DOI: 10.5061/dryad.zs7h44j5q
title: Data from: Deciphering genetic mate choice: not so simple in group-housed conservation breeding programs

description: Incorporating mate choice into conservation breeding programs can improve
 reproduction and the retention of natural behaviours. However, different
 types of genetic-based mate choice can have varied consequences for
 genetic diversity management. As a result, it is important to examine
 mechanisms of mate choice in captivity to assess its costs and benefits.
 Most research in this area has focused on experimental pairing trials,
 however this resource-intensive approach is not always feasible in captive
 settings and can interfere with other management constraints. We used
 generalised linear mixed models and permutation approaches to investigate
 overall breeding success in group-housed Tasmanian devils at three
 non-mutually exclusive mate choice hypotheses: (i) advantage of
 heterozygous individuals, (ii) advantage of dissimilar mates, and (iii)
 optimum genetic distance, using both 1,948 genome-wide SNPs and 12
 MHC-linked microsatellites. The managed devil insurance population is the
 largest such breeding program in Australia and is known to have high
 variance in reproductive success. We found that non-genetic factors such
 as age were the best predictors of breeding success in a competitive
 breeding scenario, with younger females and older males being more
 successful. We found no evidence of mate choice under the hypotheses
 tested. Mate choice varies among species and across environments, so we
 advocate for more studies in realistic captive management contexts as
 experimental or wild studies may not apply. Conservation managers must
 weigh up the need to wait for adequate sample sizes to detect mate choice
 with the risk that genetic changes may occur during this time in
 captivity. Our study shows that examining and integrating mate choice into
 the captive management of species housed in realistic, semi-natural
 group-based contexts may be more difficult than previously considered.
description: "Farquharson et al EvolAppl
 metadata.xlsx" This
 file comprises the following six sheets: a README with metadata to
 interpret the other sheets; 1) mate choice data: non-genetic and genetic
 information for each Tasmanian devil in the analysis, used to examine
 Hypothesis 1; 2) pedigree: the pedigree of offspring born in the
 free-range enclosures, used to test Hypotheses 2 & 3; 3) MHC
 genotypes: the raw genotypes at the 12 MHC-linked microsatellite loci,
 used to calculate standardised MHC-based heterozygosity and to test
 Hypotheses 2 & 3; 4) SNP genotypes: the genotypes at the 1948 SNP
 loci used to calculate standardised genome-wide heterozygosity; and 5) SNP
 data similarity: the genotypes at the 1948 SNP loci presented in
 two-column per loci format, used to test Hypotheses 2 & 3. Save
 each sheet separately as a .csv file for input directly into
 "Farquharson et al EvolAppl_code.R". "Farquharson et al
 EvolAppl_code.R" This R script can be used in conjunction
 with "Farquharson et al EvolAppl metadata.xlsx" to obtain the
 results of the various hypotheses tested. Save each sheet of
 "Farquharson et al EvolAppl metadata.xlsx" as a separate .csv
 file for input directly into the code. This code contains custom functions
 to calculate pairwise similarities of a group of breeding age individuals
 to examine observed pairwise similarities and compare these to pairwise
 similarities simulated under a random mating scenario in order to test
 mate choice hypotheses (e.g. advantage of dissimilar mates; optimum
 genetic distance).