22.3 or 11q23, 13q14, 15q22, 17p13, and 19q13. Recurrent gains included chromosomes 1q (36%), 9 (24%), 11q (24%), as well as 19 (15%). Recurrent losses affected chromosome 13 (29% monosomy) and partial losses of 14q (19%), 16q (14%) and 13q (12%), respectively. In 88% of patients with translocation t(11;14), the hallmark chromosomal aberration in AL amyloidosis, a concomitant gain of 11q22.3/11q23 detected by iFISH was part of the unbalanced translocation der(14)t(11;14)(q13;q32) with the breakpoint in the CCND1/MYEOV gene region. Partial loss of chromosome regions 14q and 16q were significantly associated to gain 1q. Gain 1q21 detected by iFISH almost always resulted from a gain of the long arm of chromosome 1 and not from trisomy 1, whereas deletions on chromosome 1p were rarely found. Overall and event-free survival analysis found a potential adverse prognostic effect of concomitant gain 1q and deletion 14q as well as of deletion 1p. In conclusion, in the first whole genome report of clonal plasma cells in AL amyloidosis, novel aberrations and hitherto unknown potential adverse prognostic effects were uncovered. Copyright© 2017 Ferrata Storti Foundation.
Vannier, Jean-Baptiste; Sandhu, Sumit; Petalcorin, Mark I R; Wu, Xiaoli; Nabi, Zinnatun; Ding, Hao; Boulton, Simon J
Regulator of telomere length 1 (RTEL1) is an essential DNA helicase that disassembles telomere loops (T loops) and suppresses telomere fragility to maintain the integrity of chromosome ends. We established that RTEL1 also associates with the replisome through binding to proliferating cell nuclear antigen (PCNA). Mouse cells disrupted for the RTEL1-PCNA interaction (PIP mutant) exhibited accelerated senescence, replication fork instability, reduced replication fork extension rates, and increased origin usage. Although T-loop disassembly at telomeres was unaffected in the mutant cells, telomere replication was compromised, leading to fragile sites at telomeres. RTEL1-PIP mutant mice were viable, but loss of the RTEL1-PCNA interaction accelerated the onset of tumorigenesis in p53-deficient mice. We propose that RTEL1 plays a critical role in both telomere and genome-wide replication, which is crucial for genetic stability and tumor avoidance.
Mechelli, Rosella; Umeton, Renato; Policano, Claudia
of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge......, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate...... immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated...
Armour, J AL; Davison, A; McManus, I C
Handedness is a human behavioural phenotype that appears to be congenital, and is often assumed to be inherited, but for which the developmental origin and underlying causation(s) have been elusive. Models of the genetic basis of variation in handedness have been proposed that fit different features of the observed resemblance between relatives, but none has been decisively tested or a corresponding causative locus identified. In this study, we applied data from well-characterised individuals studied at the London Twin Research Unit. Analysis of genome-wide SNP data from 3940 twins failed to identify any locus associated with handedness at a genome-wide level of significance. The most straightforward interpretation of our analyses is that they exclude the simplest formulations of the ‘right-shift' model of Annett and the ‘dextral/chance' model of McManus, although more complex modifications of those models are still compatible with our observations. For polygenic effects, our study is inadequately powered to reliably detect alleles with effect sizes corresponding to an odds ratio of 1.2, but should have good power to detect effects at an odds ratio of 2 or more. PMID:24065183
Christopher Y Park
Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.
Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.
Huang, Yen-Tsung; Hsu, Thomas; Christiani, David C
The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X (2) distributions that can be obtained using permutation with scaled X (2) approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (number data, and causal mechanisms of the five pathways require further study.
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
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
Renton, Alan E.; Pliner, Hannah A.; Provenzano, Carlo; Evoli, Amelia; Ricciardi, Roberta; Nalls, Michael A.; Marangi, Giuseppe; Abramzon, Yevgeniya; Arepalli, Sampath; Chong, Sean; Hernandez, Dena G.; Johnson, Janel O.; Bartoccioni, Emanuela; Scuderi, Flavia; Maestri, Michelangelo; Raphael Gibbs, J.; Errichiello, Edoardo; Chiò, Adriano; Restagno, Gabriella; Sabatelli, Mario; Macek, Mark; Scholz, Sonja W.; Corse, Andrea; Chaudhry, Vinay; Benatar, Michael; Barohn, Richard J.; McVey, April; Pasnoor, Mamatha; Dimachkie, Mazen M.; Rowin, Julie; Kissel, John; Freimer, Miriam; Kaminski, Henry J.; Sanders, Donald B.; Lipscomb, Bernadette; Massey, Janice M.; Chopra, Manisha; Howard, James F.; Koopman, Wilma J.; Nicolle, Michael W.; Pascuzzi, Robert M.; Pestronk, Alan; Wulf, Charlie; Florence, Julaine; Blackmore, Derrick; Soloway, Aimee; Siddiqi, Zaeem; Muppidi, Srikanth; Wolfe, Gil; Richman, David; Mezei, Michelle M.; Jiwa, Theresa; Oger, Joel; Drachman, Daniel B.; Traynor, Bryan J.
IMPORTANCE Myasthenia gravis is a chronic, autoimmune, neuromuscular disease characterized by fluctuating weakness of voluntary muscle groups. Although genetic factors are known to play a role in this neuroimmunological condition, the genetic etiology underlying myasthenia gravis is not well understood. OBJECTIVE To identify genetic variants that alter susceptibility to myasthenia gravis, we performed a genome-wide association study. DESIGN, SETTING, AND PARTICIPANTS DNA was obtained from 1032 white individuals from North America diagnosed as having acetylcholine receptor antibody–positive myasthenia gravis and 1998 race/ethnicity-matched control individuals from January 2010 to January 2011. These samples were genotyped on Illumina OmniExpress single-nucleotide polymorphism arrays. An independent cohort of 423 Italian cases and 467 Italian control individuals were used for replication. MAIN OUTCOMES AND MEASURES We calculated P values for association between 8114394 genotyped and imputed variants across the genome and risk for developing myasthenia gravis using logistic regression modeling. A threshold P value of 5.0 × 10−8 was set for genome-wide significance after Bonferroni correction for multiple testing. RESULTS In the over all case-control cohort, we identified association signals at CTLA4 (rs231770; P = 3.98 × 10−8; odds ratio, 1.37; 95% CI, 1.25–1.49), HLA-DQA1 (rs9271871; P = 1.08 × 10−8; odds ratio, 2.31; 95% CI, 2.02 – 2.60), and TNFRSF11A (rs4263037; P = 1.60 × 10−9; odds ratio, 1.41; 95% CI, 1.29–1.53). These findings replicated for CTLA4 and HLA-DQA1 in an independent cohort of Italian cases and control individuals. Further analysis revealed distinct, but overlapping, disease-associated loci for early- and late-onset forms of myasthenia gravis. In the late-onset cases, we identified 2 association peaks: one was located in TNFRSF11A (rs4263037; P = 1.32 × 10−12; odds ratio, 1.56; 95% CI, 1.44–1.68) and the other was detected
Full Text Available Abstract Background One of the consequences of the rapid and widespread adoption of high-throughput experimental technologies is an exponential increase of the amount of data produced by genome-wide experiments. Researchers increasingly need to handle very large volumes of heterogeneous data, including both the data generated by their own experiments and the data retrieved from publicly available repositories of genomic knowledge. Integration, exploration, manipulation and interpretation of data and information therefore need to become as automated as possible, since their scale and breadth are, in general, beyond the limits of what individual researchers and the basic data management tools in normal use can handle. This paper describes Genephony, a tool we are developing to address these challenges. Results We describe how Genephony can be used to manage large datesets of genomic information, integrating them with existing knowledge repositories. We illustrate its functionalities with an example of a complex annotation task, in which a set of SNPs coming from a genotyping experiment is annotated with genes known to be associated to a phenotype of interest. We show how, thanks to the modular architecture of Genephony and its user-friendly interface, this task can be performed in a few simple steps. Conclusion Genephony is an online tool for the manipulation of large datasets of genomic information. It can be used as a browser for genomic data, as a high-throughput annotation tool, and as a knowledge discovery tool. It is designed to be easy to use, flexible and extensible. Its knowledge management engine provides fine-grained control over individual data elements, as well as efficient operations on large datasets.
Full Text Available Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p<0.01 and 473 SNPs of p<0.05 that located in previously reported linkage regions. The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila-like 2] gene located on 9p21.3 (p = 0.00087. In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026. The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.
Akkelies E Dijkstra
Full Text Available Chronic mucus hypersecretion (CMH is associated with an increased frequency of respiratory infections, excess lung function decline, and increased hospitalisation and mortality rates in the general population. It is associated with smoking, but it is unknown why only a minority of smokers develops CMH. A plausible explanation for this phenomenon is a predisposing genetic constitution. Therefore, we performed a genome wide association (GWA study of CMH in Caucasian populations.GWA analysis was performed in the NELSON-study using the Illumina 610 array, followed by replication and meta-analysis in 11 additional cohorts. In total 2,704 subjects with, and 7,624 subjects without CMH were included, all current or former heavy smokers (≥20 pack-years. Additional studies were performed to test the functional relevance of the most significant single nucleotide polymorphism (SNP.A strong association with CMH, consistent across all cohorts, was observed with rs6577641 (p = 4.25×10(-6, OR = 1.17, located in intron 9 of the special AT-rich sequence-binding protein 1 locus (SATB1 on chromosome 3. The risk allele (G was associated with higher mRNA expression of SATB1 (4.3×10(-9 in lung tissue. Presence of CMH was associated with increased SATB1 mRNA expression in bronchial biopsies from COPD patients. SATB1 expression was induced during differentiation of primary human bronchial epithelial cells in culture.Our findings, that SNP rs6577641 is associated with CMH in multiple cohorts and is a cis-eQTL for SATB1, together with our additional observation that SATB1 expression increases during epithelial differentiation provide suggestive evidence that SATB1 is a gene that affects CMH.
Barbara E Stranger
Full Text Available The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis- to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.
Full Text Available The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis- to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.
Katharine J Sepp
Full Text Available While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new
Manning, Alisa K; Hivert, Marie-France; Scott, Robert A
pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci...... associated with fasting insulin at P triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci...
Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H
Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.
Full Text Available DNA methylation plays a central role in regulating many aspects of growth and development in mammals through regulating gene expression. The development of next generation sequencing technologies have paved the way for genome-wide, high resolution analysis of DNA methylation landscapes using methodology known as reduced representation bisulfite sequencing (RRBS. While RRBS has proven to be effective in understanding DNA methylation landscapes in humans, mice, and rats, to date, few studies have utilised this powerful method for investigating DNA methylation in agricultural animals. Here we describe the utilisation of RRBS to investigate DNA methylation in sheep Longissimus dorsi muscles. RRBS analysis of ∼1% of the genome from Longissimus dorsi muscles provided data of suitably high precision and accuracy for DNA methylation analysis, at all levels of resolution from genome-wide to individual nucleotides. Combining RRBS data with mRNAseq data allowed the sheep Longissimus dorsi muscle methylome to be compared with methylomes from other species. While some species differences were identified, many similarities were observed between DNA methylation patterns in sheep and other more commonly studied species. The RRBS data presented here highlights the complexity of epigenetic regulation of genes. However, the similarities observed across species are promising, in that knowledge gained from epigenetic studies in human and mice may be applied, with caution, to agricultural species. The ability to accurately measure DNA methylation in agricultural animals will contribute an additional layer of information to the genetic analyses currently being used to maximise production gains in these species.
Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T
Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.
Katherine W Jordan
Full Text Available Reactive oxygen species (ROS are a common byproduct of mitochondrial energy metabolism, and can also be induced by exogenous sources, including UV light, radiation, and environmental toxins. ROS generation is essential for maintaining homeostasis by triggering cellular signaling pathways and host defense mechanisms. However, an imbalance of ROS induces oxidative stress and cellular death and is associated with human disease, including age-related locomotor impairment. To identify genes affecting sensitivity and resistance to ROS-induced locomotor decline, we assessed locomotion of aged flies of the sequenced, wild-derived lines from the Drosophila melanogaster Genetics Reference Panel on standard medium and following chronic exposure to medium supplemented with 3 mM menadione sodium bisulfite (MSB. We found substantial genetic variation in sensitivity to oxidative stress with respect to locomotor phenotypes. We performed genome-wide association analyses to identify candidate genes associated with variation in sensitivity to ROS-induced decline in locomotor performance, and confirmed the effects for 13 of 16 mutations tested in these candidate genes. Candidate genes associated with variation in sensitivity to MSB-induced oxidative stress form networks of genes involved in neural development, immunity, and signal transduction. Many of these genes have human orthologs, highlighting the utility of genome-wide association in Drosophila for studying complex human disease.
Perfetti, Alessandra; Greco, Simona; Fasanaro, Pasquale; Bugiardini, Enrico; Cardani, Rosanna; Garcia-Manteiga, Jose M; Manteiga, Jose M Garcia; Riba, Michela; Cittaro, Davide; Stupka, Elia; Meola, Giovanni; Martelli, Fabio
Myotonic dystrophy type 2 (DM2) is a genetic, autosomal dominant disease due to expansion of tetraplet (CCTG) repetitions in the first intron of the ZNF9/CNBP gene. DM2 is a multisystemic disorder affecting the skeletal muscle, the heart, the eye and the endocrine system. According to the proposed pathological mechanism, the expanded tetraplets have an RNA toxic effect, disrupting the splicing of many mRNAs. Thus, the identification of aberrantly spliced transcripts is instrumental for our understanding of the molecular mechanisms underpinning the disease. The aim of this study was the identification of new aberrant alternative splicing events in DM2 patients. By genome wide analysis of 10 DM2 patients and 10 controls (CTR), we identified 273 alternative spliced exons in 218 genes. While many aberrant splicing events were already identified in the past, most were new. A subset of these events was validated by qPCR assays in 19 DM2 and 15 CTR subjects. To gain insight into the molecular pathways involving the identified aberrantly spliced genes, we performed a bioinformatics analysis with Ingenuity system. This analysis indicated a deregulation of development, cell survival, metabolism, calcium signaling and contractility. In conclusion, our genome wide analysis provided a database of aberrant splicing events in the skeletal muscle of DM2 patients. The affected genes are involved in numerous pathways and networks important for muscle physio-pathology, suggesting that the identified variants may contribute to DM2 pathogenesis.
Welderufael, B. G.; Løvendahl, Peter; de Koning, Dirk-Jan; Janss, Lucas L. G.; Fikse, W. F.
Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to – but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2) and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3) were suggested as possible causal genes for susceptibility to – and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to – and recoverability from mastitis. PMID:29755506
Covelo-Soto, L; Leunda, P M; Pérez-Figueroa, A; Morán, P
The induction of triploidization in fish is a very common practice in aquaculture. Although triploidization has been applied successfully in many salmonid species, little is known about the epigenetic mechanisms implicated in the maintenance of the normal functions of the new polyploid genome. By means of methylation-sensitive amplified polymorphism (MSAP) techniques, genome-wide methylation changes associated with triploidization were assessed in DNA samples obtained from diploid and triploid siblings of brown trout (Salmo trutta). Simple comparative body measurements showed that the triploid trout used in the study were statistically bigger, however, not heavier than their diploid counterparts. The statistical analysis of the MSAP data showed no significant differences between diploid and triploid brown trout in respect to brain, gill, heart, liver, kidney or muscle samples. Nonetheless, local analysis pointed to the possibility of differences in connection with concrete loci. This is the first study that has investigated DNA methylation alterations associated with triploidization in brown trout. Our results set the basis for new studies to be undertaken and provide a new approach concerning triploidization effects of the salmonid genome while also contributing to the better understanding of the genome-wide methylation processes. © 2015 Stichting International Foundation for Animal Genetics.
Birch, Patricia; Adam, S; Bansback, N; Coe, R R; Hicklin, J; Lehman, A; Li, K C; Friedman, J M
We describe the rationale, development, and usability testing for an integrated e-learning tool and decision aid for parents facing decisions about genome-wide sequencing (GWS) for their children with a suspected genetic condition. The online tool, DECIDE, is designed to provide decision-support and to promote high quality decisions about undergoing GWS with or without return of optional incidental finding results. DECIDE works by integrating educational material with decision aids. Users may tailor their learning by controlling both the amount of information and its format - text and diagrams and/or short videos. The decision aid guides users to weigh the importance of various relevant factors in their own lives and circumstances. After considering the pros and cons of GWS and return of incidental findings, DECIDE summarizes the user's responses and apparent preferred choices. In a usability study of 16 parents who had already chosen GWS after conventional genetic counselling, all participants found DECIDE to be helpful. Many would have been satisfied to use it alone to guide their GWS decisions, but most would prefer to have the option of consulting a health care professional as well to aid their decision. Further testing is necessary to establish the effectiveness of using DECIDE as an adjunct to or instead of conventional pre-test genetic counselling for clinical genome-wide sequencing.
Wang, Richard J; Payseur, Bret A
Recombination rate is a heritable quantitative trait that evolves despite the fundamentally conserved role that recombination plays in meiosis. Differences in recombination rate can alter the landscape of the genome and the genetic diversity of populations. Yet our understanding of the genetic basis of recombination rate evolution in nature remains limited. We used wild house mice ( Mus musculus domesticus ) from Gough Island (GI), which diverged recently from their mainland counterparts, to characterize the genetics of recombination rate evolution. We quantified genome-wide autosomal recombination rates by immunofluorescence cytology in spermatocytes from 240 F 2 males generated from intercrosses between GI-derived mice and the wild-derived inbred strain WSB/EiJ. We identified four quantitative trait loci (QTL) responsible for inter-F 2 variation in this trait, the strongest of which had effects that opposed the direction of the parental trait differences. Candidate genes and mutations for these QTL were identified by overlapping the detected intervals with whole-genome sequencing data and publicly available transcriptomic profiles from spermatocytes. Combined with existing studies, our findings suggest that genome-wide recombination rate divergence is not directional and its evolution within and between subspecies proceeds from distinct genetic loci. Copyright © 2017 by the Genetics Society of America.
Zhang, Hao; Shaffer, John R.; Hansen, Thomas; Esserlind, Ann-Louise; Boyd, Heather A.; Nohr, Ellen A.; Timpson, Nicholas J.; Fatemifar, Ghazaleh; Paternoster, Lavinia; Evans, David M.; Weyant, Robert J.; Levy, Steven M.; Lathrop, Mark; Smith, George Davey; Murray, Jeffrey C.; Olesen, Jes; Werge, Thomas; Marazita, Mary L.; Sørensen, Thorkild I. A.; Melbye, Mads
The sequence and timing of permanent tooth eruption is thought to be highly heritable and can have important implications for the risk of malocclusion, crowding, and periodontal disease. We conducted a genome-wide association study of number of permanent teeth erupted between age 6 and 14 years, analyzed as age-adjusted standard deviation score averaged over multiple time points, based on childhood records for 5,104 women from the Danish National Birth Cohort. Four loci showed association at Peruption and were also known to influence height and breast cancer, respectively. The two other loci pointed to genomic regions without any previous significant genome-wide association study results. The intronic SNP rs7924176 in ADK could be linked to gene expression in monocytes. The combined effect of the four genetic variants was most pronounced between age 10 and 12 years, where children with 6 to 8 delayed tooth eruption alleles had on average 3.5 (95% confidence interval: 2.9–4.1) fewer permanent teeth than children with 0 or 1 of these alleles. PMID:21931568
Full Text Available The success of genome-wide association studies (GWASs has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR, least absolute shrinkage and selection operator (LASSO, and Elastic-Net (EN. We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.
Gao, Yangchun; Li, Shiguo; Zhan, Aibin
Invasive species cause huge damages to ecology, environment and economy globally. The comprehensive understanding of invasion mechanisms, particularly genetic bases of micro-evolutionary processes responsible for invasion success, is essential for reducing potential damages caused by invasive species. The golden star tunicate, Botryllus schlosseri, has become a model species in invasion biology, mainly owing to its high invasiveness nature and small well-sequenced genome. However, the genome-wide genetic markers have not been well developed in this highly invasive species, thus limiting the comprehensive understanding of genetic mechanisms of invasion success. Using restriction site-associated DNA (RAD) tag sequencing, here we developed a high-quality resource of 14,119 out of 158,821 SNPs for B. schlosseri. These SNPs were relatively evenly distributed at each chromosome. SNP annotations showed that the majority of SNPs (63.20%) were located at intergenic regions, and 21.51% and 14.58% were located at introns and exons, respectively. In addition, the potential use of the developed SNPs for population genomics studies was primarily assessed, such as the estimate of observed heterozygosity (H O ), expected heterozygosity (H E ), nucleotide diversity (π), Wright's inbreeding coefficient (F IS ) and effective population size (Ne). Our developed SNP resource would provide future studies the genome-wide genetic markers for genetic and genomic investigations, such as genetic bases of micro-evolutionary processes responsible for invasion success.
Full Text Available Abstract Background Temperature adaptation is one of the most important determinants of distribution and population size of organisms in nature. Recently, quantitative trait loci (QTL mapping and gene expression profiling approaches have been used for detecting candidate genes for heat resistance. However, the resolution of QTL mapping is not high enough to examine the individual effects of various genes in each QTL. Heat stress-responsive genes, characterized by gene expression profiling studies, are not necessarily responsible for heat resistance. Some of these genes may be regulated in association with the heat stress response of other genes. Results To evaluate which heat-responsive genes are potential candidates for heat resistance with higher resolution than previous QTL mapping studies, we performed genome-wide deficiency screen for QTL for heat resistance. We screened 439 isogenic deficiency strains from the DrosDel project, covering 65.6% of the Drosophila melanogaster genome in order to map QTL for thermal resistance. As a result, we found 19 QTL for heat resistance, including 3 novel QTL outside the QTL found in previous studies. Conclusion The QTL found in this study encompassed 19 heat-responsive genes found in the previous gene expression profiling studies, suggesting that they were strong candidates for heat resistance. This result provides new insights into the genetic architecture of heat resistance. It also emphasizes the advantages of genome-wide deficiency screen using isogenic deficiency libraries.
Full Text Available Abstract Background A recent genome wide association study in 1017 African Americans identified several single nucleotide polymorphisms that reached genome-wide significance for systolic blood pressure. We attempted to replicate these findings in an independent sample of 2474 unrelated African Americans in the Milwaukee metropolitan area; 53% were women and 47% were hypertensives. Methods We evaluated sixteen top associated SNPs from the above genome wide association study for hypertension as a binary trait or blood pressure as a continuous trait. In addition, we evaluated eight single nucleotide polymorphisms located in two genes (STK-39 and CDH-13 found to be associated with systolic and diastolic blood pressures by other genome wide association studies in European and Amish populations. TaqMan MGB-based chemistry with fluorescent probes was used for genotyping. We had an adequate sample size (80% power to detect an effect size of 1.2-2.0 for all the single nucleotide polymorphisms for hypertension as a binary trait, and 1% variance in blood pressure as a continuous trait. Quantitative trait analyses were performed both by excluding and also by including subjects on anti-hypertensive therapy (after adjustments were made for anti-hypertensive medications. Results For all 24 SNPs, no statistically significant differences were noted in the minor allele frequencies between cases and controls. One SNP (rs2146204 showed borderline association (p = 0.006 with hypertension status using recessive model and systolic blood pressure (p = 0.02, but was not significant after adjusting for multiple comparisons. In quantitative trait analyses, among normotensives only, rs12748299 was associated with SBP (p = 0.002. In addition, several nominally significant associations were noted with SBP and DBP among normotensives but none were statistically significant. Conclusions This study highlights the importance of replication to confirm the validity of genome wide
Hwang, Eun-Young; Song, Qijian; Jia, Gaofeng; Specht, James E; Hyten, David L; Costa, Jose; Cregan, Perry B
Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil. This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise
Migault, Vincent; Pallas, Benoît; Costes, Evelyne
In crops, optimizing target traits in breeding programs can be fostered by selecting appropriate combinations of architectural traits which determine light interception and carbon acquisition. In apple tree, architectural traits were observed to be under genetic control. However, architectural traits also result from many organogenetic and morphological processes interacting with the environment. The present study aimed at combining a FSPM built for apple tree, MAppleT, with genetic determinisms of architectural traits, previously described in a bi-parental population. We focused on parameters related to organogenesis (phyllochron and immediate branching) and morphogenesis processes (internode length and leaf area) during the first year of tree growth. Two independent datasets collected in 2004 and 2007 on 116 genotypes, issued from a 'Starkrimson' × 'Granny Smith' cross, were used. The phyllochron was estimated as a function of thermal time and sylleptic branching was modeled subsequently depending on phyllochron. From a genetic map built with SNPs, marker effects were estimated on four MAppleT parameters with rrBLUP, using 2007 data. These effects were then considered in MAppleT to simulate tree development in the two climatic conditions. The genome wide prediction model gave consistent estimations of parameter values with correlation coefficients between observed values and estimated values from SNP markers ranging from 0.79 to 0.96. However, the accuracy of the prediction model following cross validation schemas was lower. Three integrative traits (the number of leaves, trunk length, and number of sylleptic laterals) were considered for validating MAppleT simulations. In 2007 climatic conditions, simulated values were close to observations, highlighting the correct simulation of genetic variability. However, in 2004 conditions which were not used for model calibration, the simulations differed from observations. This study demonstrates the possibility of
Horton, Matthew W; Bodenhausen, Natacha; Beilsmith, Kathleen; Meng, Dazhe; Muegge, Brian D; Subramanian, Sathish; Vetter, M Madlen; Vilhjálmsson, Bjarni J; Nordborg, Magnus; Gordon, Jeffrey I; Bergelson, Joy
Identifying the factors that influence the outcome of host-microbial interactions is critical to protecting biodiversity, minimizing agricultural losses and improving human health. A few genes that determine symbiosis or resistance to infectious disease have been identified in model species, but a comprehensive examination of how a host genotype influences the structure of its microbial community is lacking. Here we report the results of a field experiment with the model plant Arabidopsis thaliana to identify the fungi and bacteria that colonize its leaves and the host loci that influence the microbe numbers. The composition of this community differs among accessions of A. thaliana. Genome-wide association studies (GWAS) suggest that plant loci responsible for defense and cell wall integrity affect variation in this community. Furthermore, species richness in the bacterial community is shaped by host genetic variation, notably at loci that also influence the reproduction of viruses, trichome branching and morphogenesis.
Yee, S W; Giacomini, M M; Hsueh, C-H; Weitz, D; Liang, X; Goswami, S; Kinchen, J M; Coelho, A; Zur, A A; Mertsch, K; Brian, W; Kroetz, D L; Giacomini, K M
Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established. © 2016 American Society for Clinical Pharmacology and Therapeutics.
Arnedo, Javier; Svrakic, Dragan M; Del Val, Coral; Romero-Zaliz, Rocío; Hernández-Cuervo, Helena; Fanous, Ayman H; Pato, Michele T; Pato, Carlos N; de Erausquin, Gabriel A; Cloninger, C Robert; Zwir, Igor
The authors sought to demonstrate that schizophrenia is a heterogeneous group of heritable disorders caused by different genotypic networks that cause distinct clinical syndromes. In a large genome-wide association study of cases with schizophrenia and controls, the authors first identified sets of interacting single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (SNP sets) regardless of clinical status. Second, they examined the risk of schizophrenia for each SNP set and tested replicability in two independent samples. Third, they identified genotypic networks composed of SNP sets sharing SNPs or subjects. Fourth, they identified sets of distinct clinical features that cluster in particular cases (phenotypic sets or clinical syndromes) without regard for their genetic background. Fifth, they tested whether SNP sets were associated with distinct phenotypic sets in a replicable manner across the three studies. The authors identified 42 SNP sets associated with a 70% or greater risk of schizophrenia, and confirmed 34 (81%) or more with similar high risk of schizophrenia in two independent samples. Seventeen networks of SNP sets did not share any SNP or subject. These disjoint genotypic networks were associated with distinct gene products and clinical syndromes (i.e., the schizophrenias) varying in symptoms and severity. Associations between genotypic networks and clinical syndromes were complex, showing multifinality and equifinality. The interactive networks explained the risk of schizophrenia more than the average effects of all SNPs (24%). Schizophrenia is a group of heritable disorders caused by a moderate number of separate genotypic networks associated with several distinct clinical syndromes.
Winkler, Thomas W; Day, Felix R; Croteau-Chonka, Damien C
Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC...
The capacity to identify immunogens for vaccine development by genome-wide screening has been markedly enhanced by the availability of complete microbial genome sequences coupled to rapid proteomic and bioinformatic analysis. Critical to this genome-wide screening is in vivo testing in the context o...
Minster, Ryan L; Sanders, Jason L; Singh, Jatinder
BACKGROUND: The Healthy Aging Index (HAI) is a tool for measuring the extent of health and disease across multiple systems. METHODS: We conducted a genome-wide association study and a genome-wide linkage analysis to map quantitative trait loci associated with the HAI and a modified HAI weighted...
Sud, Amit; Thomsen, Hauke; Law, Philip J.
Several susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and 16,749 co...
Sud, A. (Amit); Thomsen, H. (Hauke); Law, P.J. (Philip J.); A. Försti (Asta); Filho, M.I.D.S. (Miguel Inacio Da Silva); Holroyd, A. (Amy); P. Broderick (Peter); Orlando, G. (Giulia); Lenive, O. (Oleg); Wright, L. (Lauren); R. Cooke (Rosie); D.F. Easton (Douglas); P.D.P. Pharoah (Paul); A.M. Dunning (Alison); J. Peto (Julian); F. Canzian (Federico); Eeles, R. (Rosalind); Z. Kote-Jarai; K.R. Muir (K.); Pashayan, N. (Nora); B.E. Henderson (Brian); C.A. Haiman (Christopher); S. Benlloch (Sara); F.R. Schumacher (Fredrick R); Olama, A.A.A. (Ali Amin Al); S.I. Berndt (Sonja); G. Conti (Giario); F. Wiklund (Fredrik); S.J. Chanock (Stephen); Stevens, V.L. (Victoria L.); C.M. Tangen (Catherine M.); Batra, J. (Jyotsna); Clements, J. (Judith); H. Grönberg (Henrik); Schleutker, J. (Johanna); D. Albanes (Demetrius); Weinstein, S. (Stephanie); K. Wolk (Kerstin); West, C. (Catharine); Mucci, L. (Lorelei); Cancel-Tassin, G. (Géraldine); Koutros, S. (Stella); Sorensen, K.D. (Karina Dalsgaard); L. Maehle; D. Neal (David); S.P.L. Travis (Simon); Hamilton, R.J. (Robert J.); S.A. Ingles (Sue); B.S. Rosenstein (Barry S.); Lu, Y.-J. (Yong-Jie); Giles, G.G. (Graham G.); A. Kibel (Adam); Vega, A. (Ana); M. Kogevinas (Manolis); Penney, K.L. (Kathryn L.); Park, J.Y. (Jong Y.); Stanford, J.L. (Janet L.); C. Cybulski (Cezary); B.G. Nordestgaard (Børge); Brenner, H. (Hermann); Maier, C. (Christiane); Kim, J. (Jeri); E.M. John (Esther); P.J. Teixeira; Neuhausen, S.L. (Susan L.); De Ruyck, K. (Kim); Razack, A. (Azad); Newcomb, L.F. (Lisa F.); Lessel, D. (Davor); Kaneva, R. (Radka); N. Usmani (Nawaid); F. Claessens; Townsend, P.A. (Paul A.); Dominguez, M.G. (Manuela Gago); Roobol, M.J. (Monique J.); F. Menegaux (Florence); P. Hoffmann (Per); M.M. Nöthen (Markus); K.-H. JöCkel (Karl-Heinz); Strandmann, E.P.V. (Elke Pogge Von); Lightfoot, T. (Tracy); Kane, E. (Eleanor); Roman, E. (Eve); Lake, A. (Annette); Montgomery, D. (Dorothy); Jarrett, R.F. (Ruth F.); A.J. Swerdlow (Anthony ); A. Engert (Andreas); N. Orr (Nick); K. Hemminki (Kari); Houlston, R.S. (Richard S.)
textabstractSeveral susceptibility loci for classical Hodgkin lymphoma have been reported. However, much of the heritable risk is unknown. Here, we perform a meta-analysis of two existing genome-wide association studies, a new genome-wide association study, and replication totalling 5,314 cases and
Zhu, Haidong; Wang, Xiaoling; Shi, Huidong; Su, Shaoyong; Harshfield, Gregory A.; Gutin, Bernard; Snieder, Harold; Dong, Yanbin
Objectives To test the hypothesis that changes in DNA methylation are involved in vitamin D deficiency-related immune cell regulation using an unbiased genome-wide approach combined with a genomic and epigenomic integrative approach. Study design We performed a genome-wide methylation scan using the
Nieuwboer, H.A.; Pool, R.; Dolan, C.V.; Boomsma, D.I.; Nivard, M.G.
Here we present a method of genome-wide inferred study (GWIS) that provides an approximation of genome-wide association study (GWAS) summary statistics for a variable that is a function of phenotypes for which GWAS summary statistics, phenotypic means, and covariances are available. A GWIS can be
Yu, Xijiang; Meuwissen, Theo H E
Genome-wide breeding value (GWEBV) estimation methods can be classified based on the prior distribution assumptions of marker effects. Genome-wide BLUP methods assume a normal prior distribution for all markers with a constant variance, and are computationally fast. In Bayesian methods, more flexible prior distributions of SNP effects are applied that allow for very large SNP effects although most are small or even zero, but these prior distributions are often also computationally demanding as they rely on Monte Carlo Markov chain sampling. In this study, we adopted the Pareto principle to weight available marker loci, i.e., we consider that x% of the loci explain (100 - x)% of the total genetic variance. Assuming this principle, it is also possible to define the variances of the prior distribution of the 'big' and 'small' SNP. The relatively few large SNP explain a large proportion of the genetic variance and the majority of the SNP show small effects and explain a minor proportion of the genetic variance. We name this method MixP, where the prior distribution is a mixture of two normal distributions, i.e. one with a big variance and one with a small variance. Simulation results, using a real Norwegian Red cattle pedigree, show that MixP is at least as accurate as the other methods in all studied cases. This method also reduces the hyper-parameters of the prior distribution from 2 (proportion and variance of SNP with big effects) to 1 (proportion of SNP with big effects), assuming the overall genetic variance is known. The mixture of normal distribution prior made it possible to solve the equations iteratively, which greatly reduced computation loads by two orders of magnitude. In the era of marker density reaching million(s) and whole-genome sequence data, MixP provides a computationally feasible Bayesian method of analysis.
Mathew J Barber
Full Text Available Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs contributing to this variation, we performed a combined analysis of genome-wide association (GWA results from three trials of statin efficacy.Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks, Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks, and Treating to New Targets (10 mg/day atorvastatin, 8 weeks. Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P = 1.8 x 10(-8. This SNP was less significantly associated with change in LDL-cholesterol (posterior probability = 0.16, P = 4.0 x 10(-6. Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol.Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we
Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F
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...
Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong
For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809
Zhang, Shizhong; Xu, Ruirui; Luo, Xiaocui; Jiang, Zesheng; Shu, Huairui
MAPK signal transduction modules play crucial roles in regulating many biological processes in plants, which are composed of three classes of hierarchically organized protein kinases, namely MAPKKKs, MAPKKs, and MAPKs. Although genome-wide analysis of this family has been carried out in some species, little is known about MAPK and MAPKK genes in apple (Malus domestica). In this study, a total of 26 putative apple MAPK genes (MdMPKs) and 9 putative apple MAPKK genes (MdMKKs) have been identified and located within the apple genome. Phylogenetic analysis revealed that MdMAPKs and MdMAPKKs could be divided into 4 subfamilies (groups A, B, C and D), respectively. The predicted MdMAPKs and MdMAPKKs were distributed across 13 out of 17 chromosomes with different densities. In addition, analysis of exon-intron junctions and of intron phase inside the predicted coding region of each candidate gene has revealed high levels of conservation within and between phylogenetic groups. According to the microarray and expressed sequence tag (EST) analysis, the different expression patterns indicate that they may play different roles during fruit development and rootstock-scion interaction process. Moreover, MAPK and MAPKK genes were performed expression profile analyses in different tissues (root, stem, leaf, flower and fruit), and all of the selected genes were expressed in at least one of the tissues tested, indicating that the MAPKs and MAPKKs are involved in various aspects of physiological and developmental processes of apple. To our knowledge, this is the first report of a genome-wide analysis of the apple MAPK and MAPKK gene family. This study provides valuable information for understanding the classification and putative functions of the MAPK signal in apple. © 2013.
Stricker, Georg; Engelhardt, Alexander; Schulz, Daniel; Schmid, Matthias; Tresch, Achim; Gagneur, Julien
Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . email@example.com. Supplementary information is available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org
Full Text Available Dogs, with their breed-determined limited genetic background, are great models of human disease including cancer. Canine B-cell lymphoma and hemangiosarcoma are both malignancies of the hematologic system that are clinically and histologically similar to human B-cell non-Hodgkin lymphoma and angiosarcoma, respectively. Golden retrievers in the US show significantly elevated lifetime risk for both B-cell lymphoma (6% and hemangiosarcoma (20%. We conducted genome-wide association studies for hemangiosarcoma and B-cell lymphoma, identifying two shared predisposing loci. The two associated loci are located on chromosome 5, and together contribute ~20% of the risk of developing these cancers. Genome-wide p-values for the top SNP of each locus are 4.6×10-7 and 2.7×10-6, respectively. Whole genome resequencing of nine cases and controls followed by genotyping and detailed analysis identified three shared and one B-cell lymphoma specific risk haplotypes within the two loci, but no coding changes were associated with the risk haplotypes. Gene expression analysis of B-cell lymphoma tumors revealed that carrying the risk haplotypes at the first locus is associated with down-regulation of several nearby genes including the proximal gene TRPC6, a transient receptor Ca2+-channel involved in T-cell activation, among other functions. The shared risk haplotype in the second locus overlaps the vesicle transport and release gene STX8. Carrying the shared risk haplotype is associated with gene expression changes of 100 genes enriched for pathways involved in immune cell activation. Thus, the predisposing germ-line mutations in B-cell lymphoma and hemangiosarcoma appear to be regulatory, and affect pathways involved in T-cell mediated immune response in the tumor. This suggests that the interaction between the immune system and malignant cells plays a common role in the tumorigenesis of these relatively different cancers.
Lu, Yi; Chen, Xiaoqing; Beesley, Jonathan
stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small......Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used...... in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated...
Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.
Seyhan, Attila A; Varadarajan, Usha; Choe, Sung; Liu, Yan; McGraw, John; Woods, Matthew; Murray, Stuart; Eckert, Amy; Liu, Wei; Ryan, Terence E
ErbB2 is frequently activated in tumors, and influences a wide array of cellular functions, including proliferation, apoptosis, cell motility and adhesion. HKI-272 (neratinib) is a small molecule pan-kinase inhibitor of the ErbB family of receptor tyrosine kinases, and shows strong antiproliferative activity in ErbB2-overexpressing breast cancer cells. We undertook a genome-wide pooled lentiviral RNAi screen to identify synthetic lethal or enhancer (synthetic modulator screen) genes that interact with neratinib in a human breast cancer cell line (SKBR-3). These genes upon knockdown would modulate cell viability in the presence of subeffective concentrations of neratinib. We discovered a diverse set of genes whose depletion selectively impaired or enhanced the viability of SKBR-3 cells in the presence of neratinib. We observed diverse pathways including EGFR, hypoxia, cAMP, and protein ubiquitination that, when co-treated with RNAi and neratinib, resulted in arrest of cell proliferation. Examining the changes of these genes and their protein products also led to a rationale for clinically relevant drug combination treatments. Treatment of cells with either paclitaxel or cytarabine in combination with neratinib resulted in a strong antiproliferative effect. The identification of novel mediators of cellular response to neratinib and the development of potential drug combination treatments have expanded our understanding of neratinib's mode-of-action for the development of more effective therapeutic regimens. Notably, our findings support a paclitaxel and neratinib phase III clinical trial in breast cancer patients.
Bigdeli, Tim B.; Ripke, Stephan; Bacanu, Silviu-Alin
Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence...... of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N...... history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R2=0.0021; P=0.00331; P-value threshold
Biernacka, Joanna M.; Geske, Jennifer; Jenkins, Gregory D.; Colby, Colin; Rider, David N.; Karpyak, Victor M.; Choi, Doo-Sup; Fridley, Brooke L.
It is believed that multiple genetic variants with small individual effects contribute to the risk of alcohol dependence. Such polygenic effects are difficult to detect in genome-wide association studies that test for association of the phenotype with each single nucleotide polymorphism (SNP) individually. To overcome this challenge, gene set analysis (GSA) methods that jointly test for the effects of pre-defined groups of genes have been proposed. Rather than testing for association between the phenotype and individual SNPs, these analyses evaluate the global evidence of association with a set of related genes enabling the identification of cellular or molecular pathways or biological processes that play a role in development of the disease. It is hoped that by aggregating the evidence of association for all available SNPs in a group of related genes, these approaches will have enhanced power to detect genetic associations with complex traits. We performed GSA using data from a genome-wide study of 1165 alcohol dependent cases and 1379 controls from the Study of Addiction: Genetics and Environment (SAGE), for all 200 pathways listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results demonstrated a potential role of the “Synthesis and Degradation of Ketone Bodies” pathway. Our results also support the potential involvement of the “Neuroactive Ligand Receptor Interaction” pathway, which has previously been implicated in addictive disorders. These findings demonstrate the utility of GSA in the study of complex disease, and suggest specific directions for further research into the genetic architecture of alcohol dependence. PMID:22717047
Khan Meraj A
Full Text Available Abstract Background In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n = 18 suffering from moderate (stage 3; n = 8 or severe (stage 4; n = 10 ovarian endometriosis during proliferative (n = 13 and secretory (n = 5 phases of menstrual cycle was performed. Methods Individual pure RNA samples were subjected to Agilent’s Whole Human Genome 44K microarray experiments. Microarray data were validated (P Results Higher clustering effect of pairing (cluster distance, cd = 0.1 in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd = 0.5 and phases of menstrual cycle (cd = 0.6. Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic potential in endometriotic tissue. Dys-regulation of three (CLOCK, ESR1, and MYC major transcription factors appeared to be significant causative factors in the pathogenesis of ovarian endometriosis. A novel cohort of twenty-eight (28 genes representing potential marker for ovarian endometriosis in fertile women was discovered. Conclusions Dysfunctional expression of immuno-neuro-endocrine behaviour in endometrium appeared critical to endometriosis. Although no overt oncogenic potential was evident, several genes associated with gynecological cancers were
Davies, G; Harris, S E; Reynolds, C A; Payton, A; Knight, H M; Liewald, D C; Lopez, L M; Luciano, M; Gow, A J; Corley, J; Henderson, R; Murray, C; Pattie, A; Fox, H C; Redmond, P; Lutz, M W; Chiba-Falek, O; Linnertz, C; Saith, S; Haggarty, P; McNeill, G; Ke, X; Ollier, W; Horan, M; Roses, A D; Ponting, C P; Porteous, D J; Tenesa, A; Pickles, A; Starr, J M; Whalley, L J; Pedersen, N L; Pendleton, N; Visscher, P M; Deary, I J
Cognitive decline is a feared aspect of growing old. It is a major contributor to lower quality of life and loss of independence in old age. We investigated the genetic contribution to individual differences in nonpathological cognitive ageing in five cohorts of older adults. We undertook a genome-wide association analysis using 549 692 single-nucleotide polymorphisms (SNPs) in 3511 unrelated adults in the Cognitive Ageing Genetics in England and Scotland (CAGES) project. These individuals have detailed longitudinal cognitive data from which phenotypes measuring each individual's cognitive changes were constructed. One SNP--rs2075650, located in TOMM40 (translocase of the outer mitochondrial membrane 40 homolog)--had a genome-wide significant association with cognitive ageing (P=2.5 × 10(-8)). This result was replicated in a meta-analysis of three independent Swedish cohorts (P=2.41 × 10(-6)). An Apolipoprotein E (APOE) haplotype (adjacent to TOMM40), previously associated with cognitive ageing, had a significant effect on cognitive ageing in the CAGES sample (P=2.18 × 10(-8); females, P=1.66 × 10(-11); males, P=0.01). Fine SNP mapping of the TOMM40/APOE region identified both APOE (rs429358; P=3.66 × 10(-11)) and TOMM40 (rs11556505; P=2.45 × 10(-8)) as loci that were associated with cognitive ageing. Imputation and conditional analyses in the discovery and replication cohorts strongly suggest that this effect is due to APOE (rs429358). Functional genomic analysis indicated that SNPs in the TOMM40/APOE region have a functional, regulatory non-protein-coding effect. The APOE region is significantly associated with nonpathological cognitive ageing. The identity and mechanism of one or multiple causal variants remain unclear.
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.
Thomson, John P.; Fawkes, Angie; Ottaviano, Raffaele; Hunter, Jennifer M.; Shukla, Ruchi; Mjoseng, Heidi K.; Clark, Richard; Coutts, Audrey; Murphy, Lee; Meehan, Richard R.
Modification of DNA resulting in 5-methylcytosine (5 mC) or 5-hydroxymethylcytosine (5hmC) has been shown to influence the local chromatin environment and affect transcription. Although recent advances in next generation sequencing technology allow researchers to map epigenetic modifications across the genome, such experiments are often time-consuming and cost prohibitive. Here we present a rapid and cost effective method of generating genome wide DNA modification maps utilising commercially ...
Chavez-Galarza, Julio; Johnston, J. Spencer; Azevedo, João; Muñoz, Irene; De la Rúa, Pilar; Patton, John C.; Pinto, M. Alice
Dissecting genome-wide (expansions, contractions, admixture) from genome-specific effects (selection) is a goal of central importance in evolutionary biology because it leads to more robust inferences of demographic history and to identification of adaptive divergence. The publication of the honey bee genome and the development of high-density SNPs genotyping, provide us with powerful tools, allowing us to identify signatures of selection in the honey bee genome. These signatur...
Malovini, Alberto; Rognoni, Carla; Puca, Annibale; Bellazzi, Riccardo
Experimental errors in the genotyping phases of a Genome-Wide Association Study (GWAS) can lead to false positive findings and to spurious associations. An appropriate quality control phase could minimize the effects of this kind of errors. Several filtering criteria can be used to perform quality control. Currently, no formal methods have been proposed for taking into account at the same time these criteria and the experimenter's preferences. In this paper we propose two strategies for setting appropriate genotyping rate thresholds for GWAS quality control. These two approaches are based on the Multi-Criteria Decision Making theory. We have applied our method on a real dataset composed by 734 individuals affected by Arterial Hypertension (AH) and 486 nonagenarians without history of AH. The proposed strategies appear to deal with GWAS quality control in a sound way, as they lead to rationalize and make explicit the experimenter's choices thus providing more reproducible results.
Kühnisch, Jan; Thiering, Elisabeth; Heitmüller, Daniela; Tiesler, Carla M T; Grallert, Harald; Heinrich-Weltzien, Roswitha; Hickel, Reinhard; Heinrich, Joachim
This genome-wide association study (GWAS) investigated the relationship between molar-incisor hypomineralization (MIH) and possible genetic loci. Clinical and genetic data from the 10-year follow-up of 668 children from the Munich GINI-plus and LISA-plus birth cohort studies were analyzed. The dental examinations included the diagnosis of MIH according to the criteria of the European Academy of Paediatric Dentistry (EAPD). Children with MIH were categorized as those with a minimum of one hypomineralized first permanent molar. A GWAS was implemented following a quality-control step and an additive genetic effect was assumed. A total of 2,013,491 single-nucleotide polymorphisms (SNPs) were available for analysis. Rs13058467, which is located near the SCUBE1 gene on chromosome 22 (p MIH when using a threshold of p value MIH.
van Leeuwen, D M; van Herwijnen, M H M; Pedersen, Marie
The Teplice area in the Czech Republic is a mining district where elevated levels of air pollution including airborne carcinogens, have been demonstrated, especially during winter time. This environmental exposure can impact human health; in particular children may be more vulnerable. To study....... This suggests an effect of air pollution on the primary structural unit of the condensed DNA. In addition, several other pathways were modulated. Based on the results of this study, we suggest that transcriptomic analysis represents a promising biomarker for environmental carcinogenesis....... the impact of air pollution in children at the transcriptional level, peripheral blood cells were subjected to whole genome response analysis, in order to identify significantly modulated biological pathways and processes as a result of exposure. Using genome-wide oligonucleotide microarrays, we investigated...
Full Text Available RNA-Seq, a method using next generation sequencing technologies to sequence the transcriptome, facilitates genome-wide analysis of splice junction sites. In this paper, we introduce SOAPsplice, a robust tool to detect splice junctions using RNA-Seq data without using any information of known splice junctions. SOAPsplice uses a novel two-step approach consisting of first identifying as many reasonable splice junction candidates as possible, and then, filtering the false positives with two effective filtering strategies. In both simulated and real datasets, SOAPsplice is able to detect many reliable splice junctions with low false positive rate. The improvement gained by SOAPsplice, when compared to other existing tools, becomes more obvious when the depth of sequencing is low. SOAPsplice is freely available at http://soap.genomics.org.cn/soapsplice.html.
Liu, Jin; Huang, Jian; Ma, Shuangge
Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092
Staunstrup, Nicklas H; Starnawska, Anna; Nyegaard, Mette
BACKGROUND: In utero and early-life experienced environmental exposures are suggested to play an important role in many multifactorial diseases potentially mediated through lasting effects on the epigenome. As the epigenome in addition remains modifiable throughout life, identifying specific...... biobanks. However, availability of this biological material is highly limited as each DBS is made only from a few droplets of blood and storage conditions may be suboptimal for epigenetic studies. Furthermore, as relevant markers may reside outside gene bodies, epigenome-wide interrogation is needed....... RESULTS: Here we demonstrate, as a proof of principle, that genome-wide interrogation of the methylome based on methylated DNA immunoprecipitation coupled with next-generation sequencing (MeDIP-seq) is feasible using a single 3.2 mm DBS punch (60 ng DNA) from filter cards archived for up to 16 years...
Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig
As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.
Grimm, Dominik G; Roqueiro, Damian; Salomé, Patrice A; Kleeberger, Stefan; Greshake, Bastian; Zhu, Wangsheng; Liu, Chang; Lippert, Christoph; Stegle, Oliver; Schölkopf, Bernhard; Weigel, Detlef; Borgwardt, Karsten M
The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana , using flowering and growth-related traits. © 2016 American Society of Plant Biologists. All rights reserved.
Mota, R R; Guimarães, S E F; Fortes, M R S; Hayes, B; Silva, F F; Verardo, L L; Kelly, M J; de Campos, C F; Guimarães, J D; Wenceslau, R R; Penitente-Filho, J M; Garcia, J F; Moore, S
We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken. © 2017 Blackwell Verlag GmbH.
Shim, Sungryul; Kim, Jiyoung; Jung, Wonguen; Shin, In-Soo; Bae, Jong-Myon
This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA). The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy-Weinberg equilibrium (HWE) in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The 'genhwcci' and 'metan' commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the 'metareg' command of STATA should be conducted to evaluate related factors of heterogeneities.
Bønnelykke, Klaus; Sleiman, Patrick; Nielsen, Kasper
Asthma exacerbations are among the most frequent causes of hospitalization during childhood, but the underlying mechanisms are poorly understood. We performed a genome-wide association study of a specific asthma phenotype characterized by recurrent, severe exacerbations occurring between 2 and 6......1RL1, were previously reported as asthma susceptibility loci, but the effect sizes for these loci in our cohort were considerably larger than in the previous genome-wide association studies of asthma. We also obtained strong evidence for a new susceptibility gene, CDHR3 (encoding cadherin......-related family member 3), which is highly expressed in airway epithelium. These results demonstrate the strength of applying specific phenotyping in the search for asthma susceptibility genes....
Full Text Available This review aimed to arrange the process of a systematic review of genome-wide association studies in order to practice and apply a genome-wide meta-analysis (GWMA. The process has a series of five steps: searching and selection, extraction of related information, evaluation of validity, meta-analysis by type of genetic model, and evaluation of heterogeneity. In contrast to intervention meta-analyses, GWMA has to evaluate the Hardy–Weinberg equilibrium (HWE in the third step and conduct meta-analyses by five potential genetic models, including dominant, recessive, homozygote contrast, heterozygote contrast, and allelic contrast in the fourth step. The ‘genhwcci’ and ‘metan’ commands of STATA software evaluate the HWE and calculate a summary effect size, respectively. A meta-regression using the ‘metareg’ command of STATA should be conducted to evaluate related factors of heterogeneities.
Noor, Dzul Azri Mohamed; Jeyapalan, Jennie N; Alhazmi, Safiah; Carr, Matthew; Squibb, Benjamin; Wallace, Claire; Tan, Christopher; Cusack, Martin; Hughes, Jaime; Reader, Tom; Shipley, Janet; Sheer, Denise; Scotting, Paul J
Silencing of genes by DNA methylation is a common phenomenon in many types of cancer. However, the genome-wide effect of DNA methylation on gene expression has been analysed in relatively few cancers. Germ cell tumours (GCTs) are a complex group of malignancies. They are unique in developing from a pluripotent progenitor cell. Previous analyses have suggested that non-seminomas exhibit much higher levels of DNA methylation than seminomas. The genomic targets that are methylated, the extent to which this results in gene silencing and the identity of the silenced genes most likely to play a role in the tumours' biology have not yet been established. In this study, genome-wide methylation and expression analysis of GCT cell lines was combined with gene expression data from primary tumours to address this question. Genome methylation was analysed using the Illumina infinium HumanMethylome450 bead chip system and gene expression was analysed using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Regulation by methylation was confirmed by demethylation using 5-aza-2-deoxycytidine and reverse transcription-quantitative PCR. Large differences in the level of methylation of the CpG islands of individual genes between tumour cell lines correlated well with differential gene expression. Treatment of non-seminoma cells with 5-aza-2-deoxycytidine verified that methylation of all genes tested played a role in their silencing in yolk sac tumour cells and many of these genes were also differentially expressed in primary tumours. Genes silenced by methylation in the various GCT cell lines were identified. Several pluripotency-associated genes were identified as a major functional group of silenced genes.
Boueiz, Adel; Lutz, Sharon M; Cho, Michael H; Hersh, Craig P; Bowler, Russell P; Washko, George R; Halper-Stromberg, Eitan; Bakke, Per; Gulsvik, Amund; Laird, Nan M; Beaty, Terri H; Coxson, Harvey O; Crapo, James D; Silverman, Edwin K; Castaldi, Peter J; DeMeo, Dawn L
Emphysema has considerable variability in the severity and distribution of parenchymal destruction throughout the lungs. Upper lobe-predominant emphysema has emerged as an important predictor of response to lung volume reduction surgery. Yet, aside from alpha-1 antitrypsin deficiency, the genetic determinants of emphysema distribution remain largely unknown. To identify the genetic influences of emphysema distribution in non-alpha-1 antitrypsin-deficient smokers. A total of 11,532 subjects with complete genotype and computed tomography densitometry data in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]; non-Hispanic white and African American), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints), and GenKOLS (Genetics of Chronic Obstructive Lung Disease) studies were analyzed. Two computed tomography scan emphysema distribution measures (difference between upper-third and lower-third emphysema; ratio of upper-third to lower-third emphysema) were tested for genetic associations in all study subjects. Separate analyses in each study population were followed by a fixed effect metaanalysis. Single-nucleotide polymorphism-, gene-, and pathway-based approaches were used. In silico functional evaluation was also performed. We identified five loci associated with emphysema distribution at genome-wide significance. These loci included two previously reported associations with COPD susceptibility (4q31 near HHIP and 15q25 near CHRNA5) and three new associations near SOWAHB, TRAPPC9, and KIAA1462. Gene set analysis and in silico functional evaluation revealed pathways and cell types that may potentially contribute to the pathogenesis of emphysema distribution. This multicohort genome-wide association study identified new genomic loci associated with differential emphysematous destruction throughout the lungs. These findings may point to new biologic pathways on which to expand diagnostic and therapeutic
Wattacheril, Julia; Lavine, Joel E; Chalasani, Naga P; Guo, Xiuqing; Kwon, Soonil; Schwimmer, Jeffrey; Molleston, Jean P; Loomba, Rohit; Brunt, Elizabeth M; Chen, Yii-Der Ida; Goodarzi, Mark O; Taylor, Kent D; Yates, Katherine P; Tonascia, James; Rotter, Jerome I
To identify genetic loci associated with features of histologic severity of nonalcoholic fatty liver disease in a cohort of Hispanic boys. There were 234 eligible Hispanic boys age 2-17 years with clinical, laboratory, and histologic data enrolled in the Nonalcoholic Steatohepatitis Clinical Research Network included in the analysis of 624 297 single nucleotide polymorphisms (SNPs). After the elimination of 4 outliers and 22 boys with cryptic relatedness, association analyses were performed on 208 DNA samples with corresponding liver histology. Logistic regression analyses were carried out for qualitative traits and linear regression analyses were applied for quantitative traits. The median age and body mass index z-score were 12.0 years (IQR, 11.0-14.0) and 2.4 (IQR, 2.1-2.6), respectively. The nonalcoholic fatty liver disease activity score (scores 1-4 vs 5-8) was associated with SNP rs11166927 on chromosome 8 in the TRAPPC9 region (P = 8.7 -07 ). Fibrosis stage was associated with SNP rs6128907 on chromosome 20, near actin related protein 5 homolog (p = 9.9 -07 ). In comparing our results in Hispanic boys with those of previously reported SNPs in adult nonalcoholic steatohepatitis, 2 of 26 susceptibility loci were associated with nonalcoholic fatty liver disease activity score and 2 were associated with fibrosis stage. In this discovery genome-wide association study, we found significant novel gene effects on histologic traits associated with nonalcoholic fatty liver disease activity score and fibrosis that are distinct from those previously recognized by adult nonalcoholic fatty liver disease genome-wide association studies. Copyright © 2017 Elsevier Inc. All rights reserved.
B. G. Welderufael
Full Text Available Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS to identify associated single nucleotide polymorphisms (SNPs and investigate the genetic background not only for susceptibility to – but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value < 10-4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to – or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2 and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3 were suggested as possible causal genes for susceptibility to – and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to – and recoverability from mastitis.
Need, Anna C.; Attix, Deborah K.; McEvoy, Jill M.; Cirulli, Elizabeth T.; Linney, Kristen L.; Hunt, Priscilla; Ge, Dongliang; Heinzen, Erin L.; Maia, Jessica M.; Shianna, Kevin V.; Weale, Michael E.; Cherkas, Lynn F.; Clement, Gail; Spector, Tim D.; Gibson, Greg; Goldstein, David B.
Psychiatric disorders such as schizophrenia are commonly accompanied by cognitive impairments that are treatment resistant and crucial to functional outcome. There has been great interest in studying cognitive measures as endophenotypes for psychiatric disorders, with the hope that their genetic basis will be clearer. To investigate this, we performed a genome-wide association study involving 11 cognitive phenotypes from the Cambridge Neuropsychological Test Automated Battery. We showed these measures to be heritable by comparing the correlation in 100 monozygotic and 100 dizygotic twin pairs. The full battery was tested in ∼750 subjects, and for spatial and verbal recognition memory, we investigated a further 500 individuals to search for smaller genetic effects. We were unable to find any genome-wide significant associations with either SNPs or common copy number variants. Nor could we formally replicate any polymorphism that has been previously associated with cognition, although we found a weak signal of lower than expected P-values for variants in a set of 10 candidate genes. We additionally investigated SNPs in genomic loci that have been shown to harbor rare variants that associate with neuropsychiatric disorders, to see if they showed any suggestion of association when considered as a separate set. Only NRXN1 showed evidence of significant association with cognition. These results suggest that common genetic variation does not strongly influence cognition in healthy subjects and that cognitive measures do not represent a more tractable genetic trait than clinical endpoints such as schizophrenia. We discuss a possible role for rare variation in cognitive genomics. PMID:19734545
Pain, Oliver; Dudbridge, Frank; Cardno, Alastair G; Freeman, Daniel; Lu, Yi; Lundstrom, Sebastian; Lichtenstein, Paul; Ronald, Angelica
This study aimed to test for overlap in genetic influences between psychotic-like experience traits shown by adolescents in the community, and clinically-recognized psychiatric disorders in adulthood, specifically schizophrenia, bipolar disorder, and major depression. The full spectra of psychotic-like experience domains, both in terms of their severity and type (positive, cognitive, and negative), were assessed using self- and parent-ratings in three European community samples aged 15-19 years (Final N incl. siblings = 6,297-10,098). A mega-genome-wide association study (mega-GWAS) for each psychotic-like experience domain was performed. Single nucleotide polymorphism (SNP)-heritability of each psychotic-like experience domain was estimated using genomic-relatedness-based restricted maximum-likelihood (GREML) and linkage disequilibrium- (LD-) score regression. Genetic overlap between specific psychotic-like experience domains and schizophrenia, bipolar disorder, and major depression was assessed using polygenic risk score (PRS) and LD-score regression. GREML returned SNP-heritability estimates of 3-9% for psychotic-like experience trait domains, with higher estimates for less skewed traits (Anhedonia, Cognitive Disorganization) than for more skewed traits (Paranoia and Hallucinations, Parent-rated Negative Symptoms). Mega-GWAS analysis identified one genome-wide significant association for Anhedonia within IDO2 but which did not replicate in an independent sample. PRS analysis revealed that the schizophrenia PRS significantly predicted all adolescent psychotic-like experience trait domains (Paranoia and Hallucinations only in non-zero scorers). The major depression PRS significantly predicted Anhedonia and Parent-rated Negative Symptoms in adolescence. Psychotic-like experiences during adolescence in the community show additive genetic effects and partly share genetic influences with clinically-recognized psychiatric disorders, specifically schizophrenia and
Richard A Jensen
Full Text Available Mild retinopathy (microaneurysms or dot-blot hemorrhages is observed in persons without diabetes or hypertension and may reflect microvascular disease in other organs. We conducted a genome-wide association study (GWAS of mild retinopathy in persons without diabetes.A working group agreed on phenotype harmonization, covariate selection and analytic plans for within-cohort GWAS. An inverse-variance weighted fixed effects meta-analysis was performed with GWAS results from six cohorts of 19,411 Caucasians. The primary analysis included individuals without diabetes and secondary analyses were stratified by hypertension status. We also singled out the results from single nucleotide polymorphisms (SNPs previously shown to be associated with diabetes and hypertension, the two most common causes of retinopathy.No SNPs reached genome-wide significance in the primary analysis or the secondary analysis of participants with hypertension. SNP, rs12155400, in the histone deacetylase 9 gene (HDAC9 on chromosome 7, was associated with retinopathy in analysis of participants without hypertension, -1.3±0.23 (beta ± standard error, p = 6.6×10(-9. Evidence suggests this was a false positive finding. The minor allele frequency was low (∼2%, the quality of the imputation was moderate (r(2 ∼0.7, and no other common variants in the HDAC9 gene were associated with the outcome. SNPs found to be associated with diabetes and hypertension in other GWAS were not associated with retinopathy in persons without diabetes or in subgroups with or without hypertension.This GWAS of retinopathy in individuals without diabetes showed little evidence of genetic associations. Further studies are needed to identify genes associated with these signs in order to help unravel novel pathways and determinants of microvascular diseases.
Boraska, Vesna; Jerončić, Ana; Colonna, Vincenza; Southam, Lorraine; Nyholt, Dale R.; William Rayner, Nigel; Perry, John R.B.; Toniolo, Daniela; Albrecht, Eva; Ang, Wei; Bandinelli, Stefania; Barbalic, Maja; Barroso, Inês; Beckmann, Jacques S.; Biffar, Reiner; Boomsma, Dorret; Campbell, Harry; Corre, Tanguy; Erdmann, Jeanette; Esko, Tõnu; Fischer, Krista; Franceschini, Nora; Frayling, Timothy M.; Girotto, Giorgia; Gonzalez, Juan R.; Harris, Tamara B.; Heath, Andrew C.; Heid, Iris M.; Hoffmann, Wolfgang; Hofman, Albert; Horikoshi, Momoko; Hua Zhao, Jing; Jackson, Anne U.; Hottenga, Jouke-Jan; Jula, Antti; Kähönen, Mika; Khaw, Kay-Tee; Kiemeney, Lambertus A.; Klopp, Norman; Kutalik, Zoltán; Lagou, Vasiliki; Launer, Lenore J.; Lehtimäki, Terho; Lemire, Mathieu; Lokki, Marja-Liisa; Loley, Christina; Luan, Jian'an; Mangino, Massimo; Mateo Leach, Irene; Medland, Sarah E.; Mihailov, Evelin; Montgomery, Grant W.; Navis, Gerjan; Newnham, John; Nieminen, Markku S.; Palotie, Aarno; Panoutsopoulou, Kalliope; Peters, Annette; Pirastu, Nicola; Polašek, Ozren; Rehnström, Karola; Ripatti, Samuli; Ritchie, Graham R.S.; Rivadeneira, Fernando; Robino, Antonietta; Samani, Nilesh J.; Shin, So-Youn; Sinisalo, Juha; Smit, Johannes H.; Soranzo, Nicole; Stolk, Lisette; Swinkels, Dorine W.; Tanaka, Toshiko; Teumer, Alexander; Tönjes, Anke; Traglia, Michela; Tuomilehto, Jaakko; Valsesia, Armand; van Gilst, Wiek H.; van Meurs, Joyce B.J.; Smith, Albert Vernon; Viikari, Jorma; Vink, Jacqueline M.; Waeber, Gerard; Warrington, Nicole M.; Widen, Elisabeth; Willemsen, Gonneke; Wright, Alan F.; Zanke, Brent W.; Zgaga, Lina; Boehnke, Michael; d'Adamo, Adamo Pio; de Geus, Eco; Demerath, Ellen W.; den Heijer, Martin; Eriksson, Johan G.; Ferrucci, Luigi; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Hengstenberg, Christian; Hudson, Thomas J.; Järvelin, Marjo-Riitta; Kogevinas, Manolis; Loos, Ruth J.F.; Martin, Nicholas G.; Metspalu, Andres; Pennell, Craig E.; Penninx, Brenda W.; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Schreiber, Stefan; Schunkert, Heribert; Spector, Tim D.; Stumvoll, Michael; Uitterlinden, André G.; Ulivi, Sheila; van der Harst, Pim; Vollenweider, Peter; Völzke, Henry; Wareham, Nicholas J.; Wichmann, H.-Erich; Wilson, James F.; Rudan, Igor; Xue, Yali; Zeggini, Eleftheria
The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10−8) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∼115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits. PMID:22843499
Coleman, Jonathan R. I.; Lester, Kathryn J.; Keers, Robert; Roberts, Susanna; Curtis, Charles; Arendt, Kristian; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Dalgleish, Tim; Hartman, Catharina A.; Heiervang, Einar R.; Hötzel, Katrin; Hudson, Jennifer L.; In-Albon, Tina; Lavallee, Kristen; Lyneham, Heidi J.; Marin, Carla E.; Meiser-Stedman, Richard; Morris, Talia; Nauta, Maaike H.; Rapee, Ronald M.; Schneider, Silvia; Schneider, Sophie C.; Silverman, Wendy K.; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Breen, Gerome; Eley, Thalia C.
Background Anxiety disorders are common, and cognitive–behavioural therapy (CBT) is a first-line treatment. Candidate gene studies have suggested a genetic basis to treatment response, but findings have been inconsistent. Aims To perform the first genome-wide association study (GWAS) of psychological treatment response in children with anxiety disorders (n = 980). Method Presence and severity of anxiety was assessed using semi-structured interview at baseline, on completion of treatment (post-treatment), and 3 to 12 months after treatment completion (follow-up). DNA was genotyped using the Illumina Human Core Exome-12v1.0 array. Linear mixed models were used to test associations between genetic variants and response (change in symptom severity) immediately post-treatment and at 6-month follow-up. Results No variants passed a genome-wide significance threshold (P = 5 × 10−8) in either analysis. Four variants met criteria for suggestive significance (P<5 × 10−6) in association with response post-treatment, and three variants in the 6-month follow-up analysis. Conclusions This is the first genome-wide therapygenetic study. It suggests no common variants of very high effect underlie response to CBT. Future investigations should maximise power to detect single-variant and polygenic effects by using larger, more homogeneous cohorts. PMID:26989097
Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare
The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We
Guerrieri, Francesca; Belloni, Laura; D’ Andrea, Daniel; Pediconi, Natalia; Le Pera, Loredana; Testoni, Barbara; Scisciani, Cecilia; Floriot, Oceane; Zoulim, Fabien; Tramontano, Anna; Levrero, Massimo
The Hepatitis B Virus (HBV) HBx regulatory protein is required for HBV replication and involved in HBV-related carcinogenesis. HBx interacts with chromatin modifying enzymes and transcription factors to modulate histone post
Belfield, E.J.; Gan, X.; Mithani, A.; Brown, C.; Jiang, C.; Franklin, K.; Alvey, E.; Wibowo, A.; Jung, M.; Bailey, K.; Kalwani, S.; Ragoussis, J.; Mott, R.; Harberd, N.P.
Ionizing radiation has long been known to induce heritable mutagenic change in DNA sequence. However, the genome-wide effect of radiation is not well understood. Here we report the molecular properties and frequency of mutations in phenotypically selected mutant lines isolated following exposure of the genetic model flowering plant Arabidopsis thaliana to fast neutrons (FNs). Previous studies suggested that FNs predominantly induce deletions longer than a kilobase in A. thaliana. However, we found a higher frequency of single base substitution than deletion mutations. While the overall frequency and molecular spectrum of fast-neutron (FN)-induced single base substitutions differed substantially from those of "background" mutations arising spontaneously in laboratory-grown plants, G:C>A:T transitions were favored in both. We found that FN-induced G:C>A:T transitions were concentrated at pyrimidine dinucleotide sites, suggesting that FNs promote the formation of mutational covalent linkages between adjacent pyrimidine residues. In addition, we found that FNs induced more single base than large deletions, and that these single base deletions were possibly caused by replication slippage. Our observations provide an initial picture of the genome-wide molecular profile of mutations induced in A. thaliana by FN irradiation and are particularly informative of the nature and extent of genome-wide mutation in lines selected on the basis of mutant phenotypes from FN-mutagenized A. thaliana populations.
Nilsson, Emil K; Boström, Adrian E; Mwinyi, Jessica; Schiöth, Helgi B
Despite an established link between sleep deprivation and epigenetic processes in humans, it remains unclear to what extent sleep deprivation modulates DNA methylation. We performed a within-subject randomized blinded study with 16 healthy subjects to examine the effect of one night of total sleep deprivation (TSD) on the genome-wide methylation profile in blood compared with that in normal sleep. Genome-wide differences in methylation between both conditions were assessed by applying a paired regression model that corrected for monocyte subpopulations. In addition, the correlations between the methylation of genes detected to be modulated by TSD and gene expression were examined in a separate, publicly available cohort of 10 healthy male donors (E-GEOD-49065). Sleep deprivation significantly affected the DNA methylation profile both independently and in dependency of shifts in monocyte composition. Our study detected differential methylation of 269 probes. Notably, one CpG site was located 69 bp upstream of ING5, which has been shown to be differentially expressed after sleep deprivation. Gene set enrichment analysis detected the Notch and Wnt signaling pathways to be enriched among the differentially methylated genes. These results provide evidence that total acute sleep deprivation alters the methylation profile in healthy human subjects. This is, to our knowledge, the first study that systematically investigated the impact of total acute sleep deprivation on genome-wide DNA methylation profiles in blood and related the epigenomic findings to the expression data.
Full Text Available Brachial circumference (BC, also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05 in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.
Ionizing radiation has long been known to induce heritable mutagenic change in DNA sequence. However, the genome-wide effect of radiation is not well understood. Here we report the molecular properties and frequency of mutations in phenotypically selected mutant lines isolated following exposure of the genetic model flowering plant Arabidopsis thaliana to fast neutrons (FNs). Previous studies suggested that FNs predominantly induce deletions longer than a kilobase in A. thaliana. However, we found a higher frequency of single base substitution than deletion mutations. While the overall frequency and molecular spectrum of fast-neutron (FN)-induced single base substitutions differed substantially from those of "background" mutations arising spontaneously in laboratory-grown plants, G:C>A:T transitions were favored in both. We found that FN-induced G:C>A:T transitions were concentrated at pyrimidine dinucleotide sites, suggesting that FNs promote the formation of mutational covalent linkages between adjacent pyrimidine residues. In addition, we found that FNs induced more single base than large deletions, and that these single base deletions were possibly caused by replication slippage. Our observations provide an initial picture of the genome-wide molecular profile of mutations induced in A. thaliana by FN irradiation and are particularly informative of the nature and extent of genome-wide mutation in lines selected on the basis of mutant phenotypes from FN-mutagenized A. thaliana populations.
Y.S. Aulchenko (Yurii); N. Vaessen (Norbert); P. Heutink (Peter); J. Pullen (Jan); P.J.L.M. Snijders (Pieter); A. Hofman (Albert); L.A. Sandkuijl (Lodewijk); J.J. Houwing-Duistermaat (Jeanine); S. Bennett (Simon); B.A. Oostra (Ben); C.M. van Duijn (Cornelia); M. Edwards (Mark)
textabstractMultiple genes, interacting with the environment, contribute to the susceptibility to type 2 diabetes. We performed a genome-wide search to localize type 2 diabetes susceptibility genes in a recently genetically isolated population in the Netherlands. We identified 79 nuclear families
Israel, Elliot; Lasky-Su, Jessica; Markezich, Amy; Damask, Amy; Szefler, Stanley J.; Schuemann, Brooke; Klanderman, Barbara; Sylvia, Jody; Kazani, Shamsah; Wu, Rongling; Martinez, Fernando; Boushey, Homer A.; Chinchilli, Vernon M.; Mauger, Dave; Weiss, Scott T.; Tantisira, Kelan G.; de Zeeuw, Dick; Navis, Gerjan J.
Rationale: [beta(2)-Agonists are the most common form of treatment of asthma, but there is significant variability in response to these medications. A significant proportion of this responsiveness may be heritable. Objectives: To investigate whether a genome-wide association study (GWAS) could
Pappa, I.; St Pourcain, B.; Benke, K.S.; Cavadino, A.; Hakulinen, C.; Nivard, M.G.; Nolte, I.M.; Tiesler, C.M.T.; Bakermans-Kranenburg, M.J.; Davies, G.E.; Evans, D.M.; Geoffroy, M.C.; Grallert, H.; Blokhuis, M.M.; Hudziak, J.J.; Kemp, J.P.; Keltikangas-Järvinen, L.; McMahon, G.; Mileva-Seitz, V.R.; Motazedi, E.; Power, C.; Raitakari, O.T.; Ring, S.M.; Rivadeneira, F.; Rodriguez, A.; Scheet, P.; Seppälä, I.; Snieder, H.; Standl, M.; Thiering, E.; Timpson, N.J.; Veenstra, R.; Velders, F.P.; Whitehouse, A.J.O.; Davey Smith, G.; Heinrich, J.; Hypponen, E.; Lehtimäki, T.; Middeldorp, C.M.; Oldehinkel, A.J.; Pennell, C.E.; Boomsma, D.I.; Tiemeier, H.
Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of
Coll, Francesc; Phelan, Jody; Hill-Cawthorne, Grant A.; Nair, Mridul; Mallard, Kim; Ali, Shahjahan; Abdallah, Abdallah; Alghamdi, Saad; Alsomali, Mona; Ahmed, Abdallah O.; Portelli, Stephanie; Oppong, Yaa; Alves, Adriana; Bessa, Theolis Barbosa; Campino, Susana; Caws, Maxine; Chatterjee, Anirvan; Crampin, Amelia C.; Dheda, Keertan; Furnham, Nicholas; Glynn, Judith R.; Grandjean, Louis; Minh Ha, Dang; Hasan, Rumina; Hasan, Zahra; Hibberd, Martin L.; Joloba, Moses; Jones-Ló pez, Edward C.; Matsumoto, Tomoshige; Miranda, Anabela; Moore, David J.; Mocillo, Nora; Panaiotov, Stefan; Parkhill, Julian; Penha, Carlos; Perdigã o, Joã o; Portugal, Isabel; Rchiad, Zineb; Robledo, Jaime; Sheen, Patricia; Shesha, Nashwa Talaat; Sirgel, Frik A.; Sola, Christophe; Oliveira Sousa, Erivelton; Streicher, Elizabeth M.; Helden, Paul Van; Viveiros, Miguel; Warren, Robert M.; McNerney, Ruth; Pain, Arnab; Clark, Taane G.
To characterize the genetic determinants of resistance to antituberculosis drugs, we performed a genome-wide association study (GWAS) of 6,465 Mycobacterium tuberculosis clinical isolates from more than 30 countries. A GWAS approach within a mixed
Vink, Jacqueline M; Smit, August B; de Geus, Eco J C
For the identification of genes associated with smoking initiation and current smoking, genome-wide association analyses were carried out in 3497 subjects. Significant genes that replicated in three independent samples (n = 405, 5810, and 1648) were visualized into a biologically meaningful network......) and cell-adhesion molecules (e.g., CDH23). We conclude that a network-based genome-wide association approach can identify genes influencing smoking behavior....
Muslihudeen Abdul-Razaq Abdul-Aziz
Full Text Available As our understanding of the human microbiome expands, impacts on health and disease continue to be revealed. Alterations in the microbiome can result in dysbiosis, which has now been linked to subsequent autoimmune and metabolic diseases, highlighting the need to identify factors that shape the microbiome. Research has identified that the composition and functions of the human microbiome can be influenced by diet, age, gender, and environment. More recently, studies have explored how human genetic variation may also influence the microbiome. Here, we review several recent analytical advances in this new research area, including those that use genome-wide association studies to examine host genome-microbiome interactions, while controlling for the influence of other factors. We find that current research is limited by small sample sizes, lack of cohort replication, and insufficient confirmatory mechanistic studies. In addition, we discuss the importance of understanding long-term interactions between the host genome and microbiome, as well as the potential impacts of disrupting this relationship, and explore new research avenues that may provide information about the co-evolutionary history of humans and their microorganisms.
Kelemen, Linda E; Lawrenson, Kate; Tyrer, Jonathan
at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC...... susceptibility variants and insights into the underlying biology of the disease....
Full Text Available There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57, CCL4L1 (p = 3.9x10(-21, IL18 (p = 6.8x10(-13, LPA (p = 4.4x10(-10, GGT1 (p = 1.5x10(-7, SHBG (p = 3.1x10(-7, CRP (p = 6.4x10(-6 and IL1RN (p = 7.3x10(-6 genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R, altered secretion rates of different sized proteins (LPA, variation in gene copy number (CCL4L1 and altered transcription (GGT1. We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha levels (p = 6.8x10(-40, but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis
Full Text Available Central obesity, measured by waist circumference (WC or waist-hip ratio (WHR, is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS of fat distribution among those of predominantly African ancestry (AA. We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1. Overall, 25 SNPs with single genomic control (GC-corrected p-values<5.0 × 10(-6 were followed-up (stage 2 in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10(-8 for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8 for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8; RREB1: p = 5.7 × 10(-8. Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN. Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02. In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept
Full Text Available Host-pathogen interactions are complex relationships, and a central challenge is to reveal the interactions between pathogens and their hosts. Bacillus bombysepticus (Bb which can produces spores and parasporal crystals was firstly separated from the corpses of the infected silkworms (Bombyx mori. Bb naturally infects the silkworm can cause an acute fuliginosa septicaemia and kill the silkworm larvae generally within one day in the hot and humid season. Bb pathogen of the silkworm can be used for investigating the host responses after the infection. Gene expression profiling during four time-points of silkworm whole larvae after Bb infection was performed to gain insight into the mechanism of Bb-associated host whole body effect. Genome-wide survey of the host genes demonstrated many genes and pathways modulated after the infection. GO analysis of the induced genes indicated that their functions could be divided into 14 categories. KEGG pathway analysis identified that six types of basal metabolic pathway were regulated, including genetic information processing and transcription, carbohydrate metabolism, amino acid and nitrogen metabolism, nucleotide metabolism, metabolism of cofactors and vitamins, and xenobiotic biodegradation and metabolism. Similar to Bacillus thuringiensis (Bt, Bb can also induce a silkworm poisoning-related response. In this process, genes encoding midgut peritrophic membrane proteins, aminopeptidase N receptors and sodium/calcium exchange protein showed modulation. For the first time, we found that Bb induced a lot of genes involved in juvenile hormone synthesis and metabolism pathway upregulated. Bb also triggered the host immune responses, including cellular immune response and serine protease cascade melanization response. Real time PCR analysis showed that Bb can induce the silkworm systemic immune response, mainly by the Toll pathway. Anti-microorganism peptides (AMPs, including of Attacin, Lebocin, Enbocin, Gloverin
Full Text Available Abstract Background Accurate mRNA splicing depends on multiple regulatory signals encoded in the transcribed RNA sequence. Many examples of mutations within human splice regulatory regions that alter splicing qualitatively or quantitatively have been reported and allelic differences in mRNA splicing are likely to be a common and important source of phenotypic diversity at the molecular level, in addition to their contribution to genetic disease susceptibility. However, because the effect of a mutation on the efficiency of mRNA splicing is often difficult to predict, many mutations that cause disease through an effect on splicing are likely to remain undiscovered. Results We have combined a genome-wide scan for sequence polymorphisms likely to affect mRNA splicing with analysis of publicly available Expressed Sequence Tag (EST and exon array data. The genome-wide scan uses published tools and identified 30,977 SNPs located within donor and acceptor splice sites, branch points and exonic splicing enhancer elements. For 1,185 candidate splicing polymorphisms the difference in splicing between alternative alleles was corroborated by publicly available exon array data from 166 lymphoblastoid cell lines. We developed a novel probabilistic method to infer allele-specific splicing from EST data. The method uses SNPs and alternative mRNA isoforms mapped to EST sequences and models both regulated alternative splicing as well as allele-specific splicing. We have also estimated heritability of splicing and report that a greater proportion of genes show evidence of splicing heritability than show heritability of overall gene expression level. Our results provide an extensive resource that can be used to assess the possible effect on splicing of human polymorphisms in putative splice-regulatory sites. Conclusion We report a set of genes showing evidence of allele-specific splicing from an integrated analysis of genomic polymorphisms, EST data and exon array
Ruffalo, Matthew; Bar-Joseph, Ziv
Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ email@example.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J
Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.
Cho, Seoae; Kim, Haseong; Oh, Sohee; Kim, Kyunga; Park, Taesung
The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genome. However, many challenges exist in detecting disease-causing genes among the thousands of SNPs. Examples include multicollinearity and multiple testing issues, especially when a large number of correlated SNPs are simultaneously tested. Multicollinearity can often occur when predictor variables in a multiple regression model are highly correlated, and can cause imprecise estimation of association. In this study, we propose a simple stepwise procedure that identifies disease-causing SNPs simultaneously by employing elastic-net regularization, a variable selection method that allows one to address multicollinearity. At Step 1, the single-marker association analysis was conducted to screen SNPs. At Step 2, the multiple-marker association was scanned based on the elastic-net regularization. The proposed approach was applied to the rheumatoid arthritis (RA) case-control data set of Genetic Analysis Workshop 16. While the selected SNPs at the screening step are located mostly on chromosome 6, the elastic-net approach identified putative RA-related SNPs on other chromosomes in an increased proportion. For some of those putative RA-related SNPs, we identified the interactions with sex, a well known factor affecting RA susceptibility.
Full Text Available Сarcinoembryonic antigen (CEA, CEACAM5, CD66 is a promoter of metastasis in epithelial cancers that is widely used as a prognostic clinical marker of metastasis. The aim of this study is to identify the network of genes that are associated with CEA-induced colorectal cancer liver metastasis. We compared the genome-wide transcriptomic profiles of CEA positive (MIP101 clone 8 and CEA negative (MIP 101 colorectal cancer cell lines with different metastatic potential in vivo. The CEA-producing cells displayed quantitative changes in the level of expression for 100 genes (over-expressed or down-regulated. They were confirmed by quantitative RT-PCR. The KEGG pathway analysis identified 4 significantly enriched pathways: cytokine-cytokine receptor interaction, MAPK signaling pathway, TGF-beta signaling pathway and pyrimidine metabolism. Our results suggest that CEA production by colorectal cancer cells triggers colorectal cancer progression by inducing the epithelial- mesenchymal transition, increasing tumor cell invasiveness into the surrounding tissues and suppressing stress and apoptotic signaling. The novel gene expression distinctions establish the relationships between the existing cancer markers and implicate new potential biomarkers for colorectal cancer hepatic metastasis.
Jeffrey A Gross
Full Text Available Suicide and suicide attempts are complex behaviors that result from the interaction of different factors, including genetic variants that increase the predisposition to suicidal behaviors. Copy number variations (CNVs are deletions or duplications of a segment of DNA usually larger than one kilobase. These structural genetic changes, although quite rare, have been associated with genetic liability to mental disorders, such as autism, schizophrenia, and bipolar disorder. No genome-wide level studies have been published investigating the potential role of CNVs in suicidal behaviors. Based on single-nucleotide polymorphism array data, we followed the Penn-CNV standards to detect CNVs in 1,608 subjects, comprising 475 suicide and suicide attempt cases and 1,133 controls. Although the initial algorithms determined the presence of CNVs on chromosomes 6 and 12 in seven and eight cases, respectively, compared with none of the controls, visual inspection of the raw data did not support this finding. Furthermore we were unable to validate these findings by CNV-specific real-time polymerase chain reaction. Additionally, rare CNV burden analysis did not find an association between the frequency or length of rare CNVs and suicidal behavior in our sample population. Although our findings suggest CNVs do not play an important role in the etiology of suicidal behaviors, they are not inconsistent with the strong evidence from the literature suggesting that other genetic variants account for a portion of the total phenotypic variability in suicidal behavior.
Full Text Available In Brassica napus breeding, traits related to commercial success are of highest importance for plant breeders. However, such traits can only be assessed in an advanced developmental stage. % as well as require high experimental effort due to their quantitative inheritance and the importance of genotype*environment interaction. Molecular markers genetically linked to such traits have the potential to accelerate the breeding process of B. napus by marker-assisted selection. Therefore, the objectives of this study were to identify (i genome regions associated with the examined agronomic and seed quality traits, (ii the interrelationship of population structure and the detected associations, and (iii candidate genes for the revealed associations. The diversity set used in this study consisted of 405 Brassica napus inbred lines which were genotyped using a 6K single nucleotide polymorphism (SNP array and phenotyped for agronomic and seed quality traits in field trials. In a genome-wide association study, we detected a total of 112 associations between SNPs and the seed quality traits as well as 46 SNP-trait associations for the agronomic traits with a P-value 100 and a sequence identity of > 70 % to A. thaliana or B. rapa could be found for the agronomic SNP-trait associations and 187 hits of potential candidate genes for the seed quality SNP-trait associations.
Sharma, Swarkar; Gao, Xiaochong; Londono, Douglas; Devroy, Shonn E.; Mauldin, Kristen N.; Frankel, Jessica T.; Brandon, January M.; Zhang, Dongping; Li, Quan-Zhen; Dobbs, Matthew B.; Gurnett, Christina A.; Grant, Struan F.A.; Hakonarson, Hakon; Dormans, John P.; Herring, John A.; Gordon, Derek; Wise, Carol A.
Adolescent idiopathic scoliosis (AIS) is an unexplained and common spinal deformity seen in otherwise healthy children. Its pathophysiology is poorly understood despite intensive investigation. Although genetic underpinnings are clear, replicated susceptibility loci that could provide insight into etiology have not been forthcoming. To address these issues, we performed genome-wide association studies (GWAS) of ∼327 000 single nucleotide polymorphisms (SNPs) in 419 AIS families. We found strongest evidence of association with chromosome 3p26.3 SNPs in the proximity of the CHL1 gene (P protein related to Robo3. Mutations in the Robo3 protein cause horizontal gaze palsy with progressive scoliosis (HGPPS), a rare disease marked by severe scoliosis. Other top associations in our GWAS were with SNPs in the DSCAM gene encoding an axon guidance protein in the same structural class with Chl1 and Robo3. We additionally found AIS associations with loci in CNTNAP2, supporting a previous study linking this gene with AIS. Cntnap2 is also of functional interest, as it interacts directly with L1 and Robo class proteins and participates in axon pathfinding. Our results suggest the relevance of axon guidance pathways in AIS susceptibility, although these findings require further study, particularly given the apparent genetic heterogeneity in this disease. PMID:21216876
Full Text Available The intestinal epithelium is the most rapidly self-renewing tissue in adult animals and maintained by intestinal stem cells (ISCs in both Drosophila and mammals. To comprehensively identify genes and pathways that regulate ISC fates, we performed a genome-wide transgenic RNAi screen in adult Drosophila intestine and identified 405 genes that regulate ISC maintenance and lineage-specific differentiation. By integrating these genes into publicly available interaction databases, we further developed functional networks that regulate ISC self-renewal, ISC proliferation, ISC maintenance of diploid status, ISC survival, ISC-to-enterocyte (EC lineage differentiation, and ISC-to-enteroendocrine (EE lineage differentiation. By comparing regulators among ISCs, female germline stem cells, and neural stem cells, we found that factors related to basic stem cell cellular processes are commonly required in all stem cells, and stem-cell-specific, niche-related signals are required only in the unique stem cell type. Our findings provide valuable insights into stem cell maintenance and lineage-specific differentiation.
Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L
We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.
Pottier, Cyril; Zhou, Xiaolai; Perkerson, Ralph B; Baker, Matt; Jenkins, Gregory D; Serie, Daniel J; Ghidoni, Roberta; Benussi, Luisa; Binetti, Giuliano; López de Munain, Adolfo; Zulaica, Miren; Moreno, Fermin; Le Ber, Isabelle; Pasquier, Florence; Hannequin, Didier; Sánchez-Valle, Raquel; Antonell, Anna; Lladó, Albert; Parsons, Tammee M; Finch, NiCole A; Finger, Elizabeth C; Lippa, Carol F; Huey, Edward D; Neumann, Manuela; Heutink, Peter; Synofzik, Matthis; Wilke, Carlo; Rissman, Robert A; Slawek, Jaroslaw; Sitek, Emilia; Johannsen, Peter; Nielsen, Jørgen E; Ren, Yingxue; van Blitterswijk, Marka; DeJesus-Hernandez, Mariely; Christopher, Elizabeth; Murray, Melissa E; Bieniek, Kevin F; Evers, Bret M; Ferrari, Camilla; Rollinson, Sara; Richardson, Anna; Scarpini, Elio; Fumagalli, Giorgio G; Padovani, Alessandro; Hardy, John; Momeni, Parastoo; Ferrari, Raffaele; Frangipane, Francesca; Maletta, Raffaele; Anfossi, Maria; Gallo, Maura; Petrucelli, Leonard; Suh, EunRan; Lopez, Oscar L; Wong, Tsz H; van Rooij, Jeroen G J; Seelaar, Harro; Mead, Simon; Caselli, Richard J; Reiman, Eric M; Noel Sabbagh, Marwan; Kjolby, Mads; Nykjaer, Anders; Karydas, Anna M; Boxer, Adam L; Grinberg, Lea T; Grafman, Jordan; Spina, Salvatore; Oblak, Adrian; Mesulam, M-Marsel; Weintraub, Sandra; Geula, Changiz; Hodges, John R; Piguet, Olivier; Brooks, William S; Irwin, David J; Trojanowski, John Q; Lee, Edward B; Josephs, Keith A; Parisi, Joseph E; Ertekin-Taner, Nilüfer; Knopman, David S; Nacmias, Benedetta; Piaceri, Irene; Bagnoli, Silvia; Sorbi, Sandro; Gearing, Marla; Glass, Jonathan; Beach, Thomas G; Black, Sandra E; Masellis, Mario; Rogaeva, Ekaterina; Vonsattel, Jean-Paul; Honig, Lawrence S; Kofler, Julia; Bruni, Amalia C; Snowden, Julie; Mann, David; Pickering-Brown, Stuart; Diehl-Schmid, Janine; Winkelmann, Juliane; Galimberti, Daniela; Graff, Caroline; Öijerstedt, Linn; Troakes, Claire; Al-Sarraj, Safa; Cruchaga, Carlos; Cairns, Nigel J; Rohrer, Jonathan D; Halliday, Glenda M; Kwok, John B; van Swieten, John C; White, Charles L; Ghetti, Bernardino; Murell, Jill R; Mackenzie, Ian R A; Hsiung, Ging-Yuek R; Borroni, Barbara; Rossi, Giacomina; Tagliavini, Fabrizio; Wszolek, Zbigniew K; Petersen, Ronald C; Bigio, Eileen H; Grossman, Murray; Van Deerlin, Vivianna M; Seeley, William W; Miller, Bruce L; Graff-Radford, Neill R; Boeve, Bradley F; Dickson, Dennis W; Biernacka, Joanna M; Rademakers, Rosa
Loss-of-function mutations in GRN cause frontotemporal lobar degeneration (FTLD). Patients with GRN mutations present with a uniform subtype of TAR DNA-binding protein 43 (TDP-43) pathology at autopsy (FTLD-TDP type A); however, age at onset and clinical presentation are variable, even within families. We aimed to identify potential genetic modifiers of disease onset and disease risk in GRN mutation carriers. The study was done in three stages: a discovery stage, a replication stage, and a meta-analysis of the discovery and replication data. In the discovery stage, genome-wide logistic and linear regression analyses were done to test the association of genetic variants with disease risk (case or control status) and age at onset in patients with a GRN mutation and controls free of neurodegenerative disorders. Suggestive loci (p<1 × 10 -5 ) were genotyped in a replication cohort of patients and controls, followed by a meta-analysis. The effect of genome-wide significant variants at the GFRA2 locus on expression of GFRA2 was assessed using mRNA expression studies in cerebellar tissue samples from the Mayo Clinic brain bank. The effect of the GFRA2 locus on progranulin concentrations was studied using previously generated ELISA-based expression data. Co-immunoprecipitation experiments in HEK293T cells were done to test for a direct interaction between GFRA2 and progranulin. Individuals were enrolled in the current study between Sept 16, 2014, and Oct 5, 2017. After quality control measures, statistical analyses in the discovery stage included 382 unrelated symptomatic GRN mutation carriers and 1146 controls free of neurodegenerative disorders collected from 34 research centres located in the USA, Canada, Australia, and Europe. In the replication stage, 210 patients (67 symptomatic GRN mutation carriers and 143 patients with FTLD without GRN mutations pathologically confirmed as FTLD-TDP type A) and 1798 controls free of neurodegenerative diseases were recruited
Khan, Meraj A; Sengupta, Jayasree; Mittal, Suneeta; Ghosh, Debabrata
In order to obtain a lead of the pathophysiology of endometriosis, genome-wide expressional analyses of eutopic and ectopic endometrium have earlier been reported, however, the effects of stages of severity and phases of menstrual cycle on expressional profiles have not been examined. The effect of genetic heterogeneity and fertility history on transcriptional activity was also not considered. In the present study, a genome-wide expression analysis of autologous, paired eutopic and ectopic endometrial samples obtained from fertile women (n=18) suffering from moderate (stage 3; n=8) or severe (stage 4; n=10) ovarian endometriosis during proliferative (n=13) and secretory (n=5) phases of menstrual cycle was performed. Individual pure RNA samples were subjected to Agilent's Whole Human Genome 44K microarray experiments. Microarray data were validated (Pcopy numbers by performing real time RT-PCR of seven (7) arbitrarily selected genes in all samples. The data obtained were subjected to differential expression (DE) and differential co-expression (DC) analyses followed by networks and enrichment analysis, and gene set enrichment analysis (GSEA). The reproducibility of prediction based on GSEA implementation of DC results was assessed by examining the relative expressions of twenty eight (28) selected genes in RNA samples obtained from fresh pool of eutopic and ectopic samples from confirmed ovarian endometriosis patients with stages 3 and 4 (n=4/each) during proliferative and secretory (n=4/each) phases. Higher clustering effect of pairing (cluster distance, cd=0.1) in samples from same individuals on expressional arrays among eutopic and ectopic samples was observed as compared to that of clinical stages of severity (cd=0.5) and phases of menstrual cycle (cd=0.6). Post hoc analysis revealed anomaly in the expressional profiles of several genes associated with immunological, neuracrine and endocrine functions and gynecological cancers however with no overt oncogenic
Angarica, Vladimir Espinosa; Del Sol, Antonio
Epigenetics play a central role in the regulation of many important cellular processes, and dysregulations at the epigenetic level could be the source of serious pathologies, such as neurological disorders affecting brain development, neurodegeneration, and intellectual disability. Despite significant technological advances for epigenetic profiling, there is still a need for a systematic understanding of how epigenetics shapes cellular circuitry, and disease pathogenesis. The development of accurate computational approaches for analyzing complex epigenetic profiles is essential for disentangling the mechanisms underlying cellular development, and the intricate interaction networks determining and sensing chromatin modifications and DNA methylation to control gene expression. In this chapter, we review the recent advances in the field of "computational epigenetics," including computational methods for processing different types of epigenetic data, prediction of chromatin states, and study of protein dynamics. We also discuss how "computational epigenetics" has complemented the fast growth in the generation of epigenetic data for uncovering the main differences and similarities at the epigenetic level between individuals and the mechanisms underlying disease onset and progression.
Full Text Available Genome-wide association studies (GWAS have identified hundreds of associated loci across many common diseases. Most risk variants identified by GWAS will merely be tags for as-yet-unknown causal variants. It is therefore possible that identification of the causal variant, by fine mapping, will identify alleles with larger effects on genetic risk than those currently estimated from GWAS replication studies. We show that under plausible assumptions, whilst the majority of the per-allele relative risks (RR estimated from GWAS data will be close to the true risk at the causal variant, some could be considerable underestimates. For example, for an estimated RR in the range 1.2-1.3, there is approximately a 38% chance that it exceeds 1.4 and a 10% chance that it is over 2. We show how these probabilities can vary depending on the true effects associated with low-frequency variants and on the minor allele frequency (MAF of the most associated SNP. We investigate the consequences of the underestimation of effect sizes for predictions of an individual's disease risk and interpret our results for the design of fine mapping experiments. Although these effects mean that the amount of heritability explained by known GWAS loci is expected to be larger than current projections, this increase is likely to explain a relatively small amount of the so-called "missing" heritability.
Schmutz et al., 2014). Brazil is the largest producer with an average annual production of. 3.5 million tons (MAPA, 2015). However, the grain yield in Brazil is considered low and several factors are related to this, as the adverse effects ...
The inheritance of most human diseases and agriculturally important traits is controlled by many genes with small effects. Identifying these genes, while simultaneously controlling false positives, is challenging. Among available statistical methods, the mixed linear model (MLM) has been the most fl...
Gary W Beecham
Full Text Available Alzheimer's disease (AD and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs, and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA, Lewy body disease (LBD, hippocampal sclerosis of the elderly (HS, and vascular brain injury (VBI. Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE. GalNAc transferase 7 (GALNT7, ATP-Binding Cassette, Sub-Family G (WHITE, Member 1 (ABCG1, and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2 was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related
Have, Christian Theil; Mørk, Søren
We introduce a new type of probabilistic sequence model, that model the sequential composition of reading frames of genes in a genome. Our approach extends gene finders with a model of the sequential composition of genes at the genome-level -- effectively producing a sequential genome annotation...... as output. The model can be used to obtain the most probable genome annotation based on a combination of i: a gene finder score of each gene candidate and ii: the sequence of the reading frames of gene candidates through a genome. The model --- as well as a higher order variant --- is developed and tested...... and are evaluated by the effect on prediction performance. Since bacterial gene finding to a large extent is a solved problem it forms an ideal proving ground for evaluating the explicit modeling of larger scale gene sequence composition of genomes. We conclude that the sequential composition of gene reading frames...
Gion, Jean-Marc; Hudson, Corey J; Lesur, Isabelle; Vaillancourt, René E; Potts, Brad M; Freeman, Jules S
Meiotic recombination is a fundamental evolutionary process. It not only generates diversity, but influences the efficacy of natural selection and genome evolution. There can be significant heterogeneity in recombination rates within and between species, however this variation is not well understood outside of a few model taxa, particularly in forest trees. Eucalypts are forest trees of global economic importance, and dominate many Australian ecosystems. We studied recombination rate in Eucalyptus globulus using genetic linkage maps constructed in 10 unrelated individuals, and markers anchored to the Eucalyptus reference genome. This experimental design provided the replication to study whether recombination rate varied between individuals and chromosomes, and allowed us to study the genomic attributes and population genetic parameters correlated with this variation. Recombination rate varied significantly between individuals (range = 2.71 to 3.51 centimorgans/megabase [cM/Mb]), but was not significantly influenced by sex or cross type (F1 vs. F2). Significant differences in recombination rate between chromosomes were also evident (range = 1.98 to 3.81 cM/Mb), beyond those which were due to variation in chromosome size. Variation in chromosomal recombination rate was significantly correlated with gene density (r = 0.94), GC content (r = 0.90), and the number of tandem duplicated genes (r = -0.72) per chromosome. Notably, chromosome level recombination rate was also negatively correlated with the average genetic diversity across six species from an independent set of samples (r = -0.75). The correlations with genomic attributes are consistent with findings in other taxa, however, the direction of the correlation between diversity and recombination rate is opposite to that commonly observed. We argue this is likely to reflect the interaction of selection and specific genome architecture of Eucalyptus. Interestingly, the differences amongst
Background Genome-scale RNA-interference (RNAi) screens are becoming ever more common gene discovery tools. However, whilst every screen identifies interacting genes, less attention has been given to how factors such as library design and post-screening bioinformatics may be effecting the data generated. Results Here we present a new genome-wide RNAi screen of the Drosophila JAK/STAT signalling pathway undertaken in the Sheffield RNAi Screening Facility (SRSF). This screen was carried out using a second-generation, computationally optimised dsRNA library and analysed using current methods and bioinformatic tools. To examine advances in RNAi screening technology, we compare this screen to a biologically very similar screen undertaken in 2005 with a first-generation library. Both screens used the same cell line, reporters and experimental design, with the SRSF screen identifying 42 putative regulators of JAK/STAT signalling, 22 of which verified in a secondary screen and 16 verified with an independent probe design. Following reanalysis of the original screen data, comparisons of the two gene lists allows us to make estimates of false discovery rates in the SRSF data and to conduct an assessment of off-target effects (OTEs) associated with both libraries. We discuss the differences and similarities between the resulting data sets and examine the relative improvements in gene discovery protocols. Conclusions Our work represents one of the first direct comparisons between first- and second-generation libraries and shows that modern library designs together with methodological advances have had a significant influence on genome-scale RNAi screens. PMID:23006893
Gu, Fei; Doderer, Mark S; Huang, Yi-Wen; Roa, Juan C; Goodfellow, Paul J; Kizer, E Lynette; Huang, Tim H M; Chen, Yidong
DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters. Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework. CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible
John P Masly
Full Text Available Postzygotic reproductive isolation is characterized by two striking empirical patterns. The first is Haldane's rule--the preferential inviability or sterility of species hybrids of the heterogametic (XY sex. The second is the so-called large X effect--substitution of one species's X chromosome for another's has a disproportionately large effect on hybrid fitness compared to similar substitution of an autosome. Although the first rule has been well-established, the second rule remains controversial. Here, we dissect the genetic causes of these two rules using a genome-wide introgression analysis of Drosophila mauritiana chromosome segments in an otherwise D. sechellia genetic background. We find that recessive hybrid incompatibilities outnumber dominant ones and that hybrid male steriles outnumber all other types of incompatibility, consistent with the dominance and faster-male theories of Haldane's rule, respectively. We also find that, although X-linked and autosomal introgressions are of similar size, most X-linked introgressions cause hybrid male sterility (60% whereas few autosomal introgressions do (18%. Our results thus confirm the large X effect and identify its proximate cause: incompatibilities causing hybrid male sterility have a higher density on the X chromosome than on the autosomes. We evaluate several hypotheses for the evolutionary cause of this excess of X-linked hybrid male sterility.
Masly, John P; Presgraves, Daven C
Postzygotic reproductive isolation is characterized by two striking empirical patterns. The first is Haldane's rule--the preferential inviability or sterility of species hybrids of the heterogametic (XY) sex. The second is the so-called large X effect--substitution of one species's X chromosome for another's has a disproportionately large effect on hybrid fitness compared to similar substitution of an autosome. Although the first rule has been well-established, the second rule remains controversial. Here, we dissect the genetic causes of these two rules using a genome-wide introgression analysis of Drosophila mauritiana chromosome segments in an otherwise D. sechellia genetic background. We find that recessive hybrid incompatibilities outnumber dominant ones and that hybrid male steriles outnumber all other types of incompatibility, consistent with the dominance and faster-male theories of Haldane's rule, respectively. We also find that, although X-linked and autosomal introgressions are of similar size, most X-linked introgressions cause hybrid male sterility (60%) whereas few autosomal introgressions do (18%). Our results thus confirm the large X effect and identify its proximate cause: incompatibilities causing hybrid male sterility have a higher density on the X chromosome than on the autosomes. We evaluate several hypotheses for the evolutionary cause of this excess of X-linked hybrid male sterility.
Bigdeli, Tim B.; Ripke, Stephan; Bacanu, Silviu-Alin; Lee, Sang Hong; Wray, Naomi R.; Gejman, Pablo V.; Rietschel, Marcella; Cichon, Sven; St Clair, David; Corvin, Aiden; Kirov, George; McQuillin, Andrew; Gurling, Hugh; Rujescu, Dan; Andreassen, Ole A.; Werge, Thomas; Blackwood, Douglas H.R.; Pato, Carlos N.; Pato, Michele T.; Malhotra, Anil K.; O’Donovan, Michael C.; Kendler, Kenneth S.; Fanous, Ayman H.
Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N = 978), cases reporting no such family history (N = 4,503), and unscreened controls (N = 8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke’s R2 = 0.0021; P = 0.00331; P-value threshold history positive compared to family history negative cases (0.32 and 0.22, respectively; P = 0.031).We found suggestive evidence of allelic effects detectable in large GWAS of schizophrenia that might be specific to particular family history subgroups. However, consideration of a polygenic risk score indicated a significant enrichment among family history positive cases for common allelic effects. Familial illness might, therefore, represent a more heritable form of schizophrenia, as suggested by
Zheutlin, Amanda B; Viehman, Rachael W; Fortgang, Rebecca; Borg, Jacqueline; Smith, Desmond J; Suvisaari, Jaana; Therman, Sebastian; Hultman, Christina M; Cannon, Tyrone D
We performed a whole-genome expression study to clarify the nature of the biological processes mediating between inherited genetic variations and cognitive dysfunction in schizophrenia. Gene expression was assayed from peripheral blood mononuclear cells using Illumina Human WG6 v3.0 chips in twins discordant for schizophrenia or bipolar disorder and control twins. After quality control, expression levels of 18,559 genes were screened for association with the California Verbal Learning Test (CVLT) performance, and any memory-related probes were then evaluated for variation by diagnostic status in the discovery sample (N = 190), and in an independent replication sample (N = 73). Heritability of gene expression using the twin design was also assessed. After Bonferroni correction (p schizophrenia patients, with comparable effect sizes in the same direction in the replication sample. For 41 of these 43 transcripts, expression levels were heritable. Nearly all identified genes contain common or de novo mutations associated with schizophrenia in prior studies. Genes increasing risk for schizophrenia appear to do so in part via effects on signaling cascades influencing memory. The genes implicated in these processes are enriched for those related to RNA processing and DNA replication and include genes influencing G-protein coupled signal transduction, cytokine signaling, and oligodendrocyte function. (c) 2015 APA, all rights reserved).
Tsai, Chia-Ti; Hsieh, Chia-Shan; Chang, Sheng-Nan; Chuang, Eric Y.; Ueng, Kwo-Chang; Tsai, Chin-Feng; Lin, Tsung-Hsien; Wu, Cho-Kai; Lee, Jen-Kuang; Lin, Lian-Yu; Wang, Yi-Chih; Yu, Chih-Chieh; Lai, Ling-Ping; Tseng, Chuen-Den; Hwang, Juey-Jen; Chiang, Fu-Tien; Lin, Jiunn-Lee
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Previous genome-wide association studies had identified single-nucleotide polymorphisms in several genomic regions to be associated with AF. In human genome, copy number variations (CNVs) are known to contribute to disease susceptibility. Using a genome-wide multistage approach to identify AF susceptibility CNVs, we here show a common 4,470-bp diallelic CNV in the first intron of potassium interacting channel 1 gene (KCNIP1) is strongly associated with AF in Taiwanese populations (odds ratio=2.27 for insertion allele; P=6.23 × 10−24). KCNIP1 insertion is associated with higher KCNIP1 mRNA expression. KCNIP1-encoded protein potassium interacting channel 1 (KCHIP1) is physically associated with potassium Kv channels and modulates atrial transient outward current in cardiac myocytes. Overexpression of KCNIP1 results in inducible AF in zebrafish. In conclusions, a common CNV in KCNIP1 gene is a genetic predictor of AF risk possibly pointing to a functional pathway. PMID:26831368
Tielbeek, Jorim J; Johansson, Ada; Polderman, Tinca J C; Rautiainen, Marja-Riitta; Jansen, Philip; Taylor, Michelle; Tong, Xiaoran; Lu, Qing; Burt, Alexandra S; Tiemeier, Henning; Viding, Essi; Plomin, Robert; Martin, Nicholas G; Heath, Andrew C; Madden, Pamela A F; Montgomery, Grant; Beaver, Kevin M; Waldman, Irwin; Gelernter, Joel; Kranzler, Henry R; Farrer, Lindsay A; Perry, John R B; Munafò, Marcus; LoParo, Devon; Paunio, Tiina; Tiihonen, Jari; Mous, Sabine E; Pappa, Irene; de Leeuw, Christiaan; Watanabe, Kyoko; Hammerschlag, Anke R; Salvatore, Jessica E; Aliev, Fazil; Bigdeli, Tim B; Dick, Danielle; Faraone, Stephen V; Popma, Arne; Medland, Sarah E; Posthuma, Danielle
Antisocial behavior (ASB) places a large burden on perpetrators, survivors, and society. Twin studies indicate that half of the variation in this trait is genetic. Specific causal genetic variants have, however, not been identified. To estimate the single-nucleotide polymorphism-based heritability of ASB; to identify novel genetic risk variants, genes, or biological pathways; to test for pleiotropic associations with other psychiatric traits; and to reevaluate the candidate gene era data through the Broad Antisocial Behavior Consortium. Genome-wide association data from 5 large population-based cohorts and 3 target samples with genome-wide genotype and ASB data were used for meta-analysis from March 1, 2014, to May 1, 2016. All data sets used quantitative phenotypes, except for the Finnish Crime Study, which applied a case-control design (370 patients and 5850 control individuals). This study adopted relatively broad inclusion criteria to achieve a quantitative measure of ASB derived from multiple measures, maximizing the sample size over different age ranges. The discovery samples comprised 16 400 individuals, whereas the target samples consisted of 9381 individuals (all individuals were of European descent), including child and adult samples (mean age range, 6.7-56.1 years). Three promising loci with sex-discordant associations were found (8535 female individuals, chromosome 1: rs2764450, chromosome 11: rs11215217; 7772 male individuals, chromosome X, rs41456347). Polygenic risk score analyses showed prognostication of antisocial phenotypes in an independent Finnish Crime Study (2536 male individuals and 3684 female individuals) and shared genetic origin with conduct problems in a population-based sample (394 male individuals and 431 female individuals) but not with conduct disorder in a substance-dependent sample (950 male individuals and 1386 female individuals) (R2 = 0.0017 in the most optimal model, P = 0.03). Significant inverse genetic correlation
Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through
Yang, Guanhua; Billings, Gabriel; Hubbard, Troy P; Park, Joseph S; Yin Leung, Ka; Liu, Qin; Davis, Brigid M; Zhang, Yuanxing; Wang, Qiyao; Waldor, Matthew K
Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida 's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses. IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen
Full Text Available Abstract Background Insect bite hypersensitivity is a common allergic disease in horse populations worldwide. Insect bite hypersensitivity is affected by both environmental and genetic factors. However, little is known about genes contributing to the genetic variance associated with insect bite hypersensitivity. Therefore, the aim of our study was to identify and quantify genomic associations with insect bite hypersensitivity in Shetland pony mares and Icelandic horses in the Netherlands. Methods Data on 200 Shetland pony mares and 146 Icelandic horses were collected according to a matched case–control design. Cases and controls were matched on various factors (e.g. region, sire to minimize effects of population stratification. Breed-specific genome-wide association studies were performed using 70 k single nucleotide polymorphisms genotypes. Bayesian variable selection method Bayes-C with a threshold model implemented in GenSel software was applied. A 1 Mb non-overlapping window approach that accumulated contributions of adjacent single nucleotide polymorphisms was used to identify associated genomic regions. Results The percentage of variance explained by all single nucleotide polymorphisms was 13% in Shetland pony mares and 28% in Icelandic horses. The 20 non-overlapping windows explaining the largest percentages of genetic variance were found on nine chromosomes in Shetland pony mares and on 14 chromosomes in Icelandic horses. Overlap in identified associated genomic regions between breeds would suggest interesting candidate regions to follow-up on. Such regions common to both breeds (within 15 Mb were found on chromosomes 3, 7, 11, 20 and 23. Positional candidate genes within 2 Mb from the associated windows were identified on chromosome 20 in both breeds. Candidate genes are within the equine lymphocyte antigen class II region, which evokes an immune response by recognizing many foreign molecules. Conclusions The genome-wide association
Yue, Jia-Xing; Li, Jinpeng; Wang, Dan; Araki, Hitoshi; Tian, Dacheng; Yang, Sihai
Rates of molecular evolution vary widely among species. While significant deviations from molecular clock have been found in many taxa, effects of life histories on molecular evolution are not fully understood. In plants, annual/perennial life history traits have long been suspected to influence the evolutionary rates at the molecular level. To date, however, the number of genes investigated on this subject is limited and the conclusions are mixed. To evaluate the possible heterogeneity in evolutionary rates between annual and perennial plants at the genomic level, we investigated 85 nuclear housekeeping genes, 10 non-housekeeping families, and 34 chloroplast genes using the genomic data from model plants including Arabidopsis thaliana and Medicago truncatula for annuals and grape (Vitis vinifera) and popular (Populus trichocarpa) for perennials. According to the cross-comparisons among the four species, 74-82% of the nuclear genes and 71-97% of the chloroplast genes suggested higher rates of molecular evolution in the two annuals than those in the two perennials. The significant heterogeneity in evolutionary rate between annuals and perennials was consistently found both in nonsynonymous sites and synonymous sites. While a linear correlation of evolutionary rates in orthologous genes between species was observed in nonsynonymous sites, the correlation was weak or invisible in synonymous sites. This tendency was clearer in nuclear genes than in chloroplast genes, in which the overall evolutionary rate was small. The slope of the regression line was consistently lower than unity, further confirming the higher evolutionary rate in annuals at the genomic level. The higher evolutionary rate in annuals than in perennials appears to be a universal phenomenon both in nuclear and chloroplast genomes in the four dicot model plants we investigated. Therefore, such heterogeneity in evolutionary rate should result from factors that have genome-wide influence, most likely those
Full Text Available Metals are major contaminants that influence human health. Many metals have physiologic roles, but excessive levels can be harmful. Advances in technology have made toxicogenomic analyses possible to characterize the effects of metal exposure on the entire genome. Much of what is known about cellular responses to metals has come from mammalian systems; however the use of non-mammalian species is gaining wider attention. Caenorhabditis elegans (C. elegans is a small round worm whose genome has been fully sequenced and its development from egg to adult is well characterized. It is an attractive model for high throughput screens due to its short lifespan, ease of genetic mutability, low cost and high homology with humans. Research performed in C. elegans has led to insights in apoptosis, gene expression and neurodegeneration, all of which can be altered by metal exposure. Additionally, by using worms one can potentially study how the mechanisms that underline differential responses to metals in nematodes and humans, allowing for identification of novel pathways and therapeutic targets. In this review, toxicogenomic studies performed in C. elegans exposed to various metals will be discussed, highlighting how this non-mammalian system can be utilized to study cellular processes and pathways induced by metals. Recent work focusing on neurodegeneration in Parkinson’s disease will be discussed as an example of the usefulness of genetic screens in C. elegans and the novel findings that can be produced.
Cristina, Juan; Moreno, Pilar; Moratorio, Gonzalo; Musto, Héctor
Ebola virus (EBOV) is a member of the family Filoviridae and its genome consists of a 19-kb, single-stranded, negative sense RNA. EBOV is subdivided into five distinct species with different pathogenicities, being Zaire ebolavirus (ZEBOV) the most lethal species. The interplay of codon usage among viruses and their hosts is expected to affect overall viral survival, fitness, evasion from host's immune system and evolution. In the present study, we performed comprehensive analyses of codon usage and composition of ZEBOV. Effective number of codons (ENC) indicates that the overall codon usage among ZEBOV strains is slightly biased. Different codon preferences in ZEBOV genes in relation to codon usage of human genes were found. Highly preferred codons are all A-ending triplets, which strongly suggests that mutational bias is a main force shaping codon usage in ZEBOV. Dinucleotide composition also plays a role in the overall pattern of ZEBOV codon usage. ZEBOV does not seem to use the most abundant tRNAs present in the human cells for most of their preferred codons. Copyright © 2014 Elsevier B.V. All rights reserved.
Feng, Sheng; Wang, Shengchu; Chen, Chia-Cheng; Lan, Lan
In designing genome-wide association (GWA) studies it is important to calculate statistical power. General statistical power calculation procedures for quantitative measures often require information concerning summary statistics of distributions such as mean and variance. However, with genetic studies, the effect size of quantitative traits is traditionally expressed as heritability, a quantity defined as the amount of phenotypic variation in the population that can be ascribed to the genetic variants among individuals. Heritability is hard to transform into summary statistics. Therefore, general power calculation procedures cannot be used directly in GWA studies. The development of appropriate statistical methods and a user-friendly software package to address this problem would be welcomed. This paper presents GWAPower, a statistical software package of power calculation designed for GWA studies with quantitative traits, where genetic effect is defined as heritability. Based on several popular one-degree-of-freedom genetic models, this method avoids the need to specify the non-centrality parameter of the F-distribution under the alternative hypothesis. Therefore, it can use heritability information directly without approximation. In GWAPower, the power calculation can be easily adjusted for adding covariates and linkage disequilibrium information. An example is provided to illustrate GWAPower, followed by discussions. GWAPower is a user-friendly free software package for calculating statistical power based on heritability in GWA studies with quantitative traits. The software is freely available at: http://dl.dropbox.com/u/10502931/GWAPower.zip.
Full Text Available As genome-wide association studies (GWAS are becoming more popular, two approaches, among others, could be considered in order to improve statistical power for identifying genes contributing subtle to moderate effects to human diseases. The first approach is to increase sample size, which could be achieved by combining both unrelated and familial subjects together. The second approach is to jointly analyze multiple correlated traits. In this study, by extending generalized estimating equations (GEEs, we propose a simple approach for performing univariate or multivariate association tests for the combined data of unrelated subjects and nuclear families. In particular, we correct for population stratification by integrating principal component analysis and transmission disequilibrium test strategies. The proposed method allows for multiple siblings as well as missing parental information. Simulation studies show that the proposed test has improved power compared to two popular methods, EIGENSTRAT and FBAT, by analyzing the combined data, while correcting for population stratification. In addition, joint analysis of bivariate traits has improved power over univariate analysis when pleiotropic effects are present. Application to the Genetic Analysis Workshop 16 (GAW16 data sets attests to the feasibility and applicability of the proposed method.
Lewis, Cecil M
This study examines a genome-wide dataset of 678 Short Tandem Repeat loci characterized in 444 individuals representing 29 Native American populations as well as the Tundra Netsi and Yakut populations from Siberia. Using these data, the study tests four current hypotheses regarding the hierarchical distribution of neutral genetic variation in native South American populations: (1) the western region of South America harbors more variation than the eastern region of South America, (2) Central American and western South American populations cluster exclusively, (3) populations speaking the Chibchan-Paezan and Equatorial-Tucanoan language stock emerge as a group within an otherwise South American clade, (4) Chibchan-Paezan populations in Central America emerge together at the tips of the Chibchan-Paezan cluster. This study finds that hierarchical models with the best fit place Central American populations, and populations speaking the Chibchan-Paezan language stock, at a basal position or separated from the South American group, which is more consistent with a serial founder effect into South America than that previously described. Western (Andean) South America is found to harbor similar levels of variation as eastern (Equatorial-Tucanoan and Ge-Pano-Carib) South America, which is inconsistent with an initial west coast migration into South America. Moreover, in all relevant models, the estimates of genetic diversity within geographic regions suggest a major bottleneck or founder effect occurring within the North American subcontinent, before the peopling of Central and South America. 2009 Wiley-Liss, Inc.
Genome-Wide Association Mapping for Intelligence in Military Working Dogs: Canine Cohort, Canine Intelligence Assessment Regimen, Genome-Wide Single Nucleotide Polymorphism (SNP) Typing, and Unsupervised Classification Algorithm for Genome-Wide Association Data Analysis
SNP Array v2. A ‘proof-of-concept’ advanced data mining algorithm for unsupervised analysis of genome-wide association study (GWAS) dataset was... Opal F AUS Yes U141 Peggs F AUS Yes U142 Taxi F AUS Yes U143 Riso MI MAL Yes U144 Szarik MI GSD Yes U145 Astor MI MAL Yes U146 Roy MC MAL Yes... mining of genetic studies in general, and especially GWAS. As a proof-of-concept, a classification analysis of the WG SNP typing dataset of a
Sreekumar G Pillai
Full Text Available There is considerable variability in the susceptibility of smokers to develop chronic obstructive pulmonary disease (COPD. The only known genetic risk factor is severe deficiency of alpha(1-antitrypsin, which is present in 1-2% of individuals with COPD. We conducted a genome-wide association study (GWAS in a homogenous case-control cohort from Bergen, Norway (823 COPD cases and 810 smoking controls and evaluated the top 100 single nucleotide polymorphisms (SNPs in the family-based International COPD Genetics Network (ICGN; 1891 Caucasian individuals from 606 pedigrees study. The polymorphisms that showed replication were further evaluated in 389 subjects from the US National Emphysema Treatment Trial (NETT and 472 controls from the Normative Aging Study (NAS and then in a fourth cohort of 949 individuals from 127 extended pedigrees from the Boston Early-Onset COPD population. Logistic regression models with adjustments of covariates were used to analyze the case-control populations. Family-based association analyses were conducted for a diagnosis of COPD and lung function in the family populations. Two SNPs at the alpha-nicotinic acetylcholine receptor (CHRNA 3/5 locus were identified in the genome-wide association study. They showed unambiguous replication in the ICGN family-based analysis and in the NETT case-control analysis with combined p-values of 1.48 x 10(-10, (rs8034191 and 5.74 x 10(-10 (rs1051730. Furthermore, these SNPs were significantly associated with lung function in both the ICGN and Boston Early-Onset COPD populations. The C allele of the rs8034191 SNP was estimated to have a population attributable risk for COPD of 12.2%. The association of hedgehog interacting protein (HHIP locus on chromosome 4 was also consistently replicated, but did not reach genome-wide significance levels. Genome-wide significant association of the HHIP locus with lung function was identified in the Framingham Heart study (Wilk et al., companion article
Krapohl, E; Plomin, R
One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.
Full Text Available Genome-wide association studies (GWAS are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI, a network-based method that combines GWAS data with human protein-protein interaction data (PPI. NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call 'trait prioritized sub-networks.' As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn's disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn's disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.
Akula, Nirmala; Baranova, Ancha; Seto, Donald; Solka, Jeffrey; Nalls, Michael A.; Singleton, Andrew; Ferrucci, Luigi; Tanaka, Toshiko; Bandinelli, Stefania; Cho, Yoon Shin; Kim, Young Jin; Lee, Jong-Young; Han, Bok-Ghee; McMahon, Francis J.
Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses. PMID:21915301
Mattheisen, Manuel; Samuels, Jack F.; Wang, Ying; Greenberg, Benjamin D.; Fyer, Abby J.; McCracken, James T.; Geller, Daniel A.; Murphy, Dennis L.; Knowles, James A.; Grados, Marco A.; Riddle, Mark A.; Rasmussen, Steven A.; McLaughlin, Nicole C.; Nurmi, Erica; Askland, Kathleen D.; Qin, Hai-De; Cullen, Bernadette A.; Piacentini, John; Pauls, David L.; Bienvenu, O. Joseph; Stewart, S. Evelyn; Liang, Kung-Yee; Goes, Fernando S.; Maher, Brion; Pulver, Ann E.; Shugart, Yin-Yao; Valle, David; Lange, Cristoph; Nestadt, Gerald
Obsessive-compulsive disorder (OCD) is a psychiatric condition characterized by intrusive thoughts and urges and repetitive, intentional behaviors that cause significant distress and impair functioning. The OCD Collaborative Genetics Association Study (OCGAS) is comprised of comprehensively assessed OCD patients, with an early age of OCD onset. After application of a stringent quality control protocol, a total of 1 065 families (containing 1 406 patients with OCD), combined with population-based samples (resulting in a total sample of 5 061 individuals), were studied. An integrative analyses pipeline was utilized, involving association testing at SNP- and gene-levels (via a hybrid approach that allowed for combined analyses of the family- and population-based data). The smallest P-value was observed for a marker on chromosome 9 (near PTPRD, P=4.13×10−7). Pre-synaptic PTPRD promotes the differentiation of glutamatergic synapses and interacts with SLITRK3. Together, both proteins selectively regulate the development of inhibitory GABAergic synapses. Although no SNPs were identified as associated with OCD at genome-wide significance level, follow-up analyses of GWAS signals from a previously published OCD study identified significant enrichment (P=0.0176). Secondary analyses of high confidence interaction partners of DLGAP1 and GRIK2 (both showing evidence for association in our follow-up and the original GWAS study) revealed a trend of association (P=0.075) for a set of genes such as NEUROD6, SV2A, GRIA4, SLC1A2, and PTPRD. Analyses at the gene-level revealed association of IQCK and C16orf88 (both P<1×10−6, experiment-wide significant), as well as OFCC1 (P=6.29×10−5). The suggestive findings in this study await replication in larger samples. PMID:24821223
Full Text Available Microsporidia have attracted much attention because they infect a variety of species ranging from protists to mammals, including immunocompromised patients with AIDS or cancer. Aside from the study on Nosema ceranae, few works have focused on elucidating the mechanism in host response to microsporidia infection. Nosema bombycis is a pathogen of silkworm pébrine that causes great economic losses to the silkworm industry. Detailed understanding of the host (Bombyx mori response to infection by N. bombycis is helpful for prevention of this disease. A genome-wide survey of the gene expression profile at 2, 4, 6 and 8 days post-infection by N. bombycis was performed and results showed that 64, 244, 1,328, 1,887 genes were induced, respectively. Up to 124 genes, which are involved in basal metabolism pathways, were modulated. Notably, B. mori genes that play a role in juvenile hormone synthesis and metabolism pathways were induced, suggesting that the host may accumulate JH as a response to infection. Interestingly, N. bombycis can inhibit the silkworm serine protease cascade melanization pathway in hemolymph, which may be due to the secretion of serpins in the microsporidia. N. bombycis also induced up-regulation of several cellular immune factors, in which CTL11 has been suggested to be involved in both spore recognition and immune signal transduction. Microarray and real-time PCR analysis indicated the activation of silkworm Toll and JAK/STAT pathways. The notable up-regulation of antimicrobial peptides, including gloverins, lebocins and moricins, strongly indicated that antimicrobial peptide defense mechanisms were triggered to resist the invasive microsporidia. An analysis of N. bombycis-specific response factors suggested their important roles in anti-microsporidia defense. Overall, this study primarily provides insight into the potential molecular mechanisms for the host-parasite interaction between B. mori and N. bombycis and may provide a
Full Text Available The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes. In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.
Randall, Joshua C.; Winkler, Thomas W.; Kutalik, Zoltán; Berndt, Sonja I.; 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, Asa; 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.
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
Randall, Joshua C; Winkler, Thomas W; Kutalik, Zoltán
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...
Randall, J.C.; Winkler, T.W.; Kutalik, Z.; Berndt, S.I.; Jackson, A.U.; Monda, K.L.; Kilpelainen, T.O.; Esko, T.; Magi, R.; Li, S.; Workalemahu, T.; Feitosa, M.F.; Croteau-Chonka, D.C.; Day, F.R.; Fall, T.; Ferreira, T.; Gustafsson, S.; Locke, A.E.; Mathieson, I.; Scherag, A.; Vedantam, S.; Wood, A.R.; Liang, L.; Steinthorsdottir, V.; Thorleifsson, G.; Dermitzakis, E.T.; Dimas, A.S.; Karpe, F.; Min, J.L.; Nicholson, G.; Clegg, D.J.; Person, T.; Krohn, J.P.; Bauer, S.; Buechler, C.; Eisinger, K.; Bonnefond, A.; Froguel, P.; Hottenga, J.J.; Prokopenko, I.; Waite, L.L.; Harris, T.B.; Smith, A.V.; Shuldiner, A.R.; McArdle, W.L.; Caulfield, M.J.; Munroe, P.B.; Gronberg, H.; Chen, Y.D.; Li, G.; Beckmann, J.S.; Johnson, T.; Thorsteinsdottir, U.; Teder-Laving, M.; Khaw, K.T.; Wareham, N.J.; Zhao, J.H.; Amin, N.; Oostra, B.A.; Kraja, A.T.; Province, M.A.; Cupples, L.A.; Heard-Costa, N.L.; Kaprio, J.; Ripatti, S.; Surakka, I.; Collins, F.S.; Saramies, J.; Tuomilehto, J.; Jula, A.; Salomaa, V.; Erdmann, J.; Hengstenberg, C.; Loley, C.; Schunkert, H.; Lamina, C.; Wichmann, H.E.; Albrecht, E.; Gieger, C.; Hicks, A.A.; Johansson, A; Pramstaller, P.P.; Kathiresan, S.; Speliotes, E.K.; Penninx, B.; Hartikainen, A.L.; Jarvelin, M.R.; Gyllensten, U.; Boomsma, D.I.; Campbell, H.; Wilson, J.F.; Chanock, S.J.; Farrall, M.; Goel, A.; Medina-Gomez, C.; Rivadeneira, F.; Estrada, K.; Uitterlinden, A.G.; Heijer, M. den; Kiemeney, L.A.L.M.; et al.,
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
Randall, Joshua C; Winkler, Thomas W; Kutalik, Zoltán; Berndt, Sonja I; 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; Smith, Albert Vernon; Zhao, Jing Hua; Penninx, Brenda; Nolte, Ilja M; Snieder, Harold; Van der Klauw, Melanie M; Van Vliet-Ostaptchouk, Jana V; Bakker, Stephan J L; Mateo Leach, Irene; Navis, Gerjan; van der Harst, Pim; Kumari, Meena
Derks, E. M.; Zwinderman, A. H.; Gamazon, E. R.
Population divergence impacts the degree of population stratification in Genome Wide Association Studies. We aim to: (i) investigate type-I error rate as a function of population divergence (FST) in multi-ethnic (admixed) populations; (ii) evaluate the statistical power and effect size estimates;
Peter K Joshi
Full Text Available The analysis of less common variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association. We show that addition of population-specific exome sequence data to global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1-10% in two very different European populations. The imputation improvement corresponds to an increase in effective sample size of 28-38%, for SNPs with a minor allele frequency in the range 1-3%.
Fatemifar, Ghazaleh; Hoggart, Clive J; Paternoster, Lavinia
Twin and family studies indicate that the timing of primary tooth eruption is highly heritable, with estimates typically exceeding 80%. To identify variants involved in primary tooth eruption, we performed a population-based genome-wide association study of 'age at first tooth' and 'number of teeth......' using 5998 and 6609 individuals, respectively, from the Avon Longitudinal Study of Parents and Children (ALSPAC) and 5403 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966). We tested 2 446 724 SNPs imputed in both studies. Analyses were controlled for the effect of gestational age, sex...
Sahana, Goutam; Mailund, Thomas; Lund, Mogens Sandø
be extended to incorporate other effects in a straightforward and rigorous fashion. Here, we present a complementary approach, called ‘GENMIX (genealogy based mixed model)’ which combines advantages from two powerful GWAS methods: genealogy-based haplotype grouping and MMA. Subjects and Methods: We validated......Introduction: The state-of-the-art for dealing with multiple levels of relationship among the samples in genome-wide association studies (GWAS) is unified mixed model analysis (MMA). This approach is very flexible, can be applied to both family-based and population-based samples, and can...
Anney, Richard; Klei, Lambertus; Pinto, Dalila; Regan, Regina; Conroy, Judith; Magalhaes, Tiago R.; Correia, Catarina; Abrahams, Brett S.; Sykes, Nuala; Pagnamenta, Alistair T.; Almeida, Joana; Bacchelli, Elena; Bailey, Anthony J.; Baird, Gillian; Battaglia, Agatino; Berney, Tom; Bolshakova, Nadia; Bölte, Sven; Bolton, Patrick F.; Bourgeron, Thomas; Brennan, Sean; Brian, Jessica; Carson, Andrew R.; Casallo, Guillermo; Casey, Jillian; Chu, Su H.; Cochrane, Lynne; Corsello, Christina; Crawford, Emily L.; Crossett, Andrew; Dawson, Geraldine; de Jonge, Maretha; Delorme, Richard; Drmic, Irene; Duketis, Eftichia; Duque, Frederico; Estes, Annette; Farrar, Penny; Fernandez, Bridget A.; Folstein, Susan E.; Fombonne, Eric; Freitag, Christine M.; Gilbert, John; Gillberg, Christopher; Glessner, Joseph T.; Goldberg, Jeremy; Green, Jonathan; Guter, Stephen J.; Hakonarson, Hakon; Heron, Elizabeth A.; Hill, Matthew; Holt, Richard; Howe, Jennifer L.; Hughes, Gillian; Hus, Vanessa; Igliozzi, Roberta; Kim, Cecilia; Klauck, Sabine M.; Kolevzon, Alexander; Korvatska, Olena; Kustanovich, Vlad; Lajonchere, Clara M.; Lamb, Janine A.; Laskawiec, Magdalena; Leboyer, Marion; Le Couteur, Ann; Leventhal, Bennett L.; Lionel, Anath C.; Liu, Xiao-Qing; Lord, Catherine; Lotspeich, Linda; Lund, Sabata C.; Maestrini, Elena; Mahoney, William; Mantoulan, Carine; Marshall, Christian R.; McConachie, Helen; McDougle, Christopher J.; McGrath, Jane; McMahon, William M.; Melhem, Nadine M.; Merikangas, Alison; Migita, Ohsuke; Minshew, Nancy J.; Mirza, Ghazala K.; Munson, Jeff; Nelson, Stanley F.; Noakes, Carolyn; Noor, Abdul; Nygren, Gudrun; Oliveira, Guiomar; Papanikolaou, Katerina; Parr, Jeremy R.; Parrini, Barbara; Paton, Tara; Pickles, Andrew; Piven, Joseph; Posey, David J; Poustka, Annemarie; Poustka, Fritz; Prasad, Aparna; Ragoussis, Jiannis; Renshaw, Katy; Rickaby, Jessica; Roberts, Wendy; Roeder, Kathryn; Roge, Bernadette; Rutter, Michael L.; Bierut, Laura J.; Rice, John P.; Salt, Jeff; Sansom, Katherine; Sato, Daisuke; Segurado, Ricardo; Senman, Lili; Shah, Naisha; Sheffield, Val C.; Soorya, Latha; Sousa, Inês; Stoppioni, Vera; Strawbridge, Christina; Tancredi, Raffaella; Tansey, Katherine; Thiruvahindrapduram, Bhooma; Thompson, Ann P.; Thomson, Susanne; Tryfon, Ana; Tsiantis, John; Van Engeland, Herman; Vincent, John B.; Volkmar, Fred; Wallace, Simon; Wang, Kai; Wang, Zhouzhi; Wassink, Thomas H.; Wing, Kirsty; Wittemeyer, Kerstin; Wood, Shawn; Yaspan, Brian L.; Zurawiecki, Danielle; Zwaigenbaum, Lonnie; Betancur, Catalina; Buxbaum, Joseph D.; Cantor, Rita M.; Cook, Edwin H.; Coon, Hilary; Cuccaro, Michael L.; Gallagher, Louise; Geschwind, Daniel H.; Gill, Michael; Haines, Jonathan L.; Miller, Judith; Monaco, Anthony P.; Nurnberger, John I.; Paterson, Andrew D.; Pericak-Vance, Margaret A.; Schellenberg, Gerard D.; Scherer, Stephen W.; Sutcliffe, James S.; Szatmari, Peter; Vicente, Astrid M.; Vieland, Veronica J.; Wijsman, Ellen M.; Devlin, Bernie; Ennis, Sean; Hallmayer, Joachim
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C. PMID:20663923
Full Text Available Abstract Background Cancer development is accompanied by genetic phenomena like deletion and amplification of chromosome parts or alterations of chromatin structure. It is expected that these mechanisms have a strong effect on regional gene expression. Results We investigated genome-wide gene expression in colorectal carcinoma (CRC and normal epithelial tissues from 25 patients using oligonucleotide arrays. This allowed us to identify 81 distinct chromosomal islands with aberrant gene expression. Of these, 38 islands show a gain in expression and 43 a loss of expression. In total, 7.892 genes (25.3% of all human genes are located in aberrantly expressed islands. Many chromosomal regions that are linked to hereditary colorectal cancer show deregulated expression. Also, many known tumor genes localize to chromosomal islands of misregulated expression in CRC. Conclusion An extensive comparison with published CGH data suggests that chromosomal regions known for frequent deletions in colon cancer tend to show reduced expression. In contrast, regions that are often amplified in colorectal tumors exhibit heterogeneous expression patterns: even show a decrease of mRNA expression. Because for several islands of deregulated expression chromosomal aberrations have never been observed, we speculate that additional mechanisms (like abnormal states of regional chromatin also have a substantial impact on the formation of co-expression islands in colorectal carcinoma.
Full Text Available Glioblastoma Multiforme (GBM cells are highly invasive, infiltrating into the surrounding normal brain tissue, making it impossible to completely eradicate GBM tumors by surgery or radiation. Increasing evidence also shows that these migratory cells are highly resistant to cytotoxic reagents, but decreasing their migratory capability can re-sensitize them to chemotherapy. These evidences suggest that the migratory cell population may serve as a better therapeutic target for more effective treatment of GBM. In order to understand the regulatory mechanism underlying the motile phenotype, we carried out a genome-wide RNAi screen for genes inhibiting the migration of GBM cells. The screening identified a total of twenty-five primary hits; seven of them were confirmed by secondary screening. Further study showed that three of the genes, FLNA, KHSRP and HCFC1, also functioned in vivo, and knocking them down caused multifocal tumor in a mouse model. Interestingly, two genes, KHSRP and HCFC1, were also found to be correlated with the clinical outcome of GBM patients. These two genes have not been previously associated with cell migration.
Beecham, Ashley; Dong, Chuanhui; Wright, Clinton B; Dueker, Nicole; Brickman, Adam M; Wang, Liyong; DeCarli, Charles; Blanton, Susan H; Rundek, Tatjana; Mayeux, Richard; Sacco, Ralph L
To investigate genetic variants influencing white matter hyperintensities (WMHs) in the understudied Hispanic population. Using 6.8 million single nucleotide polymorphisms (SNPs), we conducted a genome-wide association study (GWAS) to identify SNPs associated with WMH volume (WMHV) in 922 Hispanics who underwent brain MRI as a cross-section of 2 community-based cohorts in the Northern Manhattan Study and the Washington Heights-Inwood Columbia Aging Project. Multiple linear modeling with PLINK was performed to examine the additive genetic effects on ln(WMHV) after controlling for age, sex, total intracranial volume, and principal components of ancestry. Gene-based tests of association were performed using VEGAS. Replication was performed in independent samples of Europeans, African Americans, and Asians. From the SNP analysis, a total of 17 independent SNPs in 7 genes had suggestive evidence of association with WMHV in Hispanics ( p < 1 × 10 -5 ) and 5 genes from the gene-based analysis with p < 1 × 10 -3 . One SNP (rs9957475 in GATA6 ) and 1 gene ( UBE2C ) demonstrated evidence of association ( p < 0.05) in the African American sample. Four SNPs with p < 1 × 10 -5 were shown to affect binding of SPI1 using RegulomeDB. This GWAS of 2 community-based Hispanic cohorts revealed several novel WMH-associated genetic variants. Further replication is needed in independent Hispanic samples to validate these suggestive associations, and fine mapping is needed to pinpoint causal variants.
Full Text Available Understanding the actions of drugs and toxins in a cell is of critical importance to medicine, yet many of the molecular events involved in chemical resistance are relatively uncharacterized. In order to identify the cellular processes and pathways targeted by chemicals, we took advantage of the haploid Saccharomyces cerevisiae deletion strains (Winzeler et al., 1999. Although ~4800 of the strains are viable, the loss of a gene in a pathway affected by a drug can lead to a synthetic lethal effect in which the combination of a deletion and a normally sublethal dose of a chemical results in loss of viability. WE carried out genome-wide screens to determine quantitative sensitivities of the deletion set to four chemicals: hydrogen peroxide, menadione, ibuprofen and mefloquine. Hydrogen peroxide and menadione induce oxidative stress in the cell, whereas ibuprofen and mefloquine are toxic to yeast by unknown mechanisms. Here we report the sensitivities of 659 deletion strains that are sensitive to one or more of these four compounds, including 163 multichemicalsensitive strains, 394 strains specific to hydrogen peroxide and/or menadione, 47 specific to ibuprofen and 55 specific to mefloquine.We correlate these results with data from other large-scale studies to yield novel insights into cellular function.
Kostadin Evgeniev eAtanasov
Full Text Available Guazatine is a potent inhibitor of polyamine oxidase (PAO activity. In agriculture, guazatine is used as non-systemic contact fungicide efficient in the protection of cereals and citrus fruits against disease. The composition of guazatine is complex, mainly constituted by a mixture of synthetic guanidated polyamines (polyaminoguanidines. Here we have studied the effects from exposure to guazatine in the weed Arabidopsis thaliana. We report that micromolar concentrations of guazatine are sufficient to inhibit growth of Arabidopsis seedlings and induce chlorosis, whereas germination is barely affected. We observed the occurrence of quantitative variation in the response to guazatine between 107 randomly chosen Arabidopsis accessions. This enabled us to undertake genome-wide association (GWA mapping that identified a locus on chromosome one associated with guazatine tolerance. CHLOROPHYLLASE 1 (CLH1 within this locus was studied as candidate gene, together with its paralog (CLH2. The analysis of independent clh1-2, clh1-3, clh2-3, clh2-2 and double clh1-2 clh2-3 mutant alleles indicated that CLH1 and/or CLH2 loss-of-function or expression down-regulation promote guazatine tolerance in Arabidopsis. We report a natural mechanism by which Arabidopsis populations can overcome toxicity by the fungicide guazatine.
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner\\'s curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
Full Text Available Transposon insertion sequencing (TIS is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection. Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE. From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant’s fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen collected over a 2-week infection period from a natural host (the flatfish turbot. PACE uncovered more genes that affect E. piscicida’s fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses.
Cecilia M Lindgren
Full Text Available To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580 informative for adult waist circumference (WC and waist-hip ratio (WHR. We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11 and MSRA (WC, P = 8.9x10(-9. A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8. The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Anney, Richard; Klei, Lambertus; Pinto, Dalila; Regan, Regina; Conroy, Judith; Magalhaes, Tiago R; Correia, Catarina; Abrahams, Brett S; Sykes, Nuala; Pagnamenta, Alistair T; Almeida, Joana; Bacchelli, Elena; Bailey, Anthony J; Baird, Gillian; Battaglia, Agatino; Berney, Tom; Bolshakova, Nadia; Bölte, Sven; Bolton, Patrick F; Bourgeron, Thomas; Brennan, Sean; Brian, Jessica; Carson, Andrew R; Casallo, Guillermo; Casey, Jillian; Chu, Su H; Cochrane, Lynne; Corsello, Christina; Crawford, Emily L; Crossett, Andrew; Dawson, Geraldine; de Jonge, Maretha; Delorme, Richard; Drmic, Irene; Duketis, Eftichia; Duque, Frederico; Estes, Annette; Farrar, Penny; Fernandez, Bridget A; Folstein, Susan E; Fombonne, Eric; Freitag, Christine M; Gilbert, John; Gillberg, Christopher; Glessner, Joseph T; Goldberg, Jeremy; Green, Jonathan; Guter, Stephen J; Hakonarson, Hakon; Heron, Elizabeth A; Hill, Matthew; Holt, Richard; Howe, Jennifer L; Hughes, Gillian; Hus, Vanessa; Igliozzi, Roberta; Kim, Cecilia; Klauck, Sabine M; Kolevzon, Alexander; Korvatska, Olena; Kustanovich, Vlad; Lajonchere, Clara M; Lamb, Janine A; Laskawiec, Magdalena; Leboyer, Marion; Le Couteur, Ann; Leventhal, Bennett L; Lionel, Anath C; Liu, Xiao-Qing; Lord, Catherine; Lotspeich, Linda; Lund, Sabata C; Maestrini, Elena; Mahoney, William; Mantoulan, Carine; Marshall, Christian R; McConachie, Helen; McDougle, Christopher J; McGrath, Jane; McMahon, William M; Melhem, Nadine M; Merikangas, Alison; Migita, Ohsuke; Minshew, Nancy J; Mirza, Ghazala K; Munson, Jeff; Nelson, Stanley F; Noakes, Carolyn; Noor, Abdul; Nygren, Gudrun; Oliveira, Guiomar; Papanikolaou, Katerina; Parr, Jeremy R; Parrini, Barbara; Paton, Tara; Pickles, Andrew; Piven, Joseph; Posey, David J; Poustka, Annemarie; Poustka, Fritz; Prasad, Aparna; Ragoussis, Jiannis; Renshaw, Katy; Rickaby, Jessica; Roberts, Wendy; Roeder, Kathryn; Roge, Bernadette; Rutter, Michael L; Bierut, Laura J; Rice, John P; Salt, Jeff; Sansom, Katherine; Sato, Daisuke; Segurado, Ricardo; Senman, Lili; Shah, Naisha; Sheffield, Val C; Soorya, Latha; Sousa, Inês; Stoppioni, Vera; Strawbridge, Christina; Tancredi, Raffaella; Tansey, Katherine; Thiruvahindrapduram, Bhooma; Thompson, Ann P; Thomson, Susanne; Tryfon, Ana; Tsiantis, John; Van Engeland, Herman; Vincent, John B; Volkmar, Fred; Wallace, Simon; Wang, Kai; Wang, Zhouzhi; Wassink, Thomas H; Wing, Kirsty; Wittemeyer, Kerstin; Wood, Shawn; Yaspan, Brian L; Zurawiecki, Danielle; Zwaigenbaum, Lonnie; Betancur, Catalina; Buxbaum, Joseph D; Cantor, Rita M; Cook, Edwin H; Coon, Hilary; Cuccaro, Michael L; Gallagher, Louise; Geschwind, Daniel H; Gill, Michael; Haines, Jonathan L; Miller, Judith; Monaco, Anthony P; Nurnberger, John I; Paterson, Andrew D; Pericak-Vance, Margaret A; Schellenberg, Gerard D; Scherer, Stephen W; Sutcliffe, James S; Szatmari, Peter; Vicente, Astrid M; Vieland, Veronica J; Wijsman, Ellen M; Devlin, Bernie; Ennis, Sean; Hallmayer, Joachim
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
Full Text Available BACKGROUND: Genome-wide association studies (GWAS have identified three loci (rs17401966 in KIF1B, rs7574865 in STAT4, rs9275319 in HLA-DQ as being associated with hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC in a Chinese population, two loci (rs2596542 in MICA, rs9275572 located between HLA-DQA and HLA-DQB with hepatitis C virus-related HCC (HCV-related HCC in a Japanese population. In the present study, we sought to determine whether these SNPs are predictive for HBV-related HCC development in other Chinese population as well. METHOD AND FINDINGS: We genotyped 4 SNPs, rs2596542, rs9275572, rs17401966, rs7574865, in 506 HBV-related HCC patients and 772 chronic hepatitis B (CHB patients in Han Chinese by TaqMan methods. Odds ratio(ORand 95% confidence interval (CI were calculated by logistic regression. In our case-control study, significant association between rs9275572 and HCC were observed (P = 0.02, OR = 0.73, 95% CI = 0.56-0.95. In the further haplotype analysis between rs2596542 at 6p21.33 and rs9275572 at 6p21.3, G-A showed a protective effect on HBV-related HCC occurrence (P<0.001, OR = 0.66, 95% CI = 0.52-0.84. CONCLUSION: These findings provided convincing evidence that rs9275572 significantly associated with HBV-related HCC.
Chen, Kangmei; Shi, Weimei; Xin, Zhenhui; Wang, Huifen; Zhu, Xilin; Wu, Xiaopan; Li, Zhuo; Li, Hui; Liu, Ying
Genome-wide association studies (GWAS) have identified three loci (rs17401966 in KIF1B, rs7574865 in STAT4, rs9275319 in HLA-DQ) as being associated with hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC) in a Chinese population, two loci (rs2596542 in MICA, rs9275572 located between HLA-DQA and HLA-DQB) with hepatitis C virus-related HCC (HCV-related HCC) in a Japanese population. In the present study, we sought to determine whether these SNPs are predictive for HBV-related HCC development in other Chinese population as well. We genotyped 4 SNPs, rs2596542, rs9275572, rs17401966, rs7574865, in 506 HBV-related HCC patients and 772 chronic hepatitis B (CHB) patients in Han Chinese by TaqMan methods. Odds ratio(OR)and 95% confidence interval (CI) were calculated by logistic regression. In our case-control study, significant association between rs9275572 and HCC were observed (P = 0.02, OR = 0.73, 95% CI = 0.56-0.95). In the further haplotype analysis between rs2596542 at 6p21.33 and rs9275572 at 6p21.3, G-A showed a protective effect on HBV-related HCC occurrence (P<0.001, OR = 0.66, 95% CI = 0.52-0.84). These findings provided convincing evidence that rs9275572 significantly associated with HBV-related HCC.
Schaid, Daniel J; Sinnwell, Jason P; Jenkins, Gregory D; McDonnell, Shannon K; Ingle, James N; Kubo, Michiaki; Goss, Paul E; Costantino, Joseph P; Wickerham, D Lawrence; Weinshilboum, Richard M
Gene-set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene-set, have plagued current approaches, often leading to ad hoc "fixes." To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene-level and gene-set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene-sets. However, other types of gene-set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene-sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene-sets, we use an efficient computational strategy that accounts for LD and provides accurate step-down adjusted P-values for each gene-set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene-set analyses. © 2011 Wiley Periodicals, Inc.
Khan, Raees; Roy, Nazish; Choi, Kihyuck
The substantial use of triclosan (TCS) has been aimed to kill pathogenic bacteria, but TCS resistance seems to be prevalent in microbial species and limited knowledge exists about TCS resistance determinants in a majority of pathogenic bacteria. We aimed to evaluate the distribution of TCS resistance determinants in major pathogenic bacteria (N = 231) and to assess the enrichment of potentially pathogenic genera in TCS contaminated environments. A TCS-resistant gene (TRG) database was constructed and experimentally validated to predict TCS resistance in major pathogenic bacteria. Genome-wide in silico analysis was performed to define the distribution of TCS-resistant determinants in major pathogens. Microbiome analysis of TCS contaminated soil samples was also performed to investigate the abundance of TCS-resistant pathogens. We experimentally confirmed that TCS resistance could be accurately predicted using genome-wide in silico analysis against TRG database. Predicted TCS resistant phenotypes were observed in all of the tested bacterial strains (N = 17), and heterologous expression of selected TCS resistant genes from those strains conferred expected levels of TCS resistance in an alternative host Escherichia coli. Moreover, genome-wide analysis revealed that potential TCS resistance determinants were abundant among the majority of human-associated pathogens (79%) and soil-borne plant pathogenic bacteria (98%). These included a variety of enoyl-acyl carrier protein reductase (ENRs) homologues, AcrB efflux pumps, and ENR substitutions. FabI ENR, which is the only known effective target for TCS, was either co-localized with other TCS resistance determinants or had TCS resistance-associated substitutions. Furthermore, microbiome analysis revealed that pathogenic genera with intrinsic TCS-resistant determinants exist in TCS contaminated environments. We conclude that TCS may not be as effective against the majority of bacterial pathogens as previously presumed
Full Text Available The substantial use of triclosan (TCS has been aimed to kill pathogenic bacteria, but TCS resistance seems to be prevalent in microbial species and limited knowledge exists about TCS resistance determinants in a majority of pathogenic bacteria. We aimed to evaluate the distribution of TCS resistance determinants in major pathogenic bacteria (N = 231 and to assess the enrichment of potentially pathogenic genera in TCS contaminated environments. A TCS-resistant gene (TRG database was constructed and experimentally validated to predict TCS resistance in major pathogenic bacteria. Genome-wide in silico analysis was performed to define the distribution of TCS-resistant determinants in major pathogens. Microbiome analysis of TCS contaminated soil samples was also performed to investigate the abundance of TCS-resistant pathogens. We experimentally confirmed that TCS resistance could be accurately predicted using genome-wide in silico analysis against TRG database. Predicted TCS resistant phenotypes were observed in all of the tested bacterial strains (N = 17, and heterologous expression of selected TCS resistant genes from those strains conferred expected levels of TCS resistance in an alternative host Escherichia coli. Moreover, genome-wide analysis revealed that potential TCS resistance determinants were abundant among the majority of human-associated pathogens (79% and soil-borne plant pathogenic bacteria (98%. These included a variety of enoyl-acyl carrier protein reductase (ENRs homologues, AcrB efflux pumps, and ENR substitutions. FabI ENR, which is the only known effective target for TCS, was either co-localized with other TCS resistance determinants or had TCS resistance-associated substitutions. Furthermore, microbiome analysis revealed that pathogenic genera with intrinsic TCS-resistant determinants exist in TCS contaminated environments. We conclude that TCS may not be as effective against the majority of bacterial pathogens as previously
van den Berg, Stéphanie M; de Moor, Marleen H M; Verweij, K. J. H.
small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found...... at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero...
Ottolini, Christian S; Capalbo, Antonio; Newnham, Louise
We have developed a protocol for the generation of genome-wide maps (meiomaps) of recombination and chromosome segregation for the three products of human female meiosis: the first and second polar bodies (PB1 and PB2) and the corresponding oocyte. PB1 is biopsied and the oocyte is artificially......-nucleotide polymorphisms (SNPs) genome-wide by microarray. Informative maternal heterozygous SNPs are phased using a haploid PB2 or oocyte as a reference. A simple algorithm is then used to identify the maternal haplotypes for each chromosome, in all of the products of meiosis for each oocyte. This allows mapping...
Aston, Kenneth I; Conrad, Donald F
Rapidly advancing tools for genetic analysis on a genome-wide scale have been instrumental in identifying the genetic bases for many complex diseases. About half of male infertility cases are of unknown etiology in spite of tremendous efforts to characterize the genetic basis for the disorder. Advancing our understanding of the genetic basis for male infertility will require the application of established and emerging genomic tools. This chapter introduces many of the tools available for genetic studies on a genome-wide scale along with principles of study design and data analysis.
Xu, Chunsheng; Zhang, Dongfeng; Wu, Yili
Multiple loci or genes have been identified using genome-wide association studies mainly in western countries but with inconsistent results. No similar studies have been conducted in the world's largest and rapidly aging Chinese population. The paper aimed to identify the specific genetic variants....... Gene-based analysis was performed on VEGAS2. The statistically significant genes were then subject to gene set enrichment analysis to further identify the specific biological pathways associated with cognitive function. No SNPs reached genome-wide significance although there were 13 SNPs of suggestive...
Pedersen, Jakob Skou; Valen, Eivind; Velazquez, Amhed Missael Vargas
Epigenetic information is available from contemporary organisms, but is difficult to track back in evolutionary time. Here, we show that genome-wide epigenetic information can be gathered directly from next-generation sequence reads of DNA isolated from ancient remains. Using the genome sequence...... data generated from hair shafts of a 4000-yr-old Paleo-Eskimo belonging to the Saqqaq culture, we generate the first ancient nucleosome map coupled with a genome-wide survey of cytosine methylation levels. The validity of both nucleosome map and methylation levels were confirmed by the recovery...
Manning, Alisa K.; Hivert, Marie-France; Scott, Robert A.; Grimsby, Jonna L.; Bouatia-Naji, Nabila; Chen, Han; Rybin, Denis; Liu, Ching-Ti; Bielak, Lawrence F.; Prokopenko, Inga; Amin, Najaf; Barnes, Daniel; Cadby, Gemma; Hottenga, Jouke-Jan; Ingelsson, Erik; Jackson, Anne U.; Johnson, Toby; Kanoni, Stavroula; Ladenvall, Claes; Lagou, Vasiliki; Lahti, Jari; Lecoeur, Cecile; Liu, Yongmei; Martinez-Larrad, Maria Teresa; Montasser, May E.; Navarro, Pau; Perry, John R. B.; Rasmussen-Torvik, Laura J.; Salo, Perttu; Sattar, Naveed; Shungin, Dmitry; Strawbridge, Rona J.; Tanaka, Toshiko; van Duijn, Cornelia M.; An, Ping; de Andrade, Mariza; Andrews, Jeanette S.; Aspelund, Thor; Atalay, Mustafa; Aulchenko, Yurii; Balkau, Beverley; Bandinelli, Stefania; Beckmann, Jacques S.; Beilby, John P.; Bellis, Claire; Bergman, Richard N.; Blangero, John; Boban, Mladen; Boehnke, Michael; Boerwinkle, Eric; Bonnycastle, Lori L.; Boomsma, Dorret I.; Borecki, Ingrid B.; Böttcher, Yvonne; Bouchard, Claude; Brunner, Eric; Budimir, Danijela; Campbell, Harry; Carlson, Olga; Chines, Peter S.; Clarke, Robert; Collins, Francis S.; Corbatón-Anchuelo, Arturo; Couper, David; de Faire, Ulf; Dedoussis, George V; Deloukas, Panos; Dimitriou, Maria; Egan, Josephine M; Eiriksdottir, Gudny; Erdos, Michael R.; Eriksson, Johan G.; Eury, Elodie; Ferrucci, Luigi; Ford, Ian; Forouhi, Nita G.; Fox, Caroline S; Franzosi, Maria Grazia; Franks, Paul W; Frayling, Timothy M; Froguel, Philippe; Galan, Pilar; de Geus, Eco; Gigante, Bruna; Glazer, Nicole L.; Goel, Anuj; Groop, Leif; Gudnason, Vilmundur; Hallmans, Göran; Hamsten, Anders; Hansson, Ola; Harris, Tamara B.; Hayward, Caroline; Heath, Simon; Hercberg, Serge; Hicks, Andrew A.; Hingorani, Aroon; Hofman, Albert; Hui, Jennie; Hung, Joseph; Jarvelin, Marjo Riitta; Jhun, Min A.; Johnson, Paul C.D.; Jukema, J Wouter; Jula, Antti; Kao, W.H.; Kaprio, Jaakko; Kardia, Sharon L. R.; Keinanen-Kiukaanniemi, Sirkka; Kivimaki, Mika; Kolcic, Ivana; Kovacs, Peter; Kumari, Meena; Kuusisto, Johanna; Kyvik, Kirsten Ohm; Laakso, Markku; Lakka, Timo; Lannfelt, Lars; Lathrop, G Mark; Launer, Lenore J.; Leander, Karin; Li, Guo; Lind, Lars; Lindstrom, Jaana; Lobbens, Stéphane; Loos, Ruth J. F.; Luan, Jian’an; Lyssenko, Valeriya; Mägi, Reedik; Magnusson, Patrik K. E.; Marmot, Michael; Meneton, Pierre; Mohlke, Karen L.; Mooser, Vincent; Morken, Mario A.; Miljkovic, Iva; Narisu, Narisu; O’Connell, Jeff; Ong, Ken K.; Oostra, Ben A.; Palmer, Lyle J.; Palotie, Aarno; Pankow, James S.; Peden, John F.; Pedersen, Nancy L.; Pehlic, Marina; Peltonen, Leena; Penninx, Brenda; Pericic, Marijana; Perola, Markus; Perusse, Louis; Peyser, Patricia A; Polasek, Ozren; Pramstaller, Peter P.; Province, Michael A.; Räikkönen, Katri; Rauramaa, Rainer; Rehnberg, Emil; Rice, Ken; Rotter, Jerome I.; Rudan, Igor; Ruokonen, Aimo; Saaristo, Timo; Sabater-Lleal, Maria; Salomaa, Veikko; Savage, David B.; Saxena, Richa; Schwarz, Peter; Seedorf, Udo; Sennblad, Bengt; Serrano-Rios, Manuel; Shuldiner, Alan R.; Sijbrands, Eric J.G.; Siscovick, David S.; Smit, Johannes H.; Small, Kerrin S.; Smith, Nicholas L.; Smith, Albert Vernon; Stančáková, Alena; Stirrups, Kathleen; Stumvoll, Michael; Sun, Yan V.; Swift, Amy J.; Tönjes, Anke; Tuomilehto, Jaakko; Trompet, Stella; Uitterlinden, Andre G.; Uusitupa, Matti; Vikström, Max; Vitart, Veronique; Vohl, Marie-Claude; Voight, Benjamin F.; Vollenweider, Peter; Waeber, Gerard; Waterworth, Dawn M; Watkins, Hugh; Wheeler, Eleanor; Widen, Elisabeth; Wild, Sarah H.; Willems, Sara M.; Willemsen, Gonneke; Wilson, James F.; Witteman, Jacqueline C.M.; Wright, Alan F.; Yaghootkar, Hanieh; Zelenika, Diana; Zemunik, Tatijana; Zgaga, Lina; Wareham, Nicholas J.; McCarthy, Mark I.; Barroso, Ines; Watanabe, Richard M.; Florez, Jose C.; Dupuis, Josée; Meigs, James B.; Langenberg, Claudia
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction, but contributed little to our understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways may be uncovered by accounting for differences in body mass index (BMI) and potential interaction between BMI and genetic variants. We applied a novel joint meta-analytical approach to test associations with fasting insulin (FI) and glucose (FG) on a genome-wide scale. We present six previously unknown FI loci at P<5×10−8 in combined discovery and follow-up analyses of 52 studies comprising up to 96,496non-diabetic individuals. Risk variants were associated with higher triglyceride and lower HDL cholesterol levels, suggestive of a role for these FI loci in insulin resistance pathways. The localization of these additional loci will aid further characterization of the role of insulin resistance in T2D pathophysiology. PMID:22581228
Seyerle, Amanda A; Lin, Henry J; Gogarten, Stephanie M; Stilp, Adrienne; Méndez Giráldez, Raul; Soliman, Elsayed; Baldassari, Antoine; Graff, Mariaelisa; Heckbert, Susan; Kerr, Kathleen F; Kooperberg, Charles; Rodriguez, Carlos; Guo, Xiuqing; Yao, Jie; Sotoodehnia, Nona; Taylor, Kent D; Whitsel, Eric A; Rotter, Jerome I; Laurie, Cathy C; Avery, Christy L
PR interval (PR) is a heritable electrocardiographic measure of atrial and atrioventricular nodal conduction. Changes in PR duration may be associated with atrial fibrillation, heart failure and all-cause mortality. Hispanic/Latino populations have high burdens of cardiovascular morbidity and mortality, are highly admixed and represent exceptional opportunities for novel locus identification. However, they remain chronically understudied. We present the first genome-wide association study (GWAS) of PR in 14 756 participants of Hispanic/Latino ancestry from three studies. Study-specific summary results of the association between 1000 Genomes Phase 1 imputed single-nucleotide polymorphisms (SNPs) and PR assumed an additive genetic model and were adjusted for global ancestry, study centre/region and clinical covariates. Results were combined using fixed-effects, inverse variance weighted meta-analysis. Sequential conditional analyses were used to identify independent signals. Replication of novel loci was performed in populations of Asian, African and European descent. ENCODE and RoadMap data were used to annotate results. We identified a novel genome-wide association (PPR at ID2 (rs6730558), which replicated in Asian and European populations (PPR loci to Hispanics/Latinos. Bioinformatics annotation provided evidence for regulatory function in cardiac tissue. Further, for six loci that generalised, the Hispanic/Latino index SNP was genome-wide significant and identical to (or in high linkage disequilibrium with) the previously identified GWAS lead SNP. Our results suggest that genetic determinants of PR are consistent across race/ethnicity, but extending studies to admixed populations can identify novel associations, underscoring the importance of conducting genetic studies in diverse populations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise
Full Text Available Genome-wide association studies (GWAS have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS data from the Nurses' Health Study (NHS, and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ~1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint β = -0.126; joint P = 2.09 × 10(-16, downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10(-5, several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ~900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10(-5 was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.
Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo
Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits
Full Text Available Transposon insertion sequencing (TIS; also known as TnSeq is a potent approach commonly used to comprehensively define the genetic loci that contribute to bacterial fitness in diverse environments. A key presumption underlying analyses of TIS datasets is that loci with a low frequency of transposon insertions contribute to fitness. However, it is not known whether factors such as nucleoid binding proteins can alter the frequency of transposon insertion and thus whether TIS output may systematically reflect factors that are independent of the role of the loci in fitness. Here, we investigated whether the histone-like nucleoid structuring (H-NS protein, which preferentially associates with AT-rich sequences, modulates the frequency of Mariner transposon insertion in the Vibrio cholerae genome, using comparative analysis of TIS results from wild-type (wt and Δhns V. cholerae strains. These analyses were overlaid on gene classification based on GC content as well as on extant genome-wide identification of H-NS binding loci. Our analyses revealed a significant dearth of insertions within AT-rich loci in wt V. cholerae that was not apparent in the Δhns insertion library. Additionally, we observed a striking correlation between genetic loci that are overrepresented in the Δhns insertion library relative to their insertion frequency in wt V. cholerae and loci previously found to physically interact with H-NS. Collectively, our findings reveal that factors other than genetic fitness can systematically modulate the frequency of transposon insertions in TIS studies and add a cautionary note to interpretation of TIS data, particularly for AT-rich sequences.
de Moor, Marleen H.M.; van den Berg, Stéphanie M.; Verweij, Karin J.H.; Krueger, Robert F.; Luciano, Michelle; Vasquez, Alejandro Arias; Matteson, Lindsay K.; Derringer, Jaime; Esko, Tõnu; Amin, Najaf; Gordon, Scott D.; Hansell, Narelle K.; Hart, Amy B.; Seppälä, Ilkka; Huffman, Jennifer E.; Konte, Bettina; Lahti, Jari; Lee, Minyoung; Miller, Mike; Nutile, Teresa; Tanaka, Toshiko; Teumer, Alexander; Viktorin, Alexander; Wedenoja, Juho; Abecasis, Goncalo R.; Adkins, Daniel E.; Agrawal, Arpana; Allik, Jüri; Appel, Katja; Bigdeli, Timothy B.; Busonero, Fabio; Campbell, Harry; Costa, Paul T.; Smith, George Davey; Davies, Gail; de Wit, Harriet; Ding, Jun; Engelhardt, Barbara E.; Eriksson, Johan G.; Fedko, Iryna O.; Ferrucci, Luigi; Franke, Barbara; Giegling, Ina; Grucza, Richard; Hartmann, Annette M.; Heath, Andrew C.; Heinonen, Kati; Henders, Anjali K.; Homuth, Georg; Hottenga, Jouke-Jan; Janzing, Joost; Jokela, Markus; Karlsson, Robert; Kemp, John P.; Kirkpatrick, Matthew G.; Latvala, Antti; Lehtimäki, Terho; Liewald, David C.; Madden, Pamela A.F.; Magri, Chiara; Magnusson, Patrik K.E.; Marten, Jonathan; Maschio, Andrea; Medland, Sarah E.; Mihailov, Evelin; Milaneschi, Yuri; Montgomery, Grant W.; Nauck, Matthias; Ouwens, Klaasjan G.; Palotie, Aarno; Pettersson, Erik; Polasek, Ozren; Qian, Yong; Pulkki-Råback, Laura; Raitakari, Olli T.; Realo, Anu; Rose, Richard J.; Ruggiero, Daniela; Schmidt, Carsten O.; Slutske, Wendy S.; Sorice, Rossella; Starr, John M.; Pourcain, Beate St; Sutin, Angelina R.; Timpson, Nicholas J.; Trochet, Holly; Vermeulen, Sita; Vuoksimaa, Eero; Widen, Elisabeth; Wouda, Jasper; Wright, Margaret J.; Zgaga, Lina; Scotland, Generation; Porteous, David; Minelli, Alessandra; Palmer, Abraham A.; Rujescu, Dan; Ciullo, Marina; Hayward, Caroline; Rudan, Igor; Metspalu, Andres; Kaprio, Jaakko; Deary, Ian J.; Räikkönen, Katri; Wilson, James F.; Keltikangas-Järvinen, Liisa; Bierut, Laura J.; Hettema, John M.; Grabe, Hans J.; van Duijn, Cornelia M.; Evans, David M.; Schlessinger, David; Pedersen, Nancy L.; Terracciano, Antonio; McGue, Matt; Penninx, Brenda W.J.H.; Martin, Nicholas G.; Boomsma, Dorret I.
Importance Neuroticism is a personality trait that is briefly defined by emotional instability. It is a robust genetic risk factor for Major Depressive Disorder (MDD) and other psychiatric disorders. Hence, neuroticism is an important phenotype for psychiatric genetics. The Genetics of Personality Consortium (GPC) has created a resource for genome-wide association analyses of personality traits in over 63,000 participants (including MDD cases). Objective To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association (GWA) results based on 1000Genomes imputation, to evaluate if common genetic variants as assessed by Single Nucleotide Polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability, and to examine whether SNPs that predict neuroticism also predict MDD. Setting 30 cohorts with genome-wide genotype, personality and MDD data from the GPC. Participants The study included 63,661 participants from 29 discovery cohorts and 9,786 participants from a replication cohort. Participants came from Europe, the United States or Australia. Main outcome measure(s) Neuroticism scores harmonized across all cohorts by Item Response Theory (IRT) analysis, and clinically assessed MDD case-control status. Results A genome-wide significant SNP was found in the MAGI1 gene (rs35855737; P=9.26 × 10−9 in the discovery meta-analysis, and P=2.38 × 10−8 in the meta-analysis of all 30 cohorts). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 of the discovery cohorts significantly predicted neuroticism in 2 independent cohorts. Importantly, polygenic scores also predicted MDD in these cohorts. Conclusions and relevance This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study
C.M. Lindgren (Cecilia); I.M. Heid (Iris); J.C. Randall (Joshua); C. Lamina (Claudia); V. Steinthorsdottir (Valgerdur); L. Qi (Lu); E.K. Speliotes (Elizabeth); G. Thorleifsson (Gudmar); C.J. Willer (Cristen); B.M. Herrera (Blanca); A.U. Jackson (Anne); N. Lim (Noha); P. Scheet (Paul); N. Soranzo (Nicole); N. Amin (Najaf); Y.S. Aulchenko (Yurii); J.C. Chambers (John); A. Drong (Alexander); J. Luan; H.N. Lyon (Helen); F. Rivadeneira Ramirez (Fernando); S. Sanna (Serena); N.J. Timpson (Nicholas); M.C. Zillikens (Carola); H.Z. Jing; P. Almgren (Peter); S. Bandinelli (Stefania); A.J. Bennett (Amanda); R.N. Bergman (Richard); L.L. Bonnycastle (Lori); S. Bumpstead (Suzannah); S.J. Chanock (Stephen); L. Cherkas (Lynn); P.S. Chines (Peter); L. Coin (Lachlan); C. Cooper (Charles); G. Crawford (Gabe); A. Doering (Angela); A. Dominiczak (Anna); A.S.F. Doney (Alex); S. Ebrahim (Shanil); P. Elliott (Paul); M.R. Erdos (Michael); K. Estrada Gil (Karol); L. Ferrucci (Luigi); G. Fischer (Guido); N.G. Forouhi (Nita); C. Gieger (Christian); H. Grallert (Harald); C.J. Groves (Christopher); S.M. Grundy (Scott); C. Guiducci (Candace); D. Hadley (David); A. Hamsten (Anders); A.S. Havulinna (Aki); A. Hofman (Albert); R. Holle (Rolf); J.W. Holloway (John); T. Illig (Thomas); B. Isomaa (Bo); L.C. Jacobs (Leonie); K. Jameson (Karen); P. Jousilahti (Pekka); F. Karpe (Fredrik); J. Kuusisto (Johanna); J. Laitinen (Jaana); G.M. Lathrop (Mark); D.A. Lawlor (Debbie); M. Mangino (Massimo); W.L. McArdle (Wendy); T. Meitinger (Thomas); M.A. Morken (Mario); A.P. Morris (Andrew); P. Munroe (Patricia); N. Narisu (Narisu); A. Nordström (Anna); B.A. Oostra (Ben); C.N.A. Palmer (Colin); F. Payne (Felicity); J. Peden (John); I. Prokopenko (Inga); F. Renström (Frida); A. Ruokonen (Aimo); V. Salomaa (Veikko); M.S. Sandhu (Manjinder); L.J. Scott (Laura); A. Scuteri (Angelo); K. Silander (Kaisa); K. Song (Kijoung); X. Yuan (Xin); H.M. Stringham (Heather); A.J. Swift (Amy); T. Tuomi (Tiinamaija); M. Uda (Manuela); P. Vollenweider (Peter); G. Waeber (Gérard); C. Wallace (Chris); G.B. Walters (Bragi); M.N. Weedon (Michael); J.C.M. Witteman (Jacqueline); C. Zhang (Cuilin); M. Caulfield (Mark); F.S. Collins (Francis); G.D. Smith; I.N.M. Day (Ian); P.W. Franks (Paul); A.T. Hattersley (Andrew); F.B. Hu (Frank); M.-R. Jarvelin (Marjo-Riitta); A. Kong (Augustine); J.S. Kooner (Jaspal); M. Laakso (Markku); E. Lakatta (Edward); V. Mooser (Vincent); L. Peltonen (Leena Johanna); N.J. Samani (Nilesh); T.D. Spector (Timothy); D.P. Strachan (David); T. Tanaka (Toshiko); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); P. Tikka-Kleemola (Päivi); N.J. Wareham (Nick); H. Watkins (Hugh); D. Waterworth (Dawn); M. Boehnke (Michael); P. Deloukas (Panagiotis); L. Groop (Leif); D.J. Hunter (David); U. Thorsteinsdottir (Unnur); D. Schlessinger (David); H.E. Wichmann (Erich); T.M. Frayling (Timothy); G.R. Abecasis (Gonçalo); J.N. Hirschhorn (Joel); R.J.F. Loos (Ruth); J-A. Zwart (John-Anker); K.L. Mohlke (Karen); I.E. Barroso (Inês); M.I. McCarthy (Mark)
textabstractTo identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the
Lee, S.H.; Ripke, S.; Neale, B.; Faraone, S.V.; Purcell, S.M.; Perlis, R.H.; Mowry, B. J.; Thapar, A.; Goddard, M.E.; Witte, J.S.; Absher, D.; Agartz, I.; Akil, H.; Amin, F.; Andreassen, O.A.; Anjorin, A.; Anney, R.; Anttila, V.; Arking, D.E.; Asherson, P.; Azevedo, M.H.; Backlund, L.; Badner, J.A.; Bailey, A.J.; Banaschewski, T.; Barchas, J.D.; Barnes, M.R.; Barrett, T.B.; Bass, N.; Battaglia, A.; Bauer, M.; Bayés, M.; Bellivier, F.; Bergen, S.E.; Berrettini, W.; Betancur, C.; Bettecken, T.; Biederman, J; Binder, E.B.; Black, D.W.; Blackwood, D.H.; Bloss, C.S.; Boehnke, M.; Boomsma, D.I.; Breen, G.; Breuer, R.; Bruggeman, R.; Cormican, P.; Buccola, N.G.; Buitelaar, J.K.; Bunney, W.E.; Buxbaum, J.D.; Byerley, W. F.; Byrne, E.M.; Caesar, S.; Cahn, W.; Cantor, R.M.; Casas, M.; Chakravarti, A.; Chambert, K.; Choudhury, K.; Cichon, S.; Cloninger, C. R.; Collier, D.A.; Cook, E.H.; Coon, H.; Corman, B.; Corvin, A.; Coryell, W.H.; Craig, D.W.; Craig, I.W.; Crosbie, J.; Cuccaro, M.L.; Curtis, D.; Czamara, D.; Datta, S.; Dawson, G.; Day, R.; de Geus, E.J.C.; Degenhardt, F.; Djurovic, S.; Donohoe, G.; Doyle, A.E.; Duan, J.; Dudbridge, F.; Duketis, E.; Ebstein, R.P.; Edenberg, H.J.; Elia, J.; Ennis, S.; Etain, B.; Fanous, A.; Farmer, A.E.; Ferrier, I.N.; Flickinger, M.; Fombonne, E.; Foroud, T.; Frank, J.; Franke, B.; Fraser, C.; Freedman, R.; Freimer, N.B.; Freitag, C.; Friedl, M.; Frisén, L.; Gallagher, L.; Gejman, P.V.; Georgieva, L.; Gershon, E.S.; Geschwind, D.H.; Giegling, I.; Gill, M.; Gordon, S.D.; Gordon-Smith, K.; Green, E.K.; Greenwood, T.A.; Grice, D.E.; Gross, M.; Grozeva, D.; Guan, W.; Gurling, H.; de Haan, L.; Haines, J.L.; Hakonarson, H.; Hallmayer, J.; Hamilton, S.P.; Hamshere, M.L.; Hans