Recent developments in genetic data analysis: what can they tell us about human demographic history?

Beaumont, Mark A.

doi:10.1038/sj.hdy.6800447

Cited by 61 publications

(63 citation statements)

References 126 publications

(133 reference statements)

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“…TRUCTURE of populations and assigning individuals to populations have attracted considerable attention in population genetics, conservation biology, and ecology (Pritchard et al 2000;Beaumont 2004;Manel et al 2005;Platt et al 2010). Since the introduction of Wright's F ST (Wright 1921(Wright , 1943, numerous studies of population structure have been conducted for a multitude of species, using a variety of genetic or phenotypic markers.…”

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confidence: 99%

Combining Markers into Haplotypes Can Improve Population Structure Inference

Gattepaille

Jakobsson

2012

Genetics

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High-throughput genotyping and sequencing technologies can generate dense sets of genetic markers for large numbers of individuals. For most species, these data will contain many markers in linkage disequilibrium (LD). To utilize such data for population structure inference, we investigate the use of haplotypes constructed by combining the alleles at single-nucleotide polymorphisms (SNPs). We introduce a statistic derived from information theory, the gain of informativeness for assignment (GIA), which quantifies the additional information for assigning individuals to populations using haplotype data compared to using individual loci separately. Using a two-loci-two-allele model, we demonstrate that combining markers in linkage equilibrium into haplotypes always leads to nonpositive GIA, suggesting that combining the two markers is not advantageous for ancestry inference. However, for loci in LD, GIA is often positive, suggesting that assignment can be improved by combining markers into haplotypes. Using GIA as a criterion for combining markers into haplotypes, we demonstrate for simulated data a significant improvement of assigning individuals to candidate populations. For the many cases that we investigate, incorrect assignment was reduced between 26% and 97% using haplotype data. For empirical data from French and German individuals, the incorrectly assigned individuals can, for example, be decreased by 73% using haplotypes. Our results can be useful for challenging population structure and assignment problems, in particular for studies where large-scale population-genomic data are available. STRUCTURE of populations and assigning individuals to populations have attracted considerable attention in population genetics, conservation biology, and ecology (Pritchard et al. 2000;Beaumont 2004;Manel et al. 2005;Platt et al. 2010). Since the introduction of Wright's F ST (Wright 1921(Wright , 1943, numerous studies of population structure have been conducted for a multitude of species, using a variety of genetic or phenotypic markers. The recent development of high-throughput genotyping and sequencing technologies has resulted in a substantial increase in studies of population structure that are based on a large number of markers (e.g., Jakobsson et al. 2008;Platt et al. 2010;Vonholdt et al. 2010). At the same time, powerful clustering methods have been developed to infer population structure on the basis of multiloci genetic data (e.g., Pritchard et al. 2000;Dawson and Belkhir 2001;Corander et al. 2003;François et al. 2006;Huelsenbeck and Andolfatto 2007;Alexander et al. 2009).For most species, individuals rarely reproduce at random and this can create genetically differentiated subgroups within a population or species. Geographic barriers such as mountains, rivers, and oceans can furthermore hinder random mating, thereby causing populations to be structured (Hale et al. 2001;Rosenberg et al. 2005). In humans, cultural differences, such as language or religious beliefs, may play an additional role in shapin...

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confidence: 99%

Combining Markers into Haplotypes Can Improve Population Structure Inference

Gattepaille

Jakobsson

2012

Genetics

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“…Therefore, it is straightforward to include single-nucleotide polymorphisms [for instance, considering them as unique event polymorphisms where (Pritchard et al 1999)] methods. These are computationally intensive approaches but are changing the way population genetics analysis is currently done (Beaumont 2004;Beaumont and Rannala 2004). This applicability of state of the art statistics contrasts to the lack of simple summary statistics specific to linked microsatellites.…”

Section: Discussionmentioning

confidence: 99%

Characterization of Demographic Expansions From Pairwise Comparisons of Linked Microsatellite Haplotypes

2009

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This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.

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“…population genetics has traditionally proceeded through a moments approach, based on closed-form expressions for the expectation and variance of summary statistics (reviewed by Hey and Machado 2003;Beaumont 2004). For the purposes of this discussion, we regard as a summary statistic any measure of genetic variation that can be determined directly from numbers of derived mutations observed in a sample without explicit reference to the genealogy of the sampled genes.…”

Section: Stimation Of Population Parameters In Classicalmentioning

confidence: 99%

Likelihoods From Summary Statistics: Recent Divergence Between Species

Leman

Chen

Stajich³

et al. 2005

Genetics

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We describe an importance-sampling method for approximating likelihoods of population parameters based on multiple summary statistics. In this first application, we address the demographic history of closely related members of the Drosophila pseudoobscura group. We base the maximum-likelihood estimation of the time since speciation and the effective population sizes of the extant and ancestral populations on the pattern of nucleotide variation at DPS2002, a noncoding region tightly linked to a paracentric inversion that strongly contributes to reproductive isolation. Consideration of summary statistics rather than entire nucleotide sequences permits a compact description of the genealogy of the sample. We use importance sampling first to propose a genealogical and mutational history consistent with the observed array of summary statistics and then to correct the likelihood with the exact probability of the history determined from a system of recursions. Analysis of a subset of the data, for which recursive computation of the exact likelihood was feasible, indicated close agreement between the approximate and exact likelihoods. Our results for the complete data set also compare well with those obtained through Metropolis-Hastings sampling of fully resolved genealogies of entire nucleotide sequences.

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Recent developments in genetic data analysis: what can they tell us about human demographic history?

Cited by 61 publications

References 126 publications

Combining Markers into Haplotypes Can Improve Population Structure Inference

Combining Markers into Haplotypes Can Improve Population Structure Inference

Characterization of Demographic Expansions From Pairwise Comparisons of Linked Microsatellite Haplotypes

Likelihoods From Summary Statistics: Recent Divergence Between Species

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