Human migrations and population structure: what we know and why it matters

Migrants' mental health recovery in Italian reception facilities

BACKGROUND

Forced migration leaves deep marks on the psychological well-being of migrants, with post-traumatic stress disorder (PTSD) and other psychological conditions being prevalent among them. While research has clarified the extent to which pre-migration trauma is a predictor of mental health outcomes, the role of post-migration stressors in the settlement environment are yet to be fully characterized.

METHODS

We monitored mental health of a cohort of 100 asylum-seekers during their 14-day COVID-19-related quarantine in reception facilities in Rome, Italy, through the administration of six questionnaires (a demographic survey, the WHO-5 well-being index, the Primary Care PTSD Screen for Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5), the Harvard Trauma Questionnaire, the Trauma and Loss Spectrum-Self Report, and the LiMEs-Italian version). Through the combination of statistical analysis and supervised learning, we studied the impact of the first contact with the reception system on asylum-seekers' mental health and sought for possible risk and shielding factors for PTSD.

RESULTS

We find that sheltering in refugee centers has a positive impact on migrants' mental health; asylum-seekers with PTSD reported more traumatic events and personality characteristics related to loss and trauma; life events are predictors of PTSD in asylum-seekers.

CONCLUSIONS

We identify past traumatic experiences as predictors of PTSD, and establish the positive role the immediate post-migration environment can play on migrants' psychological well-being. We recommend for host countries to implement reception models that provide effective protection and integration of asylum-seekers, similar to those in the Italian system.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

Inference with selection, varying population size, and evolving population structure: application of ABC to a forward-backward coalescent process with interactions

Genetic data are often used to infer demographic history and changes or detect genes under selection. Inferential methods are commonly based on models making various strong assumptions: demography and population structures are supposed a priori known, the evolution of the genetic composition of a population does not affect demography nor population structure, and there is no selection nor interaction between and within genetic strains. In this paper, we present a stochastic birth-death model with competitive interactions and asexual reproduction. We develop an inferential procedure for ecological, demographic, and genetic parameters. We first show how genetic diversity and genealogies are related to birth and death rates, and to how individuals compete within and between strains. This leads us to propose an original model of phylogenies, with trait structure and interactions, that allows multiple merging. Second, we develop an Approximate Bayesian Computation framework to use our model for analyzing genetic data. We apply our procedure to simulated data from a toy model, and to real data by analyzing the genetic diversity of microsatellites on Y-chromosomes sampled from Central Asia human populations in order to test whether different social organizations show significantly different fertilities.

The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure

In the last years, a wide range of methods allowing to reconstruct past population size changes from genome-wide data have been developed. At the same time, there has been an increasing recognition that population structure can generate genetic data similar to those produced under models of population size change. Recently, Mazet et al. (Heredity 116:362-371, 2016) showed that, for any model of population structure, it is always possible to find a panmictic model with a particular function of population size changes, having exactly the same distribution of T₂ (the coalescence time for a sample of size two) as that of the structured model. They called this function IICR (Inverse Instantaneous Coalescence Rate) and showed that it does not necessarily correspond to population size changes under non-panmictic models. Besides, most of the methods used to analyse data under models of population structure tend to arbitrarily fix that structure and to minimise or neglect population size changes. Here, we extend the seminal work of Herbots (PhD thesis, University of London, 1994) on the structured coalescent and propose a new framework, the Non-Stationary Structured Coalescent (NSSC) that incorporates demographic events (changes in gene flow and/or deme sizes) to models of nearly any complexity. We show how to compute the IICR under a wide family of stationary and non-stationary models. As an example we address the question of human and Neanderthal evolution and discuss how the NSSC framework allows to interpret genomic data under this new perspective.

Did Our Species Evolve in Subdivided Populations across Africa, and Why Does It Matter?

We challenge the view that our species, Homo sapiens, evolved within a single population and/or region of Africa. The chronology and physical diversity of Pleistocene human fossils suggest that morphologically varied populations pertaining to the H. sapiens clade lived throughout Africa. Similarly, the African archaeological record demonstrates the polycentric origin and persistence of regionally distinct Pleistocene material culture in a variety of paleoecological settings. Genetic studies also indicate that present-day population structure within Africa extends to deep times, paralleling a paleoenvironmental record of shifting and fractured habitable zones. We argue that these fields support an emerging view of a highly structured African prehistory that should be considered in human evolutionary inferences, prompting new interpretations, questions, and interdisciplinary research directions.

The view that Homo sapiens evolved from a single region/population within Africa has been given primacy in studies of human evolution.

However, developments across multiple fields show that relevant data are no longer consistent with this view.

We argue instead that Homo sapiens evolved within a set of interlinked groups living across Africa, whose connectivity changed through time.

Genetic models therefore need to incorporate a more complex view of ancient migration and divergence in Africa.

We summarize this new framework emphasizing population structure, outline how this changes our understanding of human evolution, and identify new research directions.

Human bony labyrinth is an indicator of population history and dispersal from Africa

The cavity system of the inner ear—the so-called bony labyrinth—houses the senses of balance and hearing. This structure is embedded in dense petrous bone, fully formed by birth and generally well preserved in human skeletal remains, thus providing a rich source of morphological information about past populations. Here we show that labyrinthine morphology tracks genetic distances and geography in an isolation-by-distance model with dispersal from Africa. Because petrous bones have become prime targets of ancient DNA recovery, we propose that all destructive studies first acquire high-resolution 3D computed-tomography data prior to any invasive sampling. Such data will constitute an important archive of morphological variation in past and present populations, and will permit individual-based genotype–phenotype comparisons.

The dispersal of modern humans from Africa is now well documented with genetic data that track population history, as well as gene flow between populations. Phenetic skeletal data, such as cranial and pelvic morphologies, also exhibit a dispersal-from-Africa signal, which, however, tends to be blurred by the effects of local adaptation and in vivo phenotypic plasticity, and that is often deteriorated by postmortem damage to skeletal remains. These complexities raise the question of which skeletal structures most effectively track neutral population history. The cavity system of the inner ear (the so-called bony labyrinth) is a good candidate structure for such analyses. It is already fully formed by birth, which minimizes postnatal phenotypic plasticity, and it is generally well preserved in archaeological samples. Here we use morphometric data of the bony labyrinth to show that it is a surprisingly good marker of the global dispersal of modern humans from Africa. Labyrinthine morphology tracks genetic distances and geography in accordance with an isolation-by-distance model with dispersal from Africa. Our data further indicate that the neutral-like pattern of variation is compatible with stabilizing selection on labyrinth morphology. Given the increasingly important role of the petrous bone for ancient DNA recovery from archaeological specimens, we encourage researchers to acquire 3D morphological data of the inner ear structures before any invasive sampling. Such data will constitute an important archive of phenotypic variation in present and past populations, and will permit individual-based genotype–phenotype comparisons.

Evolutionary Patterns and Processes: Lessons from Ancient DNA

Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution—time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data.

Estimating mobility using sparse data: Application to human genetic variation

Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter-gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time.

Beyond mean allelic effects: A locus at the major color gene MC1R associates also with differing levels of phenotypic and genetic (co)variance for coloration in barn owls

The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype.

[aDNA Research From a Historical Perspective]

aDNA studies are a cooperative field of research with a broad range of applications including evolutionary biology, genetics, anthropology and archaeology. Scientists are using ancient molecules as source material for historical questions. Colleagues from the humanities are observing this with both interest and concern because aDNA research is affecting academic identities and both concepts of history and historiography. aDNA research developed in a way that can be described as a Hype Cycle (Chackie Fenn). Technological triggers such as Sanger Sequencing and the Polymerase Chain Reaction kicked off a multitude of experiments with ancient DNA during the 1980s and 1990s. Geneticists, microbiologists, anthropologists and many more euphorically joined a "molecule hunt". aDNA was promoted as a time machine. Media attention was enormous. As experiments and implementations began to fail and contamination was discovered to be a tremendous problem, media interest waned and many labs lost their interest. Some turned their disillusionment into systematic research into methodology and painstakingly established lab routines. The authenticity problem was first addressed by control oriented measures but later approached from a more cognitive theoretical perspective as the pitfalls and limits of aDNA became clearer. By the end of the 2000s the field reached its current plateau of productivity. Cross-disciplinary debates, conflicts and collaborations are increasing critical reflection among all participants. Historians should consider joining the field in a kind of critical friendship to both make the most of its possibilities and give an input from a constructivist perspective.

High mutation rates explain low population genetic divergence at copy-number-variable loci in Homo sapiens

Copy-number-variable (CNV) loci differ from single nucleotide polymorphic (SNP) sites in size, mutation rate, and mechanisms of maintenance in natural populations. It is therefore hypothesized that population genetic divergence at CNV loci will differ from that found at SNP sites. Here, we test this hypothesis by analysing 856 CNV loci from the genomes of 1184 healthy individuals from 11 HapMap populations with a wide range of ancestry. The results show that population genetic divergence at the CNV loci is generally more than three times lower than at genome-wide SNP sites. Populations generally exhibit very small genetic divergence (G_st = 0.05 ± 0.049). The smallest divergence is among African populations (G_st = 0.0081 ± 0.0025), with increased divergence among non-African populations (G_st = 0.0217 ± 0.0109) and then among African and non-African populations (G_st = 0.0324 ± 0.0064). Genetic diversity is high in African populations (~0.13), low in Asian populations (~0.11), and intermediate in the remaining 11 populations. Few significant linkage disequilibria (LDs) occur between the genome-wide CNV loci. Patterns of gametic and zygotic LDs indicate the absence of epistasis among CNV loci. Mutation rate is about twice as large as the migration rate in the non-African populations, suggesting that the high mutation rates play dominant roles in producing the low population genetic divergence at CNV loci.

Human Dispersal Out of Africa: A Lasting Debate

Unraveling the first migrations of anatomically modern humans out of Africa has invoked great interest among researchers from a wide range of disciplines. Available fossil, archeological, and climatic data offer many hypotheses, and as such genetics, with the advent of genome-wide genotyping and sequencing techniques and an increase in the availability of ancient samples, offers another important tool for testing theories relating to our own history. In this review, we report the ongoing debates regarding how and when our ancestors left Africa, how many waves of dispersal there were and what geographical routes were taken. We explore the validity of each, using current genetic literature coupled with some of the key archeological findings.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

Molecular data sampled from extant individuals contains considerable information about their demographic history. In particular, one classical question in population genetics is to reconstruct past population size changes from such data. Relating these changes to various climatic, geological or anthropogenic events allows characterizing the main factors driving genetic diversity and can have major outcomes for conservation. Until recently, mostly very simple histories, including one or two population size changes, could be estimated from genetic data. This has changed with the sequencing of entire genomes in many species, and several methods allow now inferring complex histories consisting of several tens of population size changes. However, analyzing entire genomes, while accounting for recombination, remains a statistical and numerical challenge. These methods, therefore, can only be applied to small samples with a few diploid genomes. We overcome this limitation by using an approximate estimation approach, where observed genomes are summarized using a small number of statistics related to allele frequencies and linkage disequilibrium. In contrast to previous approaches, we show that our method allows us to reconstruct also the most recent part (the last 100 generations) of the population size history. As an illustration, we apply it to large samples of whole-genome sequences in four cattle breeds.

On the importance of being structured: instantaneous coalescence rates and human evolution--lessons for ancestral population size inference?

Most species are structured and influenced by processes that either increased or reduced gene flow between populations. However, most population genetic inference methods assume panmixia and reconstruct a history characterized by population size changes. This is potentially problematic as population structure can generate spurious signals of population size change through time. Moreover, when the model assumed for demographic inference is misspecified, genomic data will likely increase the precision of misleading if not meaningless parameters. For instance, if data were generated under an n-island model (characterized by the number of islands and migrants exchanged) inference based on a model of population size change would produce precise estimates of a bottleneck that would be meaningless. In addition, archaeological or climatic events around the bottleneck's timing might provide a reasonable but potentially misleading scenario. In a context of model uncertainty (panmixia versus structure) genomic data may thus not necessarily lead to improved statistical inference. We consider two haploid genomes and develop a theory that explains why any demographic model with structure will necessarily be interpreted as a series of changes in population size by inference methods ignoring structure. We formalize a parameter, the inverse instantaneous coalescence rate, and show that it is equivalent to a population size only in panmictic models, and is mostly misleading for structured models. We argue that this issue affects all population genetics methods ignoring population structure which may thus infer population size changes that never took place. We apply our approach to human genomic data.

Genomic Scans of Zygotic Disequilibrium and Epistatic SNPs in HapMap Phase III Populations

Previous theory indicates that zygotic linkage disequilibrium (LD) is more informative than gametic or composite digenic LD in revealing natural population history. Further, the difference between the composite digenic and maximum zygotic LDs can be used to detect epistatic selection for fitness. Here we corroborate the theory by investigating genome-wide zygotic LDs in HapMap phase III human populations. Results show that non-Africa populations have much more significant zygotic LDs than do Africa populations. Africa populations (ASW, LWK, MKK, and YRI) possess more significant zygotic LDs for the double-homozygotes (D_AABB) than any other significant zygotic LDs (D_AABb, D_AaBB, and D_AaBb), while non-Africa populations generally have more significant D_AaBb’s than any other significant zygotic LDs (D_AABB, D_AABb, and D_AaBB). Average r-squares for any significant zygotic LDs increase generally in an order of populations YRI, MKK, CEU, CHB, LWK, JPT, CHD, TSI, GIH, ASW, and MEX. Average r-squares are greater for D_AABB and D_AaBb than for D_AaBB and D_AABb in each population. YRI and MKK can be separated from LWK and ASW in terms of the pattern of average r-squares. All population divergences in zygotic LDs can be interpreted with the model of Out of Africa for modern human origins. We have also detected 19735-95921 SNP pairs exhibiting strong signals of epistatic selection in different populations. Gene-gene interactions for some epistatic SNP pairs are evident from empirical findings, but many more epistatic SNP pairs await evidence. Common epistatic SNP pairs rarely exist among all populations, but exist in distinct regions (Africa, Europe, and East Asia), which helps to understand geographical genomic medicine.

Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology

With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

Detecting and measuring selection from gene frequency data

The recent advent of high-throughput sequencing and genotyping technologies makes it possible to produce, easily and cost effectively, large amounts of detailed data on the genotype composition of populations. Detecting locus-specific effects may help identify those genes that have been, or are currently, targeted by natural selection. How best to identify these selected regions, loci, or single nucleotides remains a challenging issue. Here, we introduce a new model-based method, called SelEstim, to distinguish putative selected polymorphisms from the background of neutral (or nearly neutral) ones and to estimate the intensity of selection at the former. The underlying population genetic model is a diffusion approximation for the distribution of allele frequency in a population subdivided into a number of demes that exchange migrants. We use a Markov chain Monte Carlo algorithm for sampling from the joint posterior distribution of the model parameters, in a hierarchical Bayesian framework. We present evidence from stochastic simulations, which demonstrates the good power of SelEstim to identify loci targeted by selection and to estimate the strength of selection acting on these loci, within each deme. We also reanalyze a subset of SNP data from the Stanford HGDP-CEPH Human Genome Diversity Cell Line Panel to illustrate the performance of SelEstim on real data. In agreement with previous studies, our analyses point to a very strong signal of positive selection upstream of the LCT gene, which encodes for the enzyme lactase-phlorizin hydrolase and is associated with adult-type hypolactasia. The geographical distribution of the strength of positive selection across the Old World matches the interpolated map of lactase persistence phenotype frequencies, with the strongest selection coefficients in Europe and in the Indus Valley.

Next-generation sequencing in schizophrenia and other neuropsychiatric disorders

Schizophrenia is a debilitating lifelong illness that lacks a cure and poses a worldwide public health burden. The disease is characterized by a heterogeneous clinical and genetic presentation that complicates research efforts to identify causative genetic variations. This review examines the potential of current findings in schizophrenia and in other related neuropsychiatric disorders for application in next-generation technologies, particularly whole-exome sequencing (WES) and whole-genome sequencing (WGS). These approaches may lead to the discovery of underlying genetic factors for schizophrenia and may thereby identify and target novel therapeutic targets for this devastating disorder.

Coalescent-based method for learning parameters of admixture events from large-scale genetic variation data

Detecting and quantifying the timing and the genetic contributions of parental populations to a hybrid population is an important but challenging problem in reconstructing evolutionary histories from genetic variation data. With the advent of high throughput genotyping technologies, new methods suitable for large-scale data are especially needed. Furthermore, existing methods typically assume the assignment of individuals into subpopulations is known, when that itself is a difficult problem often unresolved for real data. Here, we propose a novel method that combines prior work for inferring non reticulate population structures with an MCMC scheme for sampling over admixture scenarios to both identify population assignments and learn divergence times and admixture proportions for those populations using genome-scale admixed genetic variation data. We validated our method using coalescent simulations and a collection of real bovine and human variation data. On simulated sequences, our methods show better accuracy and faster run time than leading competitive methods in estimating admixture fractions and divergence times. Analysis on the real data further shows our methods to be effective at matching our best current knowledge about the relevant populations.

On the structural plasticity of the human genome: chromosomal inversions revisited

With the aid of novel and powerful molecular biology techniques, recent years have witnessed a dramatic increase in the number of studies reporting the involvement of complex structural variants in several genomic disorders. In fact, with the discovery of Copy Number Variants (CNVs) and other forms of unbalanced structural variation, much attention has been directed to the detection and characterization of such rearrangements, as well as the identification of the mechanisms involved in their formation. However, it has long been appreciated that chromosomes can undergo other forms of structural changes - balanced rearrangements - that do not involve quantitative variation of genetic material. Indeed, a particular subtype of balanced rearrangement – inversions – was recently found to be far more common than had been predicted from traditional cytogenetics. Chromosomal inversions alter the orientation of a specific genomic sequence and, unless involving breaks in coding or regulatory regions (and, disregarding complex trans effects, in their close vicinity), appear to be phenotypically silent. Such a surprising finding, which is difficult to reconcile with the classical interpretation of inversions as a mechanism causing subfertility (and ultimately reproductive isolation), motivated a new series of theoretical and empirical studies dedicated to understand their role in human genome evolution and to explore their possible association to complex genetic disorders. With this review, we attempt to describe the latest methodological improvements to inversions detection at a genome wide level, while exploring some of the possible implications of inversion rearrangements on the evolution of the human genome.

Female and male perspectives on the neolithic transition in Europe: clues from ancient and modern genetic data

The arrival of agriculture into Europe during the Neolithic transition brought a significant shift in human lifestyle and subsistence. However, the conditions under which the spread of the new culture and technologies occurred are still debated. Similarly, the roles played by women and men during the Neolithic transition are not well understood, probably due to the fact that mitochondrial DNA (mtDNA) and Y chromosome (NRY) data are usually studied independently rather than within the same statistical framework. Here, we applied an integrative approach, using different model-based inferential techniques, to analyse published datasets from contemporary and ancient European populations. By integrating mtDNA and NRY data into the same admixture approach, we show that both males and females underwent the same admixture history and both support the demic diffusion model of Ammerman and Cavalli-Sforza. Similarly, the patterns of genetic diversity found in extant and ancient populations demonstrate that both modern and ancient mtDNA support the demic diffusion model. They also show that population structure and differential growth between farmers and hunter-gatherers are necessary to explain both types of data. However, we also found some differences between male and female markers, suggesting that the female effective population size was larger than that of the males, probably due to different demographic histories. We argue that these differences are most probably related to the various shifts in cultural practices and lifestyles that followed the Neolithic Transition, such as sedentism, the shift from polygyny to monogamy or the increase of patrilocality.

Demographic inference using spectral methods on SNP data, with an analysis of the human out-of-Africa expansion

We present an implementation of a recently introduced method for estimating the allele-frequency spectrum under the diffusion approximation. For single-nucleotide polymorphism (SNP) frequency data from multiple populations, the method computes numerical solutions to the allele-frequency spectrum (AFS) under a complex model that includes population splitting events, migration, population expansion, and admixture. The solution to the diffusion partial differential equation (PDE) that mimics the evolutionary process is found by means of truncated polynomial expansions. In the absence of gene flow, our computation of frequency spectra yields exact results. The results are compared to those that use a finite-difference method and to forward diffusion simulations. In general, all the methods yield comparable results, although the polynomial-based approach is the most accurate in the weak-migration limit. Also, the economical use of memory attained by the polynomial expansions makes the study of models with four populations possible for the first time. The method was applied to a four-population model of the human expansion out of Africa and the peopling of the Americas, using the Environmental Genome Project (EGP) SNP database. Although our confidence intervals largely overlapped previous analyses of these data, some were significantly different. In particular, estimates of migration among African, European, and Asian populations were considerably lower than those in a previous study and the estimated time of migration out of Africa was earlier. The estimated time of founding of a human population outside of Africa was 52,000 years (95% confidence interval: 36,000–80,800 years).

DETSEL: an R-package to detect marker loci responding to selection

In the new era of population genomics, surveys of genetic polymorphism ("genome scans") offer the opportunity to distinguish locus-specific from genome-wide effects at many loci. Identifying presumably neutral regions of the genome that are assumed to be influenced by genome-wide effects only, and excluding presumably selected regions, is therefore critical to infer population demography and phylogenetic history reliably. Conversely, detecting locus-specific effects may help identify those genes that have been, or still are, targeted by natural selection. The software package DETSEL has been developed to identify markers that show deviation from neutral expectation in pairwise comparisons of diverging populations. Recently, two major improvements have been made: the analysis of dominant markers is now supported, and the estimation of empirical P-values has been implemented. These features, which are described below, have been incorporated into an R package, which replaces the stand-alone DETSEL software package.

Population divergence with or without admixture: selecting models using an ABC approach

Genetic data have been widely used to reconstruct the demographic history of populations, including the estimation of migration rates, divergence times and relative admixture contribution from different populations. Recently, increasing interest has been given to the ability of genetic data to distinguish alternative models. One of the issues that has plagued this kind of inference is that ancestral shared polymorphism is often difficult to separate from admixture or gene flow. Here, we applied an approximate Bayesian computation (ABC) approach to select the model that best fits microsatellite data among alternative splitting and admixture models. We performed a simulation study and showed that with reasonably large data sets (20 loci) it is possible to identify with a high level of accuracy the model that generated the data. This suggests that it is possible to distinguish genetic patterns due to past admixture events from those due to shared polymorphism (population split without admixture). We then apply this approach to microsatellite data from an endangered and endemic Iberian freshwater fish species, in which a clustering analysis suggested that one of the populations could be admixed. In contrast, our results suggest that the observed genetic patterns are better explained by a population split model without admixture.

Iranian human genome project: Overview of a research process among Iranian ethnicities

The Human Genome Project (HGP) refers to the international scientific research program, formally begun in October 1990 and completed in 2003, mainly designated to discover all the human genes, analyzing the structure of human DNA and determining the location of all human genes and also making them accessible for further biological and medical investigations. With the appropriate rationale approach, a similar study has been held in Iran. The study of human genome among Iranian ethnicities (IHGP) has been attempted formally in 2000 through a detailed and fully programmed research among all the major ethnic groups by more than 1,900 samples from all over Iran based on the main demographical and anthropological findings and formally known criteria considered for the international HGP. This paper overviewed the process of the research in the terms of program goals, primary data collection, research designation and methodology and also practical aspects and primary findings of the Iranian genome project and its progress during a nearly 5-year period.

The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes

The idea that molecular data should contain information on the recent evolutionary history of populations is rather old. However, much of the work carried out today owes to the work of the statisticians and theoreticians who demonstrated that it was possible to detect departures from equilibrium conditions (e.g., panmictic population/mutation-drift equilibrium) and interpret them in terms of deviations from neutrality or stationarity. During the last 20 years the detection of population size changes has usually been carried out under the assumption that samples were obtained from populations that can be approximated by a Wright-Fisher model (i.e., assuming panmixia, demographic stationarity, etc.). However, natural populations are usually part of spatial networks and are interconnected through gene flow. Here we simulated genetic data at mutation and migration-drift equilibrium under an n-island and a stepping-stone model. The simulated populations were thus stationary and not subject to any population size change. We varied the level of gene flow between populations and the scaled mutation rate. We also used several sampling schemes. We then analyzed the simulated samples using the Bayesian method implemented in MSVAR, the Markov Chain Monte Carlo simulation program, to detect and quantify putative population size changes using microsatellite data. Our results show that all three factors (genetic differentiation/gene flow, genetic diversity, and the sampling scheme) play a role in generating false bottleneck signals. We also suggest an ad hoc method to counter this effect. The confounding effect of population structure and of the sampling scheme has practical implications for many conservation studies. Indeed, if population structure is creating "spurious" bottleneck signals, the interpretation of bottleneck signals from genetic data might be less straightforward than it would seem, and several studies may have overestimated or incorrectly detected bottlenecks in endangered species.

Gene variations in the cholecystokinin system in patients with panic disorder

OBJECTIVES

Panic disorder (PD) is a common psychiatric disease occurring more frequently in women than men. Multiple common and/or rare variants in the genome contribute to the complex etiology of the disorder. The neuropeptide cholecystokinin (CCK) and its receptors (the CCK system) have been suggested to be involved in the pathogenesis of PD.

METHODS

We examined the promoter, exon, and exon-intron boundaries of the genes encoding CCK and its receptors (CCKAR and CCKBR) for variations in 187 patients with PD and 277 screened control individuals. Up to 1342 additional healthy population controls were examined for some of the variations. One CCK gene intron variation was analyzed for alternative splicing using an exon-trapping assay.

RESULTS

The promoter variant (-36C > T; rs1799923) and an intron 1 polymorphism (IVS1-7C > G; rs754635) in the CCK gene were found to protect against PD (P<0.05). The intron 1 variation did not seem to alter the splicing of the gene. None of the other variations found were associated with PD, but a 2-marker haplotype (rs1800855/rs1800857) in the CCKAR gene protected women against PD (P=0.004). In addition, we found two novel rare missense variations in the CCKBR gene (Lys329Asn and Pro446Leu) in two and one patient, respectively.

CONCLUSION

The results suggest that the CCK system may play a role in the pathogenesis of PD, with susceptibility alleles both protecting and contributing to the disease. Both common and rare variants seem to be involved. The involvement of the CCK system may also contribute to the increased prevalence of PD in women.

The microcephalin ancestral allele in a Neanderthal individual

Background

The high frequency (around 0.70 worlwide) and the relatively young age (between 14,000 and 62,000 years) of a derived group of haplotypes, haplogroup D, at the microcephalin (MCPH1) locus led to the proposal that haplogroup D originated in a human lineage that separated from modern humans >1 million years ago, evolved under strong positive selection, and passed into the human gene pool by an episode of admixture circa 37,000 years ago. The geographic distribution of haplogroup D, with marked differences between Africa and Eurasia, suggested that the archaic human form admixing with anatomically modern humans might have been Neanderthal.

Methodology/Principal Findings

Here we report the first PCR amplification and high- throughput sequencing of nuclear DNA at the microcephalin (MCPH1) locus from Neanderthal individual from Mezzena Rockshelter (Monti Lessini, Italy). We show that a well-preserved Neanderthal fossil dated at approximately 50,000 years B.P., was homozygous for the ancestral, non-D, allele. The high yield of Neanderthal mtDNA sequences of the studied specimen, the pattern of nucleotide misincorporation among sequences consistent with post-mortem DNA damage and an accurate control of the MCPH1 alleles in all personnel that manipulated the sample, make it extremely unlikely that this result might reflect modern DNA contamination.

Conclusions/Significance

The MCPH1 genotype of the Monti Lessini (MLS) Neanderthal does not prove that there was no interbreeding between anatomically archaic and modern humans in Europe, but certainly shows that speculations on a possible Neanderthal origin of what is now the most common MCPH1 haplogroup are not supported by empirical evidence from ancient DNA.

Genetic and environmental contributions to depression in Sri Lanka

BACKGROUND

Susceptibility to depression results from genetic and non-familially shared environmental influences in high-income, Western countries. Environments may play a different role for populations in different contexts.

AIMS

To examine heritability of depression in the first large, population-based twin study in a low-income country.

METHOD

Lifetime depression and a broader measure of depression susceptibility (D-probe) were assessed in 3908 adult twins in Sri Lanka (the CoTASS study).

RESULTS

There were gender differences for the broad definition (D-probe), with a higher genetic contribution in females (61%) than males (4%). Results were similar for depression, but the prevalence was too low to estimate heritability for males.

CONCLUSIONS

Genetic influences on depression in women appear to be at least as strong in this Sri Lankan sample as in higher-income countries. Conclusions are less clear for men but suggest a larger role for environments rather than genes. The nature as well as the magnitude of environmental influences may also differ across populations.

Meiotic recombination generates rich diversity in NK cell receptor genes, alleles, and haplotypes

Natural killer (NK) cells contribute to the essential functions of innate immunity and reproduction. Various genes encode NK cell receptors that recognize the major histocompatibility complex (MHC) Class I molecules expressed by other cells. For primate NK cells, the killer-cell immunoglobulin-like receptors (KIR) are a variable and rapidly evolving family of MHC Class I receptors. Studied here is KIR3DL1/S1, which encodes receptors for highly polymorphic human HLA-A and -B and comprises three ancient allelic lineages that have been preserved by balancing selection throughout human evolution. While the 3DS1 lineage of activating receptors has been conserved, the two 3DL1 lineages of inhibitory receptors were diversified through inter-lineage recombination with each other and with 3DS1. Prominent targets for recombination were D0-domain polymorphisms, which modulate enhancer function, and dimorphism at position 283 in the D2 domain, which influences inhibitory function. In African populations, unequal crossing over between the 3DL1 and 3DL2 genes produced a deleted KIR haplotype in which the telomeric "half" was reduced to a single fusion gene with functional properties distinct from its 3DL1 and 3DL2 parents. Conversely, in Eurasian populations, duplication of the KIR3DL1/S1 locus by unequal crossing over has enabled individuals to carry and express alleles of all three KIR3DL1/S1 lineages. These results demonstrate how meiotic recombination combines with an ancient, preserved diversity to create new KIR phenotypes upon which natural selection acts. A consequence of such recombination is to blur the distinction between alleles and loci in the rapidly evolving human KIR gene family.

SPAms: A user-friendly software to simulate population genetics data under complex demographic models

Patterns of genetic diversity can be used to reconstruct populations demographic history. Thus, it is crucial to understand the statistical properties of data sets generated under different scenarios. SPAms is a graphical application that allows the simulation of data under a set of demographic models of increasing complexity: (i) population size change (ii) admixture and (iii) population structure (n-island or stepping stone model). SPAms generates data under the infinite site and the stepwise mutation models and computes a set of commonly used statistics. It should thus be a useful tool for both research and teaching purposes.

Left ventricular structure in relation to the human SAH gene in the European Project on Genes in Hypertension

Earlier studies showed association of the human SAH (Spontaneously hypertensive rat-clone A-Hypertension associated) gene with hypertension and obesity. Left ventricular mass index (LVMI) increases with blood pressure and body mass index. In a family-based population study (54.5% women; mean age, 43.1 years), we measured LVMI, mean wall thickness (MWT) and the left ventricular internal diameter (LVID) at end-diastole in 699 non-Slavic and 493 Slavic participants. In multivariable-adjusted analyses, we investigated phenotype-genotype associations (SAH G-1606A and -962ins/del polymorphisms), while accounting for confounders and relatedness. Non-Slavic -1606GG homozygotes had a slightly greater LVID than -1606A allele carriers (48.6 vs. 48.0 mm; P=0.08). However, the between-family component of the variance in LVID was significant (P=0.005), suggesting that population stratification might explain the latter finding. Non-Slavic -962del carriers had higher LVMI (91.1 vs. 88.5 g m(-2); P=0.03) and MWT (9.61 vs. 9.44 mm; P=0.03) than -962ins homozygotes. Transmission of the -962del to non-Slavic offspring was also associated with higher MWT (P=0.03). In Slavic participants, in the absence of population stratification (P>or=0.69), -1606GG homozygotes had lower LVMI (96.5 vs. 102.3 g m(-2); P=0.004) and lower MWT (10.1 vs. 10.5 mm; P=0.003) than -1606A carriers. Sensitivity analyses showed that the latter associations were confined to founders. Transmission of the -962del allele to Slavic offspring was associated with lower MWT (P=0.007). In conclusion, LVMI and MWT, two phenotypes that are jointly influenced by blood pressure and obesity, might be related to variation in the human SAH gene.

Culture, population structure, and low genetic diversity in Pleistocene hominins

Paleogenomic research has shown that modern humans, Neanderthals, and their most recent common ancestor have displayed less genetic diversity than living great apes. The traditional interpretation that low levels of genetic diversity in modern humans resulted from a relatively recent demographic bottleneck cannot account for similarly low levels of genetic diversity in Middle Pleistocene hominins. A more parsimonious hypothesis proposes that the effective population size of the human lineage has been low for more than 500,000 years, but the mechanism responsible for suppressing genetic diversity in Pleistocene hominin populations without similarly affecting that of their hominoid contemporaries remains unknown. Here we use agent-based simulation to study the effect of culturally mediated migration on neutral genetic diversity in structured populations. We show that, in populations structured by culturally mediated migration, selection can suppress neutral genetic diversity over thousands of generations, even in the absence of bottlenecks or expansions in census population size. In other words, selection could have suppressed the effective population size of Pleistocene hominins for as long as the degree of cultural similarity between regionally differentiated groups played an important role in mediating intraspecific gene flow.

Genetic variation in South Indian castes: evidence from Y-chromosome, mitochondrial, and autosomal polymorphisms

Background

Major population movements, social structure, and caste endogamy have influenced the genetic structure of Indian populations. An understanding of these influences is increasingly important as gene mapping and case-control studies are initiated in South Indian populations.

Results

We report new data on 155 individuals from four Tamil caste populations of South India and perform comparative analyses with caste populations from the neighboring state of Andhra Pradesh. Genetic differentiation among Tamil castes is low (R_ST = 0.96% for 45 autosomal short tandem repeat (STR) markers), reflecting a largely common origin. Nonetheless, caste- and continent-specific patterns are evident. For 32 lineage-defining Y-chromosome SNPs, Tamil castes show higher affinity to Europeans than to eastern Asians, and genetic distance estimates to the Europeans are ordered by caste rank. For 32 lineage-defining mitochondrial SNPs and hypervariable sequence (HVS) 1, Tamil castes have higher affinity to eastern Asians than to Europeans. For 45 autosomal STRs, upper and middle rank castes show higher affinity to Europeans than do lower rank castes from either Tamil Nadu or Andhra Pradesh. Local between-caste variation (Tamil Nadu R_ST = 0.96%, Andhra Pradesh R_ST = 0.77%) exceeds the estimate of variation between these geographically separated groups (R_ST = 0.12%). Low, but statistically significant, correlations between caste rank distance and genetic distance are demonstrated for Tamil castes using Y-chromosome, mtDNA, and autosomal data.

Conclusion

Genetic data from Y-chromosome, mtDNA, and autosomal STRs are in accord with historical accounts of northwest to southeast population movements in India. The influence of ancient and historical population movements and caste social structure can be detected and replicated in South Indian caste populations from two different geographic regions.

The molecular signature of selection underlying human adaptations

In the last decade, advances in human population genetics and comparative genomics have resulted in important contributions to our understanding of human genetic diversity and genetic adaptation. For the first time, we are able to reliably detect the signature of natural selection from patterns of DNA polymorphism. Identifying the effects of natural selection in this way provides a crucial piece of evidence needed to support hypotheses of human adaptation. This review provides a detailed description of the theory and analytical approaches used to detect signatures of natural selection in the human genome. We discuss these methods in relation to four classic human traits--skin color, the Duffy blood group, bitter-taste sensation, and lactase persistence. By highlighting these four traits we are able to discuss the ways in which analyses of DNA polymorphism can lead to inferences regarding past histories of selection. Specifically, we can infer the importance of specific regimes of selection (i.e. directional selection, balancing selection, and purifying selection) in the evolution of a trait because these different types of selection leave different patterns of DNA polymorphism. In addition, we demonstrate how these types of data can be used to estimate the time frame in which selection operated on a trait. As the field has advanced, a general issue that has come to the forefront is how specific demographic events in human history, such as population expansions, bottlenecks, and subdivision of populations, have also left a signature across the genome that can interfere with our detection of the footprint of selection at particular genes. Therefore, we discuss this general problem with respect to the four traits reviewed here, and describe the ways in which the signature of selection can be teased from a background signature of demographic history. Finally, we move from a discussion of analyses of selection motivated by a "candidate-gene" approach, in which a priori information led to the analysis of specific gene, to discussion of "genome-scanning" approaches that are directed at discovering new genes that have been under positive selection. Such scans can be designed to detect those genes that have been positively selected in our divergence from chimpanzees, as well as those genes that have been under selection as human populations have migrated, differentiated, and adapted to specific geographic environments. We predict that both approaches will be applied in the future, enabling a greater insight into human species-wide adaptations, as well as the specific adaptations of human populations.

Statistical evaluation of alternative models of human evolution

An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species approximately 141 thousand years ago (Kya), an exit out-of-Africa approximately 51 Kya, and a recent colonization of the Americas approximately 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

Schizophrenia: a common disease caused by multiple rare alleles

Schizophrenia is widely held to stem from the combined effects of multiple common polymorphisms, each with a small impact on disease risk. We suggest an alternative view: that schizophrenia is highly heterogeneous genetically and that many predisposing mutations are highly penetrant and individually rare, even specific to single cases or families. This "common disease--rare alleles" hypothesis is supported by recent findings in human genomics and by allelic and locus heterogeneity for other complex traits. We review the implications of this model for gene discovery research in schizophrenia.

Going east: new genetic and archaeological perspectives on the modern human colonization of Eurasia

The pattern of dispersal of biologically and behaviorally modern human populations from their African origins to the rest of the occupied world between approximately 60,000 and 40,000 years ago is at present a topic of lively debate, centering principally on the issue of single versus multiple dispersals. Here I argue that the archaeological and genetic evidence points to a single successful dispersal event, which took genetically and culturally modern populations fairly rapidly across southern and southeastern Asia into Australasia, and with only a secondary and later dispersal into Europe.

Origins and evolution of the Europeans' genome: evidence from multiple microsatellite loci

There is general agreement that the current European gene pool is mainly derived from Palaeolithic hunting-gathering and Neolithic farming ancestors, but different studies disagree on the relative weight of these contributions. We estimated admixture rates in European populations from data on 377 autosomal microsatellite loci in 235 individuals, using five different numerical methods. On average, the Near Eastern (and presumably Neolithic) contribution was between 46 and 66%, and admixture estimates showed, with all methods, a strong and significant negative correlation with distance from the Near East. If the assumptions of the model are approximately correct, i.e. if the Basques' and Near Easterners' genomes represent a good approximation to the Palaeolithic and Neolithic settlers of Europe, respectively, these results imply that half or more of the Europeans' genes are descended from Near Eastern ancestors who immigrated in Europe 10000 years ago. If these assumptions are incorrect, our results show anyway that clinal variation is the rule in the Europeans' genomes and that lower estimates of Near Eastern admixture obtained from the analysis of single markers do not reflect the patterns observed at the genomic level.