Genetic draft, selective interference, and population genetics of rapid adaptation

To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetic inference is based on frameworks assuming adaptive evolution is rare. But if positive selection operates on many loci simultaneously, as has recently been suggested for many species including animals such as flies, a different approach is necessary. In this review, I discuss recent progress in characterizing and understanding evolution in rapidly adapting populations where random associations of mutations with genetic backgrounds of different fitness, i.e., genetic draft, dominate over genetic drift. As a result, neutral genetic diversity depends weakly on population size, but strongly on the rate of adaptation or more generally the variance in fitness. Coalescent processes with multiple mergers, rather than Kingman's coalescent, are appropriate genealogical models for rapidly adapting populations with important implications for population genetic inference.Comment: supplementary illustrations and scripts are available at http://webdav.tuebingen.mpg.de/interference

Factors influencing the nematode community during composting and nematode-based criteria for compost maturity

Pilot studies indicate that shifts in the nematode species composition, life strategies and feeding behavior during composting appear to be fairly consistent and, therefore, promising as a potential tool to assess compost maturity. However, this has been only based on a limited number of, mainly, non-replicated observations. In this study, we tested whether the nematode community succession patterns are recurrent for parallel processes and assessed the relationship between the changes in the nematode community and potential important variables (i.e., temperature, duration of composting and the microbial community). The nematode and microbial community of three simultaneously running Controlled Farm Composting and a reference Green Waste composting process were analyzed through time. Bacterial-feeding enrichment opportunists were most numerous during and directly after the heat peaks. Subsequently, the bacterial-feeding/predator community dominated and the fungal-feeding nematodes became more dominant during maturation, confirming general community patterns from previous experiments. Nematode abundances significantly fluctuated with temperature and the relative abundance of fungal-feeding nematodes increased as the duration of the curing process increased. The amount of fungal-feeding nematodes was associated significantly with both duration of composting and temperature, and the F/(F + B) ratio was only significantly associated with duration of composting. Based on these results, and additional data from an industrial reference compost process and on available literature, a Nematode-based Index of Compost Maturity (NICM) is proposed, combining four nematode-based criteria (i.e., nematode abundance, F/(F + B) ratio, the presence of more than one fungal-feeding taxon and the presence of diplogasterids). Nevertheless, the NICM should be considered as work in progress which should be tested for a wider range of composts from diverse feedstock mixtures, locations (sites) and composting techniques, to validate the use of the index and allow more reliable interpretation of particular values of this index

Deleterious synonymous mutations hitchhike to high frequency in HIV-1 env evolution

Intrapatient HIV-1 evolution is dominated by selection on the protein level in the arms race with the adaptive immune system. When cytotoxic CD8+ T-cells or neutralizing antibodies target a new epitope, the virus often escapes via nonsynonymous mutations that impair recognition. Synonymous mutations do not affect this interplay and are often assumed to be neutral. We analyze longitudinal intrapatient data from the C2-V5 part of the envelope gene (env) and observe that synonymous derived alleles rarely fix even though they often reach high frequencies in the viral population. We find that synonymous mutations that disrupt base pairs in RNA stems flanking the variable loops of gp120 are more likely to be lost than other synonymous changes, hinting at a direct fitness effect of these stem-loop structures in the HIV-1 RNA. Computational modeling indicates that these synonymous mutations have a (Malthusian) selection coefficient of the order of -0.002 and that they are brought up to high frequency by hitchhiking on neighboring beneficial nonsynonymous alleles. The patterns of fixation of nonsynonymous mutations estimated from the longitudinal data and comparisons with computer models suggest that escape mutations in C2-V5 are only transiently beneficial, either because the immune system is catching up or because of competition between equivalent escapes

FFPopSim: An efficient forward simulation package for the evolution of large populations

The analysis of the evolutionary dynamics of a population with many polymorphic loci is challenging since a large number of possible genotypes needs to be tracked. In the absence of analytical solutions, forward computer simulations are an important tool in multi-locus population genetics. The run time of standard algorithms to simulate sexual populations increases as 8^L with the number L of loci, or with the square of the population size N. We have developed algorithms that allow to simulate large populations with a run-time that scales as 3^L. The algorithm is based on an analog of the Fast-Fourier Transform (FFT) and allows for arbitrary fitness functions (i.e. any epistasis) and genetic maps. The algorithm is implemented as a collection of C++ classes and a Python interface.Comment: available from: http://code.google.com/p/ffpopsi

Competition between recombination and epistasis can cause a transition from allele to genotype selection

Biochemical and regulatory interactions central to biological networks are expected to cause extensive genetic interactions or epistasis affecting the heritability of complex traits and the distribution of genotypes in populations. However, the inference of epistasis from the observed phenotype-genotype correlation is impeded by statistical difficulties, while the theoretical understanding of the effects of epistasis remains limited, in turn limiting our ability to interpret data. Of particular interest is the biologically relevant situation of numerous interacting genetic loci with small individual contributions to fitness. Here, we present a computational model of selection dynamics involving many epistatic loci in a recombining population. We demonstrate that a large number of polymorphic interacting loci can, despite frequent recombination, exhibit cooperative behavior that locks alleles into favorable genotypes leading to a population consisting of a set of competing clones. When the recombination rate exceeds a certain critical value that depends on the strength of epistasis, this "genotype selection" regime disappears in an abrupt transition, giving way to "allele selection"-the regime where different loci are only weakly correlated as expected in sexually reproducing populations. We show that large populations attain highest fitness at a recombination rate just below critical. Clustering of interacting sets of genes on a chromosome leads to the emergence of an intermediate regime, where blocks of cooperating alleles lock into genetic modules. These haplotype blocks disappear in a second transition to pure allele selection. Our results demonstrate that the collective effect of many weak epistatic interactions can have dramatic effects on the population structure.Comment: Supplementary Material available on PNAS websit

Inferring HIV escape rates from multi-locus genotype data

Cytotoxic T-lymphocytes (CTLs) recognize viral protein fragments displayed by major histocompatibility complex (MHC) molecules on the surface of virally infected cells and generate an anti-viral response that can kill the infected cells. Virus variants whose protein fragments are not efficiently presented on infected cells or whose fragments are presented but not recognized by CTLs therefore have a competitive advantage and spread rapidly through the population. We present a method that allows a more robust estimation of these escape rates from serially sampled sequence data. The proposed method accounts for competition between multiple escapes by explicitly modeling the accumulation of escape mutations and the stochastic effects of rare multiple mutants. Applying our method to serially sampled HIV sequence data, we estimate rates of HIV escape that are substantially larger than those previously reported. The method can be extended to complex escapes that require compensatory mutations. We expect our method to be applicable in other contexts such as cancer evolution where time series data is also available

Coalescence, genetic diversity in sexual populations under selection

In sexual populations, selection operates neither on the whole genome, which is repeatedly taken apart and reassembled by recombination, nor on individual alleles that are tightly linked to the chromosomal neighborhood. The resulting interference between linked alleles reduces the efficiency of selection and distorts patterns of genetic diversity. Inference of evolutionary history from diversity shaped by linked selection requires an understanding of these patterns. Here, we present a simple but powerful scaling analysis identifying the unit of selection as the genomic "linkage block" with a characteristic length determined in a self-consistent manner by the condition that the rate of recombination within the block is comparable to the fitness differences between different alleles of the block. We find that an asexual model with the strength of selection tuned to that of the linkage block provides an excellent description of genetic diversity and the site frequency spectra when compared to computer simulations. This linkage block approximation is accurate for the entire spectrum of strength of selection and is particularly powerful in scenarios with many weakly selected loci. The latter limit allows us to characterize coalescence, genetic diversity, and the speed of adaptation in the infinitesimal model of quantitative genetics

Ecoenzymes as Indicators of Compost to Suppress Rhizoctonia solani

Reports of disease suppression by compost are inconsistent likely because there are no established standards for feedstock material, maturity age for application, and application rate. The overall goal of the study was to evaluate a suite of biological indicators for their ability to predict disease suppression. Indicators included both commercial available methods for compost stability (Solvita™, respiration) and metrics of soil ecology not yet adopted by the compost industry (e.g., ecoenzymes, nematode community index). Damping-off by Rhizoctonia solani on radish was chosen as a model system given its global importance, competitiveness affected by carbon quality, and lack of disease management options for organic production. Biological indicators were evaluated for their ability to consistently differentiate among curing process, maturity, and feedstock material as a function of disease severity of a seedling bioassay and a compost extract assay to test competition with R. solani growth. Compost processed as vermicompost and anaerobic digestate were more suppressive against R. solani than windrow or aerated static pile. Mature composts were more suppressive than immature components. Feedstocks containing dairy manure and/or hardwood bark tended to have suppressive qualities. In contrast, poultry manure-based components were conducive to disease. Microbial ecoenzymes active on chitin and cellulose and nematode community indices were better predictors of disease suppressiveness than microbial respiration. These indicators are quicker than plant bioassays and could be adopted as tools to certify commercial products