2017
DOI: 10.1101/211771
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

The role of chromosomal inversions in speciation

Abstract: The chromosomal inversions of D. persimilis and D. pseudoobscura have deeply influenced our understanding of the evolutionary forces that shape natural variation, speciation, and selfish chromosome dynamics. Here, we perform a comprehensive reconstruction of the evolutionary histories of the chromosomal inversions in these species. We provide a solution to the puzzling origins of the selfish Sex-Ratio chromosome in D. persimilis and show that this Sex-Ratio chromosome directly descends from an ancestrally-arra… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
7
0

Year Published

2018
2018
2023
2023

Publication Types

Select...
5
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(8 citation statements)
references
References 80 publications
(92 reference statements)
0
7
0
Order By: Relevance
“…Challenges remain for theorists to construct predictive models that can incorporate the complexity of the radiation process in any given system, including a distribution of effect sizes for a diverse set of polygenic traits contributing to reproductive isolation, diverse assortative mating mechanisms, complex fitness landscapes, and long-term structural evolution of the genome. In turn, many of the parameters most relevant to rapid radiation are still unknown in most case studies, including the ubiquity of phenotype matching (Kopp et al 2018), the proximity of neighboring fitness peaks in phenotype and genotype space (Blount et al 2012, Erwin 2017, Martin & Wainwright 2013b, and the frequency and timescale of physical linkages among adaptive alleles and DMIs (Fuller et al 2017, Wright et al 2013. Only with these models and data in hand will we be able to predict the full spectrum of the process of adaptive radiation.…”
Section: Discussionmentioning
confidence: 99%
See 3 more Smart Citations
“…Challenges remain for theorists to construct predictive models that can incorporate the complexity of the radiation process in any given system, including a distribution of effect sizes for a diverse set of polygenic traits contributing to reproductive isolation, diverse assortative mating mechanisms, complex fitness landscapes, and long-term structural evolution of the genome. In turn, many of the parameters most relevant to rapid radiation are still unknown in most case studies, including the ubiquity of phenotype matching (Kopp et al 2018), the proximity of neighboring fitness peaks in phenotype and genotype space (Blount et al 2012, Erwin 2017, Martin & Wainwright 2013b, and the frequency and timescale of physical linkages among adaptive alleles and DMIs (Fuller et al 2017, Wright et al 2013. Only with these models and data in hand will we be able to predict the full spectrum of the process of adaptive radiation.…”
Section: Discussionmentioning
confidence: 99%
“…In taxa with labile structural evolution (e.g., fish, mammals), simulations indicate that chromosomal rearrangements are likely to produce physically linked clusters of coadapted alleles (Yeaman 2013). Alternatively, inversions may be segregating within ancient populations, and adaptive alleles may be more likely to fix within them later, as recently found in the Drosophila persimilis and D. pseudoobscura species pair (Fuller et al 2017). More broadly, there are numerous other examples of introgression or sorting of ancient adaptive alleles during adaptive radiation, such as Heliconius butterflies (Heliconius Genome Consortium 2012), Rhagoletis flies (Feder et al 2003), Caribbean pupfishes (Richards & Martin 2017), Cameroon crater lake cichlids (Richards et al 2018), and tomatoes (Pease et al 2016).…”
Section: The Transporter Process: the Ancient Origins Of Adaptive Allmentioning
confidence: 94%
See 2 more Smart Citations
“…Pairs of dotted lines are interacting genes: co-adapted gene complexes or genetic incompatibilities. Blue represents low genetic divergence between populations, orange represents high divergence and purple (as in the model of Fuller et al 2017) represents high divergence segregating within populations. In contrast to the other models, higher divergence within inverted regions compared to collinear regions is not a consequence of (differential) gene flow.…”
Section: Genome and Gene Duplicationsmentioning
confidence: 99%