Bioinformatics Software and Methods for Genome-wide Association and ChIP-Seq Studies.

Genome-wide Association Studies;Meta-analysis of Genome-wide Association Studies;Gene Set Enrichment Testing;ChIP-seq Experiments;Genetics;Science;Bioinformatics

Welch, Ryan PatrickAbecasis, Goncalo ;

University of Michigan

关键词: Genome-wide Association Studies;    Meta-analysis of Genome-wide Association Studies;    Gene Set Enrichment Testing;    ChIP-seq Experiments;    Genetics;    Science;    Bioinformatics;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/97839/welchr_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Much of the work in modern human genetics and bioinformatics is focused on identifying the connection between our genomes and disease. Genome-wide association studies (GWAS) aim to identify common genetic variants across the genome associated with a disease or trait. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) studies aim to identify genes potentially regulated by disease-related DNA-binding proteins. I describe two bioinformatic tools for researching associated variants from GWAS and visualizing the properties of their genomic regions. The first tool, Snipper, automatically reports the biological functions of genes near associated variants. The second tool, LocusZoom, creates visualizations of the genomic regions near associated variants. I identify 41 genetic variants associated with glycemic traits (fasting levels of glucose, insulin, and glucose measured 2 hours after ingestion), bringing the total number of variants associated with these traits to 53. Of these variants, 33 are also associated with increased type 2 diabetes (T2D) risk. I apply Snipper and LocusZoom to investigate the variants for connections with their associated traits. Future functional follow-up work to investigate these variants will yield additional insights into the mechanisms behind glucose control, and potentially T2D. For ChIP-seq studies, I describe ChIP-Enrich, a method that identifies likely biological function(s) of DNA-binding proteins given knowledge of the functions of the genes surrounding the proteins’ binding sites. ChIP-Enrich is compared with existing methods. The results show that earlier methods do not properly control for the confounding effect of gene length and intergenic distance, and as a result exhibit an inflated type 1 error rate. ChIP-Enrich uses all ChIP-seq peaks for analysis, rather than only those near transcription start sites (TSSs) as in earlier methods, and can therefore potentially identify functions of proteins binding distally to TSSs. ChIP-Enrich may prove useful in future studies for identifying the function of DNA-binding proteins involved in T2D and other multi-genic diseases, and could also be applied to other whole-genome experiments, such as DNA methylation experiments (MeDIP-seq) and open chromatin sequencing (DNAse-seq or FAIRE.)