The regulatory landscape of multiple brain regions in outbred heterogeneous stock rats | Zendy

Daniel Munro | Zendy; Tengfei Wang | Zendy; Apurva S. Chitre | Zendy; Oksana Polesskaya | Zendy; Nava Ehsan | Zendy; Jianjun Gao | Zendy; Alexander Gusev | Zendy; Leah C. Solberg Woods | Zendy; Laura Saba | Zendy; Hao Chen | Zendy; Abraham A. Palmer | Zendy; Pejman Mohammadi | Zendy

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The regulatory landscape of multiple brain regions in outbred heterogeneous stock rats

Author(s) -

Daniel Munro,

Tengfei Wang,

Apurva S. Chitre,

Oksana Polesskaya,

Nava Ehsan,

Jianjun Gao,

Alexander Gusev,

Leah C. Solberg Woods,

Laura Saba,

Hao Chen,

Abraham A. Palmer,

Pejman Mohammadi

Publication year - 2022

Publication title -

nucleic acids research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 9.008

H-Index - 537

eISSN - 1362-4954

pISSN - 0305-1048

DOI - 10.1093/nar/gkac912

Subject(s) - biology , expression quantitative trait loci , quantitative trait locus , genome wide association study , genetics , gene , genetic variation , genomics , transcriptome , allele , population , human genetics , genetic association , genotype , computational biology , genome , single nucleotide polymorphism , gene expression , sociology , demography

Heterogeneous Stock (HS) rats are a genetically diverse outbred rat population that is widely used for studying genetics of behavioral and physiological traits. Mapping Quantitative Trait Loci (QTL) associated with transcriptional changes would help to identify mechanisms underlying these traits. We generated genotype and transcriptome data for five brain regions from 88 HS rats. We identified 21 392 cis-QTLs associated with expression and splicing changes across all five brain regions and validated their effects using allele specific expression data. We identified 80 cases where eQTLs were colocalized with genome-wide association study (GWAS) results from nine physiological traits. Comparing our dataset to human data from the Genotype-Tissue Expression (GTEx) project, we found that the HS rat data yields twice as many significant eQTLs as a similarly sized human dataset. We also identified a modest but highly significant correlation between genetic regulatory variation among orthologous genes. Surprisingly, we found less genetic variation in gene regulation in HS rats relative to humans, though we still found eQTLs for the orthologs of many human genes for which eQTLs had not been found. These data are available from the RatGTEx data portal (RatGTEx.org) and will enable new discoveries of the genetic influences of complex traits.

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