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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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Related in: MedlinePlus

Experimental validation of the APART-predicted putative processing products. (A) Processing of the tRNA-His(GUG). On the left, UCSC Genome Browser visualization of the APART tracks (green) showing two possible processing products (processing sites marked with arrows). On the right, results of the northern blot experiment using total RNA isolated from S. cerevisiae grown in different environmental conditions (lanes: 1-UV radiation, 2-anaerobic, 3-optimal, 4-high pH, 5-low pH, 6-amino acid starvation, 7-sugar starvation) with probes against 5′- and 3′-halves of the tRNA-His. Full length tRNA is marked with open arrows, processing products are indicated by filled arrows. Differential stability of both parts can be observed. (B) Processing of the tRNA-Ser(AGA) (labeling as above). The inexact ends of the contig displayed on UCSC Genome Browser visualization suggest decreased stability of the 3′-derived processing product, comparing to tRNA-His, which is reflected by the northern blot results (right). (C) Cytoplasmic localization and processing of snoRNAs. On the left, northern blot presenting subcellular localization of snoRNA 128 (identified in this study) and snoRNA13 (not found in our cDNA library). The localization of the small nuclear RNAs sn7, sn14 and sn6 in the particular cellular fractions is also shown. For the northern analysis, total RNAs prepared either from the nuclear fraction, the cytoplasmic fraction, or from the mono- or polysomal fraction were blotted. The observed northern blot signals in the polysomal samples suggest that snoRNAs are associated with translating ribosomes in yeast. On the right, identification of the processing products derived from snoRNA 128 by northern blot using total RNA isolated from yeast grown under different environmental conditions. In all panels 5S rRNA served as internal loading control.
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gks020-F5: Experimental validation of the APART-predicted putative processing products. (A) Processing of the tRNA-His(GUG). On the left, UCSC Genome Browser visualization of the APART tracks (green) showing two possible processing products (processing sites marked with arrows). On the right, results of the northern blot experiment using total RNA isolated from S. cerevisiae grown in different environmental conditions (lanes: 1-UV radiation, 2-anaerobic, 3-optimal, 4-high pH, 5-low pH, 6-amino acid starvation, 7-sugar starvation) with probes against 5′- and 3′-halves of the tRNA-His. Full length tRNA is marked with open arrows, processing products are indicated by filled arrows. Differential stability of both parts can be observed. (B) Processing of the tRNA-Ser(AGA) (labeling as above). The inexact ends of the contig displayed on UCSC Genome Browser visualization suggest decreased stability of the 3′-derived processing product, comparing to tRNA-His, which is reflected by the northern blot results (right). (C) Cytoplasmic localization and processing of snoRNAs. On the left, northern blot presenting subcellular localization of snoRNA 128 (identified in this study) and snoRNA13 (not found in our cDNA library). The localization of the small nuclear RNAs sn7, sn14 and sn6 in the particular cellular fractions is also shown. For the northern analysis, total RNAs prepared either from the nuclear fraction, the cytoplasmic fraction, or from the mono- or polysomal fraction were blotted. The observed northern blot signals in the polysomal samples suggest that snoRNAs are associated with translating ribosomes in yeast. On the right, identification of the processing products derived from snoRNA 128 by northern blot using total RNA isolated from yeast grown under different environmental conditions. In all panels 5S rRNA served as internal loading control.

Mentions: The ample processing of RNA transcripts let us also reconsidering the use of read counts for the estimation of RNA abundance. RNA transcripts, especially ncRNAs, are frequently post-transcriptionally processed, thus the use of read counts in next-generation-sequencing projects for the estimation of the RNA abundance is problematic. Read count works well as a starting point for analyses focused on expression profiling of known genes. In this case, after proper normalization [for review see (38)], such number correspond to the number of the observed transcripts of a particular gene. However characteristics of cDNA libraries aimed for the identification of RNA processing products differ from those used for either mRNA or miRNA profiling. The main divergence is that the library preparation procedure does not involve a random fragmentation step (unlike mRNA profiling projects do) and no strict length separation is performed (unlike in the miRNA profiling approaches) resulting in a collection of transcript of various lengths. Thus, the same read count can be obtained for long contigs with random read distribution and for a short one with clear processing pattern. In this case, the analysis of the read distribution among the contig is crucial. Assuming that two non-overlapping reads mapped within a single contig can be derived from a single primary transcript by a processing event, the ultimate measure for RNA level will be the maximum coverage observed within the transcript. This measure corresponds to the number of overlapping reads observed for the assembled contig and reflects the minimal number of separate transcript copies in the cell. The use of the maximal coverage value is even more important when differential processing patterns of similar RNAs are taken into consideration, like in the case of tRNA-His and tRNA-Ser (Figure 5A and B). In this particular case, the use of read count for tRNA-His doubles the expression value comparing to tRNA-Ser. Thus, additionally to the raw count of reads, APART also calculates the maximal coverage values for contigs and identified stable RNA species.


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)

Experimental validation of the APART-predicted putative processing products. (A) Processing of the tRNA-His(GUG). On the left, UCSC Genome Browser visualization of the APART tracks (green) showing two possible processing products (processing sites marked with arrows). On the right, results of the northern blot experiment using total RNA isolated from S. cerevisiae grown in different environmental conditions (lanes: 1-UV radiation, 2-anaerobic, 3-optimal, 4-high pH, 5-low pH, 6-amino acid starvation, 7-sugar starvation) with probes against 5′- and 3′-halves of the tRNA-His. Full length tRNA is marked with open arrows, processing products are indicated by filled arrows. Differential stability of both parts can be observed. (B) Processing of the tRNA-Ser(AGA) (labeling as above). The inexact ends of the contig displayed on UCSC Genome Browser visualization suggest decreased stability of the 3′-derived processing product, comparing to tRNA-His, which is reflected by the northern blot results (right). (C) Cytoplasmic localization and processing of snoRNAs. On the left, northern blot presenting subcellular localization of snoRNA 128 (identified in this study) and snoRNA13 (not found in our cDNA library). The localization of the small nuclear RNAs sn7, sn14 and sn6 in the particular cellular fractions is also shown. For the northern analysis, total RNAs prepared either from the nuclear fraction, the cytoplasmic fraction, or from the mono- or polysomal fraction were blotted. The observed northern blot signals in the polysomal samples suggest that snoRNAs are associated with translating ribosomes in yeast. On the right, identification of the processing products derived from snoRNA 128 by northern blot using total RNA isolated from yeast grown under different environmental conditions. In all panels 5S rRNA served as internal loading control.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

gks020-F5: Experimental validation of the APART-predicted putative processing products. (A) Processing of the tRNA-His(GUG). On the left, UCSC Genome Browser visualization of the APART tracks (green) showing two possible processing products (processing sites marked with arrows). On the right, results of the northern blot experiment using total RNA isolated from S. cerevisiae grown in different environmental conditions (lanes: 1-UV radiation, 2-anaerobic, 3-optimal, 4-high pH, 5-low pH, 6-amino acid starvation, 7-sugar starvation) with probes against 5′- and 3′-halves of the tRNA-His. Full length tRNA is marked with open arrows, processing products are indicated by filled arrows. Differential stability of both parts can be observed. (B) Processing of the tRNA-Ser(AGA) (labeling as above). The inexact ends of the contig displayed on UCSC Genome Browser visualization suggest decreased stability of the 3′-derived processing product, comparing to tRNA-His, which is reflected by the northern blot results (right). (C) Cytoplasmic localization and processing of snoRNAs. On the left, northern blot presenting subcellular localization of snoRNA 128 (identified in this study) and snoRNA13 (not found in our cDNA library). The localization of the small nuclear RNAs sn7, sn14 and sn6 in the particular cellular fractions is also shown. For the northern analysis, total RNAs prepared either from the nuclear fraction, the cytoplasmic fraction, or from the mono- or polysomal fraction were blotted. The observed northern blot signals in the polysomal samples suggest that snoRNAs are associated with translating ribosomes in yeast. On the right, identification of the processing products derived from snoRNA 128 by northern blot using total RNA isolated from yeast grown under different environmental conditions. In all panels 5S rRNA served as internal loading control.
Mentions: The ample processing of RNA transcripts let us also reconsidering the use of read counts for the estimation of RNA abundance. RNA transcripts, especially ncRNAs, are frequently post-transcriptionally processed, thus the use of read counts in next-generation-sequencing projects for the estimation of the RNA abundance is problematic. Read count works well as a starting point for analyses focused on expression profiling of known genes. In this case, after proper normalization [for review see (38)], such number correspond to the number of the observed transcripts of a particular gene. However characteristics of cDNA libraries aimed for the identification of RNA processing products differ from those used for either mRNA or miRNA profiling. The main divergence is that the library preparation procedure does not involve a random fragmentation step (unlike mRNA profiling projects do) and no strict length separation is performed (unlike in the miRNA profiling approaches) resulting in a collection of transcript of various lengths. Thus, the same read count can be obtained for long contigs with random read distribution and for a short one with clear processing pattern. In this case, the analysis of the read distribution among the contig is crucial. Assuming that two non-overlapping reads mapped within a single contig can be derived from a single primary transcript by a processing event, the ultimate measure for RNA level will be the maximum coverage observed within the transcript. This measure corresponds to the number of overlapping reads observed for the assembled contig and reflects the minimal number of separate transcript copies in the cell. The use of the maximal coverage value is even more important when differential processing patterns of similar RNAs are taken into consideration, like in the case of tRNA-His and tRNA-Ser (Figure 5A and B). In this particular case, the use of read count for tRNA-His doubles the expression value comparing to tRNA-Ser. Thus, additionally to the raw count of reads, APART also calculates the maximal coverage values for contigs and identified stable RNA species.

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