Computationally predicted gene regulatory networks in molluscan biomineralization identify extracellular matrix production and ion transportation pathways



Sleight, Victoria A, Antczak, Philipp ORCID: 0000-0001-9600-7757, Falciani, Francesco ORCID: 0000-0003-1432-2871 and Clark, Melody S
(2020) Computationally predicted gene regulatory networks in molluscan biomineralization identify extracellular matrix production and ion transportation pathways. BIOINFORMATICS, 36 (5). pp. 1326-1332.

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Abstract

Motivation The molecular processes regulating molluscan shell production remain relatively uncharacterized, despite the clear evolutionary and societal importance of biomineralization. Results Here we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineralization using Antarctic clam (Laternula elliptica) mantle gene expression data produced over an age-categorized shell damage-repair time-course. We used previously published in vivo in situ hybridization expression data to ground truth gene interactions predicted by the GRN and show that candidate biomineralization genes from different shell layers, and hence microstructures, were connected in unique modules. We characterized two biomineralization modules of the GRN and hypothesize 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.

Item Type: Article
Uncontrolled Keywords: Extracellular Matrix, Ions, Gene Expression Profiling, Gene Regulatory Networks, Biomineralization
Depositing User: Symplectic Admin
Date Deposited: 24 Oct 2019 10:08
Last Modified: 19 Jan 2023 00:21
DOI: 10.1093/bioinformatics/btz754
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3059294