A Hidden Markov Model for Investigating Recent Positive Selection through Haplotype Structure

A Hidden Markov Model for Investigating Recent Positive Selection through Haplotype Structure

Hua Chen, Jody Hey, Montgomery Slatkin
doi: http://dx.doi.org/10.1101/011247

Recent positive selection can increase the frequency of an advantageous mutant rapidly enough that a relatively long ancestral haplotype will be remained intact around it. We present a hidden Markov model (HMM) to identify such haplotype structures. With HMM identified haplotype structures, a population genetic model for the extent of ancestral haplotypes is then adopted for parameter inference of the selection intensity and the allele age. Simulations show that this method can detect selection under a wide range of conditions and has higher power than the existing frequency spectrum-based method. In addition, it provides good estimate of the selection coefficients and allele ages for strong selection. The method analyzes large data sets in a reasonable amount of running time. This method is applied to HapMap III data for a genome scan, and identifies a list of candidate regions putatively under recent positive selection. It is also applied to several genes known to be under recent positive selection, including the LCT, KITLG and TYRP1 genes in Northern Europeans, and OCA2 in East Asians, to estimate their allele ages and selection coefficients.

Estimating the Relative Rate of Recombination to Mutation in Bacteria from Single-Locus Variants using Composite Likelihood Methods

Estimating the Relative Rate of Recombination to Mutation in Bacteria from Single-Locus Variants using Composite Likelihood Methods

Paul Fearnhead, Shoukai Yu, Patrick Biggs, Barbara Holland, Nigel French
(Submitted on 5 Nov 2014)

A number of studies have suggested using comparisons between DNA sequences of closely related bacterial isolates to estimate the relative rate of recombination to mutation for that bacterial species. We consider such an approach which uses single locus variants: pairs of isolates whose DNA differ at a single gene locus. One way of deriving point estimates for the relative rate of recombination to mutation from such data is to use composite likelihood methods. We extend recent work in this area so as to be able to construct confidence intervals for our estimates, without needing to resort to computationally-intensive bootstrap procedures, and to develop a test for whether the relative rate varies across loci. Both our test and method for constructing confidence intervals are obtained by modelling the dependence structure in the data, and then applying asymptotic theory regarding the distribution of estimators obtained using a composite likelihood. We applied these methods to multi-locus sequence typing (MLST) data from eight bacteria, finding strong evidence for considerable rate variation in three of these: Bacillus cereus, Enterococcus faecium and Klebsiella pneumoniae.

Conflations of short IBD blocks can bias inferred length of IBD

Conflations of short IBD blocks can bias inferred length of IBD
Charleston W.K. Chiang, Peter Ralph, John Novembre
Comments: 12 figures, 1 table
Subjects: Populations and Evolution (q-bio.PE)

Identity-by-descent (IBD) is a fundamental concept in genetics with many applications. Often, segments between two haplotypes are said to be IBD if they are inherited from a recent shared common ancestor without intervening recombination. Long IBD blocks (> 1cM) can be efficiently detected by a number of computer programs using high-density SNP array data from a population sample. However, all programs detect IBD based on contiguous segments of identity-by-state, and can therefore be due to the conflation of smaller, nearby IBD blocks. We quantified this effect using coalescent simulations, finding that nearly 40% of inferred blocks 1-2cM long are false conflations of two or more longer blocks, under demographic scenarios typical for modern humans. This biases the inferred IBD block length distribution, and so can affect downstream inferences. We observed this conflation effect universally across different IBD detection programs and human demographic histories, and found inference of segments longer than 2cM to be much more reliable (less than 5% conflation rate). We then present and analyze a novel estimator of the de novo mutation rate using IBD blocks, and demonstrate that the biased length distribution of the IBD segments due to conflation can strongly affect this estimator if the conflation is not modeled. Thus, the conflation effect should be carefully considered, especially as methods to detect shorter IBD blocks using sequencing data are being developed.

Ancestry Composition: A Novel, Efficient Pipeline for Ancestry Deconvolution

Ancestry Composition: A Novel, Efficient Pipeline for Ancestry Deconvolution
Eric Y Durand, Chuong B Do, Joanna L Mountain, J. Michael Macpherson
doi: http://dx.doi.org/10.1101/010512

Ancestry deconvolution, the task of identifying the ancestral origin of chromosomal segments in admixed individuals, has important implications, from mapping disease genes to identifying candidate loci under natural selection. To date, however, most existing methods for ancestry deconvolution are typically limited to two or three ancestral populations, and cannot resolve contributions from populations related at a sub-continental scale. We describe Ancestry Composition, a modular three-stage pipeline that efficiently and accurately identifies the ancestral origin of chromosomal segments in admixed individuals. It assumes the genotype data have been phased. In the first stage, a support vector machine classifier assigns tentative ancestry labels to short local phased genomic regions. In the second stage, an autoregressive pair hidden Markov model simultaneously corrects phasing errors and produces reconciled local ancestry estimates and confidence scores based on the tentative ancestry labels. In the third stage, confidence estimates are recalibrated using isotonic regression. We compiled a reference panel of almost 10,000 individuals of homogeneous ancestry, derived from a combination of several publicly available datasets and over 8,000 individuals reporting four grandparents with the same country-of-origin from the member database of the personal genetics company, 23andMe, Inc., and excluding outliers identified through principal components analysis (PCA). In cross-validation experiments, Ancestry Composition achieves high precision and recall for labeling chromosomal segments across over 25 different populations worldwide.

STACEY: species delimitation and phylogeny estimation under the multispecies coalescent

STACEY: species delimitation and phylogeny estimation under the multispecies coalescent
Graham R Jones
doi: http://dx.doi.org/10.1101/010199

This article describes a new package called STACEY for BEAST2 which is capable of both species delimitation and species tree estimation using DNA sequences from multiple loci. The focus in this article is on species delimitation. STACEY is based on the multispecies coalescent model, and builds on earlier software (DISSECT), which uses a `birth-death-collapse’ prior to deal with delimitations without the need for reversible-jump Markov chain Monte Carlo moves. Like DISSECT, it requires no a priori assignment of individuals to species or populations, and no guide tree. This paper introduces two innovations. The first is a new model for the populations along the branches of the species tree, and the second is a new MCMC move for exploring the posterior when the multispecies coalescent model is assumed. The main benefit of STACEY over DISSECT is much better convergence. Current practice, using a pipeline approach to species delimitation under the multispecies coalescent, has been shown to have major problems on simulated data. The same simulated data set is used to demonstrate the accuracy and efficiency of STACEY.

Synonymous and Nonsynonymous Distances Help Untangle Convergent Evolution and Recombination

Synonymous and Nonsynonymous Distances Help Untangle Convergent Evolution and Recombination

Peter B. Chi, Sujay Chattopadhyay, Philippe Lemey, Evgeni V. Sokurenko, Vladimir N. Minin
(Submitted on 6 Oct 2014)

When estimating a phylogeny from a multiple sequence alignment, researchers often assume the absence of recombination. However, if recombination is present, then tree estimation and all downstream analyses will be impacted, because different segments of the sequence alignment support different phylogenies. Similarly, convergent selective pressures at the molecular level can also lead to phylogenetic tree incongruence across the sequence alignment. Current methods for detection of phylogenetic incongruence are not equipped to distinguish between these two different mechanisms and assume that the incongruence is a result of recombination or other horizontal transfer of genetic information. We propose a new recombination detection method that can make this distinction, based on synonymous codon substitution distances. Although some power is lost by discarding the information contained in the nonsynonymous substitutions, our new method has lower false positive probabilities than the original Dss statistic when the phylogenetic incongruence signal is due to convergent evolution. We conclude with three empirical examples, where we analyze: 1) sequences from a transmission network of the human immunodeficiency virus, 2) tlpB gene sequences from a geographically diverse set of 38 Helicobacter pylori strains, and 3) Hepatitis C virus sequences sampled longitudinally from one patient.

Inference of evolutionary forces acting on human biological pathways

Inference of evolutionary forces acting on human biological pathways

Josephine T Daub, Isabelle Dupanloup, Marc Robinson-Rechavi, Laurent Excoffier
doi: http://dx.doi.org/10.1101/009928

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects as well as evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their 2D null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection, but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of non-synonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.