Genomic analyses inform on migration events during the peopling of Eurasia.

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

A Selective Sweep on a Deleterious Mutation in CPT1A in Arctic Populations.

Arctic populations live in an environment characterized by extreme cold and the absence of plant foods for much of the year and are likely to have undergone genetic adaptations to these environmental conditions in the time they have been living there. Genome-wide selection scans based on genotype data from native Siberians have previously highlighted a 3 Mb chromosome 11 region containing 79 protein-coding genes as the strongest candidates for positive selection in Northeast Siberians. However, it was not possible to determine which of the genes might be driving the selection signal. Here, using whole-genome high-coverage sequence data, we identified the most likely causative variant as a nonsynonymous G>A transition (rs80356779; c.1436C>T [p.Pro479Leu] on the reverse strand) in CPT1A, a key regulator of mitochondrial long-chain fatty-acid oxidation. Remarkably, the derived allele is associated with hypoketotic hypoglycemia and high infant mortality yet occurs at high frequency in Canadian and Greenland Inuits and was also found at 68% frequency in our Northeast Siberian sample. We provide evidence of one of the strongest selective sweeps reported in humans; this sweep has driven this variant to high frequency in circum-Arctic populations within the last 6-23 ka despite associated deleterious consequences, possibly as a result of the selective advantage it originally provided to either a high-fat diet or a cold environment.

Genome-wide evidence of Austronesian-Bantu admixture and cultural reversion in a hunter-gatherer group of Madagascar.

Linguistic and cultural evidence suggest that Madagascar was the final point of two major dispersals of Austronesian- and Bantu-speaking populations. Today, the Mikea are described as the last-known Malagasy population reported to be still practicing a hunter-gatherer lifestyle. It is unclear, however, whether the Mikea descend from a remnant population that existed before the arrival of Austronesian and Bantu agriculturalists or whether it is only their lifestyle that separates them from the other contemporary populations of South Madagascar. To address these questions we have performed a genome-wide analysis of >700,000 SNP markers on 21 Mikea, 24 Vezo, and 24 Temoro individuals, together with 50 individuals from Bajo and Lebbo populations from Indonesia. Our analyses of these data in the context of data available from other Southeast Asian and African populations reveal that all three Malagasy populations are derived from the same admixture event involving Austronesian and Bantu sources. In contrast to the fact that most of the vocabulary of the Malagasy speakers is derived from the Barito group of the Austronesian language family, we observe that only one-third of their genetic ancestry is related to the populations of the Java-Kalimantan-Sulawesi area. Because no additional ancestry components distinctive for the Mikea were found, it is likely that they have adopted their hunter-gatherer way of life through cultural reversion, and selection signals suggest a genetic adaptation to their new lifestyle.

Genetic signatures reveal high-altitude adaptation in a set of ethiopian populations.

The Tibetan and Andean Plateaus and Ethiopian highlands are the largest regions to have long-term high-altitude residents. Such populations are exposed to lower barometric pressures and hence atmospheric partial pressures of oxygen. Such "hypobaric hypoxia" may limit physical functional capacity, reproductive health, and even survival. As such, selection of genetic variants advantageous to hypoxic adaptation is likely to have occurred. Identifying signatures of such selection is likely to help understanding of hypoxic adaptive processes. Here, we seek evidence of such positive selection using five Ethiopian populations, three of which are from high-altitude areas in Ethiopia. As these populations may have been recipients of Eurasian gene flow, we correct for this admixture. Using single-nucleotide polymorphism genotype data from multiple populations, we find the strongest signal of selection in BHLHE41 (also known as DEC2 or SHARP1). Remarkably, a major role of this gene is regulation of the same hypoxia response pathway on which selection has most strikingly been observed in both Tibetan and Andean populations. Because it is also an important player in the circadian rhythm pathway, BHLHE41 might also provide insights into the mechanisms underlying the recognized impacts of hypoxia on the circadian clock. These results support the view that Ethiopian, Andean, and Tibetan populations living at high altitude have adapted to hypoxia differently, with convergent evolution affecting different genes from the same pathway.

Evolution of the pygmy phenotype: evidence of positive selection fro genome-wide scans in African, Asian, and Melanesian pygmies.

Human pygmy populations inhabit different regions of the world, from Africa to Melanesia. In Asia, short-statured populations are often referred to as "negritos." Their short stature has been interpreted as a consequence of thermoregulatory, nutritional, and/or locomotory adaptations to life in tropical forests. A more recent hypothesis proposes that their stature is the outcome of a life history trade-off in high-mortality environments, where early reproduction is favored and, consequently, early sexual maturation and early growth cessation have coevolved. Some serological evidence of deficiencies in the growth hormone/insulin-like growth factor axis have been previously associated with pygmies' short stature. Using genome-wide single-nucleotide polymorphism genotype data, we first tested whether different negrito groups living in the Philippines and Papua New Guinea are closely related and then investigated genomic signals of recent positive selection in African, Asian, and Papuan pygmy populations. We found that negritos in the Philippines and Papua New Guinea are genetically more similar to their nonpygmy neighbors than to one another and have experienced positive selection at different genes. These results indicate that geographically distant pygmy groups are likely to have evolved their short stature independently. We also found that selection on common height variants is unlikely to explain their short stature and that different genes associated with growth, thyroid function, and sexual development are under selection in different pygmy groups.

ogaraK: a population genetics simulator for malaria.

MOTIVATION: The evolution of resistance in Plasmodium falciparum malaria against most available treatments is a major global health threat. Population genetics approaches are commonly used to model the spread of drug resistance. Due to uncommon features in malaria biology, existing forward-time population genetics simulators cannot suitably model Plasmodium falciparum malaria. RESULTS: Here we present ogaraK, a population genetics simulator for modelling the spread of drug-resistant malaria. OgaraK is designed to make malaria simulation computationally tractable as it models infections, not individual parasites. OgaraK is also able to model the life cycle of the parasite which includes both haploid and diploid phases and sexual and asexual reproduction. We also allow for the simulation of different inbreeding levels, an important difference between high and low transmission areas and a fundamental factor influencing the outcome of strategies to control or eliminate malaria. AVAILABILITY: OgaraK is available as free software (GPL) from the address http://popgen.eu/soft/ogaraK.

Mcheza: a workbench to detect selection using dominant markers.

MOTIVATION: Dominant markers (DArTs and AFLPs) are commonly used for genetic analysis in the fields of evolutionary genetics, ecology and conservation of genetic resources. The recent prominence of these markers has coincided with renewed interest in detecting the effects of local selection and adaptation at the level of the genome. RESULTS: We present Mcheza, an application for detecting loci under selection based on a well-evaluated F(ST)-outlier method. The application allows robust estimates to be made of model parameters (e.g. genome-wide average, neutral F(ST)), provides data import and export functions, iterative contour smoothing and generation of graphics in an easy to use graphical user interface with a computation engine that supports multicore processors for enhanced performance. Mcheza also provides functionality to mitigate common analytical errors when scanning for loci under selection. AVAILABILITY: Mcheza is freely available under GPL version 3 from http://popgen.eu/soft/mcheza.

Policy options for deploying anti-malarial drugs in endemic countries: a population genetics approach.

BACKGROUND: Anti-malarial drugs are constantly exposed to the threat of evolving drug resistance so good stewardship of existing therapy is an essential component of public health policy. However, the widespread availability of numerous different drugs through informal providers could undermine official drug deployment policies. A policy of multiple first-line therapy (MFT) is compared with the conventional policy of sequential drug deployment, i.e., where one drug is used until resistance evolves and then replaced by the next drug in the sequence. METHODS: Population genetic models of drug resistance are used to make the comparison; this methodology explicitly tracks the genetics of drug resistance (including, importantly, recombination in the sexual stage, intrahost dynamics, and direction of linkage disequilibrium). RESULTS: A policy of MFT outlasts sequential application providing drug usages are low to moderate, and appears not to drive widespread multi-drug resistance. Inadequate dosing is an even more potent driver of drug resistance than the MFT/sequential policy decision. CONCLUSIONS: The provision of MFT as a deliberate policy can be encouraged provided overall treatment rates are low or moderate (less than around half of malaria infections are treated) and the ad hoc provision of MFT through the private sector may be tolerated. This must be fully supported by education to ensure people take adequate doses of each of the drugs.

Environmental, pharmacological and genetic influences on the spread of drug-resistant malaria.

Plasmodium falciparum malaria is subject to artificial selection from antimalarial drugs that select for drug-resistant parasites. We describe and apply a flexible new approach to investigate how epistasis, inbreeding, selection heterogeneity and multiple simultaneous drug deployments interact to influence the spread of drug-resistant malaria. This framework recognizes that different human 'environments' within which treatment may occur (such as semi- and non-immune humans taking full or partial drug courses) influence the genetic interactions between parasite loci involved in resistance. Our model provides an explanation for how the rate of spread varies according to different malaria transmission intensities, why resistance might stabilize at intermediate frequencies and also identifies several factors that influence the decline of resistance after a drug is removed. Results suggest that studies based on clinical outcomes might overestimate the spread of resistant parasites, especially in high-transmission areas. We show that when transmission decreases, prevalence might decrease without a corresponding change in frequency of resistance and that this relationship is heavily influenced by the extent of linkage disequilibrium between loci. This has important consequences on the interpretation of data from areas where control is being successful and suggests that reducing transmission might have less impact on the spread of resistance than previously expected.

Detecting population declines via monitoring the effective number of breeders (Nb ).

Estimating the effective population size and effective number of breeders per year (Nb ) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of Nb in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. Nb estimates were biased by ~5%-10% when using SNPs or microsatellites in species ranging from fishes to mosquitoes, frogs, and seaweed. The bias (high or low) was similar for different life history types within a species suggesting that life history variation in populations will not influence Nb estimation. Precision was higher for 100 SNPs (H ≈ 0.30) than for 15 microsatellites (H ≈ 0.70). Confidence intervals (CIs) were occasionally too narrow, and biased high when Nb was small (Nb  < 50); however, the magnitude of bias would unlikely influence management decisions. The CIs (from LDNe) were sufficiently narrow to achieve high statistical power (≥0.80) to reject the null hypothesis that Nb  = 50 when the true Nb  = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject Nb  = 500 when the true Nb  = 400 and when sampling 200 individuals and 5,000 loci. Finally, we present a linear regression method that provides high power to detect a decline in Nb when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate Nb for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in Nb and population declines.

interPopula: a Python API to access the HapMap Project dataset.

BACKGROUND: The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided. RESULTS: interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided. CONCLUSIONS: interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset.

Biopython: freely available Python tools for computational molecular biology and bioinformatics.

SUMMARY: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. AVAILABILITY: Biopython is freely available, with documentation and source code at (www.biopython.org) under the Biopython license.

Niche partitioning of microbial communities in riverine floodplains.

Riverine floodplains exhibit high floral and faunal diversity as a consequence of their biophysical complexity. Extension of such niche partitioning processes to microbial communities is far less resolved or supported. Here, we evaluated the responses of aquatic biofilms diversity to environmental gradients across ten riverine floodplains with differing degrees of flow alteration and habitat diversity to assess whether complex floodplains support biofilm communities with greater biodiversity and species interactions. No significant evidence was found to support a central role for habitat diversity in promoting microbial diversity across 116 samples derived from 62 aquatic habitats, as neither α (H': 2.8-4.1) nor ß (Sørensen: 0.3-0.39) diversity were positively related to floodplain complexity across the ten floodplains. In contrast, our results documented the sensitivity of biofilm communities to regional templates manifested as gradients of carbon, nitrogen, and phosphorous availability. Large-scale conditions reflecting nitrogen limitation increased the relative abundance of N-fixing cyanobacteria (up to 0.34 as fraction of total reads), constrained the total number of interactions among bacterial taxa, and reinforced negative over positive interactions, generating unique microbial communities and networks that reflect large-scale species sorting in response to regional geochemical gradients.

LOSITAN: a workbench to detect molecular adaptation based on a Fst-outlier method.

BACKGROUND: Testing for selection is becoming one of the most important steps in the analysis of multilocus population genetics data sets. Existing applications are difficult to use, leaving many non-trivial, error-prone tasks to the user. RESULTS: Here we present LOSITAN, a selection detection workbench based on a well evaluated Fst-outlier detection method. LOSITAN greatly facilitates correct approximation of model parameters (e.g., genome-wide average, neutral Fst), provides data import and export functions, iterative contour smoothing and generation of graphics in a easy to use graphical user interface. LOSITAN is able to use modern multi-core processor architectures by locally parallelizing fdist, reducing computation time by half in current dual core machines and with almost linear performance gains in machines with more cores. CONCLUSION: LOSITAN makes selection detection feasible to a much wider range of users, even for large population genomic datasets, by both providing an easy to use interface and essential functionality to complete the whole selection detection process.

Local selection in the presence of high levels of gene flow: Evidence of heterogeneous insecticide selection pressure across Ugandan Culex quinquefasciatus populations.

BACKGROUND: Culex quinquefasciatus collected in Uganda, where no vector control interventions directly targeting this species have been conducted, was used as a model to determine if it is possible to detect heterogeneities in selection pressure driven by insecticide application targeting other insect species. METHODOLOGY/PRINCIPAL FINDINGS: Population genetic structure was assessed through microsatellite analysis, and the impact of insecticide pressure by genotyping two target-site mutations, Vgsc-1014F of the voltage-gated sodium channel target of pyrethroid and DDT insecticides, and Ace1-119S of the acetylcholinesterase gene, target of carbamate and organophosphate insecticides. No significant differences in genetic diversity were observed among populations by microsatellite markers with HE ranging from 0.597 to 0.612 and low, but significant, genetic differentiation among populations (FST = 0.019, P = 0.001). By contrast, the insecticide-resistance markers display heterogeneous allelic distributions with significant differences detected between Central Ugandan (urban) populations relative to Eastern and Southwestern (rural) populations. In the central region, a frequency of 62% for Vgsc-1014F, and 32% for the Ace1-119S resistant allele were observed. Conversely, in both Eastern and Southwestern regions the Vgsc-1014F alleles were close to fixation, whilst Ace1-119S allele frequency was 12% (although frequencies may be underestimated due to copy number variation at both loci). CONCLUSIONS/SIGNIFICANCE: Taken together, the microsatellite and both insecticide resistance target-site markers provide evidence that in the face of intense gene flow among populations, disjunction in resistance frequencies arise due to intense local selection pressures despite an absence of insecticidal control interventions targeting Culex.

Evidence of Early-Stage Selection on EPAS1 and GPR126 Genes in Andean High Altitude Populations.

The aim of this study is to identify genetic variants that harbour signatures of recent positive selection and may facilitate physiological adaptations to hypobaric hypoxia. To achieve this, we conducted whole genome sequencing and lung function tests in 19 Argentinean highlanders (>3500 m) comparing them to 16 Native American lowlanders. We developed a new statistical procedure using a combination of population branch statistics (PBS) and number of segregating sites by length (nSL) to detect beneficial alleles that arose since the settlement of the Andes and are currently present in 15-50% of the population. We identified two missense variants as significant targets of selection. One of these variants, located within the GPR126 gene, has been previously associated with the forced expiratory volume/forced vital capacity ratio. The other novel missense variant mapped to the EPAS1 gene encoding the hypoxia inducible factor 2α. EPAS1 is known to be the major selection candidate gene in Tibetans. The derived allele of GPR126 is associated with lung function in our sample of highlanders (p < 0.05). These variants may contribute to the physiological adaptations to hypobaric hypoxia, possibly by altering lung function. The new statistical approach might be a useful tool to detect selected variants in population studies.

Massive introgression drives species radiation at the range limit of Anopheles gambiae.

Impacts of introgressive hybridisation may range from genomic erosion and species collapse to rapid adaptation and speciation but opportunities to study these dynamics are rare. We investigated the extent, causes and consequences of a hybrid zone between Anopheles coluzzii and Anopheles gambiae in Guinea-Bissau, where high hybridisation rates appear to be stable at least since the 1990s. Anopheles gambiae was genetically partitioned into inland and coastal subpopulations, separated by a central region dominated by A. coluzzii. Surprisingly, whole genome sequencing revealed that the coastal region harbours a hybrid form characterised by an A. gambiae-like sex chromosome and massive introgression of A. coluzzii autosomal alleles. Local selection on chromosomal inversions may play a role in this process, suggesting potential for spatiotemporal stability of the coastal hybrid form and providing resilience against introgression of medically-important loci and traits, found to be more prevalent in inland A. gambiae.

Multi-layered population structure in Island Southeast Asians.

The history of human settlement in Southeast Asia has been complex and involved several distinct dispersal events. Here, we report the analyses of 1825 individuals from Southeast Asia including new genome-wide genotype data for 146 individuals from three Mainland Southeast Asian (Burmese, Malay and Vietnamese) and four Island Southeast Asian (Dusun, Filipino, Kankanaey and Murut) populations. While confirming the presence of previously recognised major ancestry components in the Southeast Asian population structure, we highlight the Kankanaey Igorots from the highlands of the Philippine Mountain Province as likely the closest living representatives of the source population that may have given rise to the Austronesian expansion. This conclusion rests on independent evidence from various analyses of autosomal data and uniparental markers. Given the extensive presence of trade goods, cultural and linguistic evidence of Indian influence in Southeast Asia starting from 2.5 kya, we also detect traces of a South Asian signature in different populations in the region dating to the last couple of thousand years.

Selective sweep on human amylase genes postdates the split with Neanderthals.

Humans have more copies of amylase genes than other primates. It is still poorly understood, however, when the copy number expansion occurred and whether its spread was enhanced by selection. Here we assess amylase copy numbers in a global sample of 480 high coverage genomes and find that regions flanking the amylase locus show notable depression of genetic diversity both in African and non-African populations. Analysis of genetic variation in these regions supports the model of an early selective sweep in the human lineage after the split of humans from Neanderthals which led to the fixation of multiple copies of AMY1 in place of a single copy. We find evidence of multiple secondary losses of copy number with the highest frequency (52%) of a deletion of AMY2A and associated low copy number of AMY1 in Northeast Siberian populations whose diet has been low in starch content.

Positive selection of AS3MT to arsenic water in Andean populations.

Arsenic is a carcinogen associated with skin lesions and cardiovascular diseases. The Colla population from the Puna region in Northwest Argentinean is exposed to levels of arsenic in drinking water exceeding the recommended maximum by a factor of 20. Yet, they thrive in this challenging environment since thousands of years and therefore we hypothesize strong selection signatures in genes involved in arsenic metabolism. We analyzed genome-wide genotype data for 730,000 loci in 25 Collas, considering 24 individuals of the neighbouring Calchaquíes and 24 Wichí from the Gran Chaco region in the Argentine province of Salta as control groups. We identified a strong signal of positive selection in the main arsenic methyltransferase AS3MT gene, which has been previously associated with lower concentrations of the most toxic product of arsenic metabolism monomethylarsonic acid. This study confirms recent studies reporting selection signals in the AS3MT gene albeit using different samples, tests and control populations.