Formulating a Historical and Demographic Model of Recent Human Evolution Based on Resequencing Data from Noncoding Regions

BACKGROUND: Estimating the historical and demographic parameters that characterize modern human populations is a fundamental part of reconstructing the recent history of our species. In addition, the development of a model of human evolution that can best explain neutral genetic diversity is required to identify confidently regions of the human genome that have been targeted by natural selection. METHODOLOGY/PRINCIPAL FINDINGS: We have resequenced 20 independent noncoding autosomal regions dispersed throughout the genome in 213 individuals from different continental populations, corresponding to a total of approximately 6 Mb of diploid resequencing data. We used these data to explore and co-estimate an extensive range of historical and demographic parameters with a statistical framework that combines the evaluation of multiple models of human evolution via a best-fit approach, followed by an Approximate Bayesian Computation (ABC) analysis. From a methodological standpoint, evaluating the accuracy of the parameter co-estimation allowed us to identify the most accurate set of statistics to be used for the estimation of each of the different historical and demographic parameters characterizing recent human evolution. CONCLUSIONS/SIGNIFICANCE: Our results support a model in which modern humans left Africa through a single major dispersal event occurring approximately 60,000 years ago, corresponding to a drastic reduction of approximately 5 times the effective population size of the ancestral African population of approximately 13,800 individuals. Subsequently, the ancestors of modern Europeans and East Asians diverged much later, approximately 22,500 years ago, from the population of ancestral migrants. This late diversification of Eurasians after the African exodus points to the occurrence of a long maturation phase in which the ancestral Eurasian population was not yet diversified

Genetic and Transcriptional Analysis of Human Host Response to Healthy Gut Microbiota

Many studies have demonstrated the importance of the gut microbiota in healthy and disease states. However, establishing the causality of host-microbiota interactions in humans is still challenging. Here, we describe a novel experimental system to define the transcriptional response induced by the microbiota for human cells and to shed light on the molecular mechanisms underlying host-gut microbiota interactions. In primary human colonic epithelial cells, we identified over 6,000 genes whose expression changed at various time points following coculturing with the gut microbiota of a healthy individual. Among the differentially expressed genes we found a 1.8-fold enrichment of genes associated with diseases that have been previously linked to the microbiome, such as obesity and colorectal cancer. In addition, our experimental system allowed us to identify 87 host single nucleotide polymorphisms (SNPs) that show allele-specific expression in 69 genes. Furthermore, for 12 SNPs in 12 different genes, allele-specific expression is conditional on the exposure to the microbiota. Of these 12 genes, 8 have been associated with diseases linked to the gut microbiota, specifically colorectal cancer, obesity, and type 2 diabetes. Our study demonstrates a scalable approach to study host-gut microbiota interactions and can be used to identify putative mechanisms for the interplay between host genetics and the microbiota in health and disease

Analysis of interval‐grouped data in weed science: The binnednp Rcpp package

[Abstract] Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). However, in many situations, experimental data are presented in a grouped way and, therefore, the standard nonparametric kernel estimators cannot be computed. Kernel estimators for the density and distribution functions for interval‐grouped data, as well as bootstrap confidence bands for these functions, have been proposed and implemented in the binnednp package. Analysis with different treatments can also be performed using a bootstrap approach and a Cramér‐von Mises type distance. Several bandwidth selection procedures were also implemented. This package also allows to estimate different emergence indices that measure the shape of the data distribution. The values of these indices are useful for the selection of the soil depth at which HTT should be measured which, in turn, would maximize the predictive power of the proposed methods. This paper presents the functions of the package and provides an example using an emergence data set of Avena sterilis (wild oat). The binnednp package provides investigators with a unique set of tools allowing the weed science research community to analyze interval‐grouped data.Ministerio de Economía y Competitividad; AGL2015-64130-RMinisterio de Economía y Competitividad; MTM2014-52876-RMinisterio de Economía y Competitividad; MTM2017-82724-RMinisterio de Economía y Competitividad; AGL2012-33736Xunta de Galicia; ED431C-2016-015Xunta de Galicia; ED431G/0

Gene activation precedes DNA demethylation in response to infection in human dendritic cells

DNA methylation is considered to be a relatively stable epigenetic mark. However, a growing body of evidence indicates that DNA methylation levels can change rapidly; for example, in innate immune cells facing an infectious agent. Nevertheless, the causal relationship between changes in DNA methylation and gene expression during infection remains to be elucidated. Here, we generated time-course data on DNA methylation, gene expression, and chromatin accessibility patterns during infection of human dendritic cells with Mycobacterium tuberculosis. We found that the immune response to infection is accompanied by active demethylation of thousands of CpG sites overlapping distal enhancer elements. However, virtually all changes in gene expression in response to infection occur before detectable changes in DNA methylation, indicating that the observed losses in methylation are a downstream consequence of transcriptional activation. Footprinting analysis revealed that immune-related transcription factors (TFs), such as NF-κB/Rel, are recruited to enhancer elements before the observed losses in methylation, suggesting that DNA demethylation is mediated by TF binding to cis-acting elements. Collectively, our results show that DNA demethylation plays a limited role to the establishment of the core regulatory program engaged upon infection

Primate innate immune responses to bacterial and viral pathogens reveals an evolutionary trade-off between strength and specificity

Despite their close genetic relatedness, apes and African and Asian monkeys (AAMs) differ in their susceptibility to severe bacterial and viral infections that are important causes of human disease. Such differences between humans and other primates are thought to be a result, at least in part, of interspecies differences in immune response to infection. However, because of the lack of comparative functional data across species, it remains unclear in what ways the immune systems of humans and other primates differ. Here, we report the whole-genome transcriptomic responses of ape species (human and chimpanzee) and AAMs (rhesus macaque and baboon) to bacterial and viral stimulation. We find stark differences in the responsiveness of these groups, with apes mounting a markedly stronger early transcriptional response to both viral and bacterial stimulation, altering the transcription of ∼40% more genes than AAMs. Additionally, we find that genes involved in the regulation of inflammatory and interferon responses show the most divergent early transcriptional responses across primates and that this divergence is attenuated over time. Finally, we find that relative to AAMs, apes engage a much less specific immune response to different classes of pathogens during the early hours of infection, up-regulating genes typical of anti-viral and anti-bacterial responses regardless of the nature of the stimulus. Overall, these findings suggest apes exhibit increased sensitivity to bacterial and viral immune stimulation, activating a broader array of defense molecules that may be beneficial for early pathogen killing at the potential cost of increased energy expenditure and tissue damage

Mitochondrial cyclophilin D promotes disease tolerance by licensing NK cell development and IL-22 production against influenza virus

Severity of pulmonary viral infections, including influenza A virus (IAV), is linked to excessive immunopathology, which impairs lung function. Thus, the same immune responses that limit viral replication can concomitantly cause lung damage that must be countered by largely uncharacterized disease tolerance mechanisms. Here, we show that mitochondrial cyclophilin D (CypD) protects against IAV via disease tolerance. Cyp

A new cosmological tracker solution for Quintessence

In this paper we propose a quintessence model with the potential $V(\Phi )=V_{o}[ \sinh {(\alpha \sqrt{\kappa_{o}}\Delta \Phi})] ^{\beta}$, which asymptotic behavior corresponds to an inverse power-law potential at early times and to an exponential one at late times. We demonstrate that this is a tracker solution and that it could have driven the Universe into its current inflationary stage. The exact solutions and the description for a complete evolution of the Universe are also given. We compare such model with the current cosmological observations.Comment: 13 pages REVTeX, 5 eps color figure

Density and expansion effects on pion spectra in relativistic heavy-ion collisions

We compute the pion inclusive momentum distribution in heavy-ion collisions at AGS energies, assuming thermal equilibrium and accounting for density and expansion effects at the time of decoupling. We compare to data on mid rapidity charged pions produced in central Au + Au collisions and find a very good agreement. The shape of the distribution at low $m_t-m$ is explained in part as an effect arising from the high mean pion density achieved in these reactions. The difference between the positive and negative pion distributions in the same region is attributed in part to the different average yields of each kind of charged pions.Comment: Minor changes, typo in Fig. 2b corrected, version to appear in Phys. Rev.

Human alveolar macrophage metabolism is compromised during Mycobacterium tuberculosis infection

Pulmonary macrophages have two distinct ontogenies: long-lived embryonically-seeded alveolar macrophages (AM) and bone marrow-derived macrophages (BMDM). Here, we show that after infection with a virulent strain of Mycobacterium tuberculosis (H37Rv), primary murine AM exhibit a unique transcriptomic signature characterized by metabolic reprogramming distinct from conventional BMDM. In contrast to BMDM, AM failed to shift from oxidative phosphorylation (OXPHOS) to glycolysis and consequently were unable to control infection with an avirulent strain (H37Ra). Importantly, healthy human AM infected with H37Ra equally demonstrated diminished energetics, recapitulating our observation in the murine model system. However, the results from seahorse showed that the shift towards glycolysis in both AM and BMDM was inhibited by H37Rv. We further demonstrated that pharmacological (e.g. metformin or the iron chelator desferrioxamine) reprogramming of AM towards glycolysis reduced necrosis and enhanced AM capacity to control H37Rv growth. Together, our results indicate that the unique bioenergetics of AM renders these cells a perfect target for Mtb survival and that metabolic reprogramming may be a viable host targeted therapy against TB