scholarly journals How robust are cross-population signatures of polygenic adaptation in humans?

2021 ◽  
Vol 1 ◽  
pp. 1-None
Author(s):  
Alba Refoyo-Martínez ◽  
Siyang Liu ◽  
Anja Moltke Jørgensen ◽  
Xin Jin ◽  
Anders Albrechtsen ◽  
...  
Keyword(s):  
Polygenic Adaptation

scholarly journals Polygenic adaptation in changing environments (a)

2018 ◽  
Vol 123 (4) ◽  
pp. 48002 ◽  
Author(s):  
Kavita Jain ◽  
Archana Devi
Keyword(s):  
Changing Environments ◽  
Polygenic Adaptation

scholarly journals An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
João PL Castro ◽  
Michelle N Yancoskie ◽  
Marta Marchini ◽  
Stefanie Belohlavy ◽  
Layla Hiramatsu ◽  
...  
Keyword(s):  
Bone Growth ◽  
Rapid Evolution ◽  
Genomic Analysis ◽  
Selection Response ◽  
Major Effect ◽  
Selection Experiment ◽  
Genomic Analyses ◽  
Selection Experiments ◽  
Polygenic Adaptation ◽  
History Of

Evolutionary studies are often limited by missing data that are critical to understanding the history of selection. Selection experiments, which reproduce rapid evolution under controlled conditions, are excellent tools to study how genomes evolve under selection. Here we present a genomic dissection of the Longshanks selection experiment, in which mice were selectively bred over 20 generations for longer tibiae relative to body mass, resulting in 13% longer tibiae in two replicates. We synthesized evolutionary theory, genome sequences and molecular genetics to understand the selection response and found that it involved both polygenic adaptation and discrete loci of major effect, with the strongest loci tending to be selected in parallel between replicates. We show that selection may favor de-repression of bone growth through inactivating two limb enhancers of an inhibitor, Nkx3-2. Our integrative genomic analyses thus show that it is possible to connect individual base-pair changes to the overall selection response.

Polygenic adaptation: a unifying framework to understand positive selection

2020 ◽  
Vol 21 (12) ◽  
pp. 769-781 ◽  
Author(s):  
Neda Barghi ◽  
Joachim Hermisson ◽  
Christian Schlötterer
Keyword(s):  
Positive Selection ◽  
Polygenic Adaptation

scholarly journals Genetic redundancy fuels polygenic adaptation in Drosophila

PLoS Biology ◽  
2019 ◽  
Vol 17 (2) ◽  
pp. e3000128 ◽  
Author(s):  
Neda Barghi ◽  
Raymond Tobler ◽  
Viola Nolte ◽  
Ana Marija Jakšić ◽  
François Mallard ◽  
...  
Keyword(s):  
Genetic Redundancy ◽  
Polygenic Adaptation

scholarly journals Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies

2020 ◽  
Vol 12 (6) ◽  
pp. 890-904 ◽  
Author(s):  
Neda Barghi ◽  
Christian Schlötterer
Keyword(s):  
Experimental Evolution ◽  
Selective Sweep ◽  
Time Series Data ◽  
Empirical Studies ◽  
Series Data ◽  
Stabilizing Selection ◽  
Selection Signatures ◽  
Polygenic Adaptation ◽  
Frequency Changes ◽  
Optimum Model

Abstract In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.

scholarly journals Evidence of Polygenic Adaptation in the Systems Genetics of Anthropometric Traits

PLoS ONE ◽  
2016 ◽  
Vol 11 (8) ◽  
pp. e0160654 ◽  
Author(s):  
Renato Polimanti ◽  
Bao Zhu Yang ◽  
Hongyu Zhao ◽  
Joel Gelernter
Keyword(s):  
Systems Genetics ◽  
Polygenic Adaptation

scholarly journals Whole-genome modeling accurately predicts quantitative traits, as revealed in plants

2015 ◽  
Author(s):  
Laurent Gentzbittel ◽  
Cécile Ben ◽  
Mélanie Mazurier ◽  
Min-Gyoung Shin ◽  
Martin Triska ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Symbiotic Nitrogen Fixation ◽  
Natural Populations ◽  
Whole Genome ◽  
Population Admixture ◽  
Admixture Proportion ◽  
Genome Wide ◽  
Polygenic Adaptation ◽  
In The Wild ◽  
Wild Legume

AbstractMany adaptive events in natural populations, as well as response to artificial selection, are caused by polygenic action. Under selective pressure, the adaptive traits can quickly respond via small allele frequency shifts spread across numerous loci. We hypothesize that a large proportion of current phenotypic variation between individuals may be best explained by population admixture.We thus consider the complete, genome-wide universe of genetic variability, spread across several ancestral populations originally separated. We experimentally confirmed this hypothesis by predicting the differences in quantitative disease resistance levels among accessions in the wild legume Medicago truncatula. We discovered also that variation in genome admixture proportion explains most of phenotypic variation for several quantitative functional traits, but not for symbiotic nitrogen fixation. We shown that positive selection at the species level might not explain current, rapid adaptation.These findings prove the infinitesimal model as a mechanism for adaptation of quantitative phenotypes. Our study produced the first evidence that the whole-genome modeling of DNA variants is the best approach to describe an inherited quantitative trait in a higher eukaryote organism and proved the high potential of admixture-based analyses. This insight contribute to the understanding of polygenic adaptation, and can accelerate plant and animal breeding, and biomedicine research programs.

scholarly journals Highly parallel genomic selection response in replicated Drosophila melanogaster populations with reduced genetic variation

2021 ◽  
Author(s):  
Claire Burny ◽  
Viola Nolte ◽  
Marlies Dolezal ◽  
Christian Schl&oumltterer
Keyword(s):  
Drosophila Melanogaster ◽  
Experimental Evolution ◽  
Selection Response ◽  
Adaptive Responses ◽  
Genetic Redundancy ◽  
Powerful Approach ◽  
Polygenic Adaptation ◽  
Parallel Selection ◽  
Sufficient Variation ◽  
Genomic Regions

Many adaptive traits are polygenic and frequently more loci contributing to the phenotype than needed are segregating in populations to express a phenotypic optimum. Experimental evolution provides a powerful approach to study polygenic adaptation using replicated populations adapting to a new controlled environment. Since genetic redundancy often results in non-parallel selection responses among replicates, we propose a modified Evolve and Resequencing (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29°C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Since two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.

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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