Genome-wide association studies of 14 agronomic traits in rice landraces

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ～ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ～ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.     

Control of a key transition from prostrate to erect growth in rice domestication

The transition from the prostrate growth of ancestral wild rice (O. rufipogon Griff.) to the erect growth of Oryza sativa cultivars was one of the most critical events in rice domestication. This evolutionary step importantly improved plant architecture and increased grain yield. Here we find that prostrate growth of wild rice from Yuanjiang County in China is controlled by a semi-dominant gene, PROG1 (PROSTRATE GROWTH 1), on chromosome 7 that encodes a single Cys(2)-His(2) zinc-finger protein. prog1 variants identified in O. sativa disrupt the prog1 function and inactivate prog1 expression, leading to erect growth, greater grain number and higher grain yield in cultivated rice. Sequence comparison shows that 182 varieties of cultivated rice, including 87 indica and 95 japonica cultivars from 17 countries, carry identical mutations in the prog1 coding region that may have become fixed during rice domestication.     

Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.     

Genome-wide association study identifies 12 new susceptibility loci for primary biliary cirrhosis

In addition to the HLA locus, six genetic risk factors for primary biliary cirrhosis (PBC) have been identified in recent genome-wide association studies (GWAS). To identify additional loci, we carried out a GWAS using 1,840 cases from the UK PBC Consortium and 5,163 UK population controls as part of the Wellcome Trust Case Control Consortium 3 (WTCCC3). We followed up 28 loci in an additional UK cohort of 620 PBC cases and 2,514 population controls. We identified 12 new susceptibility loci (at a genome-wide significance level of P < 5 × 10??) and replicated all previously associated loci. We identified three further new loci in a meta-analysis of data from our study and previously published GWAS results. New candidate genes include STAT4, DENND1B, CD80, IL7R, CXCR5, TNFRSF1A, CLEC16A and NFKB1. This study has considerably expanded our knowledge of the genetic architecture of PBC.     

A mixed-model approach for genome-wide association studies of correlated traits in structured populations

Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear mixed-model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait mixed model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.     

Replication of signals from recent studies of Crohn's disease identifies previously unknown disease loci for ulcerative colitis

Following up on recent genome-wide association studies (GWAS) of Crohn's disease, we investigated 50 previously reported susceptibility loci in a German sample of individuals with Crohn's disease (n = 1,850) or ulcerative colitis (n = 1,103) and healthy controls (n = 1,817). Among these loci, we identified variants in 3p21.31, NKX2-3 and CCNY as susceptibility factors for both diseases, whereas variants in PTPN2, HERC2 and STAT3 were associated only with ulcerative colitis in our sample collection.     

A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 SNPs in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls. We identified four SNPs in intron 2 of FGFR2 (which encodes a receptor tyrosine kinase and is amplified or overexpressed in some breast cancers) that were highly associated with breast cancer and confirmed this association in 1,776 affected individuals and 2,072 controls from three additional studies. Across the four studies, the association with all four SNPs was highly statistically significant (P(trend) for the most strongly associated SNP (rs1219648) = 1.1 x 10(-10); population attributable risk = 16%). Four SNPs at other loci most strongly associated with breast cancer in the initial GWAS were not associated in the replication studies. Our summary results from the GWAS are available online in a form that should speed the identification of additional risk loci.     

Genome-wide association identifies a susceptibility locus for coronary artery disease in the Chinese Han population

Coronary artery disease (CAD) causes more than 700,000 deaths each year in China. Previous genome-wide association studies (GWAS) in populations of European ancestry identified several genetic loci for CAD, but no such study has yet been reported in the Chinese population. Here we report a three-stage GWAS in the Chinese Han population. We identified a new association between rs6903956 in a putative gene denoted as C6orf105 on chromosome 6p24.1 and CAD (P = 5.00 × 10?3, stage 2 validation; P = 3.00 × 10?3, P = 1.19 × 10?? and P = 4.00 × 10?3 in three independent stage 3 replication populations; P = 4.87 × 10?12, odds ratio = 1.51 in the combined population). The minor risk allele A of rs6903956 is associated with decreased C6orf105 mRNA expression. We report the first GWAS for CAD in the Chinese Han population and identify a SNP, rs6903956, in C6orf105 associated with susceptibility to CAD in this population.     

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.     

Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways

To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 × 10(-8)). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-κB signaling and mitochondrial dysfunction as biological processes related to timing of menopause.     

Multiple newly identified loci associated with prostate cancer susceptibility

Prostate cancer is the most common cancer affecting males in developed countries. It shows consistent evidence of familial aggregation, but the causes of this aggregation are mostly unknown. To identify common alleles associated with prostate cancer risk, we conducted a genome-wide association study (GWAS) using blood DNA samples from 1,854 individuals with clinically detected prostate cancer diagnosed at 相似文献   

Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4

We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10(-7)). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci.     

Common variants at 11q12, 10q26 and 3p11.2 are associated with prostate cancer susceptibility in Japanese

We have previously reported multiple loci associated with prostate cancer susceptibility in a Japanese population using a genome-wide association study (GWAS). To identify additional prostate cancer susceptibility loci, we genotyped nine SNPs that were nominally associated with prostate cancer (P < 1 × 10(-4)) in our previous GWAS in three independent studies of prostate cancer in Japanese men (2,557 individuals with prostate cancer (cases) and 3,003 controls). In a meta-analysis of our previous GWAS and the replication studies, which included a total of 7,141 prostate cancer cases and 11,804 controls from a single ancestry group, three new loci reached genome-wide significance on chromosomes 11q12 (rs1938781; P = 1.10 × 10(-10); FAM111A-FAM111B), 10q26 (rs2252004; P = 1.98 × 10(-8)) and 3p11.2 (rs2055109; P = 3.94 × 10(-8)). We also found suggestive evidence of association at a previously reported prostate cancer susceptibility locus at 2p11 (rs2028898; P = 1.08 × 10(-7)). The identification of three new susceptibility loci should provide additional insight into the pathogenesis of prostate cancer and emphasizes the importance of conducting GWAS in diverse populations.     

Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome

Following a previous genome-wide association study (GWAS 1) including 744 cases and 895 controls, we analyzed genome-wide association data from a new cohort of Han Chinese (GWAS 2) with 1,510 polycystic ovary syndrome (PCOS) cases and 2,016 controls. We followed up significantly associated signals identified in the combined results of GWAS 1 and 2 in a total of 8,226 cases and 7,578 controls. In addition to confirming the three loci we previously reported, we identify eight new PCOS association signals at P < 5 × 10(-8): 9q22.32, 11q22.1, 12q13.2, 12q14.3, 16q12.1, 19p13.3, 20q13.2 and a second independent signal at 2p16.3 (the FSHR gene). These PCOS association signals show evidence of enrichment for candidate genes related to insulin signaling, sexual hormone function and type 2 diabetes (T2D). Other candidate genes were related to calcium signaling and endocytosis. Our findings provide new insight and direction for discovering the biological mechanisms of PCOS.     

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.     

Genome-wide association study of leaf architecture in the maize nested association mapping population

US maize yield has increased eight-fold in the past 80 years, with half of the gain attributed to selection by breeders. During this time, changes in maize leaf angle and size have altered plant architecture, allowing more efficient light capture as planting density has increased. Through a genome-wide association study (GWAS) of the maize nested association mapping panel, we determined the genetic basis of important leaf architecture traits and identified some of the key genes. Overall, we demonstrate that the genetic architecture of the leaf traits is dominated by small effects, with little epistasis, environmental interaction or pleiotropy. In particular, GWAS results show that variations at the liguleless genes have contributed to more upright leaves. These results demonstrate that the use of GWAS with specially designed mapping populations is effective in uncovering the basis of key agronomic traits.     

Genome-wide association analysis identifies three new breast cancer susceptibility loci

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ～8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ～70,000 cases and ～68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.