Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

BACKGROUND: Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS: We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS: In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION: The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

Genome-Wide Association Study Meta-Analysis Elucidates Genetic Structure and Identifies Candidate Genes of Teat Number Traits in Pigs.

The teat number is a pivotal reproductive trait that significantly influences the survival rate of piglets. A meta-analysis is a robust instrument, enhancing the universality of research findings and improving statistical power by increasing the sample size. This study aimed to identify universal candidate genes associated with teat number traits using a genome-wide association study (GWAS) meta-analysis with three breeds. We identified 21 chromosome threshold significant single-nucleotide polymorphisms (SNPs) associated with five teat number traits in single-breed and cross-breed meta-GWAS analyses. Using a co-localization analysis of expression quantitative trait loci and GWAS loci, we detected four unique genes that were co-localized with cross-breed GWAS loci associated with teat number traits. Through a meta-analysis and integrative analysis, we identified more reliable candidate genes associated with multiple-breed teat number traits. Our research provides new information for exploring the genetic mechanism affecting pig teat number for breeding selection and improvement.

rs9459874 and rs1012656 in CCR6/FGFR1OP confer susceptibility to primary biliary cholangitis.

Primary biliary cholangitis (PBC) is a chronic cholestatic autoimmune liver disease that appears to be strongly influenced by genetic factors. Recently, an international meta-analysis of genome-wide association studies (GWAS) identified CC-Motif Chemokine Receptor-6 (CCR6) and FGFR1 Oncogene-Partner (FGFR1OP) as PBC-susceptibility genes. However, the lead single nucleotide polymorphisms (SNPs) of CCR6/FGFR1OP showed low linkage disequilibrium with each other in East Asian and European populations. Additionally, the primary functional variants and the molecular mechanisms responsible for PBC-susceptibility remain unclear. Here, among the PBC-susceptibility SNPs identified by high-density association mapping in our previous meta-GWAS (Patients: n = 10,516; healthy controls: n = 20,772) within the CCR6/FGFR1OP locus, rs9459874 and rs1012656 were identified as primary functional variants. These functional variants accounted for the effects of GWAS-identified lead SNPs in CCR6/FGFR1OP. Additionally, the roles of rs9459874 and rs1012656 in regulating FGFR1OP transcription and CCR6 translation, respectively, were supported by expression quantitative trait loci (eQTL) analysis and gene editing technology using the CRISPR/Cas9 system. Immunohistochemistry showed higher expression of CCR6 protein in the livers of patients with PBC than in those of a non-diseased control. In conclusion, we identified primary functional variants in CCR6/FGFR1OP and revealed the molecular mechanisms by which these variants confer PBC-susceptibility in an eQTL-dependent or -independent manner. The approach in this study is applicable for the elucidation of the pathogenesis of other autoimmune disorders in which CCR6/FGFR1OP is known as a susceptibility locus, as well as PBC.

A flexible and parallelizable approach to genome-wide polygenic risk scores.

The heritability of most complex traits is driven by variants throughout the genome. Consequently, polygenic risk scores, which combine information on multiple variants genome-wide, have demonstrated improved accuracy in genetic risk prediction. We present a new two-step approach to constructing genome-wide polygenic risk scores from meta-GWAS summary statistics. Local linkage disequilibrium (LD) is adjusted for in Step 1, followed by, uniquely, long-range LD in Step 2. Our algorithm is highly parallelizable since block-wise analyses in Step 1 can be distributed across a high-performance computing cluster, and flexible, since sparsity and heritability are estimated within each block. Inference is obtained through a formal Bayesian variable selection framework, meaning final risk predictions are averaged over competing models. We compared our method to two alternative approaches: LDPred and lassosum using all seven traits in the Welcome Trust Case Control Consortium as well as meta-GWAS summaries for type 1 diabetes (T1D), coronary artery disease, and schizophrenia. Performance was generally similar across methods, although our framework provided more accurate predictions for T1D, for which there are multiple heterogeneous signals in regions of both short- and long-range LD. With sufficient compute resources, our method also allows the fastest runtimes.

Meta-GWAS on PCSK9 concentrations reveals associations of novel loci outside the PCSK9 locus in White populations.

BACKGROUND AND AIMS: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations. METHODS: We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis. RESULTS: Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD. CONCLUSIONS: We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected.

Data Integration, Imputation, and Meta-analysis for Genome-Wide Association Studies.

Growing genomic and phenotypic datasets require different groups around the world to collaborate and integrate these valuable resources to maximize their benefit and increase reference population sizes for genomic prediction and genome-wide association studies (GWAS). However, different studies use different genotyping techniques which requires a synchronizing step for the genotyped variants called "imputation" before combining them. Optimally, different GWAS datasets can be analysed within a meta-analysis, which recruits summary statistics instead of actual data. This chapter describes the general principles for genotypic imputation and meta-GWAS analysis with a description of study designs and command lines required for such analyses.

Identification and Validation of Candidate Genes from Genome-Wide Association Studies.

Exploiting the statistical associations coming out from a GWAS experiment to identify and validate candidate genes may be potentially difficult and time consuming. To fill the gap between the identification of candidate genes toward their functional validation onto the trait performance, the prioritization of variants underlying the GWAS-associated regions is necessary. In parallel, recent developments in genomics and statistical methods have been achieved notably in human genetic and they are accordingly being adopted in plant breeding toward the study of the genetic architecture of traits to sustain genetic gains. In this chapter, we aim at providing both theoretical and practical aspects underlying three main options including (1) the MetaGWAS analysis, (2) the statistical fine mapping and (3) the integration of functional data toward the identification and validation of candidate genes from a GWAS experiment.

GWAS Case Studies in Wheat.

With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat.

Meta-GWAS identifies the heritability of acute radiation-induced toxicities in head and neck cancer.

BACKGROUND AND PURPOSE: We aimed to the genetic components and susceptibility variants associated with acute radiation-induced toxicities (RITs) in patients with head and neck cancer (HNC). MATERIALS AND METHODS: We performed the largest meta-GWAS of seven European cohorts (n = 4,042). Patients were scored weekly during radiotherapy for acute RITs including dysphagia, mucositis, and xerostomia. We analyzed the effect of variants on the average burden (measured as area under curve, AUC) per each RIT, and standardized total average acute toxicity (STATacute) score using a multivariate linear regression. We tested suggestive variants (p < 1.0x10-5) in discovery set (three cohorts; n = 2,640) in a replication set (four cohorts; n = 1,402). We meta-analysed all cohorts to calculate RITs specific SNP-based heritability, and effect of polygenic risk scores (PRSs), and genetic correlations among RITS. RESULTS: From 393 suggestive SNPs identified in discovery set; 37 were nominally significant (preplication < 0.05) in replication set, but none reached genome-wide significance (pcombined < 5 × 10-8). In-silico functional analyses identified "3'-5'-exoribonuclease activity" (FDR = 1.6e-10) for dysphagia, "inositol phosphate-mediated signalling" for mucositis (FDR = 2.20e-09), and "drug catabolic process" for STATacute (FDR = 3.57e-12) as the most enriched pathways by the RIT specific suggestive genes. The SNP-based heritability (±standard error) was 29 ± 0.08 % for dysphagia, 9 ± 0.12 % (mucositis) and 27 ± 0.09 % (STATacute). Positive genetic correlation was rg = 0.65 (p = 0.048) between dysphagia and STATacute. PRSs explained limited variation of dysphagia (3 %), mucositis (2.5 %), and STATacute (0.4 %). CONCLUSION: In HNC patients, acute RITs are modestly heritable, sharing 10 % genetic susceptibility, when PRS explains < 3 % of their variance. We identified numerus suggestive SNPs, which remain to be replicated in larger studies.

Genome-wide association study and transcriptome analysis dissect the genetic control of silique length in Brassica napus L.

BACKGROUND: Rapeseed is the third-largest oilseed crop after soybeans and palm that produces vegetable oil for human consumption and biofuel for industrial production. Silique length (SL) is an important trait that is strongly related to seed yield in rapeseed. Although many studies related to SL have been reported in rapeseed, only a few candidate genes have been found and cloned, and the genetic mechanisms regulating SL in rapeseed remain unclear. Here, we dissected the genetic basis of SL by genome-wide association studies (GWAS) combined with transcriptome analysis. RESULTS: We identified quantitative trait locus (QTL) for SL using a recombinant inbred line (RIL) population and two independent GWAS populations. Major QTLs on chromosomes A07, A09, and C08 were stably detected in all environments from all populations. Several candidate genes related to starch and sucrose metabolism, plant hormone signal transmission and phenylpropanoid biosynthesis were detected in the main QTL intervals, such as BnaA9.CP12-2, BnaA9.NST2, BnaA7.MYB63, and BnaA7.ARF17. In addition, the results of RNA-seq and weighted gene co-expression network analysis (WGCNA) showed that starch and sucrose metabolism, photosynthesis, and secondary cell wall biosynthesis play an important role in the development of siliques. CONCLUSIONS: We propose that photosynthesis, sucrose and starch metabolism, plant hormones, and lignin content play important roles in the development of rapeseed siliques.