Computationally Predicted Gene Regulatory Networks in Molluscan Biomineralisation Identify Extracellular Matrix Production and Ion Transportation Pathways

Sleight, Victoria ORCID: https://orcid.org/0000-0003-0550-8500; Antczak, Philipp; Falciani, Francesco; Clark, Melody S. ORCID: https://orcid.org/0000-0002-3442-3824. 2020 Computationally Predicted Gene Regulatory Networks in Molluscan Biomineralisation Identify Extracellular Matrix Production and Ion Transportation Pathways. Bioinformatics, 36 (5). 1326-1332. https://doi.org/10.1093/bioinformatics/btz754

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Official URL: https://doi.org/10.1093/bioinformatics/btz754

Abstract/Summary

Motivation The molecular processes regulating molluscan shell production remain relatively uncharacterised, despite the clear evolutionary and societal importance of biomineralisation. Results Here we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineralisation using Antarctic clam (Laternula elliptica) mantle gene expression data produced over an age-categorised shell damage-repair time-course. We used previously published in vivo in situ hybridisation expression data to ground truth gene interactions predicted by the GRN and show that candidate biomineralisation genes from different shell layers, and hence microstructures, were connected in unique modules. We characterised two biomineralisation modules of the GRN and hypothesise that one module is responsible for translating the extracellular proteins required for growing, repairing or remodelling the nacreous shell layer, whereas the second module orchestrates the transport of both ions and proteins to the shell secretion site, which are required during normal shell growth, and repair. Our findings demonstrate that unbiased computational methods are particularly valuable for studying fundamental biological processes and gene interactions in non-model species where rich sources of gene expression data exist, but annotation rates are poor and the ability to carry out true functional tests are still lacking. Availability and Implementation The raw RNA-Seq data is freely available for download from NCBI SRA (Accession: PRJNA398984), the assembled and annotated transcriptome can be viewed and downloaded from molluscDB (ensembl.molluscdb.org) and in addition, the assembled transcripts, reconstructed GRN, modules and detailed annotations are all available as supplementary files.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1093/bioinformatics/btz754
ISSN:	13674803
Date made live:	23 Oct 2019 09:19 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/525417

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1093/bioinformatics/btz754

ISSN:

13674803

Date made live:

23 Oct 2019 09:19 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/525417