scholarly journals Population genomic data in spider mites point to a role for local adaptation in shaping range shifts

2020 ◽  
Vol 13 (10) ◽  
pp. 2821-2835
Author(s):  
Lei Chen ◽  
Jing‐Tao Sun ◽  
Peng‐Yu Jin ◽  
Ary A. Hoffmann ◽  
Xiao‐Li Bing ◽  
...  
Keyword(s):  
Local Adaptation ◽  
Genomic Data ◽  
Spider Mites ◽  
Range Shifts ◽  
Population Genomic

scholarly journals Inferring Adaptive Introgression Using Hidden Markov Models

2020 ◽  
Author(s):  
Jesper Svedberg ◽  
Vladimir Shchur ◽  
Solomon Reinman ◽  
Rasmus Nielsen ◽  
Russell Corbett-Detig
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Genomic Data ◽  
Diverse Populations ◽  
Powerful Method ◽  
Adaptive Genetic Variation ◽  
Adaptive Introgression ◽  
Population Genomic ◽  
Significant Interest ◽  
Selection Parameters

AbstractAdaptive introgression - the flow of adaptive genetic variation between species or populations - has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a Hidden Markov Model based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized datasets for realistic population and selection parameters. We apply Ancestry_HMM-S to a dataset of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in datasets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.

scholarly journals Estimating Seven Coefficients of Pairwise Relatedness Using Population-Genomic Data

Genetics ◽  
2017 ◽  
Vol 206 (1) ◽  
pp. 105-118 ◽  
Author(s):  
Matthew S. Ackerman ◽  
Parul Johri ◽  
Ken Spitze ◽  
Sen Xu ◽  
Thomas G. Doak ◽  
...  
Keyword(s):  
Genomic Data ◽  
Population Genomic

scholarly journals Equitable Expanded Carrier Screening Needs Indigenous Clinical and Population Genomic Data

2020 ◽  
Vol 107 (2) ◽  
pp. 175-182
Author(s):  
Simon Easteal ◽  
Ruth M. Arkell ◽  
Renzo F. Balboa ◽  
Shayne A. Bellingham ◽  
Alex D. Brown ◽  
...  
Keyword(s):  
Genomic Data ◽  
Carrier Screening ◽  
Expanded Carrier Screening ◽  
Population Genomic

FIFS: A data mining method for informative marker selection in high dimensional population genomic data

2017 ◽  
Vol 90 ◽  
pp. 146-154 ◽  
Author(s):  
Ioannis Kavakiotis ◽  
Patroklos Samaras ◽  
Alexandros Triantafyllidis ◽  
Ioannis Vlahavas
Keyword(s):  
Data Mining ◽  
Genomic Data ◽  
High Dimensional ◽  
Mining Method ◽  
Informative Marker ◽  
Data Mining Method ◽  
Marker Selection ◽  
Population Genomic

scholarly journals The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data

Genetics ◽  
2017 ◽  
Vol 207 (1) ◽  
pp. 297-309 ◽  
Author(s):  
Tom R. Booker ◽  
Rob W. Ness ◽  
Peter D. Keightley
Keyword(s):  
Genomic Data ◽  
House Mice ◽  
Population Genomic ◽  
Wild House Mice

scholarly journals An evaluation of seed zone delineation using phenotypic and population genomic data on black alderAlnus glutinosa

2014 ◽  
Vol 51 (5) ◽  
pp. 1218-1227 ◽  
Author(s):  
Hanne De Kort ◽  
Joachim Mergeay ◽  
Kristine Vander Mijnsbrugge ◽  
Guillaume Decocq ◽  
Simona Maccherini ◽  
...  
Keyword(s):  
Genomic Data ◽  
Population Genomic ◽  
Seed Zone

scholarly journals A new test suggests that balancing selection maintains hundreds of non-synonymous polymorphisms in the human genome

2021 ◽  
Author(s):  
Vivak Soni ◽  
Michiel Vos ◽  
Adam Eyre-Walker
Keyword(s):  
Genetic Diversity ◽  
Human Genome ◽  
Balancing Selection ◽  
Genomic Data ◽  
Demographic Changes ◽  
Simple Test ◽  
Direct Estimate ◽  
Population Genomic

AbstractThe role that balancing selection plays in the maintenance of genetic diversity remains unresolved. Here we introduce a new test, based on the McDonald-Kreitman test, in which the number of polymorphisms that are shared between populations is contrasted to those that are private at selected and neutral sites. We show that this simple test is robust to a variety of demographic changes, and that it can also give a direct estimate of the number of shared polymorphisms that are directly maintained by balancing selection. We apply our method to population genomic data from humans and conclude that more than a thousand non-synonymous polymorphisms are subject to balancing selection.

scholarly journals Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

2019 ◽  
Author(s):  
Colin R. Mahony ◽  
Ian R. MacLachlan ◽  
Brandon M. Lind ◽  
Jeremy B. Yoder ◽  
Tongli Wang ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Local Adaptation ◽  
Lodgepole Pine ◽  
Genomic Data ◽  
Genomic Variation ◽  
Similar Species ◽  
Adaptive Variation ◽  
Phenotypic Data ◽  
Standing Variation ◽  
Climatic Drivers

AbstractThe need for tools to cost-effectively identify adaptive variation within ecologically and economically important plant species is mounting as the detrimental effects of climate change become increasingly apparent. For crop and wild populations alike, mismatches between adaptive variation and climatic optima will reduce health, growth, survival, reproduction, and continued establishment. The ease with which land managers can quantify the relative importance of different climate factors or the spatial scale of local adaptation to climate will have direct implications for the potential of mitigating or resolving such risks. Using seed collected from 281 provenances of lodgepole pine (Pinus contorta) from across western Canada, we compare genomic data to phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and spatial scale of local adaptation in this species. We find that genomic and climate data are nearly equivalent for describing local adaptation in seedling traits. We also find strong agreement between the climate variables associated with genomic variation and with 20-year heights from a long-term provenance trial, suggesting that genomic data may be a viable option for identifying climatic drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with cold injury occur at broad spatial scales, suggesting that standing variation of adaptive alleles for this and similar species does not require management at scales finer than are indicated by phenotypic data. This study demonstrates that genomic data are most useful when paired with phenotypic data, but can also fill some of the traditional roles of phenotypic data in management of species for which phenotypic trials are not feasible.

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