Abstract
The integration of genetic information in the cellular and nuclear environments is crucial for deciphering the way in which the genome functions under different physiological conditions. Experimental techniques of 3D nuclear mapping, a high-flow approach such as transcriptomic data analyses, and statistical methods for the development of co-expressed gene networks, can be combined to develop an integrated approach for depicting the regulation of gene expression. Our work focused more specifically on the mechanisms involved in the transcriptional regulation of genes expressed in muscle during late foetal development in pig. The data generated by a transcriptomic analysis carried out on muscle of foetuses from two extreme genetic lines for birth mortality are used to construct networks of differentially expressed and co-regulated genes. We developed an innovative co-expression networking approach coupling, by means of an iterative process, a new statistical method for graph inference with data of gene spatial co-localization (3D DNA FISH) to construct a robust network grouping co-expressed genes. This enabled us to highlight relevant biological processes related to foetal muscle maturity and to discover unexpected gene associations between IGF2, MYH3 and DLK1/MEG3 in the nuclear space, genes that are up-regulated at this stage of muscle development.
Highlights
Cell type diversity in a given organism cannot be explained only by DNA sequences
We highlighted associations between the expressed alleles of IGF2 and DLK1/MEG3 locus (DLK1 being related to the control of muscle development and regeneration16), in foetal muscle and liver cells[17]
For the study described in this article, we developed a new method for the construction of a co-expression gene network with genes involved in the foetal muscle maturation process, using an original approach coupling a statistical model and observed data in an iterative process to further our understanding of the mechanisms involved in muscle development
Summary
Cell type diversity in a given organism cannot be explained only by DNA sequences. Cis- and trans-acting regulatory sequences are not the only determinants of gene expression: other epigenetic mechanisms are responsible for tissue-specific expression of genes. We highlighted associations between the expressed alleles of IGF2 and DLK1/MEG3 locus (DLK1 being related to the control of muscle development and regeneration16), in foetal muscle and liver cells[17] These results illustrate the implication in trans-interactions of genes associated with quantitative trait loci (QTLs) for growth traits, providing new evidence that genome organization could influence gene expression and phenotypic outcome in livestock species. In this context, we focused on the study of the muscle maturity process (essential for the survival of piglets) to better understand how interesting phenotypes are elaborated, by combining transcriptome and co-localization data with network modelling. This approach has been found relevant for extracting biological information such as important genes with respect to their centrality in the network structure[25], densely connected groups of genes[26] or frequent motifs[27]
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