Fast and sensitive validation of fusion transcripts in whole-genome sequencing data
Hafstað, Völundur LU ; Häkkinen, Jari LU
and Persson, Helena
LU
(2023)
In BMC Bioinformatics
24(1).
- Abstract
BACKGROUND: In cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications.
RESULTS: We describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing... (More)
BACKGROUND: In cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications.
RESULTS: We describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing (WGS) data. Our pipeline uses discordant read pairs to identify supported fusion events and analyzes soft-clipped read alignments to determine genomic breakpoints. We have tested it on matched RNA-Seq and WGS data for both tumors and cancer cell lines and show that it can be used to validate both new predicted gene fusions and experimentally validated fusion events. It was considerably faster and more sensitive than using BreakDancer and Manta, software that is instead designed to detect many different types of structural variants on a genome-wide scale.
CONCLUSIONS: We have developed a fast and very sensitive pipeline for validation of gene fusions detected by RNA-Seq in matched WGS data. It can be used to identify high-quality gene fusions for further bioinformatic and experimental studies, including validation of genomic breakpoints and studies of the mechanisms that generate fusions. In a clinical setting, it could help find expressed gene fusions for personalized therapy.
(Less)
- author
- Hafstað, Völundur
LU
; Häkkinen, Jari
LU
and Persson, Helena
LU
- organization
- publishing date
- 2023-09-23
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Whole Genome Sequencing, Genomics, Cell Line, Computational Biology, Drug Delivery Systems
- in
- BMC Bioinformatics
- volume
- 24
- issue
- 1
- article number
- 359
- publisher
- BioMed Central (BMC)
- external identifiers
-
- scopus:85172331802
- pmid:37741966
- ISSN
- 1471-2105
- DOI
- 10.1186/s12859-023-05489-5
- language
- English
- LU publication?
- yes
- id
- 5d8b8688-2561-498b-a431-f453012916b6
- date added to LUP
- 2023-09-27 10:52:20
- date last changed
- 2024-04-13 16:09:30
@article{5d8b8688-2561-498b-a431-f453012916b6,
abstract = {{<p>BACKGROUND: In cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications.</p><p>RESULTS: We describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing (WGS) data. Our pipeline uses discordant read pairs to identify supported fusion events and analyzes soft-clipped read alignments to determine genomic breakpoints. We have tested it on matched RNA-Seq and WGS data for both tumors and cancer cell lines and show that it can be used to validate both new predicted gene fusions and experimentally validated fusion events. It was considerably faster and more sensitive than using BreakDancer and Manta, software that is instead designed to detect many different types of structural variants on a genome-wide scale.</p><p>CONCLUSIONS: We have developed a fast and very sensitive pipeline for validation of gene fusions detected by RNA-Seq in matched WGS data. It can be used to identify high-quality gene fusions for further bioinformatic and experimental studies, including validation of genomic breakpoints and studies of the mechanisms that generate fusions. In a clinical setting, it could help find expressed gene fusions for personalized therapy.</p>}},
author = {{Hafstað, Völundur and Häkkinen, Jari and Persson, Helena}},
issn = {{1471-2105}},
keywords = {{Whole Genome Sequencing; Genomics; Cell Line; Computational Biology; Drug Delivery Systems}},
language = {{eng}},
month = {{09}},
number = {{1}},
publisher = {{BioMed Central (BMC)}},
series = {{BMC Bioinformatics}},
title = {{Fast and sensitive validation of fusion transcripts in whole-genome sequencing data}},
url = {{http://dx.doi.org/10.1186/s12859-023-05489-5}},
doi = {{10.1186/s12859-023-05489-5}},
volume = {{24}},
year = {{2023}},
}