Forstmeier W, Schielzeth H, Mueller JC, Ellegren H, Kempenaers B
Mol. Ecol. 21 (13) 3237-3249 [2012-07-00; online 2012-05-05]
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. Because of 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 1192 captive zebra finches and three measures of inbreeding: (i) heterozygosity across 11 microsatellite markers, (ii) heterozygosity across 1359 single-nucleotide polymorphism (SNP) markers and (iii) F, based on a 5th-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. Both marker-based approaches produced stronger correlations with phenotypes than the pedigree-based F, and this did not seem to result from the shortness of our pedigree. 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.
NGI Uppsala (SNP&SEQ Technology Platform)
National Genomics Infrastructure
PubMed 22554318
DOI 10.1111/j.1365-294X.2012.05593.x
Crossref 10.1111/j.1365-294X.2012.05593.x