Dataset Information

Measuring the Temporal Structure in Serially-Sampled Phylogenies.

ABSTRACT: Nucleotide sequences sampled at different times (serially-sampled sequences) allow researchers to study the rate of evolutionary change and the demographic history of populations. Some phylogenies inferred from serially-sampled sequences are described as having strong 'temporal clustering', such that sequences from the same sampling time tend to to cluster together and to be the direct ancestors of sequences from the following sampling time. The degree to which phylogenies exhibit these properties is thought to reflect interesting biological processes, such as positive selection or deviation from the molecular clock hypothesis.Here we introduce the Temporal Clustering (TC) statistic, which is the first quantitative measure of the degree of topological 'temporal clustering' in a serially-sampled phylogeny. The TC statistic represents the expected deviation of an observed phylogeny from the null hypothesis of no temporal clustering, as a proportion of the range of possible values, and can therefore be compared among phylogeny of different sizes.We apply the TC statistic to a range of serially-sampled sequence datasets, which represent both rapidly-evolving viruses and ancient mitochondrial DNA. In addition, the TC statistic was calculated for phylogenies simulated under a neutral coalescent process.Our results indicate significant temporal clustering in many empirical datasets. However, we also find that such clustering is exhibited by trees simulated under a neutral coalescent process; hence the observation of significant 'temporal clustering' cannot unambiguously indicate that presence of strong positive selection in a population.Quantifying topological structure in this manner will provide new insights into the evolution of measurably evolving populations.

SUBMITTER: Gray RR

PROVIDER: S-EPMC3222587 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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Measuring the Temporal Structure in Serially-Sampled Phylogenies.

Gray R R RR Pybus O G OG Salemi M M

Methods in ecology and evolution 20111001 5

Nucleotide sequences sampled at different times (serially-sampled sequences) allow researchers to study the rate of evolutionary change and the demographic history of populations. Some phylogenies inferred from serially-sampled sequences are described as having strong 'temporal clustering', such that sequences from the same sampling time tend to to cluster together and to be the direct ancestors of sequences from the following sampling time. The degree to which phylogenies exhibit these properti ...[more]

PMID: 22121470

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Project description:Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.].

Dataset Information

Measuring the Temporal Structure in Serially-Sampled Phylogenies.

Publications

Measuring the Temporal Structure in Serially-Sampled Phylogenies.

Similar Datasets

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