收敛演化
生物
声乐学习
克莱德
特质
进化生物学
多系
遗传学
基因
系统发育学
神经科学
计算机科学
程序设计语言
作者
Chul Lee,Seoae Cho,Kyu‐Won Kim,DongAhn Yoo,Matthew H. Davenport,Jae Yong Han,Hong Jo Lee,Gregory Gedman,Jean‐Nicolas Audet,Erina Hara,Miriam Rivas,Osceola Whitney,Andreas R. Pfenning,Heebal Kim,Erich D. Jarvis
摘要
Abstract Vocal learning, the ability to imitate sounds and a component of spoken language, is a complex convergent trait observed in only a few independent lineages of mammals and birds. Clear gene expression convergences have been found in vocal learning brain regions among several vocal learners, but amino acid convergences remain an open question. Here, we investigated whether avian vocal learning clades have amino acid convergences that could be related to their specialized trait. We developed a tool, Convergent Sequence Variant finder (CSV finder), applied to an alignment of 48 species representing nearly all bird orders, and identified convergent single amino acid variants among vocal learners and among most polyphyletic species combinations. We discovered that the numbers of convergent variants were associated with the product of branch lengths of the most recent common ancestors of each species combination. The number of convergent variants in vocal learning clades did not exceed that of control species combinations. However, a subset of genes with the vocal learner-specific variants was uniquely enriched in the ‘learning’ process, under positive selection, and supported by meta-analyses for FOXP2 targets, singing-induced regulation, and differential expression in song learning nuclei. Moreover, we confirmed convergent patterns were still enriched in 363 species densely sampled across the avian tree. We propose a hypothesis of a steady state background of amino acid and nucleotide convergence upon which selection acts for convergent traits, with the deeper in time their common ancestor the higher proportions of convergent genetic changes.
科研通智能强力驱动
Strongly Powered by AbleSci AI