Understanding mechanisms underlying human gene expression variation with RNA sequencing
Open accessAbstract
Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. Although all eQTL studies so far have assayed messenger RNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. By pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated untranslated regions and more than 100 new putative protein-coding exons. Using the genotypes from the HapMap project, we identified more than a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act by a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within and near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing and allele-specific expression across individuals.
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Previous eQTL studies in genetically diverse populations suggest that the most significant eQTL tend to be local.
“Previous eQTL studies in genetically diverse populations suggest that the most significant eQTL tend to be local (Rockman and Kruglyak 2006; Pickrell et al. 2010; Aylor et al. 2011; Lappalainen et al. 2013).”
From RNA-Seq Alignment to Individualized Genomes Improves Transcript Abundance Estimates in Multiparent Populations (2014) · cites this paper as Pickrell et al. 2010
Large eQTL studies have shown that genetic variation affects the expression of most genes.
“Large eQTL studies have shown that genetic variation affects the expression of most genes [125–128].”
From A survey of best practices for RNA-seq data analysis (2016) · cites this paper as [126]
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- Authors
- Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K.
- Affiliations
- University of Chicago (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Pickrell, Joseph K.
- Gilad, Yoav
- Pritchard, Jonathan K.
- ORCID
- Venue
- Nature
- Published
- 2010-03-10
- Volume
- 464
- Issue
- 7289
- Pages
- 768-772
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3089435
- OpenAlex
- W2027455260
- Cited by
- 1,256
- References
- 31
- Citations by year
- 2026: 15 · 2025: 24 · 2024: 44 · 2023: 32 · 2022: 42 · 2021: 63 · 2020: 67 · 2019: 56 · 2018: 79 · 2017: 86 · 2016: 99 · 2015: 111 · 2014: 152 · 2013: 137 · 2012: 117
- FWCI
- 68.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institute of Mental Health (R01MH084703, MH084703-01)
- National Institute of General Medical Sciences (GM077959, R01GM077959)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- gene expression variation, expression quantitative trait loci, allele-specific expression, alternative splicing, transcriptome, lymphoblastoid cell lines, HapMap, splice sites, transcriptional variation
- MeSH terms
- Alleles, Exons, Gene Expression Regulation, Humans, Nigeria, RNA, Messenger, Transcription, Genetic, Genetic Variation, Consensus Sequence, Sequence Analysis, RNA, DNA, Complementary, Polymorphism, Single Nucleotide, Gene Expression Profiling, RNA Splice Sites, Quantitative Trait Loci, Black People
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