High-throughput quantification of cis-regulatory variants and modules using allele-specific expression across cellular environments

Jun Wang (primary)
Barts Cancer Institute
Queen Mary, University of London
Marc Mansour (secondary)
Cancer Institute
University College London

Abstract

Interpreting functional consequences of millions of non-coding genetic variants in humans is essential to understand the genetic basis of variation in complex traits and phenotypes, such as gene expression. Allele-specific expression (ASE) that integrates allelic frequency in transcription and genotyping information represents the most effective approach to quantify cis-regulatory variants. In this project, we will use publicly available and newly-generated RNA-seq data of human tissue to investigate how cells modify their cis-regulatory machinery to alter gene expression and adapt to different cellular environments (e.g. stress, hormones and metabolites). This will provide valuable insights in functional roles of non-coding genetic variants.


References

  1. Gimelbrant A, Hutchinson JN, Thompson BR, Chess A. Widespread monoallelic expression on human autosomes. Science. 2007 Nov 16;318(5853):1136-40.
  2. Castel SE, Levy-Moonshine A, Mohammadi P, Banks E, Lappalainen T. Tools and best practices for data processing in allelic expression analysis. Genome Biology. 2015 Sep 17;16:195.
  3. Gregory A Moyerbrailean, Allison L Richards, Daniel Kurtz, Cynthia A Kalita, Gordon O Davis, Chris T Harvey, Adnan Alazizi, Donovan Watza, Yoram Sorokin, Nancy Hauff, Xiang Zhou, Xiaoquan Wen, Roger Pique-Regi and Francesca Luca. High-throughput allele-specific expression across 250 environmental conditions. Genome Research. 2016 Dec; 26(12): 1627–1638.
  4. Harvey CT, Moyerbrailean GA, Davis GO, Wen X, Luca F, Pique-Regi R. QuASAR: quantitative allele-specific analysis of reads. Bioinformatics. 2015 Apr 15;31(8):1235-42.
  5. Mayba, O et al. MBASED: allele-specific expression detection in cancer tissues and cell lines. Genome Biology 2014. 15:405

BBSRC Area
Genes, development and STEM* approaches to biology
Area of Biology
Cell BiologyGenetics
Techniques & Approaches
BioinformaticsGeneticsMathematics / StatisticsMolecular BiologySimulation / Modelling