Daniel Falush

Inference of population structure using multilocus genotype data: dominant markers and null alleles

Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html.

Inferring weak population structure with the assistance of sample group information.

Genetic clustering algorithms require a certain amount of data to produce informative results. In the common situation that individuals are sampled at several locations, we show how sample group information can be used to achieve better results when the amount of data is limited. New models are developed for the structure program, both for the cases of admixture and no admixture. These models work by modifying the prior distribution for each individuals population assignment. The new prior distributions allow the proportion of individuals assigned to a particular cluster to vary by location. The models are tested on simulated data, and illustrated using microsatellite data from the CEPH Human Genome Diversity Panel. We demonstrate that the new models allow structure to be detected at lower levels of divergence, or with less data, than the original structure models or principal components methods, and that they are not biased towards detecting structure when it is not present. These models are implemented in a new version of structure which is freely available online at http://pritch.bsd.uchicago.edu/structure.html.

A draft sequence of the Neandertal genome.

Kissing Cousins Neandertals, our closest relatives, ranged across Europe and Southwest Asia before their extinction approximately 30,000 years ago. Green et al. (p. 710) report a draft sequence of the Neandertal genome, created from three individuals, and compare it with genomes of five modern humans. The results suggest that ancient genomes of human relatives can be recovered with acceptably low contamination from modern human DNA. Because ancient DNA can be contaminated with microbial DNA, Burbano et al. (p. 723) developed a target sequence capture approach to obtain 14 kilobases of Neandertal DNA from a fairly poorly preserved sample with a high microbial load. A number of genomic regions and genes were revealed as candidates for positive selection early in modern human history. The genomic data suggest that Neandertals mixed with modern human ancestors some 120,000 years ago, leaving traces of Neandertal DNA in contemporary humans. Gene flow has occurred from Neandertals to humans of Eurasian descent, but not to Africans. Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.

Sex and virulence in Escherichia coli: an evolutionary perspective.

Pathogenic Escherichia coli cause over 160 million cases of dysentery and one million deaths per year, whereas non‐pathogenic E. coli constitute part of the normal intestinal flora of healthy mammals and birds. The evolutionary pathways underlying this dichotomy in bacterial lifestyle were investigated by multilocus sequence typing of a global collection of isolates. Specific pathogen types [enterohaemorrhagic E. coli, enteropathogenic E. coli, enteroinvasive E. coli, K1 and Shigella] have arisen independently and repeatedly in several lineages, whereas other lineages contain only few pathogens. Rates of evolution have accelerated in pathogenic lineages, culminating in highly virulent organisms whose genomic contents are altered frequently by increased rates of homologous recombination; thus, the evolution of virulence is linked to bacterial sex. This long‐term pattern of evolution was observed in genes distributed throughout the genome, and thereby is the likely result of episodic selection for strains that can escape the host immune response.

Composition, variability, and temporal stability of the intestinal microbiota of the elderly

Alterations in the human intestinal microbiota are linked to conditions including inflammatory bowel disease, irritable bowel syndrome, and obesity. The microbiota also undergoes substantial changes at the extremes of life, in infants and older people, the ramifications of which are still being explored. We applied pyrosequencing of over 40,000 16S rRNA gene V4 region amplicons per subject to characterize the fecal microbiota in 161 subjects aged 65 y and older and 9 younger control subjects. The microbiota of each individual subject constituted a unique profile that was separable from all others. In 68% of the individuals, the microbiota was dominated by phylum Bacteroides, with an average proportion of 57% across all 161 baseline samples. Phylum Firmicutes had an average proportion of 40%. The proportions of some phyla and genera associated with disease or health also varied dramatically, including Proteobacteria, Actinobacteria, and Faecalibacteria. The core microbiota of elderly subjects was distinct from that previously established for younger adults, with a greater proportion of Bacteroides spp. and distinct abundance patterns of Clostridium groups. Analyses of 26 fecal microbiota datasets from 3-month follow-up samples indicated that in 85% of the subjects, the microbiota composition was more like the corresponding time-0 sample than any other dataset. We conclude that the fecal microbiota of the elderly shows temporal stability over limited time in the majority of subjects but is characterized by unusual phylum proportions and extreme variability.

An African origin for the intimate association between humans and Helicobacter pylori

Infection of the stomach by Helicobacter pylori is ubiquitous among humans. However, although H. pylori strains from different geographic areas are associated with clear phylogeographic differentiation, the age of an association between these bacteria with humans remains highly controversial. Here we show, using sequences from a large data set of bacterial strains that, as in humans, genetic diversity in H. pylori decreases with geographic distance from east Africa, the cradle of modern humans. We also observe similar clines of genetic isolation by distance (IBD) for both H. pylori and its human host at a worldwide scale. Like humans, simulations indicate that H. pylori seems to have spread from east Africa around 58,000 yr ago. Even at more restricted geographic scales, where IBD tends to become blurred, principal component clines in H. pylori from Europe strongly resemble the classical clines for Europeans described by Cavalli-Sforza and colleagues. Taken together, our results establish that anatomically modern humans were already infected by H. pylori before their migrations from Africa and demonstrate that H. pylori has remained intimately associated with their human host populations ever since.

Inference of Bacterial Microevolution Using Multilocus Sequence Data

We describe a model-based method for using multilocus sequence data to infer the clonal relationships of bacteria and the chromosomal position of homologous recombination events that disrupt a clonal pattern of inheritance. The key assumption of our model is that recombination events introduce a constant rate of substitutions to a contiguous region of sequence. The method is applicable both to multilocus sequence typing (MLST) data from a few loci and to alignments of multiple bacterial genomes. It can be used to decide whether a subset of isolates share common ancestry, to estimate the age of the common ancestor, and hence to address a variety of epidemiological and ecological questions that hinge on the pattern of bacterial spread. It should also be useful in associating particular genetic events with the changes in phenotype that they cause. We show that the model outperforms existing methods of subdividing recombinogenic bacteria using MLST data and provide examples from Salmonella and Bacillus. The software used in this article, ClonalFrame, is available from http://bacteria.stats.ox.ac.uk/.

A new model for prediction of the age of onset and penetrance for Huntington's disease based on CAG length.

Huntingtons disease (HD) is a neurodegenerative disorder caused by an unstable CAG repeat. For patients at risk, participating in predictive testing and learning of having CAG expansion, a major unanswered question shifts from “Will I get HD?” to “When will it manifest?” Using the largest cohort of HD patients analyzed to date (2913 individuals from 40 centers worldwide), we developed a parametric survival model based on CAG repeat length to predict the probability of neurological disease onset (based on motor neurological symptoms rather than psychiatric onset) at different ages for individual patients. We provide estimated probabilities of onset associated with CAG repeats between 36 and 56 for individuals of any age with narrow confidence intervals. For example, our model predicts a 91% chance that a 40‐year‐old individual with 42 repeats will have onset by the age of 65, with a 95% confidence interval from 90 to 93%. This model also defines the variability in HD onset that is not attributable to CAG length and provides information concerning CAG‐related penetrance rates.

Recombination and mutation during long-term gastric colonization by Helicobacter pylori: Estimates of clock rates, recombination size, and minimal age

The bacterium Helicobacter pylori colonizes the gastric mucosa of half of the human population, resulting in chronic gastritis, ulcers, and cancer. We sequenced ten gene fragments from pairs of strains isolated sequentially at a mean interval of 1.8 years from 26 individuals. Several isolates had acquired small mosaic segments from other H. pylori or point mutations. The maximal mutation rate, the import size, and the frequency of recombination were calculated by using a Bayesian model. The calculations indicate that the last common ancestor of H. pylori existed at least 2,500–11,000 years ago. Imported mosaics have a median size of 417 bp, much smaller than for other bacteria, and recombination occurs frequently (60 imports spanning 25,000 bp per genome per year). Thus, the panmictic population structure of H. pylori results from very frequent recombination during mixed colonization by unrelated strains.

Roary: rapid large-scale prokaryote pan genome analysis

Summary: A typical prokaryote population sequencing study can now consist of hundreds or thousands of isolates. Interrogating these datasets can provide detailed insights into the genetic structure of prokaryotic genomes. We introduce Roary, a tool that rapidly builds large-scale pan genomes, identifying the core and accessory genes. Roary makes construction of the pan genome of thousands of prokaryote samples possible on a standard desktop without compromising on the accuracy of results. Using a single CPU Roary can produce a pan genome consisting of 1000 isolates in 4.5 hours using 13 GB of RAM, with further speedups possible using multiple processors. Availability and implementation: Roary is implemented in Perl and is freely available under an open source GPLv3 license from http://sanger-pathogens.github.io/Roary Contact: roary@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.