Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Despite representing an important source of genetic variation, tandem repeats (TRs) remain poorly studied due to technical difficulties. We hypothesized that TRs can operate as expression (eQTLs) and methylation (mQTLs) quantitative trait loci. To test this we analyzed the effect of variation at 4849 promoter-associated TRs, genotyped in 120 individuals, on neighboring gene expression and DNA methylation. Polymorphic promoter TRs were associated with increased variance in local gene expression and DNA methylation, suggesting functional consequences related to TR variation. We identified >100 TRs associated with expression/methylation levels of adjacent genes. These potential eQTL/mQTL TRs were enriched for overlaps with transcription factor binding and DNaseI hypersensitivity sites, providing a rationale for their effects. Moreover, we showed that most TR variants are poorly tagged by nearby single nucleotide polymorphisms (SNPs) markers, indicating that many functional TR variants are not effectively assayed by SNP-based approaches. Our study assigns biological significance to TR variations in the human genome, and suggests that a significant fraction of TR variations exert functional effects via alterations of local gene expression or epigenetics. We conclude that targeted studies that focus on genotyping TR variants are required to fully ascertain functional variation in the genome.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4857002PMC
http://dx.doi.org/10.1093/nar/gkw219DOI Listing

Publication Analysis

Top Keywords

gene expression
16
expression dna
12
dna methylation
12
tandem repeats
8
trs associated
8
local gene
8
trs
6
gene
5
expression
5
polymorphic tandem
4

Similar Publications

Background: Alzheimer's disease (AD) patients and animal models exhibit an altered gut microbiome that is associated with pathological changes in the brain. Intestinal miRNA enters bacteria and regulates bacterial metabolism and proliferation. This study aimed to investigate whether the manipulation of miRNA could alter the gut microbiome and AD pathologies.

View Article and Find Full Text PDF

Nuclear receptors (NRs) are a superfamily of ligand-activated transcription factors that regulate gene expression in response to metabolic, hormonal, and environmental signals. These receptors play a critical role in metabolic homeostasis, inflammation, immune function, and disease pathogenesis, positioning them as key therapeutic targets. This review explores the mechanistic roles of NRs such as PPARs, FXR, LXR, and thyroid hormone receptors (THRs) in regulating lipid and glucose metabolism, energy expenditure, cardiovascular health, and neurodegeneration.

View Article and Find Full Text PDF

Background: Recent advances in high-throughput sequencing technologies have enabled the collection and sharing of a massive amount of omics data, along with its associated metadata-descriptive information that contextualizes the data, including phenotypic traits and experimental design. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability and limit secondary analyses.

View Article and Find Full Text PDF

Background: Gastric cancer is one of the most common cancers worldwide, with its prognosis influenced by factors such as tumor clinical stage, histological type, and the patient's overall health. Recent studies highlight the critical role of lymphatic endothelial cells (LECs) in the tumor microenvironment. Perturbations in LEC function in gastric cancer, marked by aberrant activation or damage, disrupt lymphatic fluid dynamics and impede immune cell infiltration, thereby modulating tumor progression and patient prognosis.

View Article and Find Full Text PDF

Background: Most RNA-seq datasets harbor genes with extreme expression levels in some samples. Such extreme outliers are usually treated as technical errors and are removed from the data before further statistical analysis. Here we focus on the patterns of such outlier gene expression to investigate whether they provide insights into the underlying biology.

View Article and Find Full Text PDF