RNA variant identification discrepancy among splice-aware alignment algorithms

Ji Hyung Hong, Yoon Ho Ko and Keunsoo Kang

PLOS ONE, 2018, vol. 13, issue 8, 1-10

Abstract: Next-generation sequencing (NGS) techniques have been generating various molecular maps, including transcriptomes via RNA-seq. Although the primary purpose of RNA-seq is to quantify the expression level of known genes, RNA variants are also identifiable. However, care must be taken to account for RNA’s dynamic nature. In this study, we evaluated the following popular splice-aware alignment algorithms in the context of RNA variant-calling analysis: HISAT2, STAR, STAR (two-pass mode), Subread, and Subjunc. For this, we performed RNA-seq with ten pieces of invasive ductal carcinoma from breast tissue and three pieces of adjacent normal tissue from a single patient. These RNA-seq data were used to evaluate the performance of splice-aware aligners. Surprisingly, the number of common potential RNA editing sites (pRESs) identified by all alignment algorithms was less than 2% of the total. The main cause of this difference was the mapped reads on the splice junctions. In addition, the RNA quality significantly affected the outcome. Therefore, researchers must consider these experimental and bioinformatic features during RNA variant analysis. Further investigations of common pRESs discovered that BDH1, CCDC137, and TBC1D10A transcripts contained a single non-synonymous RNA variant that was unique to breast cancer tissue compared to adjacent normal tissue; thus, further clinical validation is required.

Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0201822 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 01822&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0201822

DOI: 10.1371/journal.pone.0201822

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().