Biomedical subjects

Vincent Plagnol

Publications and source records attributed to Vincent Plagnol.

4 recordsLinked to original sources

PubMed2006

Possible ancestral structure in human populations.

Determining the evolutionary relationships between fossil hominid groups such as Neanderthals and modern humans has been a question of enduring interest in human evolutionary genetics. Here we present a new method for addressing whether archaic human groups contributed to the modern gene pool (called ancient admixture), using the patterns of variation in contemporary human populations. Our method improves on previous work by explicitly accounting for recent population history before performing the analyses. Using sequence data from the Environmental Genome Project, we find strong evidence for ancient admixture in both a European and a West African population (p approximately 10(-7)), with contributions to the modern gene pool of at least 5%. While Neanderthals form an obvious archaic source population candidate in Europe, there is not yet a clear source population candidate in West Africa.

Animals↗

PubMed2005

Relative influences of crossing over and gene conversion on the pattern of linkage disequilibrium in Arabidopsis thaliana.

In this article we infer the rates of gene conversion and crossing over in Arabidopsis thaliana from population genetic data. Our data set is a genomewide survey consisting of 1347 fragments of length 600 bp sequenced in 96 accessions. It has several orders of magnitude more markers than any previous nonhuman study. This allows for more accurate inference as well as a detailed comparison between theoretical expectations and observations. Our methodology is specifically set to account for deviations such as recurrent mutations or a skewed frequency spectrum. We found that even if some components of the model clearly do not fit, the pattern of LD conforms to theoretical expectations quite well. The ratio of gene conversion to crossing over is estimated to be around one. We also find evidence for fine-scale variations of the crossing-over rate.

Arabidopsis↗

PubMed2005

The pattern of polymorphism in Arabidopsis thaliana.

We resequenced 876 short fragments in a sample of 96 individuals of Arabidopsis thaliana that included stock center accessions as well as a hierarchical sample from natural populations. Although A. thaliana is a selfing weed, the pattern of polymorphism in general agrees with what is expected for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb. Variation is shared worldwide, although population structure and isolation by distance are evident. The data fail to fit standard neutral models in several ways. There is a genome-wide excess of rare alleles, at least partially due to selection. There is too much variation between genomic regions in the level of polymorphism. The local level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. Because the data do not fit theoretical null distributions, attempts to infer natural selection from polymorphism data will require genome-wide surveys of polymorphism in order to identify anomalous regions. Despite this, our data support the utility of A. thaliana as a model for evolutionary functional genomics.

Arabidopsis↗

PubMed2003

Markov chain Monte Carlo without likelihoods.

Many stochastic simulation approaches for generating observations from a posterior distribution depend on knowing a likelihood function. However, for many complex probability models, such likelihoods are either impossible or computationally prohibitive to obtain. Here we present a Markov chain Monte Carlo method for generating observations from a posterior distribution without the use of likelihoods. It can also be used in frequentist applications, in particular for maximum-likelihood estimation. The approach is illustrated by an example of ancestral inference in population genetics. A number of open problems are highlighted in the discussion.

Algorithms↗