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Functional Annotation of GWAS Loci Using Public Transcriptome and Epigenome Datasets Reveals Non-Coding Genes and
Chunting Yang1,2,3, Xiangyuan Yu4, Erica L Kleinbrink5
1Department of Biology, College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou 325035, China.
This study prioritizes genetic variants linked to body mass index (BMI) by analyzing non-coding DNA. Researchers identified several long non-coding RNA (lncRNA) genes associated with obesity risk, offering targets for future research.
Area of Science:
- Genetics
- Genomics
- Molecular Biology
Background:
- Genome-wide association studies (GWAS) have identified many genetic variants associated with body mass index (BMI).
- The functional roles of single nucleotide polymorphisms (SNPs) in non-coding DNA regions influencing BMI are largely unknown.
- Understanding these non-coding variants is crucial for unraveling obesity's genetic architecture.
Purpose of the Study:
- To prioritize functional candidate loci among 94 BMI-associated SNPs using a multi-criteria scoring system.
- To identify non-coding variants, particularly those within long non-coding RNA (lncRNA) genes, that may contribute to BMI regulation.
- To provide a foundation for experimental validation of obesity-associated non-coding variants.
Main Methods:
- Implemented an integrative 7-criterion quantitative scoring system to prioritize BMI-associated SNPs.
- Evaluated criteria including gene localization, histone modifications, transcription factor binding sites (TFBS), SNP clouds, tissue expression, evolutionary conservation, and COVID-19 associations.
- Focused on SNPs located within lncRNA gene bodies for prioritized functional assessment.
Main Results:
- Six BMI-associated SNPs were identified within lncRNA genes (e.g., rs2245368 in *DTX2P1-UPK3BP1-PMS2P11*, rs2033529 in *LINC00951*).
- Multiple variants showed evidence of regulatory potential via TFBS (e.g., rs1928295 with GATA2, rs13201877 with 64 factors) and epigenomic data (DNase I hypersensitivity, chromatin accessibility).
- Most identified BMI risk alleles are conserved across primates, indicating ancient regulatory roles.
Conclusions:
- The study successfully prioritized functional candidate non-coding regulatory elements associated with BMI.
- lncRNA gene bodies represent a significant location for obesity-associated non-coding variants.
- The findings provide a refined list of obesity-associated non-coding variants for subsequent functional validation and mechanistic studies.
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