Search

Functional annotation and interpretation of genetic variants are a critical step in genetic diagnosis, as it may lead to personalized therapeutic options and genetic counseling. While the number of confirmed pathogenic genetic variants in an individual is relatively low, the number of variants of uncertain significance (VOUS) can be considerably higher, increasing the number of potential carriers of genetic disorders. Thus, reducing uncertainty and assessing the real effect of VOUS are crucial for clinical and medical genetics. In this study, we evaluated the efficacy of genetic screening technologies in accurately predicting pathogenic variants and their corresponding disease prevalence in a cohort of over 6000 healthy individuals involved in assisted reproduction programs. Using data from 305 genes associated with recessive disorders, we determined the frequency of carriers of pathogenic variants and VOUS in our dataset and compared the predicted prevalence based on this information with reported population prevalence data. The higher predicted prevalence in some disorders when considering VOUS suggests a mostly benign effect., (© 2024 The Author(s). Clinical Genetics published by John Wiley & Sons Ltd.)

RNA-binding proteins are emerging as critical modulators of oncogenic cell transformation, malignancy and therapy resistance. We have previously found that the RNA-binding protein Cold Shock Domain containing protein E1 (CSDE1) promotes invasion and metastasis of melanoma, the deadliest form of skin cancer and also a highly heterogeneous disease in need of predictive biomarkers and druggable targets. Here, we design a monoclonal antibody useful for IHC in the clinical setting and use it to evaluate the prognosis potential of CSDE1 in an exploratory cohort of 149 whole tissue sections including benign nevi and primary tumors and metastasis from melanoma patients. Contrary to expectations for an oncoprotein, we observed a global decrease in CSDE1 levels with increasing malignancy. However, the CSDE1 cytoplasmic/nuclear ratio exhibited a positive correlation with adverse clinical features of primary tumors and emerged as a robust indicator of progression free survival in cutaneous melanoma, highlighting the potential of CSDE1 as a biomarker of prognosis. Our findings provide a novel feature for prognosis assessment and highlight the intricacies of RNA-binding protein dynamics in cancer progression.

An important fraction of patients with rare disorders remains with no clear genetic diagnostic, even after whole-exome or whole-genome sequencing, posing a difficulty in giving adequate treatment and genetic counseling. The analysis of genomic data in rare disorders mostly considers the presence of single gene variants in coding regions that follow a concrete monogenic mode of inheritance. A digenic inheritance, with variants in two functionally-related genes in the same individual, is a plausible alternative that might explain the genetic basis of the disease in some cases. In this case, digenic disease combinations should be absent or underrepresented in healthy individuals. We develop a framework to evaluate the significance of digenic combinations and test its statistical power in different scenarios. We suggest that this approach will be relevant with the advent of new sequencing efforts including hundreds of thousands of samples., (© 2022. The Author(s).)

The occurrence of natural variation in human microRNAs has been the focus of numerous studies during the last 20 years. Most of them have been focused on the role of specific mutations in disease, while a minor proportion seek to analyse microRNA diversity in the genomes of human populations. We analyse the latest human microRNA annotations in the light of the most updated catalogue of genetic variation provided by the 1000 Genomes Project. By means of the in silico analysis of microRNA genetic variation we show that the level of evolutionary constraint of these sequences is governed by the interplay of different factors, like their evolutionary age or genomic location. The role of mutations in the shaping of microRNA-driven regulatory interactions is emphasized with the acknowledgement that, while the whole microRNA sequence is highly conserved, the seed region shows a pattern of higher genetic diversity that appears to be caused by the dramatic frequency shifts of a fraction of human microRNAs. We highlight the participation of these microRNAs in population-specific processes by identifying that not only the seed, but also the loop, are particularly differentiated regions among human populations. The quantitative computational comparison of signatures of population differentiation showed that candidate microRNAs with the largest differences are enriched in variants implicated in gene expression levels (eQTLs), selective sweeps and pathological processes. We explore the implication of these evolutionary-driven microRNAs and their SNPs in human diseases, such as different types of cancer, and discuss their role in population-specific disease risk., (© 2022. The Author(s).)

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Villegas-Mirón, Acosta, Nye, Bertranpetit and Laayouni.)

Tissue function and homeostasis reflect the gene expression signature by which the combination of ubiquitous and tissue-specific genes contribute to the tissue maintenance and stimuli-responsive function. Enhancers are central to control this tissue-specific gene expression pattern. Here, we explore the correlation between the genomic location of enhancers and their role in tissue-specific gene expression. We find that enhancers showing tissue-specific activity are highly enriched in intronic regions and regulate the expression of genes involved in tissue-specific functions, whereas housekeeping genes are more often controlled by intergenic enhancers, common to many tissues. Notably, an intergenic-to-intronic active enhancers continuum is observed in the transition from developmental to adult stages: the most differentiated tissues present higher rates of intronic enhancers, whereas the lowest rates are observed in embryonic stem cells. Altogether, our results suggest that the genomic location of active enhancers is key for the tissue-specific control of gene expression., (© 2021 Borsari et al.; Published by Cold Spring Harbor Laboratory Press.)

Background: In the process of adaptation of humans to their environment, positive or adaptive selection has played a main role. Positive selection has, however, been under-studied in African populations, despite their diversity and importance for understanding human history., Results: Here, we have used 119 available whole-genome sequences from five Ethiopian populations (Amhara, Oromo, Somali, Wolayta and Gumuz) to investigate the modes and targets of positive selection in this part of the world. The site frequency spectrum-based test SFselect was applied to idfentify a wide range of events of selection (old and recent), and the haplotype-based statistic integrated haplotype score to detect more recent events, in each case with evaluation of the significance of candidate signals by extensive simulations. Additional insights were provided by considering admixture proportions and functional categories of genes. We identified both individual loci that are likely targets of classic sweeps and groups of genes that may have experienced polygenic adaptation. We found population-specific as well as shared signals of selection, with folate metabolism and the related ultraviolet response and skin pigmentation standing out as a shared pathway, perhaps as a response to the high levels of ultraviolet irradiation, and in addition strong signals in genes such as IFNA, MRC1, immunoglobulins and T-cell receptors which contribute to defend against pathogens., Conclusions: Signals of positive selection were detected in Ethiopian populations revealing novel adaptations in East Africa, and abundant targets for functional follow-up.

The Roma people are the largest transnational ethnic minority in Europe and can be considered the last human migration of South Asian origin into the continent. They left Northwest India approximately 1,000 years ago, reaching the Balkan Peninsula around the twelfth century and Romania in the fourteenth century. Here, we analyze whole-genome sequencing data of 40 Roma and 40 non-Roma individuals from Romania. We performed a genome-wide scan of selection comparing Roma, their local host population, and a Northwestern Indian population, to identify the selective pressures faced by the Roma mainly after they settled in Europe. We identify under recent selection several pathways implicated in immune responses, among them cellular metabolism pathways known to be rewired after immune stimulation. We validated the interaction between PIK3-mTOR-HIF-1α and cytokine response influenced by bacterial and fungal infections. Our results point to a significant role of these pathways for host defense against the most prevalent pathogens in Europe during the last millennium.

After diverging, each chimpanzee subspecies has been the target of unique selective pressures. Here, we employ a machine learning approach to classify regions as under positive selection or neutrality genome-wide. The regions determined to be under selection reflect the unique demographic and adaptive history of each subspecies. The results indicate that effective population size is important for determining the proportion of the genome under positive selection. The chimpanzee subspecies share signals of selection in genes associated with immunity and gene regulation. With these results, we have created a selection map for each population that can be displayed in a genome browser (www.hsb.upf.edu/chimp_browser). This study is the first to use a detailed demographic history and machine learning to map selection genome-wide in chimpanzee. The chimpanzee selection map will improve our understanding of the impact of selection on closely related subspecies and will empower future studies of chimpanzee., (© The Author(s) 2019. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Multiple sequence alignments (MSAs) are used for structural 1,2 and evolutionary predictions 1,2 , but the complexity of aligning large datasets requires the use of approximate solutions 3 , including the progressive algorithm 4 . Progressive MSA methods start by aligning the most similar sequences and subsequently incorporate the remaining sequences, from leaf to root, based on a guide tree. Their accuracy declines substantially as the number of sequences is scaled up 5 . We introduce a regressive algorithm that enables MSA of up to 1.4 million sequences on a standard workstation and substantially improves accuracy on datasets larger than 10,000 sequences. Our regressive algorithm works the other way around from the progressive algorithm and begins by aligning the most dissimilar sequences. It uses an efficient divide-and-conquer strategy to run third-party alignment methods in linear time, regardless of their original complexity. Our approach will enable analyses of extremely large genomic datasets such as the recently announced Earth BioGenome Project, which comprises 1.5 million eukaryotic genomes 6 .

Background: Determining the factors involved in the likelihood of a gene being under adaptive selection is still a challenging goal in Evolutionary Biology. Here, we perform an evolutionary analysis of the human metabolic genes to explore the associations between network structure and the presence and strength of natural selection in the genes whose products are involved in metabolism. Purifying and positive selection are estimated at interspecific (among mammals) and intraspecific (among human populations) levels, and the connections between enzymatic reactions are differentiated between incoming (in-degree) and outgoing (out-degree) links., Results: We confirm that purifying selection has been stronger in highly connected genes. Long-term positive selection has targeted poorly connected enzymes, whereas short-term positive selection has targeted different enzymes depending on whether the selective sweep has reached fixation in the population: genes under a complete selective sweep are poorly connected, whereas those under an incomplete selective sweep have high out-degree connectivity. The last steps of pathways are more conserved due to stronger purifying selection, with long-term positive selection targeting preferentially enzymes that catalyze the first steps. However, short-term positive selection has targeted enzymes that catalyze the last steps in the metabolic network. Strong signals of positive selection have been found for metabolic processes involved in lipid transport and membrane fluidity and permeability., Conclusions: Our analysis highlights the importance of analyzing the same biological system at different evolutionary timescales to understand the evolution of metabolic genes and of distinguishing between incoming and outgoing links in a metabolic network. Short-term positive selection has targeted enzymes with a different connectivity profile depending on the completeness of the selective sweep, while long-term positive selection has targeted genes with fewer connections that code for enzymes that catalyze the first steps in the network., Reviewers: This article was reviewed by Diamantis Sellis and Brandon Invergo.

Metabolic networks comprise thousands of enzymatic reactions functioning in a controlled manner and have been shaped by natural selection. Thanks to the genome data, the footprints of adaptive (positive) selection are detectable, and the strength of purifying selection can be measured. This has made possible to know where, in the metabolic network, adaptive selection has acted and where purifying selection is more or less strong and efficient. We have carried out a comprehensive molecular evolutionary study of all the genes involved in the human metabolism. We investigated the type and strength of the selective pressures that acted on the enzyme-coding genes belonging to metabolic pathways during the divergence of primates and rodents. Then, we related those selective pressures to the functional and topological characteristics of the pathways. We have used DNA sequences of all enzymes (956) of the metabolic pathways comprised in the HumanCyc database, using genome data for humans and five other mammalian species. We have found that the evolution of metabolic genes is primarily constrained by the layer of the metabolism in which the genes participate: while genes encoding enzymes of the inner core of metabolism are much conserved, those encoding enzymes participating in the outer layer, mediating the interaction with the environment, are evolutionarily less constrained and more plastic, having experienced faster functional evolution. Genes that have been targeted by adaptive selection are endowed by higher out-degree centralities than non-adaptive genes, while genes with high in-degree centralities are under stronger purifying selection. When the position along the pathway is considered, a funnel-like distribution of the strength of the purifying selection is found. Genes at bottom positions are highly preserved by purifying selection, whereas genes at top positions, catalyzing the first steps, are open to evolutionary changes. These results show how functional and topological characteristics of metabolic pathways contribute to shape the patterns of evolutionary pressures driven by natural selection and how pathway network structure matters in the evolutionary process that shapes the evolution of the system., Competing Interests: The authors have declared that no competing interests exist.

Common variable immunodeficiency (CVID) is the most frequent symptomatic primary immunodeficiency characterized by recurrent infections, hypogammaglobulinemia and poor response to vaccines. Its diagnosis is made based on clinical and immunological criteria, after exclusion of other diseases that can cause similar phenotypes. Currently, less than 20% of cases of CVID have a known underlying genetic cause. We have analyzed whole-exome sequencing and copy number variants data of 36 children and adolescents diagnosed with CVID and healthy relatives to estimate the proportion of monogenic cases. We have replicated an association of CVID to p.C104R in TNFRSF13B and reported the second case of homozygous patient to date. Our results also identify five causative genetic variants in LRBA, CTLA4, NFKB1 , and PIK3R1 , as well as other very likely causative variants in PRKCD, MAPK8 , or DOCK8 among others. We experimentally validate the effect of the LRBA stop-gain mutation which abolishes protein production and downregulates the expression of CTLA4, and of the frameshift indel in CTLA4 producing expression downregulation of the protein. Our results indicate a monogenic origin of at least 15-24% of the CVID cases included in the study. The proportion of monogenic patients seems to be lower in CVID than in other PID that have also been analyzed by whole exome or targeted gene panels sequencing. Regardless of the exact proportion of CVID monogenic cases, other genetic models have to be considered for CVID. We propose that because of its prevalence and other features as intermediate penetrancies and phenotypic variation within families, CVID could fit with other more complex genetic scenarios. In particular, in this work, we explore the possibility of CVID being originated by an oligogenic model with the presence of heterozygous mutations in interacting proteins or by the accumulation of detrimental variants in particular immunological pathways, as well as perform association tests to detect association with rare genetic functional variation in the CVID cohort compared to healthy controls.

[This corrects the article DOI: 10.1371/journal.pone.0179446.].

During the demographic history of the Pan clade, there has been gene-flow between species, likely >200,000 years ago. Bonobo haplotypes in three subspecies of chimpanzee have been identified to be segregating in modern-day chimpanzee populations, suggesting that these haplotypes, with increased differentiation, may be a target of natural selection. Here, we investigate signatures of adaptive introgression within the bonobo-like haplotypes in chimpanzees using site frequency spectrum-based tests. We find evidence for subspecies-specific adaptations in introgressed regions involved with male reproduction in central chimpanzees, the immune system in eastern chimpanzees, female reproduction and the nervous system in Nigeria-Cameroon chimpanzees. Furthermore, our results indicate signatures of balancing selection in some of the putatively introgressed regions. This might be the product of long-term balancing selection resulting in a similar genomic signature as introgression, or possibly balancing selection acting on alleles reintroduced through gene flow.

The 1000 Genomes Project (1000GP) represents the most comprehensive world-wide nucleotide variation data set so far in humans, providing the sequencing and analysis of 2504 genomes from 26 populations and reporting >84 million variants. The availability of this sequence data provides the human lineage with an invaluable resource for population genomics studies, allowing the testing of molecular population genetics hypotheses and eventually the understanding of the evolutionary dynamics of genetic variation in human populations. Here we present PopHuman, a new population genomics-oriented genome browser based on JBrowse that allows the interactive visualization and retrieval of an extensive inventory of population genetics metrics. Efficient and reliable parameter estimates have been computed using a novel pipeline that faces the unique features and limitations of the 1000GP data, and include a battery of nucleotide variation measures, divergence and linkage disequilibrium parameters, as well as different tests of neutrality, estimated in non-overlapping windows along the chromosomes and in annotated genes for all 26 populations of the 1000GP. PopHuman is open and freely available at http://pophuman.uab.cat., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The chimpanzee is arguably the most important species for the study of human origins. A key resource for these studies is a high-quality reference genome assembly; however, as with most mammalian genomes, the current iteration of the chimpanzee reference genome assembly is highly fragmented. In the current iteration of the chimpanzee reference genome assembly (Pan_tro_2.1.4), the sequence is scattered across more then 183 000 contigs, incorporating more than 159 000 gaps, with a genome-wide contig N50 of 51 Kbp. In this work, we produce an extensive and diverse array of sequencing datasets to rapidly assemble a new chimpanzee reference that surpasses previous iterations in bases represented and organized in large scaffolds. To this end, we show substantial improvements over the current release of the chimpanzee genome (Pan_tro_2.1.4) by several metrics, such as increased contiguity by >750% and 300% on contigs and scaffolds, respectively, and closure of 77% of gaps in the Pan_tro_2.1.4 assembly gaps spanning >850 Kbp of the novel coding sequence based on RNASeq data. We further report more than 2700 genes that had putatively erroneous frame-shift predictions to human in Pan_tro_2.1.4 and show a substantial increase in the annotation of repetitive elements. We apply a simple 3-way hybrid approach to considerably improve the reference genome assembly for the chimpanzee, providing a valuable resource for the study of human origins. Furthermore, we produce extensive sequencing datasets that are all derived from the same cell line, generating a broad non-human benchmark dataset., (© The Author 2017. Published by Oxford University Press.)

We present 42 new Y-chromosomal sequences from diverse Indian tribal and non-tribal populations, including the Jarawa and Onge from the Andaman Islands, which are analysed within a calibrated Y-chromosomal phylogeny incorporating South Asian (in total 305 individuals) and worldwide (in total 1286 individuals) data from the 1000 Genomes Project. In contrast to the more ancient ancestry in the South than in the North that has been claimed, we detected very similar coalescence times within Northern and Southern non-tribal Indian populations. A closest neighbour analysis in the phylogeny showed that Indian populations have an affinity towards Southern European populations and that the time of divergence from these populations substantially predated the Indo-European migration into India, probably reflecting ancient shared ancestry rather than the Indo-European migration, which had little effect on Indian male lineages. Among the tribal populations, the Birhor (Austro-Asiatic-speaking) and Irula (Dravidian-speaking) are the nearest neighbours of South Asian non-tribal populations, with a common origin in the last few millennia. In contrast, the Riang (Tibeto-Burman-speaking) and Andamanese have their nearest neighbour lineages in East Asia. The Jarawa and Onge shared haplogroup D lineages with each other within the last ~7000 years, but had diverged from Japanese haplogroup D Y-chromosomes ~53000 years ago, most likely by a split from a shared ancestral population. This analysis suggests that Indian populations have complex ancestry which cannot be explained by a single expansion model.

Natural selection is crucial for the adaptation of populations to their environments. Here, we present the first global study of natural selection in the Hominidae (humans and great apes) based on genome-wide information from population samples representing all extant species (including most subspecies). Combining several neutrality tests we create a multi-species map of signatures of natural selection covering all major types of natural selection. We find that the estimated efficiency of both purifying and positive selection varies between species and is significantly correlated with their long-term effective population size. Thus, even the modest differences in population size among the closely related Hominidae lineages have resulted in differences in their ability to remove deleterious alleles and to adapt to changing environments. Most signatures of balancing and positive selection are species-specific, with signatures of balancing selection more often being shared among species. We also identify loci with evidence of positive selection across several lineages. Notably, we detect signatures of positive selection in several genes related to brain function, anatomy, diet and immune processes. Our results contribute to a better understanding of human evolution by putting the evidence of natural selection in humans within its larger evolutionary context. The global map of natural selection in our closest living relatives is available as an interactive browser at http://tinyurl.com/nf8qmzh., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Nucleotide variants in microRNA regions have been associated with disease; nevertheless, few studies still have addressed the allele-dependent effect of these changes. We studied microRNA genetic variation in human populations and found that while low-frequency variants accumulate indistinctly in microRNA regions, the mature and seed regions tend to be depleted of high-frequency variants, probably as a result of purifying selection. Comparison of pairwise population fixation indexes among regions showed that the seed had higher population fixation indexes than the other regions, suggesting the existence of local adaptation in the seed region. We further performed functional studies of three microRNA variants associated with cancer (rs2910164:C > G in MIR146A, rs11614913:C > T in MIR196A2, and rs3746444:A > G in both MIR499A and MIR499B). We found differences in the expression between alleles and in the regulation of several genes involved in cancer, such as TP53, KIT, CDH1, CLH, and TERT, which may result in changes in regulatory networks related to tumorigenesis. Furthermore, luciferase-based assays showed that MIR499A could be regulating the cadherin CDH1 and the cell adhesion molecule CLH1 in an allele-dependent fashion. A better understanding of the effect of microRNA variants associated with disease could be key in our way to a more personalized medicine., (© 2016 WILEY PERIODICALS, INC.)

To shed light on the peopling of South Asia and the origins of the morphological adaptations found there, we analyzed whole-genome sequences from 10 Andamanese individuals and compared them with sequences for 60 individuals from mainland Indian populations with different ethnic histories and with publicly available data from other populations. We show that all Asian and Pacific populations share a single origin and expansion out of Africa, contradicting an earlier proposal of two independent waves of migration. We also show that populations from South and Southeast Asia harbor a small proportion of ancestry from an unknown extinct hominin, and this ancestry is absent from Europeans and East Asians. The footprints of adaptive selection in the genomes of the Andamanese show that the characteristic distinctive phenotypes of this population (including very short stature) do not reflect an ancient African origin but instead result from strong natural selection on genes related to human body size.

Motivation: Detecting positive selection in genomic regions is a recurrent topic in natural population genetic studies. However, there is little consistency among the regions detected in several genome-wide scans using different tests and/or populations. Furthermore, few methods address the challenge of classifying selective events according to specific features such as age, intensity or state (completeness)., Results: We have developed a machine-learning classification framework that exploits the combined ability of some selection tests to uncover different polymorphism features expected under the hard sweep model, while controlling for population-specific demography. As a result, we achieve high sensitivity toward hard selective sweeps while adding insights about their completeness (whether a selected variant is fixed or not) and age of onset. Our method also determines the relevance of the individual methods implemented so far to detect positive selection under specific selective scenarios. We calibrated and applied the method to three reference human populations from The 1000 Genome Project to generate a genome-wide classification map of hard selective sweeps. This study improves detection of selective sweep by overcoming the classical selection versus no-selection classification strategy, and offers an explanation to the lack of consistency observed among selection tests when applied to real data. Very few signals were observed in the African population studied, while our method presents higher sensitivity in this population demography., Availability and Implementation: The genome-wide results for three human populations from The 1000 Genomes Project and an R-package implementing the 'Hierarchical Boosting' framework are available at http://hsb.upf.edu/., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

East Africa is a strategic region to study human genetic diversity due to the presence of ethnically, linguistically, and geographically diverse populations. Here, we provide new insight into the genetic history of populations living in the Sudanese region of East Africa by analysing nine ethnic groups belonging to three African linguistic families: Niger-Kordofanian, Nilo-Saharan and Afro-Asiatic. A total of 500 individuals were genotyped for 200,000 single-nucleotide polymorphisms. Principal component analysis, clustering analysis using ADMIXTURE, FST statistics, and the three-population test were used to investigate the underlying genetic structure and ancestry of the different ethno-linguistic groups. Our analyses revealed a genetic component for Sudanese Nilo-Saharan speaking groups (Darfurians and part of Nuba populations) related to Nilotes of South Sudan, but not to other Sudanese populations or other sub-Saharan populations. Populations inhabiting the North of the region showed close genetic affinities with North Africa, with a component that could be remnant of North Africans before the migrations of Arabs from Arabia. In addition, we found very low genetic distances between populations in genes important for anti-malarial and anti-bacterial host defence, suggesting similar selective pressures on these genes and stressing the importance of considering functional pathways to understand the evolutionary history of populations.

Genes vary in their likelihood to undergo adaptive evolution. The genomic factors that determine adaptability, however, remain poorly understood. Genes function in the context of molecular networks, with some occupying more important positions than others and thus being likely to be under stronger selective pressures. However, how positive selection distributes across the different parts of molecular networks is still not fully understood. Here, we inferred positive selection using comparative genomics and population genetics approaches through the comparison of 10 mammalian and 270 human genomes, respectively. In agreement with previous results, we found that genes with lower network centralities are more likely to evolve under positive selection (as inferred from divergence data). Surprisingly, polymorphism data yield results in the opposite direction than divergence data: Genes with higher centralities are more likely to have been targeted by recent positive selection during recent human evolution. Our results indicate that the relationship between centrality and the impact of adaptive evolution highly depends on the mode of positive selection and/or the evolutionary time-scale., (© The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Summary: A wealth of large-scale genome sequencing projects opens the doors to new approaches to study the relationship between genotype and phenotype. One such opportunity is the possibility to apply genotype networks analysis to population genetics data. Genotype networks are a representation of the set of genotypes associated with a single phenotype, and they allow one to estimate properties such as the robustness of the phenotype to mutations, and the ability of its associated genotypes to evolve new adaptations. So far, though, genotype networks analysis has rarely been applied to population genetics data. To help fill this gap, here we present VCF2Networks, a tool to determine and study genotype network structure from single-nucleotide variant data., Availability and Implementation: VCF2Networks is available at https://bitbucket.org/dalloliogm/vcf2networks., Contact: giovanni.dallolio@kcl.ac.uk, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Indian demographic history includes special features such as founder effects, interpopulation segregation, complex social structure with a caste system and elevated frequency of consanguineous marriages. It also presents a higher frequency for some rare mendelian disorders and in the last two decades increased prevalence of some complex disorders. Despite the fact that India represents about one-sixth of the human population, deep genetic studies from this terrain have been scarce. In this study, we analyzed high-density genotyping and whole-exome sequencing data of a North and a South Indian population. Indian populations show higher differentiation levels than those reported between populations of other continents. In this work, we have analyzed its consequences, by specifically assessing the transferability of genetic markers from or to Indian populations. We show that there is limited genetic marker portability from available genetic resources such as HapMap or the 1,000 Genomes Project to Indian populations, which also present an excess of private rare variants. Conversely, tagSNPs show a high level of portability between the two Indian populations, in contrast to the common belief that North and South Indian populations are genetically very different. By estimating kinship from mates and consanguinity in our data from trios, we also describe different patterns of assortative mating and inbreeding in the two populations, in agreement with distinct mating preferences and social structures. In addition, this analysis has allowed us to describe genomic regions under recent adaptive selection, indicating differential adaptive histories for North and South Indian populations. Our findings highlight the importance of considering demography for design and analysis of genetic studies, as well as the need for extending human genetic variation catalogs to new populations and particularly to those with particular demographic histories.

Genotype networks are a concept used in systems biology to study sets of genotypes having the same phenotype, and the ability of these to bring forth novel phenotypes. In the past they have been applied to determine the genetic heterogeneity, and stability to mutations, of systems such as metabolic networks and RNA folds. Recently, they have been the base for reconciling the neutralist and selectionist views on evolution. Here, we adapted this concept to the study of population genetics data. Specifically, we applied genotype networks to the human 1000 genomes dataset, and analyzed networks composed of short haplotypes of Single Nucleotide Variants (SNV). The result is a scan of how properties related to genetic heterogeneity and stability to mutations are distributed along the human genome. We found that genes involved in acquired immunity, such as some HLA and MHC genes, tend to have the most heterogeneous and connected networks, and that coding regions tend to be more heterogeneous and stable to mutations than non-coding regions. We also found, using coalescent simulations, that regions under selection have more extended and connected networks. The application of the concept of genotype networks can provide a new opportunity to understand the evolutionary processes that shaped our genome. Learning how the genotype space of each region of our genome has been explored during the evolutionary history of the human species can lead to a better understanding on how selective pressures and neutral factors have shaped genetic diversity within populations and among individuals. Combined with the availability of larger datasets of sequencing data, genotype networks represent a new approach to the study of human genetic diversity that looks to the whole genome, and goes beyond the classical division between selection and neutrality methods.