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 data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, 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data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in 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 data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. 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 data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.We thank four reviewers and the handling editor for helpful comments on previous versions of our manuscript. We are grateful to the members of the DrosEU and DrosRTEC consortia for their long-standing support, collaboration, and for discussion. DrosEU was funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). M.K. was supported by the Austrian Science Foundation (grant no. FWF P32275); J.G. 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); T.F. 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); M.K. by Academy of Finland grant 322980; V.L. by Danish Natural Science Research Council (FNU) (grant no. 4002-00113B); FS Deutsche Forschungsgemeinschaft (DFG) (grant no. STA1154/4-1), Project 408908608; J.P. by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; A.U. by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) (grant no. 1737/17); M.S.V., M.S.R. and M.J. by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); A.P., K.E. and M.T. 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. The authors acknowledge Research Computing at The University of Virginia for providing computational resources and technical support that have contributed to the results reported within this publication (https://rc.virginia.edu, last accessed September 6, 2021)

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

Corrigendum to: 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

Nivel de conocimiento de diagnóstico y manejo inicial del Síndrome Metabólico en residentes de los posgrados de Medicina Interna y Medicina Familiar y Comunitaria de la Pontificia Universidad Católica del Ecuador

Introducción: El síndrome metabólico es un grupo de enfermedades que se encuentran caracterizadas por una aparición insidiosa, que, por lo general tarda en ser diagnosticado. Es causado por los cambios en estilo de vida, predominio del sedentarismo y malos hábitos alimentarios. Los profesionales de la salud deben diagnosticarlo a tiempo para poder iniciar el tratamiento adecuado. Objetivo: Determinar el nivel de conocimiento de diagnóstico y manejo inicial del SM en residentes de los postgrados de Medicina Interna y Medicina Familiar y Comunitaria de la Pontificia Universidad Católica del Ecuador. Metodología: Estudio descriptivo y transversal, en 235 residentes de Medicina Interna y Medicina Familiar y Comunitaria de todas las sedes de la Pontificia Universidad Católica del Ecuador, a los cuales se les aplicó una encuesta. Esta consiste en preguntas relacionadas al conocimiento sobre el síndrome metabólico, su diagnóstico y manejo inicial. Para el análisis de los datos se utilizó el programa estadístico SPSS en su versión 23. Resultados: El nivel de conocimiento sobre síndrome metabólico fue bueno en la mayoría de los participantes (66,4%). La esfera más afectada fue la de la dieta recomendada en los pacientes y la más sobresaliente fue la de los factores de riesgo para el desarrollo de esta enfermedad. El conocimiento insuficiente se relacionó a la presencia de antecedentes familiares de patologías metabólicas mientras que el no tener dislipidemia se asoció a un buen manejo de la información sobre el síndrome metabólico. Conclusiones: El 66,4% de los residentes maneja un buen conocimiento, sin embargo, una parte importante no lo hace, por lo tanto, es indispensable mejorar la información que reciben en referencia a esta condición

Efecto del nivel de dióxido de carbono de la incubadora sobre el desarrollo embrionario y parámetros de eclosión en pollo de engorda

Oxygen (O2) and carbon dioxide (CO2) are vital gases for the embryo during the incubation process, its level is essential at pipping, to evaluate the effect of incubator carbon dioxide level on embryonic development, hatching parameters, and post-hatch growth of broiler, humidity loss, hatchability, weight of chicken, size of chicken, blood glucose, hematocrit and plasma proteins were measured. A total of 600 eggs from commercial breeding Cobb 500 41 weeks, were selected by weight from 65 to 70 g, were distributed on two incubators. A machine was kept at 4000 ppm and the other to 3000 ppm CO2. We used a 2 x 2 factorial design. The hatchability was better to 3000 ppm of CO2 and egg weight of 65 g chicken egg; the chicken was heavier with eggs of 70 g, to more ppm of CO2 reduction in the loss of humidity, was observed over a large chicken, blood glucose levels were not affected, but the values of plasma protein were less than 3000 ppm CO2. Improved hatching parameters at lower ppm of CO2 during the incubation processEl oxígeno (O2) y el dióxido de carbono (CO2) son gases vitales para el embrión durante el proceso de incubación, su nivel es imprescindible en el momento del picaje, con la finalidad de evaluar el efecto del nivel de dióxido de carbono de la incubadora sobre el desarrollo embrionario, los parámetros de eclosión y el posterior crecimiento del pollo de engorda, se midió la pérdida de humedad, incubabilidad, peso del pollo, tamaño del pollo, glucosa sanguínea, hematocrito y proteínas plasmáticas. Un total de 600 huevos de reproductora comercial Cobb 500 de 41 semanas, se seleccionaron por peso de 65 y 70 g, se distribuyeron en dos máquinas incubadoras. Una máquina se mantuvo a 4000 ppm y la otra a 3000 ppm de CO2. Se utilizó un diseño factorial 2 x 2. La incubabilidad fue mayor a 3000 ppm de CO2 y peso de huevo de 65 g; el pollo más pesado fue con huevo de 70 g, a mayor ppm de CO2 menor pérdida de humedad, a menor ppm de CO2 se observó un pollo más grande, los niveles de glucosa no se afectaron, pero los valores de proteínas plasmáticas fueron menores a 3000 ppm de CO2. Se mejoran los parámetros de eclosión al bajar las ppm de CO2 durante el proceso de incubació

Argovit™ Silver Nanoparticles Effects on Allium cepa: Plant Growth Promotion without Cyto Genotoxic Damage

Due to their antibacterial and antiviral effects, silver nanoparticles (AgNP) are one of the most widely used nanomaterials worldwide in various industries, e.g., in textiles, cosmetics and biomedical-related products. Unfortunately, the lack of complete physicochemical characterization and the variety of models used to evaluate its cytotoxic/genotoxic effect make comparison and decision-making regarding their safe use difficult. In this work, we present a systematic study of the cytotoxic and genotoxic activity of the commercially available AgNPs formulation Argovit™ in Allium cepa. The evaluated concentration range, 5–100 µg/mL of metallic silver content (85–1666 µg/mL of complete formulation), is 10–17 times higher than the used for other previously reported polyvinylpyrrolidone (PVP)-AgNP formulations and showed no cytotoxic or genotoxic damage in Allium cepa. Conversely, low concentrations (5 and 10 µg/mL) promote growth without damage to roots or bulbs. Until this work, all the formulations of PVP-AgNP evaluated in Allium cepa regardless of their size, concentration, or the exposure time had shown phytotoxicity. The biological response observed in Allium cepa exposed to Argovit™ is caused by nanoparticles and not by silver ions. The metal/coating agent ratio plays a fundamental role in this response and must be considered within the key physicochemical parameters for the design and manufacture of safer nanomaterials

A modified supraclavicular approach to scalenotomy without first rib resection for the treatment of neurogenic thoracic outlet syndrome

Background: Current approaches to scalenectomy for brachial plexus decompression can cause nerve injuries in patients with neurogenic thoracic outlet syndrome (nTOS), especially when first rib resection (FRR) is performed. We describe a modified supraclavicular approach for scalenotomy that reduces the postoperative morbidity of nTOS patients. Methods: The patient is placed in supine position with the neck slightly extended and turned to the opposite side of the procedure. The modified incision begins above the clavicle 2.5 cm lateral to its first third, extends in medial direction, and turns upwards along the lateral edge of the sternocleidomastoid muscle (SCM) 2.5 cm from the clavicle. Skin flaps are elevated. The external jugular vein is dissected and retracted. The supraclavicular nerves and omohyoid muscle are conserved if found. The phrenic nerve is identified, dissected, and retracted. The anterior scalene muscle is divided, and the brachial plexus is freed. The clinical data and postoperative outcomes of patients that underwent surgery over the last three years were retrieved. The functionality of the arm after surgery was evaluated using the Disabilities of the Arm, Shoulder, and Hand questionnaire in Spanish (DASHe). Results: Sixteen nTOS patients received surgery with one bilateral procedure (17 procedures). Seventy-five percent were females with a median age of 53 years. Obesity and smoking were observed in 43.75% and 37.5% of patients, respectively. No postoperative complications occurred, except for one partial phrenic nerve palsy. All patients reduced their DASHe scores after surgery (mean reduction 41.09 ± 18.37). Conclusion: Our modified supraclavicular approach for scalenotomy is safe and improves outcomes in patients with nTOS, reducing the need for FRR