Clines, clusters, and the effect of study design on the inference of human population structure

Previously, we observed that without using prior information about individual sampling locations, a clustering algorithm applied to multilocus genotypes from worldwide human populations produced genetic clusters largely coincident with major geographic regions. It has been argued, however, that the degree of clustering is diminished by use of samples with greater uniformity in geographic distribution, and that the clusters we identified were a consequence of uneven sampling along genetic clines. Expanding our earlier dataset from 377 to 993 markers, we systematically examine the influence of several study design variables—sample size, number of loci, number of clusters, assumptions about correlations in allele frequencies across populations, and the geographic dispersion of the sample—on the “clusteredness” of individuals. With all other variables held constant, geographic dispersion is seen to have comparatively little effect on the degree of clustering. Examination of the relationship between genetic and geographic distance supports a view in which the clusters arise not as an artifact of the sampling scheme, but from small discontinuous jumps in genetic distance for most population pairs on opposite sides of geographic barriers, in comparison with genetic distance for pairs on the same side. Thus, analysis of the 993-locus dataset corroborates our earlier results: if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe, with some individuals from intermediate geographic locations having mixed membership in the clusters that correspond to neighboring regions.     

Bias correction with a single null marker for population stratification in candidate gene association studies

Population stratification is a form of confounding by ethnicity that may cause bias to effect estimates and inflate test statistics in genetic association studies. Unlinked genetic markers have been used to adjust for test statistics, but their use in correcting biased effect estimates has not been addressed. We evaluated the potential of bias correction that could be achieved by a single null marker (M) in studies involving one candidate gene (G). When the distribution of M varied greatly across ethnicities, controlling for M in a logistic regression model substantially reduced biases on odds ratio estimates. When M had same distributions as G across ethnicities, biases were further reduced or eliminated by subtracting the regression coefficient of M from the coefficient of G in the model, which was fitted either with or without a multiplicative interaction term between M and G. Correction of bias due to population stratification depended specifically on the distributions of G and M, the difference between baseline disease risks across ethnicities, and whether G had an effect on disease risk or not. Our results suggested that marker choice and the specific treatment of that marker in analysis greatly influenced bias correction.     

Canine population structure: assessment and impact of intra-breed stratification on SNP-based association studies

Background

In canine genetics, the impact of population structure on whole genome association studies is typically addressed by sampling approximately equal numbers of cases and controls from dogs of a single breed, usually from the same country or geographic area. However one way to increase the power of genetic studies is to sample individuals of the same breed but from different geographic areas, with the expectation that independent meiotic events will have shortened the presumed ancestral haplotype around the mutation differently. Little is known, however, about genetic variation among dogs of the same breed collected from different geographic regions.

Methodology/Principal Findings

In this report, we address the magnitude and impact of genetic diversity among common breeds sampled in the U.S. and Europe. The breeds selected, including the Rottweiler, Bernese mountain dog, flat-coated retriever, and golden retriever, share susceptibility to a class of soft tissue cancers typified by malignant histiocytosis in the Bernese mountain dog. We genotyped 722 SNPs at four unlinked loci (between 95 and 271 per locus) on canine chromosome 1 (CFA1). We showed that each population is characterized by distinct genetic diversity that can be correlated with breed history. When the breed studied has a reduced intra-breed diversity, the combination of dogs from international locations does not increase the rate of false positives and potentially increases the power of association studies. However, over-sampling cases from one geographic location is more likely to lead to false positive results in breeds with significant genetic diversity.

Conclusions

These data provide new guidelines for association studies using purebred dogs that take into account population structure.     

Isozymes,plant population genetic structure and genetic conservation

Summary The exploration, conservation and use of the genetic resources of plants is a contemporary issue which requires a multidisciplinary approach. Here the role of population genetic data, particularly those derived from electrophoretic analysis of protein variation, is reviewed. Measures of the geographic structure of genetic variation are used to check on sampling theory. Current estimates justify the contention that alleles which have a highly localised distribution, yet are in high frequency in some neighbourhoods, represent a substantial fraction of the variation. This class, which is the most important class in the framing of sampling strategies, accounts for about 20–30% of variants found in 12 plant species. The importance of documenting possible coadapted complexes and gene-environment relationships is discussed. Furthermore, the genetic structure of natural populations of crop relatives might suggest the best structure to use in the breeding of crops for reduced vulnerability to pest and disease attack, or for adaptation to inferior environments. The studies reported to date show that whilst monomorphic natural populations do occur, particularly in inbreeding colonisers, or at the extreme margins of the distribution, polymorphism seems to be the more common mode. It is stressed here that the genetic resources of the wild relatives of crop plants should be systematically evaluated. These sources will supplement, and might even rival, the primitive land races in their effectiveness in breeding programmes. We may look forward to a wider application of gel electrophoresis in the evaluation of plant genetic resources because this technique is currently the best available for detecting genetic differences close to the DNA level on samples of reasonable size.     

New method for surname studies of ancient patrilineal population structures, and possible application to improvement of Y-chromosome sampling

Several studies showed that surnames are good markers to infer patrilineal genetic structures of populations, both on regional and microregional scales. As a case study, the spatial patterns of the 9,929 most common surnames of the Netherlands were analyzed by a clustering method called self-organizing maps (SOMs). The resulting clusters grouped surnames with a similar geographic distribution and origin. The analysis was shown to be in agreement with already known features of Dutch surnames, such as 1) the geographic distribution of some well-known locative suffixes, 2) historical census data, 3) the distribution of foreign surnames, and 4) polyphyletic surnames. Thus, these results validate the SOM clustering of surnames, and allow for the generalization of the technique. This method can be applied as a new strategy for a better Y-chromosome sampling design in retrospective population genetics studies, since the idenfication of surnames with a defined geographic origin enables the selection of the living descendants of those families settled, centuries ago, in a given area. In other words, it becomes possible to virtually sample the population as it was when surnames started to be in use. We show that, in a given location, the descendants of those individuals who inhabited the area at the time of origin of surnames can be as low as approximately 20%. This finding suggests 1) the major role played by recent migrations that are likely to have distorted or even defaced ancient genetic patterns, and 2) that standard-designed samplings can hardly portray a reliable picture of the ancient Y-chromosome variability of European populations.     

Global analysis of regional differences in craniometric diversity and population substructure.

Estimates of genetic diversity in major geographic regions are frequently made by pooling all individuals into regional aggregates. This method can potentially bias results if there are differences in population substructure within regions, since increased variation among local populations could inflate regional diversity. A preferred method of estimating regional diversity is to compute the mean diversity within local populations. Both methods are applied to a global sample of craniometric data consisting of 57 measurements taken on 1734 crania from 18 local populations in six geographic regions: sub-Saharan Africa, Europe, East Asia, Australasia, Polynesia, and the Americas. Each region is represented by three local populations. Both methods for estimating regional diversity show sub-Saharan Africa to have the highest levels of phenotypic variation, consistent with many genetic studies. Polynesia and the Americas both show high levels of regional diversity when regional aggregates are used, but the lowest mean local population diversity. Regional estimates of F(ST) made using quantitative genetic methods show that both Polynesia and the Americas also have the highest levels of differentiation among local populations, which inflates regional diversity. Regional differences in F(ST) are directly related to the geographic dispersion of samples within each region; higher F(ST) values occur when the local populations are geographically dispersed. These results show that geographic sampling can affect results, and suggest caution in making inferences regarding regional diversity when population substructure is ignored.     

The population biology of coevolution

New populational approaches to the study of coevolution among species are confronting two major problems: the geographic scale at which coevolution proceeds, and the long-standing issue of how species may coevolve with more than one other species. By incorporating the ecological structure of life histories and populations into analyses of the coevolutionary process, these studies are indicating that coevolutionary change is much more ecologically dynamic than indicated by earlier work. Rather than simply a slow, stately process shaping species over long periods of time, parts of the coevolutionary process may proceed rapidly (sometimes observable in less than a decade), continually molding and remolding populations and communities locally and over broad geographic scales.     

Biological Affinities Between Migrant and Parental Populations in Punjab, India

In the present study, we have examined biological affinities between parental population, migrants from Pakistan after 1947 and non-Punjabi migrants from other states of India in Punjab. About 500 adult individuals of both sexes from 300 families among three groups were measured for 16 anthropometric and physiometric variables. Analysis of both univariate and multivariate suggests an overall significant migration effect in almost all variables especially anthropometric measurements between both sexes. The higher discrimination has been found in migrants from other states of India with reference to anthropometric traits as compared to other two populations. This is because of more genetic heterogeneity as would be expected from many states and many ethnicities of migrants. It was also found that the other two populations are more or less qualitatively similar, which reflects common ethnohistorical or geographic affiliations. However, overall, women showed a greater migration effect than men.     

Seven common mistakes in population genetics and how to avoid them

As the data resulting from modern genotyping tools are astoundingly complex, genotyping studies require great care in the sampling design, genotyping, data analysis and interpretation. Such care is necessary because, with data sets containing thousands of loci, small biases can easily become strongly significant patterns. Such biases may already be present in routine tasks that are present in almost every genotyping study. Here, I discuss seven common mistakes that can be frequently encountered in the genotyping literature: (i) giving more attention to genotyping than to sampling, (ii) failing to perform or report experimental randomization in the laboratory, (iii) equating geopolitical borders with biological borders, (iv) testing significance of clustering output, (v) misinterpreting Mantel's r statistic, (vi) only interpreting a single value of k and (vii) forgetting that only a small portion of the genome will be associated with climate. For every of those issues, I give some suggestions how to avoid the mistake. Overall, I argue that genotyping studies would benefit from establishing a more rigorous experimental design, involving proper sampling design, randomization and better distinction of a priori hypotheses and exploratory analyses.     

Sex‐biased migration in humans: what should we expect from genetic data?

Different patterns of mitochondrial and Y-chromosome diversity have been cited as evidence of long-term patrilocality in human populations. However, what patterns are expected depends on the nature of the sampling scheme. Samples from a local region reveal only the recent demographic history of that region, whereas sampling over larger geographic scales accesses older demographic processes. A historical change in migration becomes evident first at local geographic scales, and alters global patterns of genetic diversity only after sufficient time has passed. Analysis of forager populations in the ethnographic record suggests that patrilocality may not have predominated among pre-agricultural humans. The higher female migration rate inferred by some genetic studies may reflect a shift to patrilocality in association with the emergence of agriculture. A recent global survey does not show the expected effects of higher female migration, possibly because the sampling scheme used for this study is accessing pre-agricultural human migration patterns. In this paper, we show how the demographic shift associated with agriculture might affect genetic diversity over different spatial scales. We also consider the prospects for studying sex-biased migration using the X-linked and autosomal markers. These multi-locus comparisons have the potential of providing more robust estimates of sex differences than Y-linked and mitochondrial data, but only if a very large number of loci are included in the analysis.     

种群分布格局测定的样方尺度效应

以粤西黑石顶自然保护区西部船底窝的永久样地为研究对象,在一个面积为1600m2的人工次生裸地样地上,借助地理信息系统(GIS)技术,对各个种群分别用3种不同的样方面积(10m×10m,8m×8m,5m×5m)和不同的测定方法来研究演替初期优势种群的分布格局,从而研究不同的样方面积对测定南亚热带森林群落内种群分布格局的影响。结果表明,在南亚热带森林群落演替初期以8m×8m的样方面积来测定种群分布格局较为有效。同时运用GIS技术作数据处理及图形输出,大大简化了分析过程,提高了分析水平。     

Predicting speciation probability from replicated population histories

In this issue of Molecular Ecology, Yamasaki et al. (2020) use genetic data from extensive sampling of Rhinogobius goby fish across the Ryukyu Archipelago in Japan to demonstrate the parallel speciation of a freshwater form from an ancestral amphidromous form. They then show that ecosystem size strongly predicts the probability of speciation between the two forms across islands. In doing so, this study connects population‐level processes (microevolution) to broad‐scale biodiversity patterns (macroevolution), an important but understudied link in evolutionary biology. Moving forward, we can build on this research to (a) more directly determine how geographic, ecological and historical factors influence the different stages of the speciation process, and (b) understand whether mechanisms inferred from insular radiations extend to those on continents, where both demographic histories and environmental regimes are likely more complex.     

The need for continued scientific collecting; a geographic analysis of Mexican bird specimens

The geographic and spatial distribution of more than 221,000 bird specimens collected in Mexico was analyzed on a grid of 1̀ blocks to assess adequacy of representation of the country's avifauna in world systematic collections. Frequency distributions of specimens per block, specimens per species expected in blocks and total specimens per species were all severely right-skewed, with a few blocks well sampled but most represented by very few specimens. Overall, seven scattered blocks out of about 240 were considered well sampled. The best sampled species in the country (House Finch Carpodacus mexicanus ) and the best sampled Mexican endemic species (Russet Nightingale-thrush Catharus occidentalis ) were characterized by uneven and inadequate spatiotemporal sampling, especially in autumn, when plumages are generally fresh and most useful for studies of geographic variation; sampling for a species close to the median of the distribution (Great Black-hawk Buteogallus urubitinga ) was scattered and inappropriate for statistical analysis. Results suggest strongly that sampling of Mexican birds is incomplete, that continued scientific collecting is needed to complete knowledge of the country's avifauna and that similar collecting efforts will be necessary throughout much of the tropics     

Sampling Effort in Neotropical Primate Diet Studies: Collective Gains and Underlying Geographic and Taxonomic Biases

Primates are among the most observable and best studied mammalian orders, yet the distribution of sampling effort by primatologists has inevitably concentrated on a few genera and a limited number of study sites. We present the first systematic review of sampling effort and associated biases in wild primate field research, focusing on dietary studies across the Neotropics. Our literature review of all 24 neotropical primate ecospecies spans 42 years (1969–2011) and covers 290 dietary studies at 164 study sites across 17 countries. We use a standardized measure of sampling effort to assimilate data sets derived from multiple methodologies and attempt to understand the distribution of effort (total equivalent to 193,804 h) using geographic variables and primate species traits. Results indicate that there are both geographic and taxonomic biases, with sampling effort generally skewed towards large-bodied species occupying large geographic ranges, and concentrated at a select few primatology research hubs. We also note that full primate assemblages at any given study site are rarely investigated. Our assessment thus reveals severely undersampled primate taxa and geographic regions that must be considered in future research. Current biases could be ameliorated by deliberately targeting poorly studied genera anywhere in their geographic distribution, well-studied genera in poorly studied regions, and striving to study multiple sympatric taxa within a single site. Although continued inequalities in sampling effort are probably inevitable, this study shows that this need not inhibit successful compilations and meta-analyses, provided that adequate data on feeding records and sampling effort can be made available.     

Standardizing methods to address clonality in population studies

Although clonal species are dominant in many habitats, from unicellular organisms to plants and animals, ecological and particularly evolutionary studies on clonal species have been strongly limited by the difficulty in assessing the number, size and longevity of genetic individuals within a population. The development of molecular markers has allowed progress in this area, and although allozymes remain of limited use due to their typically low level of polymorphism, more polymorphic markers have been discovered during the last decades, supplying powerful tools to overcome the problem of clonality assessment. However, population genetics studies on clonal organisms lack a standardized framework to assess clonality, and to adapt conventional data analyses to account for the potential bias due to the possible replication of the same individuals in the sampling. Moreover, existing studies used a variety of indices to describe clonal diversity and structure such that comparison among studies is difficult at best. We emphasize the need for standardizing studies on clonal organisms, and particularly on clonal plants, in order to clarify the way clonality is taken into account in sampling designs and data analysis, and to allow further comparison of results reported in distinct studies. In order to provide a first step towards a standardized framework to address clonality in population studies, we review, on the basis of a thorough revision of the literature on population structure of clonal plants and of a complementary revision on other clonal organisms, the indices and statistics used so far to estimate genotypic or clonal diversity and to describe clonal structure in plants. We examine their advantages and weaknesses as well as various conceptual issues associated with statistical analyses of population genetics data on clonal organisms. We do so by testing them on results from simulations, as well as on two empirical data sets of microsatellites of the seagrasses Posidonia oceanica and Cymodocea nodosa. Finally, we also propose a selection of new indices and methods to estimate clonal diversity and describe clonal structure in a way that should facilitate comparison between future studies on clonal plants, most of which may be of interest for clonal organisms in general.     

Sampling design in large-scale vegetation studies: Do not sacrifice ecological thinking to statistical purism!

Most of the historical phytosociological data on vegetation composition have been sampled preferentially and thus belong to those ecological data that do not fulfill the statistical assumption of independence of observations, necessary for valid statistical testing and inference. Nevertheless, phytosociological data have been recently used for various ecological meta-analyses, especially in studies of large-scale vegetation patterns. For this reason, we focus on the comparison of preferential sampling with other sampling designs that have been recommended as more convenient alternatives from the point of view of statistical theory. We discuss that while simple random sampling, systematic sampling and stratified random sampling better meet some of the statistical assumptions, preferential sampling yields data sets that cover a broader range of vegetation variability. Moreover, today’s large phytosociological databases provide huge amounts of vegetation data with unrivalled geographic extent and density. We conclude that in the near future ecologists will not be able to replace the preferentially sampled phytosociological data in large-scale studies. At the same time, phytosociological databases have to be complemented with relevés of vegetation composed mostly of common and generalist species, which are under-represented in historical data. Stratified random sampling seems to be a suitable tool for doing this. Nevertheless, a methodology and input data for stratification have to be developed to make stratified random sampling an ecologically more relevant and practical method.     

The impact of the species-area relationship on estimates of paleodiversity

Estimates of paleodiversity patterns through time have relied on datasets that lump taxonomic occurrences from geographic areas of varying size per interval of time. In essence, such estimates assume that the species–area effect, whereby more species are recorded from larger geographic areas, is negligible for fossil data. We tested this assumption by using the newly developed Miocene Mammal Mapping Project database of western North American fossil mammals and its associated analysis tools to empirically determine the geographic area that contributed to species diversity counts in successive temporal bins. The results indicate that a species–area effect markedly influences counts of fossil species, just as variable spatial sampling influences diversity counts on the modern landscape. Removing this bias suggests some traditionally recognized peaks in paleodiversity are just artifacts of the species–area effect while others stand out as meriting further attention. This discovery means that there is great potential for refining existing time-series estimates of paleodiversity, and for using species–area relationships to more reliably understand the magnitude and timing of such biotically important events as extinction, lineage diversification, and long-term trends in ecological structure.     

The Impact of the Species–Area Relationship on Estimates of Paleodiversity

Estimates of paleodiversity patterns through time have relied on datasets that lump taxonomic occurrences from geographic areas of varying size per interval of time. In essence, such estimates assume that the species–area effect, whereby more species are recorded from larger geographic areas, is negligible for fossil data. We tested this assumption by using the newly developed Miocene Mammal Mapping Project database of western North American fossil mammals and its associated analysis tools to empirically determine the geographic area that contributed to species diversity counts in successive temporal bins. The results indicate that a species–area effect markedly influences counts of fossil species, just as variable spatial sampling influences diversity counts on the modern landscape. Removing this bias suggests some traditionally recognized peaks in paleodiversity are just artifacts of the species–area effect while others stand out as meriting further attention. This discovery means that there is great potential for refining existing time-series estimates of paleodiversity, and for using species–area relationships to more reliably understand the magnitude and timing of such biotically important events as extinction, lineage diversification, and long-term trends in ecological structure.     

Testing the Rio Doce as a riverine barrier in shaping the Atlantic rainforest population divergence in the rodent Akodon cursor

Akodon cursor occurs in dense rainforest from northern (8° S) to southern (26° S) states along the Atlantic coast of Brazil. Previous karyological and molecular data revealed two major clades, one including northern (8-15° S) and the other southern (19-26° S) populations. The center of geographic distribution (15-20° S), which included the state of Espírito Santo, was identified as a potential vicariance region. Since river barriers are among the most discussed models in the study of Neotropical diversification, we examined whether the Rio Doce (19° S) plays an important role in shaping the population genetic divergence of A. cursor by including samples from Espírito Santo in the analysis. Our results showed that the northern-southern division region in Atlantic forest was no coincidence with the presence of the Rio Doce by refuting the hypothesis that this river is an effective barrier to gene flow between populations. Instead, we found evidence that isolation by geographical distance shaped the phylogeographical structure in the southern lineage. However, there is uncertainty about effectiveness of the processes involved and further studies based on wider sampling are needed.