Rapid forward-in-time simulation at the chromosome and genome level

Background: In population genetics, simulation is a fundamental tool for analyzing how basic evolutionary forces such as natural selection, recombination, and mutation shape the genetic landscape of a population. Forward simulation represents the most powerful, but, at the same time, most compute-intensive approach for simulating the genetic material of a population. Results: We introduce AnA-FiTS, a highly optimized forward simulation software, that is up to two orders of magnitude faster than current state-of-the-art software. In addition, we present a novel algorithm that further improves runtimes by up to an additional order of magnitude, for simulations where a fraction of the mutations is neutral (e.g., only 10% of mutations have an effect on fitness). Apart from simulated sequences, our tool also generates a graph structure that depicts the complete observable history of neutral mutations. Conclusions: The substantial performance improvements allow for conducting forward simulations at the chromosome and genome level. The graph structure generated by our algorithm can give rise to novel approaches for visualizing and analyzing the output of forward simulations

XSim: Simulation of Descendants from Ancestors with Sequence Data.

Real or imputed high-density SNP genotypes are routinely used for genomic prediction and genome-wide association studies. Many researchers are moving toward the use of actual or imputed next-generation sequence data in whole-genome analyses. Simulation studies are useful to mimic complex scenarios and test different analytical methods. We have developed the software tool XSim to efficiently simulate sequence data in descendants in arbitrary pedigrees. In this software, a strategy to drop-down origins and positions of chromosomal segments rather than every allele state is implemented to simulate sequence data and to accommodate complicated pedigree structures across multiple generations. Both C++ and Julia versions of XSim have been developed

Human-chimpanzee alignment: Ortholog Exponentials and Paralog Power Laws

Genomic subsequences conserved between closely related species such as human and chimpanzee exhibit an exponential length distribution, in contrast to the algebraic length distribution observed for sequences shared between distantly related genomes. We find that the former exponential can be further decomposed into an exponential component primarily composed of orthologous sequences, and a truncated algebraic component primarily composed of paralogous sequences.Comment: Main text: 31 pages, 13 figures, 1 table; Supplementary materials: 9 pages, 9 figures, 1 tabl

Natural selection reduced diversity on human Y chromosomes

The human Y chromosome exhibits surprisingly low levels of genetic diversity. This could result from neutral processes if the effective population size of males is reduced relative to females due to a higher variance in the number of offspring from males than from females. Alternatively, selection acting on new mutations, and affecting linked neutral sites, could reduce variability on the Y chromosome. Here, using genome-wide analyses of X, Y, autosomal and mitochondrial DNA, in combination with extensive population genetic simulations, we show that low observed Y chromosome variability is not consistent with a purely neutral model. Instead, we show that models of purifying selection are consistent with observed Y diversity. Further, the number of sites estimated to be under purifying selection greatly exceeds the number of Y-linked coding sites, suggesting the importance of the highly repetitive ampliconic regions. While we show that purifying selection removing deleterious mutations can explain the low diversity on the Y chromosome, we cannot exclude the possibility that positive selection acting on beneficial mutations could have also reduced diversity in linked neutral regions, and may have contributed to lowering human Y chromosome diversity. Because the functional significance of the ampliconic regions is poorly understood, our findings should motivate future research in this area.Comment: 43 pages, 11 figure

forqs: Forward-in-time Simulation of Recombination, Quantitative Traits, and Selection

forqs is a forward-in-time simulation of recombination, quantitative traits, and selection. It was designed to investigate haplotype patterns resulting from scenarios where substantial evolutionary change has taken place in a small number of generations due to recombination and/or selection on polygenic quantitative traits. forqs is implemented as a command- line C++ program. Source code and binary executables for Linux, OSX, and Windows are freely available under a permissive BSD license.Comment: preprint include Supplementary Information. https://bitbucket.org/dkessner/forq

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