The in-silico zebrafish matrisome: A new tool to study extracellular matrix gene and protein functions
Introduction
Extracellular matrix (ECM) proteins are major components of multicellular organisms that influence tissue biomechanics and a large number of biological processes. ECM proteins localized outside the cell or at the cell membrane where they adopt diverse conformations. Their specific structural features allowed their classification into different families, such as the laminins, the proteoglycans and the collagens [1], [2], [3].
To clarify the definition of an ECM protein and to identify all the corresponding protein-coding genes, the human and mouse matrisomes have been characterized. They were respectively established as composed of 1027 and 1110 genes, which represent about 4 to 5% of the gene content of their genomes [4], [5], [6]. Based on structural and functional features, matrisome genes were divided in two main divisions: the core matrisome and the matrisome-associated genes. The core matrisome group was further divided in three categories: collagens, proteoglycans and glycoproteins; matrisome-associated genes were further classified as encoding ECM-affiliated proteins, ECM regulators or secreted factors [4]. The different gene sets are available on the Matrisome Project website (http://matrisome.org/) and are now widely used to comprehensively annotate “-omic” data [6].
The zebrafish model rapidly gained popularity in developmental biology and health research because it presents several attractive features such as the small size of the larvae and adults, the large numbers of offspring, the external development of embryos, and genetic similarities with humans, to name but a few [7]. Morpholino-based gene knockdown and, later on, the CRISPR/Cas9 genome editing methodology, have truly revolutionized zebrafish genetics and rose it up to the rank of «top model» to study development, human diseases, and conduct drug screening [8], [9], [10], [11], [12]. Several studies have convincingly demonstrated the usefulness of zebrafish to study the contribution of ECM to a range of biological processes [13], [14], [15], [16], [17], [18], [19]. It has also emerged as a powerful model to understand human connective tissue diseases and other ECM-associated diseases such as cancers [17], [18], [19], [20].
Although ECM genes are often enriched in “-omic” datasets, no list is available to comprehensively annotate ECM genes and proteins in large-scale datasets obtain in zebrafish. We decided to fill this gap by defining the first draft of the zebrafish matrisome. To do so, we took advantage of the work previously done to establish the human and murine matrisome and devised an orthology-based approach to build the in-silico zebrafish matrisome. This novel tool should greatly facilitate the study of ECM proteins in zebrafish.
Section snippets
In-silico orthology-based approach to define the zebrafish matrisome
As a teleost fish, the genome of the zebrafish shows specific characteristics. Indeed, an additional whole-genome duplication took place in the common ancestor of all extant teleosts, 320–350 million years ago, called the teleost-specific whole-genome duplication (TS-WGD) [21], [22]. Even if various mechanisms acted for the loss or maintenance of duplicate genes (e.g. non-functionalization of one copy or on the contrary preservation of the duplicates with subfunctionalization,
Conclusions
In this study, we provide a novel tool to investigate in greater depth the involvement of the ECM in the zebrafish model organism. We believe that this first in-silico zebrafish matrisome will be of great interest for two main reasons. First, the use of the zebrafish model by the scientific community has been increasing for a decade and, secondly, the interest for ECM biology has recently regained attention due to its role as a main regulator of cell behavior and mechanotransduction. The
Acknowledgments
This work was done in part thanks to computing resources from CBP (Centre Blaise Pascal) from ENS of Lyon. The authors would like to thank Emmanuel Quemener that maintains the local Galaxy platform available. PN is a recipient of a “Fondation l'Oréal” 2016 French Fellowship L'Oréal-UNESCO For Women in Science, the French government (NMRT) and the “Fondation pour la Recherche Médicale” (FDT20160435169). This work was supported by the ANR (ANR-16-CE18-0023-03) to FR.
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