Application of annotation-agnostic RNA sequencing data analysis tools for biomarker discovery in liquid biopsy

Frontiers in Bioinformatics

Bioinformatics

Gabriel Wajnberg¹  Anirban Ghosh¹  Nicolas Crapoulet¹  Shruti Srivastava¹  Jeremy W. Roy²  Stephen M. Lewis³  Rodney J. Ouellette⁴  Eric P. Allain⁵  Pier Morin⁶  Daniel Saucier⁶  Alier Marrero⁷  Colleen O’Connell⁸ 

[1] Atlantic Cancer Research Institute, Moncton, NB, Canada;Atlantic Cancer Research Institute, Moncton, NB, Canada;Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada;Atlantic Cancer Research Institute, Moncton, NB, Canada;Department of Chemistry and Biochemistry, Université de Moncton, Moncton, NB, Canada;Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada;Atlantic Cancer Research Institute, Moncton, NB, Canada;Department of Chemistry and Biochemistry, Université de Moncton, Moncton, NB, Canada;Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada;Dr. Georges-L.-Dumont University Hospital Centre, Moncton, NB, Canada;Atlantic Cancer Research Institute, Moncton, NB, Canada;Department of Clinical Genetics, Vitalité Health Network, Dr. Georges-L.-Dumont University Hospital Centre, Moncton, NB, Canada;Department of Chemistry and Biochemistry, Université de Moncton, Moncton, NB, Canada;Beatrice Hunter Cancer Research Institute, Halifax, NS, Canada;Department of Chemistry and Biochemistry, Université de Moncton, Moncton, NB, Canada;Dr. Georges-L.-Dumont University Hospital Centre, Moncton, NB, Canada;Stan Cassidy Centre for Rehabilitation, Fredericton, NB, Canada;

关键词: small RNA;    extracellular vesicles;    annotation-agnostic;    quantification algorithms;    biomarkers;    liquid biopsy;    genetic diseases;   

DOI  :  10.3389/fbinf.2023.1127661

 received in 2022-12-19, accepted in 2023-04-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

RNA sequencing analysis is an important field in the study of extracellular vesicles (EVs), as these particles contain a variety of RNA species that may have diagnostic, prognostic and predictive value. Many of the bioinformatics tools currently used to analyze EV cargo rely on third-party annotations. Recently, analysis of unannotated expressed RNAs has become of interest, since these may provide complementary information to traditional annotated biomarkers or may help refine biological signatures used in machine learning by including unknown regions. Here we perform a comparative analysis of annotation-free and classical read-summarization tools for the analysis of RNA sequencing data generated for EVs isolated from persons with amyotrophic lateral sclerosis (ALS) and healthy donors. Differential expression analysis and digital-droplet PCR validation of unannotated RNAs also confirmed their existence and demonstrates the usefulness of including such potential biomarkers in transcriptome analysis. We show that find-then-annotate methods perform similarly to standard tools for the analysis of known features, and can also identify unannotated expressed RNAs, two of which were validated as overexpressed in ALS samples. We demonstrate that these tools can therefore be used for a stand-alone analysis or easily integrated into current workflows and may be useful for re-analysis as annotations can be integrated post hoc.

【 授权许可】

Unknown   
Copyright © 2023 Wajnberg, Allain, Roy, Srivastava, Saucier, Morin, Marrero, O’Connell, Ghosh, Lewis, Ouellette and Crapoulet.