SOME PATTERNS OF MOLECULAR EVOLUTION AND VARIATION 1. Regions of the genome with unusually low rates of genetic recombination seem to have low levels of.

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SOME PATTERNS OF MOLECULAR EVOLUTION AND VARIATION 1. Regions of the genome with unusually low rates of genetic recombination seem to have low levels of within-species DNA sequence variability. 2. Species with low levels of genome-wide recombination, such as largely self-fertilizing plants and animals, also show reduced variability.

3. The level of adaptation in non-recombining genomic regions is often reduced. 4. Repetitive DNA sequences (satellite DNA, transposable elements) often accumulate in genomic regions with low rates of genetic recombination.

Diversity on the D. melanogaster X

Comparing within- population diversity of A. lyrata and total A. thaliana diversity Data of Stephen Wright and Béatrice Lauga Roughly twofold reduction in the inbreeder, but some outbreeding populations also have low diversity. This suggests importance of historical processes. k S /k T A.petraea ~ 1 A. thaliana ~ 0

Drosophila miranda Neo-Sex Chromosomes

A GENERAL FEATURE OF LOW RECOMBINATION REGIONS A lack of recombination among a set of genes in a genome or genomic region means that the evolutionary fates of mutations at different sites are not independent of each other (the Hill- Robertson effect). … unless advantageous mutations occur so seldom that each has had time to become predominant before the next appears, they can only come to be simultaneously in the same gamete by means of recombination (Fisher 1930)

Present Fitness = 1 Fitness = 0. 9 Fitness = Fitness = Absent

The effective population size (N e ) of large non- recombining portions of the genome is substantially reduced by such interference among genes subject to selection. This leads to a reduction in the level of neutral variability in DNA sequences Loci in low recombination genomic regions are more likely to accumulate deleterious mutations, and less likely to fix selectively advantageous mutations, than in regions with normal or high recombination rates.

POSSIBLE FORCES INVOLVED Hitchhiking by favourable mutations (selective sweeps) Hitchhiking by deleterious mutations (background selection) Stochastic accumulation of deleterious mutations (Muller’s ratchet) Mutual interference among weakly selected sites (weak selection Hill-Robertson effects)

MUTATION-SELECTION BALANCE Assume a very large population size, so that the loci under selection are approximately at deterministic equilibrium. Assume a mean number of new deleterious mutations per haploid genome per generation of U, and a harmonic mean selection coefficient against heterozygous mutations of t. The equilibrium mean number of deleterious mutations per haploid genome is: n = U/t

With independent effects on fitness of mutations at different loci, the frequencies of gametes carrying i deleterious mutations are Poisson-distributed with mean n = U/t. The frequency of the mutation-free class is: f 0 = exp - n e.g. with n =5, f 0 =

Hitchhiking by Favourable Mutations The spread of a favourable mutation in a non- recombining genome will drag to fixation any (sufficiently weakly selected) mutant alleles initially associated with it (a selective sweep). Successive adaptive substitutions on non- recombining chromosome can lead to the fixation of deleterious mutations at other loci, contributing to its degeneration. There is an associated loss of variability at neutral sites on the chromosome.

For deleterious mutations which are sufficiently strongly selected that they are near mutation- selection equilibrium in the absence of selective sweeps, a succession of S selective sweeps changes the expected fitness of a population by a factor of at most approximately exp - SU/h where h is the harmonic mean reduction in fitness to mutant heterozygotes compared with heterozygotes (the dominance coefficient).

Background Selection A neutral or weakly selected mutation that arises in a large non-recombining population has a non- zero chance of survival only if it arises on a chromosome free of strongly deleterious mutations. This accelerates the fixation of weakly deleterious mutations, and retards the fixation of advantageous mutations. Neutral variability is also reduced.

…it will only be the best adapted genotypes which can become the ancestors of future generations, and the beneficial mutations which occur will have only the minutest chance of not appearing in types of organisms so inferior to some of their competitors, that their offspring will certainly be supplanted by those of the latter (Fisher 1930)

The net effect of background selection is that the effective population size, N e, is reduced to f 0 N e (in the absence of recombination). This means that the equilibrium level of neutral or nearly-neutral within-population variability will be reduced accordingly. The chance of fixation of deleterious mutations can be greatly increased, and the chance of fixation of advantageous mutations reduced, due to this reduction in N e.

This effect can be very large; e.g. if f 0 = 0.007, and N e = 500,000, a deleterious mutation with a heterozygous effect on fitness of has a probability of fixation on the neo-Y of 98% of the value for a neutral mutation, whereas the probability in the absence of background selection is only 3% of the neutral value. Similarly, the rate of fixation of advantageous mutations is reduced by a factor of approximately f 0, unless their selection coefficients are larger than those of the deleterious mutations in the background (as is required for the selective sweep model to work).

Muller’s Ratchet This involves the stochastic loss from a finite population of the class of chromosomes carrying the fewest deleterious mutations. In the absence of recombination and back mutation, this class of chromosome cannot be restored. The next best class then replaces it and is in turn lost, in a process of successive irreversible steps. Each “ click” of the ratchet is quickly followed by the fixation of one mutation in the whole population, unless mutations are strongly selected and highly recessive.

Mutation Drift

SPEED OF MULLER’S RATCHET N U t Time between Clicks Mean Fitness Sims. Theory (at 5 x10 5 gens) 5 x x x

Weak Selection Hill-Robertson Effects The previous models assume that selection is sufficiently strong relative to drift that deleterious mutations are mostly held close to their equilibrium value for an infinitely large population, if recombination is frequent. If selection coefficients against deleterious mutations are of the order of 1/ N e, or less, this does not hold, and deleterious variants can drift to intermediate frequencies, even with free recombination

Testing Hypotheses Can the various models quantitatively explain the general patterns seen in the data? When two or more models produce similar predictions about patterns, can we discriminate among them?

Nucleotide Diversity in Drosophila as a Test-Case This is the problem for which it is easiest to make quantitative predictions about expected patterns i.e., how should variability in a gene relate to its position on a chromosome? In addition, the different models make somewhat different predictions about the extent of departures of the distribution of variant frequencies from those expected in the absence of Hill-Robertson effects

Testing for Departures from Neutrality Various statistical tests for departures from the distribution of nucleotide variants expected in a population at statistical equilibrium have been devised, mostly concerned with detecting an excess/deficiency of rare variants. Different types of Hill-Robertson effects, as well as other factors such as population size changes, have different effects on departures from neutral expectation.

Patterns of Codon Usage Bias The theory suggests that background selection and selective sweeps should produce a regional pattern of codon usage bias across the genome that parallels that for neutral diversity. The data on Drosophila melanogaster contradict this; codon usage (after correcting for local base composition) is reduced only in regions of the genome with very low rates of crossing over.

ACKNOWLEDGEMENTS THEORY: Deborah Charlesworth, Isabel Gordo, Gabriel Marais, Martin Morgan, Magnus Nordborg DATA: Peter Andolfatto, Doris Bachtrog, Carolina Bartlomomé, Mark Jensen, Xulio Maside, Soojin Yi MONEY: BBSRC, EMBO, NSF, Royal Society