Population genetic consequences of the Allee effect and the role of offspring-number variation
Meike J. Wittmann, Wilfried Gabriel, Dirk Metzler
(Submitted on 21 Nov 2013)
A strong demographic Allee effect in which the expected population growth rate is negative below a certain critical population size can cause high extinction probabilities in small introduced populations. However, many species are repeatedly introduced to the same location and eventually one population may overcome the Allee effect by chance. With the help of stochastic models, we investigate how much genetic diversity such successful populations harbour on average and how this depends on offspring-number variation, an important source of stochastic variability in population size. We find that with increasing variability, the Allee effect increasingly promotes genetic diversity in successful populations. Successful Allee-effect populations with highly variable population dynamics escape rapidly from the region of small population sizes and do not linger around the critical population size. Therefore, they are exposed to relatively little genetic drift. We show that here—unlike in classical population genetics models—the role of offspring-number variation cannot be accounted for by an effective-population-size correction. Thus, our results highlight the importance of detailed biological knowledge, in this case on the probability distribution of family sizes, when predicting the evolutionary potential of newly founded populations or when using genetic data to reconstruct their demographic history.
Calibrated birth-death phylogenetic time-tree priors for Bayesian inference
Joseph Heled, Alexei J.Drummond
(Submitted on 19 Nov 2013)
Here we introduce a general class of multiple calibration birth-death tree priors for use in Bayesian phylogenetic inference. All tree priors in this class separate ancestral node heights into a set of “calibrated nodes” and “uncalibrated nodes” such that the marginal distribution of the calibrated nodes is user-specified whereas the density ratio of the birth-death prior is retained for trees with equal values for the calibrated nodes. We describe two formulations, one in which the calibration information informs the prior on ranked tree topologies, through the (conditional) prior, and the other which factorizes the prior on divergence times and ranked topologies, thus allowing uniform, or any arbitrary prior distribution on ranked topologies. While the first of these formulations has some attractive properties the algorithm we present for computing its prior density is computationally intensive. On the other hand, the second formulation is always computationally efficient. We demonstrate the utility of the new class of multiple-calibration tree priors using both small simulations and a real-world analysis and compare the results to existing schemes. The two new calibrated tree priors described in this paper offer greater flexibility and control of prior specification in calibrated time-tree inference and divergence time dating, and will remove the need for indirect approaches to the assessment of the combined effect of calibration densities and tree process priors in Bayesian phylogenetic inference.
Natural Allelic Variations of Xenobiotic Enzymes Pleiotropically Affect Sexual Dimorphism in Oryzias latipes
Takafumi Katsumura, Shoji Oda, Shigeki Nakagome, Tsunehiko Hanihara, Hiroshi Kataoka, Hiroshi Mitani, Shoji Kawamura, Hiroki Oota
Sexual dimorphisms, which are phenotypic differences between males and females, are driven by sexual selection [1, 2]. Interestingly, sexually selected traits show geographic variations within species despite strong directional selective pressures [3, 4]. However, genetic factors that regulate varied sexual differences remain unknown. In this study, we show that polymorphisms in cytochrome P450 (CYP) 1B1, which encodes a xenobiotic-metabolising enzyme, are associated with local differences of sexual dimorphisms in the anal fin morphology of medaka fish (Oryzias latipes). High and low activity CYP1B1 alleles increased and decreased differences in anal fin sizes, respectively. Behavioural and phylogenetic analyses suggest maintenance of the high activity allele by sexual selection, whereas the low activity allele may have evolved by positive selection due to by-product effects of CYP1B1. The present data can elucidate evolutionary mechanisms behind genetic variations in sexual dimorphism and indicate pleiotropic effects of xenobiotic enzymes.
Patterns of positive selection in seven ant genomes
Julien Roux, Eyal Privman, Sebastien Moretti, Josephine T. Daub, Marc Robinson-Rechavi, Laurent Keller
(Submitted on 19 Nov 2013)
The evolution of ant species is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with specific patterns of molecular evolution we searched for signs of positive selection on amino-acid changes in proteins during the evolution of the ant lineage. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide dataset in bees and flies with the same methodology to check if genes under positive selection in ants were also under positive selection in the other analyzed lineages. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on this set of genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera, although it is assumed that the main challenges of the olfactory and neural systems in this lineage occurred with the evolution of social living. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was relaxed selective pressure for genes related to metabolism in ants but not in bees and flies, possibly reflecting the loss of flight in ant workers. By contrast, there was recurrent positive selection on genes with mitochondrial functions specifically in ants, suggesting that the activity of mitochondria was improved during ant evolution. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of this lineage.
Joint analysis of functional genomic data and genome-wide association studies of 18 human traits
Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWAS). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. We describe a statistical model that uses association statistics computed across the genome to identify classes of genomic element that are enriched or depleted for loci that influence a trait. The model naturally incorporates multiple types of annotations. We applied the model to GWAS of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, BMI, and Crohn’s disease. For each trait, we evaluated the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over a hundred tissues and cell lines. We show that the fraction of phenotype-associated SNPs that influence protein sequence ranges from around 2% (for platelet volume) up to around 20% (for LDL cholesterol); that repressed chromatin is significantly depleted for SNPs associated with several traits; and that cell type-specific DNase-I hypersensitive sites are enriched for SNPs associated with several traits (for example, fibroblasts in Crohn’s disease and muscle tissue in bone density). Finally, by re-weighting each GWAS using information from functional genomics, we increase the number of loci with high-confidence associations by around 5%.
On the concept of biological function, junk DNA and the gospels of ENCODE and Graur et al.
Claudiu I Bandea
In a recent article entitled On the immortality of television sets: “function” in the human genome according to the evolution-free gospel of ENCODE, Graur et al. dismantle ENCODEs evidence and conclusion that 80% of the human genome is functional. However, the article by Graur et al. contains assumptions and statements that are questionable. Primarily, the authors limit their evaluation of DNAs biological functions to informational roles, sidestepping putative non-informational functions. Here, I bring forward an old hypothesis on the evolution of genome size and on the role of so called junk DNA (jDNA), which might explain C-value enigma. According to this hypothesis, the jDNA functions as a defense mechanism against insertion mutagenesis by endogenous and exogenous inserting elements such as retroviruses, thereby protecting informational DNA sequences from inactivation or alteration of their expression. Notably, this model couples the mechanisms and the selective forces responsible for the origin of jDNA with its putative protective biological function, which represents a classic case of fighting fire with fire. One of the key tenets of this theory is that in humans and many other species, jDNAs serves as a protective mechanism against insertional oncogenic transformation. As an adaptive defense mechanism, the amount of protective DNA varies from one species to another based on the rate of its origin, insertional mutagenesis activity, and evolutionary constraints on genome size.
Validity of covariance models for the analysis of geographical variation
Gilles Guillot, René Schilling, Emilio Porcu, Moreno Bevilacqua
(Submitted on 17 Nov 2013)
Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. We focus here on a class of parametric covariance models that received sustained attention lately and show that the conditions under which they are valid mathematical models have been overlooked so far. We provide rigorous results for the construction of valid covariance models in this family. We also outline how to construct alternative covariance models for the analysis of geographical variation that are both mathematically well behaved and easily implementable.