Dataset Information

Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.

ABSTRACT: Considerable progress towards an understanding of complex diseases has been made in recent years due to the development of high-throughput genotyping technologies. Using microarrays that contain millions of single-nucleotide polymorphisms (SNPs), Genome Wide Association Studies (GWASs) have identified SNPs that are associated with many complex diseases or traits. For example, as of February 2015, 2111 association studies have identified 15,396 SNPs for various diseases and traits, with the number of identified SNP-disease/trait associations increasing rapidly in recent years. However, it has been difficult for researchers to understand disease risk from GWAS results. This is because most GWAS-identified SNPs are located in non-coding regions of the genome. It is important to consider that the GWAS-identified SNPs serve only as representatives for all SNPs in the same haplotype block, and it is equally likely that other SNPs in high linkage disequilibrium (LD) with the array-identified SNPs are causal for the disease. Because it was hoped that disease-associated coding variants would be identified if the true casual SNPs were known, investigators have expanded their analyses using LD calculation and fine-mapping. However, such analyses also identified risk-associated SNPs located in non-coding regions. Thus, the GWAS field has been left with the conundrum as to how a single-nucleotide change in a non-coding region could confer increased risk for a specific disease. One possible answer to this puzzle is that the variant SNPs cause changes in gene expression levels rather than causing changes in protein function. This review provides a description of (1) advances in genomic and epigenomic approaches that incorporate functional annotation of regulatory elements to prioritize the disease risk-associated SNPs that are located in non-coding regions of the genome for follow-up studies, (2) various computational tools that aid in identifying gene expression changes caused by the non-coding disease-associated SNPs, and (3) experimental approaches to identify target genes of, and study the biological phenotypes conferred by, non-coding disease-associated SNPs.

SUBMITTER: Tak YG

PROVIDER: S-EPMC4696349 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.

Tak Yu Gyoung YG Farnham Peggy J PJ

Epigenetics & chromatin 20151230

Considerable progress towards an understanding of complex diseases has been made in recent years due to the development of high-throughput genotyping technologies. Using microarrays that contain millions of single-nucleotide polymorphisms (SNPs), Genome Wide Association Studies (GWASs) have identified SNPs that are associated with many complex diseases or traits. For example, as of February 2015, 2111 association studies have identified 15,396 SNPs for various diseases and traits, with the numbe ...[more]

PMID: 26719772

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Project description:Genetic risk factors for osteoporosis, a prevalent disease associated with aging, have been examined in many genome-wide association studies (GWASs). A major challenge is to prioritize transcription-regulatory GWAS-derived variants that are likely to be functional. Given the critical role of epigenetics in gene regulation, we have used an unusual epigenetics-based and transcription-based approach to identify some of the credible regulatory single-nucleotide polymorphisms (SNPs) relevant to osteoporosis from 38 reported bone mineral density (BMD) GWASs. Using Roadmap databases, we prioritized SNPs based upon their overlap with strong enhancer or promoter chromatin preferentially in osteoblasts relative to 12 heterologous cell culture types. We also required that these SNPs overlap open chromatin (Deoxyribonuclease I [DNaseI]-hypersensitive sites) and DNA sequences predicted to bind to osteoblast-relevant transcription factors in an allele-specific manner. From >50,000 GWAS-derived SNPs, we identified 14 novel and credible regulatory SNPs (Tier-1 SNPs) for osteoporosis risk. Their associated genes, BICC1, LGR4, DAAM2, NPR3, or HMGA2, are involved in osteoblastogenesis or bone homeostasis and regulate cell signaling or enhancer function. Four of these genes are preferentially expressed in osteoblasts. BICC1, LGR4, and DAAM2 play important roles in canonical Wnt signaling, a pathway critical for bone formation and repair. The transcription factors predicted to bind to the Tier-1 SNP-containing DNA sequences also have bone-related functions. We present evidence that some of the Tier-1 SNPs exert their effects on BMD risk indirectly through little-studied long noncoding RNA (lncRNA) genes, which may, in turn, control the nearby bone-related protein-encoding gene. Our study illustrates a method to identify novel BMD-related causal regulatory SNPs for future study and to prioritize candidate regulatory GWAS-derived SNPs, in general. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Project description:BackgroundThe evaluation of less frequent genetic variants and their effect on complex disease pose new challenges for genomic research. To investigate whether epigenetic data can be used to inform aggregate rare-variant association methods (RVAM), we assessed whether variants more significantly associated with colorectal cancer (CRC) were preferentially located in non-coding regulatory regions, and whether enrichment was specific to colorectal tissues.MethodsActive regulatory elements (ARE) were mapped using data from 127 tissues and cell-types from NIH Roadmap Epigenomics and Encyclopedia of DNA Elements (ENCODE) projects. We investigated whether CRC association p-values were more significant for common variants inside versus outside AREs, or 2) inside colorectal (CR) AREs versus AREs of other tissues and cell-types. We employed an integrative epigenomic RVAM for variants with allele frequency <1%. Gene sets were defined as ARE variants within 200 kilobases of a transcription start site (TSS) using either CR ARE or ARE from non-digestive tissues. CRC-set association p-values were used to evaluate enrichment of less frequent variant associations in CR ARE versus non-digestive ARE.ResultsARE from 126/127 tissues and cell-types were significantly enriched for stronger CRC-variant associations. Strongest enrichment was observed for digestive tissues and immune cell types. CR-specific ARE were also enriched for stronger CRC-variant associations compared to ARE combined across non-digestive tissues (p-value = 9.6 × 10-4). Additionally, we found enrichment of stronger CRC association p-values for rare variant sets of CR ARE compared to non-digestive ARE (p-value = 0.029).ConclusionsIntegrative epigenomic RVAM may enable discovery of less frequent variants associated with CRC, and ARE of digestive and immune tissues are most informative. Although distance-based aggregation of less frequent variants in CR ARE surrounding TSS showed modest enrichment, future association studies would likely benefit from joint analysis of transcriptomes and epigenomes to better link regulatory variation with target genes.

Project description:BACKGROUND: Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. RESULTS: The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. CONCLUSIONS: Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Dataset Information

Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.

Publications

Making sense of GWAS: using epigenomics and genome engineering to understand the functional relevance of SNPs in non-coding regions of the human genome.

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