scholarly journals Global adaptation complicates the interpretation of genome scans for local adaptation

2020 ◽  
Author(s):  
Tom R. Booker ◽  
Sam Yeaman ◽  
Michael C. Whitlock
Keyword(s):  
Local Adaptation ◽  
Genome Scans

scholarly journals SNP-level FST outperforms window statistics for detecting soft sweeps in local adaptation

2022 ◽  
Author(s):  
Tiago da Silva Ribeiro ◽  
José A Galván ◽  
John E Pool
Keyword(s):  
Genetic Differentiation ◽  
Local Adaptation ◽  
Genetic Variant ◽  
Real Data ◽  
Selective Sweeps ◽  
Functional Categories ◽  
Genome Scans ◽  
Genome Wide ◽  
A Genome ◽  
Local Selection

Local adaptation can lead to elevated genetic differentiation at the targeted genetic variant and nearby sites. Selective sweeps come in different forms, and depending on the initial and final frequencies of a favored variant, very different patterns of genetic variation may be produced. If local selection favors an existing variant that had already recombined onto multiple genetic backgrounds, then the width of elevated genetic differentiation (high FST) may be too narrow to detect using a typical windowed genome scan, even if the targeted variant becomes highly differentiated. We therefore used a simulation approach to investigate the power of SNP-level FST (specifically, the maximum SNP FST value within a window) to detect diverse scenarios of local adaptation, and compared it against whole-window FST and the Comparative Haplotype Identity statistic. We found that SNP FST had superior power to detect complete or mostly complete soft sweeps, but lesser power than window-wide statistics to detect partial hard sweeps. To investigate the relative enrichment and nature of SNP FST outliers from real data, we applied the two FST statistics to a panel of Drosophila melanogaster populations. We found that SNP FST had a genome-wide enrichment of outliers compared to demographic expectations, and though it yielded a lesser enrichment than window FST, it detected mostly unique outlier genes and functional categories. Our results suggest that SNP FST is highly complementary to typical window-based approaches for detecting local adaptation, and merits inclusion in future genome scans and methodologies.

scholarly journals Genome Scans for Detecting Footprints of Local Adaptation Using a Bayesian Factor Model

2014 ◽  
Vol 31 (9) ◽  
pp. 2483-2495 ◽  
Author(s):  
Nicolas Duforet-Frebourg ◽  
Eric Bazin ◽  
Michael G.B. Blum
Keyword(s):  
Local Adaptation ◽  
Factor Model ◽  
Genome Scans ◽  
Bayesian Factor

The relative power of genome scans to detect local adaptation depends on sampling design and statistical method

2015 ◽  
Vol 24 (5) ◽  
pp. 1031-1046 ◽  
Author(s):  
Katie E. Lotterhos ◽  
Michael C. Whitlock
Keyword(s):  
Statistical Method ◽  
Local Adaptation ◽  
Sampling Design ◽  
Relative Power ◽  
Genome Scans

Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis)

2011 ◽  
Vol 20 (7) ◽  
pp. 1450-1462 ◽  
Author(s):  
MARTIN C. FISCHER ◽  
MATTHIEU FOLL ◽  
LAURENT EXCOFFIER ◽  
GERALD HECKEL
Keyword(s):  
High Altitude ◽  
Local Adaptation ◽  
Small Rodent ◽  
Microtus Arvalis ◽  
Genome Scans

scholarly journals The coupling hypothesis: why genome scans may fail to map local adaptation genes

2011 ◽  
Vol 20 (10) ◽  
pp. 2044-2072 ◽  
Author(s):  
NICOLAS BIERNE ◽  
JOHN WELCH ◽  
ETIENNE LOIRE ◽  
FRANÇOIS BONHOMME ◽  
PATRICE DAVID
Keyword(s):  
Local Adaptation ◽  
Genome Scans

scholarly journals Background selection and the statistics of population differentiation: consequences for detecting local adaptation

2018 ◽  
Author(s):  
Remi Matthey-Doret ◽  
Michael C. Whitlock
Keyword(s):  
Local Adaptation ◽  
Dna Sequences ◽  
Population Differentiation ◽  
False Positive Rate ◽  
Parameter Estimates ◽  
Background Selection ◽  
Deleterious Mutations ◽  
Effective Population ◽  
Genome Scans ◽  
Positive Rate

AbstractBackground selection is a process whereby recurrent deleterious mutations cause a decrease in the effective population size and genetic diversity at linked loci. Several authors have suggested that variation in the intensity of background selection could cause variation in FST across the genome, which could confound signals of local adaptation in genome scans. We performed realistic simulations of DNA sequences, using parameter estimates from humans and sticklebacks, to investigate how variation in the intensity of background selection affects different statistics of population differentiation. We show that, in populations connected by gene flow, Weir & Cockerham’s (1984) estimator of FST is largely insensitive to locus-to-locus variation in the intensity of background selection. Unlike FST, however, dXY is negatively correlated with background selection. We also show that background selection does not greatly affect the false positive rate in FST outlier studies. Overall, our study indicates that background selection will not greatly interfere with finding the variants responsible for local adaptation.

scholarly journals Performing Highly Efficient Genome Scans for Local Adaptation with R Package pcadapt Version 4

2020 ◽  
Vol 37 (7) ◽  
pp. 2153-2154 ◽  
Author(s):  
Florian Privé ◽  
Keurcien Luu ◽  
Bjarni J Vilhjálmsson ◽  
Michael G B Blum
Keyword(s):  
Local Adaptation ◽  
Principal Components ◽  
Computational Efficiency ◽  
Computation Time ◽  
R Package ◽  
Large Reduction ◽  
Genome Scans ◽  
Highly Efficient ◽  
User Friendly

Abstract R package pcadapt is a user-friendly R package for performing genome scans for local adaptation. Here, we present version 4 of pcadapt which substantially improves computational efficiency while providing similar results. This improvement is made possible by using a different format for storing genotypes and a different algorithm for computing principal components of the genotype matrix, which is the most computationally demanding step in method pcadapt. These changes are seamlessly integrated into the existing pcadapt package, and users will experience a large reduction in computation time (by a factor of 20–60 in our analyses) as compared with previous versions.

scholarly journals Unpacking conditional neutrality: genomic signatures of selection on conditionally beneficial and conditionally deleterious mutations

2019 ◽  
Author(s):  
Jonathan A. Mee ◽  
Samuel Yeaman
Keyword(s):  
Allele Frequency ◽  
Local Adaptation ◽  
Home Environment ◽  
Cumulative Effect ◽  
Antagonistic Pleiotropy ◽  
Deleterious Mutations ◽  
Genome Scans ◽  
Beneficial Mutations ◽  
Local Environments ◽  
Non Local

AbstractIt is common to look for signatures of local adaptation in genomes by identifying loci with extreme levels of allele frequency divergence among populations. This approach to finding genes associated with local adaptation often assumes antagonistic pleiotropy, wherein alternative alleles are strongly favoured in alternative environments. Conditional neutrality has been proposed as an alternative to antagonistic pleiotropy, but conditionally neutral polymorphisms are transient and it is unclear how much outlier signal would be maintained under different forms of conditional neutrality. Here, we use individual-based simulations and a simple analytical heuristic to show that a pattern that mimics local adaptation at the phenotypic level, where each genotype has the highest fitness in its home environment, can be produced by the accumulation of mutations that are neutral in their home environment and deleterious in non-local environments. Because conditionally deleterious mutations likely arise at a rate many times higher than conditionally beneficial mutations, they can have a significant cumulative effect on fitness even when individual effect sizes are small. We show that conditionally deleterious mutations driving non-local maladaptation may be undetectable by even the most powerful genome scans, as differences in allele frequency between populations are typically small. We also explore the evolutionary effects of conditionally-beneficial mutations and find that they can maintain significant signals of local adaptation, and they would be more readily detectable than conditionally deleterious mutations using conventional genome scan approaches. We discuss implications for interpreting outcomes of transplant experiments and genome scans that are used to study the genetic basis of local adaptation.

Geographic biotype and host-associated local adaptation in a polyphagous species, Lambdina fiscellaria (Lepidoptera: Geometridae) feeding on balsam fir on Anticosti Island, Canada

2006 ◽  
Vol 96 (6) ◽  
pp. 619-627 ◽  
Author(s):  
C. Hébert ◽  
R. Berthiaume ◽  
É. Bauce ◽  
J. Brodeur
Keyword(s):  
Local Adaptation ◽  
Balsam Fir ◽  
Anticosti Island

Genome scans find clues to childhood cancer

2008 ◽  
Author(s):  
Edward R. Winstead
Keyword(s):  
Childhood Cancer ◽  
Genome Scans
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