Document Detail


Modularity, noise, and natural selection.
MedLine Citation:
PMID:  22519787     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Most biological systems are formed by component parts that are to some degree interrelated. Groups of parts that are more associated among themselves and are relatively autonomous from others are called modules. One of the consequences of modularity is that biological systems usually present an unequal distribution of the genetic variation among traits. Estimating the covariance matrix that describes these systems is a difficult problem due to a number of factors such as poor sample sizes and measurement errors. We show that this problem will be exacerbated whenever matrix inversion is required, as in directional selection reconstruction analysis. We explore the consequences of varying degrees of modularity and signal-to-noise ratio on selection reconstruction. We then present and test the efficiency of available methods for controlling noise in matrix estimates. In our simulations, controlling matrices for noise vastly improves the reconstruction of selection gradients. We also perform an analysis of selection gradients reconstruction over a New World Monkeys skull database to illustrate the impact of noise on such analyses. Noise-controlled estimates render far more plausible interpretations that are in full agreement with previous results.
Authors:
Gabriel Marroig; Diogo A R Melo; Guilherme Garcia
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Publication Detail:
Type:  Journal Article     Date:  2012-02-06
Journal Detail:
Title:  Evolution; international journal of organic evolution     Volume:  66     ISSN:  1558-5646     ISO Abbreviation:  Evolution     Publication Date:  2012 May 
Date Detail:
Created Date:  2012-04-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0373224     Medline TA:  Evolution     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1506-24     Citation Subset:  IM    
Copyright Information:
© 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
Affiliation:
Laboratório de Evolução de Mamíferos, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências Universidade de São Paulo, Caixa Postal 11.461, CEP 05422 970, São Paulo, SP, Brasil E-mail: gmarroig@usp.br.
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