A quantitative comparison of the similarity between genes and geography in worldwide human populations

Intelligence, brain structure, dendrites, and genes: Genetic, epigenetic and the underlying of the quadruple helix complexity

Intelligence can be referred to as the mental ability to learn, comprehend abstract concepts, and solve complex problems. Twin and adoption studies have provided insights into the influence of the familial environment and highlighted the importance of heritability in the development of cognition. Detecting the relative contribution of brain areas, neuronal structures, and connectomes has brought some understanding on how various brain areas, white/gray matter structures and neuronal connectivity process information and contribute to intelligence. Using histological, anatomical, electrophysiological, neuropsychological, neuro-imaging and molecular biology methods, several key concepts have emerged: 1) the parietofrontal-hippocampal integrations probably constitute a substrate for smart behavior, 2) neuronal activity results in structural plasticity of dendritic branches responsible for information transfer, critical for learning and memory, 3) intelligent people process information efficiently, 4) the environment triggers mnemonic epigenomic programs (via dynamic regulation of chromatin accessibility, DNA methylation, loop interruption/formation and histone modification) conferring cognitive phenotypes throughout life, and 5) single/double DNA breaks are prominent in human brain disorders associated with cognitive impairment including Alzheimer's disease and schizophrenia. Along with these observations, molecular/cellular/biological studies have identified sets of specific genes associated with higher scores on intelligence tests. Interestingly, many of these genes are associated with dendritogenesis. Because dendrite structure/function is involved in cognition, the control of dendrite genesis/maintenance may be critical for understanding the landscape of general/specific cognitive ability and new pathways for therapeutic approaches.

Genome diversity and signatures of natural selection in mainland Southeast Asia

Mainland Southeast Asia (MSEA) has rich ethnic and cultural diversity with a population of nearly 300 million1,2. However, people from MSEA are underrepresented in the current human genomic databases. Here we present the SEA3K genome dataset (phase I), generated by deep short-read whole-genome sequencing of 3,023 individuals from 30 MSEA populations, and long-read whole-genome sequencing of 37 representative individuals. We identified 79.59 million small variants and 96,384 structural variants, among which 22.83 million small variants and 24,622 structural variants are unique to this dataset. We observed a high genetic heterogeneity across MSEA populations, reflected by the varied combinations of genetic components. We identified 44 genomic regions with strong signatures of Darwinian positive selection, covering 89 genes involved in varied physiological systems such as physical traits and immune response. Furthermore, we observed varied patterns of archaic Denisovan introgression in MSEA populations, supporting the proposal of at least two distinct instances of Denisovan admixture into modern humans in Asia3. We also detected genomic regions that suggest adaptive archaic introgressions in MSEA populations. The large number of novel genomic variants in MSEA populations highlight the necessity of studying regional populations that can help answer key questions related to prehistory, genetic adaptation and complex diseases.

Population connectivity and size reductions in the Anthropocene: the consequence of landscapes and historical bottlenecks in white forsythia fragmented habitats

BACKGROUND

White forsythia (Abeliophyllum distichum) is an endangered Korean Peninsula endemic that has been subjected to recent population genomics studies using SNPs via RAD sequencing. Here, we primarily employed the often underutilized haplotype information from RAD loci to further describe the species' previously uninvestigated haplotype-based genomic variation and structure, and genetic-geographic characteristics and gene flow patterns among its five earlier identified genetic groups. We also inferred the time of past events that may have impacted the effective population size of these groups, as well as the species' potential future distribution amidst the warming climate and anthropogenic threats.

RESULTS

Our findings emphasized the recognition of the species' regional patterns of genetic structure, and the role of topography and its associated gene flow patterns as some of the possible factors that may have influenced the species' present-day fragmented population distribution. The inferred bottleneck events during the Anthropocene, some of which aligned with the time of historical catastrophic events on the Peninsula (e.g., the Korean War), were revealed to have contributed to the generally low effective population size of its five lineages, particularly those with marginal distributional range. Future distribution under both optimistic and pessimistic climatic scenarios suggests unlikely suitable habitats for these populations to expand from their current range limits, at least in the next 80 years.

CONCLUSIONS

The small effective population size and landscape-driven limited gene flow among white forsythia populations will remain a big challenge for the conservation management of the species' already fragmented population distribution. To help mitigate these impacts, the merging of various research approaches and the use of genomic data to their full potential is recommended to provide the optimized knowledge-based tools for the conservation of this endangered species, and other similar plants under pressure.

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

YHP: Y-chromosome Haplogroup Predictor for predicting male lineages based on Y-STRs

Human Y chromosome reflects the evolutionary process of males. Male lineage tracing by Y chromosome is of great use in evolutionary, forensic, and anthropological studies. Identifying the male lineage based on the specific distribution of Y haplogroups narrows down the investigation scope, which has been used in forensic scenarios. However, existing software aids in familial searching using Y-STRs (Y-chromosome short tandem repeats) to predict Y-SNP (Y-chromosome single nucleotide polymorphism) haplogroups, they often lack resolution. In this study, we developed YHP (Y Haplogroup Predictor), a novel software offering high-resolution haplogroup inference without requiring extensive Y-SNP sequencing. Leveraging existing datasets (219 haplogroups, 4064 samples in total), YHP predicts haplogroups with 0.923 accuracy under the highest haplogroup resolution, employing a random forest algorithm. YHP, available on Github (https://github.com/cissy123/YHP-Y-Haplogroup-Predictor-), facilitates high-resolution haplogroup prediction, haplotype mismatch analysis, and haplotype similarity comparison. Notably, it demonstrates efficacy in East Asian populations, benefiting from training data from eight distinct East Asian ethnic populations. Moreover, it enables seamless integration of additional training sets, extending its utility to diverse populations.

On the connections between the spatial Lambda-Fleming-Viot model and other processes for analysing geo-referenced genetic data

The introduction of the spatial Lambda-Fleming-Viot model (ΛV) in population genetics was mainly driven by the pioneering work of Alison Etheridge, in collaboration with Nick Barton and Amandine Véber about ten years ago (Barton et al., 2010; Barton et al., 2013). The ΛV model provides a sound mathematical framework for describing the evolution of a population of related individuals along a spatial continuum. It alleviates the "pain in the torus" issue with Wright and Malécot's isolation by distance model and is sampling consistent, making it a tool of choice for statistical inference. Yet, little is known about the potential connections between the ΛV and other stochastic processes generating trees and the spatial coordinates along the corresponding lineages. This work focuses on a version of the ΛV whereby lineages move rapidly over small distances. Using simulations, we show that the induced ΛV tree-generating process is well approximated by a birth-death model. Our results also indicate that Brownian motions modelling the movements of lines of descent along birth-death trees do not generally provide a good approximation of the ΛV due to habitat boundaries effects that play an increasingly important role in the long run. Accounting for habitat boundaries through reflected Brownian motions considerably increases the similarity to the ΛV model however. Finally, we describe efficient algorithms for fast simulation of the backward and forward in time versions of the ΛV model.

Genomic data revealed inbreeding despite a geographically connected stable effective population size since the Holocene in the protected Formosan Long-Arm Scarab beetle, Cheirotonus formosanus

Biodiversity conservation is a top priority in the face of global environmental change, and the practical restoration of biodiversity has emerged as a key objective. Nevertheless, the question of how to effectively contribute to biodiversity restoration and identify suitable systems for such efforts continues to present major challenges. By using genome-wide SNP data, our study revealed that populations from different mountain ranges of the Formosan Long-Arm Scarab beetle, a flagship species that receives strict protection, exhibited a single genetic cluster with no subdivision. Additionally, our result implied an association between the demographic history and historical fluctuations in climate and environmental conditions. Furthermore, we showed that, despite a stable and moderately sized effective population over recent history, all the individuals we studied exhibited signs of genetic inbreeding. We argued that the current practice of protecting the species as one evolutionarily significant unit remains the best conservation plan and that recent habitat change may have led to the pattern of significant inbreeding. We closed by emphasizing the importance of conservation genetic studies in guiding policy decisions and highlighting the potential of genomic data for identifying ideal empirical systems for genetic rescue, or assisted gene flow studies.

Genetic and molecular architecture of complex traits

Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.

Climate influences the genetic structure and niche differentiation among populations of the olive field mouse Abrothrix olivacea (Cricetidae: Abrotrichini)

Even when environmental variation over time and space is commonly considered as an important driver of population divergence, few evaluations of intraspecific genetic variation explicitly assess whether observed structure has been caused by or is correlated with landscape heterogeneity. Several phylogeographic studies have characterized the mitochondrial diversity of Abrothrix olivacea, but none has incorporated landscape genetics analyses and ecological niche modeling, leaving a gap in the understanding of the species evolutionary history. Here, these aspects were addressed based on 186 single nucleotide polymorphisms, extracted from sequences of 801 bp of Cytb gene, gathered from 416 individuals collected at 103 localities in Argentina and Chile. Employing multivariate statistical analyses (gPCA, Mantel and Partial Mantel Tests, Procrustes Analysis, and RDA), associations between genetic differences and geographic and climatic distances were evaluated. Presence data was employed to estimate the potential geographic distribution of this species during historical and contemporary climatic scenarios, and to address differences among the climatic niches of their main mitochondrial lineages. The significant influence of landscape features in structuring mitochondrial variability was evidenced at different spatial scales, as well as the role of past climatic dynamics in driving geographic range shifts, mostly associated to Quaternary glaciations. Overall, these results suggest that throughout geographic range gene flow is unevenly influenced by climatic dissimilarity and the geographic distancing, and that studied lineages do not exhibit distributional signals of climatic niche conservatism. Additionally, genetic differentiation occurred by more complex evolutionary processes than mere disruption of gene flow or drift.

ddRAD-Seq reveals evolutionary insights into population differentiation and the cryptic phylogeography of Hyporhamphus intermedius in Mainland China

Species differentiation and local adaptation in heterogeneous environments have attracted much attention, although little is known about the mechanisms involved. Hyporhamphus intermedius is an anadromous, brackish-water halfbeak that is widely distributed in coastal areas and hyperdiverse freshwater systems in China, making it an interesting model for research on phylogeography and local adaptation. Here, 156 individuals were sampled at eight sites from heterogeneous aquatic habitats to examine environmental and genetic contributions to phenotypic divergence. Using double-digest restriction-site-associated DNA sequencing (ddRAD-Seq) in the specimens from the different watersheds, 5498 single nucleotide polymorphisms (SNPs) were found among populations, with obvious population differentiation. We find that present-day Mainland China populations are structured into distinct genetic clusters stretching from southern and northern ancestries, mirroring geography. Following a transplant event in Plateau Lakes, there were virtually no variations of genetic diversity occurred in two populations, despite the fact two main splits were unveiled in the demographic history. Additionally, dorsal, and anal fin traits varied widely between the southern group and the others, which highlighted previously unrecognized lineages. We then explore genotype-phenotype-environment associations and predict candidate loci. Subgroup ranges appeared to correspond to geographic regions with heterogeneous hydrological factors, indicating that these features are likely important drivers of diversification. Accordingly, we conclude that genetic and phenotypic polymorphism and a moderate amount of genetic differentiation occurred, which might be ascribed to population subdivision, and the impact of abiotic factors.

A deep learning framework for characterization of genotype data

Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are principal component analysis, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns. Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and have been shown to present a promising alternative to traditional statistical methods for various applications in omics research. In this study, we propose a deep learning model based on a convolutional autoencoder architecture for dimensionality reduction of genotype data. Using a highly diverse cohort of human samples, we demonstrate that the model can identify population clusters and provide richer visual information in comparison to principal component analysis, while preserving global geometry to a higher extent than t-SNE and UMAP, yielding results that are comparable to an alternative deep learning approach based on variational autoencoders. We also discuss the use of the methodology for more general characterization of genotype data, showing that it preserves spatial properties in the form of decay of linkage disequilibrium with distance along the genome and demonstrating its use as a genetic clustering method, comparing results to the ADMIXTURE software frequently used in population genetic studies.

Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers

The inference of ancestry has become a part of the services many forensic genetic laboratories provide. Interest in ancestry may be to provide investigative leads or identify the region of origin in cases of unidentified missing persons. There exist many biostatistical methods developed for the study of population structure in the area of population genetics. However, the challenges and questions are slightly different in the context of forensic genetics, where the origin of a specific sample is of interest compared to the understanding of population histories and genealogies. In this paper, the methodologies for modelling population admixture and inferring ancestral populations are reviewed with a focus on their strengths and weaknesses in relation to ancestry inference in the forensic context.

Rare variant association tests for ancestry-matched case-control data based on conditional logistic regression

With the increasing volume of human sequencing data available, analysis incorporating external controls becomes a popular and cost-effective approach to boost statistical power in disease association studies. To prevent spurious association due to population stratification, it is important to match the ancestry backgrounds of cases and controls. However, rare variant association tests based on a standard logistic regression model are conservative when all ancestry-matched strata have the same case-control ratio and might become anti-conservative when case-control ratio varies across strata. Under the conditional logistic regression (CLR) model, we propose a weighted burden test (CLR-Burden), a variance component test (CLR-SKAT) and a hybrid test (CLR-MiST). We show that the CLR model coupled with ancestry matching is a general approach to control for population stratification, regardless of the spatial distribution of disease risks. Through extensive simulation studies, we demonstrate that the CLR-based tests robustly control type 1 errors under different matching schemes and are more powerful than the standard Burden, SKAT and MiST tests. Furthermore, because CLR-based tests allow for different case-control ratios across strata, a full-matching scheme can be employed to efficiently utilize all available cases and controls to accelerate the discovery of disease associated genes.

Tinnitus prevalence in Europe: a multi-country cross-sectional population study

BACKGROUND

Tinnitus prevalence studies report large variability across countries that might be due to inconsistent research methods. Our study aimed to report a single Pan-European estimate for tinnitus prevalence and investigate the effect of individual and country-level characteristics on prevalence. We explored the relationships of healthcare resource use and hearing difficulty with tinnitus symptoms.

METHODS

Between 2017-2018, a cross-sectional European Tinnitus Survey (ETS) was conducted in 12 European Union nations (Bulgaria, England, France, Germany, Greece, Ireland, Italy, Latvia, Poland, Portugal, Romania, and Spain), using a standardised set of tinnitus-related questions and response options in country-specific languages. We recruited 11,427 adults aged ≥18 years.

FINDINGS

Prevalence of any tinnitus was 14·7% (14·0% in men and 15·2% in women), ranging from 8·7% in Ireland to 28·3% in Bulgaria. Severe tinnitus was found in 1·2% participants (1·0% in men and 1·4% in women), ranging from 0·6% in Ireland to 4·2% in Romania. Tinnitus prevalence significantly increased with increasing age and worsening of hearing status. Healthcare resource use for tinnitus increased with increasing tinnitus symptom severity.

INTERPRETATION

This is the first multinational report of Pan-European tinnitus prevalence using standardised questions. The overall prevalence estimates refine previous findings, although widespread inter-country heterogeneity was noted. The results indicate that more than 1 in 7 adults in the EU have tinnitus. Extrapolating to the overall population, approximately 65 million adults in EU28 have tinnitus, 26 million have bothersome tinnitus and 4 million have severe tinnitus.

FUNDING

National Institute for Health Research, European Union's Horizon 2020, Medical Research Council, and GENDER-Net Co-Plus Fund.

Seascape Genetics of the Atlantic Spotted Dolphin (Stenella frontalis) Based on Mitochondrial DNA

The Atlantic spotted dolphin (Stenella frontalis) is endemic to tropical, subtropical, and warm temperate waters of the Atlantic Ocean. Throughout its distribution, both geographic distance and environmental variation may contribute to population structure of the species. In this study, we follow a seascape genetics approach to investigate population differentiation of Atlantic spotted dolphins based on a large worldwide dataset and the relationship with marine environmental variables. The results revealed that the Atlantic spotted dolphin exhibits population genetic structure across its distribution based on mitochondrial DNA control region (mtDNA-CR) data. Analyses based on the contemporary landscape suggested, at both the individual and population level, that the population genetic structure is consistent with the isolation-by-distance model. However, because geography and environmental matrices were correlated, and because in some, but not all analyses, we found a significant effect for the environment, we cannot rule out the addition contribution of environmental factors in structuring genetic variation. Future analyses based on nuclear data are needed to evaluate whether local processes, such as social structure and some level of philopatry within populations, may be contributing to the associations among genetic structure, geographic, and environmental distance.

A genetic basis for friendship? Homophily for membrane-associated PDE11A-cAMP-CREB signaling in CA1 of hippocampus dictates mutual social preference in male and female mice

Although the physical and mental benefits of friendships are clear, the neurobiological mechanisms driving mutual social preferences are not well understood. Studies in humans suggest friends are more genetically similar, particularly for targets within the 3',5'-cyclic adenosine monophosphate (cAMP) cascade. Unfortunately, human studies can not provide conclusive evidence for such a biological driver of friendship given that other genetically related factors tend to co-segregate with friendship (e.g., geographical proximity). As such, here we use mice under controlled conditions to test the hypothesis that homophily in the cAMP-degrading enzyme phosphodiesterase 11A4 (PDE11A4) can dictate mutual social preference. Using C57BL/6J and BALB/cJ mice in two different behavioral assays, we showed that mice with two intact alleles of Pde11a prefer to interact with Pde11 wild-type (WT) mice of the same genetic background over knockout (KO) mice or novel objects; whereas, Pde11 KO mice prefer to interact with Pde11 KO mice over WT mice or novel objects. This mutual social preference was seen in both adult and adolescent mice, and social preference could be eliminated or artificially elicited by strengthening or weakening PDE11A homodimerization, respectively. Stereotactic delivery of an isolated PDE11A GAF-B domain to the mouse hippocampus revealed the membrane-associated pool of PDE11A-cAMP-CREB signaling specifically within the CA1 subfield of hippocampus is most critical for regulating social preference. Our study here not only identifies PDE11A homophily as a key driver of mutual social preference across the lifespan, it offers a paradigm in which other mechanisms can be identified in a controlled fashion.

Demographic modeling informs functional connectivity and management interventions in Graham’s beardtongue

Functional connectivity (i.e., the movement of individuals across a landscape) is essential for the maintenance of genetic variation and persistence of rare species. However, illuminating the processes influencing functional connectivity and ultimately translating this knowledge into management practice remains a fundamental challenge. Here, we combine various population structure analyses with pairwise, population-specific demographic modeling to investigate historical functional connectivity in Graham’s beardtongue (Penstemon grahamii), a rare plant narrowly distributed across a dryland region of the western US. While principal component and population structure analyses indicated an isolation-by-distance pattern of differentiation across the species’ range, spatial inferences of effective migration exposed an abrupt shift in population ancestry near the range center. To understand these seemingly conflicting patterns, we tested various models of historical gene flow and found evidence for recent admixture (~ 3400 generations ago) between populations near the range center. This historical perspective reconciles population structure patterns and suggests management efforts should focus on maintaining connectivity between these previously isolated lineages to promote the ongoing transfer of genetic variation. Beyond providing species-specific knowledge to inform management options, our study highlights how understanding demographic history may be critical to guide conservation efforts when interpreting population genetic patterns and inferring functional connectivity.

A dynamic history of admixture from Mediterranean and Carpathian glacial refugia drives genomic diversity in the bank vole

Understanding the historical contributions of differing glacial refugia is key to evaluating the roles of microevolutionary forces, such as isolation, introgression, and selection in shaping genomic diversity in present-day populations. In Europe, where both Mediterranean and extra-Mediterranean (e.g., Carpathian) refugia of the bank vole (Clethrionomys glareolus) have been identified, mtDNA indicates that extra-Mediterranean refugia were the main source of colonization across the species range, while Mediterranean peninsulas harbor isolated, endemic lineages. Here, we critically evaluate this hypothesis using previously generated genomic data (>6,000 SNPs) for over 800 voles, focusing on genomic contributions to bank voles in central Europe, a key geographic area in considering range-wide colonization. The results provide clear evidence that both extra-Mediterranean (Carpathian) and Mediterranean (Spanish, Calabrian, and Balkan) refugia contributed to the ancestry and genomic diversity of bank vole populations across Europe. Few strong barriers to dispersal and frequent admixture events in central Europe have led to a prominent mid-latitude peak in genomic diversity. Although the genomic contribution of the centrally located Carpathian refugium predominates, populations in different parts of Europe have admixed origins from Mediterranean (28%-47%) and the Carpathian (53%-72%) sources. We suggest that the admixture from Mediterranean refugia may have provisioned adaptive southern alleles to more northern populations, facilitating the end-glacial spread of the admixed populations and contributing to increased bank vole diversity in central Europe. This study adds critical details to the complex end-glacial colonization history of this well-studied organism and underscores the importance of genomic data in phylogeographic interpretation.

Evaluating Causes of Current Genetic Gradients of Modern Humans of the Iberian Peninsula

The history of modern humans in the Iberian Peninsula includes a variety of population arrivals sometimes presenting admixture with resident populations. Genetic data from current Iberian populations revealed an overall east–west genetic gradient that some authors interpreted as a direct consequence of the Reconquista, where Catholic Kingdoms expanded their territories toward the south while displacing Muslims. However, this interpretation has not been formally evaluated. Here, we present a qualitative analysis of the causes of the current genetic gradient observed in the Iberian Peninsula using extensive spatially explicit computer simulations based on a variety of evolutionary scenarios. Our results indicate that the Neolithic range expansion clearly produces the orientation of the observed genetic gradient. Concerning the Reconquista (including political borders among Catholic Kingdoms and regions with different languages), if modeled upon a previous Neolithic expansion, it effectively favored the orientation of the observed genetic gradient and shows local isolation of certain regions (i.e., Basques and Galicia). Despite additional evolutionary scenarios could be evaluated to more accurately decipher the causes of the Iberian genetic gradient, here we show that this gradient has a more complex explanation than that previously hypothesized.

Population structure, inbreeding and stripe pattern abnormalities in plains zebras

One of the most iconic wild equids, the plains zebra occupies a broad region of sub-Saharan Africa and exhibits a wide range of phenotypic diversity in stripe patterns that have been used to classify multiple subspecies. After decades of relative stability, albeit with a loss of at least one recognized subspecies, the total population of plains zebras has undergone an approximate 25% decline since 2002. Individuals with abnormal stripe patterns have been recognized in recent years but the extent to which their appearance is related to demography and/or genetics is unclear. Investigating population genetic health and genetic structure are essential for developing effective strategies for plains zebra conservation. We collected DNA from 140 plains zebra, including seven with abnormal stripe patterns, from nine locations across the range of plains zebra, and analyzed data from restriction site-associated and whole genome sequencing (RAD-seq, WGS) libraries to better understand the relationships between population structure, genetic diversity, inbreeding, and abnormal phenotypes. We found that genetic structure did not coincide with described subspecific variation, but did distinguish geographic regions in which anthropogenic habitat fragmentation is associated with reduced gene flow and increased evidence of inbreeding, especially in certain parts of East Africa. Further, zebras with abnormal striping exhibited increased levels of inbreeding relative to normally striped individuals from the same populations. Our results point to a genetic cause of stripe pattern abnormalities, and dramatic evidence of the consequences of habitat fragmentation.

Dispersal barriers and opportunities drive multiple levels of phylogeographic concordance in the Southern Alps of New Zealand

Phylogeographic concordance, or the sharing of phylogeographic patterns among codistributed species, suggests similar responses to topography or climatic history. While the orientation and timing of breaks between lineages are routinely compared, spatial dynamics within regions occupied by individual lineages provide a second opportunity for comparing responses to past events. In environments with complex topography and glacial history, such as New Zealand's South Island, geographically nested comparisons can identify the processes leading to phylogeographic concordance between and within regional genomic clusters. Here, we used single nucleotide polymorphisms (obtained via ddRADseq) for two codistributed forest beetle species, Agyrtodes labralis (Leiodidae) and Brachynopus scutellaris (Staphylinidae), to evaluate the role of climate change and topography in shaping phylogeographic concordance at two, nested spatial scales: do species diverge over the same geographic barriers, with similar divergence times? And within regions delimited by these breaks, do species share similar spatial dynamics of directional expansion or isolation-by-distance? We found greater congruence of phylogeographic breaks between regions divided by the strongest dispersal barriers (i.e., the Southern Alps). However, these shared breaks were not indicative of shared spatial dynamics within the regions they delimit, and the most similar spatial dynamics between species occurred within regions with the strongest gradients in historical climatic stability. Our results indicate that lack of concordance as traditionally detected by lineage turnover does not rule out the possibility of shared histories, and variation in the presence and type of concordance may provide insights into the different processes shaping phylogeographic patterns across geologically dynamic regions.

Population Genetic Structure and Demographic History of Primula fasciculata in Southwest China

Understanding the factors that drive the genetic structure of a species and its responses to past climatic changes is an important first step in modern population management. The response to the last glacial maximum (LGM) has been well studied, however, the effect of previous glaciation periods on plant demographic history is still not well studied. Here we investigated the population structure and demographic history of Primula fasciculata that widely occurs in the Hengduan Mountains and Qinghai-Tibetan Plateau. We obtained genomic data for 234 samples of the species using restriction site-associated DNA (RAD) sequencing and combined approximate Bayesian computation (ABC) and species distribution modeling (SDM) to evaluate the effects of multiple glaciation periods by testing several population divergence models and demographic scenarios. The analyses of population structure showed that P. fasciculata displays a striking population structure with six groups that could be identified genetically. Our ABC modeling suggested that the current groups diverged from ancestral populations located in the eastern Hengduan Mountains after the largest glaciation occurred in the region (~ 0.8-0.5 million years ago), which is consistent with the result of SDMs. Each current group has survived in different glacial refugia during the LGM and experienced expansions and/or bottlenecks since their divergence during or across the following Quaternary glacial cycles. Our study demonstrates the usefulness of population genomics for evaluating the effects of past climatic changes in alpine plant species with shallow population structure.

Demographic correlates of inflammatory and antiviral gene expression in the study of Midlife in the United States (MIDUS)

The present study examined the demographic correlates of gene expression in a sample of adults (n = 543) from the Study of Midlife in the United States (MIDUS). Inflammatory and antiviral gene sets were operationalized using a priori composite scores and empirically derived co-regulatory gene sets. For both composite scores and co-regulatory gene sets, White/European Americans showed lower while Black/African Americans showed higher expression of genes involved in interferon responses and antibody synthesis. The effects of chronological age on gene expression varied by sex, such that pro-inflammatory gene expression increased with age more rapidly for females than males. The difference between the average expression of inflammatory and antiviral genes also increased with age for females but not males. Results shed light on differential gene expression as a potential physiological correlate for race/ethnicity, age, and sex-related health disparities in adulthood.

Genetic Landscapes Reveal How Human Genetic Diversity Aligns with Geography

Geographic patterns in human genetic diversity carry footprints of population history and provide insights for genetic medicine and its application across human populations. Summarizing and visually representing these patterns of diversity has been a persistent goal for human geneticists, and has revealed that genetic differentiation is frequently correlated with geographic distance. However, most analytical methods to represent population structure do not incorporate geography directly, and it must be considered post hoc alongside a visual summary of the genetic structure. Here, we estimate "effective migration" surfaces to visualize how human genetic diversity is geographically structured. The results reveal local patterns of differentiation in detail and emphasize that while genetic similarity generally decays with geographic distance, the relationship is often subtly distorted. Overall, the visualizations provide a new perspective on genetics and geography in humans and insight to the geographic distribution of human genetic variation.

Unique bacterial assembly, composition, and interactions in a parasitic plant and its host

How plant-associated microbiota are shaped by, and potentially contribute to, the unique ecology and heterotrophic life history of parasitic plants is relatively unknown. Here, we investigate the leaf and root bacterial communities of the root holoparasite Orobanche hederae and its host Hedera spp. from natural populations. Root bacteria inhabiting Orobanche were less diverse, had fewer co-associations, and displayed increased compositional similarity to leaf bacteria relative to Hedera. Overall, Orobanche bacteria exhibited significant congruency with Hedera root bacteria across sites, but not the surrounding soil. Infection had localized and systemic effects on Hedera bacteria, which included effects on the abundance of individual taxa and root network properties. Collectively, our results indicate that the parasitic plant microbiome is derived but distinct from the host plant microbiota, exhibits increased homogenization between shoot and root tissues, and displays far fewer co-associations among individual bacterial members. Host plant infection is accompanied by modest changes of associated microbiota at both local and systemic scales compared with uninfected individuals. Our results are a first step towards extending the growing insight into the assembly and function of the plant microbiome to include the ecologically unique but often overlooked guild of heterotrophic plants.

Consequences of PCA graphs, SNP codings, and PCA variants for elucidating population structure

SNP datasets are high-dimensional, often with thousands to millions of SNPs and hundreds to thousands of samples or individuals. Accordingly, PCA graphs are frequently used to provide a low-dimensional visualization in order to display and discover patterns in SNP data from humans, animals, plants, and microbes—especially to elucidate population structure. PCA is not a single method that is always done the same way, but rather requires three choices which we explore as a three-way factorial: two kinds of PCA graphs by three SNP codings by six PCA variants. Our main three recommendations are simple and easily implemented: Use PCA biplots, SNP coding 1 for the rare allele and 0 for the common allele, and double-centered PCA (or AMMI1 if main effects are also of interest). We also document contemporary practices by a literature survey of 125 representative articles that apply PCA to SNP data, find that virtually none implement our recommendations. The ultimate benefit from informed and optimal choices of PCA graph, SNP coding, and PCA variant, is expected to be discovery of more biology, and thereby acceleration of medical, agricultural, and other vital applications.

The genetic history of admixture across inner Eurasia

The indigenous populations of inner Eurasia-a huge geographic region covering the central Eurasian steppe and the northern Eurasian taiga and tundra-harbour tremendous diversity in their genes, cultures and languages. In this study, we report novel genome-wide data for 763 individuals from Armenia, Georgia, Kazakhstan, Moldova, Mongolia, Russia, Tajikistan, Ukraine and Uzbekistan. We furthermore report additional damage-reduced genome-wide data of two previously published individuals from the Eneolithic Botai culture in Kazakhstan (~5,400 BP). We find that present-day inner Eurasian populations are structured into three distinct admixture clines stretching between various western and eastern Eurasian ancestries, mirroring geography. The Botai and more recent ancient genomes from Siberia show a decrease in contributions from so-called 'ancient North Eurasian' ancestry over time, which is detectable only in the northern-most 'forest-tundra' cline. The intermediate 'steppe-forest' cline descends from the Late Bronze Age steppe ancestries, while the 'southern steppe' cline further to the south shows a strong West/South Asian influence. Ancient genomes suggest a northward spread of the southern steppe cline in Central Asia during the first millennium BC. Finally, the genetic structure of Caucasus populations highlights a role of the Caucasus Mountains as a barrier to gene flow and suggests a post-Neolithic gene flow into North Caucasus populations from the steppe.

Spatially explicit analysis reveals complex human genetic gradients in the Iberian Peninsula

The Iberian Peninsula is a well-delimited geographic region with a rich and complex human history. However, the causes of its genetic structure and past migratory dynamics are not yet fully understood. In order to shed light on them, here we evaluated the gene flow and genetic structure throughout the Iberian Peninsula with spatially explicit modelling applied to a georeferenced genetic dataset composed of genome-wide SNPs from 746 individuals belonging to 17 different regions of the Peninsula. We found contrasting patterns of genetic structure throughout Iberia. In particular, we identified strong patterns of genetic differentiation caused by relevant barriers to gene flow in northern regions and, on the other hand, a large genetic similarity in central and southern regions. In addition, our results showed a preferential north to south migratory dynamics and suggest a sex-biased dispersal in Mediterranean and southern regions. The estimated genetic patterns did not fit with the geographical relief of the Iberian landscape and they rather seem to follow political and linguistic territorial boundaries.

A genetic portrait of the South-Eastern Carpathians based on autosomal short tandem repeats loci used in forensics

OBJECTIVES

This work aimed to describe the genetic landscape of the Balkan Peninsula, as revealed by STR markers commonly used in forensics and spatial methods specifically developed for genetic data.

METHODS

We generated and analyzed 16 short tandem repeats (STRs) autosomal genotypes in 287 subjects from ten administrative/geographical regions of Eastern Europe (Romania and the Republic of Moldova). We report estimates of the allele frequencies in these sub-populations, their fixation indexes, and use these results to complement previous spatial analyses of Southern Europe.

RESULTS

In seven out of ten analyzed regional samples the heterozygosity, averaged across loci, was lower than expected. The average Fis was 0.011. Among the 16 loci, five returned a significant fixation index Fst. The composite Fst across the 16 loci, among the 10 regional samples, was 0.00417, a figure twice as large as that obtained with the same markers across the entire Northern Mediterranean. The first spatial principal component (sPC1) returned the picture of a Central-European pattern of frequencies for the Carpathians, which extended to the Southern boundary of the Balkan Peninsula. However, the 8 alleles extracted by sPC1 returned a picture of a strong reduction of the migration rate in the Carpathian region, mostly between the inner locations.

CONCLUSIONS

Our results revealed an unexpected heterogeneity in the area. We believe that populations from some regions will require treatment as distinct entities when considered in forensic applications.

Complex genetic patterns in human arise from a simple range-expansion model over continental landmasses

Although it is generally accepted that geography is a major factor shaping human genetic differentiation, it is still disputed how much of this differentiation is a result of a simple process of isolation-by-distance, and if there are factors generating distinct clusters of genetic similarity. We address this question using a geographically explicit simulation framework coupled with an Approximate Bayesian Computation approach. Based on six simple summary statistics only, we estimated the most probable demographic parameters that shaped modern human evolution under an isolation by distance scenario, and found these were the following: an initial population in East Africa spread and grew from 4000 individuals to 5.7 million in about 132 000 years. Subsequent simulations with these estimates followed by cluster analyses produced results nearly identical to those obtained in real data. Thus, a simple diffusion model from East Africa explains a large portion of the genetic diversity patterns observed in modern humans. We argue that a model of isolation by distance along the continental landmasses might be the relevant null model to use when investigating selective effects in humans and probably many other species.

Evaluating methods to visualize patterns of genetic differentiation on a landscape

With advances in sequencing technology, research in the field of landscape genetics can now be conducted at unprecedented spatial and genomic scales. This has been especially evident when using sequence data to visualize patterns of genetic differentiation across a landscape due to demographic history, including changes in migration. Two recent model-based visualization methods that can highlight unusual patterns of genetic differentiation across a landscape, SpaceMix and EEMS, are increasingly used. While SpaceMix's model can infer long-distance migration, EEMS' model is more sensitive to short-distance changes in genetic differentiation, and it is unclear how these differences may affect their results in various situations. Here, we compare SpaceMix and EEMS side by side using landscape genetics simulations representing different migration scenarios. While both methods excel when patterns of simulated migration closely match their underlying models, they can produce either un-intuitive or misleading results when the simulated migration patterns match their models less well, and this may be difficult to assess in empirical data sets. We also introduce unbundled principal components (un-PC), a fast, model-free method to visualize patterns of genetic differentiation by combining principal components analysis (PCA), which is already used in many landscape genetics studies, with the locations of sampled individuals. Un-PC has characteristics of both SpaceMix and EEMS and works well with simulated and empirical data. Finally, we introduce msLandscape, a collection of tools that streamline the creation of customizable landscape-scale simulations using the popular coalescent simulator ms and conversion of the simulated data for use with un-PC, SpaceMix and EEMS.

On the substructure controls in rare variant analysis: Principal components or variance components?

Recent studies showed that population substructure (PS) can have more complex impact on rare variant tests and that similarity-based collapsing tests (e.g., SKAT) may suffer more severely by PS than burden-based tests. In this work, we evaluate the performance of SKAT coupling with principal components (PC) or variance components (VC) based PS correction methods. We consider confounding effects caused by PS including stratified populations, admixed populations, and spatially distributed nongenetic risk; we investigate which types of variants (e.g., common, less frequent, rare, or all variants) should be used to effectively control for confounding effects. We found that (i) PC-based methods can account for confounding effects in most scenarios except for admixture, although the number of sufficient PCs depends on the PS complexity and the type of variants used. (ii) PCs based on all variants (i.e., common + less frequent + rare) tend to require equal or fewer sufficient PCs and often achieve higher power than PCs based on other variant types. (iii) VC-based methods can effectively adjust for confounding in all scenarios (even for admixture), though the type of variants should be used to construct VC may vary. (iv) VC based on all variants works consistently in all scenarios, though its power may be sometimes lower than VC based on other variant types. Given that the best-performed method and which variants to use depend on the underlying unknown confounding mechanisms, a robust strategy is to perform SKAT analyses using VC-based methods based on all variants.

Inferring the geographic origin of a range expansion: Latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program x-origin

Climatic or environmental change is not only driving distributional shifts in species today, but it has also caused distributions to expand and contract in the past. Inferences about the geographic locations of past populations especially regions that served as refugia (i.e., source populations) and migratory routes are a challenging endeavour. Refugial areas may be evidenced from fossil records or regions of temporal stability inferred from ecological niche models. Genomic data offer an alternative and broadly applicable source of information about the locality of refugial areas, especially relative to fossil data, which are either unavailable or incomplete for most species. Here, we present a pipeline we developed (called x-origin) for statistically inferring the geographic origin of range expansion using a spatially explicit coalescent model and an approximate Bayesian computation testing framework. In addition to assessing the probability of specific latitudinal and longitudinal coordinates of refugial or source populations, such inferences can also be made accounting for the effects of temporal and spatial environmental heterogeneity, which may impact migration routes. We demonstrate x-origin with an analysis of genomic data collected in the Collared pika that underwent postglacial expansion across Alaska, as well as present an assessment of its accuracy under a known model of expansion to validate the approach.

Population Stratification in Genetic Association Studies

Population stratification (PS) is a primary consideration in studies of genetic determinants of human traits. Failure to control for PS may lead to confounding, causing a study to fail for lack of significant results, or resources to be wasted following false-positive signals. Here, historical and current approaches for addressing PS when performing genetic association studies in human populations are reviewed. Methods for detecting the presence of PS, including global and local ancestry methods, are described. Also described are approaches for accounting for PS when calculating association statistics, such that measures of association are not confounded. Many traits are being examined for the first time in minority populations, which may inherently feature PS. © 2017 by John Wiley & Sons, Inc.

mvmapper: Interactive spatial mapping of genetic structures

Characterizing genetic structure across geographic space is a fundamental challenge in population genetics. Multivariate statistical analyses are powerful tools for summarizing genetic variability, but geographic information and accompanying metadata are not always easily integrated into these methods in a user-friendly fashion. Here, we present a deployable Python-based web-tool, mvmapper, for visualizing and exploring results of multivariate analyses in geographic space. This tool can be used to map results of virtually any multivariate analysis of georeferenced data, and routines for exporting results from a number of standard methods have been integrated in the R package adegenet, including principal components analysis (PCA), spatial PCA, discriminant analysis of principal components, principal coordinates analysis, nonmetric dimensional scaling and correspondence analysis. mvmapper's greatest strength is facilitating dynamic and interactive exploration of the statistical and geographic frameworks side by side, a task that is difficult and time-consuming with currently available tools. Source code and deployment instructions, as well as a link to a hosted instance of mvmapper, can be found at https://popphylotools.github.io/mvMapper/.

Subspecies delineation amid phenotypic, geographic and genetic discordance in a songbird

Understanding the processes that drive divergence within and among species is a long-standing goal in evolutionary biology. Traditional approaches to assessing differentiation rely on phenotypes to identify intra- and interspecific variation, but many species express subtle morphological gradients in which boundaries among forms are unclear. This intraspecific variation may be driven by differential adaptation to local conditions and may thereby reflect the evolutionary potential within a species. Here, we combine genetic and morphological data to evaluate intraspecific variation within the Nelson's (Ammodramus nelsoni) and salt marsh (Ammodramus caudacutus) sparrow complex, a group with populations that span considerable geographic distributions and a habitat gradient. We evaluated genetic structure among and within five putative subspecies of A. nelsoni and A. caudacutus using a reduced-representation sequencing approach to generate a panel of 1929 SNPs among 69 individuals. Although we detected morphological differences among some groups, individuals sorted along a continuous phenotypic gradient. In contrast, the genetic data identified three distinct clusters corresponding to populations that inhabit coastal salt marsh, interior freshwater marsh and coastal brackish-water marsh habitats. These patterns support the current species-level recognition but do not match the subspecies-level taxonomy within each species-a finding which may have important conservation implications. We identified loci exhibiting patterns of elevated divergence among and within these species, indicating a role for local selective pressures in driving patterns of differentiation across the complex. We conclude that this evidence for adaptive variation among subspecies warrants the consideration of evolutionary potential and genetic novelty when identifying conservation units for this group.

Genetic consequences of Quaternary climatic oscillations in the Himalayas: Primula tibetica as a case study based on restriction site-associated DNA sequencing

The effects of Quaternary climatic oscillations on the demography of organisms vary across regions and continents. In taxa distributed in Europe and North America, several paradigms regarding the distribution of refugia have been identified. By contrast, less is known about the processes that shaped the species' spatial genetic structure in areas such as the Himalayas, which is considered a biodiversity hotspot. Here, we investigated the phylogeographic structure and population dynamics of Primula tibetica by combining genomic phylogeography and species distribution models (SDMs). Genomic data were obtained for 293 samples of P. tibetica using restriction site-associated DNA sequencing (RADseq). Ensemble SDMs were carried out to predict potential present and past distribution ranges. Four distinct lineages were identified. Approximate Bayesian computation analyses showed that each of them have experienced both expansions and bottlenecks since their divergence, which occurred during or across the Quaternary glacial cycles. The two lineages at both edges of the distribution were found to be more vulnerable and responded in different ways to past climatic changes. These results illustrate how past climatic changes affected the demographic history of Himalayan organisms. Our findings highlight the significance of combining genomic approaches with environmental data when evaluating the effects of past climatic changes.

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

Genetic diversity and divergence among Spanish beef cattle breeds assessed by a bovine high-density SNP chip

The availability of SNP chips for massive genotyping has proven to be useful to genetically characterize populations of domestic cattle and to assess their degree of divergence. In this study, the Illumina BovineHD BeadChip genotyping array was used to describe the genetic variability and divergence among 7 important autochthonous Spanish beef cattle breeds. The within-breed genetic diversity, measured as the marker expected heterozygosity, was around 0.30, similar to other European cattle breeds. The analysis of molecular variance revealed that 94.22% of the total variance was explained by differences within individuals whereas only 4.46% was the result of differences among populations. The degree of genetic differentiation was small to moderate as the pairwise fixation index of genetic differentiation among breeds (F) estimates ranged from 0.026 to 0.068 and the Nei's D genetic distances ranged from 0.009 to 0.016. A neighbor joining (N-J) phylogenetic tree showed 2 main groups of breeds: Pirenaica, Bruna dels Pirineus, and Rubia Gallega on the one hand and Avileña-Negra Ibérica, Morucha, and Retinta on the other. In turn, Asturiana de los Valles occupied an independent and intermediate position. A principal component analysis (PCA) applied to a distance matrix based on marker identity by state, in which the first 2 axes explained up to 17.3% of the variance, showed a grouping of animals that was similar to the one observed in the N-J tree. Finally, a cluster analysis for ancestries allowed assigning all the individuals to the breed they belong to, although it revealed some degree of admixture among breeds. Our results indicate large within-breed diversity and a low degree of divergence among the autochthonous Spanish beef cattle breeds studied. Both N-J and PCA groupings fit quite well to the ancestral trunks from which the Spanish beef cattle breeds were supposed to derive.