Dataset Information

Using chromatin marks to interpret and localize genetic associations to complex human traits and diseases.

ABSTRACT: While studies to associate genomic variants to complex traits have gradually become increasingly productive, the molecular mechanisms that underlie these associations are rarely understood. Because only a small fraction of trait-associated variants can be linked to coding sequences, investigators have speculated that many of the underlying causal alleles influence non-coding gene regulatory sites. Recent studies have successfully identified examples of mechanisms for non-coding alleles at individual loci. Now, genome-wide chromatin assays have resulted in maps of dozens of genomic annotations of the non-coding genome across multiple different tissues, cell types and cell lines. This gives a tremendous opportunity to integrate these annotations with complex trait signals to globally interpret associated variants, and prioritize likely causal alleles. Here, we review the examples of mechanisms by which non-coding, common alleles result in phenotypes. We discuss the efforts to integrate common trait-associated variants with genomic annotations. Finally, we highlight some caveats of these approaches and outline future directions for improvement.

SUBMITTER: Trynka G

PROVIDER: S-EPMC4073234 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using chromatin marks to interpret and localize genetic associations to complex human traits and diseases.

Trynka Gosia G Raychaudhuri Soumya S

Current opinion in genetics & development 20131125 6

While studies to associate genomic variants to complex traits have gradually become increasingly productive, the molecular mechanisms that underlie these associations are rarely understood. Because only a small fraction of trait-associated variants can be linked to coding sequences, investigators have speculated that many of the underlying causal alleles influence non-coding gene regulatory sites. Recent studies have successfully identified examples of mechanisms for non-coding alleles at indivi ...[more]

PMID: 24287333

Similar Datasets

Project description:Purpose of reviewNeurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits.Recent findingsSeveral common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits.SummaryGWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.

Project description:The Mu transposon system of maize is highly active, with each of the approximately 50-100 copies transposing on average once each generation. The approximately one dozen distinct Mu transposons contain highly similar approximately 215 bp terminal inverted repeats (TIRs) and generate 9-bp target site duplications (TSDs) upon insertion. Using a novel genome walking strategy that uses these conserved TIRs as primer binding sites, Mu insertion sites were amplified from Mu stocks and sequenced via 454 technology. 94% of approximately 965,000 reads carried Mu TIRs, demonstrating the specificity of this strategy. Among these TIRs, 21 novel Mu TIRs were discovered, revealing additional complexity of the Mu transposon system. The distribution of >40,000 non-redundant Mu insertion sites was strikingly non-uniform, such that rates increased in proportion to distance from the centromere. An identified putative Mu transposase binding consensus site does not explain this non-uniformity. An integrated genetic map containing more than 10,000 genetic markers was constructed and aligned to the sequence of the maize reference genome. Recombination rates (cM/Mb) are also strikingly non-uniform, with rates increasing in proportion to distance from the centromere. Mu insertion site frequencies are strongly correlated with recombination rates. Gene density does not fully explain the chromosomal distribution of Mu insertion and recombination sites, because pronounced preferences for the distal portion of chromosome are still observed even after accounting for gene density. The similarity of the distributions of Mu insertions and meiotic recombination sites suggests that common features, such as chromatin structure, are involved in site selection for both Mu insertion and meiotic recombination. The finding that Mu insertions and meiotic recombination sites both concentrate in genomic regions marked with epigenetic marks of open chromatin provides support for the hypothesis that open chromatin enhances rates of both Mu insertion and meiotic recombination.

Dataset Information

Using chromatin marks to interpret and localize genetic associations to complex human traits and diseases.

Publications

Using chromatin marks to interpret and localize genetic associations to complex human traits and diseases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets