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J He, State Key Laboratory of Genetic Resource and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
D Irwin, Banting and Best Diabetes Centre, Department of Laboratory Medicine and Pathobiology, Toronto, Ontario, Canada
R Chen, State Key Laboratory of Genetic Resource and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
Y Zhang, State Key Laboratory of Genetic Resource and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China

Correspondence: Ya-ping Zhang, Email: zhangyp{at}mail.kiz.ac.cn

Abstract

Specific interactions among biomolecules drive virtually all cellular functions and underlie phenotypic complexity and diversity. Biomolecules are not isolated particles, but are elements of integrated interaction networks, and play their roles through specific interactions. Simultaneous emergence or loss of multiple interacting partners is unlikely. If one of the interacting partners is lost, what then are the evolutionary consequences for the retained partner? Taking advantages of the availability of the large number of mammalian genome sequences and knowledge of phylogenetic relationships of the species, we examined the evolutionary fate of the motilin hormone gene, after the pseudogenization of its specific receptor, MLNR, on the rodent lineage. We speculate that the motilin receptor gene became a pseudogene before the divergence of the squirrel and other rodents about 75 MYA. The evolutionary consequences for the motilin gene were diverse. While an intact ORF for the motilin gene, which appears functional, was preserved in the Kangaroo rat, the motilin gene became inactivated independently on the lineages leading to the guinea pig and the common ancestor of the mouse and rat. Gain and loss of specific interactions among biomolecules through the birth and death of genes for biomolecules point to a general evolutionary dynamic: gene birth and death are widespread phenomena in genome evolution, at the genetic level, thus, once mutations arise a stepwise process of elaboration and optimization ensues that gradually integrates and orders mutations into a coherent pattern.