Abstract
Introgression can be an important source of new alleles for adaption under rapidly changing environments, perhaps even more important than standing variation. Though introgression has been extensively studied in many plants and animals, key questions on the underlying mechanisms of introgression still remain unanswered. In particular, we are yet to determine the genomic distribution of introgressed regions along the genome; whether the extent and patterns of introgression are influenced by ecological factors; and when and how introgression contributes to adaptation. Here, we generated high-quality genomic resources for two sympatric widespread Asian oak species, Quercus acutissima and Q. variabilis, sampled in multiple forests to study introgression between them. We show that introgressed regions are broadly distributed across the genome. Introgression was affected by genetic divergence between pairs of populations and by the similarity of the environments in which they live—populations occupying similar ecological sites tended to share the same introgressed regions. Introgressed genomic footprints of adaptation were preferentially located in regions with suppressed recombination rate. Introgression probably confers adaptation in these oak populations by introducing allelic variation in cis-regulatory elements, in particular through transposable element insertions, thereby altering the regulation of genes related to stress. Our results provide new avenues of research for uncovering mechanisms of adaptation due to hybridization in sympatric species.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Genomic evidence reveals high genetic diversity in a narrowly distributed species and natural hybridization risk with a widespread species in the genus Geodorum
BMC Plant Biology Open Access 14 June 2023
-
Haplotype-resolved genome assembly of Coriaria nepalensis a non-legume nitrogen-fixing shrub
Scientific Data Open Access 09 May 2023
-
Abiotic factors predict taxonomic composition and genetic admixture in populations of hybridizing white oak species (Quercus sect. Quercus) on regional scale
Tree Genetics & Genomes Open Access 05 April 2023
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout




Data availability
All sequencing data used in this study have been deposited in NCBI SRA database with the Bioproject number PRJNA763710 for the reference genome, PRJNA765790 for population resequencing libraries and PRJNA762601 for the RNA-seq libraries. The reference genome and gene annotations have also been deposited in the Genome Warehouse in National Genomics Data Center (https://ngdc.cncb.ac.cn/gwh) under the accession number GWHBGBO00000000. Figures 1–4 have associated source data at https://github.com/cjevol/protocols-for-introgression-in-oaks. There are no restrictions on data availability.
Code availability
All codes used for main analyses in this paper are available for download from https://github.com/cjevol/protocols-for-introgression-in-oaks and zenodo (https://doi.org/10.5281/zenodo.5726659).
References
Suarez-Gonzalez, A. et al. Introgression from Populus balsamifera underlies adaptively significant variation and range boundaries in P. trichocarpa. New Phytol. 217, 416–427 (2018).
Mallet, J. Hybridization as an invasion of the genome. Trends Ecol. Evol. 20, 229–237 (2005).
Harrison, R. G. & Larson, E. L. Hybridization, introgression, and the nature of species boundaries. J. Hered. 105, 795–809 (2014).
Anderson, E. Introgressive Hybridization (John Wiley, 1949).
Hedrick, P. W. Adaptive introgression in animals: examples and comparison to new mutation and standing variation as sources of adaptive variation. Mol. Ecol. 22, 4606–4618 (2013).
Edelman, N. B. et al. Genomic architecture and introgression shape a butterfly radiation. Science 366, 594–599 (2019).
Dasmahapatra, K. K. et al. Butterfly genome reveals promiscuous exchange of mimicry adaptations among species. Nature 487, 94–98 (2012).
Soltis, P. S. in Encyclopedia of Biodiversity 2nd edn (ed. Levin, S. A.)166–176 (Academic Press, 2013).
Mallet, J. Hybrid speciation. Nature 446, 279–283 (2007).
Grant, V. Plant Speciation (Columbia Univ. Press, 1981).
Burgarella, C. et al. Adaptive introgression: an untapped evolutionary mechanism for crop adaptation. Front. Plant Sci. 10, 4 (2019).
Janzen, G. M., Wang, L. & Hufford, M. B. The extent of adaptive wild introgression in crops. New Phytol. 221, 1279–1288 (2019).
Calfee, E. et al. Selective sorting of ancestral introgression in maize and teosinte along an elevational cline. PLoS Genet. 17, e1009810 (2021).
Janke, A. Divergence with Genetic Exchange.—M. L. Arnold. Syst. Biol. 65, 941–942 (2016).
Edelman, N. B. & Mallet, J. Prevalence and adaptive impact of introgression. Annu. Rev. Genet. 55, 265–283 (2021).
Yeaman, S. & Whitlock, M. C. The genetic architecture of adaptation under migration–selection balance. Evolution 65, 1897–1911 (2011).
Hamala, T. & Savolainen, O. Genomic patterns of local adaptation under gene flow in Arabidopsis lyrata. Mol. Biol. Evol. 36, 2557–2571 (2019).
Leroy, T. et al. Adaptive introgression as a driver of local adaptation to climate in European white oaks. New Phytol. 226, 1171–1182 (2020).
Gower, G. et al. Detecting adaptive introgression in human evolution using convolutional neural networks. eLife 10, e64669 (2021).
Jones, M. R. et al. The origin and spread of locally adaptive seasonal camouflage in snowshoe hares. Am. Nat. 196, 316–332 (2020).
Kim, M. S. et al. The patterns of deleterious mutations during the domestication of soybean. Nat. Commun. 12, 97 (2021).
Weiss, C. V. et al. The cis-regulatory effects of modern human-specific variants. eLife 10, e63713 (2021).
Kim, M. et al. Regulatory genes control a key morphological and ecological trait transferred between species. Science 322, 1116–1119 (2008).
Plomion, C. et al. Oak genome reveals facets of long lifespan. Nat. Plants 4, 440–452 (2018).
Kremer, A. & Hipp, A. L. Oaks: an evolutionary success story. New Phytol. 226, 987–1011 (2020).
Hipp, A. L. et al. Genomic identity of white oak species in an Eastern North American syngameon. Ann. Missouri Bot. Gard. 104, 455–477 (2019).
Li, X. et al. Hybridization and introgression in sympatric and allopatric populations of four oak species. BMC Plant Biol. 21, 266 (2021).
Chin, C. S. et al. Phased diploid genome assembly with single-molecule real-time sequencing. Nat. Methods 13, 1050–1054 (2016).
Chin, C. S. et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods 10, 563–569 (2013).
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).
Adey, A. et al. In vitro, long-range sequence information for de novo genome assembly via transposase contiguity. Genome Res. 24, 2041–2049 (2014).
Burton, J. N. et al. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nat. Biotechnol. 31, 1119–1125 (2013).
Parra, G., Bradnam, K. & Korf, I. CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics 23, 1061–1067 (2007).
Currat, M. et al. The hidden side of invasions: massive introgression by local genes. Evolution 62, 1908–1920 (2008).
Excofffier, L. et al. fastsimcoal2: demographic inference under complex evolutionary scenarios. Bioinformatics 37, 4882–4885 (2021).
Martin, S. H. et al. Genome-wide evidence for speciation with gene flow in Heliconius butterflies. Genome Res. 23, 1817–1828 (2013).
Torres-Ruiz, J. M. et al. Genetic differentiation in functional traits among European sessile oak populations. Tree Physiol. 39, 1736–1749 (2019).
Godbout, J., Yeh, F. C. & Bousquet, J. Large-scale asymmetric introgression of cytoplasmic DNA reveals Holocene range displacement in a North American boreal pine complex. Ecol. Evol. 2, 1853–1866 (2012).
Sella, G. et al. Pervasive natural selection in the Drosophila genome?. PLoS Genetics 5, e1000495 (2009).
Murphy, D. et al. Broad-scale variation in human genetic diversity levels is predicted by purifying selection on coding and non-coding elements. Preprint at bioRxiv https://doi.org/10.1101/2021.07.02.450762 (2021).
Chen, J. et al. What does the distribution of fitness effects of new mutations reflect? Insights from plants. New Phytol. 233, 1613–1619 (2022).
Martin, S. H. et al. Recombination rate variation shapes barriers to introgression across butterfly genomes. PLoS Biol. https://doi.org/10.1371/journal.pbio.2006288 (2019).
Dreissig, S. et al. Natural variation in meiotic recombination rate shapes introgression patterns in intraspecific hybrids between wild and domesticated barley. New Phytol. 228, 1852–1863 (2020).
Finnegan, D. J. Eukaryotic transposable elements and genome evolution. Trends Genet. 5, 103–107 (1989).
Mcdonald, J. F. Evolution and consequences of transposable elements. Curr. Opin. Genet. Dev. 3, 855–864 (1993).
Klein, S. J. & O’Neill, R. J. Transposable elements: genome innovation, chromosome diversity, and centromere conflict. Chromosome Res. 26, 5–23 (2018).
Kirkpatrick, M. How and why chromosome inversions evolve. PLoS Biol. 8, e1000501 (2010).
Hirsch, C. D. & Springer, N. M. Transposable element influences on gene expression in plants. Biochim. Biophys.Acta Gene Regul. Mech. 1860, 157–165 (2017).
Negi, P., Rai, A. N. & Suprasanna, P. Moving through the stressed genome: emerging regulatory roles for transposons in plant stress response. Front. Plant Sci. 7, 1448 (2016).
Lu, Z. F. et al. The prevalence, evolution and chromatin signatures of plant regulatory elements. Nat. Plants 5, 1250–1259 (2019).
Noshay, J. M. et al. Cis-regulatory elements within TEs can influence expression of nearby maize genes. Preprint at bioRxiv https://www.biorxiv.org/content/https://doi.org/10.1101/2020.05.20.107169 (2020).
Benoit, M. et al. Environmental and epigenetic regulation of Rider retrotransposons in tomato. PLoS Genet. 15, e1008370 (2019).
Vickrey, A. I. et al. Introgression of regulatory alleles and a missense coding mutation drive plumage pattern diversity in the rock pigeon. eLife 7, e34803 (2018).
Dannemann, M., Prufer, K. & Kelso, J. Functional implications of Neandertal introgression in modern humans. Genome Biol. 18, 61 (2017).
Silvert, M., Quintana-Murci, L. & Rotival, M. Impact and evolutionary determinants of Neanderthal introgression on transcriptional and post-transcriptional regulation. Am. J. Hum. Genet. 104, 1241–1250 (2019).
King, M.-C. & Wilson, A. C. Evolution at two levels in humans and chimpanzees. Science 188, 107–116 (1975).
Fraser, H. B. Gene expression drives local adaptation in humans. Genome Res. 23, 1089–1096 (2013).
Kita, R. & Fraser, H. B. Local adaptation of sun-exposure-dependent gene expression regulation in human skin. PLoS Genet. 12, e1006382 (2016).
Gould, B. A., Chen, Y. & Lowry, D. B. Gene regulatory divergence between locally adapted ecotypes in their native habitats. Mol. Ecol. 27, 4174–4188 (2018).
Qiu, Y. C. & Kohler, C. Mobility connects: transposable elements wire new transcriptional networks by transferring transcription factor binding motifs. Biochem. Soc. Trans. 48, 1005–1017 (2020).
Makarevitch, I. et al. Transposable elements contribute to activation of maize genes in response to abiotic stress. PLoS Genet. 11, e1004915 (2015).
Hiroki, S. & Kamiya, T. Discrimination of hybrids between Quercus variabilis and Q. acutissima by using stellate hairs, and analysis of the hybridization zone in the Chubu District of central Japan. J. Phytogeogr. Taxon. 53, 145–152 (2005).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://doi.org/10.48550/arXiv.1303.3997 (2013).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
McKenna, A. et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Linck, E. & Battey, C. J. Minor allele frequency thresholds strongly affect population structure inference with genomic data sets. Mol. Ecol. Resour. 19, 639–647 (2019).
Browning, B. L., Zhou, Y. & Browning, S. R. A one-penny imputed genome from next-generation reference panels. Am. J. Hum. Genet. 103, 338–348 (2018).
Quick, C. et al. emeraLD: rapid linkage disequilibrium estimation with massive datasets. Bioinformatics 35, 164–166 (2019).
Gao, F. et al. New software for the fast estimation of population recombination rates (FastEPRR) in the genomic era. Genes Genomes Genet. 6, 1563–1571 (2016).
Rausch, T. et al. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28, I333–I339 (2012).
Nguyen, L.-T. et al. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2014).
Diaz-Papkovich, A. et al. UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts. PLoS Genet. 15, e1008432 (2019).
Alexander, D. H., Novembre, J. & Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 19, 1655–1664 (2009).
Keightley, P. D. & Jackson, B. C. Inferring the probability of the derived vs. the ancestral allelic state at a polymorphic site. Genetics 209, 897–906 (2018).
Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).
Durand, E. Y. et al. Testing for ancient admixture between closely related populations. Mol. Biol. Evol. 28, 2239–2252 (2011).
Martin, S. H., Davey, J. W. & Jiggins, C. D. Evaluating the use of ABBA-BABA statistics to locate introgressed loci. Mol. Biol. Evol. 32, 244–257 (2015).
Reich, D. et al. Reconstructing Indian population history. Nature 461, 489–494 (2009).
Zhang, W. et al. Genome-wide introgression among distantly related Heliconius butterfly species. Genome Biol. 17, 25 (2016).
Malinsky, M., Matschiner, M. & Svardal, H. Dsuite—Fast D-statistics and related admixture evidence from VCF files. Mol. Ecol. Resour. 21, 584–595 (2021).
Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).
Gautier, M. Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201, 1555–1579 (2015).
Olazcuaga, L. et al. A whole-genome scan for association with invasion success in the fruit fly Drosophila suzukii using contrasts of allele frequencies corrected for population structure. Mol. Biol. Evol. 37, 2369–2385 (2020).
Higo, K. et al. Plant cis-acting regulatory DNA elements (PLACE) database: 1999. Nucleic Acids Res. 27, 297–300 (1999).
Wu, T. D. & Watanabe, C. K. GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics 21, 1859–1875 (2005).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Mi, H. Y. et al. Large-scale gene function analysis with the PANTHER classification system. Nat. Protoc. 8, 1551–1566 (2013).
Acknowledgements
This project was supported by National Natural Science Foundation of China (31972946) and the Fundamental Research Funds for the Central Universities 2-2050205-21-688 granted to J.C.
Author information
Authors and Affiliations
Contributions
J.C. conceived the research. All analyses were performed by R.F., with contributions to chromosome inversion analysis and gene expression analysis from Y.Z. and Y. Liu, respectively. Y.Z., Y.F., R.-S.L., Y. Li. and P.L. contributed plant material collection. R.F., J.C., A.K. and M.L. wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Ecology & Evolution thanks the anonymous reviewers 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
Extended Data Fig. 1
Admixture plots with K values from 2 to 4.
Extended Data Fig. 2 The correlation between environmental distance and geographic distance.
Shaded areas represent 95% confidence intervals. Each dot represents one population pairs. Statistical significance was determined by Mantel test based on Pearson’s product-moment correlation with two-sided and multiple comparisons was performed. Adjusted R2 and significance of the correlation (p-value) are shown for plot.
Extended Data Fig. 3 FST distribution for allopatric (red) and sympatric (blue) Q. acutissima -Q. variabilis pairs examined in ABBA analyses.
Populations were labelled in ((P1, P2), P3) order. Significance shows introgression has lowered the genetic divergence between sympatric species. Statistical significance was determined by T-test with two-sided and multiple comparisons was performed (p-values: * ≤ 0.05, **≤ 0.01, ***≤ 0.001, **** ≤ 0.0001). Specifically, Adjusted P-values = 8.9E-249, 1.9E-134, 4.6E-249, 1.1E-128, 0, 0.58, 1.1E-4, 0, 4.1E-5, 0 from BWL_KYS_KY to LFS_TBS_TB, respectively. The box plots were based on n=72,866 sliding windows for all Q. acutissima -Q. variabilis pairs (from BWL_KYS_KY to LFS_TBS_TB). The central lines, box limits, whiskers and the top and bottom ends show the median values, upper and lower quartiles, 1.5× the interquartile ranges, and the maximum and minimum values, respectively.
Extended Data Fig. 4
The distribution of population recombination rate (rho = 4Ner) for all chromosomes.
Extended Data Fig. 5
The cross-validation errors against K values in Admixture analysis.
Extended Data Fig. 6 The comparison of FST matrix and covariance matrix for Q. acutissima.
FST matrix of Q. acutissima populations (left) and the covariance matrix of Q. acutissima populations (right).
Supplementary information
Supplementary Information
Supplementary Methods, Results and Figs. 1–9.
Supplementary Tables
Supplementary Tables 1–18.
Rights and permissions
About this article
Cite this article
Fu, R., Zhu, Y., Liu, Y. et al. Genome-wide analyses of introgression between two sympatric Asian oak species. Nat Ecol Evol 6, 924–935 (2022). https://doi.org/10.1038/s41559-022-01754-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41559-022-01754-7
This article is cited by
-
Genomic evidence reveals high genetic diversity in a narrowly distributed species and natural hybridization risk with a widespread species in the genus Geodorum
BMC Plant Biology (2023)
-
Haplotype-resolved genome assembly of Coriaria nepalensis a non-legume nitrogen-fixing shrub
Scientific Data (2023)
-
Abiotic factors predict taxonomic composition and genetic admixture in populations of hybridizing white oak species (Quercus sect. Quercus) on regional scale
Tree Genetics & Genomes (2023)