Your browser doesn't support javascript.
loading
A resource for integrated genomic analysis of the human liver.
Zhou, Yi-Hui; Gallins, Paul J; Etheridge, Amy S; Jima, Dereje; Scholl, Elizabeth; Wright, Fred A; Innocenti, Federico.
Affiliation
  • Zhou YH; Department of Biological Sciences, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA. yihui_zhou@ncsu.edu.
  • Gallins PJ; Bioinformatics Research Center, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA. yihui_zhou@ncsu.edu.
  • Etheridge AS; Bioinformatics Research Center, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA.
  • Jima D; Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.
  • Scholl E; Bioinformatics Research Center, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA.
  • Wright FA; Bioinformatics Research Center, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA.
  • Innocenti F; Department of Biological Sciences, North Carolina State University, Raleigh NC State University, Raleigh, NC, 27695, USA.
Sci Rep ; 12(1): 15151, 2022 09 07.
Article in En | MEDLINE | ID: mdl-36071064
ABSTRACT
In this study, we generated whole-transcriptome RNA-Seq from n = 192 genotyped liver samples and used these data with existing data from the GTEx Project (RNA-Seq) and previous liver eQTL (microarray) studies to create an enhanced transcriptomic sequence resource in the human liver. Analyses of genotype-expression associations show pronounced enrichment of associations with genes of drug response. The associations are primarily consistent across the two RNA-Seq datasets, with some modest variation, indicating the importance of obtaining multiple datasets to produce a robust resource. We further used an empirical Bayesian model to compare eQTL patterns in liver and an additional 20 GTEx tissues, finding that MHC genes, and especially class II genes, are enriched for liver-specific eQTL patterns. To illustrate the utility of the resource to augment GWAS analysis with small sample sizes, we developed a novel meta-analysis technique to combine several liver eQTL data sources. We also illustrate its application using a transcriptome-enhanced re-analysis of a study of neutropenia in pancreatic cancer patients. The associations of genotype with liver expression, including splice variation and its genetic associations, are made available in a searchable genome browser.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Quantitative Trait Loci / Genome-Wide Association Study Type of study: Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Quantitative Trait Loci / Genome-Wide Association Study Type of study: Prognostic_studies / Systematic_reviews Limits: Humans Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Estados Unidos
...