Allopatric speciation in cattails: Genomics reveal bottlenecks, balancing selection, and adaptive introgressions in Typha, a wetland ecosystem engineer

Allopatric speciation in cattails: Genomics reveal bottlenecks, balancing selection, and adaptive introgressions in Typha, a wetland ecosystem engineer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Allopatric speciation in cattails: Genomics reveal bottlenecks, balancing selection, and adaptive introgressions in Typha , a wetland ecosystem engineer Alberto Aleman, Aaron Shafer, Joanna R Freeland, Marcel Dorken This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6778557/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Speciation can be broadly understood within two non-mutually exclusive frameworks: genetic drift under isolation and natural selection under ecological divergence. Here, we examined the genomic diversity and differentiation of five Typha species, a group of plants foundational to freshwaters with widespread, partially sympatric distributions and at least one widespread hybrid zone. Using genome-wide data from 207 individuals, we examined the contributions of demographic fluctuations, selection, and hybridisation in driving their speciation history. Demographic reconstructions revealed sequential bottlenecks and expansions coincident with lineage splits, and indicated a drift-driven scenario with no migration events for all five species. The genomic landscapes showed balancing selection, sparse divergent selection, and low net divergence. Introgressions from T. latifolia to T. angustifolia and T. domingensis were found. Our findings suggest histories of allopatric speciation followed by range expansions and secondary contacts, leading to contemporary hybridisation between some species. Our results also emphasise the roles of balancing selection and introgression as sources of standing genetic variation. Allopatric speciation in T. latifolia and T. angustifolia could explain their ability to hybridise, highlighting the need to stop the human-mediated dispersal of Typha (e.g., the intercontinental sourcing via garden centres). Biological sciences/Genetics/Population genetics/Genetic variation Biological sciences/Evolution/Population genetics climate‐driven barriers divergence drift evolutionary history genomic landscapes hybridisation secondary contact Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Speciation can follow two non-mutually exclusive pathways: geographic isolation (“allopatric speciation”) and natural selection (“ecological speciation”) (Stankowski and Ravinet, 2021). In isolation, divergence is primarily driven by genetic drift (Mayr et al. , 1963), and although local adaptations occur, they are not assumed to be the driving force underlying species formation (Hernández-Hernández et al. , 2021). Conversely, divergent selection is mandatory during ecological speciation (Pinho and Hey, 2010; Nosil, 2012). Understanding how these pathways lead to lineages diverging is key to speciation genomics and can help us characterise how biological diversity originates (Seehausen et al. , 2014). Global climatic oscillations have repeatedly shaped species’ ranges and population sizes, triggering isolation and providing opportunities for allopatric divergence (Hewitt, 2000). These fluctuations include the rapid transformations of the Neogene (Andersson, 2009) and the glacial cycles of the Quaternary, which promoted speciation through drift events (e.g., Chacón et al. , 2019; Kong et al. , 2022; Dagallier et al. , 2024). Drift-driven speciation can be linked to sharp changes in species’ past demographic sizes (Bock et al. , 2023) and is the most common cause of divergence in plants (Hernández-Hernández et al. , 2021). In contrast, natural selection promotes ecological divergence by fixing beneficial alleles and purging deleterious ones (Schluter, 2001). Under this model, speciation leads to the emergence of “genomic landscapes” (Wolf and Ellegren, 2017). These landscapes are highly differentiated (“islands”) or conserved (“valleys”) genomic regions along (or linked to) loci associated with natural selection and reproductive isolation (Ravinet et al. , 2017). Reconstructing these landscapes can be used to identify the contributions of natural selection to speciation (Andrew and Rieseberg, 2013; Ravinet et al. , 2017; Han et al. , 2017; Irwin et al. , 2018; Ottenburghs et al. , 2020; Kessler et al. , 2023; Shang et al. , 2023). Gene flow plays an important role in speciation (Feder et al. , 2012; Tigano and Friesen, 2016). The restriction of gene flow, through allopatry or natural selection, permits genetic differentiation and the formation of distinct lineages (Morjan and Rieseberg, 2004), whereas gene flow generally plays a homogenising role (Woodruff, 2001). However, gene flow between genetically distinct species (hybridisation) has diverse outcomes (Harrison and Larson, 2014; Taylor and Larson, 2019). Hybridisation can cause the formation of new species, the extinction of parental taxa through genetic swamping, or the reinforcement of species’ boundaries (Noor, 1999; Garner et al. , 2018; Runemark et al. , 2019). In stable hybrid zones, hybridisation can cause introgressions (the movement of genes from one species to another), promoting adaptation when introgressed loci provide higher fitness (Whitney et al. , 2010; Suarez-Gonzalez, Lexer, et al. , 2018; Leroy et al. , 2020; Rendón-Anaya et al. , 2021). Cattails ( Typha ) are rhizomatous perennial, monoecious, self-compatible, and wind-pollinated plants crucial to freshwater and brackish ecosystems; they play a vital ecological role in cycling nutrients, preventing erosion, maintaining water levels, and providing food and shelter for amphibians, birds, fish, insects, and mammals (Bonanno and Cirelli, 2017; Bansal et al. , 2019; Svedarsky et al. , 2019). The three most widespread Typha spp. ( T. angustifolia L., T. domingensis Pers., and T. latifolia L.) have extensive areas of sympatry and allopatry (Figure 1) and are capable of hybridising (Smith, 1967). Typha angustifolia and T. latifolia share a widespread hybrid zone in North America involving the highly impactful invasive T. × glauca, which forms dense stands, altering habitats and outcompeting and displacing native plants (reviewed in Bansal et al. , 2019). Here, we examined the genomic diversity and differentiation of five cattail species to evaluate the role of drift, selection, and hybridisation in their speciation history. These comprised T. angustifolia , T. domingensis , and T. latifolia ; we also included two closely related Typha , T. laxmannii Lepech. and T. shuttleworthii W. D. J. Koch and Sond (Zhou et al. , 2018), which have more restricted ranges (Figure 1). The genomes of 207 plants sampled across multiple continents were sequenced to address the following questions: (1) What are the demographic histories and (2) levels of genetic diversity and divergence of these species? (3) How has selection shaped their genomic landscapes? (4) Has hybridisation led to (adaptive or non-adaptive) introgressions between T. angustifolia and T. latifolia ? Understanding how Typha species have diverged could provide important insights for wetland conservation. Speciation in allopatry (without developing reproductive genetic barriers) could help explain cattails’ ability to create invasive hybrids; this, in turn, could highlight potential risks associated with human-mediated dispersal, for example, intercontinental Typha sourcing by garden centres (Ciotir and Freeland, 2016). Materials and Methods Data preparation Sampling, DNA extraction, and sequencing Samples were obtained from a previous study (Aleman et al. , 2024) and supplemented with additional collections to increase taxonomic diversity and sampling range (Figure 1; Supplementary Table S1). Plants were identified beforehand using known morphological characteristics (Smith, 1967; Grace and Harrison, 1986) and/or a combination of three to four microsatellite loci (Ciotir et al. , 2013, 2017; Ciotir and Freeland, 2016; Tisshaw et al. , 2020; Pieper et al. , 2020; Bhargav et al. , 2022). DNA was extracted following published protocols (Pieper et al. , 2017, 2020) and then converted into Nextera XT libraries for reduced-representation genotyping-by-sequencing as per Aleman et al. (2024) (Supplementary information – Methods). Paired-end sequencing was conducted on a Miseq (151 bp) and a Novaseq 6000 (126 bp) at The Centre for Applied Genomics (Toronto, Ontario, Canada) for 64 T. angustifolia , 25 T. domingensis , 104 T. latifolia , 11 T. laxmannii , and 3 T. shuttleworthii . Raw data processing The quality of the demultiplexed raw sequences was evaluated using FastQC 0.11.9 (Andrews, 2017) and MultiQC 1.14 (Ewels et al. , 2016). Read pairing and adapter pruning were carried out with Trimmomatic 0.39 (Bolger et al. , 2014), removing cleaned reads shorter than 100 bp. All reads were mapped to the T. latifolia nuclear (15 chromosomes, 285.11 Mb, GenBank accession JAIOKV000000000.2) and chloroplast (161.57 kb, GenBank accession NC_013823) genomes with BWA 0.7.17 (Li and Durbin, 2009). Mapping statistics were evaluated using SAMtools 1.15.1 (Li et al. , 2009). Genotype-calling Genotype calling was performed through ANGSD 0.93 (Korneliussen et al. , 2014). Two datasets were created using all samples. SNPs were retrieved requiring a minimum mapping and Phred scores of 20 and a minimum p-value of 1e −6 (referred to as the SNP dataset ). Reconstructing the genomic landscape requires variant and invariant loci; hence, a dataset including SNPs and invariant sites (referred to as the all-sites dataset ) was created using the same mapping and Phred filters. SNPs with more than 20% missing data and sites mapped to the plastome were removed from the SNP dataset with VCFtools 0.1.16 (Danecek et al. , 2011). The plastome data were also removed from the all-sites dataset— for the coverage requirements in the all-sites dataset , see Role of selection and introgressive hybridisation on species’ divergence . No individuals were removed from any dataset. The absence of clones (multiple ramets from the same genet) was verified by calculating kinship coefficients with Plink 2.0 (Chang et al. , 2015)and the SNP dataset . Genetic structure and species’ demographic histories Two approaches were used to investigate the genetic structure and relationships among samples: (1) a principal component analysis (PCA; PC1 to PC3) and (2) a neighbour-joining (NJ) tree based on the samples’ pairwise distances (expressed as allele counts, transformed with the R 4.3.1 package ape 5.7-1 (Paradis and Schliep, 2019; R Core Team, 2022) were both produced with Plink 1.9 (Purcell et al. , 2007) and the SNP dataset . Species splits and migration events were inferred with TreeMix 1.13 (Pickrell and Pritchard, 2012) and the SNP dataset . This analysis tested migration events between 0 and 10, and the optimal number of migrations was chosen based on the data variance. Demographic fluctuations were reconstructed using a Stairway Plot 2.1.2 analysis (Liu and Fu, 2015, 2020), which generates estimates of N e over generations in the past. Using the SNP dataset , a folded site frequency spectrum (SFS) per species was produced in easysfs 0.0.1 (Gutenkunst et al. , 2009); given that intraspecific structure was observed in T. latifolia, distinguishing two lineages (“Eastern” and “Western”, see Results ), independent SFSs were produced for each of these lineages. The resultant SFSs and the mutation rate of Arabidopsis thaliana (7×10 -9 mutations per site per generation (Weng et al. , 2019)) were used as inputs for Stairway Plot. Role of selection and introgressive hybridisation on species’ divergence To estimate the genetic diversity within and divergence between species, F ST (Weir and Cockerham, 1984), d XY (Nei and Miller, 1990), and π (Nei and Li, 1979) were computed in 5 kb windows for all species pairs using pixy 1.2.7 (Korunes and Samuk, 2021) and the all-sites dataset . To ensure data reliability, windows with coverage below 50% (in each pairwise comparison) were discarded. The means for each statistic and the net divergence between species (d a ; Nei and Li (1979)) were calculated. To test the role of selection on species’ genetic differentiation, islands and valleys of divergence consistent with the alternative types of selection proposed by Irwin et al. (2018) were identified using the retained windows in each pairwise comparison (see above ). Individual F ST , d XY , and π values were standardised into Z-scores (e.g., ZF ST = [(window F ST – genome-wide median F ST ) / genome-wide F ST standard deviation] ), and windows with exceptionally high or low diversity and divergence were characterised by detecting outliers where the absolute value of a Z-score≥ 1.96; intermediate d XY values were also documented (Z-score between –0.1257 and 0.1257). Following Kessler et al. (2023) and Shang et al. (2023), islands and valleys of divergence (i.e., positive and negative F ST outliers) were classified into four models of selection using joint combinations of statistics as follows: (i) divergent with gene flow (high F ST and d XY , low π); (ii) divergent without gene flow (high F ST , intermediate d XY , and low π); (iii) background (high F ST , low d XY and π); and (iv) balancing (low F ST , high d XY and π). Additionally, Tajima’s D (Tajima, 1989) was estimated in 5 kb windows for each species using VCFtools and the all-sites dataset . Within each species, only those windows with more than 50 SNPs were kept, and loci with Tajima’s D higher than +2 or lower than –2 were interpreted as experiencing balancing selection and selective sweeps, respectively. ABBA BABA was used to identify introgressions; T. laxmannii was designated as outgroup, and all possible combinations of donor and recipient species were examined (Supplementary Table S2). The script ABBABABAwindows.py (Martin and Jiggins, 2017) was used to compute f d (Martin et al. , 2015) in 5 kb windows. Two or more loci with a positive f d , ZF ST and Zd XY ≤–1.96, and at least within 50 kb of each other, were classified as introgressions. Introgressions from T. latifolia to T. angustifolia were observed (see Results ); thus, ABBA BABA was replicated, splitting data into “North America” and “Europe” to test whether introgressions occur on both continents. Results Genetic structure and species’ demographic histories We assembled 21,759,123 nuclear SNPs across 207 samples and kept 77,207 with missing data below 20%. The PCA (PC1 to PC3, Supplementary Figure S1) and NJ tree (Figure 2) distinguished all five species; the NJ tree also revealed intraspecific structure in T. latifolia distinguishing two lineages, named “Western” (n = 77; North America, Western and Central Europe) and “Eastern” (n = 27; Eastern Europe and the Iturup Island in the Russian Kuril Chain). TreeMix indicated T. angustifolia – T. domingensis and T. latifolia – T. shuttleworthii as sister lineages, and T. laxmannii as outgroup species (Figure 1); this topology was consistent with the NJ tree. The most likely number of gene flow events was determined to be zero, explaining over 99.9% of the data variance. Typha laxmannii , inferred by Treemix to be the oldest species, exhibited a stable N e from ~18 million to ~5 million generations ago, when a sharp decline appeared to coincide with sharp expansions for T. angustifolia and T. domingensis . Another sharp decline for T. laxmannii appeared to coincide with a sharp expansion ~3 million generations ago for Eastern T. latifolia . Western T. latifolia appeared to experience a cycle of expansion-decline-expansion between ~2 million and ~400,000 generations ago; finally, T. shuttleworthii appeared to undergo a sharp expansion ~1 million generations ago. The series of sharp declines and expansions inferred by Stairway Plot overlapped with the order of species splits revealed by Treemix; moreover, assuming a ~2-year generation time, this series of events coincides with the divergence times of T. angustifolia – T. domingensis and T. latifolia – T. shuttleworthii in the literature (Figure 3 ; see Discussion ). Role of selection and introgressive hybridisation on species’ divergence Covering 65% of the genome (variant and invariant sites, depth = 4×), mean F ST varied from 0.317 ( T. angustifolia – T. domingensis ) to 0.617 ( T. latifolia – T. laxmannii ), d XY from 0.016 ( T. latifolia – T. shuttleworthii ) to 0.030 ( T. domingensis – T. shuttleworthii ), π from 0.005 ( T. latifolia ) to 0.024 ( T. domingensis ), and d a from 0.007 ( T. latifolia – T. shuttleworthii ) to 0.015 ( T. latifolia – T. angustifolia ) (Table 1; Figure 2). Typha latifolia was the only species with low diversity (π < 0.01). The net divergence among the five species was low (d a <0.02). The genomic landscapes between species pairs showed a heterogeneous role of selection on species’ differentiation (Supplementary Figures S3 to S12). Most loci (5 kb) with exceptionally high or low F ST could not be associated with any of the types of selection tested (on average, 1398 out of 1839; Table 2). On average, from the 441 loci that could be associated with selection, balancing selection was the most frequently detected in pairwise comparisons (375 loci, 0.66% of the genome); background selection was the second (46 loci, 0.08% of the genome), followed by selection without and with gene flow (15 and 6 loci – 0.03%, and 0.01% of the genome, respectively). A prominent island of background selection was observed between T. laxmannii and most species in our study (~350 kb, chromosome 14); no genes could be identified in this island. Except for T. latifolia , all species had mean positive Tajima’s D per species, from 0.05 ( T. angustifolia ) to 1.55 ( T . laxmannii ) (Figure 4) and more loci with values higher than +2 (~8,129) vs lower than –2 (~43), consistent with the widespread balancing selection observed across the genomic landscapes; T. shuttleworthii had no loci with values higher than 2 a mean Tajima’s D of 0.66, T. domingensis mean was 1.14; T. latifolia had a mean negative Tajima’s D (–1.27) and a large number of windows lower than –2 (12,252), in line with the most recent expansion observed in its demographic history. The f d identified introgressions from T. latifolia to T. angustifolia on chromosomes 11 and 14 (~145 kb); no genes could be identified in these introgressions. The introgressed regions exhibited values of Tajima’s D from –0.77 to –1.96, suggesting positive selection. Splitting the data by continent confirmed that these introgressions are found in North America and Europe (Supplementary Figures S13 and S14). Additional introgressions from T. latifolia to T. domingensis were identified in chromosomes 8, 14, and 15; no genes were found in these introgressions, and their Tajima’s D values ranged from –0.004 to –1.73. Discussion During allopatric speciation, genetic divergence primarily accumulates through drift (Abbott et al. , 2013); in contrast, ecological (sympatric) speciation requires divergent selection (Rundle and Nosil, 2005; Nosil, 2012). This means that ecological speciation should produce stronger reproductive barriers than geographic isolation, and that speciation in isolation could enable hybridisation if species experience secondary contact (Hewitt, 2000; Rheindt and Edwards, 2011; Sobel, 2016)—although the later development of genetic barriers between species (e.g., through reinforcement (Noor, 1999)) would depend on their history after secondary contact and hybridisation occur (Runemark et al. , 2019; Moran et al. , 2021). Here, we examined the genomic diversity and differentiation of five cattail species to evaluate the role of drift, selection, and hybridisation in their speciation history. We revealed (1) species splits (without migration events) coincident with past sharp demographic declines, (2) low net genomic divergence between species (d a from 0.007 to 0.015), (3) predominant valleys of balancing selection between species, and (4) introgressions from T. latifolia to T. angustifolia— both in North America and Europe, despite the absence of hybrids in the latter—and T. domingensis . Our results suggest that demographic contractions are the primary factor responsible for the speciation of these Typha , possibly followed by range expansions and secondary contact, enabling hybridisation between some species. Demographic history and scarcity of divergent selection in Typha Treemix reported a topology with no migration events, indicating that species split events without gene flow events can account for all the observed genetic variation among the species in our study. While it does not rule out the possibility of hybridisation after secondary contact, this result suggests that genetic drift—without gene flow—was the primary driver of differentiation among the species in this study. Stairway Plot revealed a series of sharp N e declines and expansions that coincide chronologically with the Treemix topology and the divergence times of Zhou et al. (2018). Geoclimatic events, including the Miocene aridification and the Quaternary glacial cycles (Hewitt, 2000; Herbert et al. , 2016; Butiseacă et al. , 2021), could have led to these bottlenecks, both periods potentially fragmenting the extent and connectivity of wetland habitats. These reductions in N e likely reflect episodes of geographic isolation that triggered species divergence via genetic drift. Stairway Plot also indicated that T. latifolia possibly underwent an expansion-decline-expansion cycle between ~2 million and ~400,000 generations ago, which is in line with the genome-wide negative Tajima’s D (–1.765) in this species. The islands and valleys of divergence associated with divergent selection were scarce, occurring on average in 0.12% of the genome and 2.88% of the loci with exceptionally high or low F ST in pairwise comparisons. This result suggests a negligible role of ecological divergence in the speciation of the Typha in this study. Some signatures of divergent due to selection could have been eroded by time and recombination, which is consistent with the late stages of speciation (Burri et al. , 2015)— the age of Typha is estimated between 20 and 70 Ma (Zhou et al. , 2018; Widanagama et al. , 2022)—however, the net divergence (d a ) among these Typha species is low ( 0.25 (Wright, 1984)) between species. Balancing selection and introgressions as sources of genetic variation Standing genetic variation can be as important as mutations to adaptation (Barrett and Schluter, 2008; Matuszewski et al. , 2015). Several mechanisms maintain standing genetic variation, including balancing selection (Llaurens et al. , 2017; Fijarczyk et al. , 2018). Across the genomic landscapes of the species in our study, most regions associated with adaptive divergence were valleys of balancing selection—as confirmed by Tajima’s D results—in which the maintenance of standing polymorphisms causes an excessively reduced divergence (Guerrero and Hahn, 2017). Signatures of balancing selection are congruent with Typha spp. ability to self-fertilise; selfing leads to increased homozygosity, so balancing selection can be crucial in preserving polymorphism at important loci (Glémin, 2021). Genes experiencing balancing selection have been shown to underlie a wide range of phenotypes (Isildak et al. , 2021; Promy et al. , 2023) and promote adaptation to divergent habitats (Delph and Kelly, 2014; Wu et al. , 2017). A predominant role of balancing selection has been detected among other widespread plants, including Arabidopsis , Arbutus , Capsella , Populus ,and Quercus (Santiso et al. , 2016; Meireles et al. , 2017; Wu et al. , 2017; Bachmann et al. , 2018; Koenig et al. , 2019; Wang et al. , 2019, 2020; Rendón-Anaya et al. , 2019; Le Veve et al. , 2023; Shang et al. , 2023). The growing evidence supporting a prominent role of balancing selection (Delph and Kelly, 2014; Fijarczyk and Babik, 2015; Guerrero and Hahn, 2017; Llaurens et al. , 2017; Thorburn et al. , 2022; Kessler et al. , 2023) challenges the view of background selection being the leading force shaping species’ genetic diversity (Comeron, 2017). Introgressive hybridisation is another important source of standing genetic variation (Tigano and Friesen, 2016; Suarez-Gonzalez, Lexer, et al. , 2018). Research on the T. × glauca hybrid swarm in North America has demonstrated the fertility of F1 hybrids in natural populations (Grace and Harrison, 1986; Snow et al. , 2010; Travis et al. , 2010; Kirk et al. , 2011) and their ability to backcross (Pieper et al. , 2017; Bhargav et al. , 2022). Under these circumstances, introgressions between T. latifolia and T. angustifolia could be expected, and those identified might be under positive selection. Introgressions were also present in Europe, where these species do not currently hybridise (Ciotir et al. , 2017)—suggesting that hybridisation between these species could have happened in the past. Introgressions have been documented in other widespread plants, including Helianthus (Kim and Rieseberg, 1999; Whitney et al. , 2006, 2010), Populus (Suarez-Gonzalez, Hefer, et al. , 2018; Rendón-Anaya et al. , 2021), and Quercus (Goicoechea et al. , 2019; Leroy et al. , 2020; Li et al. , 2021),and are recognised as essential sources of genetic variation for adaptation. Genetic diversity in Typha Genetic diversity reflects the reservoir of traits and potential responses to environmental changes that species encounter, thereby influencing their resilience in different ecosystems (Gregorius, 1987; Frankham et al. , 2002; Hartl and Clark, 2006). Excluding T. latifolia , species’ genetic diversity was high (π > 0.01 (Begun et al. , 2007)), consistent with large population sizes and substantial gene flow. Low genetic diversity is often considered detrimental, as it can reflect a reduced adaptive potential (Teixeira and Huber, 2021; Kardos et al. , 2021). However, some species—including invasive species—thrive despite having low genetic diversity (Tsutsui et al. , 2000; Roman and Darling, 2007; Charlesworth and Jensen, 2022). Typha tolerates wide-ranging climates, nutrients, pHs, pollutants, and water levels (Sojda and Solberg, 1993; Kadlec and Wallace, 2008; Sesin et al. , 2021), and the most widespread and commonly recognised cattail species is T. latifolia , presumed to have large census sizes, and is considered invasive in Oceania (Xu et al. , 2013). Low genetic diversity in T. latifolia suggests that alternative mechanisms, such as epigenetic modifications and associated phenotypic plasticity, may be responsible for the success of this species (Mounger et al. , 2021). In Arabidopsis thaliana , epigenetic diversity underlies morphological variation and phenotypic plasticity when genetic diversity is low (Zhang et al. , 2013; Kooke et al. , 2015; Schmid et al. , 2018). An inquiry for future research is testing if epigenetic modifications and phenotypic plasticity are more extensive in T. latifolia than in other Typha species. Conclusions Understanding the causes of speciation is a central aspect of evolutionary biology. Here, we tested the roles of drift, selection, and hybridisation in driving species divergence in Typha , an old and widespread plant genus that is foundational to freshwater ecosystems. Our results support bottlenecks and geographic isolation as the primary causes of speciation, as well as widespread balancing selection across Typha , and introgressions from T. latifolia into T. angustifolia and T. domingensis . The absence of divergent selection does not rule out the role of ecological divergence as a promoter of speciation for the Typha in our study—this genic view of speciation requires only a handful of genes (Lexer and Widmer, 2008)—rather, it indicates a primary role of genetic drift. Our results add Typha to the body of evidence supporting an important role of balancing selection in preserving standing genetic variation despite the accumulation of divergence (e.g., Selechnik et al. , 2019). Declarations Acknowledgements We acknowledge that the laboratory procedures and data analyses were conducted at Trent University, which is on the traditional territory of the Mississauga Anishinaabeg, to whom we show our respect. We thank Polina A. Volkova and Tulsi Patel for their invaluable contributions to the laboratory and the field. The Natural Sciences and Engineering Research Council of Canada financially supported this work, and Alberto Aleman is funded by the Environmental and Life Sciences Graduate Program at Trent University. SHARCNET and Compute Canada provided computational resources for this study. We are grateful to Camille Kessler, Marie-Laurence Cossette, Beibei Zhou, Xinwei Xu, the Associate Editor, and the anonymous reviewers for their valuable feedback, which significantly improved the quality of this manuscript. Finally, we thank Enrique Ruiz for his work in Figure 1. Author contribution statement Conceptualisation, developing methods, conducting research, data interpretation, writing, data analysis, and preparation of figures and tables : Aaron Shafer, Alberto Aleman, Joanna Freeland, and Marcel Dorken. All authors contributed to the manuscript and approved its final version. Conflict of Interest The authors declare that they have no conflict of interest. Data archiving Data and scripts for this study can be found at https://gitlab.com/WiDGeT_TrentU/graduate_theses/-/tree/master/aleman/hdy and https://github.com/al-aleman/totoras_hdy. Raw sequencing data are available from the authors upon request. 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T. laxmannii T. domingensis T. angustifolia T. shuttleworthii T. latifolia T. laxmannii 0.029 0.028 0.024 0.023 T. domingensis 0.330 0.029 0.030 0.029 T. angustifolia 0.384 0.317 0.028 0.027 T. shuttleworthii 0.380 0.398 0.447 0.016 T. latifolia 0.617 0.614 0.575 0.544 Table 2. Number of genetic islands and valleys of divergence (5 kb) consistent with alternative types of selection between five Typha species: (i) divergent with gene flow, (ii) divergent without gene flow, (iii) background selection, (iv) balancing selection. The number of islands and valleys of divergence that could not be assigned to the alternative types of selection tested is shown in (v). (i) (ii) (iii) (iv) (v) T. angustifolia - T. domingensis 0 23 46 551 1384 T. angustifolia - T. latifolia 0 1 10 45 2169 T. angustifolia - T. laxmannii 0 18 82 585 996 T. angustifolia - T. shuttleworthii 0 15 99 468 1255 T. domingensis - T. latifolia 1 5 9 123 1932 T. domingensis - T. laxmannii 0 17 79 655 879 T. domingensis - T. shuttleworthii 0 5 81 574 1096 T. latifolia - T. laxmannii 15 19 7 124 1552 T. latifolia - T. shuttleworthii 42 27 1 29 1825 T. laxmannii - T. shuttleworthii 0 17 45 591 893 Additional Declarations There is no duality of interest Supplementary Files HDYSupplementaryMaterials.docx Supplementary Materials SupplementaryFiguresS3S14.pdf Supplementary Figures S3-S14 Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: revise 27 Aug, 2025 Review # 2 received at journal 02 Aug, 2025 Review # 3 received at journal 20 Jul, 2025 Reviewer # 3 agreed at journal 27 Jun, 2025 Review # 1 received at journal 24 Jun, 2025 Reviewer # 2 agreed at journal 16 Jun, 2025 Reviewer # 1 agreed at journal 11 Jun, 2025 Reviewers invited by journal 10 Jun, 2025 First submitted to journal 29 May, 2025 Editor assigned by journal 29 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6778557","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":463775395,"identity":"446cf3ae-b997-4e3e-ba88-75e95c75ce7b","order_by":0,"name":"Alberto Aleman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABJUlEQVRIiWNgGAWjYDACdh4wJQPhFYAI5gP4tTCDtCQwQDQyGIAItsQGIClBihYeQ7xa+Jt5Dz6u/GHDwy/dfPjDDwObaP7ZPd8fV1TcqTM4wPzwAxYtEof5kg3PJKTxSM45lmDYY5CWO+PO2Y2NZ848kzA4wGaM1arDPGaSDQmHeQxu5Bgk8Bgczm24kbuxsbHtMFALD1bXyR/mMf8J0ZL/4eAfg/+582/kPGxs/AfWwvwDixYDoC2MUFsYm3kMDuRuADIaGxvAWtiw2WII9ItkQxrYL8bMMgbJuRtvpBnObDh2WHLmYTYzCyxa5I73HvzYYGMjBwyxxx/fVNjlzruR/OBjQ81hfr7jzY9v4AppSNhhiDDjVY9VyygYBaNgFIwCCAAAThlpm4WcCBoAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0000-6236-6401","institution":"Trent University","correspondingAuthor":true,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Aleman","suffix":""},{"id":463775396,"identity":"13718abf-4057-4037-8335-a655d8eca4fe","order_by":1,"name":"Aaron Shafer","email":"","orcid":"https://orcid.org/0000-0001-7652-225X","institution":"Trent University","correspondingAuthor":false,"prefix":"","firstName":"Aaron","middleName":"","lastName":"Shafer","suffix":""},{"id":463775397,"identity":"79afdba9-babe-453a-958f-e79e52383143","order_by":2,"name":"Joanna R Freeland","email":"","orcid":"https://orcid.org/0000-0002-5251-7680","institution":"Trent University, Canada","correspondingAuthor":false,"prefix":"","firstName":"Joanna","middleName":"R","lastName":"Freeland","suffix":""},{"id":463775398,"identity":"7397b33f-32f1-4695-9443-dae91894ccb2","order_by":3,"name":"Marcel Dorken","email":"","orcid":"https://orcid.org/0000-0001-7400-5136","institution":"Trent University","correspondingAuthor":false,"prefix":"","firstName":"Marcel","middleName":"","lastName":"Dorken","suffix":""}],"badges":[],"createdAt":"2025-05-29 17:20:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6778557/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6778557/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83905391,"identity":"b6479047-c5d5-4d4f-842a-ec6ffaed6a24","added_by":"auto","created_at":"2025-06-04 10:11:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133325,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions (coloured grids) and sample sites (black and white circles) in this study for \u003cem\u003eT. angustifolia \u003c/em\u003e(a), \u003cem\u003eT. domingensis \u003c/em\u003e(b), \u003cem\u003eT. latifolia \u003c/em\u003e(c), \u003cem\u003eT. laxmannii \u003c/em\u003e(d), and \u003cem\u003eT. shuttleworthii \u003c/em\u003e(e). Distributions from Ciotir and Freeland (2016) and GBIF. Sample sizes are not represented graphically. (f) Species relationships inferred by Treemix; the maximum likelihood tree produced indicated zero migration events. The colour scheme represents species, as in the tree in (f). Note: Shading is based on maps that represent geopolitical boundaries of areas from which species have been recorded.\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/1ace05d0132070e25d745832.png"},{"id":83905392,"identity":"73a1c3d1-3e5a-4b2d-ae2c-038e7f336ec5","added_by":"auto","created_at":"2025-06-04 10:11:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44942,"visible":true,"origin":"","legend":"\u003cp\u003eGenetic structure, species relationships, and diversity and divergence for five \u003cem\u003eTypha\u003c/em\u003e species\u003cstrong\u003e \u003c/strong\u003e(a) Neighbour-joining tree. Branches represent individuals; different colours indicate species, as in the labels. (b) Nucleotide diversity (π, inside shapes) for each species and net divergence (d\u003csub\u003ea\u003c/sub\u003e, dashed lines) between species. Shapes and colours represent species.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/14a4fa0d71714427d951fbf5.png"},{"id":83905393,"identity":"15ade450-b859-40d5-8a3b-14c4f968fcaf","added_by":"auto","created_at":"2025-06-04 10:11:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":77863,"visible":true,"origin":"","legend":"\u003cp\u003eEvolutionary history of the \u003cem\u003eTypha\u003c/em\u003e in this study. Demographic fluctuations over generations in the past reconstructed with Stairway Plot. The tree (bottom right) is based on the TreeMix results in this study; the dates correspond to Zhou \u003cem\u003eet al.\u003c/em\u003e (2018). * and ** indicate speciation events.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/b4ca41afd0b2c4ce2bd4beb9.png"},{"id":83905396,"identity":"3bb4668e-cc82-452b-b8fc-be1f80b661c7","added_by":"auto","created_at":"2025-06-04 10:11:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":232106,"visible":true,"origin":"","legend":"\u003cp\u003eGenome-wide Tajima’s D for five \u003cem\u003eTypha\u003c/em\u003e species. Points represent 5 kb windows, solid lines represent means, and dashed lines represent 95% confidence intervals. The introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e to \u003cem\u003eT. angustifolia\u003c/em\u003e and \u003cem\u003eT. domingensis\u003c/em\u003e detected by ABBA BABA are highlighted in green.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/7bc242d2f0edf84a2b4e0ab3.png"},{"id":83905875,"identity":"132feb54-9829-4eb4-b9a1-5131ac18dfb3","added_by":"auto","created_at":"2025-06-04 10:19:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1578523,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/21db97be-1329-496e-88ca-c9f3bbe287bb.pdf"},{"id":83905394,"identity":"9a5a4a5e-6733-441f-9123-00663db2b589","added_by":"auto","created_at":"2025-06-04 10:11:58","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":307114,"visible":true,"origin":"","legend":"Supplementary Materials","description":"","filename":"HDYSupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/b19647f596713817327e2967.docx"},{"id":83905398,"identity":"6160c914-1fc9-4d61-8af9-7d58a1e7fe32","added_by":"auto","created_at":"2025-06-04 10:12:00","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":96946763,"visible":true,"origin":"","legend":"Supplementary Figures S3-S14","description":"","filename":"SupplementaryFiguresS3S14.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6778557/v1/a1bbd8d3e58829f17be8136a.pdf"}],"financialInterests":"There is no duality of interest","formattedTitle":"Allopatric speciation in cattails: Genomics reveal bottlenecks, balancing selection, and adaptive introgressions in \u003ci\u003eTypha\u003c/i\u003e, a wetland ecosystem engineer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSpeciation can follow two non-mutually exclusive pathways: geographic isolation (“allopatric speciation”) and natural selection (“ecological speciation”) (Stankowski and Ravinet, 2021). In isolation, divergence is primarily driven by genetic drift (Mayr \u003cem\u003eet al.\u003c/em\u003e, 1963), and although local adaptations occur, they are not assumed to be the driving force underlying species formation (Hernández-Hernández \u003cem\u003eet al.\u003c/em\u003e, 2021). Conversely, divergent selection is mandatory during ecological speciation (Pinho and Hey, 2010; Nosil, 2012). Understanding how these pathways lead to lineages diverging is key to speciation genomics and can help us characterise how biological diversity originates (Seehausen \u003cem\u003eet al.\u003c/em\u003e, 2014).\u003c/p\u003e\n\u003cp\u003eGlobal climatic oscillations have repeatedly shaped species’ ranges and population sizes, triggering isolation and providing opportunities for allopatric divergence (Hewitt, 2000). These fluctuations include the rapid transformations of the Neogene (Andersson, 2009) and the glacial cycles of the Quaternary, which promoted speciation through drift events (e.g., Chacón \u003cem\u003eet al.\u003c/em\u003e, 2019; Kong \u003cem\u003eet al.\u003c/em\u003e, 2022; Dagallier \u003cem\u003eet al.\u003c/em\u003e, 2024). Drift-driven speciation can be linked to sharp changes in species’ past demographic sizes (Bock \u003cem\u003eet al.\u003c/em\u003e, 2023) and is the most common cause of divergence in plants (Hernández-Hernández \u003cem\u003eet al.\u003c/em\u003e, 2021). In contrast, natural selection promotes ecological divergence by fixing beneficial alleles and purging deleterious ones (Schluter, 2001). Under this model, speciation leads to the emergence of “genomic landscapes” (Wolf and Ellegren, 2017). These landscapes are highly differentiated (“islands”) or conserved (“valleys”) genomic regions along (or linked to) loci associated with natural selection and reproductive isolation (Ravinet \u003cem\u003eet al.\u003c/em\u003e, 2017). Reconstructing these landscapes can be used to identify the contributions of natural selection to speciation (Andrew and Rieseberg, 2013; Ravinet \u003cem\u003eet al.\u003c/em\u003e, 2017; Han \u003cem\u003eet al.\u003c/em\u003e, 2017; Irwin \u003cem\u003eet al.\u003c/em\u003e, 2018; Ottenburghs \u003cem\u003eet al.\u003c/em\u003e, 2020; Kessler \u003cem\u003eet al.\u003c/em\u003e, 2023; Shang \u003cem\u003eet al.\u003c/em\u003e, 2023).\u003c/p\u003e\n\u003cp\u003eGene flow plays an important role in speciation (Feder \u003cem\u003eet al.\u003c/em\u003e, 2012; Tigano and Friesen, 2016). The restriction of gene flow, through allopatry or natural selection, permits genetic differentiation and the formation of distinct lineages (Morjan and Rieseberg, 2004), whereas gene flow generally plays a homogenising role (Woodruff, 2001). However, gene flow between genetically distinct species (hybridisation) has diverse outcomes (Harrison and Larson, 2014; Taylor and Larson, 2019). Hybridisation can cause the formation of new species, the extinction of parental taxa through genetic swamping, or the reinforcement of species’ boundaries (Noor, 1999; Garner \u003cem\u003eet al.\u003c/em\u003e, 2018; Runemark \u003cem\u003eet al.\u003c/em\u003e, 2019). In stable hybrid zones, hybridisation can cause introgressions (the movement of genes from one species to another), promoting adaptation when introgressed loci provide higher fitness (Whitney \u003cem\u003eet al.\u003c/em\u003e, 2010; Suarez-Gonzalez, Lexer, \u003cem\u003eet al.\u003c/em\u003e, 2018; Leroy \u003cem\u003eet al.\u003c/em\u003e, 2020; Rendón-Anaya \u003cem\u003eet al.\u003c/em\u003e, 2021).\u003c/p\u003e\n\u003cp\u003eCattails (\u003cem\u003eTypha\u003c/em\u003e) are rhizomatous perennial, monoecious, self-compatible, and wind-pollinated plants crucial to freshwater and brackish ecosystems; they play a vital ecological role in cycling nutrients, preventing erosion, maintaining water levels, and providing food and shelter for amphibians, birds, fish, insects, and mammals (Bonanno and Cirelli, 2017; Bansal \u003cem\u003eet al.\u003c/em\u003e, 2019; Svedarsky \u003cem\u003eet al.\u003c/em\u003e, 2019). The three most widespread \u003cem\u003eTypha\u003c/em\u003e spp. (\u003cem\u003eT. angustifolia\u0026nbsp;\u003c/em\u003eL., \u003cem\u003eT. domingensis\u0026nbsp;\u003c/em\u003ePers., and \u003cem\u003eT. latifolia\u0026nbsp;\u003c/em\u003eL.) have extensive areas of sympatry and allopatry (Figure 1) and are capable of hybridising (Smith, 1967). \u003cem\u003eTypha angustifolia\u003c/em\u003e and \u003cem\u003eT. latifolia\u003c/em\u003e share a widespread hybrid zone in North America involving the highly impactful invasive \u003cem\u003eT.\u003c/em\u003e × \u003cem\u003eglauca,\u0026nbsp;\u003c/em\u003ewhich forms dense stands, altering habitats and outcompeting and displacing native plants (reviewed in Bansal \u003cem\u003eet al.\u003c/em\u003e, 2019).\u003c/p\u003e\n\u003cp\u003eHere, we examined the genomic diversity and differentiation of five cattail species to evaluate the role of drift, selection, and hybridisation in their speciation history. These comprised \u003cem\u003eT. angustifolia\u003c/em\u003e,\u003cem\u003e\u0026nbsp;T. domingensis\u003c/em\u003e, and \u003cem\u003eT. latifolia\u003c/em\u003e; we also included two closely related \u003cem\u003eTypha\u003c/em\u003e, \u003cem\u003eT. laxmannii\u003c/em\u003e Lepech. and \u003cem\u003eT. shuttleworthii\u003c/em\u003e W. D. J. Koch and Sond (Zhou \u003cem\u003eet al.\u003c/em\u003e, 2018), which have more restricted ranges (Figure 1). The genomes of 207 plants sampled across multiple continents were sequenced to address the following questions: (1) What are the demographic histories and (2) levels of genetic diversity and divergence of these species? (3) How has selection shaped their genomic landscapes? (4) Has hybridisation led to (adaptive or non-adaptive) introgressions between \u003cem\u003eT. angustifolia\u003c/em\u003e and \u003cem\u003eT. latifolia\u003c/em\u003e? Understanding how \u003cem\u003eTypha\u003c/em\u003e species have diverged could provide important insights for wetland conservation. Speciation in allopatry (without developing reproductive genetic barriers) could help explain cattails’ ability to create invasive hybrids; this, in turn, could highlight potential risks associated with human-mediated dispersal, for example, intercontinental \u003cem\u003eTypha\u003c/em\u003e sourcing by garden centres (Ciotir and Freeland, 2016).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData preparation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSampling, DNA extraction, and sequencing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSamples were obtained from a previous study (Aleman \u003cem\u003eet al.\u003c/em\u003e, 2024) and supplemented with additional collections to increase taxonomic diversity and sampling range (Figure 1; Supplementary Table S1). Plants were identified beforehand using known morphological characteristics (Smith, 1967; Grace and Harrison, 1986) and/or a combination of three to four microsatellite loci (Ciotir \u003cem\u003eet al.\u003c/em\u003e, 2013, 2017; Ciotir and Freeland, 2016; Tisshaw \u003cem\u003eet al.\u003c/em\u003e, 2020; Pieper \u003cem\u003eet al.\u003c/em\u003e, 2020; Bhargav \u003cem\u003eet al.\u003c/em\u003e, 2022). DNA was extracted following published protocols (Pieper \u003cem\u003eet al.\u003c/em\u003e, 2017, 2020) and then converted into Nextera XT libraries for reduced-representation genotyping-by-sequencing as per Aleman \u003cem\u003eet al.\u003c/em\u003e (2024) (Supplementary information – Methods). Paired-end sequencing was conducted on a Miseq (151 bp) and a Novaseq 6000 (126 bp) at The Centre for Applied Genomics (Toronto, Ontario, Canada) for 64 \u003cem\u003eT. angustifolia\u003c/em\u003e, 25 \u003cem\u003eT. domingensis\u003c/em\u003e, 104\u003cem\u003e\u0026nbsp;T. latifolia\u003c/em\u003e, 11 \u003cem\u003eT. laxmannii\u003c/em\u003e, and 3 \u003cem\u003eT. shuttleworthii\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRaw data processing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe quality of the demultiplexed raw sequences was evaluated using FastQC 0.11.9 (Andrews, 2017) and MultiQC 1.14 (Ewels \u003cem\u003eet al.\u003c/em\u003e, 2016). Read pairing and adapter pruning were carried out with Trimmomatic 0.39 (Bolger \u003cem\u003eet al.\u003c/em\u003e, 2014), removing cleaned reads shorter than 100 bp. All reads were mapped to the \u003cem\u003eT. latifolia\u003c/em\u003e nuclear (15 chromosomes, 285.11 Mb, GenBank accession JAIOKV000000000.2) and chloroplast (161.57 kb, GenBank accession NC_013823) genomes with BWA 0.7.17 (Li and Durbin, 2009). Mapping statistics were evaluated using SAMtools 1.15.1 (Li \u003cem\u003eet al.\u003c/em\u003e, 2009).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGenotype-calling\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGenotype calling was performed through ANGSD 0.93 (Korneliussen \u003cem\u003eet al.\u003c/em\u003e, 2014). Two datasets were created using all samples. SNPs were retrieved requiring a minimum mapping and Phred scores of 20 and a minimum p-value of 1e\u003csup\u003e−6\u003c/sup\u003e (referred to as the \u003cem\u003eSNP dataset\u003c/em\u003e). Reconstructing the genomic landscape requires variant and invariant loci; hence, a dataset including SNPs and invariant sites (referred to as the \u003cem\u003eall-sites dataset\u003c/em\u003e) was created using the same mapping and Phred filters. SNPs with more than 20% missing data and sites mapped to the plastome were removed from the \u003cem\u003eSNP dataset\u003c/em\u003e with VCFtools 0.1.16\u0026nbsp;(Danecek \u003cem\u003eet al.\u003c/em\u003e, 2011). The plastome data were also removed from the \u003cem\u003eall-sites dataset—\u003c/em\u003efor the coverage requirements in the \u003cem\u003eall-sites dataset\u003c/em\u003e, see \u003cem\u003eRole of selection and introgressive hybridisation on species’ divergence\u003c/em\u003e. No individuals were removed from any dataset. The absence of clones (multiple ramets from the same genet) was verified by calculating kinship coefficients with Plink 2.0\u0026nbsp;(Chang \u003cem\u003eet al.\u003c/em\u003e, 2015)and the\u0026nbsp;\u003cem\u003eSNP dataset\u003c/em\u003e.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGenetic structure and species’ demographic histories\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo approaches were used to investigate the genetic structure and relationships among samples: (1) a principal component analysis (PCA; PC1 to PC3) and (2) a neighbour-joining (NJ) tree based on the samples’ pairwise distances (expressed as allele counts, transformed with the R 4.3.1 package ape 5.7-1 (Paradis and Schliep, 2019; R Core Team, 2022) were both produced with Plink 1.9 (Purcell \u003cem\u003eet al.\u003c/em\u003e, 2007) and the \u003cem\u003eSNP dataset\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eSpecies splits and migration events were inferred with TreeMix 1.13 (Pickrell and Pritchard, 2012) and the \u003cem\u003eSNP dataset\u003c/em\u003e. This analysis tested migration events between 0 and 10, and the optimal number of migrations was chosen based on the data variance.\u0026nbsp;Demographic fluctuations were reconstructed using a Stairway Plot 2.1.2 analysis (Liu and Fu, 2015, 2020), which generates estimates of N\u003csub\u003ee\u003c/sub\u003e over generations in the past. Using the \u003cem\u003eSNP dataset\u003c/em\u003e, a folded site frequency spectrum (SFS) per species was produced in easysfs 0.0.1 (Gutenkunst \u003cem\u003eet al.\u003c/em\u003e, 2009); given that intraspecific structure was observed in \u003cem\u003eT. latifolia,\u003c/em\u003e distinguishing two lineages (“Eastern” and “Western”, see \u003cem\u003eResults\u003c/em\u003e), independent SFSs were produced for each of these lineages. The resultant SFSs and the mutation rate of \u003cem\u003eArabidopsis thaliana\u003c/em\u003e (7×10\u003csup\u003e-9\u003c/sup\u003e mutations per site per generation (Weng\u0026nbsp;\u003cem\u003eet al.\u003c/em\u003e, 2019)) were used as inputs for Stairway Plot.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRole of selection and introgressive hybridisation on species’ divergence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo estimate the genetic diversity within and divergence between species, F\u003csub\u003eST\u003c/sub\u003e (Weir and Cockerham, 1984), d\u003csub\u003eXY\u003c/sub\u003e (Nei and Miller, 1990), and π (Nei and Li, 1979) were computed in 5 kb windows for all species pairs using pixy 1.2.7 (Korunes and Samuk, 2021) and the \u003cem\u003eall-sites dataset\u003c/em\u003e. To ensure data reliability, windows with coverage below 50% (in each pairwise comparison) were discarded. The means for each statistic and the net divergence between species (d\u003csub\u003ea\u003c/sub\u003e; Nei and Li (1979)) were calculated.\u003c/p\u003e\n\u003cp\u003eTo test the role of selection on species’ genetic differentiation, islands and valleys of divergence consistent with the alternative types of selection proposed by Irwin \u003cem\u003eet al.\u003c/em\u003e (2018) were identified using the retained windows in each pairwise comparison (see \u003cem\u003eabove\u003c/em\u003e). Individual F\u003csub\u003eST\u003c/sub\u003e, d\u003csub\u003eXY\u003c/sub\u003e, and π values were standardised into Z-scores (e.g., \u003cem\u003eZF\u003csub\u003eST\u003c/sub\u003e = [(window F\u003csub\u003eST\u003c/sub\u003e – genome-wide median F\u003csub\u003eST\u003c/sub\u003e) / genome-wide F\u003csub\u003eST\u003c/sub\u003e standard deviation]\u003c/em\u003e), and windows with exceptionally high or low diversity and divergence were characterised by detecting outliers where the absolute value of a Z-score≥ 1.96; intermediate d\u003csub\u003eXY\u003c/sub\u003e values were also documented (Z-score between –0.1257 and 0.1257). Following Kessler \u003cem\u003eet al.\u003c/em\u003e (2023) and Shang \u003cem\u003eet al.\u003c/em\u003e (2023), islands and valleys of divergence (i.e., positive and negative F\u003csub\u003eST\u003c/sub\u003e outliers) were classified into four models of selection using joint combinations of statistics as follows: (i) divergent with gene flow (high F\u003csub\u003eST\u003c/sub\u003e and d\u003csub\u003eXY\u003c/sub\u003e, low π); (ii) divergent without gene flow (high F\u003csub\u003eST\u003c/sub\u003e, intermediate d\u003csub\u003eXY\u003c/sub\u003e, and low π); (iii) background (high F\u003csub\u003eST\u003c/sub\u003e, low d\u003csub\u003eXY\u003c/sub\u003e and π); and (iv) balancing (low F\u003csub\u003eST\u003c/sub\u003e, high d\u003csub\u003eXY\u003c/sub\u003e and π).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, Tajima’s D (Tajima, 1989) was estimated in 5 kb windows for each species using VCFtools and the \u003cem\u003eall-sites dataset\u003c/em\u003e. Within each species, only those windows with more than 50 SNPs were kept, and loci with Tajima’s D higher than +2 or lower than –2 were interpreted as experiencing balancing selection and selective sweeps, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eABBA BABA was used to identify introgressions; \u003cem\u003eT. laxmannii\u0026nbsp;\u003c/em\u003ewas designated as outgroup, and all possible combinations of donor and recipient species were examined (Supplementary Table S2). The script ABBABABAwindows.py (Martin and Jiggins, 2017) was used to compute f\u003csub\u003ed\u003c/sub\u003e (Martin \u003cem\u003eet al.\u003c/em\u003e, 2015) in 5 kb windows. Two or more loci with a positive f\u003csub\u003ed\u003c/sub\u003e, ZF\u003csub\u003eST\u0026nbsp;\u003c/sub\u003eand Zd\u003csub\u003eXY\u003c/sub\u003e ≤–1.96, and at least within 50 kb of each other, were classified as introgressions. Introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e to \u003cem\u003eT. angustifolia\u0026nbsp;\u003c/em\u003ewere observed (see \u003cem\u003eResults\u003c/em\u003e); thus, ABBA BABA was replicated, splitting data into “North America” and “Europe” to test whether introgressions occur on both continents.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGenetic structure and species’ demographic histories\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe assembled 21,759,123 nuclear SNPs across 207 samples and kept 77,207 with missing data below 20%. The PCA (PC1 to PC3, Supplementary Figure S1) and NJ tree (Figure 2) distinguished all five species; the NJ tree also revealed intraspecific structure in \u003cem\u003eT. latifolia\u003c/em\u003e distinguishing two lineages, named “Western” (n = 77; North America, Western and Central Europe) and “Eastern” (n = 27; Eastern Europe and the Iturup Island in the Russian Kuril Chain).\u003c/p\u003e\n\u003cp\u003eTreeMix indicated \u003cem\u003eT. angustifolia\u003c/em\u003e – \u003cem\u003eT. domingensis\u003c/em\u003e and \u003cem\u003eT. latifolia\u003c/em\u003e – \u003cem\u003eT. shuttleworthii\u003c/em\u003e as sister lineages, and \u003cem\u003eT. laxmannii\u003c/em\u003e as outgroup species (Figure 1); this topology was consistent with the NJ tree. The most likely number of gene flow events was determined to be zero, explaining over 99.9% of the data variance. \u003cem\u003eTypha laxmannii\u003c/em\u003e, inferred by Treemix to be the oldest species, exhibited a stable N\u003csub\u003ee\u003c/sub\u003e from ~18 million to ~5 million generations ago, when a sharp decline appeared to coincide with sharp expansions for \u003cem\u003eT. angustifolia\u003c/em\u003e and \u003cem\u003eT. domingensis\u003c/em\u003e. Another sharp decline for \u003cem\u003eT. laxmannii\u003c/em\u003e appeared to coincide with a sharp expansion ~3 million generations ago for Eastern \u003cem\u003eT. latifolia\u003c/em\u003e. Western \u003cem\u003eT. latifolia\u003c/em\u003e appeared to experience a cycle of expansion-decline-expansion between ~2 million and ~400,000 generations ago; finally, \u003cem\u003eT. shuttleworthii\u003c/em\u003e appeared to undergo a sharp expansion ~1 million generations ago. The series of sharp declines and expansions inferred by Stairway Plot overlapped with the order of species splits revealed by Treemix; moreover, assuming a ~2-year generation time, this series of events coincides with the divergence times of \u003cem\u003eT. angustifolia\u003c/em\u003e – \u003cem\u003eT. domingensis\u003c/em\u003e and \u003cem\u003eT. latifolia\u003c/em\u003e – \u003cem\u003eT. shuttleworthii\u003c/em\u003e in the literature (Figure 3\u003cem\u003e;\u0026nbsp;\u003c/em\u003esee\u003cem\u003e\u0026nbsp;Discussion\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRole of selection and introgressive hybridisation on species’ divergence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCovering 65% of the genome (variant and invariant sites, depth = 4×), mean F\u003csub\u003eST\u003c/sub\u003e varied from 0.317 (\u003cem\u003eT. angustifolia\u003c/em\u003e–\u003cem\u003eT. domingensis\u003c/em\u003e) to 0.617 (\u003cem\u003eT. latifolia\u003c/em\u003e–\u003cem\u003eT. laxmannii\u003c/em\u003e), d\u003csub\u003eXY\u003c/sub\u003e from 0.016 (\u003cem\u003eT. latifolia\u003c/em\u003e–\u003cem\u003eT. shuttleworthii\u003c/em\u003e) to 0.030 (\u003cem\u003eT. domingensis\u003c/em\u003e–\u003cem\u003eT. shuttleworthii\u003c/em\u003e), π from 0.005 (\u003cem\u003eT. latifolia\u003c/em\u003e) to 0.024 (\u003cem\u003eT. domingensis\u003c/em\u003e), and d\u003csub\u003ea\u003c/sub\u003e from 0.007 (\u003cem\u003eT. latifolia\u003c/em\u003e–\u003cem\u003eT. shuttleworthii\u003c/em\u003e) to 0.015 (\u003cem\u003eT. latifolia\u003c/em\u003e–\u003cem\u003eT. angustifolia\u003c/em\u003e) (Table 1; Figure 2). \u003cem\u003eTypha\u003c/em\u003e \u003cem\u003elatifolia\u003c/em\u003e was the only species with low diversity (π \u0026lt; 0.01). The net divergence among the five species was low (d\u003csub\u003ea\u003c/sub\u003e \u0026lt;0.02).\u003c/p\u003e\n\u003cp\u003eThe genomic landscapes between species pairs showed a heterogeneous role of selection on species’ differentiation (Supplementary Figures S3 to S12). Most loci (5 kb) with exceptionally high or low F\u003csub\u003eST\u003c/sub\u003e could not be associated with any of the types of selection tested (on average, 1398 out of 1839; Table 2). On average, from the 441 loci that could be associated with selection, balancing selection was the most frequently detected in pairwise comparisons (375 loci, 0.66% of the genome); background selection was the second (46 loci, 0.08% of the genome), followed by selection without and with gene flow (15 and 6 loci – 0.03%, and 0.01% of the genome, respectively). A prominent island of background selection was observed between \u003cem\u003eT. laxmannii\u0026nbsp;\u003c/em\u003eand most species in our study (~350 kb, chromosome 14); no genes could be identified in this island.\u003c/p\u003e\n\u003cp\u003eExcept for \u003cem\u003eT. latifolia\u003c/em\u003e, all species had mean positive Tajima’s D per species, from 0.05 (\u003cem\u003eT. angustifolia\u003c/em\u003e) to 1.55 (\u003cem\u003eT\u003c/em\u003e. \u003cem\u003elaxmannii\u003c/em\u003e) (Figure 4) and more loci with values higher than +2 (~8,129) vs lower than –2 (~43), consistent with the widespread balancing selection observed across the genomic landscapes; \u003cem\u003eT. shuttleworthii\u003c/em\u003e had no loci with values higher than 2 a mean Tajima’s D of 0.66, \u003cem\u003eT. domingensis\u003c/em\u003e mean was 1.14; \u003cem\u003eT. latifolia\u003c/em\u003e had a mean negative Tajima’s D (–1.27) and a large number of windows lower than –2 (12,252), in line with the most recent expansion observed in its demographic history.\u003c/p\u003e\n\u003cp\u003eThe f\u003csub\u003ed\u003c/sub\u003e identified introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e to \u003cem\u003eT. angustifolia\u003c/em\u003e on chromosomes 11 and 14 (~145 kb); no genes could be identified in these introgressions. The introgressed regions exhibited values of Tajima’s D from –0.77 to –1.96, suggesting positive selection. Splitting the data by continent confirmed that these introgressions are found in North America and Europe (Supplementary Figures S13 and S14). Additional introgressions from \u003cem\u003eT. latifolia\u0026nbsp;\u003c/em\u003eto \u003cem\u003eT. domingensis\u003c/em\u003e were identified in chromosomes 8, 14, and 15; no genes were found in these introgressions, and their Tajima’s D values ranged from –0.004 to –1.73.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDuring allopatric speciation, genetic divergence primarily accumulates through drift (Abbott \u003cem\u003eet al.\u003c/em\u003e, 2013); in contrast, ecological (sympatric) speciation requires divergent selection (Rundle and Nosil, 2005; Nosil, 2012). This means that ecological speciation should produce stronger reproductive barriers than geographic isolation, and that speciation in isolation could enable hybridisation if species experience secondary contact (Hewitt, 2000; Rheindt and Edwards, 2011; Sobel, 2016)—although the later development of genetic barriers between species (e.g., through reinforcement (Noor, 1999)) would depend on their history after secondary contact and hybridisation occur (Runemark \u003cem\u003eet al.\u003c/em\u003e, 2019; Moran \u003cem\u003eet al.\u003c/em\u003e, 2021). Here, we examined the genomic diversity and differentiation of five cattail species to evaluate the role of drift, selection, and hybridisation in their speciation history. We revealed (1) species splits (without migration events) coincident with past sharp demographic declines, (2) low net genomic divergence between species (d\u003csub\u003ea\u003c/sub\u003e from 0.007 to 0.015), (3) predominant valleys of balancing selection between species, and (4) introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e to \u003cem\u003eT. angustifolia—\u003c/em\u003eboth in North America and Europe, despite the absence of hybrids in the latter—and \u003cem\u003eT. domingensis\u003c/em\u003e. Our results suggest that demographic contractions are the primary factor responsible for the speciation of these\u0026nbsp;\u003cem\u003eTypha\u003c/em\u003e, possibly followed by range expansions and secondary contact, enabling hybridisation between some species.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDemographic history and scarcity of divergent selection in Typha\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTreemix reported a topology with no migration events, indicating that species split events without gene flow events can account for all the observed genetic variation among the species in our study. While it does not rule out the possibility of hybridisation after secondary contact, this result suggests that genetic drift—without gene flow—was the primary driver of differentiation among the species in this study. Stairway Plot revealed a series of sharp N\u003csub\u003ee\u003c/sub\u003e declines and expansions that coincide chronologically with the Treemix topology and the divergence times of Zhou \u003cem\u003eet al.\u003c/em\u003e (2018). Geoclimatic events, including the Miocene aridification and the Quaternary glacial cycles (Hewitt, 2000; Herbert \u003cem\u003eet al.\u003c/em\u003e, 2016; Butiseacă \u003cem\u003eet al.\u003c/em\u003e, 2021), could have led to these bottlenecks, both periods potentially fragmenting the extent and connectivity of wetland habitats. These reductions in N\u003csub\u003ee\u003c/sub\u003e likely reflect episodes of geographic isolation that triggered species divergence via genetic drift. Stairway Plot also indicated that \u003cem\u003eT. latifolia\u003c/em\u003e possibly underwent an expansion-decline-expansion cycle between ~2 million and ~400,000 generations ago, which is in line with the genome-wide negative Tajima’s D (–1.765) in this species.\u003c/p\u003e\n\u003cp\u003eThe islands and valleys of divergence associated with divergent selection were scarce, occurring on average in 0.12% of the genome and 2.88% of the loci with exceptionally high or low F\u003csub\u003eST\u003c/sub\u003e in pairwise comparisons. This result suggests a negligible role of ecological divergence in the speciation of the \u003cem\u003eTypha\u003c/em\u003e in this study. Some signatures of divergent due to selection could have been eroded by time and recombination, which is consistent with the late stages of speciation (Burri \u003cem\u003eet al.\u003c/em\u003e, 2015)— the age of \u003cem\u003eTypha\u0026nbsp;\u003c/em\u003eis estimated between 20 and 70 Ma (Zhou \u003cem\u003eet al.\u003c/em\u003e, 2018; Widanagama \u003cem\u003eet al.\u003c/em\u003e, 2022)—however, the net divergence (d\u003csub\u003ea\u003c/sub\u003e) among these \u003cem\u003eTypha\u0026nbsp;\u003c/em\u003especies is low (\u0026lt;0.02; ‘grey zone of speciation’ (Roux \u003cem\u003eet al.\u003c/em\u003e, 2016)), which suggests that reproductive isolation remains incomplete despite \u003cem\u003eTypha\u003c/em\u003e being and old genus and the high relative divergence (F\u003csub\u003eST\u0026nbsp;\u003c/sub\u003e\u0026gt; 0.25 (Wright, 1984)) between species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBalancing selection and introgressions as sources of genetic variation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStanding genetic variation can be as important as mutations to adaptation (Barrett and Schluter, 2008; Matuszewski \u003cem\u003eet al.\u003c/em\u003e, 2015). Several mechanisms maintain standing genetic variation, including balancing selection (Llaurens \u003cem\u003eet al.\u003c/em\u003e, 2017; Fijarczyk \u003cem\u003eet al.\u003c/em\u003e, 2018). Across the genomic landscapes of the species in our study, most regions associated with adaptive divergence were valleys of balancing selection—as confirmed by Tajima’s D results—in which the maintenance of standing polymorphisms causes an excessively reduced divergence (Guerrero and Hahn, 2017). Signatures of balancing selection are congruent with \u003cem\u003eTypha\u003c/em\u003e spp. ability to self-fertilise; selfing leads to increased homozygosity, so balancing selection can be crucial in preserving polymorphism at important loci (Glémin, 2021). Genes experiencing balancing selection have been shown to underlie a wide range of phenotypes (Isildak \u003cem\u003eet al.\u003c/em\u003e, 2021; Promy \u003cem\u003eet al.\u003c/em\u003e, 2023) and promote adaptation to divergent habitats (Delph and Kelly, 2014; Wu \u003cem\u003eet al.\u003c/em\u003e, 2017). A predominant role of balancing selection has been detected among other widespread plants, including \u003cem\u003eArabidopsis\u003c/em\u003e, \u003cem\u003eArbutus\u003c/em\u003e, \u003cem\u003eCapsella\u003c/em\u003e, \u003cem\u003ePopulus\u003c/em\u003e,and \u003cem\u003eQuercus\u003c/em\u003e (Santiso \u003cem\u003eet al.\u003c/em\u003e, 2016; Meireles \u003cem\u003eet al.\u003c/em\u003e, 2017; Wu \u003cem\u003eet al.\u003c/em\u003e, 2017; Bachmann \u003cem\u003eet al.\u003c/em\u003e, 2018; Koenig \u003cem\u003eet al.\u003c/em\u003e, 2019; Wang \u003cem\u003eet al.\u003c/em\u003e, 2019, 2020; Rendón-Anaya \u003cem\u003eet al.\u003c/em\u003e, 2019; Le Veve \u003cem\u003eet al.\u003c/em\u003e, 2023; Shang \u003cem\u003eet al.\u003c/em\u003e, 2023). The growing evidence supporting a prominent role of balancing selection (Delph and Kelly, 2014; Fijarczyk and Babik, 2015; Guerrero and Hahn, 2017; Llaurens \u003cem\u003eet al.\u003c/em\u003e, 2017; Thorburn \u003cem\u003eet al.\u003c/em\u003e, 2022; Kessler \u003cem\u003eet al.\u003c/em\u003e, 2023) challenges the view of background selection being the leading force shaping species’ genetic diversity (Comeron, 2017).\u003c/p\u003e\n\u003cp\u003eIntrogressive hybridisation is another important source of standing genetic variation (Tigano and Friesen, 2016; Suarez-Gonzalez, Lexer, \u003cem\u003eet al.\u003c/em\u003e, 2018). Research on the \u003cem\u003eT. × glauca\u003c/em\u003e hybrid swarm in North America has demonstrated the fertility of F1 hybrids in natural populations (Grace and Harrison, 1986; Snow \u003cem\u003eet al.\u003c/em\u003e, 2010; Travis \u003cem\u003eet al.\u003c/em\u003e, 2010; Kirk \u003cem\u003eet al.\u003c/em\u003e, 2011) and their ability to backcross (Pieper \u003cem\u003eet al.\u003c/em\u003e, 2017; Bhargav \u003cem\u003eet al.\u003c/em\u003e, 2022). Under these circumstances, introgressions between \u003cem\u003eT. latifolia\u003c/em\u003e and \u003cem\u003eT. angustifolia\u0026nbsp;\u003c/em\u003ecould be expected, and those identified might be under positive selection. Introgressions were also present in Europe, where these species do not currently hybridise (Ciotir \u003cem\u003eet al.\u003c/em\u003e, 2017)—suggesting that hybridisation between these species could have happened in the past. Introgressions have been documented in other widespread plants, including \u003cem\u003eHelianthus\u003c/em\u003e (Kim and Rieseberg, 1999; Whitney \u003cem\u003eet al.\u003c/em\u003e, 2006, 2010), \u003cem\u003ePopulus\u003c/em\u003e (Suarez-Gonzalez, Hefer, \u003cem\u003eet al.\u003c/em\u003e, 2018; Rendón-Anaya \u003cem\u003eet al.\u003c/em\u003e, 2021), and \u003cem\u003eQuercus\u003c/em\u003e (Goicoechea \u003cem\u003eet al.\u003c/em\u003e, 2019; Leroy \u003cem\u003eet al.\u003c/em\u003e, 2020; Li \u003cem\u003eet al.\u003c/em\u003e, 2021),and are recognised as essential sources of genetic variation for adaptation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGenetic diversity in Typha\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenetic diversity reflects the reservoir of traits and potential responses to environmental changes that species encounter, thereby influencing their resilience in different ecosystems (Gregorius, 1987; Frankham \u003cem\u003eet al.\u003c/em\u003e, 2002; Hartl and Clark, 2006). Excluding \u003cem\u003eT. latifolia\u003c/em\u003e, species’ genetic diversity was high (π \u0026gt; 0.01 (Begun \u003cem\u003eet al.\u003c/em\u003e, 2007)), consistent with large population sizes and substantial gene flow. Low genetic diversity is often considered detrimental, as it can reflect a reduced adaptive potential (Teixeira and Huber, 2021; Kardos \u003cem\u003eet al.\u003c/em\u003e, 2021). However, some species—including invasive species—thrive despite having low genetic diversity (Tsutsui \u003cem\u003eet al.\u003c/em\u003e, 2000; Roman and Darling, 2007; Charlesworth and Jensen, 2022). \u003cem\u003eTypha\u003c/em\u003e tolerates wide-ranging climates, nutrients, pHs, pollutants, and water levels (Sojda and Solberg, 1993; Kadlec and Wallace, 2008; Sesin \u003cem\u003eet al.\u003c/em\u003e, 2021), and the most widespread and commonly recognised cattail species is \u003cem\u003eT. latifolia\u003c/em\u003e, presumed to have large census sizes, and is considered invasive in Oceania (Xu \u003cem\u003eet al.\u003c/em\u003e, 2013). Low genetic diversity in \u003cem\u003eT. latifolia\u003c/em\u003e suggests that alternative mechanisms, such as epigenetic modifications and associated phenotypic plasticity, may be responsible for the success of this species (Mounger \u003cem\u003eet al.\u003c/em\u003e, 2021). In \u003cem\u003eArabidopsis thaliana\u003c/em\u003e, epigenetic diversity underlies morphological variation and phenotypic plasticity when genetic diversity is low (Zhang \u003cem\u003eet al.\u003c/em\u003e, 2013; Kooke \u003cem\u003eet al.\u003c/em\u003e, 2015; Schmid \u003cem\u003eet al.\u003c/em\u003e, 2018). An inquiry for future research is testing if epigenetic modifications and phenotypic plasticity are more extensive in \u003cem\u003eT. latifolia\u003c/em\u003e than in other \u003cem\u003eTypha\u003c/em\u003e species.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eUnderstanding the causes of speciation is a central aspect of evolutionary biology. Here, we tested the roles of drift, selection, and hybridisation in driving species divergence in \u003cem\u003eTypha\u003c/em\u003e, an old and widespread plant genus that is foundational to freshwater ecosystems. Our results support bottlenecks and geographic isolation as the primary causes of speciation, as well as widespread balancing selection across \u003cem\u003eTypha\u003c/em\u003e, and introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e into\u003cem\u003e\u0026nbsp;T. angustifolia\u0026nbsp;\u003c/em\u003eand \u003cem\u003eT. domingensis\u003c/em\u003e. The absence of divergent selection does not rule out the role of ecological divergence as a promoter of speciation for the \u003cem\u003eTypha\u003c/em\u003e in our study\u0026mdash;this genic view of speciation requires only a handful of genes (Lexer and Widmer, 2008)\u0026mdash;rather, it indicates a primary role of genetic drift. Our results add \u003cem\u003eTypha\u003c/em\u003e to the body of evidence supporting an important role of balancing selection in preserving standing genetic variation despite the accumulation of divergence (e.g., Selechnik \u003cem\u003eet al.\u003c/em\u003e, 2019).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge that the laboratory procedures and data analyses were conducted at Trent University, which is on the traditional territory of the Mississauga Anishinaabeg, to whom we show our respect. We thank Polina A. Volkova and Tulsi Patel for their invaluable contributions to the laboratory and the field. The Natural Sciences and Engineering Research Council of Canada financially supported this work, and Alberto Aleman is funded by the Environmental and Life Sciences Graduate Program at Trent University. SHARCNET and Compute Canada provided computational resources for this study. We are grateful to\u0026nbsp;Camille Kessler, Marie-Laurence Cossette, Beibei Zhou, Xinwei Xu, the Associate Editor, and the anonymous reviewers for their valuable feedback, which significantly improved the quality of this manuscript. Finally, we thank Enrique Ruiz for his work in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConceptualisation, developing methods, conducting research, data interpretation, writing, data analysis, and preparation of figures and tables\u003c/em\u003e: Aaron Shafer, Alberto Aleman, Joanna Freeland, and Marcel Dorken. All authors contributed to the manuscript and approved its final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData archiving\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData and scripts for this study can be found at https://gitlab.com/WiDGeT_TrentU/graduate_theses/-/tree/master/aleman/hdy and https://github.com/al-aleman/totoras_hdy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRaw sequencing data are available from the authors upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Ethics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not require any ethical permissions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbott R, Albach D, Ansell S, Arntzen JW, Baird SJE, Bierne N, \u003cem\u003eet al.\u003c/em\u003e (2013). 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In: Levin SA (ed) \u003cem\u003eEncyclopedia of Biodiversity\u003c/em\u003e, Elsevier: New York, pp 811\u0026ndash;829.\u003c/li\u003e\n\u003cli\u003eWright S (1984). \u003cem\u003eEvolution and the Genetics of Populations, Volume 4: Variability Within and Among Natural Populations\u003c/em\u003e. University of Chicago Press.\u003c/li\u003e\n\u003cli\u003eWu Q, Han T-S, Chen X, Chen J-F, Zou Y-P, Li Z-W, \u003cem\u003eet al.\u003c/em\u003e (2017). Long-term balancing selection contributes to adaptation in Arabidopsis and its relatives. \u003cem\u003eGenome Biology\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e: 217.\u003c/li\u003e\n\u003cli\u003eXu Z, Feng Z, Yang J, Zheng J, Zhang F (2013). Nowhere to Invade: Rumex crispus and Typha latifolia Projected to Disappear under Future Climate Scenarios. \u003cem\u003ePLOS ONE\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e: e70728.\u003c/li\u003e\n\u003cli\u003eZhang Y-Y, Fischer M, Colot V, Bossdorf O (2013). 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Revised phylogeny and historical biogeography of the cosmopolitan aquatic plant genus Typha (Typhaceae). \u003cem\u003eSci Rep\u003c/em\u003e\u003cstrong\u003e8\u003c/strong\u003e: 8813.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eMean relative (F\u003csub\u003eST\u003c/sub\u003e, below diagonal) and absolute (d\u003csub\u003eXY\u003c/sub\u003e, above diagonal) genetic divergence between five \u003cem\u003eTypha\u003c/em\u003e species, measured in 5 kb windows.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. laxmannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. domingensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. latifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. laxmannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. domingensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eT. latifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eNumber of genetic islands and valleys of divergence (5 kb) consistent with alternative types of selection between five \u003cem\u003eTypha\u003c/em\u003e species: (i) divergent with gene flow, (ii) divergent without gene flow, (iii) background selection, (iv) balancing selection. The number of islands and valleys of divergence that could not be assigned to the alternative types of selection tested is shown in (v).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e(i)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e(ii)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(iii)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e(iv)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e(v)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia - T. domingensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia - T. latifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e2169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia - T. laxmannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. angustifolia - T. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1255\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. domingensis - T. latifolia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. domingensis - T. laxmannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. domingensis - T. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. latifolia - T. laxmannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1552\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. latifolia - T. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e1825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cem\u003eT. laxmannii - T. shuttleworthii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e893\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"heredity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"hdy","sideBox":"Learn more about [Heredity](http://www.nature.com/hdy/)","snPcode":"41437","submissionUrl":"https://mts-hdy.nature.com/cgi-bin/main.plex","title":"Heredity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"climate‐driven barriers, divergence, drift, evolutionary history, genomic landscapes, hybridisation, secondary contact","lastPublishedDoi":"10.21203/rs.3.rs-6778557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6778557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSpeciation can be broadly understood within two non-mutually exclusive frameworks: genetic drift under isolation and natural selection under ecological divergence. Here, we examined the genomic diversity and differentiation of five \u003cem\u003eTypha\u003c/em\u003e species, a group of plants foundational to freshwaters with widespread, partially sympatric distributions and at least one widespread hybrid zone. Using genome-wide data from 207 individuals, we examined the contributions of demographic fluctuations, selection, and hybridisation in driving their speciation history. Demographic reconstructions revealed sequential bottlenecks and expansions coincident with lineage splits, and indicated a drift-driven scenario with no migration events for all five species. The genomic landscapes showed balancing selection, sparse divergent selection, and low net divergence. Introgressions from \u003cem\u003eT. latifolia\u003c/em\u003e to \u003cem\u003eT. angustifolia \u003c/em\u003eand \u003cem\u003eT. domingensis\u003c/em\u003e were found. Our findings suggest histories of allopatric speciation followed by range expansions and secondary contacts, leading to contemporary hybridisation between some species. Our results also emphasise the roles of balancing selection and introgression as sources of standing genetic variation. Allopatric speciation in \u003cem\u003eT. latifolia\u003c/em\u003e and \u003cem\u003eT. angustifolia\u003c/em\u003e could explain their ability to hybridise, highlighting the need to stop the human-mediated dispersal of \u003cem\u003eTypha\u003c/em\u003e (e.g., the intercontinental sourcing via garden centres).\u003c/p\u003e","manuscriptTitle":"Allopatric speciation in cattails: Genomics reveal bottlenecks, balancing selection, and adaptive introgressions in Typha, a wetland ecosystem engineer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-04 10:11:53","doi":"10.21203/rs.3.rs-6778557/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-08-27T15:58:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-08-02T11:03:11+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-20T13:54:27+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-27T11:20:31+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-06-24T08:04:51+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-16T22:20:22+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-11T13:13:46+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-06-10T08:44:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Heredity","date":"2025-05-29T17:16:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-29T17:16:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"heredity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"hdy","sideBox":"Learn more about [Heredity](http://www.nature.com/hdy/)","snPcode":"41437","submissionUrl":"https://mts-hdy.nature.com/cgi-bin/main.plex","title":"Heredity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c7d668ee-b829-48ef-8b39-96b832725fe0","owner":[],"postedDate":"June 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":49246455,"name":"Biological sciences/Genetics/Population genetics/Genetic variation"},{"id":49246456,"name":"Biological sciences/Evolution/Population genetics"}],"tags":[],"updatedAt":"2025-08-27T16:02:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-04 10:11:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6778557","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6778557","identity":"rs-6778557","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}