| Literature DB >> 28495267 |
Matthew Hartfield1, Thomas Bataillon2, Sylvain Glémin3.
Abstract
Genome-wide surveys of nucleotide polymorphisms, obtained from next-generation sequencing, have uncovered numerous examples of adaptation in self-fertilizing organisms, especially regarding changes to climate, geography, and reproductive systems. Yet existing models for inferring attributes of adaptive mutations often assume idealized outcrossing populations, which risks mischaracterizing properties of these variants. Recent theoretical work is emphasizing how various aspects of self-fertilization affects adaptation, yet empirical data on these properties are lacking. We review theoretical and empirical studies demonstrating how self-fertilization alters the process of adaptation, illustrated using examples from current sequencing projects. We propose ideas for how future research can more accurately quantify aspects of adaptation in self-fertilizers, including incorporating the effects of standing variation, demographic history, and polygenic adaptation.Entities:
Keywords: adaptation; demography; dominance; genomics; invasions; self-fertilization
Mesh:
Year: 2017 PMID: 28495267 PMCID: PMC5450926 DOI: 10.1016/j.tig.2017.04.002
Source DB: PubMed Journal: Trends Genet ISSN: 0168-9525 Impact factor: 11.639
Figure 1Self-Fertilization, Dominance, and Signatures of Adaptive Mutation. (A) Different allele trajectories over time. Curves are obtained by numerically evaluating Equation (II) in Box 1, with initial frequency p0 = 1/2N (with N = 50 000). The beneficial allele has selective advantage s = 0.05; dominance (h) and self-fertilization (σ) parameters are as shown in the legend. (B) Pairwise diversity (π) relative to neutral expectations (π0) will be reduced close to the sweep, and recover further from the sweep. This sweep signature is weakened if the beneficial variant is recessive (h = 0.1, dashed lines), but is strengthened with increased self-fertilization due to reduced recombination and quicker fixation times (Boxes 1 and 2). (C) Expected site frequency spectra following a selective sweep, based on 10 genetic samples. A sweep is characterised by many variants at low and high frequencies (1 and 9 respectively, in this example), with more pronounced signatures with higher rates of self-fertilization. Values used in (B) and (C) were obtained using Equations 7 and 15 respectively from [73], modified to account for self-fertilizing trajectories
Overview of Methods for Detecting Selection Footprints in Data from Genome-wide Re-sequencing Studies
| Type of method | Summary of method | Data needed | How does selfing affect the method? | Refs |
|---|---|---|---|---|
| McDonald–Kreitman (MK) test | Detects abnormally high nonsynonymous over synonymous divergence ratio, relative to nonsynonymous over synonymous polymorphism ratio | SNP data, unlinked, and divergence to an outgroup (e.g., a related sister-species) | Linked selection could be more prevalent with selfing, which can alter estimates of the distribution of fitness effects of deleterious mutations. This distribution usually has to be accurately calculated to correctly infer the proportion of adaptive substitutions. | |
| SFS in sweep regions consists of elevated low- and high-frequency variants compared to neutral case | SNPs data, unlinked, unphased | Selfing will affect expectation for SFS under soft and hard sweeps ( | ||
| Neutrality tests based on SFS (Tajima’s D, Fay and Wu’s H, etc.) | These tests measure the excess or deficit of rare alleles in the SFS compared to neutral expectations | SNPs data, unlinked, unphased | Should work; selfing | |
| Linkage disequilibrium (LD) | Increase in linkage disequilibrium at loci flanking a sweep | SNPs data, linked and phased | A decrease in effective recombination rate might further amplify the effect of selective sweeps and expand the width of high LD regions. | |
| Fst-based tests | Tracks local adaptation between two geographic regions by finding highly differentiated loci, as measured using the Fst statistic | SNP frequencies from two or more populations | Fst scans for excess differentiation will be robust to selfing when using a background genomic distribution as a null neutral distribution. Fst scans relying on a model-based approach to derive a neutral distribution might be sensitive to misspecification of population structure. Selfing species often have complex population structures that are hard to model accurately. | |
| Haplotype tests | Average number of haplotypes around sweep is reduced; mean haplotype length is increased | SNPs data, linked and phased | Haplotype tests relying on detecting abnormal haplotype length surrounding a focal SNP should be robust to any levels of selfing. | |
| Singleton density score | The physical distance between | SNPs data, linked but unphased | Currently unclear. Since a sweep still reduces average number of singletons with self-fertilization, this test should work. |
Figure ISchematics of Effect of Demographic History on Genealogies. (A) Genealogies for a selective sweep in a fixed-size population. The effective recombination rate r depends on the level of self-fertilization (Box 1). The point when the top lineage was affected by recombination is marked ‘×’. (B) Genealogies where the population experienced a bottleneck in the recent past
Figure 2Response to Selection on a Polygenic Trait under Outcrossing and Selfing. Evolution of additive genetic variance is shown for a quantitative trait under directional selection with outcrossing or selfing. We assume both scenarios start from the same initial outcrossing population. Under outcrossing, genetic variance is mostly conserved and the trait mean changes linearly through time, at least on short time scales if selection is not too strong. Under selfing, genetic variance initially increases much more rapidly than in the outcrossing population. Here, more extreme phenotypes (i.e., those with very high or low values) are generated due to creating homozygotes at multiple loci, speeding up the response to selection. Genetic variance can then be quickly eroded because only a few haplotypes are retained after selection, and new combinations cannot be readily created because of a lack of effective recombination. The trait mean can therefore rapidly plateau