Integrated Analysis of Genomic and Transcriptomic Data for the Discovery of Splice-associated Variants in Cancer

Overview

Journal Nat Commun

Specialty Biology

Date 2023 Mar 23

PMID 36949070

Authors

Kelsy C Cotto

Yang-Yang Feng

Avinash Ramu

Megan Richters

Sharon L Freshour

Zachary L Skidmore

Huiming Xia

Joshua F McMichael

Jason Kunisaki

Katie M Campbell

Timothy Hung-Po Chen

Emily B Rozycki

Douglas Adkins

Siddhartha Devarakonda

Sumithra Sankararaman

Yiing Lin

William C Chapman

Christopher A Maher

Vivek Arora

Gavin P Dunn

Ravindra Uppaluri

Ramaswamy Govindan

Obi L Griffith

Malachi Griffith

Affiliations

Soon will be listed here.

Abstract

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

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