Estimating the Genomewide Rate of Adaptive Protein Evolution in Drosophila

Abstract

When polymorphism and divergence data are available for multiple loci, extended forms of the McDonald-Kreitman test can be used to estimate the average proportion of the amino acid divergence due to adaptive evolution-a statistic denoted a. But such tests are subject to many biases. Most serious is the possibility that high estimates of a reflect demographic changes rather than adaptive substitution. Testing for between-locus variation in a is one possible way of distinguishing between demography and selection. However, such tests have yielded contradictory results, and their efficacy is unclear. Estimates of a from the same model organisms have also varied widely. This study clarifies the reasons for these discrepancies, identifying several method-specific biases in widely used estimators and assessing the power of the methods. As part of this process, a new maximum-likelihood estimator is introduced. This estimator is applied to a newly compiled data set of 115 genes from Drosophila simulans, each with each orthologs from D. melanogaster and D. yakuba. In this way, it is estimated that a % 0:4 6 0:1, a value that does not vary substantially between different loci or over different periods of divergence. The implications of these results are discussed. T HE McDonald-Kreitman test (McDonald andKreitman 1991; Kreitman and Akashi 1995) is an important technique for quantifying the contribution of positive Darwinian selection to molecular evolution. The test compares levels of polymorphism within a species to measures of divergence between species and relies on the assumption that a certain class of mutations can be treated as effectively neutral, a priori. Following McDonald and Kreitman, most studies have focused on protein-coding sequences and used synonymous mutations as their assumed-neutral referent. As such, the tests compare levels of synonymous polymorphism (P s ) and divergence (D s ) with their nonsynonymous (amino acid changing) equivalents (P n and D n ). The focus of many studies has been to estimate the proportion of the nonsynonymous divergence, D n , that was due to adaptive evolution, a statistic that is denoted a.A serious problem with these tests is that levels of polymorphism are typically low in most population samples at most loci, especially if rare variants are excluded, and this means that single-locus estimates of a can be unreliable. To solve this problem, many methods of combining data from multiple loci have been introduced (Fay et al. 2001;Bustamante et al. 2002;Smith and Eyre-Walker 2002;Sawyer et al. 2003;Bierne and Eyre-Walker 2004). Such methods can be used to estimate a, the average value of a across the sampled loci. However, it is now clear that different variants of the test have given different results when applied to data from the same model organism. Consider, for example, published results using polymorphism data from Drosophila simulans. Smith and Eyre-Walker (2002) introduced a heuristic estimator of a that they applied to a data set of 35 loci. Measuring diverg...

Extensive X-linked adaptive evolution in central chimpanzees

“…Last, we examined the 37 most abundant gene ontology categories in our data (58% and 38% of the exome data on the autosome and the X, respectively). We found a significant heterogeneity in α among categories on autosomes (Λ = 184, P < 1e-6) and on the X chromosome (Λ = 54, P < 0.003), suggesting that the differences above are genuine (6).…”

“…This allows measurement of the amount of adaptive evolution on the branch leading to chimpanzees, using the approach of ref. 6. All autosomes have an excess of nonsynonymous polymorphisms segregating compared with nonsynonymous fixed differences, leading to a neutrality index (NI) >1 and no evidence for adaptive evolution (Table S8).…”

“…To make a more robust estimation, we first used a series of models of increasing complexity ranging from a simplistic pure neutrality (f = 1, α = 0) model to models incorporating a variable intensity of positive or purifying selection (f and α were allowed to vary according to each chromosome or gene category). Estimation of parameters for each gene or category of gene was made using a likelihood framework as implemented in the MKtest software (6). To compare the various models, we used AIC as suggested by Welch (6).…”

“…Theory predicts and recent empirical studies emphasize that the demographic history as well as variation in mutation and recombination rates can blur footprints of molecular adaptation by Darwinian selection (3,4). This in turn can complicate the inference of DFE and α (5,6).…”

Evolution of genes and genomes on the Drosophila phylogeny

“…Previous work has suggested that a substantial fraction of nonsynonymous substitutions in Drosophila were fixed through positive selection [81][82][83][84][85] . We estimate that 33.1% of single-copy orthologues in the melanogaster group have experienced positive selection on at least a subset of codons (q-value true-positive tests 77 ) (Supplementary Information section 11.1).…”