title: Genomic Complexity Places Less Restrictions on the Evolution of Young Coexpression Networks than Protein-Protein Interactions.
abstract: The differences in evolutionary patterns of young protein-protein interactions (PPIs) among distinct species have long been a puzzle. However, based on our genome-wide analysis of available integrated experimental data, we confirm that young genes preferentially integrate into ancestral PPI networks, and that this manner is consistent in all of six model organisms with widely different levels of phenotypic complexity. We demonstrate that the level of restrictions placed on the evolution of biological networks declines with a decrease of phenotypic complexity. Compared with young PPI networks, new co-expression links have less evolutionary restrictions, so a young gene with a high possibility to be coexpressed other young genes relatively frequently emerges in the four simpler genomes among the six studied. However, it is not favorable for such young-young coexpression in terms of a young gene evolving into a coexpression hub, so the coexpression pattern could gradually decline. To explain this apparent contradiction, we suggest that young genes that are initially peripheral to networks are temporarily coexpressed with other young genes, driving functional evolution because of low selective pressure. However, as the expression levels of genes increase and they gradually develop a greater effect on fitness, young genes start to be coexpressed more with members of ancestral networks and less with other young genes. Our findings provide new insights into the evolution of biological networks.
authors: School of Life Sciences, Chongqing University, Chongqing, China School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
authors: Wen
authors: W
authors: Wei
authors: Key Laboratory for Neuroinformation of the Ministry of Education, Center of Bioinformatics, University of Electronic Science and Technology of China, Chengdu, China Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China.
authors: Yan-Ting
authors: YT
authors: Jin
authors: Key Laboratory for Neuroinformation of the Ministry of Education, Center of Bioinformatics, University of Electronic Science and Technology of China, Chengdu, China Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China.
authors: Meng-Ze
authors: MZ
authors: Du
authors: School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.
authors: Ju
authors: J
authors: Wang
authors: Key Laboratory for Neuroinformation of the Ministry of Education, Center of Bioinformatics, University of Electronic Science and Technology of China, Chengdu, China Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China.
authors: Nini
authors: N
authors: Rao
authors: Key Laboratory for Neuroinformation of the Ministry of Education, Center of Bioinformatics, University of Electronic Science and Technology of China, Chengdu, China Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China fbguo@uestc.edu.cn.
authors: Feng-Biao
authors: FB
authors: Guo
mesh_terms: D000818:Animals; D001105:Archaea / Q000235:genetics; D001419:Bacteria / Q000235:genetics; D019143:Evolution, Molecular; D005658:Fungi / Q000235:genetics; D053263:Gene Regulatory Networks; D056084:Genetic Fitness; D016678:Genome; D006801:Humans; D010641:Phenotype; D060066:Protein Interaction Maps
keywords: biological network; phenotypic complexity; young gene