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Revealing stable processing products from ribosome-associated small RNAs by deep-sequencing data analysis.

Zywicki M, Bakowska-Zywicka K, Polacek N - Nucleic Acids Res. (2012)

Bottom Line: Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases.Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data.To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae.

View Article: PubMed Central - PubMed

Affiliation: Innsbruck Biocenter, Medical University Innsbruck, Division of Genomics and RNomics, Fritz-Pregl-Strasse 3, 6020 Innsbruck, Austria. marek.zywicki@i-med.ac.at

ABSTRACT
The exploration of the non-protein-coding RNA (ncRNA) transcriptome is currently focused on profiling of microRNA expression and detection of novel ncRNA transcription units. However, recent studies suggest that RNA processing can be a multi-layer process leading to the generation of ncRNAs of diverse functions from a single primary transcript. Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases. Thus the correct assessment of widespread RNA processing events is one of the major obstacles in transcriptome research. Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data. The major features include efficient handling of non-unique reads, detection of novel stable ncRNA transcripts and processing products and annotation of known transcripts based on multiple sources of information. To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae. By employing the APART pipeline, we were able to detect and confirm by independent experimental methods multiple novel stable RNA molecules differentially processed from well known ncRNAs, like rRNAs, tRNAs or snoRNAs, in a stress-dependent manner.

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Schematic representation of the key steps of the experimental workflow leading to identification of RNA processing products. (A) Experimental preparation of the cDNA library. In order to select for functional RNAs, yeast ribosomes have been used here as bait. The next important step is the size selection of ribosome-associated RNAs and the subsequent attachment of 5′- and 3′-adaptors which are marking the natural ends of the RNAs. After deep-sequencing of the library, adaptor sequences are used to select for the reads covering the full length of the original RNA molecule (both adaptors are observed). (B) Computational analysis of the data with the APART pipeline. First, reads are aligned to the reference genome and contigs together with respective coverage plots are created. Next, contigs derived from the same read sets are clustered and only non-representative contigs (marked by lighter colors) are removed from the main results list. Processing products are predicted by scanning of the coverage plots and their abundance is estimated by subtraction of the background coverage from the maximal coverage within the predicted product (abundance correspond to the area of coverage plot marked with color).
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gks020-F1: Schematic representation of the key steps of the experimental workflow leading to identification of RNA processing products. (A) Experimental preparation of the cDNA library. In order to select for functional RNAs, yeast ribosomes have been used here as bait. The next important step is the size selection of ribosome-associated RNAs and the subsequent attachment of 5′- and 3′-adaptors which are marking the natural ends of the RNAs. After deep-sequencing of the library, adaptor sequences are used to select for the reads covering the full length of the original RNA molecule (both adaptors are observed). (B) Computational analysis of the data with the APART pipeline. First, reads are aligned to the reference genome and contigs together with respective coverage plots are created. Next, contigs derived from the same read sets are clustered and only non-representative contigs (marked by lighter colors) are removed from the main results list. Processing products are predicted by scanning of the coverage plots and their abundance is estimated by subtraction of the background coverage from the maximal coverage within the predicted product (abundance correspond to the area of coverage plot marked with color).

Mentions: The major assumption behind the construction of a cDNA library aiming at identifying stable ncRNA species is that merely functional RNAs are expected to be protected from degradation. In order to enrich for functional ncRNAs, it has previously been shown that construction of libraries from ribonucleoprotein (RNP) particles rather than from purified total RNA is beneficial (7). Following the same logic, we have generated a cDNA library enriched for small RNAs (sized 20–500 nt) that co-purified with S. cerevisiae ribosomes under 12 different growth conditions. The rationale for choosing yeast was the lack of the miRNA pathway, since miRNAs are very abundant in other organisms and often mask other small RNAs in transcriptomic data (4). The employed procedure did not include a random RNA fragmentation step, resulting in cDNAs with ends correspond to the natural ends of the RNA species. Moreover, we have used amplification adaptors attached to both the 5′- and 3′-ends of the cDNA (see ‘Materials and Methods’ section for details) in order to validate if sequencing spans the full length of the cDNAs (Figure 1). Before addition of the 5′-adaptor, we have treated the RNAs with tobacco acid pyrophosphatase in order to enable the adaptor ligation to both, processed and primary transcripts. However, by omitting this step, it would be possible to select exclusively for processed RNAs, as it is commonly used for micro RNA identification (35).Figure 1.


Revealing stable processing products from ribosome-associated small RNAs by deep-sequencing data analysis.

Zywicki M, Bakowska-Zywicka K, Polacek N - Nucleic Acids Res. (2012)

Schematic representation of the key steps of the experimental workflow leading to identification of RNA processing products. (A) Experimental preparation of the cDNA library. In order to select for functional RNAs, yeast ribosomes have been used here as bait. The next important step is the size selection of ribosome-associated RNAs and the subsequent attachment of 5′- and 3′-adaptors which are marking the natural ends of the RNAs. After deep-sequencing of the library, adaptor sequences are used to select for the reads covering the full length of the original RNA molecule (both adaptors are observed). (B) Computational analysis of the data with the APART pipeline. First, reads are aligned to the reference genome and contigs together with respective coverage plots are created. Next, contigs derived from the same read sets are clustered and only non-representative contigs (marked by lighter colors) are removed from the main results list. Processing products are predicted by scanning of the coverage plots and their abundance is estimated by subtraction of the background coverage from the maximal coverage within the predicted product (abundance correspond to the area of coverage plot marked with color).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3351166&req=5

gks020-F1: Schematic representation of the key steps of the experimental workflow leading to identification of RNA processing products. (A) Experimental preparation of the cDNA library. In order to select for functional RNAs, yeast ribosomes have been used here as bait. The next important step is the size selection of ribosome-associated RNAs and the subsequent attachment of 5′- and 3′-adaptors which are marking the natural ends of the RNAs. After deep-sequencing of the library, adaptor sequences are used to select for the reads covering the full length of the original RNA molecule (both adaptors are observed). (B) Computational analysis of the data with the APART pipeline. First, reads are aligned to the reference genome and contigs together with respective coverage plots are created. Next, contigs derived from the same read sets are clustered and only non-representative contigs (marked by lighter colors) are removed from the main results list. Processing products are predicted by scanning of the coverage plots and their abundance is estimated by subtraction of the background coverage from the maximal coverage within the predicted product (abundance correspond to the area of coverage plot marked with color).
Mentions: The major assumption behind the construction of a cDNA library aiming at identifying stable ncRNA species is that merely functional RNAs are expected to be protected from degradation. In order to enrich for functional ncRNAs, it has previously been shown that construction of libraries from ribonucleoprotein (RNP) particles rather than from purified total RNA is beneficial (7). Following the same logic, we have generated a cDNA library enriched for small RNAs (sized 20–500 nt) that co-purified with S. cerevisiae ribosomes under 12 different growth conditions. The rationale for choosing yeast was the lack of the miRNA pathway, since miRNAs are very abundant in other organisms and often mask other small RNAs in transcriptomic data (4). The employed procedure did not include a random RNA fragmentation step, resulting in cDNAs with ends correspond to the natural ends of the RNA species. Moreover, we have used amplification adaptors attached to both the 5′- and 3′-ends of the cDNA (see ‘Materials and Methods’ section for details) in order to validate if sequencing spans the full length of the cDNAs (Figure 1). Before addition of the 5′-adaptor, we have treated the RNAs with tobacco acid pyrophosphatase in order to enable the adaptor ligation to both, processed and primary transcripts. However, by omitting this step, it would be possible to select exclusively for processed RNAs, as it is commonly used for micro RNA identification (35).Figure 1.

Bottom Line: Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases.Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data.To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae.

View Article: PubMed Central - PubMed

Affiliation: Innsbruck Biocenter, Medical University Innsbruck, Division of Genomics and RNomics, Fritz-Pregl-Strasse 3, 6020 Innsbruck, Austria. marek.zywicki@i-med.ac.at

ABSTRACT
The exploration of the non-protein-coding RNA (ncRNA) transcriptome is currently focused on profiling of microRNA expression and detection of novel ncRNA transcription units. However, recent studies suggest that RNA processing can be a multi-layer process leading to the generation of ncRNAs of diverse functions from a single primary transcript. Up to date no methodology has been presented to distinguish stable functional RNA species from rapidly degraded side products of nucleases. Thus the correct assessment of widespread RNA processing events is one of the major obstacles in transcriptome research. Here, we present a novel automated computational pipeline, named APART, providing a complete workflow for the reliable detection of RNA processing products from next-generation-sequencing data. The major features include efficient handling of non-unique reads, detection of novel stable ncRNA transcripts and processing products and annotation of known transcripts based on multiple sources of information. To disclose the potential of APART, we have analyzed a cDNA library derived from small ribosome-associated RNAs in Saccharomyces cerevisiae. By employing the APART pipeline, we were able to detect and confirm by independent experimental methods multiple novel stable RNA molecules differentially processed from well known ncRNAs, like rRNAs, tRNAs or snoRNAs, in a stress-dependent manner.

Show MeSH
Related in: MedlinePlus