Inference of chromosomal inversion dynamics from<scp>P</scp>ool‐<scp>S</scp>eq data in natural and laboratory populations of<i><scp>D</scp>rosophila melanogaster</i>

Kapun, Martin; Schalkwyk, Hester van; McAllister, Bryant F.; Flatt, Thomas; Schlötterer, Christian

doi:10.1111/mec.12594

Cited by 108 publications

(180 citation statements)

References 73 publications

(135 reference statements)

Supporting

Mentioning

169

Contrasting

Order By: Relevance

“…In Raleigh, North Carolina, In(3R)Mo has increased dramatically in frequency from nearly undetectable levels in 1977 (Mettler et al 1977) to 20% frequency in 2003 (Langley et al 2012). Similar frequency increases have been observed for In(3R)Mo in many other populations as well (Kapun et al 2014(Kapun et al , 2016. Furthermore, In(3R)Mo maintains linkage between large haplotypes (1 Mb) that are distant from the inversion breakpoints both inside and outside of the inverted region (Corbett-Detig and Hartl 2012; Langley et al 2012), potentially consistent with stronglysuppressed recombination across much of chromosome arm 3R and selection to maintain linkage between distant alleles.…”

Section: Discussionsupporting

confidence: 58%

Selection on Inversion Breakpoints Favors Proximity to Pairing Sensitive Sites in Drosophila melanogaster

Corbett-Detig

2016

Genetics

View full text Add to dashboard Cite

Chromosomal inversions are widespread among taxa, and have been implicated in a number of biological processes including adaptation, sex chromosome evolution, and segregation distortion. Consistent with selection favoring linkage between loci, it is well established that length is a selected trait of inversions. However, the factors that affect the distribution of inversion breakpoints remain poorly understood. "Sensitive sites" have been mapped on all euchromatic chromosome arms in Drosophila melanogaster, and may be a source of natural selection on inversion breakpoint positions. Briefly, sensitive sites are genomic regions wherein proximal structural rearrangements result in large reductions in local recombination rates in heterozygotes. Here, I show that breakpoints of common inversions are significantly more likely to lie within a cytological band containing a sensitive site than are breakpoints of rare inversions. Furthermore, common inversions for which neither breakpoint intersects a sensitive site are significantly longer than rare inversions, but common inversions whose breakpoints intersect a sensitive site show no evidence for increased length. I interpret these results to mean that selection favors inversions whose breakpoints disrupt synteny near to sensitive sites, possibly because these inversions suppress recombination in large genomic regions. To my knowledge this is the first evidence consistent with positive selection acting on inversion breakpoint positions.KEYWORDS chromosomal inversions; Drosophila melanogaster; sensitive sites; structural variation; breakpoints S UCCESSFUL chromosomal inversions are generally thought to be favorable due to reduced recombination rates between arrangements (Krimbas and Powell 1992;Hoffmann and Rieseberg 2008;Kirkpatrick 2010). In the majority of theoretical treatments, it is believed that inversions are favored because they suppress recombination between genetically distant alleles that are favored in similar contexts. For example, this can result from an array of biological processes including local adaptation (Kirkpatrick and Barton 2006), sex chromosome evolution (Charlesworth et al. 2005), and maintenance of segregation distortion complexes (Lyon 2003). Consistent with this idea, longer chromosomal inversions are expected to be favored by selection relative to shorter inversions because they can suppress recombination between a larger number of genetically distant loci (Crumpacker and Kastritsis 1967;Krimbas and Powell 1992). Indeed, numerous studies in Drosophila have shown that high frequency and fixed inversions are significantly longer than rare and low frequency inversions (Olvera et al. 1979;Ruiz et al. 1984;Cáceres et al. 1997). Furthermore, common inversions are significantly longer than theoretical predictions of the length distribution that should be generated through neutral processes (Van Valen and Levins 1968;Brehm and Krimbas 1991;Krimbas and Powell 1992). Although some evidence indicates that intermediate length inversions are fa...

show abstract

Section: Discussionsupporting

confidence: 58%

Selection on Inversion Breakpoints Favors Proximity to Pairing Sensitive Sites in Drosophila melanogaster

Corbett-Detig

2016

Genetics

View full text Add to dashboard Cite

show abstract

“…We estimated inversion frequency from pooled allele frequency data by calculating the average frequency of SNPs previously identified as being closely linked to these inversions (Kapun et al 2014). With the exception of In(2L)t, we find that most inversions are rare in the populations that we examined, typically segregating at less than 15% frequency in most populations (Supplemental Figure 10).…”

Section: Cc-by-nc-ndmentioning

confidence: 90%

“…To test whether large cosmopolitan inversions change in frequency between spring and fall we calculated the average frequency of SNPs that are closely linked to inversion karyotype (Kapun et al 2014). .…”

Section: Seasonal Changes In Inversion Frequenciesmentioning

confidence: 99%

Broad geographic sampling reveals predictable, pervasive, and strong seasonal adaptation inDrosophila

Taylor

et al. 2018

Preprint

Self Cite

173

View full text Add to dashboard Cite

Local adaptation in response to spatially varying selection pressures is widely recognized as a ubiquitous feature for many organisms. In contrast, our understanding of local adaptation to temporally varying selection pressures is limited. To advance our understanding of local adaptation to temporally varying selection pressures, we studied genomic signatures of seasonal adaptation in Drosophila melanogaster. We generated whole-genome estimates of allele frequencies from flies sampled during the spring and fall from 15 localities. We show that seasonal adaptation is a general feature fly populations and that the direction of seasonal adaptation can be predicted by weather conditions in the weeks prior to sampling. We find that seasonal changes in allele frequency are mirrored by spatial variation in allele frequency and that seasonal adaptation affects allele frequencies at ~1.0-2.5% of polymorphisms genomewide. Our work demonstrates that seasonal adaptation is a major evolutionary force affecting D. melanogaster populations living in temperate environments.

show abstract

“…Furthermore, b N e is low on the entire chromosome arm 3R and also on parts of 3L. Overall, these patterns can be attributed to strong LD, caused either by low recombination rates around the centromeres (Chan et al 2012) or by segregating inversions (Kapun et al 2014) in combination with selection potentially on rare variants. The reduction in b N e is also well captured by the segmentation algorithm (Figure 7), which shows a similar pattern when applied on simulated data with selection ( Figure S15).…”

Section: Heterogeneous Bmentioning

confidence: 94%

Estimating effective population size from temporal allele frequency changes in experimental evolution

Jónás¹,

Taus²,

Kosiol³

et al. 2016

Preprint

Self Cite

View full text Add to dashboard Cite

The effective population size (N e ) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term N e : They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to N e : Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of N e ; which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate N e estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide N e estimates, we extend our method using a recursive partitioning approach to estimate N e locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their N e estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest. KEYWORDS effective population size; genetic drift; Pool-seq; experimental evolution D URING experimental evolution studies, populations are maintained under specific laboratory conditions (Kawecki et al. 2012;Long et al. 2015;Schlötterer et al. 2015). In sexually reproducing organisms, the census population size is typically kept fixed at fairly low numbers, rarely exceeding 2000 individuals. With such small population sizes, genetic drift causes stochastic fluctuations in allele frequencies. Under neutrality, the level of random frequency changes is determined by the effective population size (N e ) (Wright 1931). Furthermore, the efficacy of selection is influenced by N e : For weakly selected alleles, the probability of fixation is directly proportional to the product of N e and the intensity of selection (Fisher 1930;Kimura 1964). As changes in allele frequency are greatly affected by the population size, it is fundamental to estimate N e accurately to understand molecular variation in experimental evolution studies. Krimbas and Tsakas (1971) estimated N e using the standardized variance of allele frequency (F, see also Falconer and Mackay 1996) from longitudinal samples in natural populations of olive flies. As F was calculated from these samples, they accounted for the sampling variance that also contributed to the true allele frequency variance. This approach was further improved and used by sev...

show abstract

Inference of chromosomal inversion dynamics fromPool‐Seq data in natural and laboratory populations ofDrosophila melanogaster

Cited by 108 publications

References 73 publications

Selection on Inversion Breakpoints Favors Proximity to Pairing Sensitive Sites in Drosophila melanogaster

Selection on Inversion Breakpoints Favors Proximity to Pairing Sensitive Sites in Drosophila melanogaster

Broad geographic sampling reveals predictable, pervasive, and strong seasonal adaptation inDrosophila

Estimating effective population size from temporal allele frequency changes in experimental evolution

Contact Info

Product

Resources

About