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Regions of Lower Crossing Over Harbor More Rare Variants in African Populations of Drosophila Melanogaster

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Regions of Lower Crossing Over Harbor More Rare Variants in African Populations of Drosophila Melanogaster Copyright 2001 by the Genetics Society of America Regions of Lower Crossing Over Harbor More Rare Variants in African Populations of Drosophila melanogaster Peter Andolfatto* and Molly Przeworski² *Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh, EH9 3JT, United Kingdom and ²Department of Statistics, Oxford University, Oxford, OX1 3TG, United Kingdom Manuscript received November 7, 2000 Accepted for publication February 3, 2001 ABSTRACT A correlation between diversity levels and rates of recombination is predicted both by models of positive selection, such as hitchhiking associated with the rapid ®xation of advantageous mutations, and by models of purifying selection against strongly deleterious mutations (commonly referred to as ªbackground selec- tionº). With parameter values appropriate for Drosophila populations, only the ®rst class of models predicts a marked skew in the frequency spectrum of linked neutral variants, relative to a neutral model. Here, we consider 29 loci scattered throughout the Drosophila melanogaster genome. We show that, in African populations, a summary of the frequency spectrum of polymorphic mutations is positively correlated with the meiotic rate of crossing over. This pattern is demonstrated to be unlikely under a model of background selection. Models of weakly deleterious selection are not expected to produce both the observed correlation and the extent to which nucleotide diversity is reduced in regions of low (but nonzero) recombination. Thus, of existing models, hitchhiking due to the recurrent ®xation of advantageous variants is the most plausible explanation for the data. T has been known for a decade that levels of nucleo- pie 2000). This occurs because the physical length of the I tide diversity in Drosophila melanogaster, but not levels hitchhiking region depends on the strength of selection of divergence with its sibling species, are correlated with relative to the recombination rate (Kaplan et al. 1989). crossing over rates, a pattern inconsistent with a strictly If selection coef®cients are similar across the genome, neutral model of molecular evolution (Aguade et al. loci in regions of low recombination will be affected by 1989; Berry et al. 1991; Begun and Aquadro 1992; more selective sweeps per unit time, and hence are more Aquadro et al. 1994). A similar pattern has emerged in likely to be sampled shortly after a sweep. In the recovery a variety of organisms (Stephan 1994; Nachman 1997; phase, most polymorphisms will be young (i.e., post- Nachman et al. 1998; Stephan and Langley 1998; sweep) and at low frequency. Przeworski et al. 2000). Explanations for the correla- An alternative to positive selection models is purifying tion include positive selection (Maynard Smith and selection against strongly deleterious mutations, hereafter Haigh 1974; Kaplan et al. 1989; Gillespie 1997, 2000) referred to as ªbackground selectionº (Charlesworth as well as selection against strongly deleterious muta- et al. 1993, 1995; Hudson and Kaplan 1994, 1995). In tions (Charlesworth et al. 1993, 1995; Hudson and this model, a neutral allele will persist in the population Kaplan 1995). These explanations assume that the sam- only if it ®nds itself on a deleterious mutation-free chro- pled variation is neutral and re¯ects the action of selec- mosome (or segment of chromosome), either when it tion at linked sites. ®rst arises in the population or by recombination. If Particular theoretical attention has been paid to a selection coef®cients and deleterious mutation rates are model of recurrent but nonoverlapping episodes of pos- the same in different regions, the rate of recombination itive selection, in which neutral variants linked to a will determine the extent of the reduction in neutral strongly favored mutation are swept to ®xation in the diversity (i.e., the extent to which neutral alleles can population. This so-called ªhitchhikingº model predicts escape from background selection). that loci in regions of low recombination will harbor While purifying selection undoubtedly occurs, uncer- lower levels of variation and more low frequency poly- tainty about key parameters, such as the distribution of morphisms than loci in regions of normal recombina- selection coef®cients and the deleterious mutation rate, tion (Kaplan et al. 1989; Braverman et al. 1995; Gilles- renders unclear its importance in reducing levels of variability. Similar uncertainty exists for positive selec- tion models. As a result, considerable debate has revolved about the relative importance of background selection Corresponding author: Peter Andolfatto, Institute for Cell and Animal and hitchhiking in shaping patterns of variability. Population Biology, Ashworth Labs, Kings Bldgs., University of Edin- burgh, Edinburgh, EH9 3JT, United Kingdom. While positive selection models predict an excess of E-mail: [email protected] rare alleles at linked neutral sites relative to a model of Genetics 158: 657±665 ( June 2001) 658 P. Andolfatto and M. Przeworski no selection (Braverman et al. 1995; Gillespie 2000), sequence (except zeste, which is 3Ј untranslated DNA) and the background selection model does not, so long as were sampled from the same 13 individuals. PCR products were sequenced directly on both strands using a Big-Dye se- the population is large and the deleterious mutation quencing kit and run on an ABI377XL automated sequencer rate not extremely high (Hudson and Kaplan 1994; (Perkin-Elmer-Applied Biosystems, Norwalk, CT). Sequence Charlesworth et al. 1995). In D. melanogaster, these contigs were managed with Sequencher 3.0 software (Gene two conditions are likely to be met (Li et al. 1999; Codes, Ann Arbor, MI) and aligned manually. Aligned se- McVean and Vieira 2001). Thus, polymorphism data quences were deposited into GenBank under accession nos. AF345663±AF345791. from D. melanogaster provide a means to distinguish be- From published data, we include the 19 loci available for tween models. Two previous surveys of loci in D. melano- African populations with sample sizes greater than three. For gaster did not detect a skew toward rare variants in re- the majority of these loci (12), population samples were drawn gions with low rates of crossing over (Begun and from a Zimbabwe population (as above) with the exceptions Aquadro 1993; Charlesworth et al. 1995). These ob- of Fbp2, Su(H), and Vha68, where samples are from an Ivory Coast population; Acp29AB, from a Malawi population; and servations suggested that background selection might Dras1, Dras2, and R, from a number of African populations. be a suf®cient explanation for the correlation between CecC was chosen as a representative from a cluster of closely diversity levels and recombination rates, i.e., that there related genes (cf. Clark and Wang 1997). exists no unequivocal evidence for positive selection. For each locus, we include all polymorphisms at synonymous The effects of background selection and hitchhiking sites and in noncoding DNA (including both insertion- deletions and single nucleotide polymorphisms). Single nu- on the frequency spectrum of linked neutral sites are cleotide polymorphisms within deletions and overlapping known for a random-mating population of constant size. deletions were excluded from analyses. Excluding insertion- Demographic departures from these model assump- deletion variation has no effect on the conclusions (results tions can alter the signature of selection (e.g., see Nord- not shown). In situations where a nucleotide polymorphism borg 1997; Slatkin and Wiehe 1998; Hamblin and Di occurs immediately adjacent to a deletion, and the two are in complete coupling, the two polymorphisms are treated as a Rienzo 2000). Recent multilocus surveys suggest that single event. For these reasons, the numbers reported in tables patterns of polymorphism in D. melanogaster do not con- may differ slightly from previously published values. DnaSP3.0 form to the expectations of a panmictic population of (Rozas and Rozas 1999) was used for a subset of polymor- constant size (Andolfatto and Przeworski 2000; phism analyses. Andolfatto 2001; Przeworski et al. 2001). In particu- Estimating rates of crossing over: For each locus, we esti- mate r, the sex-averaged local rate of meiotic crossing over lar, the species probably has an African origin and has per kilobase per generation, following the approach of only recently become cosmopolitan (David and Capy Charlesworth (1996). In this method, each chromosomal 1988; Lachaise et al. 1988). There is also evidence that arm is divided into several regions. Each region was assigned populations are geographically structured (e.g., Hale either a linear or a quadratic function relating genetic distance and Singh 1991; Begun and Aquadro 1993). Given to physical distance. We modi®ed this method to incorporate estimates of the DNA content of each cytological band (Heino that African populations are thought to be ancestral, et al. 1994). Thus, the rate of crossing over is expressed in they are likely to have a more stable evolutionary history units of centimorgans per million bases (cM/Mb) rather than than non-African populations. As a result, they may be centimorgans per band (cM/ band). Since there is no crossing closer to the demographic assumptions of population over in D. melanogaster males (Ashburner 1989), female rates 1 2 genetic models; i.e., the effective population size is likely of crossing over are multiplied by ¤2 for autosomes and ¤3 for X-linked loci. to be
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