Testing the neutral hypothesis of phenotypic evolution

Although evolution by natural selection is widely regarded as the most important principle of biology, it is unknown whether phenotypic variations within and between species are mostly adaptive or neutral due to the lack of relevant studies of large, unbiased samples of phenotypic traits. Here, we e...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 114; no. 46; pp. 12219 - 12224
Main Authors Ho, Wei-Chin, Ohya, Yoshikazu, Zhang, Jianzhi
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 14.11.2017
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Summary:Although evolution by natural selection is widely regarded as the most important principle of biology, it is unknown whether phenotypic variations within and between species are mostly adaptive or neutral due to the lack of relevant studies of large, unbiased samples of phenotypic traits. Here, we examine 210 yeast morphological traits chosen because of experimental feasibility irrespective of their potential adaptive values. Our analysis is based on the premise that, under neutrality, the rate of phenotypic evolution measured in the unit of mutational size declines as the trait becomes more important to fitness, analogous to the neutral paradigm that functional genes evolve more slowly than functionless pseudogenes. However, we find faster evolution of more important morphological traits within and between species, rejecting the neutral hypothesis. By contrast, an analysis of 3,466 gene expression traits fails to refute neutrality. Thus, at least in yeast, morphological evolution appears largely adaptive, but the same may not apply to other classes of phenotypes. Our neutrality test is applicable to other species, especially genetic model organisms, for which estimations of mutational size and trait importance are relatively straightforward.
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Author contributions: W.-C.H. and J.Z. designed research; W.-C.H. and Y.O. performed research; Y.O. contributed new reagents/analytic tools; W.-C.H. analyzed data; and W.-C.H. and J.Z. wrote the paper.
Edited by Wen-Hsiung Li, Academia Sinica, Taipei, Taiwan, and approved October 6, 2017 (received for review June 29, 2017)
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.1710351114