Mantle transcriptome sequencing of Mytilus spp. and identification of putative biomineralization genes

In molluscs, the shell secreted by mantle tissue during the biomineralization process is the first barrier against predators and mechanical damage. Changing environmental conditions, such as ocean acidification, influence shell strength and thus protection of the soft body within. Mussels are marine bivalves with important commercial and ecological value worldwide. Despite this importance, the proteins involved in the biomineralization and pigmentation processes in Mytilus spp. remain unclear, as does taxonomy of Mytilus taxa, though there have been many molecular studies. To further understanding in these areas, this study aimed to characterize and compare mantle transcriptomes of four mussel taxa using next generation sequencing. Mussels representing four taxa, were collected from several localities and RNA from mantle tissue was extracted. RNA sequences obtained were assembled, annotated and potential molecular markers, including simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) were identified. Candidate contigs putatively related to biomineralization and pigmentation processes were then selected and several transcripts were chosen for phylogenetic analyses from the Bivalvia class. Transcriptome comparisons between Mytilus taxa, including gene ontology (GO) enrichment analysis and orthologues identification were performed. Of assembled contigs, 46.57%, 37.28% and 17.53% were annotated using NCBI NR, GO and Kyoto Encyclopedia of Genes and Genomes databases, respectively. Potential SSRs (483) and SNPs (1,497) were identified. Results presented a total of 1,292 contigs putatively involved in biomineralization and melanogenesis. Phylogenetic analyses of α-carbonic anhydrase, chitinase and tyrosinase revealed complex evolutionary history and diversity of these genes, which may be a result of duplication events or adaptation to different environments in mussels and other bivalves. Enrichment analyses revealed GO terms associated with pH and thermal response in Mytilus edulis from the North Sea and M. galloprovincialis from the Mediterranean Sea. The phylogenetic analysis within the genus Mytilus revealed M. californianus and M. coruscus to be genetically more distant from the other taxa: M. trossulus, M. edulis, M. chilensis and M. galloprovincialis. This work represents the first mantle transcriptome comparison between Mytilus taxa and provides contigs putatively involved in biomineralization

A marine biodiversity observation network for genetic monitoring of hard-bottom communities (ARMS-MBON)

Marine hard-bottom communities are undergoing severe change under the influence of multiple drivers, notably climate change, extraction of natural resources, pollution and eutrophication, habitat degradation, and invasive species. Monitoring marine biodiversity in such habitats is, however, challenging as it typically involves expensive, non-standardized, and often destructive sampling methods that limit its scalability. Differences in monitoring approaches furthermore hinders inter-comparison among monitoring programs. Here, we announce a Marine Biodiversity Observation Network (MBON) consisting of Autonomous Reef Monitoring Structures (ARMS) with the aim to assess the status and changes in benthic fauna with genomic-based methods, notably DNA metabarcoding, in combination with image-based identifications. This article presents the results of a 30-month pilot phase in which we established an operational and geographically expansive ARMS-MBON. The network currently consists of 20 observatories distributed across European coastal waters and the polar regions, in which 134 ARMS have been deployed to date. Sampling takes place annually, either as short-term deployments during the summer or as long-term deployments starting in spring. The pilot phase was used to establish a common set of standards for field sampling, genetic analysis, data management, and legal compliance, which are presented here. We also tested the potential of ARMS for combining genetic and image-based identification methods in comparative studies of benthic diversity, as well as for detecting non-indigenous species. Results show that ARMS are suitable for monitoring hard-bottom environments as they provide genetic data that can be continuously enriched, re-analyzed, and integrated with conventional data to document benthic community composition and detect non-indigenous species. Finally, we provide guidelines to expand the network and present a sustainability plan as part of the European Marine Biological Resource Centre (www.embrc.eu).Peer reviewe

<i>De novo</i> assembly of the sea trout (<i>Salmo trutta</i> m. <i>trutta</i>) skin transcriptome to identify putative genes involved in the immune response and epidermal mucus secretion

<div><p>In fish, the skin is a multifunctional organ and the first barrier against pathogens. Salmonids differ in their susceptibility to microorganisms due to varied skin morphology and gene expression patterns. The brown trout is a salmonid species with important commercial and ecological value in Europe. However, there is a lack of knowledge regarding the genes involved in the immune response and mucus secretion in the skin of this fish. Thus, we characterized the skin transcriptome of anadromous brown trout using next-generation sequencing (NGS). A total of 1,348,306 filtered reads were obtained and assembled into 75,970 contigs. Of these contigs 48.57% were identified using BLAST tool searches against four public databases. KEGG pathway and Gene Ontology analyses revealed that 13.40% and 34.57% of the annotated transcripts, respectively, represent a variety of biological processes and functions. Among the identified KEGG Orthology categories, the best represented were signal transduction (23.28%) and immune system (8.82%), with a variety of genes involved in immune pathways, implying the differentiation of immune responses in the trout skin. We also identified and transcriptionally characterized 8 types of mucin proteins–the main structural components of the mucosal layer. Moreover, 140 genes involved in mucin synthesis were identified, and 1,119 potential simple sequence repeats (SSRs) were detected in 3,134 transcripts.</p></div

List of the immune pathways identified in the sea trout skin transcriptome.

<p>List of the immune pathways identified in the sea trout skin transcriptome.</p

Classification of the mucins identified in skin transcriptome, according to the BLASTX and BLASTN searches.

<p>Classification of the mucins identified in skin transcriptome, according to the BLASTX and BLASTN searches.</p

Unrooted phylogenetic tree showing the evolutionary relationship of the secreted gel-forming mucins (Muc2, Muc5AC, Muc5B, and I-Muc) in teleosts.

<p>The tree was constructed using multiple alignment of the VWD and C8 domains of the translated (ST_9981, ST_36280, ST_39) and selected teleost families: Salmonidae, Esocidae, and Cichlidae. The maximum likelihood phylogeny in MEGA 7 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172282#pone.0172282.ref061" target="_blank">61</a>] was selected. The tree was bootstrapped 1,000 times. Accession numbers: Atlantic salmon I-Muc* (XP_014041914), northern pike I-Muc* (XP_012994242.1), northern pike I-Muc** (XP_012993966.1), Atlantic salmon I-Muc** (XP_013982567.1), <i>Astatotilapia burtoni</i> I-Muc* (XP_005941718.1), <i>A</i>. <i>burtoni</i> I-Muc** (XP_005946303.1); <i>A</i>. <i>burtoni</i> I-Muc*** (XP_005952623.1), Atlantic salmon I-Muc*** (XP_014038548.1), Atlantic salmon Muc5B (XP_014031349.1), Atlantic salmon Muc5AC (XP_014036802.1), northern pike Muc5AC (XP_010867519.2), <i>A</i>. <i>burtoni</i> Muc5AC (XP_005946314.1), <i>A</i>. <i>burtoni</i> Muc2 (XP_005952624.2), northern pike Muc2 (XP_012994223.1), Atlantic salmon Muc2 (XP_014040158.1).</p

Characteristics of the homology search of sea trout transcripts.

<p>(A) Venn diagram illustrating the distribution of matches against four public databases (NCBI nr, Swiss-Prot, Teleost Ensembl and KOG databases). In total, 36,902 (48.57%) transcripts were annotated. (B) E-value and (C) species distribution of the best hits based on the NCBI nr database.</p

The eukaryotic orthologous groups (KOG) classification of the sea trout contigs.

<p>The eukaryotic orthologous groups (KOG) classification of the sea trout contigs.</p

Statistical summary of sea trout skin transcriptome data.

<p>Statistical summary of sea trout skin transcriptome data.</p

Gene Ontology comparative classification of the sea trout skin transcriptome (black) and multi-tissue transcriptome from the River Hayle and River Teign in southwest England (orange).

<p>Gene Ontology comparative classification of the sea trout skin transcriptome (black) and multi-tissue transcriptome from the River Hayle and River Teign in southwest England (orange).</p