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Methods for Estimating Demography and Detecting Between-Locus Differences in the Effective Population Size and Mutation Rate.

ABSTRACT: It is known that the effective population size (Ne) and the mutation rate (u) vary across the genome. Here, we show that ignoring this heterogeneity may lead to biased estimates of past demography. To solve the problem, we develop new methods for jointly inferring past changes in population size and detecting variation in Ne and u between loci. These methods rely on either polymorphism data alone or both polymorphism and divergence data. In addition to inferring demography, we can use the methods to study a variety of questions: 1) comparing sex chromosomes with autosomes (for finding evidence for male-driven evolution, an unequal sex ratio, or sex-biased demographic changes) and 2) analyzing multilocus data from within autosomes or sex chromosomes (for studying determinants of variability in Ne and u). Simulations suggest that the methods can provide accurate parameter estimates and have substantial statistical power for detecting difference in Ne and u. As an example, we use the methods to analyze a polymorphism data set from Drosophila simulans. We find clear evidence for rapid population expansion. The results also indicate that the autosomes have a higher mutation rate than the X chromosome and that the sex ratio is probably female-biased. The new methods have been implemented in a user-friendly package.

SUBMITTER: Zeng K

PROVIDER: S-EPMC6409433 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Methods for Estimating Demography and Detecting Between-Locus Differences in the Effective Population Size and Mutation Rate.

Zeng Kai K Jackson Benjamin C BC Barton Henry J HJ

Molecular biology and evolution 20190201 2

It is known that the effective population size (Ne) and the mutation rate (u) vary across the genome. Here, we show that ignoring this heterogeneity may lead to biased estimates of past demography. To solve the problem, we develop new methods for jointly inferring past changes in population size and detecting variation in Ne and u between loci. These methods rely on either polymorphism data alone or both polymorphism and divergence data. In addition to inferring demography, we can use the method ...[more]

PMID: 30428070

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Project description:The One Health paradigm recognizes that information on infectious diseases, zoonosis and related predictors in animal populations is essential. Pets live in close contact with humans and interact with wild animals, but the lack of reliable information on pet population size, demography and ownership profiles is a constant worldwide. Reliable data must be made available in order to address proper public health policies regarding the design of surveillance plans, the management of canine welfare and stray dog phenomenon, the control of dog behaviour-related problems, and the livestock/wildlife endangerment. Dog identification & registration (I&R) have become mandatory in most European countries in recent years, but the process is far from being widely accomplished, thus resulting in an underestimation of the real canine population. To date, data on the completeness of Dog Registries is very limited. A cross-sectional survey through 630 face-to-face questionnaires was performed with the aim of investigating the dog population size, demography, ownership profiles, and the I&R rate in central Italy. Logistic regression models investigated risk factors with the following outcome variables: dog presence into the Dog Registry, veterinary care frequency, and dog ownership. The present study identified that the dog population is higher than previously reported in Italy and in Europe, whilst lower compared to countries with a poor Human Development Index (a statistic composite index of life expectancy, education, and per capita income indicators used by United Nation). Almost half of the interviewed people (47%) owned at least one dog, totalling 315 dogs. The mean number of dogs per household was 0.7 and 1.5 per dog-owning household. The Bayesian model estimated 481,294 (95% CI: 470,860-491,978) dogs (90 dogs/km2; human:dog ratio 9.0, 95% CI: 8.8-9.2) suggesting that a high density of people does not limit the dog ownership. Dogs resulted predominant among pets. The majority of dogs were males, crossbred, acquires as a gift, lived in rural areas, outdoors and attended a veterinary visit 1-2 times per year. The percentage of neutered dogs were higher in females (55%) than in males (8%). Only 75.3% (95% CI: 73.6-76.9) of the dogs were correctly identified and registered. The Dog Registry completeness increased during the first decades after its establishment, but no improvement has been made afterwards. The dogs correctly identified and registered were more likely to be purebred, neutered, lived in urban areas and visited a veterinarian frequently. Several strategies are recommended to encourage I&R, including promoting responsible dog ownership, engaging private veterinarians and dog breeders, and establishing an effective control system. The present study identified also that the dog source and the kind of feeding were variables associated with the veterinary care frequency. Owning a dog was associated with living in rural areas and the presence of children. The present study reported the poor presence of reliable predictors for the dog ownership. This is the first study to provide an estimate of the canine population abundance, characteristics, and ownership profiles in a European large metropolitan area.

Dataset Information

Methods for Estimating Demography and Detecting Between-Locus Differences in the Effective Population Size and Mutation Rate.

Publications

Methods for Estimating Demography and Detecting Between-Locus Differences in the Effective Population Size and Mutation Rate.

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