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PLoS One
2015 Nov 03;1011:e0142003. doi: 10.1371/journal.pone.0142003.
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De Novo Assembly and Characterization of the Invasive Northern Pacific Seastar Transcriptome.
Richardson MF
,
Sherman CD
.
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Invasive species are a major threat to global biodiversity but can also serve as valuable model systems to examine important evolutionary processes. While the ecological aspects of invasions have been well documented, the genetic basis of adaptive change during the invasion process has been hampered by a lack of genomic resources for the majority of invasive species. Here we report the first larval transcriptomic resource for the Northern Pacific Seastar, Asterias amurensis, an invasive marine predator in Australia. Approximately 117.5 million 100 base-pair (bp) paired-end reads were sequenced from a single RNA-Seq library from a pooled set of full-sibling A. amurensis bipinnaria larvae. We evaluated the efficacy of a pre-assembly error correction pipeline on subsequent de novo assembly. Error correction resulted in small but important improvements to the final assembly in terms of mapping statistics and core eukaryotic genes representation. The error-corrected de novo assembly resulted in 115,654 contigs after redundancy clustering. 41,667 assembled contigs were homologous to sequences from NCBI''s non-redundant protein and UniProt databases. We assigned Gene Ontology, KEGG Orthology, Pfam protein domain terms and predicted protein-coding sequences to > 36,000 contigs. The final transcriptome dataset generated here provides functional information for 18,319 unique proteins, comprising at least 11,355 expressed genes. Furthermore, we identified 9,739 orthologs to P. miniata proteins, evaluated our annotation pipeline and generated a list of 150 candidate genes for responses to several environmental stressors that may be important for adaptation of A. amurensis in the invasive range. Our study has produced a large set of A. amurensis RNA contigs with functional annotations that can serve as a resource for future comparisons to other echinoderm transcriptomes and gene expression studies. Our data can be used to study the genetic basis of adaptive change and other important evolutionary processes during a successful invasion.
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???displayArticle.pmcLink???PMC4631335 ???displayArticle.link???PLoS One
Fig 1. Length and coverage distributions of assembled contigs.(A) Contig length (bp) distribution for the error-corrected (EC) and original (O) datasets. (B) Contig coverage, calculated as average per base coverage across a contig, for the error-corrected (EC) and original (O) datasets.
Fig 3. Gene Ontology (GO) annotations.The top 10 represented GO terms for each of the GO categories: Biological Process, Molecular Function and Cellular Component. GO functional annotations are derived from similarity to the protein databases (Swiss-Prot, TrEMBL and NCBIâs non-redundant database).
Fig 4. Kegg Orthology (KO) annotations.The top 10 represented KO terms from the KEGG Automatic Annotation Server (KAAS) annotation results.
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