postGWAS: A web server for deciphering the causality post the genome-wide association studies

While genome-wide association studies (GWAS) have unequivocally identified vast disease susceptibility variants, a majority of them are situated in non-coding regions and are in high linkage disequilibrium (LD). To pave the way of translating GWAS signals to clinical drug targets, it is essential to identify the underlying causal variants and further causal genes. To this end, a myriad of post-GWAS methods have been devised, each grounded in distinct principles including fine-mapping, co-localization, and transcriptome-wide association study (TWAS) techniques. Yet, no platform currently exists that seamlessly integrates these diverse post-GWAS methodologies. In this work, we present a user-friendly web server for post-GWAS analysis, that seamlessly integrates 9 distinct methods with 12 models, categorized by fine-mapping, colocalization, and TWAS. The server mainly helps users decipher the causality hindered by complex GWAS signals, including casual variants and casual genes, without the burden of computational skills and complex environment configuration, and provides a convenient platform for post-GWAS analysis, result visualization, facilitating the understanding and interpretation of the genome-wide association studies. The postGWAS server is available at http://g2g.biographml.com/.

Functional Annotation and Gene Set Analysis of Gastric Cancer Risk Loci in a Korean Population

PURPOSE

We aimed to identify the associated single nucleotide polymorphisms (SNPs) with gastric cancer (GC) risk by genome-wide association study (GWAS) and to explore the pathway enrichment of implicated genes and gene-sets with expression patterns.

MATERIALS AND METHODS

The study population was comprised of 1,253 GC cases and 4,827 controls from National Cancer Center and an urban community of the Korean Genome Epidemiology Study and their genotyping was performed. SNPs were annotated, and mapped to genes to prioritize by three mapping approaches by functional mapping and annotation (FUMA). The gene-based analysis and gene-set analysis were conducted with full GWAS summary data using MAGMA. Gene-set pathway enrichment test with those prioritized genes were performed.

RESULTS

In GWAS, rs2303771, a nonsynonymous variant of KLHDC4 gene was top SNP associated significantly with GC (odds ratio, 2.59; p=1.32×10-83). In post-GWAS, 71 genes were prioritized. In gene-based GWAS, seven genes were under significant p < 3.80×10-6 (0.05/13,114); DEFB108B had the lowest p=5.94×10-15, followed by FAM86C1 (p=1.74×10-14), PSCA (p=1.81×10-14), and KLHDC4 (p=5.00×10-10). In gene prioritizing, KLDHC4 was the only gene mapped with all three gene-mapping approaches. In pathway enrichment test with prioritized genes, FOLR2, PSCA, LY6K, LYPD2, and LY6E showed strong enrichment related to cellular component of membrane; a post-translation modification by synthesis of glycosylphosphatidylinositol (GPI)-anchored proteins pathway.

CONCLUSION

While 37 SNPs were significantly associated with the risk of GC, genes involved in signaling pathways related to purine metabolism and GPI-anchored protein in cell membrane are pinpointed to be playing important role in GC.

CRISPR/Cas9 genome editing demonstrates functionality of the autoimmunity-associated SNP rs12946510

Genome-wide association studies (GWAS) map genetic associations of complex traits with precision limited to a linkage disequilibrium group. To translate GWAS results into new understanding of disease mechanisms, individual causative polymorphisms and their target genes should be identified. CRISPR/Cas9 genome editing can be used to create isogenic cell lines bearing alternative genotypes of candidate single-nucleotide polymorphisms to test their causality and to reveal gene targets. An intergenic polymorphism rs12946510 is associated with multiple sclerosis, inflammatory bowel disease and asthma. We created sublines of the T-helper cell line bearing alternative genotypes of rs12946510 and showed that its risk ("T") allele is associated with lower expression of IKZF3 and ORMDL3 genes and reduced cell activation. Our editing procedure can become an effective tool for discovering new genes involved in pathogenesis of complex diseases.

Discovery and Functional Characterization of Two Regulatory Variants Underlying Lupus Susceptibility at 2p13.1

Genome-wide association studies have identified 2p13.1 as a prominent susceptibility locus for systemic lupus erythematosus (SLE)—a complex, multisystem autoimmune disease. However, the identity of underlying causal variant (s) and molecular mechanisms for increasing disease susceptibility are poorly understood. Using meta-analysis (cases = 10,252, controls = 21,604) followed by conditional analysis, bioinformatic annotation, and eQTL and 3D-chromatin interaction analyses, we computationally prioritized potential functional variants and subsequently experimentally validated their effects. Ethnicity-specific meta-analysis revealed striking allele frequency differences between Asian and European ancestries, but with similar odds ratios. We identified 20 genome-wide significant (p < 5 × 10−8) variants, and conditional analysis pinpointed two potential functional variants, rs6705628 and rs2272165, likely to explain the association. The two SNPs are near DGUOK, mitochondrial deoxyguanosine kinase, and its associated antisense RNA DGUOK-AS1. Using luciferase reporter gene assays, we found significant cell type- and allele-specific promoter activity at rs6705628 and enhancer activity at rs2272165. This is supported by ChIP-qPCR showing allele-specific binding with three histone marks (H3K27ac, H3K4me3, and H3K4me1), RNA polymerase II (Pol II), transcriptional coactivator p300, CCCTC-binding factor (CTCF), and transcription factor ARID3A. Transcriptome data across 28 immune cell types from Asians showed both SNPs are cell-type-specific but only in B-cells. Splicing QTLs showed strong regulation of DGUOK-AS1. Genotype-specific DGOUK protein levels are supported by Western blots. Promoter capture Hi-C data revealed long-range chromatin interactions between rs2272165 and several nearby promoters, including DGUOK. Taken together, we provide mechanistic insights into how two noncoding variants underlie SLE risk at the 2p13.1 locus.

Detection of candidate gene networks involved in resistance to Sclerotinia sclerotiorum in soybean

Quantitative trait locus (QTL) mapping often yields associations with dissimilar loci/genes as a consequence of diverse factors. One trait for which very limited agreement between mapping studies has been observed is resistance to white mold in soybean. To explore whether different approaches applied to a single data set could lead to more consistent results, haplotype-trait association and epistasis interaction effects were explored as a complement to a more conventional marker-trait analysis. At least 10 genomic regions were significantly associated with Sclerotinia sclerotiorum resistance in soybean, which have not been previously reported. At a significance level of α = 0.05, haplotype-trait association showed that the most prominent signal originated from a haplotype with 4-SNP (single nucleotide polymorphism) on chromosome 17, and single SNP-trait analysis located a nucleotide polymorphism at position rs34387780 on chromosome 3. All of the peak-SNPs (p-value < 0.05) of each chromosome also appeared in their respective haplotypes. Samples with extreme phenotypes were singled-out for association studies, 25-30% from each end of the phenotypic spectrum appeared in the present investigation to be the most appropriate sample size. Some key genes were identified by epistasis interaction analysis. By combining information on the nearest positional genes indicated that most loci have not been previously reported. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses suggest potential candidate genes underlying callose deposition in the cell wall and mitogen-activated protein kinase (MAPK) signaling pathway-plant, as well as plant-pathogen interaction pathway, were activated. Integration of multi-method genome-wide association study (GWAS) revealed novel genomic regions and promising candidate genes in novel regions, which include Glyma.01g048500, Glyma.03g129100, Glyma.17g072200, and the Dishevelled (Dvl) family of proteins on chromosomes 1, 3, 17, and 20, respectively.

Genome wide association study for the identification of genes associated with tail fat deposition in Chinese sheep breeds

Chinese indigenous sheep can be classified into three types based on tail morphology: fat-tailed, fat-rumped, and thin-tailed sheep, of which the typical breeds are large-tailed Han sheep, Altay sheep, and Tibetan sheep, respectively. To unravel the molecular genetic basis underlying the phenotypic differences among Chinese indigenous sheep with these three different tail types, we used ovine high-density 600K single nucleotide polymorphism (SNP) arrays to detect genome-wide associations, and performed general linear model analysis to identify candidate genes, using genotyping technology to validate the candidate genes. Tail type is an important economic trait in sheep. However, the candidate genes associated with tail type are not known. The objective of this study was to identify SNP markers, genes, and chromosomal regions related to tail traits. We performed a genome-wide association study (GWAS) using data from 40 large-tailed Han sheep, 40 Altay sheep (cases) and 40 Tibetan sheep (controls). A total of 31 significant (P<0.05) SNPs associated with tail-type traits were detected. For significant SNPs' loci, we determined their physical location and performed a screening of candidate genes within each region. By combining information from previously reported and annotated biological functional genes, we identified SPAG17, Tbx15, VRTN, NPC2, BMP2 and PDGFD as the most promising candidate genes for tail-type traits. Based on the above identified candidate genes for tail-type traits, BMP2 and PDGFD genes were selected to investigate the relationship between SNPs within the tails in the Altay and Tibetan populations. rs119 T>C in exon1 of the BMP2 gene and one SNP in exon4 (rs69 C>A) of the PDGFD gene were detected. rs119 was of the TT genotype in Altay sheep, while it was of the CC genotype in Tibetan sheep. On rs69 of the PDGFD gene, Altay sheep presented with the CC genotype; however, Tibetan sheep presented with the AA genotype.

Cocaine reward is reduced by decreased expression of receptor-type protein tyrosine phosphatase D (PTPRD) and by a novel PTPRD antagonist

Receptor-type protein tyrosine phosphatase D (PTPRD) is a neuronal cell-adhesion molecule/synaptic specifier that has been implicated in addiction vulnerability and stimulant reward by human genomewide association and mouse cocaine-conditioned place-preference data. However, there have been no reports of effects of reduced expression on cocaine self-administration. There have been no reports of PTPRD targeting by any small molecule. There are no data about behavioral effects of any PTPRD ligand. We now report (i) robust effects of heterozygous PTPRD KO on cocaine self-administration (These data substantially extend prior conditioned place-preference data and add to the rationale for PTPRD as a target for addiction therapeutics.); (ii) identification of 7-butoxy illudalic acid analog (7-BIA) as a small molecule that targets PTPRD and inhibits its phosphatase with some specificity; (iii) lack of toxicity when 7-BIA is administered to mice acutely or with repeated dosing; (iv) reduced cocaine-conditioned place preference when 7-BIA is administered before conditioning sessions; and (v) reductions in well-established cocaine self-administration when 7-BIA is administered before a session (in WT, not PTPRD heterozygous KOs). These results add to support for PTPRD as a target for medications to combat cocaine use disorders. 7-BIA provides a lead compound for addiction therapeutics.

Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle

Background

Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes.

Results

We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle.

Conclusion

Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5050-x) contains supplementary material, which is available to authorized users.

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

Background

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of “Gene Ontology” (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability.

Results

Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020).

Conclusions

Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4004-z) contains supplementary material, which is available to authorized users.

Effect of polymorphisms in the CAMKMT gene on growth traits in Ujumqin sheep

Our previous genome-wide association study in sheep revealed that OAR3-84073899.1 (SNP31) in intron 8 of the CAMKMT gene was significantly associated with post-weaning gain at the genomic level. Herein, we performed a replication study to investigate single nucleotide polymorphisms (SNPs) within the CAMKMT gene exons, and 1000 bp of the 5'- and 3'-intranslated regions (UTRs) and their associations with growth traits in Ujumqin sheep. Five SNPs were identified through DNA pool sequencing technology: SNP26 in the 5'-UTR, SNP06 in exon 5, SNP07 in exon 8 and SNP27 and SNP28 in the 3'-UTR. Six SNPs, including SNP31 in intron 8, were genotyped in the validation group of 343 Ujumqin sheep, and each SNP was classified into three genotypes. The chi-square test suggested that all the variations were in Hardy-Weinberg equilibrium (P > 0.05) except for SNP28 and SNP31. Linkage disequilibrium analysis showed that SNP07 and SNP31 were strongly linked. An association analysis suggested that SNP06 was significantly associated with chest girth at 6 months of age (P < 0.05). SNP07 exhibited significant correlation with body weight and chest girth at 4 months of age and with body weight, chest girth and chest width at 6 months of age (P < 0.05). SNP27 was highly associated with body weight and chest girth at 4 months of age (P < 0.05), and SNP28 was extremely significantly associated with body weight and chest girth at 4 months of age and with chest girth at 6 months of age (P < 0.01). SNP31 was significantly associated with body weight and shin circumference at 4 months of age and with post-weaning gain (P < 0.05). Association analysis of the combined effect of SNP07 and SNP31 showed significant correlation with body weight and chest girth at four of months of age (P < 0.05) and with body weight and chest girth at 6 months of age (P < 0.05). These results indicate that the SNPs could be used as meritorious and available genetic markers in growth traits breeding and that the CAMKMT gene may be one of the key candidate genes that affect Ujumqin economic traits.

Pathway, in silico and tissue-specific expression quantitative analyses of oesophageal squamous cell carcinoma genome-wide association studies data

BACKGROUND

Oesophageal cancer is the fourth leading cause of cancer death in China where essentially all cases are histologically oesophageal squamous cell carcinoma (ESCC). Agnostic pathway-based analyses of genome-wide association study (GWAS) data combined with tissue-specific expression quantitative trait loci (eQTL) analysis and publicly available functional data can identify biological pathways and/or genes enriched with functionally-relevant disease-associated variants.

METHOD

We used the adaptive multilocus joint test to analyse 1827 pathways containing 6060 genes using GWAS data from 1942 ESCC cases and 2111 controls with Chinese ancestry. We examined the function of risk alleles using in silico and eQTL analyses in oesophageal tissues.

RESULTS

Associations with ESCC risk were observed for 36 pathways predominantly involved in apoptosis, cell cycle regulation and DNA repair and containing known GWAS-associated genes. After excluding genes with previous GWAS signals, candidate pathways (and genes) for ESCC risk included taste transduction (KEGG_hsa04742; TAS2R13, TAS2R42, TAS2R14, TAS2R46,TAS2R50), long-patch base excision repair (Reactome_pid; POLD2) and the metabolics pathway (KEGG_hsa01100; MTAP, GAPDH, DCTD, POLD2, AMDHD1). We identified and validated CASP8 rs13016963 and IDH2 rs11630814 as eQTLs, and CASP8 rs3769823 and IDH2 rs4561444 as the potential functional variants in high-linkage disequilibrium with these single nucleotide polymorphisms (SNPs), respectively. Further, IDH2 mRNA levels were down-regulated in ESCC (tumour:normal-fold change = 0.69, P =  .75E-14).

CONCLUSION

Agnostic pathway-based analyses and integration of multiple types of functional data provide new evidence for the contribution of genes in taste transduction and metabolism to ESCC susceptibility, and for the functionality of both established and new ESCC risk-related SNPs.

Systems genetics: From GWAS to disease pathways

Most common diseases are complex, involving multiple genetic and environmental factors and their interactions. In the past decade, genome-wide association studies (GWAS) have successfully identified thousands of genetic variants underlying susceptibility to complex diseases. However, the results from these studies often do not provide evidence on how the variants affect downstream pathways and lead to the disease. Therefore, in the post-GWAS era the greatest challenge lies in combining GWAS findings with additional molecular data to functionally characterize the associations. The advances in various ~omics techniques have made it possible to investigate the effect of risk variants on intermediate molecular levels, such as gene expression, methylation, protein abundance or metabolite levels. As disease aetiology is complex, no single molecular analysis is expected to fully unravel the disease mechanism. Multiple molecular levels can interact and also show plasticity in different physiological conditions, cell types and disease stages. There is therefore a great need for new integrative approaches that can combine data from different molecular levels and can help construct the causal inference from genotype to phenotype. Systems genetics is such an approach; it is used to study genetic effects within the larger scope of systems biology by integrating genotype information with various ~omics datasets as well as with environmental and physiological variables. In this review, we describe this approach and discuss how it can help us unravel the molecular mechanisms through which genetic variation causes disease. This article is part of a Special Issue entitled: From Genome to Function.