Diverse environmental perturbations reveal the evolution and context-dependency of genetic effects on gene expression levels.
Diverse environmental perturbations reveal the evolution and context-dependency of genetic effects on gene expression levels.
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DOI:
10.1101/gr.276430.121
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发表时间:
2022-10
期刊:
影响因子:
7
通讯作者:
Ayroles, Julien F.
中科院分区:
文献类型:
--
作者:
Lea, Amanda J.;Peng, Julie;Ayroles, Julien F.
There is increasing appreciation that, in addition to being shaped by an individual's genotype and environment, most complex traits are also determined by poorly understood interactions between these two factors. So-called “genotype × environment” (G×E) interactions remain difficult to map at the organismal level but can be uncovered using molecular phenotypes. To do so at large scale, we used TM3′seq to profile transcriptomes across 12 cellular environments in 544 immortalized B cell lines from the 1000 Genomes Project. We mapped the genetic basis of gene expression levels across environments and revealed a context-dependent genetic architecture: The average heritability of gene expression levels increased in treatment relative to control conditions, and on average, each treatment revealed new expression quantitative trait loci (eQTLs) at 11% of genes. Across our experiments, 22% of all identified eQTLs were context-dependent, and this group was enriched for trait- and disease-associated loci. Further, evolutionary analyses suggested that positive selection has shaped G×E loci involved in responding to immune challenges and hormones but not to man-made chemicals. We hypothesize that this reflects a reduced opportunity for selection to act on responses to molecules recently introduced into human environments. Together, our work highlights the importance of considering an exposure's evolutionary history when studying and interpreting G×E interactions, and provides new insight into the evolutionary mechanisms that maintain G×E loci in human populations.
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DOI:
10.1093/bioinformatics/btu638
发表时间:
2015-01-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Anders S;Pyl PT;Huber W
通讯作者:
Huber W
影响因子:
64.8
作者:
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者:
Montgomery SB
影响因子:
64.8
作者:
通讯作者:
--
影响因子:
9.8
作者:
Dahl, Andy;Khiem Nguyen;Zaitlen, Noah
通讯作者:
Zaitlen, Noah
DOI:
10.1073/pnas.1115761109
发表时间:
2012-01-24
影响因子:
11.1
作者:
Barreiro, Luis B.;Tailleux, Ludovic;Gilad, Yoav
通讯作者:
Gilad, Yoav