The human transcriptome across tissues and individuals

Marta Melé(Centre for Genomic Regulation), Pedro G. Ferreira(University of Geneva), Ferrán Reverter(Universitat Pompeu Fabra), David S. DeLuca(Broad Institute), Jean Monlong(Universitat Pompeu Fabra), Michael Sammeth(Universitat Pompeu Fabra), Taylor Young(Broad Institute), Jakob M. Goldmann(Radboud University Nijmegen), Dmitri D. Pervouchine(Universitat Pompeu Fabra), Timothy J. Sullivan(Broad Institute), Rory Johnson(Universitat Pompeu Fabra), Ayellet V. Segrè(Broad Institute), Sarah Djebali(Universitat Pompeu Fabra), Anastasia Niarchou(University of Geneva), Fred A. Wright(North Carolina State University), Tuuli Lappalainen(University of Geneva), Miquel Calvo(University of Geneva), Gad Getz(Broad Institute), Emmanouil T. Dermitzakis(Broad Institute), Kristin Ardlie(Broad Institute), Roderic Guigó(Broad Institute)
Science
May 7, 2015
Cited by 1,422Open Access
Full Text

Abstract

Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes—which is most clearly seen in blood—though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.


Related Papers

No related papers found

Powered by citation graph analysis