High-density SNP microarrays ("SNP chips") are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this article, we describe the development and application of a high-density Affymetrix Axiom chip with around 500,000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation. The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genomewide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays; (ii) detecting SNPs by more than one pipeline, and in independent data sets, ensures a high proportion of working assays; (iii) allele frequency ascertainment bias is minimized by performing SNP discovery in individuals from multiple populations; and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.

Population genetic theory predicts that selection should be more effective when the effective population size (Ne) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger Ne. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete.

Graphical AbstractHighlights d Laterally acquired genes rapidly spread among established populations of a grass d Subsequent genomic erosion created neutral gene presenceabsence polymorphisms d One of these neutral genes was secondarily swept into a population d Lateral gene transfers have both direct and delayed adaptive impacts

Small insertions and deletions (INDELs; ≤50 bp) are the most common type of variability after single nucleotide polymorphism (SNP). However, compared with SNPs, we know little about the distribution of fitness effects (DFE) of new INDEL mutations and how prevalent adaptive INDEL substitutions are. Studying INDELs has been difficult partly because identifying ancestral states at these sites is error-prone and misidentification can lead to severely biased estimates of the strength of selection. To solve these problems, we develop new maximum likelihood methods, which use polymorphism data to simultaneously estimate the DFE, the mutation rate, and the misidentification rate. These methods are applicable to both INDELs and SNPs. Simulations show that they can provide highly accurate results. We applied the methods to an INDEL polymorphism data set in Drosophila melanogaster. We found that the DFE for polymorphic INDELs in protein-coding regions is bimodal, with the variants being either nearly neutral or strongly deleterious. Based on the DFE, we estimated that 71.5–83.7% of the INDEL substitutions that took place along the D. melanogaster lineage were fixed by positive selection, which is comparable with the prevalence of adaptive substitutions at nonsynonymous sites. The new methods have been implemented in the software package anavar.

Recent progress has been made in identifying genomic regions implicated in trait evolution on a microevolutionary scale in many species, but whether these are relevant over macroevolutionary time remains unclear. Here, we directly address this fundamental question using bird beak shape, a key evolutionary innovation linked to patterns of resource use, divergence, and speciation, as a model trait. We integrate class-wide geometric-morphometric analyses with evolutionary sequence analyses of 10,322 protein-coding genes as well as 229,001 genomic regions spanning 72 species. We identify 1434 proteincoding genes and 39,806 noncoding regions for which molecular rates were significantly related to rates of bill shape evolution. We show that homologs of the identified protein-coding genes as well as genes in close proximity to the identified noncoding regions are involved in craniofacial embryo development in mammals. They are associated with embryonic stem cell pathways, including BMP and Wnt signaling, both of which have repeatedly been implicated in the morphological development of avian beaks. This suggests that identifying genotype-phenotype association on a genome-wide scale over macroevolutionary time is feasible. Although the coding and noncoding gene sets are associated with similar pathways, the actual genes are highly distinct, with significantly reduced overlap between them and bill-related phenotype associations specific to noncoding loci. Evidence for signatures of recent diversifying selection on our identified noncoding loci in Darwin finch populations further suggests that regulatory rather than coding changes are major drivers of morphological diversification over macroevolutionary times.