De novo metatranscriptome assembly and coral gene expression profile of Montipora capitata with growth anomaly

Abstract

BackgroundScleractinian corals are a vital component of coral reef ecosystems, and of significant cultural and economic value worldwide. As anthropogenic and natural stressors are contributing to a global decline of coral reefs, understanding coral health is critical to help preserve these ecosystems. Growth anomaly (GA) is a coral disease that has significant negative impacts on coral biology, yet our understanding of its etiology and pathology is lacking. In this study we used RNA-seq along with de novo metatranscriptome assembly and homology assignment to identify coral genes that are expressed in three distinct coral tissue types: tissue from healthy corals (“healthy”), GA lesion tissue from diseased corals (“GA-affected”) and apparently healthy tissue from diseased corals (“GA-unaffected”). We conducted pairwise comparisons of gene expression among these three tissue types to identify genes and pathways that help us to unravel the molecular pathology of this coral disease.ResultsThe quality-filtered de novo-assembled metatranscriptome contained 76,063 genes, of which 13,643 were identified as putative coral genes. Overall gene expression profiles of coral genes revealed high similarity between healthy tissue samples, in contrast to high variance among diseased samples. This indicates GA has a variety of genetic effects at the colony level, including on seemingly healthy (GA-unaffected) tissue. A total of 105 unique coral genes were found differentially expressed among tissue types. Pairwise comparisons revealed the greatest number of differentially expressed genes between healthy and GA-affected tissue (93 genes), followed by healthy and GA-unaffected tissue (33 genes), and GA-affected and -unaffected tissue (7 genes). The putative function of these genes suggests GA is associated with changes in the activity of genes involved in developmental processes and activation of the immune system.ConclusionThis is one of the first transcriptome-level studies to investigate coral GA, and the first metatranscriptome assembly for the M. capitata holobiont. The gene expression data, metatranscriptome assembly and methodology developed through this study represent a significant addition to the molecular information available to further our understanding of this coral disease.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4090-y) contains supplementary material, which is available to authorized users.

Development of a Novel Reference Transcriptome for Scleractinian Coral Porites lutea Using Single-Molecule Long-Read Isoform Sequencing (Iso-Seq)

“…Mean GC content of the coral-specific assembly was 42.04%, which was comparable to the numbers reported for other anthozoan transcriptomes (Figure 1) (Shinzato et al, 2014;Anderson et al, 2016;Mansour et al, 2016;Frazier et al, 2017;Kenkel and Bay, 2017). Mean GC content of the Symbiodinium transcripts (51.77%) was also consistent with previous reports (Bayer et al, 2012;Shinzato et al, 2014;Mansour et al, 2016).…”

PhyloMagnet: Fast and accurate screening of short-read meta-omics data using gene-centric phylogenetics

“…To be able to compare our classification results to a more extensive set of extracted genome bins, we inferred taxonomic labels for those bins that were not part of the 13 non-redundant MAGs using the tool sourmash that uses k-mer matches to taxonomically classify genomes (Titus Brown and Irber, 2016). Finally, we analysed the metatranscriptomes published by Frazier et al (2017), who sequenced mRNA from both healthy corals and such that are a↵ected by so-called 'bleaching', a stress response in which Symbiodinium symbionts are expulsed . We used the chloroplast protein references to search for Dinophyceae (and especially Symbiodinium) sequences in the metatranscriptome data.…”

“…We then compared the assembled sequences and their placement in the reference trees with the sequences from the metatranscriptomic assembly available at NCBI's GEO database (Barrett et al, 2012). Similar to how the assembly was generated, we combined all of the 27 individual datasets by Frazier et al (2017) into a single dataset for this analysis. In order to identify the transcripts in the assembly, we performed a tblastN search, querying the reference sequences against a database of the quality filtered transcripts.…”

“…To evaluate the performance of the PhyloMagnet workflow and exemplify its potential uses, we performed three benchmark experiments using an in vitro mock community as well as environmental metagenomic and metatranscriptomic sequencing datasets. We chose the datasets such that we could compare the results produced by PhyloMagnet to reference genome mapping data (Singer et al, 2016), genomes extracted from metagenomes with taxonomic annotation (Delmont et al, 2018) and an assembled metatranscriptome (Frazier et al, 2017), respectively. For details on command line parameters see the supplementary methods.…”

“…Using PhyloMagnet contigs were reconstructed from the pooled coral bleaching dataset of Frazier et al (2017). Using the Phylogenetic placement workflow, contigs classified as Symbiodiniaceae could be identified in 10 out of the 12 chloroplast gene reference trees.…”