The incorporation of ecological processes into models of trait evolution is important for understanding past drivers of evolutionary change. Species interactions have long been thought to be key drivers of trait evolution. However, models for comparative data that account for interactions between species are lacking. One of the challenges is that such models are intractable and difficult to express analytically. Here we present phylogenetic models of trait evolution that includes interspecific competition amongst species. Competition is modelled as a tendency of sympatric species to evolve towards distinct niches, producing trait overdispersion and high phylogenetic signal. The model predicts elevated trait variance across species and a slowdown in evolutionary rate both across the clade and within each branch. The model also predicts a reduction in correlation between otherwise correlated traits. We used an Approximate Bayesian Computation (ABC) approach to estimate model parameters. We tested the power of the model to detect deviations from Brownian trait evolution using simulations, finding reasonable power to detect competition in sufficiently large (20+ species) trees. We applied the model to examine the evolution of bill morphology of Darwin’s finches, and found evidence that competition affects the evolution of bill length.

Reticulate evolution is thought to accelerate the process of evolution beyond simple genetic drift and selection, helping to rapidly generate novel hybrids with combinations of adaptive traits. However, the long-standing dogma that reticulate evolutionary processes are likewise advantageous for switching ecological niches, as in microbial pathogen host switch events, has not been explicitly tested. We use data from the influenza genome sequencing project and a phylogenetic heuristic approach to show that reassortment, a reticulate evolutionary mechanism, predominates over mutational drift in transmission between different host species. Moreover, as host evolutionary distance increases, reassortment is increasingly favored. We conclude that the greater the quantitative difference between ecological niches, the greater the importance of reticulate evolutionary processes in overcoming niche barriers.

Adaptation in diploids is predicted to proceed via mutations that are at least partially dominant in fitness. Recently we argued that many adaptive mutations might also be commonly overdominant in fitness. Natural (directional) selection acting on overdominant mutations should drive them into the population but then, instead of bringing them to fixation, should maintain them as balanced polymorphisms via heterozygote advantage. If true, this would make adaptive evolution in sexual diploids differ drastically from that of haploids. Unfortunately, the validity of this prediction has not yet been tested experimentally. Here we performed 4 replicate evolutionary experiments with diploid yeast populations (Saccharomyces cerevisiae) growing in glucose-limited continuous cultures. We sequenced 24 evolved clones and identified initial adaptive mutations in all four chemostats. The first adaptive mutations in all four chemostats were three CNVs, all of which proved to be overdominant in fitness. The fact that fitness overdominant mutations were always the first step in independent adaptive walks strongly supports the prediction that heterozygote advantage can arise as a common outcome of directional selection in diploids and demonstrates that overdominance of de novo adaptive mutations in diploids is not rare.

Lamarckian inheritance has been largely discredited until the recent discovery of transgenerational epigenetic inheritance. However, transgenerational epigenetic inheritance is still under debate for unable to rule out DNA sequence changes as the underlying cause for heritability. Here, through profiling of the sperm methylomes and genomes of two recently diverged rat subspecies, we analyzed the relationship between epigenetic variation and DNA variation, and their relative contribution to evolution of species. We found that only epigenetic markers located in differentially methylated regions (DMRs) between subspecies, but not within subspecies, can be stably and effectively passed through generations. DMRs in response to both random and stable environmental difference show increased nucleotide diversity, and we demonstrated that it is variance of methylation level but not deamination caused by methylation driving increasing of nucleotide diversity in DMRs, indicating strong relationship between environment-associated changes of chromatin accessibility and increased nucleotide diversity. Further, we detected that accelerated fixation of DNA variants occur only in inter-subspecies DMRs in response to stable environmental difference but not intra-subspecies DMRs in response to random environmental difference or non-DMRs, indicating that this process is possibly driven by environment-associated fixation of divergent methylation status. Our results thus establish a bridge between Lamarckian inheritance and Darwinian selection.

Measurements from structural brain magnetic resonance imaging (MRI) scans have been increasingly analyzed as intermediate phenotypes to bridge the gap between clinical features and genetic variation. To date, most imaging phenotypes are scalar, such as the volume of a brain region, which can miss subtle or localized morphological variation associated with genetics or relevant to disease. Neuroanatomical shape measurements – multidimensional geometric descriptions of a brain structure – provide an alternate class of phenotypes that remain largely unexplored. In this paper, we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide single nucleotide polymorphism (SNP) and MRI data from 1,317 unrelated, young (18-35 years) and healthy individuals. Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and thus can serve as a complementary phenotype to study the genetic underpinnings and clinical relevance of brain structure.

Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach that enables the prediction of multiple medically relevant phenotypes without the costs associated with developing a genetic test for each of them. As a proof of principle, we used a common panel of 319,038 SNPs to train the prediction models in 114,264 unrelated White-British for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given their explained heritable component. This represents an improvement of up to 75% over the phenotypic variance explained by the predictors developed through large collaborations, which used more than twice as many training samples. Across-population predictions in White non-British individuals were similar to those of White-British whilst those in Asian and Black individuals were informative but less accurate. The genotyping of circa 500,000 UK Biobank participants will yield predictions ranging between 66% and 83% of the maximum. We anticipate that our models and a common panel of genetic markers, which can be used across multiple traits and diseases, will be the starting point to tailor disease management to the individual. Ultimately, we will be able to capitalise on whole-genome sequence and environmental risk factors to realise the full potential of genomic medicine.