Article abstract


Nature Methods 6, 613 - 618 (2009)
Published online: 20 July 2009 | doi:10.1038/nmeth.1357

Digital RNA allelotyping reveals tissue-specific and allele-specific gene expression in human

Kun Zhang1,7, Jin Billy Li2,7, Yuan Gao3,4,7, Dieter Egli5, Bin Xie3, Jie Deng1, Zhe Li1, Je-Hyuk Lee2, John Aach2, Emily M Leproust6, Kevin Eggan5 & George M Church2


We developed a digital RNA allelotyping method for quantitatively interrogating allele-specific gene expression. This method involves ultra-deep sequencing of padlock-captured single-nucleotide polymorphisms (SNPs) from the transcriptome. We characterized four cell lines established from two human subjects in the Personal Genome Project. Approximately 11–22% of the heterozygous mRNA-associated SNPs showed allele-specific expression in each cell line and 4.3–8.5% were tissue-specific, suggesting the presence of tissue-specific cis regulation. When we applied allelotyping to two pairs of sibling human embryonic stem cell lines, the sibling lines were more similar in allele-specific expression than were the genetically unrelated lines. We found that the variation of allelic ratios in gene expression among different cell lines was primarily explained by genetic variations, much more so than by specific tissue types or growth conditions. Comparison of expressed SNPs on the sense and antisense transcripts suggested that allelic ratios are primarily determined by cis-regulatory mechanisms on the sense transcripts.

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  1. Department of Bioengineering, University of California at San Diego, La Jolla, California, USA.
  2. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.
  3. Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA.
  4. Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, USA.
  5. The Stowers Medical Institute, Harvard Stem Cell Institute and Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA.
  6. Genomics Solution Unit, Agilent Technologies Inc., Santa Clara, California, USA.
  7. These authors contributed equally to this work.

Correspondence to: Kun Zhang1,7 e-mail: kzhang@bioeng.ucsd.edu

Correspondence to: George M Church2 e-mail: gmc@harvard.edu