The Population Genetics of Adaptation: The Distribution of Factors Fixed During Adaptive Evolution

Orr, H. Allen

doi:10.1111/j.1558-5646.1998.tb01823.x

Cited by 729 publications

(869 citation statements)

References 23 publications

(12 reference statements)

Supporting

Mentioning

797

Contrasting

Order By: Relevance

“…This sometimes led to an increase in the variance in breakdown score (Fig. S3f), but otherwise, the Brownian bridge approximation remained accurate.Figure S4 shows further simulations, where the optima can move in discrete jumps (as in Orr 1998; Barton 2001). For

n = 2

traits, we compare divergence with a stable, fixed optimum (Fig.…”

Section: Results With Haploid Geneticsmentioning

confidence: 99%

Coadapted genomes and selection on hybrids: Fisher's geometric model explains a variety of empirical patterns

2018

View full text Add to dashboard Cite

Natural selection plays a variety of roles in hybridization, speciation, and admixture. Most research has focused on two extreme cases: crosses between closely related inbred lines, where hybrids are fitter than their parents, or crosses between effectively isolated species, where hybrids suffer severe breakdown. But many natural populations must fall into intermediate regimes, with multiple types of gene interaction, and these are more difficult to study. Here, we develop a simple fitness landscape model, and show that it naturally interpolates between previous modeling approaches, which were designed for the extreme cases, and invoke either mildly deleterious recessives, or discrete hybrid incompatibilities. Our model yields several new predictions, which we test with genomic data from Mytilus mussels, and published data from plants (Zea, Populus, and Senecio) and animals (Mus, Teleogryllus, and Drosophila). The predictions are generally supported, and the model explains a number of surprising empirical patterns. Our approach enables novel and complementary uses of genome‐wide datasets, which do not depend on identifying outlier loci, or “speciation genes” with anomalous effects. Given its simplicity and flexibility, and its predictive successes with a wide range of data, the approach should be readily extendable to other outstanding questions in the study of hybridization.

show abstract

n = 2

traits, we compare divergence with a stable, fixed optimum (Fig.…”

Section: Results With Haploid Geneticsmentioning

confidence: 99%

Coadapted genomes and selection on hybrids: Fisher's geometric model explains a variety of empirical patterns

2018

View full text Add to dashboard Cite

show abstract

“…Nevertheless, understanding how evolutionary processes cause heterogeneous genomic divergence remains challenging (e.g., Slatkin & Wiehe 1998; Barton 2000; Hermisson & Pennings 2005; Excoffier & Ray 2008; Bierne 2010; Feder & Nosil 2010; Bierne et al 2011; Roesti et al 2012a, 2013; reviewed in Wu 2001; Nosil et al 2009). Traditional population genetic theory has primarily focused on a scenario in which a new genetic variant arises by mutation in a population colonizing a new environment (hereafter called a ‘derived’ population) where the variant is beneficial (Orr 1998; Barrett & Schluter 2008; Messer & Petrov 2013). The new genetic variant is then expected to fix in the derived population, whereas the initial genetic variant remains favored and is thus retained in the ‘source’ population inhabiting the ancestral environment.…”

Section: Introductionmentioning

confidence: 99%

The genomic signature of parallel adaptation from shared genetic variation

et al. 2014

View full text Add to dashboard Cite

Parallel adaptation is common and may often occur from shared genetic variation, but the genomic consequences of this process remain poorly understood. We first use individual-based simulations to demonstrate that comparisons among populations adapted in parallel from shared variation reveal a characteristic genomic signature around a selected locus: a low divergence valley centered at the locus and flanked by twin peaks of high divergence. This signature is initiated by the hitchhiking of haplotype tracts differing among derived populations in the broader neighborhood of the selected locus (driving the high divergence twin peaks) and shared haplotype tracts in the tight neighborhood of the locus (driving the low divergence valley). This initial hitchhiking signature is reinforced over time because the selected locus acts as a barrier to gene flow from the source to the derived populations, thus promoting divergence by drift in its close neighborhood. We next empirically confirm the peak-valley-peak signature by combining targeted and RAD sequence data at three candidate adaptation genes in multiple marine (source) and freshwater (derived) populations of threespine stickleback. Finally, we use a genome-wide screen for the peak-valley-peak signature to discover additional genome regions involved in parallel marine-freshwater divergence. Our findings offer a new explanation for heterogeneous genomic divergence and thus challenge the standard view that peaks in population divergence harbor divergently selected loci, and that low-divergence regions result from balancing selection or localized introgression. We anticipate that genome scans for peak-valley-peak divergence signatures will promote the discovery of adaptation genes in other organisms.

show abstract

“…The mutation rate and the distribution of fitness effects of mutation figure prominently in evolutionary theory in such varied subjects as adaptation (e.g., Fisher, 1930; Orr, 1998), the evolution of sex (e.g., Kondrashov, 1988; Muller, 1964), and expectations about standing genetic variation (Barrett & Schluter, 2008; Haldane, 1937). The effects of mutation may also depend on environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

Quantifying natural seasonal variation in mutation parameters with mutation accumulation lines

Rutter

Roles

Fenster

2018

Ecology and Evolution

View full text Add to dashboard Cite

Mutations create novel genetic variants, but their contribution to variation in fitness and other phenotypes may depend on environmental conditions. Furthermore, natural environments may be highly heterogeneous. We assessed phenotypes associated with survival and reproductive success in over 30,000 plants representing 100 mutation accumulation lines of Arabidopsis thaliana across four temporal environments at a single field site. In each of the four assays, environmental variance was substantially larger than mutational variance. For some traits, whether mutational variance was significantly varied between seasons. The founder genotype had mean trait values near the mean of the distribution of the mutation accumulation lines in all field experiments. New mutations also contributed more phenotypic variation than would be predicted, given phenotypic and sequence‐level divergence among natural populations of A. thaliana. The combination of large environmental variance with a mean effect of mutation near zero suggests that mutations could contribute substantially to standing genetic variation.

show abstract

The Population Genetics of Adaptation: The Distribution of Factors Fixed During Adaptive Evolution

Cited by 729 publications

References 23 publications

Coadapted genomes and selection on hybrids: Fisher's geometric model explains a variety of empirical patterns

Coadapted genomes and selection on hybrids: Fisher's geometric model explains a variety of empirical patterns

The genomic signature of parallel adaptation from shared genetic variation

Quantifying natural seasonal variation in mutation parameters with mutation accumulation lines

Contact Info

Product

Resources

About