The evolutionary stability of quantitative traits depends on whether a population can resist invasion by any mutant. While uninvadability is well understood in well-mixed populations, it is much less so in subdivided populations when multiple traits evolve jointly. Here, we investigate whether a spatially subdivided population at a monomorphic equilibrium for multiple traits can withstand invasion by any mutant, or is subject to diversifying selection. Our model also explores the among traits correlations arising from diversifying selection and how they depend on relatedness due to limited dispersal. We find that selection favours a positive (negative) correlation between two traits, when the selective effects of one trait on relatedness is positively (negatively) correlated to the indirect fitness effects of the other trait. We study the evolution of traits for which this matters: dispersal that decreases relatedness, and helping that has positive indirect fitness effects. We find that when dispersal cost is low and the benefits of helping accelerate faster than its costs, selection leads to the coexistence of mobile defectors and sessile helpers. Otherwise, the population evolves to a monomorphic state with intermediate helping and dispersal. Overall, our results highlight the importance of population subdivision for evolutionary stability and correlations among traits.
We propose a faster algorithm for individual based simulations for adaptive dynamics based on a simple modification to the standard Gillespie Algorithm for simulating stochastic birth-death processes. We provide an analytical explanation that shows that simulations based on the modified algorithm, in the deterministic limit, lead to the same equations of adaptive dynamics as well as same conditions for evolutionary branching as those obtained from the standard Gillespie algorithm. Based on this algorithm, we provide an intuitive and simple interpretation of the canonical equation of adaptive dynamics. With the help of examples we compare the performance of this algorithm to the standard Gillespie algorithm and demonstrate its efficiency. We also study an example using this algorithm to study evolutionary dynamics in a multi-dimensional phenotypic space and study the question of predictability of evolution.
Fast coalescent-based computation of local branch support from quartet frequencies
Erfan Sayyari, Siavash Mirarab
Species tree reconstruction is complicated by effects of Incomplete Lineage Sorting (ILS), commonly modeled by the multi-species coalescent model. While there has been substantial progress in developing methods that estimate a species tree given a collection of gene trees, less attention has been paid to fast and accurate methods of quantifying support. In this paper, we propose a fast algorithm to compute quartet-based support for each branch of a given species tree with regard to a given set of gene trees. We then show how the quartet support can be used in the context of the multi-species coalescent model to compute i) the local posterior probability that the branch is in the species tree and ii) the length of the branch in coalescent units. We evaluate the precision and recall of the local posterior probability on a wide set of simulated and biological data, and show that it has very high precision and improved recall compared to multi-locus bootstrapping. The estimated branch lengths are highly accurate when gene trees have little error, but are underestimated when gene tree estimation error increases. Computation of both branch length and local posterior probability is implemented as a new feature in ASTRAL.
Using runs of homozygosity to detect genomic regions associated with susceptibility to infectious and metabolic diseases in dairy cows under intensive farming conditions
Filippo Biscarini, Stefano Biffani, Nicola Morandi, Ezequiel L. Nicolazzi, Alessandra Stella
Runs of homozygosity (ROH) are contiguous stretches of homozygous genome which likely reflect transmission from common ances- tors and can be used to track the inheritance of haplotypes of interest. In the present paper, ROH were extracted from 50K SNPs and used to detect regions of the genome associated with susceptibility to diseases in a population of 468 Holstein-Frisian cows. Diagnosed diseases were categorised as infectious diseases, metabolic syndromes, mastitis, reproductive diseases and locomotive disorders. ROH associated with infectious diseases, mastitis and locomotive disorders were found on BTA 12. A long region of homozygosity linked with metabolic syndromes, infectious and reproductive diseases was detected on BTA 15, disclosing complex relationships between immunity, metabolism and functional disorders. ROH associated with infectious and reproductive diseases, mastitis and metabolic syndromes were observed on chromosomes 3, 5, 7, 13 and 18. Previous studies reported QTLs for milk production traits on all of these regions, thus substantiating the known negative relationship between selection for milk production and health in dairy cattle.
Bayesian phylogenetic estimation of fossil ages
Alexei J. Drummond, Tanja Stadler
Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular the fossilized birth-death tree prior and the Lewis-MK model of evolution of discrete morphological change allow for the estimation of both divergence times and phylogenetic relationships between fossil and extant taxa. We exploit this statistical framework to investigate the internal consistency of these models by estimating the phylogenetic age of each fossil in turn, within two rich and well-characterized data sets of fossil and extant species. We find that we can accurately estimate the age of individual fossils based only on phylogenetic evidence. In fact in the two data sets we analyze the phylogenetic age of a fossil species is on average <2My from the midpoint age of the geological strata from which it was excavated. The high level of internal consistency found in our analyses provides strong evidence that the Bayesian statistical model employed is a good fit for both the geological and morphological data, and provides striking evidence from real data that the framework used can accurately model the evolution of discrete morphological traits coded from fossil and extant taxa. We anticipate that this approach will have diverse applications beyond divergence time dating, including dating fossils that are temporally unconstrained, testing the “morphological clock”, and for uncovering potential model misspecification and/or data errors when controversial phylogenetic hypotheses are obtained based on combined divergence dating analyses.