Is a Multivariate Consensus Representation of Genetic Relationships Among Populations Always Meaningful?

Linking genomics and population genetics with R

Population genetics and genomics have developed and been treated as independent fields of study despite having common roots. The continuous progress of sequencing technologies is contributing to (re-)connect these two disciplines. We review the challenges faced by data analysts and software developers when handling very big genetic data sets collected on many individuals. We then expose how r, as a computing language and development environment, proposes some solutions to meet these challenges. We focus on some specific issues that are often encountered in practice: handling and analysing single-nucleotide polymorphism data, handling and reading variant call format files, analysing haplotypes and linkage disequilibrium and performing multivariate analyses. We illustrate these implementations with some analyses of three recently published data sets that contain between 60 000 and 1 000 000 loci. We conclude with some perspectives on future developments of r software for population genomics.

Rank and order: evaluating the performance of SNPs for individual assignment in a non-model organism

Single nucleotide polymorphisms (SNPs) are valuable tools for ecological and evolutionary studies. In non-model species, the use of SNPs has been limited by the number of markers available. However, new technologies and decreasing technology costs have facilitated the discovery of a constantly increasing number of SNPs. With hundreds or thousands of SNPs potentially available, there is interest in comparing and developing methods for evaluating SNPs to create panels of high-throughput assays that are customized for performance, research questions, and resources. Here we use five different methods to rank 43 new SNPs and 71 previously published SNPs for sockeye salmon: F(ST), informativeness (I(n)), average contribution to principal components (LC), and the locus-ranking programs BELS and WHICHLOCI. We then tested the performance of these different ranking methods by creating 48- and 96-SNP panels of the top-ranked loci for each method and used empirical and simulated data to obtain the probability of assigning individuals to the correct population using each panel. All 96-SNP panels performed similarly and better than the 48-SNP panels except for the 96-SNP BELS panel. Among the 48-SNP panels, panels created from F(ST), I(n), and LC ranks performed better than panels formed using the top-ranked loci from the programs BELS and WHICHLOCI. The application of ranking methods to optimize panel performance will become more important as more high-throughput assays become available.

Genetic diversity and admixture of indigenous cattle from North Ethiopia: implications of historical introgressions in the gateway region to Africa

Microsatellite variation was surveyed to determine the genetic diversity, population structure and admixture of seven North Ethiopian cattle breeds by combining multiple microsatellite data sets of Indian and West African zebu, and European, African and Near-Eastern taurine in genetic analyses. Based on allelic distribution, we identified four diagnostic alleles (HEL1-123 bp, CSSM66-201 bp, BM2113-150 bp and ILSTS6-285 bp) specific to the Near-Eastern taurine. Results of genetic relationship and population structure analyses confirmed the previously established marked genetic distinction between taurine and zebu, and indicated further divergence among the bio-geographical groupings of breeds such as North Ethiopian, Indian and West African zebu, and African, European and Near-Eastern taurine. Using the diagnostic alleles for bio-geographical groupings and a Bayesian method for population structure inference, we estimated the genetic influences of major historical introgressions in North Ethiopian cattle. The breeds have been heavily (>90%) influenced by zebu, followed by African, European and the Near-Eastern taurine. Overall, North Ethiopian cattle show a high level of within-population genetic variation (e.g. observed heterozygosity = 0.659-0.687), which is in the upper range of that reported for domestic cattle and indicates their potential for future breeding applications, even in a global context. Rather low but significant population differentiation (F(ST) = 1.1%, P < 0.05) was recorded as a result of multiple introgression events and strong genetic exchanges among the North Ethiopian breeds.

Population genetic analysis of the Brahman cattle (Bos indicus) in Colombia with microsatellite markers

The Brahman is one of the most popular breeds for meat production in the Neotropics. However, genetic studies of the breed in Latin American countries have only recently begun. In total, 178 animals of the Brahman breed from 20 Colombian provinces were genotyped at 11 microsatellite markers with the aim of studying the genetic diversity of this population and its genetic relationships with zebuine and taurine breeds. The outcomes of multivariate analyses, Bayesian inferences and inter-individual genetic distances suggested that there is no genetic sub-structure in the population, because of the high rate of animal migration among provinces. The population shows a high degree of heterozygosity and allelic diversity compared with other breeds, reflecting its multibreed origin. The study of the genetic relationships among the breeds reveals that the Brahman breed belongs to the zebuine group. However, it is the population nearest to taurine breeds with high frequencies of taurine alleles. Intensive artificial selection may have favoured the taurine alleles after the breed was formed. There has also been some degree of mixture with local taurine breeds while the Brahman breed has evolved in Colombia.

Genetic relationships of ethnic minorities in Southwest China revealed by microsatellite markers

Population migrations in Southwest and South China have played an important role in the formation of East Asian populations and led to a high degree of cultural diversity among ethnic minorities living in these areas. To explore the genetic relationships of these ethnic minorities, we systematically surveyed the variation of 10 autosomal STR markers of 1,538 individuals from 30 populations of 25 ethnic minorities, of which the majority were chosen from Southwest China, especially Yunnan Province. With genotyped data of the markers, we constructed phylogenies of these populations with both D(A) and D(C) measures and performed a principal component analysis, as well as a clustering analysis by structure. Results showed that we successfully recovered the genetic structure of analyzed populations formed by historical migrations. Aggregation patterns of these populations accord well with their linguistic affiliations, suggesting that deciphering of genetic relationships does in fact offer clues for study of ethnic differentiation.

Genetic markers in the playground of multivariate analysis

Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current innovations, these approaches have proven to be efficient for the analysis of the genetic variability in various contexts such as human genetics, conservation and adaptation studies. However, because multivariate analysis is a wide and diversified area of statistics, choosing a method appropriate to both the data and to the question being asked can be difficult. Moreover, some particularities of genetic markers need to be taken into account when using multivariate methods. As a consequence, multivariate analyses are often used as black boxes, which results in frequent mistakes in the literature. In this review, we provide a critical analysis of the application of multivariate methods to genetic markers, using a general framework that unifies all these methods for the sake of clarity. First, we focus on some common mistakes in these applications and ways to avoid these pitfalls. We then detail the most critical particularities of allele frequencies that demand adaptations of multivariate methods, and we propose solutions to the subsequent problems. Finally, we tackle several questions of interest in which multivariate analysis has a great role to play, such as the study of the typological coherence of different genetic markers, or the investigation of spatial genetic patterns.

Microsatellite-based phylogeny of Indian domestic goats

Background

The domestic goat is one of the important livestock species of India. In the present study we assess genetic diversity of Indian goats using 17 microsatellite markers. Breeds were sampled from their natural habitat, covering different agroclimatic zones.

Results

The mean number of alleles per locus (NA) ranged from 8.1 in Barbari to 9.7 in Jakhrana goats. The mean expected heterozygosity (He) ranged from 0.739 in Barbari to 0.783 in Jakhrana goats. Deviations from Hardy-Weinberg Equilibrium (HWE) were statistically significant (P < 0.05) for 5 loci breed combinations. The D_A measure of genetic distance between pairs of breeds indicated that the lowest distance was between Marwari and Sirohi (0.135). The highest distance was between Pashmina and Black Bengal. An analysis of molecular variance indicated that 6.59% of variance exists among the Indian goat breeds. Both a phylogenetic tree and Principal Component Analysis showed the distribution of breeds in two major clusters with respect to their geographic distribution.

Conclusion

Our study concludes that Indian goat populations can be classified into distinct genetic groups or breeds based on the microsatellites as well as mtDNA information.

New analysis for consistency among markers in the study of genetic diversity: development and application to the description of bacterial diversity

Background

The development of post-genomic methods has dramatically increased the amount of qualitative and quantitative data available to understand how ecological complexity is shaped. Yet, new statistical tools are needed to use these data efficiently. In support of sequence analysis, diversity indices were developed to take into account both the relative frequencies of alleles and their genetic divergence. Furthermore, a method for describing inter-population nucleotide diversity has recently been proposed and named the double principal coordinate analysis (DPCoA), but this procedure can only be used with one locus. In order to tackle the problem of measuring and describing nucleotide diversity with more than one locus, we developed three versions of multiple DPCoA by using three ordination methods: multiple co-inertia analysis, STATIS, and multiple factorial analysis.

Results

This combination of methods allows i) testing and describing differences in patterns of inter-population diversity among loci, and ii) defining the best compromise among loci. These methods are illustrated by the analysis of both simulated data sets, which include ten loci evolving under a stepping stone model and a locus evolving under an alternative population structure, and a real data set focusing on the genetic structure of two nitrogen fixing bacteria, which is influenced by geographical isolation and host specialization. All programs needed to perform multiple DPCoA are freely available.

Conclusion

Multiple DPCoA allows the evaluation of the impact of various loci in the measurement and description of diversity. This method is general enough to handle a large variety of data sets. It complements existing methods such as the analysis of molecular variance or other analyses based on linkage disequilibrium measures, and is very useful to study the impact of various loci on the measurement of diversity.

Genetic evidence from mitochondrial, nuclear, and endosymbiont markers for the evolution of host plant associated species in the aphid genus Hyalopterus (Hemiptera: Aphididae)

Over the past several decades biologists' fascination with plant-herbivore interactions has generated intensive research into the implications of these interactions for insect diversification. The study of closely related phytophagous insect species or populations from an evolutionary perspective can help illuminate ecological and selective forces that drive these interactions. Here we present such an analysis for aphids in the genus Hyalopterus (Hemiptera: Aphididae), a cosmopolitan group that feeds on plants in the genus Prunus (Rosaceae). Hyalopterus currently contains two recognized species associated with different Prunus species, although the taxonomy and evolutionary history of the group is poorly understood. Using mitochondrial COI sequences, 16S rDNA sequences from the aphid endosymbiont Buchnera aphidicola, and nine microsatellite loci we investigated population structure in Hyalopterus from the most commonly used Prunus host species throughout the Mediterranean as well as in California, where the species H. pruni is an invasive pest. We found three deeply divergent lineages structured in large part by specific associations with plum, almond, and peach trees. There was no evidence that geographic or temporal barriers could explain the overall diversity in the genus. Levels of genetic differentiation are consistent with that typically attributed to aphid species and indicate divergence times older than the domestication of Prunus for agriculture. Interestingly, in addition to their typical hosts, aphids from each of the three lineages were frequently found on apricot trees. Apricot also appears to act as a resource mediated hybrid zone for plum and almond associated lineages. Together, results suggest that host plants have played a role in maintaining host-associated differentiation in Hyalopterus for as long as several million years, despite worldwide movement of host plants and the potential for ongoing hybridization.

Genetic diversity in European pigs utilizing amplified fragment length polymorphism markers

The use of DNA markers to evaluate genetic diversity is an important component of the management of animal genetic resources. The Food and Agriculture Organisation of the United Nations (FAO) has published a list of recommended microsatellite markers for such studies; however, other markers are potential alternatives. This paper describes results obtained with a set of amplified fragment length polymorphism (AFLP) markers as part of a genetic diversity study of European pig breeds that also utilized microsatellite markers. Data from 148 AFLP markers genotyped across samples from 58 European and one Chinese breed were analysed. The results were compared with previous analyses of data from 50 microsatellite markers genotyped on the same animals. The AFLP markers had an average within-breed heterozygosity of 0.124 but there was wide variation, with individual markers being monomorphic in 3-98% of the populations. The biallelic and dominant nature of AFLP markers creates a challenge for their use in genetic diversity studies as each individual marker contains limited information and AFLPs only provide indirect estimates of the allelic frequencies that are needed to estimate genetic distances. Nonetheless, AFLP marker-based characterization of genetic distances was consistent with expectations based on breed and regional distributions and produced a similar pattern to that obtained with microsatellites. Thus, data from AFLP markers can be combined with microsatellite data for measuring genetic diversity.

High-resolution characterization of linkage disequilibrium structure and selection of tagging single nucleotide polymorphisms: application to the cholesteryl ester transfer protein gene

Full characterization of intragenic variation may improve candidate gene associations. This study selected tagging (t) single nucleotide polymorphisms (SNPs) to comprehensively represent genetic variability in the cholesteryl ester transfer protein (CETP) gene. Nineteen SNPs were identified in 50 unrelated individuals in the SNP discovery phase, and 13 intronic SNPs were added from the literature. These 32 SNPs were genotyped in 339 apparently healthy individuals and 190 coronary artery disease (CAD) patients. Using phased haplotypes, linkage disequilibrium (LD) structure was characterized and tSNPs selected using a principal component analysis (PCA) method. In healthy individuals, seven LD groups were identified that accounted for 93.4% of the observed genetic variation. These LD groups highlighted a complex LD structure for CETP, including both recombination and mutation, and eleven tSNPs were selected. Among CAD patients the results were essentially the same. Results from PCA using diploid genotype data were reasonably comparable. Finally, the selected tSNPs successfully represented the association evidence discovered for all of the other SNPs studied. This study provides an optimal set of tSNPs for association analyses of CETP. The observed complexity of LD structure highlights the importance of using methods, such as PCA, that allow for multiple dynamics in intragenic LD structure.

Variation in population structure across the ecological range of the Queensland fruit fly, Bactrocera tryoni

We sampled a pest fruit fly species, the Queensland fruit fly, Bactrocera tryoni, across its entire ecological range in eastern Australia, from ancestral high-density populations in tropical regions through to isolated outbreak populations in marginal arid areas. Using DNA microsatellite markers, we found that in ancestral areas, population differentiation was low and populations were genetically homogeneous over large distances. In more temperate areas, populations were far more genetically differentiated but there was no pattern of isolation-by-distance (no drift/migration equilibrium). Genetic drift appeared to be the major influence on population differentiation. The transition between these extremes was abrupt and unexpectedly far from the species border. Limited geographic structuring among the non-equilibrium populations was apparent from patterns of genetic differentiation, patterns of allelic richness and an ordination analysis. Our results also suggested that there might be recurring migration of flies into a neighbouring quarantine area.

Characterization and conservation of genetic diversity in subdivided populations

We review the available tools for analysing genetic diversity in conservation programmes of subdivided populations. Ways for establishing conservation priorities have been developed in the context of livestock populations, both from the classical population genetic analysis and from the more recent Weitzman's approach. We discuss different reasons to emphasize either within or between-population variation in conservation decisions and the methodology to establish some compromise. The comparison between neutral and quantitative variation is reviewed from both theoretical and empirical points of view, and the different procedures for the dynamic management of conserved subdivided populations are discussed.

Genetic consequences of white-tailed deer (Odocoileus virginianus) restoration in Mississippi

White-tailed deer (Odocoileus virginianus) were nearly extirpated from the southeastern USA during the late 19th and early 20th centuries. Recovery programmes, including protection of remnant native stocks and transplants from other parts of the species' range, were initiated in the early 1900's. The recovery programmes were highly successful and deer are presently numerous and continuously distributed throughout the southeastern USA. However, the impact of the recovery programmes on the present genetic structure of white-tailed deer remains to be thoroughly investigated. We used 17 microsatellite DNA loci to assess genetic differentiation and diversity for 543 white-tailed deer representing 16 populations in Mississippi and three extra-state reference populations. There was significant genetic differentiation among all populations and the majority of genetic variation (> or = 93%) was contained within populations. Patterns of genetic structure, genetic similarity and isolation by distance within Mississippi were not concordant with geographical proximity of populations or subspecies delineations. We detected evidence of past genetic bottlenecks in nine of the 19 populations examined. However, despite experiencing genetic bottlenecks or founder events, allelic diversity and heterozygosity were uniformly high in all populations. These exceeded reported values for other cervid species that experienced similar population declines within the past century. The recovery programme was successful in that deer were restored to their former range while maintaining high and uniform genetic variability. Our results seem to confirm the importance of rapid population expansion and habitat continuity in retaining genetic variation in restored populations. However, the use of diverse transplant stocks and the varied demographic histories of populations resulted in fine-scale genetic structuring.