Beyond Genomics: Studying Evolution with Gene Coexpression Networks. (April 2017)

• Record Type: Journal Article
• Authors: Ruprecht, Colin; Vaid, Neha; Proost, Sebastian; Persson, Staffan; Mutwil, Marek
• Is Part Of: Trends in plant science. Volume 22:Number 4(2017)
• Page Start: 298
• Page End: 307
• Publication Date: 2017-04
• Subjects: Botany -- Periodicals; Botanique -- Périodiques; Botany; Periodicals; 580.5
• DOI: 10.1016/j.tplants.2016.12.011
• Languages: English
• ISSNs: 1360-1385

Abstract

Abstract : Understanding how genomes change as organisms become more complex is a central question in evolution. Molecular evolutionary studies typically correlate the appearance of genes and gene families with the emergence of biological pathways and morphological features. While such approaches are of great importance to understand how organisms evolve, they are also limited, as functionally related genes work together in contexts of dynamic gene networks. Since functionally related genes are often transcriptionally coregulated, gene coexpression networks present a resource to study the evolution of biological pathways. In this opinion article, we discuss recent developments in this field and how coexpression analyses can be merged with existing genomic approaches to transfer functional knowledge between species to study the appearance or extension of pathways. Trends: Genomic studies correlate the appearance of new gene families with the emergence of novel biological processes. However, biological processes and pathways are composed of multiple genes that work together (i.e., gene modules). To provide a more complete understanding of evolution, these functional relationships need to be taken into account. Since functionally related genes are often transcriptionally coordinated (coexpressed), coexpression networks, and comparative studies of these, provide a basis for studying evolution of gene modules. Systematic analyses of coexpression networks demonstrated that gene modules can be highly conserved across distant species. Recent bioinformatic advances revealed that some gene modules have duplicated over time, suggesting that certain biological pathways are present in multiple copies within an organism. By combining traditional genomic approaches with coexpression networks of lower and higher plants, we can expand our knowledge on how biological pathways emerge or are extended.