DOI: 10.5061/dryad.6v0h65g3
title: Data from: Heterozygosity-fitness correlations in zebra finches: microsatellite markers can be better than their reputation

description: Numerous studies have reported associations between heterozygosity in
 microsatellite markers and fitness-related traits (heterozygosity-fitness
 correlations, HFCs). However, it has often been questioned whether HFCs
 reflect general inbreeding depression, because a small panel of
 microsatellite markers does not reflect very well an individual’s
 inbreeding coefficient (F) as calculated from a pedigree. Here we
 challenge this prevailing view. Due to chance events during Mendelian
 segregation, an individual’s realized proportion of the genome that is
 identical by descent (IBD) may substantially deviate from the
 pedigree-based expectation (i.e. F). This Mendelian noise may result in a
 weak correlation between F and multi-locus heterozygosity, but this does
 not imply that multi-locus heterozygosity is a bad estimator of realized
 IBD. We examined correlations between 11 fitness-related traits measured
 in up to 1,192 captive zebra finches and three measures of inbreeding: (1)
 heterozygosity across 11 microsatellite markers, (2) heterozygosity across
 1,359 SNP markers, and (3) F, based on a 5-generation pedigree. All 11
 phenotypic traits showed positive relationships with measures of
 heterozygosity, especially traits that are most closely related to
 fitness. Remarkably, the small panel of microsatellite markers produced
 equally strong HFCs as the large panel of SNP markers, and both
 marker-based approaches produced stronger correlations with phenotypes
 than the pedigree-based F. We argue that a small panel of microsatellites
 with high allelic richness may better reflect an individual’s realized IBD
 than previously appreciated, especially in species like the zebra finch,
 where much of the genome is inherited in large blocks that rarely
 experience cross-over during meiosis.
description: data_trait_ccattrTable that contains male attractiveness phenotypes based on choice chamber trials (2 columns). Ind_ID: identifier of the individual; CCattr: attractiveness score.data_trait_cchopsTable that contains choice activity phenotypes based on choice chamber trials (4 columns). Ind_ID: identifier of the individual; testFemale: sequence of tests per female; HopsTotal: total number of hops in choice chamber, HopsTotalSq: square-root transformed number of hops.data_trait_eggsizeTable that contains egg size phenotypes of egg laying females (5 columns). Ind_ID: identifier of the individual (the egg laying female); EggVolume: egg volume calculated from egg width and egg length (see paper for formula); EggLength: egg length in mm; EggWidth: egg width in mm; EggID: unique egg identifier.data_trait_cagefecundityTable that contains fecundity data measured in cages (5 columns). Ind_ID: identifier of the individual; nEggs: number of eggs produced; Days: duration of the breeding period in days; nWeeks: duration of the breeding period in (fractions of) weeks; FecundityCagesWeek: average number of eggs produced per week of the breeding period.data_trait_aviaryfecundityTable that contains fecundity data measured in aviaries (3 columns). Ind_ID: identifier of the individual; RelFitness: number of eggs produced standardized to relative fecundity within aviaries (division by aviary mean); Season: year of the breeding season.data_trait_beakcolourTable that contains beak colour phenotypes (4 columns). Ind_ID: identifier of the individual; BeakColourDA: beak colour score based on discriminant analysis (for details see paper); Sex: sex of the individual (0 = female, 1 = male); Session: identifier for the measuring session.data_trait_malefitnessTable that contains male siring success measured in aviaries (3 columns). Ind_ID: identifier of the individual; RelFitness: number of eggs sired standardized to relative siring success within aviaries (division by aviary mean); Season: year of the breeding season.data_trait_mass8Table that contains phenotypes of chick mass at day 8 (3 columns). Ind_ID: identifier of the individual; Mass8: chick weight in gram; Sex: sex of the individual (0 = female, 1 = male).data_trait_courtshiprateTable that contains courtship rate phenotypes (2 columns). Ind_ID: identifier of the individual; SongSq: square-root transformed number of seconds of song in standardized courtship trials.data_trait_tarsusTable that contains tarsus length phenotypes (3 columns). Ind_ID: identifier of the individual; Tarsus: tarsus length in mm; Sex: sex of the individual (0 = female, 1 = male).data_trait_weightTable that contains adult mass phenotypes (5 columns). Ind_ID: identifier of the individual; Mass: weight in gram; MassCubeRoot: cube-root transformed weight; Sex: sex of the individual (0 = female, 1 = male); Session: identifier for the measuring session.data_microsatellite_genotypesTable that contains microsatellite genotypes (6 columns). Ind_ID: identifier of the individual; InbredYN: whether or not an individual with the offspring a brother-sister mating (1 = true, 0 = false); Locus: locus name; Allele1: allele call of the shorter allele (0 represents null alleles); Allele2: allele call of the longer allele (0 represents null alleles); Heterozygote: whether or not the individual was heterozygous at the given locus (1 = true, 0 = false).data_heterozygositiesTable that contains pedigree-based inbreeding coefficient and marker-based heterozygosities (14 columns). Ind_ID: identifier of the individual; InbredYN: whether or not an individual with the offspring a brother-sister mating (1 = true, 0 = false); F: pedigree-based inbreeding coefficient; MLHms: multilocus heterozygosity based on microsatellites; IRms: internal relatedness based on microsatellites; HLms: homozygosity by locus based on microsatellites; d2ms: mean d square based on microsatellites; MLHsnp: multilocus heterozygosity based on SNPs; sMLHsnp: standardized multilocus heterozygosity based on SNPs; IRsnp: internal relatedness based on SNPs; MLHsnp: multilocus heterozygosity based on SNPs; HLsnp: homozygosity by locus based on SNPs; PCirirF: first principle component of F, IRms and IRsnp.