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Sequencing and characterization of the guppy (Poecilia reticulata) transcriptome.

Fraser BA, Weadick CJ, Janowitz I, Rodd FH, Hughes KA - BMC Genomics (2011)

Bottom Line: The resulting 1,162,670 reads assembled into 54,921 contigs, creating a reference transcriptome for the guppy with an average read depth of 28×.We show that next-generation sequencing provided a reliable and broad reference transcriptome.This resource allowed us to identify candidate gene variants, SNPs in coding regions, and sex-specific gene expression, and permitted quantitative analysis of differential gene expression.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Science, Florida State University, Tallahassee, USA. fraser.bonnie8@gmail.com

ABSTRACT

Background: Next-generation sequencing is providing researchers with a relatively fast and affordable option for developing genomic resources for organisms that are not among the traditional genetic models. Here we present a de novo assembly of the guppy (Poecilia reticulata) transcriptome using 454 sequence reads, and we evaluate potential uses of this transcriptome, including detection of sex-specific transcripts and deployment as a reference for gene expression analysis in guppies and a related species. Guppies have been model organisms in ecology, evolutionary biology, and animal behaviour for over 100 years. An annotated transcriptome and other genomic tools will facilitate understanding the genetic and molecular bases of adaptation and variation in a vertebrate species with a uniquely well known natural history.

Results: We generated approximately 336 Mbp of mRNA sequence data from male brain, male body, female brain, and female body. The resulting 1,162,670 reads assembled into 54,921 contigs, creating a reference transcriptome for the guppy with an average read depth of 28×. We annotated nearly 40% of this reference transcriptome by searching protein and gene ontology databases. Using this annotated transcriptome database, we identified candidate genes of interest to the guppy research community, putative single nucleotide polymorphisms (SNPs), and male-specific expressed genes. We also showed that our reference transcriptome can be used for RNA-sequencing-based analysis of differential gene expression. We identified transcripts that, in juveniles, are regulated differently in the presence and absence of an important predator, Rivulus hartii, including two genes implicated in stress response. For each sample in the RNA-seq study, >50% of high-quality reads mapped to unique sequences in the reference database with high confidence. In addition, we evaluated the use of the guppy reference transcriptome for gene expression analyses in a congeneric species, the sailfin molly (Poecilia latipinna). Over 40% of reads from the sailfin molly sample aligned to the guppy transcriptome.

Conclusions: We show that next-generation sequencing provided a reliable and broad reference transcriptome. This resource allowed us to identify candidate gene variants, SNPs in coding regions, and sex-specific gene expression, and permitted quantitative analysis of differential gene expression.

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Gene ontology (GO) ID representations for our guppy transcriptome database (white) and the zebrafish transcriptome (grey). Three comparisons are shown: (a) biological processes ontology; (b) molecular function ontology; (c) cellular component ontology. Asterisks denote significant differences between species for each category. Significance was determined via χ2 tests with a p-value corrected for multiple tests.
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Figure 1: Gene ontology (GO) ID representations for our guppy transcriptome database (white) and the zebrafish transcriptome (grey). Three comparisons are shown: (a) biological processes ontology; (b) molecular function ontology; (c) cellular component ontology. Asterisks denote significant differences between species for each category. Significance was determined via χ2 tests with a p-value corrected for multiple tests.

Mentions: Guppy sequences that had matches in either the Swiss-Prot or NR databases were annotated with Gene Ontology (GO) annotations with the Uniprot database [23]. Of these, 22,029 of 22,773 (83%) were annotated with GO IDs corresponding to 10,442 unique matches in the Uniprot database. These unique matches were then grouped into generic GO terms (GO slims) [24] (Figure 1). We found that 5,201 (49.8%) records were annotated with a cellular component (GO:005575), 9,120 (87.4%) with a molecular function (GO:0003674), and 6,673 (63.9%) with a biological process (GO:008150).


Sequencing and characterization of the guppy (Poecilia reticulata) transcriptome.

Fraser BA, Weadick CJ, Janowitz I, Rodd FH, Hughes KA - BMC Genomics (2011)

Gene ontology (GO) ID representations for our guppy transcriptome database (white) and the zebrafish transcriptome (grey). Three comparisons are shown: (a) biological processes ontology; (b) molecular function ontology; (c) cellular component ontology. Asterisks denote significant differences between species for each category. Significance was determined via χ2 tests with a p-value corrected for multiple tests.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3113783&req=5

Figure 1: Gene ontology (GO) ID representations for our guppy transcriptome database (white) and the zebrafish transcriptome (grey). Three comparisons are shown: (a) biological processes ontology; (b) molecular function ontology; (c) cellular component ontology. Asterisks denote significant differences between species for each category. Significance was determined via χ2 tests with a p-value corrected for multiple tests.
Mentions: Guppy sequences that had matches in either the Swiss-Prot or NR databases were annotated with Gene Ontology (GO) annotations with the Uniprot database [23]. Of these, 22,029 of 22,773 (83%) were annotated with GO IDs corresponding to 10,442 unique matches in the Uniprot database. These unique matches were then grouped into generic GO terms (GO slims) [24] (Figure 1). We found that 5,201 (49.8%) records were annotated with a cellular component (GO:005575), 9,120 (87.4%) with a molecular function (GO:0003674), and 6,673 (63.9%) with a biological process (GO:008150).

Bottom Line: The resulting 1,162,670 reads assembled into 54,921 contigs, creating a reference transcriptome for the guppy with an average read depth of 28×.We show that next-generation sequencing provided a reliable and broad reference transcriptome.This resource allowed us to identify candidate gene variants, SNPs in coding regions, and sex-specific gene expression, and permitted quantitative analysis of differential gene expression.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biological Science, Florida State University, Tallahassee, USA. fraser.bonnie8@gmail.com

ABSTRACT

Background: Next-generation sequencing is providing researchers with a relatively fast and affordable option for developing genomic resources for organisms that are not among the traditional genetic models. Here we present a de novo assembly of the guppy (Poecilia reticulata) transcriptome using 454 sequence reads, and we evaluate potential uses of this transcriptome, including detection of sex-specific transcripts and deployment as a reference for gene expression analysis in guppies and a related species. Guppies have been model organisms in ecology, evolutionary biology, and animal behaviour for over 100 years. An annotated transcriptome and other genomic tools will facilitate understanding the genetic and molecular bases of adaptation and variation in a vertebrate species with a uniquely well known natural history.

Results: We generated approximately 336 Mbp of mRNA sequence data from male brain, male body, female brain, and female body. The resulting 1,162,670 reads assembled into 54,921 contigs, creating a reference transcriptome for the guppy with an average read depth of 28×. We annotated nearly 40% of this reference transcriptome by searching protein and gene ontology databases. Using this annotated transcriptome database, we identified candidate genes of interest to the guppy research community, putative single nucleotide polymorphisms (SNPs), and male-specific expressed genes. We also showed that our reference transcriptome can be used for RNA-sequencing-based analysis of differential gene expression. We identified transcripts that, in juveniles, are regulated differently in the presence and absence of an important predator, Rivulus hartii, including two genes implicated in stress response. For each sample in the RNA-seq study, >50% of high-quality reads mapped to unique sequences in the reference database with high confidence. In addition, we evaluated the use of the guppy reference transcriptome for gene expression analyses in a congeneric species, the sailfin molly (Poecilia latipinna). Over 40% of reads from the sailfin molly sample aligned to the guppy transcriptome.

Conclusions: We show that next-generation sequencing provided a reliable and broad reference transcriptome. This resource allowed us to identify candidate gene variants, SNPs in coding regions, and sex-specific gene expression, and permitted quantitative analysis of differential gene expression.

Show MeSH
Related in: MedlinePlus