AlleleSeq: analysis of allele‐specific expression and binding in a network framework

Molecular Systems Biology

Joel Rozowsky³  Alexej Abyzov³  Jing Wang⁴  Pedro Alves⁴  Debasish Raha²  Arif Harmanci³  Jing Leng⁴  Robert Bjornson¹  Yong Kong⁶  Naoki Kitabayashi⁵  Nitin Bhardwaj³  Mark Rubin⁵  Michael Snyder⁷ 

[1] Department of Computer Science, Yale University, New Haven, CT, USA;Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, USA;Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA;Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA;Department of Pathology and Laboratory Medicine, Weill Cornell Medical Center, New York, NY, USA;Keck Biotechnology Resource Laboratory, Yale University, New Haven, CT, USA;Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

关键词: allele‐specific;    ChIP‐Seq;    networks;    RNA‐Seq;   

DOI  :  10.1038/msb.2011.54

来源: Wiley

【 摘 要 】

Abstract

To study allele-specific expression (ASE) and binding (ASB), that is, differences between the maternally and paternally derived alleles, we have developed a computational pipeline (AlleleSeq). Our pipeline initially constructs a diploid personal genome sequence (and corresponding personalized gene annotation) using genomic sequence variants (SNPs, indels, and structural variants), and then identifies allele-specific events with significant differences in the number of mapped reads between maternal and paternal alleles. There are many technical challenges in the construction and alignment of reads to a personal diploid genome sequence that we address, for example, bias of reads mapping to the reference allele. We have applied AlleleSeq to variation data for NA12878 from the 1000 Genomes Project as well as matched, deeply sequenced RNA-Seq and ChIP-Seq data sets generated for this purpose. In addition to observing fairly widespread allele-specific behavior within individual functional genomic data sets (including results consistent with X-chromosome inactivation), we can study the interaction between ASE and ASB. Furthermore, we investigate the coordination between ASE and ASB from multiple transcription factors events using a regulatory network framework. Correlation analyses and network motifs show mostly coordinated ASB and ASE.

【 授权许可】

CC BY-NC-SA   
Copyright © 2011 EMBO and Macmillan Publishers Limited

Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation without specific permission.