Dataset on the transcriptome of the mangrove oyster Crassostrea gasar
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The growing accessibility to NGS technologies led to the rapid development of innovative bioinformatics tools to analyze sequence data and fill the databases with new finds. However, current bioinformatics workflows focus on emerging technologies data. In contrast, bioinformatics tools dedicated to former sequencing methods (i.e., Roche 454 GS FLX+) have become deprecated. Therefore, we revisited the pyro-sequenced C. gasar raw reads, and we discovered they contain unraveled and valuable information. As such, this data contains information about the comparison of different bioinformatics tools and their capabilities to generate informative transcriptomes from the Roche 454 read data of gills and digestive glands of the oyster C. gasar previously challenged with environmental pollutants and thus retrieve a more comprehensive transcriptome. The Trinotate pipeline (http://trinotate.github.io) was used to annotate protein function and gene ontology, and pathway assignment of identified open reading frames (ORFs). Nucleotide and protein sequences were used to search against the NCBI nr and UniProtKB/Swiss-Prot (uniprot_sprot.trinotate_v2.0.pep.gz) databases using NCBI-BLASTx and BLASTp v2.10.0 (e-value 1e−10 -max_target_seqs 1 -outfmt 6), respectively. In this novel transcriptome, we were able to identify genes related to Zn distribution in cells (Zn transporters - ZIP, ZnT), metallothionein (MTI and MTIV), Ca+ transporter (NCX and ATP2B), and Cu distribution in cells (ATP7, ATOX1, CCS, and laccase-like).
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Publication Details
Subfield
Molecular Biology
Field
Biochemistry, Genetics and Molecular Biology
Domain
Life Sciences
Confidence Score
53%
Source
Scholar Data Model