DOI: 10.5061/dryad.2280gb5pb
title: Data from: Predicting multivariate responses of sexual dimorphism to direct and indirect selection

description: Sexual dimorphism is often assumed to result from balancing the strength
 of antagonistic selection in favor of dimorphism against the degree of
 constraint imposed by the shared genome of the sexes, reflected in
 the  B  matrix of genetic inter-sexual
 covariances.  To investigate the totality of forces shaping
 dimorphism, we reparameterized the Lande equation to predict changes in
 trait averages and trait differences between the sexes.  As
 genetic constraints on the evolution of dimorphism in response to
 antagonistic selection become larger, dimorphism will tend to respond more
 rapidly to concordant selection  (which favors the same direction
 of change in male and female traits) than to antagonistic
 selection.  When we apply this theory to four empirical estimates
 of  B  in Drosophila melanogaster, the indirect
 responses of dimorphism to concordant selection are of comparable or
 larger magnitude than the direct responses of dimorphism to antagonistic
 selection in two suites of traits with typical levels of inter-sex
 correlation.  Antagonistic selection is more important in two
 suites of traits where the inter-sex correlations are unusually
 low.  This suggests that the evolution of sexual dimorphism may
 sometimes be dominated by concordant selection, rather than antagonistic
 selection. 
description: This submission include data set includes sexually differentiated
 G-matrix estimates, and SAS code to estimate the genetic variation within
 and between sexually antagonistic and concordant subspaces, and calculate
 estimates of the direct and indirect respondabilities to selection in each
 subspace. The G-matrix estimates are drawn from
 <em>Drosophila melanogaster</em> populations presented in
 three papers (Houle and Cheng 2020; Sztepanacz and Houle 2019 and Ingleby
 et al. 2014): The Houle and Cheng (2020) and Sztepanacz and Houle (2019)
 data include 1,000 estimates of G-matrices consistent with the underlying
 data estimated using the REML-MVN method. The Ingleby et al. (2014) data
 includes just the best estimates of G given in that paper's Tables 3
 and 5.  No estimates of sampling variation are given. Houle, D., and C.
 Cheng. 2020. Predicted evolution of multivariate sexual dimorphism of gene
 expression in Drosophila melanogaster. bioRxiv doi: Sztepanacz, J.
 L., and D. Houle. 2019. Cross-sex genetic covariances limit the
 evolvability of wing-shape within and among species of
 <i>Drosophila</i>. Evolution 73:1617-1633. Ingleby, F. C.,
 P. Innocenti, H. D. Rundle, and E. H. Morrow. 2014. Between-sex genetic
 covariance constrains the evolution of sexual dimorphism in<i>
 Drosophila melanogaster</i>. Journal of Evolutionary Biology
 27:1721-1732.  
description: To analyze these data as presented, you must have the  SAS system
 software (e.g.SAS 2016) installed.  Once you have unpacked the ZIP file,
 change the path within the SAS files to point to the  directory where you
 have unpacked the data, and run the programs, which have .SAS extensions. 
 Some data are in .csv files, but most are in SAS data sets. If you do not
 have SAS, you can still use conversion utilities in other software, such
 as R, to read that data.   SAS Institute, Inc. 2016.The
 SAS System for Windows, Release 9.4.SAS Institute, Cary, NC.<br>