Abstract
The systematic identification of regulatory elements that control gene expression remains a challenge. Genetic screens that use untargeted mutagenesis have the potential to identify protein-coding genes, non-coding RNAs and regulatory elements, but their analysis has mainly focused on identifying the former two. To identify regulatory elements, we conducted a new bioinformatics analysis of insertional mutagenesis screens interrogating WNT signaling in haploid human cells. We searched for specific patterns of retroviral gene trap integrations (used as mutagens in haploid screens) in short genomic intervals overlapping with introns and regions upstream of genes. We uncovered atypical patterns of gene trap insertions that were not predicted to disrupt coding sequences, but caused changes in the expression of two key regulators of WNT signaling, suggesting the presence of cis-regulatory elements. Our methodology extends the scope of haploid genetic screens by enabling the identification of regulatory elements that control gene expression.
Highlights
An outstanding challenge in genomics is the identification of functional regulatory elements that control spatial and temporal expression of protein-coding genes and non-coding RNAs
Haploid genetic screens rely on the phenotypic selection of a population of cells mutagenized by integration of a gene trap (GT)-bearing retrovirus
To distinguish features identified in these two new analyses from the more typical disruption of protein-coding genes or non-coding RNAs by GT insertions, we looked for enrichment of gene-inactivating insertions, as defined above; we refer to this analysis as “inactivating insertion enrichment analysis.”
Summary
Discovery of gene regulatory elements from haploid genetic screen data grant R00 CA168987-03, a National Institute of General Medical Sciences Gov) grant R01 GM116847, a Joint Initiative for Metrology in Biology (http://jimb.stanford.edu) seed grant, a National Science Foundation (https:// www.nsf.gov) CAREER Award, a McCormickGabilan Fellowship and a Baxter Family Fellowship (all to JS), by National Institutes of Health (https:// www.nih.gov) grants DP2 AI104557 (JEC), DP2 GM105448 (RR), R35 GM118082 (RR) and by startup funds from the Stanford Cancer Institute (RR). Sloan Foundation (https:// sloan.org) fellow in Computational & Evolutionary Molecular Biology, and RR is a Josephine Q. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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