Genome-Wide Estimates of Coancestry and Inbreeding in a Closed Herd of Ancient Iberian Pigs

Maintaining genetic variation and controlling the increase in inbreeding are crucial requirements in animal conservation programs. The most widely accepted strategy for achieving these objectives is to maximize the effective population size by minimizing the global coancestry obtained from a particular pedigree. However, for most natural or captive populations genealogical information is absent. In this situation, microsatellites have been traditionally the markers of choice to characterize genetic variation, and several estimators of genealogical coefficients have been developed using marker data, with unsatisfactory results. The development of high-throughput genotyping techniques states the necessity of reviewing the paradigm that genealogical coancestry is the best parameter for measuring genetic diversity. In this study, the Illumina PorcineSNP60 BeadChip was used to obtain genome-wide estimates of rates of coancestry and inbreeding and effective population size for an ancient strain of Iberian pigs that is now in serious danger of extinction and for which very accurate genealogical information is available (the Guadyerbas strain). Genome-wide estimates were compared with those obtained from microsatellite and from pedigree data. Estimates of coancestry and inbreeding computed from the SNP chip were strongly correlated with genealogical estimates and these correlations were substantially higher than those between microsatellite and genealogical coefficients. Also, molecular coancestry computed from SNP information was a better predictor of genealogical coancestry than coancestry computed from microsatellites. Rates of change in coancestry and inbreeding and effective population size estimated from molecular data were very similar to those estimated from genealogical data. However, estimates of effective population size obtained from changes in coancestry or inbreeding differed. Our results indicate that genome-wide information represents a useful alternative to genealogical information for measuring and maintaining genetic diversity.     

Analysis of genealogical structure of populations. I. A method of collecting genealogical data in numerical form

A method for collecting genealogical data with respect to an individual, a family, and members of the whole population is suggested. The essence of vertical pedigree construction consists of the same type of steps for filling in data (in the fixed order which excludes skips in the enumeration of lines of descent) about the father and the mother of the next ancestor. Each number in the received ordered list of ancestors uniquely determines a path (line of descent) to the given pedigree member. The path is explicitly described by a sequence of digits 0 and 1 (that corresponds to the sequence of fathers and mothers in the line of descent) at binary notation of this number. As a result, a pedigree is presented as a set of numbered rows that contain information, which uniquely identifies direct ancestors as individual persons. Results of joining separate pedigrees are recorded as a family list that contains lists of children for each parental pair. A pair of parents (more exactly, pointers of their families in the previous generation and numbers of pair members in their families) plays the role of the family "heading." Such a family list permits one to trace lines of descent and relationships for any population members presented in the list. It contains all genealogical information within the bounds of the study in a compact form. Here the process of collection requires considerably less time than traditional graphic representation of pedigrees. In addition, due to repeated checks of data during accumulation of material, error is minimized. Using pedigrees that have been collected, it is possible to calculate the coefficient of inbreeding manually. In connection with the wide prevalence of personal computers at present, it is also important that the data received are in fact ready to direct input to a computer for further automated data processing.     

Genomic and genealogical investigation of the French Canadian founder population structure

Characterizing the genetic structure of worldwide populations is important for understanding human history and is essential to the design and analysis of genetic epidemiological studies. In this study, we examined genetic structure and distant relatedness and their effect on the extent of linkage disequilibrium (LD) and homozygosity in the founder population of Quebec (Canada). In the French Canadian founder population, such analysis can be performed using both genomic and genealogical data. We investigated genetic differences, extent of LD, and homozygosity in 140 individuals from seven sub-populations of Quebec characterized by different demographic histories reflecting complex founder events. Genetic findings from genome-wide single nucleotide polymorphism data were correlated with genealogical information on each of these sub-populations. Our genomic data showed significant population structure and relatedness present in the contemporary Quebec population, also reflected in LD and homozygosity levels. Our extended genealogical data corroborated these findings and indicated that this structure is consistent with the settlement patterns involving several founder events. This provides an independent and complementary validation of genomic-based studies of population structure. Combined genomic and genealogical data in the Quebec founder population provide insights into the effects of the interplay of two important sources of bias in genetic epidemiological studies, unrecognized genetic structure and cryptic relatedness.     

Efficient genetic markers for population biology

Population genetics has come of age. Three important components have come together: efficient techniques to examine informative segments of DNA, statistics to analyse DNA data and the availability of easy-to-use computer packages. Single-locus genetic markers and those that produce gene genealogies yield information that is truly comparable among studies. These markers answer biological questions most efficiently and also contribute to much broader investigations of evolutionary, population and conservation biology. For these reasons, single-locus and genealogical markers should be the focus of the intensive genetic data collection that has begun owing to the power of genetics in population biology.     

Genetic genealogy comes of age: Perspectives on the use of deep‐rooted pedigrees in human population genetics

In this article, we promote the implementation of extensive genealogical data in population genetic studies. Genealogical records can provide valuable information on the origin of DNA donors in a population genetic study, going beyond the commonly collected data such as residence, birthplace, language, and self‐reported ethnicity. Recent studies demonstrated that extended genealogical data added to surname analysis can be crucial to detect signals of (past) population stratification and to interpret the population structure in a more objective manner. Moreover, when in‐depth pedigree data are combined with haploid markers, it is even possible to disentangle signals of temporal differentiation within a population genetic structure during the last centuries. Obtaining genealogical data for all DNA donors in a population genetic study is a labor‐intensive task but the vastly growing (genetic) genealogical databases, due to the broad interest of the public, are making this job more time‐efficient if there is a guarantee for sufficient data quality. At the end, we discuss the advantages and pitfalls of using genealogy within sampling campaigns and we provide guidelines for future population genetic studies. Am J Phys Anthropol 150:505–511, 2013. © 2013 Wiley Periodicals, Inc.     

Detecting population expansion and decline using microsatellites

This article considers a demographic model where a population varies in size either linearly or exponentially. The genealogical history of microsatellite data sampled from this population can be described using coalescent theory. A method is presented whereby the posterior probability distribution of the genealogical and demographic parameters can be estimated using Markov chain Monte Carlo simulations. The likelihood surface for the demographic parameters is complicated and its general features are described. The method is then applied to published microsatellite data from two populations. Data from the northern hairy-nosed wombat show strong evidence of decline. Data from European humans show weak evidence of expansion.     

aflpdat: a collection of r functions for convenient handling of AFLP data

aflpdat is a collection of R functions that facilitates the handling of dominant genotypic data. It converts data from a standard tab‐separated table to the input formats of the following programs: arlequin , structure , treecon , paup and hickory . In addition, it calculates the proportion of polymorphic markers in each population, and estimates gene diversity as the average proportion of pairwise differences between individuals with confidence intervals based on bootstrapping across markers. It also produces summary tables of marker frequencies and the presence or absence of markers in each population. aflpdat can be downloaded from http://www.nhm.uio.no/ncb/ .     

Population genetics of the population of the European north of the RSFSR. IV. The level of blood relationship in 5 villages of Pinega District, Archangel Province]

Computer program "RODAN-1" is used for inbreeding coefficient estimation. The population studied consists of two communities of 5 villages. 385 marriages were computed. The coefficient of inbreeding is 0.00145 for pedigree for rural Russian population (the Arkhangelsk region). The inverse dependence between a village size and corresponding data of inbreeding coefficient is suggested. An attempt was undertaken to estimate the genealogical information value for each pedigree and average information value for a village.     

Estimation of genealogical coancestry in plant species using a pedigree reconstruction algorithm and application to an oil palm breeding population

Key message

Explicit pedigree reconstruction by simulated annealing gave reliable estimates of genealogical coancestry in plant species, especially when selfing rate was lower than 0.6, using a realistic number of markers. Genealogical coancestry information is crucial in plant breeding to estimate genetic parameters and breeding values. The approach of Fernández and Toro (Mol Ecol 15:1657–1667, 2006) to estimate genealogical coancestries from molecular data through pedigree reconstruction was limited to species with separate sexes. In this study it was extended to plants, allowing hermaphroditism and monoecy, with possible selfing. Moreover, some improvements were made to take previous knowledge on the population demographic history into account. The new method was validated using simulated and real datasets. Simulations showed that accuracy of estimates was high with 30 microsatellites, with the best results obtained for selfing rates below 0.6. In these conditions, the root mean square error (RMSE) between the true and estimated genealogical coancestry was small (<0.07), although the number of ancestors was overestimated and the selfing rate could be biased. Simulations also showed that linkage disequilibrium between markers and departure from the Hardy–Weinberg equilibrium in the founder population did not affect the efficiency of the method. Real oil palm data confirmed the simulation results, with a high correlation between the true and estimated genealogical coancestry (>0.9) and a low RMSE (<0.08) using 38 markers. The method was applied to the Deli oil palm population for which pedigree data were scarce. The estimated genealogical coancestries were highly correlated (>0.9) with the molecular coancestries using 100 markers. Reconstructed pedigrees were used to estimate effective population sizes. In conclusion, this method gave reliable genealogical coancestry estimates. The strategy was implemented in the software MOLCOANC 3.0.     

Molecular phylogeny and species delimitation in the section Longibrachiatum of Trichoderma

The phylogenetically most derived group of the genus Trichoderma - section Longibrachiatum, includes some of the most intensively studied species, such as the industrial cellulase producer T. reesei (teleomorph Hypocrea jecorina), or the facultative opportunistic human pathogens T. longibrachiatum and H. orientalis. At the same time, the phylogeny of this clade is only poorly understood. Here we used a collection of 112 strains representing all currently recognized species and isolates that were tentatively identified as members of the group, to analyze species diversity and molecular evolution. Bayesian phylogenetic analyses based on several unlinked loci in individual and concatenated datasets confirmed 13 previously described species and 3 previously recognized phylogenetic species all of which were not yet described formally. When the genealogical concordance criterion, the K/θ method and comparison of frequencies of pairwise nucleotide differences were applied to the data sample, 10 additional new phylogenetic species were recognized, seven of which consisted only of a single lineage. Our analysis thus identifies 26 putative species in section Longibrachiatum, what doubles the currently estimated taxonomic diversity of the group, and illustrates the power of combining genealogical concordance and population genetic analysis for dissecting species in a recently diverged group of fungal species.     

New methods for inference of local tree topologies with recombinant SNP sequences in populations

Large amount of population-scale genetic variation data are being collected in populations. One potentially important biological problem is to infer the population genealogical history from these genetic variation data. Partly due to recombination, genealogical history of a set of DNA sequences in a population usually cannot be represented by a single tree. Instead, genealogy is better represented by a genealogical network, which is a compact representation of a set of correlated local genealogical trees, each for a short region of genome and possibly with different topology. Inference of genealogical history for a set of DNA sequences under recombination has many potential applications, including association mapping of complex diseases. In this paper, we present two new methods for reconstructing local tree topologies with the presence of recombination, which extend and improve the previous work in. We first show that the "tree scan" method can be converted to a probabilistic inference method based on a hidden Markov model. We then focus on developing a novel local tree inference method called RENT that is both accurate and scalable to larger data. Through simulation, we demonstrate the usefulness of our methods by showing that the hidden-Markov-model-based method is comparable with the original method in terms of accuracy. We also show that RENT is competitive with other methods in terms of inference accuracy, and its inference error rate is often lower and can handle large data.     

A note on the rationale for estimating genealogical coancestry from molecular markers

Background

Genetic relatedness or similarity between individuals is a key concept in population, quantitative and conservation genetics. When the pedigree of a population is available and assuming a founder population from which the genealogical records start, genetic relatedness between individuals can be estimated by the coancestry coefficient. If pedigree data is lacking or incomplete, estimation of the genetic similarity between individuals relies on molecular markers, using either molecular coancestry or molecular covariance. Some relationships between genealogical and molecular coancestries and covariances have already been described in the literature.

Methods

We show how the expected values of the empirical measures of similarity based on molecular marker data are functions of the genealogical coancestry. From these formulas, it is easy to derive estimators of genealogical coancestry from molecular data. We include variation of allelic frequencies in the estimators.

Results

The estimators are illustrated with simulated examples and with a real dataset from dairy cattle. In general, estimators are accurate and only slightly biased. From the real data set, estimators based on covariances are more compatible with genealogical coancestries than those based on molecular coancestries. A frequently used estimator based on the average of estimated coancestries produced inflated coancestries and numerical instability. The consequences of unknown gene frequencies in the founder population are briefly discussed, along with alternatives to overcome this limitation.

Conclusions

Estimators of genealogical coancestry based on molecular data are easy to derive. Estimators based on molecular covariance are more accurate than those based on identity by state. A correction considering the random distribution of allelic frequencies improves accuracy of these estimators, especially for populations with very strong drift.     

The Anthropology of Personal Identity: Intellectual Property Rights Issues in Papua New Guinea,West Papua and Australia

This paper discusses large‐scale genealogical work at three projects in Papua New Guinea, West Papua and Australia and considers three questions: in what respects is genealogy intellectual property (IP) and, if so, who owns it; what were the regimes of permissions that permitted the collection of genealogical knowledge in each of the three cases; and what duty of care do collectors/curators of genealogical knowledge have in respect of preservation and safeguarding against improper use? It is argued that a new form of ‘emergent’ knowledge arises in which intellectual property rights (IPR) are unclear. What is more certain is that anthropologists owe a ‘cultural heritage duty of care’ towards genealogical information. The key criterion is that anthropologists must be in a position, and allowed by those who employ them, to guarantee ‘unbroken oversight’ of genealogical materials regardless of what media they are on or how they are stored.     

Maintaining genetic diversity using molecular coancestry: the effect of marker density and effective population size

Background

The most efficient method to maintain genetic diversity in populations under conservation programmes is to optimize, for each potential parent, the number of offspring left to the next generation by minimizing the global coancestry. Coancestry is usually calculated from genealogical data but molecular markers can be used to replace genealogical coancestry with molecular coancestry. Recent studies showed that optimizing contributions based on coancestry calculated from a large number of SNP markers can maintain higher levels of diversity than optimizing contributions based on genealogical data. In this study, we investigated how SNP density and effective population size impact the use of molecular coancestry to maintain diversity.

Results

At low SNP densities, the genetic diversity maintained using genealogical coancestry for optimization was higher than that maintained using molecular coancestry. The performance of molecular coancestry improved with increasing marker density, and, for the scenarios evaluated, it was as efficient as genealogical coancestry if SNP density reached at least 3 times the effective population size.However, increasing SNP density resulted in reduced returns in terms of maintained diversity. While a benefit of 12% was achieved when marker density increased from 10 to 100 SNP/Morgan, the benefit was only 2% when it increased from 100 to 500 SNP/Morgan.

Conclusions

The marker density of most SNP chips already available for farm animals is sufficient for molecular coancestry to outperform genealogical coancestry in conservation programmes aimed at maintaining genetic diversity. For the purpose of effectively maintaining genetic diversity, a marker density of around 500 SNPs/Morgan can be considered as the most cost effective density when developing SNP chips for new species. Since the costs to develop SNP chips are decreasing, chips with 500 SNPs/Morgan should become available in a short-term horizon for non domestic species.     

Genealogical approach to the formation of the winter wheat core collection

The correctness of the genealogical approach to the estimation of genetic diversity has been substantiated. The approach implies a comparison of the estimates of similarity based on genetic markers and coefficients of parentage. A method of the application of the genealogical approach to the formation of the core collection has been developed. The adequacy of the core set has been estimated using Shannon's diversity index adapted for genetic profiles and the correlation between the distributions of ancestors' contributions. A core collection has been formed. This collection contains 25% of the accessions of the original winter wheat (Triticum aestivum L.) collection from the Czech Genebank and represents 70-76% of the intracluster diversity. A decrease in intercluster diversity has not been found in the core collection.     

Genealogical Approach to the Formation of the Winter Wheat Core Collection

The correctness of the genealogical approach to the estimation of genetic diversity has been substantiated. The approach implies a comparison of the estimates of similarity based on genetic markers and coefficients of parentage. A method of the application of the genealogical approach to the formation of the core collection has been developed. The adequacy of the core set has been estimated using Shannon's diversity index adapted for genetic profiles and the correlation between the distributions of ancestors' contributions. A core collection has been formed. This collection contains 25% of the accessions of the entire winter wheat (Triticum aestivum L.) collection from the Czech Genebank and represents 70–76% of the within-cluster diversity. A decrease in between-cluster diversity has not been found in the core collection.     

The mapping of epistatic effects onto a genealogical tree in haploid populations

In this paper we present a model that maps epistatic effects onto a genealogical tree for a haploid population. Prior work has demonstrated that genealogical structure causes the genotypic values of individuals to covary. Our results indicate that epistasis can reduce genotypic covariance that is caused by genealogical structure. Genotypic effects (both additive and epistatic) occur along the branches of a genealogical tree, from the base of the tree to its tips. Epistasis reduces genotypic covariance because there is a reweighting of the contribution of branches to the states of genotypes compared to the additive case. Branches near the tips of a genealogical tree contribute proportionally more genetic effects with epistasis than without epistasis. Epistatic effects are most numerous at basal positions in a genealogical tree when a population is constant in size and experiencing no selection, optimizing selection, diversifying selection or directional selection, indicating that epistatic effects are typically old. For a population that is growing in size, epistatic effects are most numerous at midpoints in a genealogical tree, indicating epistatic effects are of moderate age. Our results are important in that they suggest epistatic effects may typically explain deep (old) divergences and broad patterns of divergence that exist in populations, except in growing populations. In a growing population, epistatic effects may cause more within group divergence higher up in a tree and less between group divergence that is deep in a tree. The distribution of the number of epistatic effects and the expected variance and covariance in the number of epistatic effects is also provided assuming neutrality.     

Estimation of population growth or decline in genetically monitored populations

This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.     

Line-of-descent and genealogical processes,and their applications in population genetics models

A variety of results for genealogical and line-of-descent processes that arise in connection with the theory of some classical selectively neutral population genetics models are reviewed. While some new results and derivations are included, the principle aim is to demonstrate the central importance and simplicity of genealogical Markov chains in this theory. Considerable attention is given to “diffusion time scale” approximations of such genealogical processes. A wide variety of results pertinent to (diffusion approximations of) the classical multiallele single-locus Wright-Fisher model and its relatives are simplified and unified by this approach. Other examples where such genealogical processes play an explicit role, such as the infinite sites and infinite alleles models, are discussed.