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PMID: 20598109 Published · ppublish English Comparative Study Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Screening the human exome: a comparison of whole genome and whole transcriptome sequencing.

Genome biology ·Vol. 11 ·No. 5 ·2010-00-00 ·Pages R57

Cirulli ET, Singh A, Shianna KV, Ge D, Smith JP, Maia JM, Heinzen EL, Goedert JJ, Goldstein DB, Center for HIV/AIDS Vaccine Immunology CHAVI

Abstract

There is considerable interest in the development of methods to efficiently identify all coding variants present in large sample sets of humans. There are three approaches possible: whole-genome sequencing, whole-exome sequencing using exon capture methods, and RNA-Seq. While whole-genome sequencing is the most complete, it remains sufficiently expensive that cost effective alternatives are important. Here we provide a systematic exploration of how well RNA-Seq can identify human coding variants by comparing variants identified through high coverage whole-genome sequencing to those identified by high coverage RNA-Seq in the same individual. This comparison allowed us to directly evaluate the sensitivity and specificity of RNA-Seq in identifying coding variants, and to evaluate how key parameters such as the degree of coverage and the expression levels of genes interact to influence performance. We find that although only 40% of exonic variants identified by whole genome sequencing were captured using RNA-Seq; this number rose to 81% when concentrating on genes known to be well-expressed in the source tissue. We also find that a high false positive rate can be problematic when working with RNA-Seq data, especially at higher levels of coverage. We conclude that as long as a tissue relevant to the trait under study is available and suitable quality control screens are implemented, RNA-Seq is a fast and inexpensive alternative approach for finding coding variants in genes with sufficiently high expression levels.

MeSH Terms
Base Sequence Databases, Genetic Exons/genetics Gene Expression Profiling Gene Expression Regulation Genome, Human/genetics Humans Leukocytes, Mononuclear/metabolism Polymorphism, Single Nucleotide/genetics Sequence Alignment Sequence Analysis, DNA/methods Sequence Homology, Nucleic Acid
Authors & Affiliations
10 authors, click to expand affiliations / ORCID
Cirulli Elizabeth T
Center for Human Genome Variation, Duke University School of Medicine, Box 91009, Durham, NC 27708, USA. [email protected]
Singh Abanish
Shianna Kevin V
Ge Dongliang
Smith Jason P
Maia Jessica M
Heinzen Erin L
Goedert James J
Goldstein David B
Center for HIV/AIDS Vaccine Immunology (CHAVI)
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Article Info
Journal
Genome biology
Abbr.
Genome Biol
ISSN
1474-760X
Published
2010-00-00
Epub
2010-00-28
Pages
R57
Language
English
Region
England
NLM ID
100960660
PMCID
PMC2898068
Subset
IM
Grants
NIAID NIH HHS · AI067854 · United States
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