Transcriptome genetics using second generation sequencing in a Caucasian population
Open accessAbstract
Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.
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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 [125]
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- Authors
- Montgomery, S. B., Sammeth, M., Gutierrez-Arcelus, M., Lach, R. P., Ingle, C., Nisbett, J., Guigo, R., & Dermitzakis, E. T.
- Affiliations
- University of Geneva (CH)
- Wellcome Sanger Institute (GB)
- Corresponding author
- Montgomery, Stephen B.
- Dermitzakis, Emmanouil T.
- Venue
- Nature
- Published
- 2010-03-10
- Volume
- 464
- Issue
- 7289
- Pages
- 773-777
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3836232
- OpenAlex
- W2065776802
- Cited by
- 797
- References
- 35
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 10 · 2023: 14 · 2022: 17 · 2021: 22 · 2020: 23 · 2019: 48 · 2018: 30 · 2017: 40 · 2016: 85 · 2015: 92 · 2014: 105 · 2013: 107 · 2012: 89
- FWCI
- 54.20
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion)
- Funders
- Wellcome Trust (077046)
- 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, alternative splicing, allele-specific expression, mRNA sequencing, HapMap, lymphoblastoid cell lines, transcript structure, Caucasian population
- MeSH terms
- Alleles, Exons, Haplotypes, Homozygote, Humans, RNA, Messenger, Alternative Splicing, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Gene Expression Profiling, Quantitative Trait Loci, White People
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