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Hybridization Underlies Localized Trait Evolution in Cavefish

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Hybridization Underlies Localized Trait Evolution in Cavefish bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 1 2 Hybridization underlies localized trait evolution in cavefish 3 4 5 Moran, Rachel L.,1 Jaggard, James B. 2,3, Roback, Emma Y.1, Rohner, Nicolas4,5, Kowalko, 6 Johanna E.6, Ornelas-García, C. Patricia7 McGaugh, Suzanne E. 1*, Keene, Alex C. 2* 7 1. Department of Ecology, Evolution, and Behavior, University of Minnesota, Saint Paul, MN 8 2. Department of Biological Sciences, Florida Atlantic University, Jupiter FL 9 3. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 10 4. Stowers Institute for Medical Research, Kansas City, MO 11 5. Department of Molecular & Integrative Physiology, KU Medical Center, Kansas City, KS 12 6. Harriet L. Wilkes Honors College, Florida Atlantic University, Jupiter FL 13 7. Departamento de Zoología, Instituto de Biología, Universidad Autónoma de México, CP 14 04510, Mexico City, Mexico 15 16 17 18 19 20 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 21 Summary 22 Compared to selection on new mutations and standing genetic variation, the role of gene flow in 23 generating adaptive genetic variation has been subject to much debate. Theory predicts that gene 24 flow constrains adaptive evolution via natural selection by homogenizing allele frequencies among 25 populations and introducing migrant alleles that may be locally maladaptive1. However, recent 26 work has revealed that populations can diverge even when high levels of gene flow are present2– 27 4 and that gene flow may play an underappreciated role in facilitating local adaptation by 28 increasing the amount of genetic variation present for selection to act upon5–8. Here, we 29 investigate how genetic variation introduced by gene flow contributes to adaptive evolution of 30 complex traits using an emerging eco-evolutionary model system, the Mexican tetra (Astyanax 31 mexicanus). The ancestral surface form of the Mexican tetra has repeatedly invaded and adapted 32 to cave environments. The Chica cave is unique in that it contains several pool microenvironments 33 inhabited by putative hybrids between surface and cave populations9, providing an opportunity to 34 investigate the dynamics of complex trait evolution and gene flow on a local scale. Here we 35 conduct high-resolution genomic mapping and analysis of eye morphology and pigmentation in 36 fish from multiple pools within Chica cave. We demonstrate that hybridization between cave and 37 surface populations contributes to highly localized variation in behavioral and morphological traits. 38 Analysis of sleep and locomotor behaviors between individual pools within this cave revealed 39 reduced sleep associated with an increase in ancestry derived from cave populations, suggesting 40 pool-specific ecological differences may drive the highly-localized evolution of sleep and 41 locomotor behaviors. Lastly, our analyses uncovered a compelling example of convergent 42 evolution in a core circadian clock gene in multiple independent cavefish lineages and burrowing 43 mammals, indicating a shared genetic mechanism underlying circadian disruption in subterranean 44 vertebrates. Together, our results provide insight into the evolutionary mechanisms that promote 45 adaptive genetic variation and the genetic basis of complex behavioral phenotypes involved in 46 local adaptation. 2 bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 47 Main Text 48 A rapidly growing body of research demonstrates that gene flow, both among populations within 49 species and between different species, is more common than previously thought and can play a 50 key role in the evolutionary process by impeding or promoting adaptive divergence5,6,10–12. Hybrid 51 zones resulting from interbreeding between lineages that occupy different environmental 52 extremes offer a powerful means to detect targets of selection in the genome underlying complex, 53 locally adapted traits. Natural variation present in recombinant hybrids can be leveraged through 54 admixture mapping13,14, which identifies associations between genetic ancestry and trait variation 55 in admixed populations formed by interbreeding between two or more diverged lineages. This 56 association-based approach was first developed to uncover the genetic basis of diseases in 57 humans following the observation that the frequencies of some disease-causing variants differ 58 substantially among populations15,16. Recent advances in sequencing technology and statistical 59 approaches have made it feasible to apply admixture mapping to identify adaptive loci underlying 60 ecological divergence in plant and animal models of evolution17–24. However, previous studies in 61 plants and animals have focused on hybrids formed between distinct species with substantial 62 genetic divergence and reproductive isolation, making it difficult to identify regions associated with 63 ecologically relevant traits versus intrinsic incompatibilities25. The application of admixture 64 mapping to models of trait evolution has the potential to define fundamental interactions between 65 genetic and environmental variation that shape evolution. Studies that apply whole genome 66 sequencing to hybrids formed between interbreeding lineages in the earliest stages of divergence 67 are likely to provide the most insight into the genetic basis of evolutionary change24,26, but are 68 currently lacking. 69 70 The Mexican tetra, Astyanax mexicanus, is a powerful model system for investigating the genetic 71 and evolutionary basis of trait development and behavior27–31. Surface populations inhabit rivers 3 bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 72 from Texas to Mexico and have invaded caves multiple times, resulting in at least 30 populations 73 of cave-morphs in the Sierra de El Abra region of Northeast Mexico9,32. At least two independent 74 lineages of surface fish, commonly referred to in the literature as “old” and “new” lineages, have 75 invaded caves within the past roughly 200,000 years33–37. Cavefish populations have converged 76 on numerous morphological traits that are thought to be adaptive in the cave environment, 77 including albinism and eye loss38. In addition, cavefish have repeatedly evolved multiple 78 behavioral changes, including sleep loss, which may increase time allocated to foraging in 79 nutrient-poor cave environments29,39. Recently, the application of molecular genetic approaches 80 has led to the identification of genetic factors that regulate some of these trait differences, but the 81 evolutionary mechanisms underlying these genetic differences remain poorly understood. 82 83 Cave and surface populations are interfertile under laboratory conditions, and we recently 84 identified a surprising amount of historical and contemporary gene flow between surface and cave 85 populations36. The presence of admixture between populations raises the possibility that gene 86 flow is a critical driver of trait evolution36. Unlike most caves, the Chica cave contains fish that 87 appear to exhibit high levels of phenotypic variation, and fish are present across four pools that 88 differ in proximity to the cave entrance, nutrient input, and physicochemical properties (e.g., 89 dissolved oxygen) (Fig. 1A)9,40–42. Historical surveys suggested that fish exhibit a morphological 90 gradation in troglobitic traits across pools, potentially shaped by environmental variation within 91 the cave and ongoing influx of surface and cave morphs from underground waterways that feed 92 into the cave9. Thus, this cave provides a natural system to study the effects of hybridization on 93 trait evolution across a variable environment. Quantification of trait variation and formal tests for 94 hybridization have yet to be conducted. Here we leverage robust differences in behavior and 95 morphology between surface and cavefish populations of Mexican tetras, combined with whole 96 genome sequencing, to investigate the ancestry of putative hybrids in Chica cave and to examine 97 the genetic basis of trait variability across a heterogeneous environment. 4 bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 98 Figure 1. (A) Map of Chica cave modified with permission from 43. (B) Collection locations for cave and 99 surface populations. For the two surface populations, the collection location for Río Choy is represented by 100 a light blue circle and the collection location for Rascón is represented by a dark blue circle. (C) 101 Representative images of wild-caught fish. Scale bar denotes 1 cm. (D) Representative images of eye 5 bioRxiv preprint doi: https://doi.org/10.1101/2021.05.11.443489; this version posted May 12, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
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