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GASS: genome structural annotation for Eukaryotes based on species similarity.

Wang Y, Chen L, Song N, Lei X - BMC Genomics (2015)

Bottom Line: The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS.We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons' boundary and then the incomplete splicing canonical sites in Refseq annotations.GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

View Article: PubMed Central - PubMed

Affiliation: Department of Automation, School of Information Science and Technology, Xiamen University, Xiamen, Fujian, 361005, China. wangying@xmu.edu.cn.

ABSTRACT

Background: With the development of high-throughput sequencing techniques, more and more genomes were sequenced and assembled. However, annotating a genome's structure rapidly and expressly remains challenging. Current eukaryotic genome annotations require various, abundant supporting data, such as: species-specific and cross-species protein sequences, ESTs, cDNA and RNA-Seq data. Collecting those data and merging their analytical results to achieve a consistent complete annotation is a complex, time and cost consuming task.

Results: In our study, we proposed a fast and easy-to-use computational tool: GASS (Genome Annotation based on Species Similarity). It annotates a eukaryotic genome based on only the annotations from another similar species. With aligning the exons' sequences of an annotated similar species to the un-annotated genome, GASS detects the optimal transcript annotations with a shortest-path model. In our study, GASS was used to achieve the rhesus annotations based on the human annotations. The produced annotations were evaluated by comparing them to the two existing rhesus annotation databases (RefSeq and Ensembl) directly and being aligned with three RNA-Seq data of rhesus. The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS. GASS's sensitivity was higher than RefSeq's, and was close to Ensembl's. GASS had higher specificities than Ensembl at gene, transcript, exon and splicing junction levels. We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons' boundary and then the incomplete splicing canonical sites in Refseq annotations. These detections were further supported by various data sources.

Conclusions: GASS quickly produces structural genome annotations in sufficient abundance and accuracy. With simple and rapid running of GASS, small labs can create quick views of genome annotations for an un-annotated species, without the necessity to create, collect, analyze and synthesize extra various data sources, or wait several months for the annotations from professional organizations. GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

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Genes’ boundaries in RefSeq-rheMac3 and GASS. The genes’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis for comparison respectively. Almost all the dots are highly close to the line Y = X, which means that the genes’ boundaries from GASS and RefSeq-rheMac3 are highly identical. The logarithm is applied to re-scale the coordinates. The black sold line is an offset of 3° and 95% of the points are close to the sold line.
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Fig5: Genes’ boundaries in RefSeq-rheMac3 and GASS. The genes’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis for comparison respectively. Almost all the dots are highly close to the line Y = X, which means that the genes’ boundaries from GASS and RefSeq-rheMac3 are highly identical. The logarithm is applied to re-scale the coordinates. The black sold line is an offset of 3° and 95% of the points are close to the sold line.

Mentions: We also compared the transcripts’ starting and termination sites identified in RefSeq-rheMac3 and GASS for the 3,647 common genes. The transcripts starting and termination positions are marked with circles and stars in Figure 5, respectively. The transcripts’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis respectively. Almost all the dots are highly close to the line Y = X, which means that the transcripts’ starting and termination sites from GASS and RefSeq-rheMac3 are highly identical.Figure 5


GASS: genome structural annotation for Eukaryotes based on species similarity.

Wang Y, Chen L, Song N, Lei X - BMC Genomics (2015)

Genes’ boundaries in RefSeq-rheMac3 and GASS. The genes’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis for comparison respectively. Almost all the dots are highly close to the line Y = X, which means that the genes’ boundaries from GASS and RefSeq-rheMac3 are highly identical. The logarithm is applied to re-scale the coordinates. The black sold line is an offset of 3° and 95% of the points are close to the sold line.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4352269&req=5

Fig5: Genes’ boundaries in RefSeq-rheMac3 and GASS. The genes’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis for comparison respectively. Almost all the dots are highly close to the line Y = X, which means that the genes’ boundaries from GASS and RefSeq-rheMac3 are highly identical. The logarithm is applied to re-scale the coordinates. The black sold line is an offset of 3° and 95% of the points are close to the sold line.
Mentions: We also compared the transcripts’ starting and termination sites identified in RefSeq-rheMac3 and GASS for the 3,647 common genes. The transcripts starting and termination positions are marked with circles and stars in Figure 5, respectively. The transcripts’ boundaries of GASS and RefSeq-rheMac3 are designated in X-axis and Y-axis respectively. Almost all the dots are highly close to the line Y = X, which means that the transcripts’ starting and termination sites from GASS and RefSeq-rheMac3 are highly identical.Figure 5

Bottom Line: The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS.We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons' boundary and then the incomplete splicing canonical sites in Refseq annotations.GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

View Article: PubMed Central - PubMed

Affiliation: Department of Automation, School of Information Science and Technology, Xiamen University, Xiamen, Fujian, 361005, China. wangying@xmu.edu.cn.

ABSTRACT

Background: With the development of high-throughput sequencing techniques, more and more genomes were sequenced and assembled. However, annotating a genome's structure rapidly and expressly remains challenging. Current eukaryotic genome annotations require various, abundant supporting data, such as: species-specific and cross-species protein sequences, ESTs, cDNA and RNA-Seq data. Collecting those data and merging their analytical results to achieve a consistent complete annotation is a complex, time and cost consuming task.

Results: In our study, we proposed a fast and easy-to-use computational tool: GASS (Genome Annotation based on Species Similarity). It annotates a eukaryotic genome based on only the annotations from another similar species. With aligning the exons' sequences of an annotated similar species to the un-annotated genome, GASS detects the optimal transcript annotations with a shortest-path model. In our study, GASS was used to achieve the rhesus annotations based on the human annotations. The produced annotations were evaluated by comparing them to the two existing rhesus annotation databases (RefSeq and Ensembl) directly and being aligned with three RNA-Seq data of rhesus. The experiment results showed that more than 65% RefSeq exons and splicing junctions were exactly found by GASS. GASS's sensitivity was higher than RefSeq's, and was close to Ensembl's. GASS had higher specificities than Ensembl at gene, transcript, exon and splicing junction levels. We also found the mis-assemblies of rheMac3 genome, which led to the 2 bp shifts in annotating position on exons' boundary and then the incomplete splicing canonical sites in Refseq annotations. These detections were further supported by various data sources.

Conclusions: GASS quickly produces structural genome annotations in sufficient abundance and accuracy. With simple and rapid running of GASS, small labs can create quick views of genome annotations for an un-annotated species, without the necessity to create, collect, analyze and synthesize extra various data sources, or wait several months for the annotations from professional organizations. GASS can be applied to many study occasions, such as the analysis of RNA-Seq datasets from the unannotated species whose genome drafts are available but the annotations are not.

Show MeSH