Literature DB >> 31980822

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA.

Vincent Boivin1, Gaspard Reulet1, Olivier Boisvert1, Sonia Couture1, Sherif Abou Elela2, Michelle S Scott1.   

Abstract

The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2020        PMID: 31980822     DOI: 10.1093/nar/gkaa028

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  14 in total

1.  TGIRT-seq Protocol for the Comprehensive Profiling of Coding and Non-coding RNA Biotypes in Cellular, Extracellular Vesicle, and Plasma RNAs.

Authors:  Hengyi Xu; Ryan M Nottingham; Alan M Lambowitz
Journal:  Bio Protoc       Date:  2021-12-05

2.  Size-Exclusion Chromatography Separation Reveals That Vesicular and Non-Vesicular Small RNA Profiles Differ in Cell Free Urine.

Authors:  Jenni Karttunen; Sarah E Stewart; Lajos Kalmar; Andrew J Grant; Fiona E Karet Frankl; Tim L Williams
Journal:  Int J Mol Sci       Date:  2021-05-05       Impact factor: 5.923

3.  Identification of protein-protected mRNA fragments and structured excised intron RNAs in human plasma by TGIRT-seq peak calling.

Authors:  Jun Yao; Douglas C Wu; Ryan M Nottingham; Alan M Lambowitz
Journal:  Elife       Date:  2020-09-02       Impact factor: 8.140

4.  Annotation of snoRNA abundance across human tissues reveals complex snoRNA-host gene relationships.

Authors:  Étienne Fafard-Couture; Danny Bergeron; Sonia Couture; Sherif Abou-Elela; Michelle S Scott
Journal:  Genome Biol       Date:  2021-06-04       Impact factor: 13.583

5.  Twelve quick steps for genome assembly and annotation in the classroom.

Authors:  Hyungtaek Jung; Tomer Ventura; J Sook Chung; Woo-Jin Kim; Bo-Hye Nam; Hee Jeong Kong; Young-Ok Kim; Min-Seung Jeon; Seong-Il Eyun
Journal:  PLoS Comput Biol       Date:  2020-11-12       Impact factor: 4.475

Review 6.  Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology.

Authors:  Ianthe A E M van Belzen; Alexander Schönhuth; Patrick Kemmeren; Jayne Y Hehir-Kwa
Journal:  NPJ Precis Oncol       Date:  2021-03-02

Review 7.  Small nucleolar RNAs: continuing identification of novel members and increasing diversity of their molecular mechanisms of action.

Authors:  Danny Bergeron; Étienne Fafard-Couture; Michelle S Scott
Journal:  Biochem Soc Trans       Date:  2020-04-29       Impact factor: 5.407

Review 8.  Beyond Back Splicing, a Still Poorly Explored World: Non-Canonical Circular RNAs.

Authors:  Annie Robic; Christa Kühn
Journal:  Genes (Basel)       Date:  2020-09-22       Impact factor: 4.096

9.  In-Depth Analysis Reveals Production of Circular RNAs from Non-Coding Sequences.

Authors:  Annie Robic; Julie Demars; Christa Kühn
Journal:  Cells       Date:  2020-07-30       Impact factor: 6.600

Review 10.  Emerging Classes of Small Non-Coding RNAs With Potential Implications in Diabetes and Associated Metabolic Disorders.

Authors:  Cécile Jacovetti; Mustafa Bilal Bayazit; Romano Regazzi
Journal:  Front Endocrinol (Lausanne)       Date:  2021-05-10       Impact factor: 5.555

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