IMKT : the integrative McDonald and Kreitman test

The McDonald and Kreitman test (MKT) is one of the most powerful and widely used methods to detect and quantify recurrent natural selection using DNA sequence data. Here we present iMKT (acronym for integrative McDonald and Kreitman test), a novel web-based service performing four distinct MKT types. It allows the detection and estimation of four different selection regimes -adaptive, neutral, strongly deleterious and weakly deleterious- acting on any genomic sequence. iMKT can analyze both user's own population genomic data and pre-loaded Drosophila melanogaster and human sequences of protein-coding genes obtained from the largest population genomic datasets to date. Advanced options in the website allow testing complex hypotheses such as the application example showed here: do genes located in high recombination regions undergo higher rates of adaptation? We aim that iMKT will become a reference site tool for the study of evolutionary adaptation in massive population genomics datasets, especially in Drosophila and humans. iMKT is a free resource online at https://imkt.uab.cat

PopHumanScan : the online catalog of human genome adaptation

Since the migrations that led humans to colonize Earth, our species has faced frequent adaptive challenges that have left signatures in the landscape of genetic variation and that we can identify in our today-s genomes. Here, we (i) perform an outlier approach on eight different population genetic statistics for 22 non-admixed human populations of the Phase III of the 1000 Genomes Project to detect selective sweeps at different historical ages, as well as events of recurrent positive selection in the human lineage; and (ii) create PopHumanScan, an online catalog that compiles and annotates all candidate regions under selection to facilitate their validation and thoroughly analysis. Well-known examples of human genetic adaptation published elsewhere are included in the catalog, as well as hundreds of other attractive candidates that will require further investigation. Designed as a collaborative database, PopHumanScan aims to become a central repository to share information, guide future studies and help advance our understanding of how selection has modeled our genomes as a response to changes in the environment or lifestyle of human populations. PopHumanScan is open and freely available at https://pophumanscan.uab.cat

Identifiquen més de 800 noves regions del genoma que podrien ser rellevants en l'evolució humana

Un estudi del grup de recerca Bioinformàtica de la Diversitat Genòmica de la UAB, publicat a la revista Nucleic Acids Research, incrementa en un 40% el total dels senyals de selecció natural en el genoma humà detectades fins ara. Els investigadors han aconseguit sumar un total de 873 noves regions del genoma humà com a fermes candidates d'haver estat el blanc de la selecció natural en algun moment des del sorgiment de la nostra espècie fins al present. Aquestes se sumen a les 1986 que ja s'havien detectat fins a la data, proporcionant un conjunt de dades molt valuós per respondre a la pregunta: què ens fa humans? Les dades són fruit del projecte PopHumanScan, un catàleg exhaustiu de regions que mostren evidències de la selecció natural en el genoma humà.Un estudio del grupo de investigación Bioinformática de la Diversidad Genómica de la UAB, publicado en la revista Nucleic Acids Research, incrementa en un 40% el total de las señales de selección natural en el genoma humano detectadas hasta la fecha. Los investigadores han conseguido sumar un total de 873 nuevas regiones del genoma humano como firmes candidatas de haber sido el blanco de la selección natural en algún momento desde el surgimiento de nuestra especie hasta el presente. Estas se suman a las 1986 que ya se habían detectado hasta la fecha, proporcionado un conjunto de datos muy valioso para responder a la pregunta: ¿qué nos hace humanos? Los datos son fruto del proyecto PopHumanScan, un catálogo exhaustivo de regiones que muestran evidencias de la selección natural en el genoma humano.A study by the research group Bioinformatics of Genome Diversity at the Universitat Autònoma de Barcelona (UAB), published in the journal Nucleic Acids Research, increases by 40% the total number of signals of natural selection detected in the human genome to date. Researchers were able to add a total of 873 new regions of the human genome as firm candidates to have been the target of natural selection at some point from the emergence of our species to the present. These are added to the 1986 regions that had already been detected, providing a very valuable set of data to help answer the question: what makes us humans? The data is part of the PopHumanScan project, an exhaustive catalog of regions that show evidence of natural selection in the human genome

Twin-Grating Fiber Optic Sensors Applied on Wavelength- Division Multiplexing and Its Numerical Resolution

In this work, the twin-grating fiber optic sensor has been applied on wavelength-division multiplexing. A quasi-distributed sensor formed by three local twin-grating sensors, is numerically simulated. The wavelength channels were 1531.5, 1535.5, and 1539.5 nm. The numerical simulation shows the resolution vs. signal-to-noise rate. Three local twin-grating sensors have approximately the same resolution because all local sensors have the same cavity length and the wavelength channels are very close. All local sensors have two numerical resolutions because the Fourier domain phase analysis algorithm makes two evaluations of the Bragg wavelength shift. The transition between both resolutions can be calculated with the parameters: cavity length, Bragg wavelength channel, refraction index, and enveloped resolution. This transition depends on the noise system, demodulation algorithm, instrumentation, and local sensor properties. A very important point is, a theoretical analysis will permit to know the exact resolution for each local twin-grating sensor

Drosophila evolution over space and time (DEST):A new population genomics resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.Peer reviewe

EDUCACIÓN AMBIENTAL Y SOCIEDAD. SABERES LOCALES PARA EL DESARROLLO Y LA SUSTENTABILIDAD

Este texto contribuye al análisis científico de varias áreas del conocimiento como la filosofía social, la patología, la educación para el cuidado del medio ambiente y la sustentabilidad que inciden en diversas unidades de aprendizaje de la Licenciatura en Educación para la Salud y de la Maestría en Sociología de la SaludLas comunidades indígenas de la sierra norte de Oaxaca México, habitan un territorio extenso de biodiversidad. Sin que sea una área protegida y sustentable, la propia naturaleza de la región ofrece a sus visitantes la riqueza de la vegetación caracterizada por sus especies endémicas que componen un paisaje de suma belleza

impMKT : the imputed McDonald and Kreitman test, a straightforward correction that significantly increases the evidence of positive selection of the McDonald and Kreitman test at the gene level

The McDonald and Kreitman test is one of the most powerful and widely used methods to detect and quantify recurrent natural selection in DNA sequence data. One of its main limitations is the underestimation of positive selection due to the presence of slightly deleterious variants segregating at low frequencies. Although several approaches have been developed to overcome this limitation, most of them work on gene pooled analyses. Here, we present the imputed McDonald and Kreitman test (impMKT), a new straightforward approach for the detection of positive selection and other selection components of the distribution of fitness effects at the gene level. We compare imputed McDonald and Kreitman test with other widely used McDonald and Kreitman test approaches considering both simulated and empirical data. By applying imputed McDonald and Kreitman test to humans and Drosophila data at the gene level, we substantially increase the statistical evidence of positive selection with respect to previous approaches (e.g. by 50% and 157% compared with the McDonald and Kreitman test in Drosophila and humans, respectively). Finally, we review the minimum number of genes required to obtain a reliable estimation of the proportion of adaptive substitution (a) in gene pooled analyses by using the imputed McDonald and Kreitman test compared with other McDonald and Kreitman test implementations. Because of its simplicity and increased power to detect recurrent positive selection on genes, we propose the imputed McDonald and Kreitman test as the first straightforward approach for testing specific evolutionary hypotheses at the gene level. The software implementation and population genomics data are available at the web-server imkt.uab.cat

Identifiquen més de 800 noves regions del genoma que podrien ser rellevants en l'evolució humana

Un estudi del grup de recerca Bioinformàtica de la Diversitat Genòmica de la UAB, publicat a la revista Nucleic Acids Research, incrementa en un 40% el total dels senyals de selecció natural en el genoma humà detectades fins ara. Els investigadors han aconseguit sumar un total de 873 noves regions del genoma humà com a fermes candidates d'haver estat el blanc de la selecció natural en algun moment des del sorgiment de la nostra espècie fins al present. Aquestes se sumen a les 1986 que ja s'havien detectat fins a la data, proporcionant un conjunt de dades molt valuós per respondre a la pregunta: què ens fa humans? Les dades són fruit del projecte PopHumanScan, un catàleg exhaustiu de regions que mostren evidències de la selecció natural en el genoma humà.Un estudio del grupo de investigación Bioinformática de la Diversidad Genómica de la UAB, publicado en la revista Nucleic Acids Research, incrementa en un 40% el total de las señales de selección natural en el genoma humano detectadas hasta la fecha. Los investigadores han conseguido sumar un total de 873 nuevas regiones del genoma humano como firmes candidatas de haber sido el blanco de la selección natural en algún momento desde el surgimiento de nuestra especie hasta el presente. Estas se suman a las 1986 que ya se habían detectado hasta la fecha, proporcionado un conjunto de datos muy valioso para responder a la pregunta: ¿qué nos hace humanos? Los datos son fruto del proyecto PopHumanScan, un catálogo exhaustivo de regiones que muestran evidencias de la selección natural en el genoma humano.A study by the research group Bioinformatics of Genome Diversity at the Universitat Autònoma de Barcelona (UAB), published in the journal Nucleic Acids Research, increases by 40% the total number of signals of natural selection detected in the human genome to date. Researchers were able to add a total of 873 new regions of the human genome as firm candidates to have been the target of natural selection at some point from the emergence of our species to the present. These are added to the 1986 regions that had already been detected, providing a very valuable set of data to help answer the question: what makes us humans? The data is part of the PopHumanScan project, an exhaustive catalog of regions that show evidence of natural selection in the human genome

PopHumanScan : the online catalog of human genome adaptation

Since the migrations that led humans to colonize Earth, our species has faced frequent adaptive challenges that have left signatures in the landscape of genetic variation and that we can identify in our today-s genomes. Here, we (i) perform an outlier approach on eight different population genetic statistics for 22 non-admixed human populations of the Phase III of the 1000 Genomes Project to detect selective sweeps at different historical ages, as well as events of recurrent positive selection in the human lineage; and (ii) create PopHumanScan, an online catalog that compiles and annotates all candidate regions under selection to facilitate their validation and thoroughly analysis. Well-known examples of human genetic adaptation published elsewhere are included in the catalog, as well as hundreds of other attractive candidates that will require further investigation. Designed as a collaborative database, PopHumanScan aims to become a central repository to share information, guide future studies and help advance our understanding of how selection has modeled our genomes as a response to changes in the environment or lifestyle of human populations. PopHumanScan is open and freely available at https://pophumanscan.uab.cat

IMKT : the integrative McDonald and Kreitman test

The McDonald and Kreitman test (MKT) is one of the most powerful and widely used methods to detect and quantify recurrent natural selection using DNA sequence data. Here we present iMKT (acronym for integrative McDonald and Kreitman test), a novel web-based service performing four distinct MKT types. It allows the detection and estimation of four different selection regimes -adaptive, neutral, strongly deleterious and weakly deleterious- acting on any genomic sequence. iMKT can analyze both user's own population genomic data and pre-loaded Drosophila melanogaster and human sequences of protein-coding genes obtained from the largest population genomic datasets to date. Advanced options in the website allow testing complex hypotheses such as the application example showed here: do genes located in high recombination regions undergo higher rates of adaptation? We aim that iMKT will become a reference site tool for the study of evolutionary adaptation in massive population genomics datasets, especially in Drosophila and humans. iMKT is a free resource online at https://imkt.uab.cat