Movatterモバイル変換


[0]ホーム

URL:


Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature
  • Article
  • Published:

An ancient recombination desert is a speciation supergene in placental mammals

Nature (2025)Cite this article

Subjects

Abstract

Gene flow between biological species is a common and often adaptive evolutionary phenomenon throughout the tree of life1,2,3,4. Given the pervasive nature of genetic exchange, a daunting challenge is how best to infer the correct relationships between species from the complex collection of histories arrayed across genomes5. The local rate of meiotic recombination influences the distribution of signatures of, and barriers to, gene flow during the early stages of speciation6. Still, a broader understanding of this relationship and its application to accurately discerning phylogeny is lacking due to a scarcity of recombination maps. Here we applied deep learning methods to genome alignments from 22 divergent placental mammal species to infer the evolution of the recombination landscape. We identified a large and evolutionarily conserved X-linked recombination desert constituting 30% of the chromosome. Recombination-aware phylogenomic analyses from 94 species revealed that the X-linked recombination desert is an ancient and recurrent barrier to gene flow and retains the species history when introgression dominates genome-wide ancestry. The functional basis for this supergene is manifold, enriched with genes that influence sex chromosome silencing and reproduction traits. Because the locus underpins reproductive isolation across ordinal lineages, it may represent a reliable marker for resolving challenging relationships across the mammalian phylogeny.

This is a preview of subscription content,access via your institution

Access options

Access through your institution

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

9,800 Yen / 30 days

cancel any time

Subscription info for Japanese customers

We have a dedicated website for our Japanese customers. Please go tonatureasia.com to subscribe to this journal.

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Comparative dataset for recombination-aware phylogenomics.
Fig. 2: Evolutionary conservation of synteny, linkage and recombination patterns across the placental mammal phylogeny.
Fig. 3: Species-tree frequency is highest in genomic regions with low recombination rates and in the XLRD.
Fig. 4: Genome-wide ancestry distribution patterns.
Fig. 5: XLRD restricted gene flow is reflected in population genomic data.

Similar content being viewed by others

Data availability

All publicly available data used as part of this study are listed in the relevant tables. New Illumina short-read sequencing data have been submitted to NCBI’s short-read archive and are available under bioproject IDsPRJNA1333566 andPRJNA1335549. Recombination maps and.vcf files are available at Zenodo (https://doi.org/10.5281/zenodo.15131984)93.

Code availability

Existing software used as part of the analyses is referenced in the main text. Custom scripts associated with the analyses are available at GitHub (https://github.com/eutherialab/Foley_XLRD).

References

  1. Rossi, M. et al. Adaptive introgression of a visual preference gene.Science383, 1368–1373 (2024).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  2. Fontsere, C., de Manuel, M., Marques-Bonet, T. & Kuhlwilm, M. Admixture in mammals and how to understand its functional implications.Bioessays41, e1900123 (2019).

    Article PubMed  Google Scholar 

  3. Fontaine, M. C. et al. Extensive introgression in a malaria vector species complex revealed by phylogenomics.Science347, 1258524 (2015).

    Article PubMed  Google Scholar 

  4. Jones, M. R. et al. Adaptive introgression underlies polymorphic seasonal camouflage in snowshoe hares.Science360, 1355–1358 (2018).

    Article CAS PubMed ADS  Google Scholar 

  5. Hibbins, M. & Hahn, M. Distinguishing between histories of speciation and introgression using genomic data.Bull. Soc. Syst. Biol.https://doi.org/10.18061/bssb.v3i1.9227 (2024).

    Article  Google Scholar 

  6. Schumer, M. et al. Natural selection interacts with recombination to shape the evolution of hybrid genomes.Science360, 656–660 (2018).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  7. Edelman, N. B. & Mallet, J. Prevalence and adaptive impact of introgression.Annu. Rev. Genet.55, 265–283 (2021).

    Article CAS PubMed  Google Scholar 

  8. Harrison, R. G. & Larson, E. L. Hybridization, introgression, and the nature of species boundaries.J. Hered.105, 795–809 (2014).

    PubMed  Google Scholar 

  9. Mayr, E.Animal Species and Evolution (Harvard Univ. Press, 1963).

  10. Bravo, G. A. et al. Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics.PeerJ7, e6399 (2019).

    Article PubMed PubMed Central  Google Scholar 

  11. Li, G., Figueiró, H. V., Eizirik, E. & Murphy, W. J. Recombination-aware phylogenomics reveals the structured genomic landscape of hybridizing cat species.Mol. Biol. Evol.36, 2111–2126 (2019).

    Article CAS PubMed PubMed Central  Google Scholar 

  12. Foley, N. M. et al. Karyotypic stasis and swarming influenced the evolution of viral tolerance in a species-rich bat radiation.Cell Genomics4, 100482 (2024).

    Article CAS PubMed PubMed Central  Google Scholar 

  13. Christmas, M. J. et al. Evolutionary constraint and innovation across hundreds of placental mammals.Science380, eabn3943 (2023).

    Article CAS PubMed PubMed Central  Google Scholar 

  14. Noor, M. A., Grams, K. L., Bertucci, L. A. & Reiland, J. Chromosomal inversions and the reproductive isolation of species.Proc. Natl Acad. Sci. USA98, 12084–12088 (2001).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  15. Nachman, M. W. & Payseur, B. A. Recombination rate variation and speciation: theoretical predictions and empirical results from rabbits and mice.Philos. Trans. R. Soc. Lond. B Biol. Sci.367, 409–421 (2012).

    Article PubMed PubMed Central  Google Scholar 

  16. Edelman, N. B. et al. Genomic architecture and introgression shape a butterfly radiation.Science366, 594–599 (2019).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  17. Burbrink, F. T., DeBaun, D., Foley, N. M. & Murphy, W. J. Recombination-aware phylogenomics.Trends Ecol. Evol.9, 900–912 (2025).

    Article  Google Scholar 

  18. Coyne, J. A. & Orr, H. A.Speciation (Sinauer Associates, 2004).

  19. Adrion, J. R., Galloway, J. G. & Kern, A. D. Predicting the landscape of recombination using deep learning.Mol. Biol. Evol.37, 1790–1808 (2020).

    Article CAS PubMed PubMed Central  Google Scholar 

  20. Foley, N. M. et al. A genomic timescale for placental mammal evolution.Science380, eabl8189 (2023).

    Article CAS PubMed PubMed Central  Google Scholar 

  21. Pathak, S. & Stock, A. D. The X chromosomes of mammals: karylogical homology as revealed by banding techniques.Genetics78, 703–714 (1974).

    Article CAS PubMed PubMed Central  Google Scholar 

  22. Graves, J. A. M. Evolution of vertebrate sex chromosomes and dosage compensation.Nat. Rev. Genet.17, 33–46 (2016).

    Article CAS PubMed  Google Scholar 

  23. Lahn, B. T. & Page, D. C. Four evolutionary strata on the human X chromosome.Science286, 964–967 (1999).

    Article CAS PubMed  Google Scholar 

  24. Rieseberg, L. H. Chromosomal rearrangements and speciation.Trends Ecol. Evol.16, 351–358 (2001).

    Article PubMed  Google Scholar 

  25. Haenel, Q., Laurentino, T. G., Roesti, M. & Berner, D. Meta-analysis of chromosome-scale crossover rate variation in eukaryotes and its significance to evolutionary genomics.Mol. Ecol.27, 2477–2497 (2018).

    Article PubMed  Google Scholar 

  26. Carneiro, M. et al. The genomic architecture of population divergence between subspecies of the European rabbit.PLoS Genet.10, e1003519 (2014).

    Article PubMed PubMed Central  Google Scholar 

  27. Christmas, M. J. et al. Genetic barriers to historical gene flow between cryptic species of alpine bumblebees revealed by comparative population genomics.Mol. Biol. Evol.38, 3126–3143 (2021).

    Article CAS PubMed PubMed Central  Google Scholar 

  28. Hibbins, M. S. & Hahn, M. W. Phylogenomic approaches to detecting and characterizing introgression.Genetics220, iyab173 (2022).

    Article PubMed  Google Scholar 

  29. Schierup, M. H. & Hein, J. Consequences of recombination on traditional phylogenetic analysis.Genetics156, 879–891 (2000).

    Article CAS PubMed PubMed Central  Google Scholar 

  30. Brashear, W. A., Bredemeyer, K. R. & Murphy, W. J. Genomic architecture constrained placental mammal X chromosome evolution.Genome Res.31, 1353–1365 (2021).

    Article CAS PubMed PubMed Central  Google Scholar 

  31. Kruger, A. N. et al. A neofunctionalized X-linked ampliconic gene family is essential for male fertility and equal sex ratio in mice.Curr. Biol.29, 3699–3706 (2019).

    Article CAS PubMed PubMed Central  Google Scholar 

  32. Davis, B. W. et al. Mechanisms underlying mammalian hybrid sterility in two feline interspecies models.Mol. Biol. Evol.32, 2534–2546 (2015).

    Article CAS PubMed PubMed Central  Google Scholar 

  33. Kaelin, C. B. et al. Ancestry dynamics and trait selection in a designer cat breed.Curr. Biol.34, 1506–1518 (2024).

    Article CAS PubMed PubMed Central  Google Scholar 

  34. Jamieson, A. et al. Limited historical admixture between European wildcats and domestic cats.Curr. Biol.33, 4751–4760 (2023).

    Article CAS PubMed  Google Scholar 

  35. Ai, H., Huang, L. & Ren, J. Genetic diversity, linkage disequilibrium and selection signatures in Chinese and Western pigs revealed by genome-wide SNP markers.PLoS ONE8, e56001 (2013).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  36. Darlington, C. D. & Mather, K.Elements of Genetics (George Allen & Unwin Ltd, 1949).

  37. Thompson, M. J. & Jiggins, C. D. Supergenes and their role in evolution.Heredity113, 1–8 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  38. Berdan, E. L., Flatt, T., Kozak, G. M., Lotterhos, K. E. & Wielstra, B. Genomic architecture of supergenes: connecting form and function.Philos. Trans. R. Soc. Lond. B Biol. Sci.377, 20210192 (2022).

    Article PubMed PubMed Central  Google Scholar 

  39. Jay, P., Jeffries, D., Hartmann, F. E., Véber, A. & Giraud, T. Why do sex chromosomes progressively lose recombination?.Trends Genet.40, 564–579 (2024).

    Article CAS PubMed  Google Scholar 

  40. Lenormand, T. & Roze, D. Y recombination arrest and degeneration in the absence of sexual dimorphism.Science375, 663–666 (2022).

    Article CAS PubMed ADS  Google Scholar 

  41. Loda, A., Collombet, S. & Heard, E. Gene regulation in time and space during X-chromosome inactivation.Nat. Rev. Mol. Cell Biol.23, 231–249 (2022).

    Article CAS PubMed  Google Scholar 

  42. Sauteraud, R. et al. Inferring genes that escape X-chromosome inactivation reveals important contribution of variable escape genes to sex-biased diseases.Genome Res.31, 1629–1637 (2021).

    Article CAS PubMed PubMed Central  Google Scholar 

  43. Bansal, P., Kondaveeti, Y. & Pinter, S. F. Forged byDXZ4,FIRRE, andICCE: How tandem repeats shape the active and inactive X chromosome.Front. Cell Dev. Biol.7, 328 (2019).

    Article PubMed  Google Scholar 

  44. Westervelt, N. & Chadwick, B. P. Characterization of theICCE repeat in mammals reveals an evolutionary relationship with theDXZ4 macrosatellite through conserved CTCF binding motifs.Genome Biol. Evol.10, 2190–2204 (2018).

    Article CAS PubMed PubMed Central  Google Scholar 

  45. Bredemeyer, K. R. et al. Rapid macrosatellite evolution promotes X-linked hybrid male sterility in a feline interspecies cross.Mol. Biol. Evol.38, 5588–5609 (2021).

    Article CAS PubMed PubMed Central  Google Scholar 

  46. Guo, J. et al. The adult human testis transcriptional cell atlas.Cell Res.28, 1141–1157 (2018).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  47. Larson, E. L., Kopania, E. E. K. & Good, J. M. Spermatogenesis and the evolution of mammalian sex chromosomes.Trends Genet.34, 722 (2018).

    Article CAS PubMed PubMed Central  Google Scholar 

  48. Sinnott-Armstrong, N., Naqvi, S., Rivas, M. & Pritchard, J. GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background.eLife10, e58615 (2020).

    Article  Google Scholar 

  49. Rice, W. Sex chromosomes and the evolution of sexual dimorphism.Evolution38, 735–742 (1984).

    Article PubMed  Google Scholar 

  50. Chakrabarty, A., Chakraborty, S., Nandi, D. & Basu, A. Multivariate genetic architecture reveals testosterone-driven sexual antagonism in contemporary humans.Proc. Natl Acad. Sci. USA121, e2404364121 (2024).

    Article CAS PubMed PubMed Central  Google Scholar 

  51. Ruth, K. S. et al. Using human genetics to understand the disease impacts of testosterone in men and women.Nat. Med.26, 252–258 (2020).

    Article CAS PubMed PubMed Central  Google Scholar 

  52. Mueller, J. L. et al. Independent specialization of the human and mouse X chromosomes for the male germ line.Nat. Genet.45, 1083–1087 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  53. Bohutínská, M. & Peichel, C. L. Divergence time shapes gene reuse during repeated adaptation.Trends Ecol. Evol.39, 396–407 (2024).

    Article PubMed  Google Scholar 

  54. Lenormand, T. & Roze, D. A single theory for the evolution of sex chromosomes and the two rules of speciation.Science389, eado9032 (2025).

    Article CAS PubMed  Google Scholar 

  55. Delmore, K. E., DaCosta, J. M. & Winker, K. Thrushes in love: Extensive gene flow, with differential resistance and selection, obscures and reveals the evolutionary history of a songbird clade.Mol. Ecol.https://doi.org/10.1111/mec.17635 (2025).

    Article PubMed  Google Scholar 

  56. de Queiroz, A. & Gatesy, J. The supermatrix approach to systematics.Trends Ecol. Evol.22, 34–41 (2007).

    Article PubMed  Google Scholar 

  57. Faircloth, B. C. et al. Ultraconserved elements anchor thousands of genetic markers spanning multiple evolutionary timescales.Syst. Biol.61, 717–726 (2012).

    Article PubMed  Google Scholar 

  58. Murat, F. et al. The molecular evolution of spermatogenesis across mammals.Nature613, 308–316 (2023).

    Article CAS PubMed ADS  Google Scholar 

  59. Stiller, J. et al. Complexity of avian evolution revealed by family-level genomes.Nature629, 851–860 (2024).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  60. Moore, T. X centromeric drive may explain the prevalence of polycystic ovary syndrome and other conditions.Bioessays46, e2400056 (2024).

    Article PubMed  Google Scholar 

  61. O’Brien, S. J., Graphodatsky, A. S. & Perelman, P. L.Atlas of Mammalian Chromosomes (Wiley Blackwell, 2020).

  62. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint athttps://doi.org/10.48550/arXiv.1303.3997 (2013).

  63. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform.Bioinformatics25, 1754–1760 (2009).

    Article CAS PubMed PubMed Central  Google Scholar 

  64. García-Alcalde, F. et al. Qualimap: evaluating next-generation sequencing alignment data.Bioinformatics28, 2678–2679 (2012).

    Article PubMed  Google Scholar 

  65. Li, H. et al. The sequence alignment/map format and SAMtools.Bioinformatics25, 2078–2079 (2009).

    Article PubMed PubMed Central  Google Scholar 

  66. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.Genome Res.20, 1297–1303 (2010).

    Article CAS PubMed PubMed Central  Google Scholar 

  67. Van der Auwera, G. A. et al. From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline.Curr. Protoc. Bioinformatics11, 11.10.1–11.10.33 (2013).

    Google Scholar 

  68. Kumar, S. & Subramanian, S. Mutation rates in mammalian genomes.Proc. Natl Acad. Sci. USA99, 803–808 (2002).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  69. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses.Am. J. Hum. Genet.81, 559–575 (2007).

    Article CAS PubMed PubMed Central  Google Scholar 

  70. Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations.BMC Genet.11, 94 (2010).

    Article PubMed PubMed Central  Google Scholar 

  71. Wilder, A. P. et al. The contribution of historical processes to contemporary extinction risk in placental mammals.Science380, eabn5856 (2023).

    Article CAS PubMed PubMed Central  Google Scholar 

  72. Danecek, P. et al. The variant call format and VCFtools.Bioinformatics27, 2156–2158 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  73. Lovell, J. T. et al. GENESPACE tracks regions of interest and gene copy number variation across multiple genomes.eLife11, e78526 (2022).

    Article CAS PubMed PubMed Central  Google Scholar 

  74. Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics.Genome Biol.20, 238 (2019).

    Article PubMed PubMed Central  Google Scholar 

  75. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool.J. Mol. Biol.215, 403–410 (1990).

    Article CAS PubMed  Google Scholar 

  76. Porubsky, D. et al. SVbyEye: a visual tool to characterize structural variation among whole-genome assemblies.Bioinformatics41, btaf332 (2025).

    Article CAS PubMed PubMed Central  Google Scholar 

  77. Li, H. Minimap2: pairwise alignment for nucleotide sequences.Bioinformatics34, 3094–3100 (2018).

    Article CAS PubMed PubMed Central  Google Scholar 

  78. Murphy, W. J., Foley, N. M., Bredemeyer, K. R., Gatesy, J. & Springer, M. S. Phylogenomics and the genetic architecture of the placental mammal radiation.Annu. Rev. Anim. Biosci.9, 29–53 (2020).

    Article PubMed  Google Scholar 

  79. Korneliussen, T. S., Albrechtsen, A. & Nielsen, R. ANGSD: analysis of next generation sequencing data.BMC Bioinf.15, 356 (2014).

    Article  Google Scholar 

  80. Harris, A. J., Foley, N. M., Williams, T. L. & Murphy, W. J. Tree House Explorer: a novel genome browser for phylogenomics.Mol. Biol. Evol.39, msac130 (2022).

    Article CAS PubMed PubMed Central  Google Scholar 

  81. Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses.Bioinformatics25, 1972–1973 (2009).

    Article PubMed PubMed Central  Google Scholar 

  82. Borowiec, M. L. AMAS: a fast tool for alignment manipulation and computing of summary statistics.PeerJ4, e1660 (2016).

    Article PubMed PubMed Central  Google Scholar 

  83. Minh, B. Q. et al. IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era.Mol. Biol. Evol.37, 1530–1534 (2020).

    Article CAS PubMed PubMed Central  Google Scholar 

  84. Crotty, S. M. et al. GHOST: recovering historical signal from heterotachously evolved sequence alignments.Syst. Biol.69, 249–264 (2020).

    CAS PubMed  Google Scholar 

  85. Minh, B. Q., Nguyen, M. A. T. & von Haeseler, A. Ultrafast approximation for phylogenetic bootstrap.Mol. Biol. Evol.30, 1188–1195 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  86. Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: improving the ultrafast bootstrap approximation.Mol. Biol. Evol.35, 518–522 (2018).

    Article CAS PubMed  Google Scholar 

  87. Lemey, P., Salemi, M. & Vandamme, A.-M.The Phylogenetic Handbook: A Practical Approach to Phylogenetic Analysis and Hypothesis Testing (Cambridge Univ. Press, 2009).

  88. Green, R. E. et al. A draft sequence of the Neandertal genome.Science328, 710–722 (2010).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  89. Feder, J. L. et al. Mayr, Dobzhansky, and Bush and the complexities of sympatric speciation inRhagoletis.Proc. Natl Acad. Sci. USA102, 6573–6580 (2005).

    Article CAS PubMed PubMed Central ADS  Google Scholar 

  90. Pandey, R. S., Wilson Sayres, M. A. & Azad, R. K. Detecting evolutionary strata on the human X chromosome in the absence of gametologous Y-linked sequences.Genome Biol. Evol.5, 1863–1871 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  91. Gel, B. & Serra, E. karyoploteR: an R/Bioconductor package to plot customizable genomes displaying arbitrary data.Bioinformatics33, 3088–3090 (2017).

    Article CAS PubMed PubMed Central  Google Scholar 

  92. Wickham, H.Ggplot2: Elegant Graphics for Data Analysis (Springer International Publishing, 2016).

  93. Foley, N. An ancient recombination desert is a speciation supergene in placental mammals.Zenodohttps://doi.org/10.5281/zenodo.15131984 (2025).

  94. Li, G. et al. A high-resolution SNP array-based linkage map anchors a new domestic cat draft genome assembly and provides detailed patterns of recombination.G3 (Bethesda)6, 1607–1616 (2016).

    Article PubMed  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the undergraduate researchers who participated in Aggie Research Teams during this project: S. Archard, M. Clark, S. Gaikaiwari and J. Arukakkal. We also thank A. Camagnini, L. Frantz and G. Larson for providing a published version of a variant call file ofFelis species. Portions of this research were conducted with the advanced computing resources provided by Texas A&M High-Performance Research Computing. This work was funded by National Science Foundation grants DEB-1753760, awarded to W.J.M., and DEB-2150664, awarded to W.J.M. and T.R. The black-footed ferret data were funded by a Morris Animal Foundation grant, D18ZO-058, awarded to K.P.K.

Author information

Authors and Affiliations

  1. Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA

    Nicole M. Foley, Richard G. Rasulis, Zoya Wani, Mayra N. Mendoza Cerna, Terje Raudsepp & William J. Murphy

  2. Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA

    Mayra N. Mendoza Cerna, Terje Raudsepp & William J. Murphy

  3. Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA, USA

    Henrique V. Figueiró & Klaus Peter Koepfli

Authors
  1. Nicole M. Foley
  2. Richard G. Rasulis
  3. Zoya Wani
  4. Mayra N. Mendoza Cerna
  5. Henrique V. Figueiró
  6. Klaus Peter Koepfli
  7. Terje Raudsepp
  8. William J. Murphy

Contributions

W.J.M. and N.M.F. conceived and designed the project. W.J.M., T.R. and N.M.F. supervised the project. Recombination maps were created by N.M.F., R.G.R., Z.W. and M.N.M.C. Comparative recombination analyses were carried out by N.M.F.Mustela nigripes population genomic data were supplied by H.V.F. and K.P.K. Phylogenomic, population genomic and functional analyses were conducted by N.M.F. The paper was authored by W.J.M. and N.M.F. with contributions from all authors. All authors reviewed and approved the final manuscript.

Corresponding authors

Correspondence toNicole M. Foley orWilliam J. Murphy.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks the anonymous reviewer(s) for their contribution to the peer review of this work.Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Comparison of recombination maps using parent-offspring trio-inferred versus pan-mammal mutation rates.

a,Macaca mulatta (n = 4: individuals) maps inferred with both rates showed a significant correlation (Spearman’s rho = 0.75,p < 2.2e-16; Kendall’s tau = 0.55,p < 2.2e-16, z = 44.972).b,Papio anubis (n = 3: individuals) maps inferred with both rates also showed a significant correlation (Spearman’s rho = 0.80,p < 2.2e-16; Kendall’s tau = 0.61,p < 2.2e-16, z = 47.838).

Extended Data Fig. 2 The effect of population substructure on estimating recombination rates along the X chromosome.

PCA of three data subsets (colors), with varying numbers of individuals shown in the PCA forMacaca mulatta. All samples were submitted to SRA by Oregon Health and Science University. Statistical analysis focused on the extremes of the dataset comparisons; N-12 vs N = 4, and the indicated recombination landscapes were significantly correlated (Spearman’s rho = 0.74,p < 2.2e-16) (Kendall’s tau = 0.56,p < 2.2e-16, z = 44.587).

Extended Data Fig. 3 Comparison of ReLERNN recombination maps for the X chromosome with multigenerational pedigree-based linkage maps.

a, The ReLERNN map generated forSus scrofa closely resembles the landscape shown in pedigree-based recombination maps35.b, Comparison of recombination maps for the domestic cat X chromosome based on linkage analysis of multigenerational pedigrees94 (blue) and a domestic cat ReLERNN map derived from 10 (orange) and 3 (green) individuals of the Persian cat breed.

Extended Data Fig. 4 The recombination landscape of the X chromosome is conserved among closely related species.

a, Conservation of the recombination landscape between subspecies ofPanthera tigris (P. t. jacksoni n = 4: individuals;P.t. sumatrae n = 4: individuals) (Spearman’s rho = 0.78,p < 2.2e-16) (Kendall’s tau = 0.60,p < 2.2e-16, z = 38.719).b, Conservation of the recombination landscape between closely related dolphin species,Tursiops truncatus (n = 4: individuals) andTursiops aduncus (n = 4: individuals) (Spearman’s rho = 0.90,p < 2.2e-16) (Kendall’s tau = 0.72,p < 2.2e-16, z = 54.865).

Extended Data Fig. 5 Nucleotide diversity and effective population size across a subset of species for which we generated a recombination map.

a, There was no systematic difference between primates derived from captive populations used for research purposes and the rest of the wild and domestic species in terms of nucleotide diversity and effective population size. Estimates of effective population sizes are from Wilder et al.71. Species names in purple indicate closely related species with similar IUCN statuses.b, Despite a large difference in nucleotide diversity betweenPrionailurus bengalensis (n = 5: individuals; IUCN Least Concern) andPanthera tigris (n = 4: individuals; IUCN Endangered), a similar recombination landscape on the X chromosome was observed. These results suggest that our recombination maps are robust to differences in nucleotide diversity (Spearman’s rho = 0.81,p < 2.2e-16) (Kendall’s tau = 0.60,p < 2.2e-16, z = 39.92).

Extended Data Fig. 6 The relationship between the frequency of T1 (shown in blue – the species tree) and recombination quintiles for Group 1 and 2.

The relationship between the recombination quintiles and the next most frequent non-species topology is shown in red. Where correlations do not match the patterns observed in most species (e.g., dolphins – bottom), these clades typically show a higher level of ILS as the cause of discordance (see Supplementary Table6).

Extended Data Fig. 7 Genome-wide distribution patterns of species (blue) and introgression (red) locus trees in laurasiatherian mammals with rearranged X chromosomes.

a, Genome-wide distributions of the species tree and introgression-associated tree. Note the enrichment of the species tree on the X.b, SVbyEye76 plots detail which parts of the rearranged X chromosomes ofMyotis andBos are syntenic to the human XLRD. Despite rearrangement, regions syntenic to the human XLRD coincide with peaks of species tree frequency.

Extended Data Fig. 9 Functional components of a speciation supergene.

a, An ideogram of the human X chromosome showing the locations of major evolutionary strata in mammals: the X-added region, and the X-conserved region. The positions of X chromosome inactivation (XCI; female-specific) and meiotic sex chromosome inactivation (MSCI; male-specific) expressed components are indicated below the ideogram43. The locations of significant loci from a male-specific testosterone GWAS are shown relative to the XLRD. The distribution and density of genes associated with ovary- and testis-biased gene expression are also displayed relative to the XLRD. Genes with biased expression in the ovaries are significantly enriched inside of the XLRD (chi-squared = 3.92,p-value = 0.048). Ampliconic genes are clustered within the XLRD compared to the whole X chromosome: a, human (53%),b, cat (87%), and pig (79%). Testis-specific ampliconic genes in cats (chi-squared = 36.11,p-value < 0.00001) and pigs (chi-squared = 19.66,p-value < 0.00001) are significantly enriched in the XLRD at α = 0.05.

Extended Data Table 1 Previous phylogenomic and population genomic studies that identified introgression

Supplementary information

Supplementary Information

Supplementary Figs. 1–42 and Tables 1–10.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Foley, N.M., Rasulis, R.G., Wani, Z.et al. An ancient recombination desert is a speciation supergene in placental mammals.Nature (2025). https://doi.org/10.1038/s41586-025-09740-2

Download citation

Access through your institution
Buy or subscribe

Advertisement

Search

Advanced search

Quick links

Nature Briefing

Sign up for theNature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox.Sign up for Nature Briefing

[8]ページ先頭

©2009-2025 Movatter.jp