Ancestral Inference from Samples of DNA Sequences with Recombination

Griffiths, R. C.; Marjoram, Paul

doi:10.1089/cmb.1996.3.479

Cited by 376 publications

(311 citation statements)

References 19 publications

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“…The simulation generates the ancestral recombination graph (Griffiths and Marjoram 1996) for one or more chromosome regions linked to the SDR. That graph is then used to determine the coalescence time at the site(s) of interest.…”

Section: Modelsmentioning

confidence: 99%

Patterns of Neutral Genetic Variation on Recombining Sex Chromosomes

2010

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Many animals and plants have sex chromosomes that recombine over much of their length. Here we develop coalescent models for neutral sites on these chromosomes. The emphasis is on expected coalescence times (proportional to the expected amount of neutral genetic polymorphism), but we also derive some results for linkage disequilibria between neutral sites. We analyze the standard neutral model, a model with polymorphic Y chromosomes under balancing selection, and the invasion of a neo-Y chromosome. The results may be useful for testing hypotheses regarding how new sex chromosomes originate and how selection acts upon them.

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Section: Modelsmentioning

confidence: 99%

Patterns of Neutral Genetic Variation on Recombining Sex Chromosomes

2010

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“…Some statistical approaches have attempted to incorporate haplotype structure directly into association tests for this purpose [14,21,15,12]. An alternative strategy is to characterize the haplotype structure in a recombining population independently of its application to a particular association test, a strategy that has been pursued from many directions [11,7,26,27,25,28,3,20,23].…”

Section: Introductionmentioning

confidence: 99%

Inferring Piecewise Ancestral History from Haploid Sequences

Schwartz¹

2004

Computational Methods for SNPs and Haplotype Inference

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Abstract. There has been considerable recent interest in the use of haplotype structure to aid in the design and analysis of case-control association studies searching for genetic predictors of human disease. The use of haplotype structure is based on the premise that genetic variations that are physically close on the genome will often be predictive of one another due to their frequent descent intact through recent evolution. Understanding these correlations between sites should make it possible to minimize the amount of redundant information gathered through assays or examined in association tests, improving the power and reducing the cost of the studies. In this work, we evaluate the potential value of haplotype structure in this context by applying it to two key subproblems: inferring hidden polymorphic sites in partial haploid sequences and choosing subsets of variants that optimally capture the information content of the full set of sequences. We develop methods for these approaches based on a prior method we developed for predicting piece-wise shared ancestry of haploid sequences. We apply these methods to a case study of two genetic regions with very different levels of sequence diversity. We conclude that haplotype correlations do have considerable potential for these problems, but that the degree to which they are useful will be strongly dependent on the population sizes available and the specifics of the genetic regions examined.

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“…7 and 8) has confirmed the presence of recombination hotspots. Although more recent population genetic modeling efforts (9)(10)(11) have included recombination hotspots, these methods, like their predecessors (12)(13)(14)(15)(16), assume that the recombination rate is (i) homogeneous across the population, and (ii) constant throughout time. However, sperm typing has also demonstrated that some hotspots are heterogeneous in the population (17).…”

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A population genetics model with recombination hotspots that are heterogeneous across the population

Calabrese

2007

Proc. Natl. Acad. Sci. U.S.A.

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Both sperm typing and linkage disequilibrium patterns from large population genetic data sets have demonstrated that recombination hotspots are responsible for much of the recombination activity in the human genome. Sperm typing has also revealed that some hotspots are heterogeneous in the population; and linkage disequilibrium patterns from the chimpanzee have implied that hotspots change at least on the separation time between these species. We propose a population genetics model, inspired by the double-strand break model, which features recombination hotspots that are heterogeneous across the population and whose population frequency changes with time. We have derived a diffusion approximation and written a coalescent simulation program. This model has implications for the ''hotspot paradox.'' A nalysis of the Seattle SNP, Perlegen, and HapMap data sets has suggested that the fine-scale recombination rate varies with position across the chromosome (1-3). Indeed 80% of the recombination activity is believed to occur in as little as 10-20% of the sequence. So-called recombination hotspots, narrow regions generally 1 kb wide with elevated recombination rates, have been estimated approximately every 100 kb across the human genome. Sperm typing (4-6) (for reviews, see refs. 7 and 8) has confirmed the presence of recombination hotspots. Although more recent population genetic modeling efforts (9-11) have included recombination hotspots, these methods, like their predecessors (12-16), assume that the recombination rate is (i) homogeneous across the population, and (ii) constant throughout time. However, sperm typing has also demonstrated that some hotspots are heterogeneous in the population (17). Moreover, analysis of linkage disequilibrium patterns in the human and chimpanzee populations (18,19) has shown little congruence between the location of hotspots in the two species, implying that recombination rates change at least on the order of the separation time between these species.The predominant mechanistic model of recombination is the double-strand break model illustrated in Fig. 1 (20) (for a review see ref. 21). In this model, there is a break through both strands of one of the chromosomes. On this chromosome there is a loss of several hundred base pairs around the break. This loss is then replaced by copying from the other chromosome. The break can be resolved as either a crossover or a conversion event. In most population genetic models, this loss and copy of DNA has been ignored: in these models there is an exchange of DNA between chromosomes, but, despite this rearrangement, all sections of the chromosome are assumed to retain their original quantities. Because the length of this loss is relatively small, this simplification had seemed benign.However, this loss is the key factor in the ''hotspot paradox'' (e.g., refs. 22 and 23). This paradox states that if the hotspot is caused by some motif in the DNA sequence that elevates the local double-strand break rate, then this motif will often be lost in a reco...

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Ancestral Inference from Samples of DNA Sequences with Recombination

Cited by 376 publications

References 19 publications

Patterns of Neutral Genetic Variation on Recombining Sex Chromosomes

Patterns of Neutral Genetic Variation on Recombining Sex Chromosomes

Inferring Piecewise Ancestral History from Haploid Sequences

A population genetics model with recombination hotspots that are heterogeneous across the population

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