scholarly journals Detecting adaptive differentiation in structured populations with genomic data and common gardens

2018 ◽  
Author(s):  
Emily B. Josephs ◽  
Jeremy J. Berg ◽  
Jeffrey Ross-Ibarra ◽  
Graham Coop
Keyword(s):  
Quantitative Traits ◽  
Genomic Data ◽  
Common Garden ◽  
Structured Populations ◽  
Human Populations ◽  
Trait Variation ◽  
New Methods ◽  
Common Gardens ◽  
Polygenic Adaptation ◽  
Maize Landraces

ABSTRACTAdaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci, a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the relatedness matrix to detect excess divergence consistent with polygenic adaptation and using a conditional test to control for confounding effects due to population structure. We apply these methods to inbred maize lines from the USDA germplasm pool and maize landraces from Europe. Ultimately, these methods can be applied to additional domesticated and wild species to give us a broader picture of the specific traits that contribute to adaptation and the overall importance of polygenic adaptation in shaping quantitative trait variation.

scholarly journals Detecting Adaptive Differentiation in Structured Populations with Genomic Data and Common Gardens

Genetics ◽  
2019 ◽  
Vol 211 (3) ◽  
pp. 989-1004 ◽  
Author(s):  
Emily B. Josephs ◽  
Jeremy J. Berg ◽  
Jeffrey Ross-Ibarra ◽  
Graham Coop
Keyword(s):  
Quantitative Traits ◽  
Genomic Data ◽  
Common Garden ◽  
The United States ◽  
Structured Populations ◽  
Human Populations ◽  
United States Department ◽  
Department Of Agriculture ◽  
Common Gardens ◽  
Polygenic Adaptation

Adaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci—a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the relatedness matrix to detect excess divergence consistent with polygenic adaptation, and using a conditional test to control for confounding effects due to population structure. We apply these methods to inbred maize lines from the United States Department of Agriculture germplasm pool and maize landraces from Europe. Ultimately, these methods can be applied to additional domesticated and wild species to give us a broader picture of the specific traits that contribute to adaptation and the overall importance of polygenic adaptation in shaping quantitative trait variation.

scholarly journals Combining climatic and genomic data improves range-wide tree height growth prediction in a forest tree

2020 ◽  
Author(s):  
Juliette Archambeau ◽  
Marta Benito Garzón ◽  
Frédéric Barraquand ◽  
Marina de Miguel Vega ◽  
Christophe Plomion ◽  
...  
Keyword(s):  
Demographic History ◽  
Genomic Data ◽  
Common Garden ◽  
Height Growth ◽  
Forest Trees ◽  
Trait Variation ◽  
Species Ranges ◽  
Adaptive Trait ◽  
Common Gardens ◽  
Plastic Components

AbstractPredicting adaptive-trait variation across species ranges is essential to assess the potential of populations to survive under future environmental conditions. In forest trees, multi-site common gardens have long been the gold standard for separating the genetic and plastic components of trait variation and predicting population responses to new environments. However, relying on common gardens alone limits our ability to extrapolate predictions to populations or sites not included in these logistically expensive and time-consuming experiments. In this study, we aimed to determine whether models that integrate large-scale climatic and genomic data could capture the underlying drivers of tree adaptive-trait variation, and thus improve predictions at large geographical scales. Using a clonal common garden consisting of 34 provenances of maritime pine (523 genotypes and 12,841 trees) planted in five sites under contrasted environments, we compared twelve statistical models to: (i) separate the genetic and plastic components of height growth, a key adaptive trait in forest trees, (ii) identify the relative importance of factors underlying height-growth variation across individuals and populations, and (iii) improve height-growth prediction of unknown observations and provenances. We found that the height-growth plastic component exceeded more than twice the genetic component. The plastic component was likely due to multiple environmental factors, including annual climatic variables, while the genetic component was driven by the confounded effects of past demographic history and provenance adaptation to the climate-of-origin. Distinct gene pools were characterized by different total genetic variance, with broad-sense heritability ranging from 0.104 (95% CIs: 0.065-0.146) to 0.223 (95% CIs: 0.093-0.363), suggesting different potential response to selection along the geographical distribution of maritime pine. When predicting height-growth of new observations, models combining population demographic history, provenance climate-of-origin, and positive-effect height-associated alleles (PEAs; previously identified by GWAs) explained as much variance as models relying directly on the common garden design. Noteworthy, these models explained substantially more variance when predicting height-growth in new provenances, particularly in harsh environments. Predicting quantitative traits of ecological and/or economic importance across species ranges would therefore benefit from integrating ecological and genomic information.

scholarly journals An Ancient Baboon Genome Demonstrates Long-Term Population Continuity in Southern Africa

2020 ◽  
Vol 12 (4) ◽  
pp. 407-412 ◽  
Author(s):  
Iain Mathieson ◽  
Federico Abascal ◽  
Lasse Vinner ◽  
Pontus Skoglund ◽  
Cristina Pomilla ◽  
...  
Keyword(s):  
Southern Africa ◽  
Nonhuman Primates ◽  
Demographic History ◽  
Structured Populations ◽  
Human Populations ◽  
Papio Ursinus ◽  
Anthropological Research ◽  
Population Continuity ◽  
High Degree

Abstract Baboons are one of the most abundant large nonhuman primates and are widely studied in biomedical, behavioral, and anthropological research. Despite this, our knowledge of their evolutionary and demographic history remains incomplete. Here, we report a 0.9-fold coverage genome sequence from a 5800-year-old baboon from the site of Ha Makotoko in Lesotho. The ancient baboon is closely related to present-day Papio ursinus individuals from southern Africa—indicating a high degree of continuity in the southern African baboon population. This level of population continuity is rare in recent human populations but may provide a good model for the evolution of Homo and other large primates over similar timespans in structured populations throughout Africa.

scholarly journals The effect of life-history and mode of inheritance on neutral genetic variability

2001 ◽  
Vol 77 (2) ◽  
pp. 153-166 ◽  
Author(s):  
BRIAN CHARLESWORTH
Keyword(s):  
Sequence Variation ◽  
Adult Mortality ◽  
Structured Populations ◽  
Human Populations ◽  
Effective Population ◽  
Transmission Modes ◽  
Population Sizes ◽  
Age Structured ◽  
Infinite Sites Model ◽  
Site Diversity

Formulae for the effective population sizes of autosomal, X-linked, Y-linked and maternally transmitted loci in age-structured populations are developed. The approximations used here predict both asymptotic rates of increase in probabilities of identity, and equilibrium levels of neutral nucleotide site diversity under the infinite-sites model. The applications of the results to the interpretation of data on DNA sequence variation in Drosophila, plant, and human populations are discussed. It is concluded that sex differences in demographic parameters such as adult mortality rates generally have small effects on the relative effective population sizes of loci with different modes of inheritance, whereas differences between the sexes in variance in reproductive success can have major effects, either increasing or reducing the effective population size for X-linked loci relative to autosomal or Y-linked loci. These effects need to be accounted for when trying to understand data on patterns of sequence variation for genes with different transmission modes.

scholarly journals Evolutionary inference from QST-FST comparisons: disentangling local adaptation from altitudinal gradient selection in snapdragon plants

2018 ◽  
Author(s):  
Sara Marin ◽  
Juliette Archambeau ◽  
Vincent Bonhomme ◽  
Mylène Lascoste ◽  
Benoit Pujol
Keyword(s):  
Local Adaptation ◽  
Natural Populations ◽  
Common Garden ◽  
Global Scale ◽  
Structured Populations ◽  
Adaptive Divergence ◽  
Adaptation To Climate Change ◽  
Phenotypic Differentiation ◽  
Multiple Populations ◽  
Environmental Demand

ABSTRACTPhenotypic differentiation among natural populations can be explained by natural selection or by neutral processes such as drift. There are many examples in the literature where comparing the effects of these processes on multiple populations has allowed the detection of local adaptation. However, these studies rarely identify the agents of selection. Whether population adaptive divergence is caused by local features of the environment, or by the environmental demand emerging at a more global scale, for example along altitudinal gradients, is a question that remains poorly investigated. Here, we measured neutral genetic (FST) and quantitative genetic (QST) differentiation among 13 populations of snapdragon plants (Antirrhinum majus) in a common garden experiment. We found low but significant genetic differentiation at putatively neutral markers, which supports the hypothesis of either ongoing pervasive homogenisation via gene flow between diverged populations or reproductive isolation between disconnected populations. Our results also support the hypothesis of local adaptation involving phenological, morphological, reproductive and functional traits. They also showed that phenotypic differentiation increased with altitude for traits reflecting the reproduction and the phenology of plants, thereby confirming the role of such traits in their adaptation to environmental differences associated with altitude. Our approach allowed us to identify candidate traits for the adaptation to climate change in snapdragon plants. Our findings imply that environmental conditions changing with altitude, such as the climatic envelope, influenced the adaptation of multiple populations of snapdragon plants on the top of their adaptation to local environmental features. They also have implications for the study of adaptive evolution in structured populations because they highlight the need to disentangle the adaptation of plant populations to climate envelopes and altitude from the confounding effects of selective pressures acting specifically at the local scale of a population.

scholarly journals Putting RFMix and ADMIXTURE to the test in a complex admixed population

2020 ◽  
Author(s):  
Caitlin Uren ◽  
Eileen G. Hoal ◽  
Marlo Möller
Keyword(s):  
World Wide ◽  
Association Studies ◽  
Structured Populations ◽  
Human Populations ◽  
Computational Tools ◽  
Association Analyses ◽  
Local Ancestry ◽  
Diverse World ◽  
Admixed Population ◽  
Global And Local

Abstract Background Global and local ancestry inference in admixed human populations can be performed using computational tools implementing distinct algorithms. The development and resulting accuracy of these tools has been tested largely on populations with relatively straightforward admixture histories but little is known about how well they perform in more complex admixture scenarios. Results Using simulations, we show that RFMix outperforms ADMIXTURE in determining global ancestry proportions even in a complex 5-way admixed population, in addition to assigning local ancestry with an accuracy of 89%. The ability of RFMix to determine global and local ancestry to a high degree of accuracy, particularly in admixed populations provides the opportunity for more accurate association analyses. Conclusion This study highlights the utility of the extension of computational tools to become more compatible to genetically structured populations, as well as the need to expand the sampling of diverse world-wide populations. This is particularly noteworthy as modern-day societies are becoming increasingly genetically complex and some genetic tools and commonly used ancestral populations are less appropriate. Based on these caveats and the results presented here, we suggest that RFMix be used for both global and local ancestry estimation in world-wide complex admixture scenarios particularly when including these estimates in association studies.

scholarly journals Genetic specificity of a plant–insect food web: Implications for linking genetic variation to network complexity

2016 ◽  
Vol 113 (8) ◽  
pp. 2128-2133 ◽  
Author(s):  
Matthew A. Barbour ◽  
Miguel A. Fortuna ◽  
Jordi Bascompte ◽  
Joshua R. Nicholson ◽  
Riitta Julkunen-Tiitto ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Food Web ◽  
Host Plant ◽  
Trophic Interactions ◽  
Common Garden ◽  
Ecological Networks ◽  
Experimental Population ◽  
Trait Variation ◽  
Intraspecific Genetic Variation ◽  
Food Web Complexity

Theory predicts that intraspecific genetic variation can increase the complexity of an ecological network. To date, however, we are lacking empirical knowledge of the extent to which genetic variation determines the assembly of ecological networks, as well as how the gain or loss of genetic variation will affect network structure. To address this knowledge gap, we used a common garden experiment to quantify the extent to which heritable trait variation in a host plant determines the assembly of its associated insect food web (network of trophic interactions). We then used a resampling procedure to simulate the additive effects of genetic variation on overall food-web complexity. We found that trait variation among host-plant genotypes was associated with resistance to insect herbivores, which indirectly affected interactions between herbivores and their insect parasitoids. Direct and indirect genetic effects resulted in distinct compositions of trophic interactions associated with each host-plant genotype. Moreover, our simulations suggest that food-web complexity would increase by 20% over the range of genetic variation in the experimental population of host plants. Taken together, our results indicate that intraspecific genetic variation can play a key role in structuring ecological networks, which may in turn affect network persistence.

scholarly journals New methods for detection of low levels of DNA damage in human populations.

1983 ◽  
Vol 48 ◽  
pp. 29-41 ◽  
Author(s):  
W A Haseltine ◽  
W Franklin ◽  
J A Lippke
Keyword(s):  
Dna Damage ◽  
Human Populations ◽  
New Methods ◽  
Low Levels

scholarly journals Anthropogenic disturbance drives dispersal syndromes, demography, and gene flow in spatially structured amphibian populations

2019 ◽  
Author(s):  
Hugo Cayuela ◽  
Aurélien Besnard ◽  
Julien Cote ◽  
Martin Laporte ◽  
Eric Bonnaire ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Gene Flow ◽  
Common Garden ◽  
Structured Populations ◽  
Habitat Patch ◽  
Dispersal Syndromes ◽  
Spatially Structured Populations ◽  
Capture Recapture ◽  
Common Garden Experiments ◽  
Dispersal Evolution

AbstractThere is growing evidence that anthropogenic landscapes can strongly influence the evolution of dispersal, particularly through fragmentation, and may drive organisms into an evolutionary trap by suppressing dispersal. However, the influence on dispersal evolution of anthropogenic variation in habitat patch turnover has so far been largely overlooked. In this study, we examined how human-driven variation in patch persistence affects dispersal rates and distances, determines dispersal-related phenotypic specialization, and drives neutral genetic structure in spatially structured populations. We addressed this issue in an amphibian, Bombina variegata, using an integrative approach combining capture–recapture modeling, demographic simulation, common garden experiments, and population genetics. B. variegata reproduces in small ponds that occur either in habitat patches that are persistent (i.e. several decades or more), located in riverine environments with negligible human activity, or in patches that are highly temporary (i.e. a few years), created by logging operations in intensively harvested woodland. Our capture–recapture models revealed that natal and breeding dispersal rates and distances were drastically higher in spatially structured populations (SSPs) in logging environments than in riverine SSPs. Population simulations additionally showed that dispersal costs and benefits drive the fate of logging SSPs, which cannot persist without dispersal. The common garden experiments revealed that toadlets reared in laboratory conditions have morphological and behavioral specialization that depends on their habitat of origin. Toadlets from logging SSPs were found to have higher boldness and exploration propensity than those from riverine SSPs, indicating transgenerationally transmitted dispersal syndromes. We also found contrasting patterns of neutral genetic diversity and gene flow in riverine and logging SSPs, with genetic diversity and effective population size considerably higher in logging than in riverine SSPs. In parallel, intra-patch inbreeding and relatedness levels were lower in logging SSPs. Controlling for the effect of genetic drift and landscape connectivity, gene flow was found to be higher in logging than in riverine SSPs. Taken together, these results indicate that anthropogenic variation in habitat patch turnover may have an effect at least as important as landscape fragmentation on dispersal evolution and the long-term viability and genetic structure of wild populations.

scholarly journals Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies

2018 ◽  
Author(s):  
Mashaal Sohail ◽  
Robert M. Maier ◽  
Andrea Ganna ◽  
Alex Bloemendal ◽  
Alicia R. Martin ◽  
...  
Keyword(s):  
Population Structure ◽  
Association Studies ◽  
Meta Analysis ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Multiple Traits ◽  
Large Numbers ◽  
Genome Wide ◽  
Polygenic Adaptation ◽  
The Uk

AbstractGenetic predictions of height differ among human populations and these differences are too large to be explained by genetic drift. This observation has been interpreted as evidence of polygenic adaptation. Differences across populations were detected using SNPs genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of subsignificant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection and claims of polygenic adaptation for multiple traits. Polygenic adaptation studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure.

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