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Heredity (Edinb) ; 119(3): 197-205, 2017 Sep.
Article in English | MEDLINE | ID: mdl-28613280

ABSTRACT

Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (VP), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of VP). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.


Subject(s)
Genetics, Population , Inheritance Patterns , Phenotype , Songbirds/genetics , Sparrows/genetics , Animals , Genetic Association Studies , Genotype , Linear Models , Male , Models, Genetic , Polymorphism, Single Nucleotide
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