Taming Strong Selection with Large Sample Sizes

The fate of mutations and the genetic load of populations depend on the relative importance of genetic drift and natural selection. In addition, the accuracy of numerical models of evolution depends on the strength of both selection and drift: strong selection breaks the assumptions of the nearly neutral model, and drift coupled with large sample sizes breaks Kingman's coalescent model. Thus, the regime with strong selection and large sample sizes, relevant to the study of pathogenic variation, appears particularly daunting. Surprisingly, we find that the interplay of drift and selection in that regime can be used to define asymptotically closed recursions for the distribution of allele frequencies that are accurate well beyond the strong selection limit. Selection becomes more analytically tractable when the sample size n is larger than twice the population-scaled selection coefficient: n >= 2Ns (4Ns in diploids). That is, when the expected number of coalescent events in the sample is larger than the number of selective events. We construct the relevant transition matrices, show how they can be used to accurately compute distributions of allele frequencies, and show that the distribution of deleterious allele frequencies is sensitive to details of the evolutionary model.

Unmatched Level of Molecular Convergence among Deeply Divergent Complex Multicellular Fungi

Convergent evolution is pervasive in nature, but it is poorly understood how various constraints and natural selection limit the diversity of evolvable phenotypes. Here, we analyze the transcriptome across fruiting body development to understand the independent evolution of complex multicellularity in the two largest clades of fungi—the Agarico- and Pezizomycotina. Despite >650 My of divergence between these clades, we find that very similar sets of genes have convergently been co-opted for complex multicellularity, followed by expansions of their gene families by duplications. Over 82% of shared multicellularity-related gene families were expanding in both clades, indicating a high prevalence of convergence also at the gene family level. This convergence is coupled with a rich inferred repertoire of multicellularity-related genes in the most recent common ancestor of the Agarico- and Pezizomycotina, consistent with the hypothesis that the coding capacity of ancestral fungal genomes might have promoted the repeated evolution of complex multicellularity. We interpret this repertoire as an indication of evolutionary predisposition of fungal ancestors for evolving complex multicellular fruiting bodies. Our work suggests that evolutionary convergence may happen not only when organisms are closely related or are under similar selection pressures, but also when ancestral genomic repertoires render certain evolutionary trajectories more likely than others, even across large phylogenetic distances.

Unmatched level of molecular convergence among deeply divergent complex multicellular fungi

Convergent evolution is pervasive in nature, but it is poorly understood how various constraints and natural selection limit the diversity of evolvable phenotypes. Here, we report that, despite >650 million years of divergence, the same genes have repeatedly been co-opted for the development of complex multicellularity in the two largest clades of fungi—the Ascomycota and Basidiomycota. Co-opted genes have undergone duplications in both clades, resulting in >81% convergence across shared multicellularity-related families. This convergence is coupled with a rich repertoire of multicellularity-related genes in ancestors that predate complex multicellular fungi, suggesting that the coding capacity of early fungal genomes was well suited for the repeated evolution of complex multicellularity. Our work suggests that evolution may be predictable not only when organisms are closely related or are under similar selection pressures, but also if the genome biases the potential evolutionary trajectories organisms can take, even across large phylogenetic distances.

Long-term Response: 1. Deterministic Aspects

In a large population in the absence of new mutation, selection is expected to eventually drive all of the additive-genetic variance in a trait toward zero, resulting in a selection limit. This chapter examines the underlying population-genetics of such a limit, how it is estimated, and reviews the actual nature of limits observed in artificial selection experiments. It also examines the conditions under which a major gene is more important than polygenic response.

Genome-based establishment of a high-yielding heterotic pattern for hybrid wheat breeding

Hybrid breeding promises to boost yield and stability. The single most important element in implementing hybrid breeding is the recognition of a high-yielding heterotic pattern. We have developed a three-step strategy for identifying heterotic patterns for hybrid breeding comprising the following elements. First, the full hybrid performance matrix is compiled using genomic prediction. Second, a high-yielding heterotic pattern is searched based on a developed simulated annealing algorithm. Third, the long-term success of the identified heterotic pattern is assessed by estimating the usefulness, selection limit, and representativeness of the heterotic pattern with respect to a defined base population. This three-step approach was successfully implemented and evaluated using a phenotypic and genomic wheat dataset comprising 1,604 hybrids and their 135 parents. Integration of metabolomic-based prediction was not as powerful as genomic prediction. We show that hybrid wheat breeding based on the identified heterotic pattern can boost grain yield through the exploitation of heterosis and enhance recurrent selection gain. Our strategy represents a key step forward in hybrid breeding and is relevant for self-pollinating crops, which are currently shifting from pure-line to high-yielding and resilient hybrid varieties.

Racehorses are getting faster

Previous studies have concluded that thoroughbred racehorse speed is improving very slowly, if at all, despite heritable variation for performance and putatively intensive selective breeding. This has led to the suggestion that racehorses have reached a selection limit. However, previous studies have been limited, focusing only on the winning times of a few elite races run over middle and long distances, and failing to account for potentially confounding factors. Using a much larger dataset covering the full range of race distances and accounting for variation in factors such as ground softness, we show that improvement is, in fact, ongoing for the population as a whole, but driven largely by increasing speed in sprint races. In contrast, speed over middle and long distances, at least at the elite level, appears to be reaching an asymptote. Whether this reflects a selection limit to speed over middle and long distances or a shift in breeding practices to target sprint performances remains to be determined.