Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking

Vitalik Bezuglov
ORCID logo ,
Alexey Stupnikov
ORCID logo ,
Ivan Skakov
,
Victoria Shtratnikova
ORCID logo ,
Jonathan Richard Pilsner
,
Alexander Suvorov
,
Oleg Sergeyev
* ORCID logo
Version 1 : Received: 7 December 2022 / Approved: 9 December 2022 / Online: 9 December 2022 (10:07:27 CET)
Version 2 : Received: 9 February 2023 / Approved: 10 February 2023 / Online: 10 February 2023 (11:26:06 CET)

A peer-reviewed article of this Preprint also exists.

Bezuglov, V.; Stupnikov, A.; Skakov, I.; Shtratnikova, V.; Pilsner, J.R.; Suvorov, A.; Sergeyev, O. Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking. Int. J. Mol. Sci. 2023, 24, 4195. Bezuglov, V.; Stupnikov, A.; Skakov, I.; Shtratnikova, V.; Pilsner, J.R.; Suvorov, A.; Sergeyev, O. Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking. Int. J. Mol. Sci. 2023, 24, 4195.

Abstract

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = \(Read\ length - 40\% Adapter\ length\); (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

Keywords

sRNA analysis; small RNA; microRNA; piRNA; tRNA-derived small RNA; RNA-seq; small RNA fragments; benchmarking; differential expression analysis

Subject

Biology and Life Sciences, Biochemistry and Molecular Biology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Comments (1)

Comment 1
Received: 10 February 2023
Commenter: Oleg Sergeyev
Commenter's Conflict of Interests: Author
Comment: Per Revewers' suggestions, we have revised the Introduction, Methods, Results, Discussion and Conclusion sections. Additionally, we once again carefully checked the manuscript with the help of a co-author who is a native English speaker and verified that citations are used appropriately.
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