Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mapping short tandem repeats for liver gene expression traits helps prioritize potential causal variants for complex traits in pigs.

ABSTRACT:

Background

Short tandem repeats (STRs) were recently found to have significant impacts on gene expression and diseases in humans, but their roles on gene expression and complex traits in pigs remain unexplored. This study investigates the effects of STRs on gene expression in liver tissues based on the whole-genome sequences and RNA-Seq data of a discovery cohort of 260 F6 individuals and a validation population of 296 F7 individuals from a heterogeneous population generated from crosses among eight pig breeds.

Results

We identified 5203 and 5868 significantly expression STRs (eSTRs, FDR < 1%) in the F6 and F7 populations, respectively, most of which could be reciprocally validated (π1 = 0.92). The eSTRs explained 27.5% of the cis-heritability of gene expression traits on average. We further identified 235 and 298 fine-mapped STRs through the Bayesian fine-mapping approach in the F6 and F7 pigs, respectively, which were significantly enriched in intron, ATAC peak, compartment A and H3K4me3 regions. We identified 20 fine-mapped STRs located in 100 kb windows upstream and downstream of published complex trait-associated SNPs, which colocalized with epigenetic markers such as H3K27ac and ATAC peaks. These included eSTR of the CLPB, PGLS, PSMD6 and DHDH genes, which are linked with genome-wide association study (GWAS) SNPs for blood-related traits, leg conformation, growth-related traits, and meat quality traits, respectively.

Conclusions

This study provides insights into the effects of STRs on gene expression traits. The identified eSTRs are valuable resources for prioritizing causal STRs for complex traits in pigs.

SUBMITTER: Wu Z

PROVIDER: S-EPMC8762894 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Properties of structural variants and short tandem repeats associated with gene expression and complex traits.

Project description:Structural variants (SVs) and short tandem repeats (STRs) comprise a broad group of diverse DNA variants which vastly differ in their sizes and distributions across the genome. Here, we identify genomic features of SV classes and STRs that are associated with gene expression and complex traits, including their locations relative to eGenes, likelihood of being associated with multiple eGenes, associated eGene types (e.g., coding, noncoding, level of evolutionary constraint), effect sizes, linkage disequilibrium with tagging single nucleotide variants used in GWAS, and likelihood of being associated with GWAS traits. We identify a set of high-impact SVs/STRs associated with the expression of three or more eGenes via chromatin loops and show that they are highly enriched for being associated with GWAS traits. Our study provides insights into the genomic properties of structural variant classes and short tandem repeats that are associated with gene expression and human traits.

| S-EPMC7286898 | biostudies-literature

Integrating functional data to prioritize causal variants in statistical fine-mapping studies.

Project description:Standard statistical approaches for prioritization of variants for functional testing in fine-mapping studies either use marginal association statistics or estimate posterior probabilities for variants to be causal under simplifying assumptions. Here, we present a probabilistic framework that integrates association strength with functional genomic annotation data to improve accuracy in selecting plausible causal variants for functional validation. A key feature of our approach is that it empirically estimates the contribution of each functional annotation to the trait of interest directly from summary association statistics while allowing for multiple causal variants at any risk locus. We devise efficient algorithms that estimate the parameters of our model across all risk loci to further increase performance. Using simulations starting from the 1000 Genomes data, we find that our framework consistently outperforms the current state-of-the-art fine-mapping methods, reducing the number of variants that need to be selected to capture 90% of the causal variants from an average of 13.3 to 10.4 SNPs per locus (as compared to the next-best performing strategy). Furthermore, we introduce a cost-to-benefit optimization framework for determining the number of variants to be followed up in functional assays and assess its performance using real and simulation data. We validate our findings using a large scale meta-analysis of four blood lipids traits and find that the relative probability for causality is increased for variants in exons and transcription start sites and decreased in repressed genomic regions at the risk loci of these traits. Using these highly predictive, trait-specific functional annotations, we estimate causality probabilities across all traits and variants, reducing the size of the 90% confidence set from an average of 17.5 to 13.5 variants per locus in this data.

| S-EPMC4214605 | biostudies-literature

Polymorphic short tandem repeats make widespread contributions to blood and serum traits.

Project description:Short tandem repeats (STRs) are genomic regions consisting of repeated sequences of 1-6 bp in succession. Single-nucleotide polymorphism (SNP)-based genome-wide association studies (GWASs) do not fully capture STR effects. To study these effects, we imputed 445,720 STRs into genotype arrays from 408,153 White British UK Biobank participants and tested for association with 44 blood phenotypes. Using two fine-mapping methods, we identify 119 candidate causal STR-trait associations and estimate that STRs account for 5.2%-7.6% of causal variants identifiable from GWASs for these traits. These are among the strongest associations for multiple phenotypes, including a coding CTG repeat associated with apolipoprotein B levels, a promoter CGG repeat with platelet traits, and an intronic poly(A) repeat with mean platelet volume. Our study suggests that STRs make widespread contributions to complex traits, provides stringently selected candidate causal STRs, and demonstrates the need to consider a more complete view of genetic variation in GWASs.

| S-EPMC10726533 | biostudies-literature

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-02-11 | GSE136703 | GEO

Fine-mapping and cell-specific enrichment at corneal resistance factor loci prioritize candidate causal regulatory variants.

Project description:Corneal resistance factor (CRF) is altered during corneal diseases progression. Genome-wide-association studies (GWAS) indicated potential CRF and disease genetics overlap. Here, we characterise 135 CRF loci following GWAS in 76029 UK Biobank participants. Enrichment of extra-cellular matrix gene-sets, genetic correlation with corneal thickness (70% (SE?=?5%)), reported keratoconus risk variants at 13 loci, all support relevance to corneal stroma biology. Fine-mapping identifies a subset of 55 highly likely causal variants, 91% of which are non-coding. Genomic features enrichments, using all associated variants, also indicate prominent regulatory causal role. We newly established open chromatin landscapes in two widely-used human cornea immortalised cell lines using ATAC-seq. Variants associated with CRF were significantly enriched in regulatory regions from the corneal stroma-derived cell line and enrichment increases to over 5 fold for variants prioritised by fine-mapping-including at GAS7, SMAD3 and COL6A1 loci. Our analysis generates many hypotheses for future functional validation of aetiological mechanisms.

| S-EPMC7732848 | biostudies-literature

The SSV Evaluation System: A Tool to Prioritize Short Structural Variants for Studies of Possible Regulatory and Causal Variants.

Project description:Short structural variants (SSVs) are short genomic variants (<50 bp) other than SNPs. It has been suggested that SSVs contribute to many human complex traits. However, high-throughput analysis of SSVs presents numerous technical challenges. In order to facilitate the discovery and assessment of SSVs, we have developed a prototype bioinformatics tool, "SSV evaluation system," which is a searchable, annotated database of SSVs in the human genome, with associated customizable scoring software that is used to evaluate and prioritize SSVs that are most likely to have significant biological effects and impact on disease risk. This new bioinformatics tool is a component in a larger strategy that we have been using to discover potentially important SSVs within candidate genomic regions that have been identified in genome-wide association studies, with the goal to prioritize potential functional/causal SSVs and focus the follow-up experiments on a relatively small list of strong candidate SSVs. We describe our strategy and discuss how we have used the SSV evaluation system to discover candidate causal variants related to complex neurodegenerative diseases. We present the SSV evaluation system as a powerful tool to guide genetic investigations aiming to uncover SSVs that underlie human complex diseases including neurodegenerative diseases in aging.

| S-EPMC4983215 | biostudies-literature

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [MPRA]

Project description:Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we used seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in three disease-relevant immune cell types, based on a set of features related to regulatory potential. Trait/disease-associated variants were enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 had at least one variant meeting one or both of these criteria, with 3 of these haplotypes having a single prioritized variant. 5 of the 9 prioritized variants were further supported by genetic fine-mapping in our and other studies. Our work provides evidence for the efficacy and limitations of strategies for prioritizing disease- and trait-associated genetic variants.

2020-02-11 | GSE136702 | GEO

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [ATAC-seq]

2020-02-11 | GSE136686 | GEO

Assessing the ability of various genomic features to prioritize causal non-coding variants associated with diseases and traits [CRISPR guide-seq]

2020-02-11 | GSE136693 | GEO

Discovery and quality analysis of a comprehensive set of structural variants and short tandem repeats.

Project description:Structural variants (SVs) and short tandem repeats (STRs) are important sources of genetic diversity but are not routinely analyzed in genetic studies because they are difficult to accurately identify and genotype. Because SVs and STRs range in size and type, it is necessary to apply multiple algorithms that incorporate different types of evidence from sequencing data and employ complex filtering strategies to discover a comprehensive set of high-quality and reproducible variants. Here we assemble a set of 719 deep whole genome sequencing (WGS) samples (mean 42×) from 477 distinct individuals which we use to discover and genotype a wide spectrum of SV and STR variants using five algorithms. We use 177 unique pairs of genetic replicates to identify factors that affect variant call reproducibility and develop a systematic filtering strategy to create of one of the most complete and well characterized maps of SVs and STRs to date.

| S-EPMC7287045 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data