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79 results for “Genetic admixture”
Data from: Genetic admixture increases phenotypic diversity in the nectar yeast Metschnikowia reukaufii,
<p>Raw data and supplementary files for the manuscript "Genetic admixture increases phenotypic diversity in the nectar yeast <em>Metschnikowia reukaufii</em>."</p> <p>-------------------</p> <p><strong>Table S5.xlsx </strong>-- Pairwise correlations between phenotypic traits of <em>Metschnikowia reukaufii</em>.</p> <p><strong>Table S6.xlsx</strong> -- Detailed results obtained in tests of phylogenetic signal for different phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>.</p> <p><strong>Table S7.xlsx</strong> -- Detailed model fitting results obtained for phenotypic traits and indices of overall performance of <em>Metschnikowia reukaufii</em>.</p> <p><strong>mronlyvcf-renamed.vcf</strong> -- High coverage SNPs obtained from whole genome mapping of 73 <em>Metschnikowia reukaufii</em> strains to diploid reference (mean coverage = 47.9×, range 23 – 116×).</p> <p><strong>MR_phenotypes.xlsx</strong> -- Phenotypic data obtained for 73 <em>Metschnikowia reukaufii</em> strains.</p>
Influence of Paleolithic Range Contraction, Admixture and Long-Distance Dispersal on Genetic Gradients of Modern Humans in Asia
<p>Each folder is identified according to the scenario, and contains another folder with the input files (files *.txt, *.par, *.sam, *.asc) to simulate it, the corresponding simulated genetic data (files *.arp) and the derived PC maps (files *.png). A file with the locations of the samples is also included (coord.txt).</p> <p>* Pure Paleolithic expansion * <br> The folder “Paleo” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion, ignoring the range contraction induced by the LGM and LDD events.</p> <p>* Pure Paleolithic expansion considering the range contraction induced by the LGM * <br> The folder “Paleo_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion suffering the range contraction induced by the LGM.</p> <p> * Pure Paleolithic expansion considering long-distance dispersal (LDD) events * <br> The folder “Paleo_LDD” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a pure Paleolithic expansion considering LDD events. </p> <p>* Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and East Asia considering the range contraction induced by the LGM * <br> The folder “Paleo2NeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and later from East Asia suffering the range contraction induced by the LGM. </p> <p>* Paleolithic expansion followed by two Neolithic expansions (IR=0) from Middle East and East Asia considering LDD events * <br> The folder “Paleo2NeoIR0_LDD” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by two Neolithic expansions from Middle East and later from East Asia considering LDD events. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0) from Middle East considering the range contraction induced by the LGM * <br> The folder “Paleo_MiddleEastNeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0) from Middle East suffering the range contraction induced by the LGM. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering the range contraction induced by the LGM * <br> The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES) and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia suffering the range contraction induced by the LGM. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0) from Middle East considering LDD events * <br> The folder “Paleo_MiddleEastNeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0) from Middle East considering LDD events. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering LDD events * <br> The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES) the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0) from East Asia considering LDD events. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from Middle East considering the range contraction induced by the LGM * <br> The folder “Paleo_MiddleEastNeoIR004_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia suffering the range contraction induced by the LGM. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering the range contraction induced by the LGM * <br> The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0.04) from East Asia suffering the range contraction induced by the LGM. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from Middle East considering LDD events * <br> The folder “Paleo_MiddleEastNeoIR004_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering LDD events. </p> <p>* Paleolithic expansion followed by a single Neolithic expansion (IR=0.04) from East Asia considering LDD events * <br> The folder “Paleo_EastAsiaNeoIR0_REC” contains the input files (INFILES), the genetic data and the corresponding PC maps simulated under the scenario of a Paleolithic expansion followed by a single Neolithic expansions (IR=0.04) from East Asia considering LDD events.</p>
Ancient DNA reveals genetic admixture in China during tiger evolution
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Data from: Influence of paleolithic range contraction, admixture and long-distance dispersal on genetic gradients of modern humans in Asia
<p>Cavalli-Sforza and coauthors originally explored the genetic variation of modern humans throughout the world and observed an overall east-west genetic gradient in Asia. However, the specific environmental and population genetics processes causing this gradient were not formally investigated and promoted discussion in recent studies. Here we studied the influence of diverse environmental and population genetics processes on Asian genetic gradients and identified which could have produced the observed gradient. To do so, we performed extensive spatially-explicit computer simulations of genetic data under the following scenarios: (<i>i</i>) variable levels of admixture between Paleolithic and Neolithic populations, (<i>ii</i>) migration through long-distance dispersal (LDD), (<i>iii</i>) Paleolithic range contraction induced by the last glacial maximum (LGM) and, (<i>iv</i>) Neolithic range expansions from one or two geographic origins (the Fertile Crescent and the Yangzi and Yellow River Basins). Next, we estimated genetic gradients from the simulated data and we found that they were sensible to the analyzed processes, especially to the range contraction induced by LGM and to the number of Neolithic expansions. Some scenarios were compatible with the observed east-west genetic gradient, such as the Paleolithic expansion with a range contraction induced by the LGM or two Neolithic range expansions from both the east and the west. In general, LDD increased the variance of genetic gradients among simulations. We interpreted the obtained gradients as a consequence of both <i>allele surfing</i> caused by range expansions and isolation by distance along the vast east-west geographic axis of this continent.</p>
Genetic admixture between Central European and Alpine wolf populations
<p>The recovery and expansion of formerly isolated wolf populations in Europe raise questions about the nature of their interactions and future consequences for population viability and conservation. Will fragmented populations fuse or maintain a certain level of isolation with migration? Central Europe is suitable for obtaining empirical data in this field as it represents a "crossroad" with the potential for contact among several phylogeographic lineages. In this study, non-invasive genetic samples obtained during population monitoring in the Bohemian and Bavarian Forest (BBF) mountain ranges in the Czech Republic and Germany (Bohemian Massif) were analysed at different neutral markers including mitochondrial sequence, nuclear autosomal microsatellites and gonosomal sex markers. Resultant genetic profiles were compared with reference data to study population ancestry. Both cluster analyses of microsatellite genotypes and syntopic occurrence of haplotypes HW01 and HW22 showed genetic admixture between Central European and Alpine populations. This represents secondary contact and interbreeding of formerly allopatric populations with different phylogeographic histories and distant expansion centres in different biomes in the Baltic region versus the Apennine peninsula and Alps. Moreover, the study describes the founding event and genealogy of this admixed deme, inhabiting intermediate environmental conditions compared to parental forms, and emphasises the role of protected areas as stepping stones in the range recolonization process in endangered large mammals.</p>
Population differentiation and intraspecific genetic admixture in two Eucryptorrhynchus weevils (Coleoptera: Curculionidae) across northern China
<p><span>Inreasing damage of pests in agriculture and forestry can arise both as a consequence of changes in local species and through the introduction of alien species. In this study, we used population genetics approaches to examine population processes of two pests of the tree-of-heaven trunk weevil (TTW), <em>Eucryptorrhynchus brandti</em> (Harold) and the tree-of-heaven root weevil (TRW), <em>E. scrobiculatus</em> (Motschulsky) on the tree-of-heaven across their native range of China. We analyzed the population genetics of the two weevils based on ten highly polymorphic microsatellite markers. Population genetic diversity analysis showed strong population differentiation among populations of each species, with FST ranges from 0.0197 to 0.6650 and from -0.0724 to 0.6845, respectively. Populations from the same geographical areas can be divided into different genetic clusters, and the same genetic cluster contained populations from different geographical populations, pointing to dispersal of the weevils possibly being human-mediated. Redundancy analysis showed that the independent effects of environment and geography could account for 93.94% and 29.70% of the explained genetic variance in TTW, and 41.90% and 55.73% of the explained genetic variance in TRW, respectively, indicating possible impacts of local climates on population genetic differentiation. Our study helps to uncover population genetic processes of these local pest species with relevance to control methods.</span></p>
Sex-biased admixture and assortative mating shape genetic variation and influence demographic inference in admixed Cabo Verdeans
<p>Inferred ROH and IBD calls from Korunes et al (2022). bioRxiv DOI: https://doi.org/10.1101/2020.12.14.422766</p> <p>Samples originally collected and analyzed in Beleza et al. 2013, PLoS Genetics. Inferred local ancestry information can be found at <a href="https://doi.org/10.5281/zenodo.4021277">https://doi.org/10.5281/zenodo.4021277</a></p> <p>See README.txt in upload for more detailed information.</p>
Give and take: Effects of genetic admixture on mutation load in endangered Florida panthers
<p>Genetic admixture is a biological event inherent to genetic rescue programs aimed at the long-term conservation of endangered wildlife. Although the success of such programs can be measured by the increase in genetic diversity and fitness of subsequent admixed individuals, predictions supporting admixture costs to fitness due to the introduction of novel deleterious alleles are necessary. Here, we analyzed nonsynonymous variation from conserved genes to quantify and compare levels of mutation load (i.e., proportion of deleterious alleles and genotypes carrying these alleles) among endangered Florida panthers and non-endangered Texas pumas. Specifically, we used canonical (i.e., non-admixed) Florida panthers, Texas pumas, and F<sub>1</sub> (canonical Florida x Texas) panthers dating from a genetic rescue program and Everglades National Park panthers with Central American ancestry resulting from an earlier admixture event. We found neither genetic drift nor selection significantly reduced overall proportions of deleterious alleles in the severely bottlenecked canonical Florida panthers. Nevertheless, the deleterious alleles identified were distributed into a disproportionately high number of homozygous genotypes due to close inbreeding in this group. Conversely, admixed Florida panthers (either with Texas or Central American ancestry) presented reduced levels of homozygous genotypes carrying deleterious alleles but increased levels of heterozygous genotypes carrying these variants relative to canonical Florida panthers. Although admixture is likely to alleviate the load of standing deleterious variation present in homozygous genotypes, our results suggest introduced novel deleterious alleles (temporarily present in heterozygous state) in genetically rescued populations could potentially be expressed in subsequent generations if their effective sizes remain small.</p>
Data from: Admixture facilitates genetic adaptations to high altitude in Tibet
<p>Genotype data for the 69 high altitude Sherpa individuals from</p> <p> </p> <p>Jeong C, Alkorta-Aranburu G, Basnyat B, Neupane M, Witonsky DB, Pritchard JK, Beall CM, Di Rienzo A. Admixture facilitates genetic adaptations to high altitude in Tibet. Nat Commun. 2014;5:3281. doi: 10.1038/ncomms4281. PMID: 24513612; PMCID: PMC4643256.</p> <p> </p> <p>Files are in PLINK binary format.</p>
Genetic admixture and evolutionary history of Han Chinese in the Shandong Peninsula inferred from integrative modern and ancient genomic resources
<p>The allele frequency data of 264 individuals from Shandong Province and supplementary table.</p>
Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China
<p>Informations about the locations and genetic diversity of <em>Ambrosia artemisiifolia</em> populations in published paper "Patterns of genetic variation reflect multiple introductions and pre-admixture sources of common ragweed (Ambrosia artemisiifolia) in China".</p>
Data from: Colonization of marginal host plants by Callosobruchus seed beetles (Coleoptera: Chrysomelidae): effects of geographic source and genetic admixture
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Data from: Genome-wide SNP assessment of contemporary European red deer genetic structure highlights the distinction between peripheral populations and the main admixture zones in Europe
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Data from: Genomic analysis of a cardinalfish with larval homing potential reveals genetic admixture in the Okinawa Islands
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Data from: Genetic admixture and novel host shifts in a parasitic plant, Orobanche boninsimae (Orobanchaceae), endemic to the Ogasawara Islands
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Give and take: Effects of genetic admixture on mutation load in endangered Florida panthers
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Data from: Influence of paleolithic range contraction, admixture and long-distance dispersal on genetic gradients of modern humans in Asia
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Population differentiation and intraspecific genetic admixture in two Eucryptorrhynchus weevils (Coleoptera: Curculionidae) across northern China
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Genetic admixture between Central European and Alpine wolf populations
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Data from: Genetic differentiation and admixture between sibling allopolyploids in the Dactylorhiza majalis complex
Allopolyploidization often happens recurrently, but the evolutionary significance of its iterative nature is not yet fully understood. Of particular interest are the gene flow dynamics and the mechanisms that allow young sibling polyploids to remain distinct while sharing the same ploidy, heritage and overlapping distribution areas. By using eight highly variable nuclear microsatellites, newly reported here, we investigate the patterns of divergence and gene flow between 386 polyploid and 42 diploid individuals, representing the sibling allopolyploids Dactylorhiza majalis s.s. and D. traunsteineri s.l. and their parents at localities across Europe. We make use in our inference of the distinct distribution ranges of the polyploids, including areas in which they are sympatric (that is, the Alps) or allopatric (for example, Pyrenees with D. majalis only and Britain with D. traunsteineri only). Our results show a phylogeographic signal, but no clear genetic differentiation between the allopolyploids, despite the visible phenotypic divergence between them. The results indicate that gene flow between sibling Dactylorhiza allopolyploids is frequent in sympatry, with potential implications for the genetic patterns across their entire distribution range. Limited interploidal introgression is also evidenced, in particular between D. incarnata and D. traunsteineri. Altogether the allopolyploid genomes appear to be porous for introgression from related diploids and polyploids. We conclude that the observed phenotypic divergence between D. majalis and D. traunsteineri is maintained by strong divergent selection on specific genomic areas with strong penetrance, but which are short enough to remain undetected by genotyping dispersed neutral markers.
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