= Solution
Sequence divergence alone does not identify its cause. A difference can arise through <mutation> and spread through <genetic drift>, <natural selection>, or both. The useful comparison is with an explicit neutral expectation that accounts for shared ancestry, <mutation rate> and demographic history, rather than treating every conspicuous genomic difference as an adaptation.
First establish <orthology>, align homologous sequence accurately, and sample several individuals from each species. An apparent fixed difference in one pair of genomes may actually be segregating variation, an assembly error or comparison of <paralogues>. An outgroup can help polarize changes, although ancestral polymorphism and <introgression> can make different genomic regions have different histories. Estimate population size changes, migration and relatedness from many suitably chosen loci before interpreting an exceptional region.
For coding sequence, compare nonsynonymous and synonymous substitution rates per eligible site through the <nonsynonymous-to-synonymous substitution rate ratio>. A ratio greater than one in an appropriate branch or site model supports adaptive amino-acid substitution; a low average ratio indicates pervasive constraint but can hide positive selection at a few sites. A rise toward one can reflect relaxed <purifying selection> rather than adaptation. Synonymous sites are useful controls, not guaranteed neutral standards: codon usage, splicing regulation and mutation-context effects can matter.
Within-species polymorphism adds an independent timescale. In the <McDonald-Kreitman test>, let $D_N,D_S$ be nonsynonymous and synonymous fixed differences and $P_N,P_S$ their polymorphic counterparts. A simple neutral model predicts matching ratios. An excess $D_N/D_S>P_N/P_S$ is consistent with adaptive fixation, and the idealized estimator
$$
\boxed{\alpha=1-\frac{D_SP_N}{D_NP_S}}
$$
estimates the adaptive fraction of nonsynonymous divergence. <John H. McDonald> and <Martin Kreitman> introduced this logic with the Drosophila Adh locus. Slightly deleterious variants inflate $P_N$, demographic changes affect which variants persist, and low counts make the ratio unstable; the model and uncertainty must therefore be examined rather than interpreting every positive estimate literally.<Adaptive protein evolution at the Adh locus in Drosophila by John H. McDonald and Martin Kreitman>[Polymorphism-divergence comparison and the Adh example]{ref}
Other signatures are complementary. A recent <selective sweep> can reduce linked diversity and distort the <site frequency spectrum> and <linkage disequilibrium>. Excess differentiation measured by <FST> can suggest geographically divergent selection, but can also result from reduced within-population diversity or population history. <Background selection> can mimic some diversity reductions. Comparisons with matched recombination and <mutation> environments, demographic simulations and several independent populations help discriminate these explanations. Long-maintained variation can instead leave signatures of <balancing selection>.
Noncoding differences require their own functional tests. A conserved regulatory element with an accelerated lineage-specific substitution rate is a candidate for altered function, but altered <mutation> bias or <GC-biased gene conversion> can also produce rapid sequence change. Reporter assays, <allele> replacement and measurements of expression, <phenotype> and fitness connect a candidate to a mechanism. Demonstrating an effect on expression does not by itself establish an advantage in the historical environment.
The strongest inference combines an appropriate population-genetic null, agreement among independent signatures, and a functional explanation connected to reproductive success. Conversely, failure to reject neutrality means that the evidence does not discriminate the models at the available resolution; it does not prove that a difference has no effect.
Back to article page
