Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA
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ABSTRACT:
PROVIDER: PRJNA523366 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12851454_1.fastq.gz | Fastqsanger.gz | |||
| SRR12851454_2.fastq.gz | Fastqsanger.gz | |||
| SRR8595560_1.fastq.gz | Fastqsanger.gz | |||
| SRR8595560_2.fastq.gz | Fastqsanger.gz | |||
| SRR8595561_1.fastq.gz | Fastqsanger.gz |
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Project description: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 115 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 tRNA and snoRNA 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 distort the perceived architecture of the human transcriptome.
2019-02-21 | GSE126797 | GEO
Project description: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.
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Project description:The ligation step in RNA sequencing library generation is a known source of bias. We present the first comparison of the standard duplex adaptor protocol supplied by Life Technologies for use on the Ion Torrent PGM with an alternate single adaptor approach involving CircLigase (CircLig). We also investigate whether using the thermostable ligase Methanobacterium thermoautotrophicum RNA ligase K97A (Mth K97A) for the initial ligation step in the CircLigase protocol reduces bias. A pool of small RNA fragments of known composition was converted into a sequencing library using one of three protocols and sequenced on an Ion Torrent PGM. The single adaptor CircLigase-based approach significantly reduces, but does not eliminate, bias in Ion Torrent data. Using Mth K97A as part of the CircLig method does not further reduce bias.
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Project description:BackgroundNext-generation sequencing does not yield fully unbiased estimates for read abundance, which may impact on the conclusions that can be drawn from sequencing data. The ligation step in RNA sequencing library generation is a known source of bias, motivating developments in enzyme technology and library construction protocols. We present the first comparison of the standard duplex adaptor protocol supplied by Life Technologies for use on the Ion Torrent PGM with an alternate single adaptor approach involving CircLigase (CircLig protocol).A correlation between over-representation in sequenced libraries and degree of secondary structure has been reported previously, therefore we also investigated whether bias could be reduced by ligation with an enzyme that functions at a temperature not permissive for such structure.ResultsA pool of small RNA fragments of known composition was converted into a sequencing library using one of three protocols and sequenced on an Ion Torrent PGM. The CircLig protocol resulted in less over-representation of specific sequences than the standard protocol. Over-represented sequences are more likely to be predicted to have secondary structure and to co-fold with adaptor sequences. However, use of the thermostable ligase Methanobacterium thermoautotrophicum RNA ligase K97A (Mth K97A) was not sufficient to reduce bias.ConclusionsThe single adaptor CircLigase-based approach significantly reduces, but does not eliminate, bias in Ion Torrent data. Ligases that function at temperatures to remove the possible influence of secondary structure on library generation may be of value, although Mth K97A is not effective in this case.
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