Literature DB >> 26817417

Random genetic drift, natural selection, and noise in human cranial evolution.

Charles C Roseman1.   

Abstract

OBJECTIVES: This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology.
MATERIALS AND METHODS: Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality.
RESULTS: Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. DISCUSSION: The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  hominin evolution; phenomics; population genomics; population history

Mesh:

Year:  2016        PMID: 26817417     DOI: 10.1002/ajpa.22918

Source DB:  PubMed          Journal:  Am J Phys Anthropol        ISSN: 0002-9483            Impact factor:   2.868


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