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


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.

SUBMITTER: Boivin V 

PROVIDER: S-EPMC7049693 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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

Boivin Vincent V   Reulet Gaspard G   Boisvert Olivier O   Couture Sonia S   Elela Sherif Abou SA   Scott Michelle S MS  

Nucleic acids research 20200301 5


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.  ...[more]

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