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Comparative Study
, 7 (3), e33784

High Through-Put Sequencing of the Parhyale Hawaiensis mRNAs and microRNAs to Aid Comparative Developmental Studies

Comparative Study

High Through-Put Sequencing of the Parhyale Hawaiensis mRNAs and microRNAs to Aid Comparative Developmental Studies

Martin J Blythe et al. PLoS One.


Understanding the genetic and evolutionary basis of animal morphological diversity will require comparative developmental studies that use new model organisms. This necessitates development of tools for the study of genetics and also the generation of sequence information of the organism to be studied. The development of next generation sequencing technology has enabled quick and cost effective generation of sequence information. Parhyale hawaiensis has emerged as a model organism of choice due to the development of advanced molecular tools, thus P. hawaiensis genetic information will help drive functional studies in this organism.Here we present a transcriptome and miRNA collection generated using next generation sequencing platforms. We generated approximately 1.7 million reads from a P. hawaiensis cDNA library constructed from embryos up to the germ band stage. These reads were assembled into a dataset comprising 163,501 transcripts.Using the combined annotation of Annot8r and pfam2go, Gene Ontology classifications was assigned to 20,597 transcripts. Annot8r was used to provide KEGG orthology to our transcript dataset. A total of 25,292 KEGG pathway assignments were defined and further confirmed with reciprocal blast against the NCBI nr protein database. This has identified many P. hawaiensis gene orthologs of key conserved signalling pathways involved in development. We also generated small RNA sequences from P. hawaiensis, identifying 55 conserved miRNAs. Sequenced small RNAs that were not annotated by stringent comparison to mirBase were used to search the Daphnia pulex for possible novel miRNAs. Using a conservative approach, we have identified 51 possible miRNA candidates conserved in the Daphnia pulex genome, which could be potential crustacean/arthropod specific miRNAs. Our study presents gene and miRNA discovery in a new model organism that does not have a sequenced genome. The data provided by our work will be valuable for the P. hawaiensis community as well as the wider evolutionary developmental biology community.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Figure 1
Figure 1. 454 read length distribution.
A plot showing the distribution of the trimmed P. hawaiensis cDNA sequence reads generated from 454 Titanium sequencing chemistry.
Figure 2
Figure 2. Transcriptome assembly metrics according to the number of input reads.
The complete transcriptome assembly method was applied to an increasing number of randomly selected reads from the 454 sequencing data. With increasing reads the change in Isogroup (gene) discovery decreases in relation to that of Isotigs (transcript isoforms). This suggests further sequencing would define more alternately spliced transcripts in relation to fewer additional genes. The relative proportion of singlet and CAP3 contig transcripts also decreases as increasing read coverage of the transcriptome allows these low coverage transcripts to be assembled into isotigs.
Figure 3
Figure 3. Isogroup maximum open reading frame length distribution.
The distribution of the longest putative protein coding region in each Isogroup. Open reading frames are defined as translated regions that are free of stop codons. The frequency of ORFs according to length and Isogroup homology classification are shown. A classified Isogroup confers a homology match to Pfam, a selected proteome, or to the KEGG and GO databases via Annot8r. Isogroups with a maximal ORF length less than 150aa are typically shown to have no determined homology to known proteins, while those with longer ORFs, as shown in the subplot, are more frequently classified.
Figure 4
Figure 4. Cross-species BLASTX results.
The cross-species BLASTX results for P. hawaiensis transcripts compared to selected proteomes. The frequencies of transcript matches to each species with a significant hit (E-value ≤1e-5 green bar, ≤1e-10 red bar) are shown. The frequencies of top transcript matches (blue bar) compared to the total number of proteins are also shown.
Figure 5
Figure 5. The classifications of transcripts according to Gene Ontology (GO) terms.
The classification counts are shown for each of the first tier terms of the three GO database domains; Cellular Component (A), Biological Process (B), and Molecular Function (C).
Figure 6
Figure 6. The classification frequencies of transcripts according to Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways.
Classifications were determined by Annot8r for all transcripts. Shown are the classification counts for each of the first tier pathways under the 5 main KEGG categories.

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