39 research outputs found
The evolutionary history of Drosophila buzzatii. XVII. Double mating and sperm predominance
Sperm predominance in males and double mating in females have been studied in 2 stocks of the cactophilic species Drosophila buzzatii. The relationship between double mating and total productivity of females was also ascertained. Our results show high values of sperm predominance and double mating. Moreover, female productivity is increased with a second mate. These results are discussed in relation to the mating strategy of this species.On a étudié la prédominance du sperme chez les mâles et le double accouplement chez les femelles dans 2 souches de l'espèce cactophile Drosophila buzzatii. La relation entre le double accouplement et la productivité totale des femelles a été aussi recherchée. Nos résultats montrent des valeurs élevées pour la prédominance du sperme et pour le double accouplement. De plus, on constate que la productivité des femelles est augmentée par un deuxième accouplement. Ces résultats sont discutés par rapport à la stratégie d'accouplement de cette espèce
Mapping selection within Drosophila melanogaster embryo's anatomy
We present a survey of selection across Drosophila melanogaster embryonic anatomy. Our approach integrates genomic variation, spatial gene expression patterns and development, with the aim of mapping adaptation over the entire embryo's anatomy. Our adaptation map is based on analyzing spatial gene expression information for 5,969 genes (from text-based annotations of in situ hybridization data directly from the BDGP database, Tomancak et al. 2007) and the polymorphism and divergence in these genes (from the project DGRP, Mackay et al. 2012).The proportion of non-synonymous substitutions that are adaptive, neutral or slightly deleterious are estimated for the set of genes expressed in each embryonic anatomical structure using the DFE-alpha method (Eyre-Walker and Keightley 2009),. This method is a robust derivative of the McDonald and Kreitman test (McDonald and Kreitman 1991). We also explore whether different anatomical structures differ in the phylogenetic age, codon usage or expression bias of the genes they express and whether genes expressed in many anatomical structures show more adaptive substitutions than other genes.We found that: (i) most of the digestive system and ectoderm-derived structures are under selective constraint, (ii) the germ line and some specific mesoderm-derived structures show high rates of adaptive substitution and (iii) the genes that are expressed in a small number of anatomical structures show higher expression bias, lower phylogenetic ages and less constraint
Standard and generalized McDonald–Kreitman test: a website to detect selection by comparing different classes of DNA sites
The McDonald and Kreitman test (MKT) is one of the most powerful and extensively used tests to detect the signature of natural selection at the molecular level. Here, we present the standard and generalized MKT website, a novel website that allows performing MKTs not only for synonymous and nonsynonymous changes, as the test was initially described, but also for other classes of regions and/or several loci. The website has three different interfaces: (i) the standard MKT, where users can analyze several types of sites in a coding region, (ii) the advanced MKT, where users can compare two closely linked regions in the genome that can be either coding or noncoding, and (iii) the multi-locus MKT, where users can analyze many separate loci in a single multi-locus test. The website has already been used to show that selection efficiency is positively correlated with effective population size in the Drosophila genus and it has been applied to include estimates of selection in DPDB. This website is a timely resource, which will presumably be widely used by researchers in the field and will contribute to enlarge the catalogue of cases of adaptive evolution. It is available at http://mkt.uab.es
Atlantic cod (Gadus morhua) hemoglobin genes: multiplicity and polymorphism
Background: Hemoglobin (Hb) polymorphism, assessed by protein gel electrophoresis, has been used almost exclusively to characterize the genetic structure of Atlantic cod (Gadus morhua) populations and to establish correlations with phenotypic traits such as Hb oxygen binding capacity, temperature tolerance and growth characteristics. The genetic system used to explain the results of gel electrophoresis entails the presence of one polymorphic locus with two major alleles (HbI-1; HbI-2). However, vertebrates have more than one gene encoding Hbs and recent studies have reported that more than one Hb gene is present in Atlantic cod. These observations prompted us to re-evaluate the number of Hb genes expressed in Atlantic cod, and to perform an in depth search for polymorphisms that might produce relevant phenotypes for breeding programs. Results: Analysis of Expressed Sequence Tags (ESTs) led to the identification of nine distinct Hb transcripts; four corresponding to the α Hb gene family and five to the β Hb gene family. To gain insights about the Hb genes encoding these transcripts, genomic sequence data was generated from heterozygous (HbI-1/2) parents and fifteen progeny; five of each HbI type, i.e., HbI-1/1, HbI-1/2 and HbI-2/2. β Hb genes displayed more polymorphism than α Hb genes. Two major allele types (β1A and β1B) that differ by two linked non-synonymous substitutions (Met55Val and Lys62Ala) were found in the β1 Hb gene, and the distribution of these β1A and β1B alleles among individuals was congruent with that of the HbI-1 and HbI-2 alleles determined by protein gel electrophoresis. RT-PCR and Q-PCR analysis of the nine Hb genes indicates that all genes are expressed in adult fish, but their level of expression varies greatly; higher expression of almost all Hb genes was found in individuals displaying the HbI-2/2 electrophoretic type. Conclusion: This study indicates that more Hb genes are present and expressed in adult Atlantic cod than previously documented. Our finding that nine Hb genes are expressed simultaneously in adult fish suggests that Atlantic cod, similarly to fish such as rainbow trout, carp, and goldfish, might be able to respond to environmental challenges such as chronic hypoxia or long-term changes in temperature by altering the level of expression of these genes. In this context, the role of the non-conservative substitution Lys62Ala found in the β1 Hb gene, which appears to explain the occurrence of the HbI-1 and HbI-2 alleles described by gel electrophoresis, and which was found to be present in other fish such as eel, emerald rockcod, rainbow trout and moray, requires further investigation
The Drosophila melanogaster Genetic Reference Panel
A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics
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