Contrasting genomic routes to domestication in Occidental and Oriental pears

Contrasting genomic routes to domestication in Occidental and Oriental pears | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var 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, Lijuan Gao , Guofang Li , Monika Hoefer , Nicolas Francillone , Anamaria Roman , Lehel Lukács , Caroline Denance , Takashi Akagi , Anush Nersesyan , Astghik Papikyan , Ivan George Gabrielyan , Hamid Abdollahi , Nahla Victor Bassil , Serena Steffensmeier , Karine Alix , View ORCID Profile Yuanwen Teng , View ORCID Profile Amandine Cornille doi: https://doi.org/10.1101/2025.11.17.687327 Yuqi Nie 1 Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon , 91190 Gif-sur-Yvette, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yuqi Nie Xilong Chen 1 Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon , 91190 Gif-sur-Yvette, France 2 Division of Science, New York University Abu Dhabi, Saadiyat Island , Abu Dhabi, United Arab Emirates Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Xilong Chen For correspondence: karine.alix{at}inrae.fr chen_xilong{at}outlook.com ywteng{at}zju.edu.cn amandine.cornille{at}nyu.edu Somia Saidi 2 Division of Science, New York University Abu Dhabi, Saadiyat Island , Abu Dhabi, United Arab Emirates Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yann Bourgeois 3 DIADE, University of Montpellier , CIRAD, IRD, 34394, Montpellier, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anthony Venon 2 Division of Science, New York University Abu Dhabi, Saadiyat Island , Abu Dhabi, United Arab Emirates Find this author on Google Scholar Find this author on PubMed Search for this author on this site Johann Confais 4 Université Paris-Saclay , INRAE, BioinfOmics, URGI, 78026 Versailles, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Aurélie Mesnil 2 Division of Science, New York University Abu Dhabi, Saadiyat Island , Abu Dhabi, United Arab Emirates Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shuo Liu 5 Liaoning Institute of Pomology , Yingkou City, Liaoning 115009, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yuhao Gao 6 College of Agriculture and Biotechnology, Zhejiang University , Hangzhou, Zhejiang 310058, China 7 Zhejiang Provincial Key Laboratory of Integrative Biology of Horticultural Plants , Hangzhou, 310058 Zhejiang, China 8 The Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture of China , Hangzhou, 310058, Zhejiang, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Junbei Ni 6 College of Agriculture and Biotechnology, Zhejiang University , Hangzhou, Zhejiang 310058, China 7 Zhejiang Provincial Key Laboratory of Integrative Biology of Horticultural Plants , Hangzhou, 310058 Zhejiang, China 8 The Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture of China , Hangzhou, 310058, Zhejiang, China 9 Hainan Institute of Zhejiang University , Sanya, Hainan 572000, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Songling Bai 6 College of Agriculture and Biotechnology, Zhejiang University , Hangzhou, Zhejiang 310058, China 7 Zhejiang Provincial Key Laboratory of Integrative Biology of Horticultural Plants , Hangzhou, 310058 Zhejiang, China 8 The Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture of China , Hangzhou, 310058, Zhejiang, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lijuan Gao 10 Changli Institute of Pomology, Hebei Academy of Agriculture and Forestry Sciences , Changli 066600, Hebei, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Guofang Li 11 College of Horticulture, Hebei Agricultural University , Hebei 071000, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Monika Hoefer 12 Institute of Breeding Research on Fruit Crops, Federal Research Centre for Cultivated Plants (JKI) , Dresden, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicolas Francillone 4 Université Paris-Saclay , INRAE, BioinfOmics, URGI, 78026 Versailles, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anamaria Roman 13 Institute of Biological Research Cluj – National Institute for Research and Development in Biological Sciences , 400015, Cluj-Napoca, Romania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lehel Lukács 14 University of Agricultural Sciences and Veterinary Medicine , 400372, Cluj-Napoca, Romania Find this author on Google Scholar Find this author on PubMed Search for this author on this site Caroline Denance 15 Univ Angers, Institut Agro, INRAE, IRHS, SFR QUASAV , F-49000 Angers, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Takashi Akagi 16 Graduate School of Environmental and Life Science, Okayama University , Okayama, Japan 17 Japan Science and Technology Agency (JST), PRESTO, Kawaguchi-shi , Saitama, Japan 18 Kihara Institute for Biological Research, Yokohama City University , Yokohama, Kanagawa, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anush Nersesyan 19 A.Takhtajan Institute of Botany NAS RA , Achryan Street 1, 0063 Yerevan, Armenia 20 Nature Heritage NGO, Luxemburg Street 9-38 , 0090 Yerevan, Armenia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Astghik Papikyan 19 A.Takhtajan Institute of Botany NAS RA , Achryan Street 1, 0063 Yerevan, Armenia 20 Nature Heritage NGO, Luxemburg Street 9-38 , 0090 Yerevan, Armenia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ivan George Gabrielyan 19 A.Takhtajan Institute of Botany NAS RA , Achryan Street 1, 0063 Yerevan, Armenia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hamid Abdollahi 21 Temperate Fruits Research Center, Horticultural Sciences Research Institute, Agricultural Research, Education and Extension Organization (AREEO) , Karaj, Iran Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nahla Victor Bassil 22 USDA-ARS National Clonal Germplasm Repository (NCGR) , Corvallis, Oregon, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Serena Steffensmeier 22 USDA-ARS National Clonal Germplasm Repository (NCGR) , Corvallis, Oregon, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Karine Alix 1 Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon , 91190 Gif-sur-Yvette, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: karine.alix{at}inrae.fr chen_xilong{at}outlook.com ywteng{at}zju.edu.cn amandine.cornille{at}nyu.edu Yuanwen Teng 6 College of Agriculture and Biotechnology, Zhejiang University , Hangzhou, Zhejiang 310058, China 7 Zhejiang Provincial Key Laboratory of Integrative Biology of Horticultural Plants , Hangzhou, 310058 Zhejiang, China 8 The Key Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Ministry of Agriculture of China , Hangzhou, 310058, Zhejiang, China 9 Hainan Institute of Zhejiang University , Sanya, Hainan 572000, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yuanwen Teng For correspondence: karine.alix{at}inrae.fr chen_xilong{at}outlook.com ywteng{at}zju.edu.cn amandine.cornille{at}nyu.edu Amandine Cornille 1 Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon , 91190 Gif-sur-Yvette, France 2 Division of Science, New York University Abu Dhabi, Saadiyat Island , Abu Dhabi, United Arab Emirates Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Amandine Cornille For correspondence: karine.alix{at}inrae.fr chen_xilong{at}outlook.com ywteng{at}zju.edu.cn amandine.cornille{at}nyu.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract The domestication of perennial fruit trees remains poorly understood compared with annual crops, which were shaped by strong bottlenecks and elevated genetic load. Pears ( Pyrus spp.) provide an ideal model for exploring how long-lived, outcrossing crops evolved under human selection. Here, we combined high-coverage whole-genome resequencing of 396 wild and cultivated accessions from Occidental and Oriental pears with analyses of nucleotide and transposable element (TE) polymorphisms to reconstruct the demographic and adaptive history of pear domestication. Demographic inferences revealed weak or no domestication bottlenecks and extensive gene flow between wild and cultivated populations. In the Occidental lineage, dessert and perry P. communis cultivars underwent independent domestications from the same wild progenitor, P. pyraster , with divergent selection linked to fruit use. In the Oriental lineage, regionally independent domestications gave rise to Chinese and Japanese P. pyrifolia cultivars, shaped by both environmental adaptation and human selection. Selection scans identified lineage- and use-specific targets related to fruit texture, metabolism, and immunity. Contrary to the classical “cost of domestication” hypothesis, cultivated pears carried fewer deleterious variants than their wild relatives, suggesting efficient purging through selection and introgression. TE insertions mirrored population structure and occasionally occurred near selected genes, indicating a limited but detectable adaptive role. Together, our findings go beyond confirming the dual origins of Pyrus domestication to reveal contrasting demographic and adaptive pathways in Occidental and Oriental pears, illustrating independent adaptive trajectories in perennial crops, where long lifespan, self-incompatibility, and recurrent introgression shape distinctive genomic outcomes. Introduction Plant domestication represents one of the most profound evolutionary transitions in human history, providing a natural experiment to study how selection, gene flow, and demography shape adaptation on short evolutionary timescales ( Miller & Gross, 2011 ; Purugganan, 2022 ; Purugganan & Fuller, 2009 ). While domestication in annual crops has been intensively investigated, less is known about the genomic consequences of domestication in long-lived perennial fruit tree species. Perennials differ fundamentally from annuals in the way selection and demography interact during domestication. Their long generation times and outcrossing systems maintain high heterozygosity, enabling extensive gene flow between their wild and cultivated forms ( Cornille et al., 2014 ; Gaut et al., 2015 ; Gross et al., 2014 ; Mesnil et al., 2025 ). As a result, perennial crops often experience weak or no domestication bottlenecks, and frequently exhibit bidirectional introgression between wild and cultivated populations. These features make perennial fruit trees ideal systems for exploring how adaptive evolution proceeds under continuous gene flow and long-term selection. In several perennial models, including apple ( Malus domestica Borkh.), grapevine ( Vitis vinifera L.), olive ( Olea europaea L.), and peach ( Prunus persica (L.) Batsch), genes under selection during domestication have been linked to fruit development, ripening, and stress tolerance ( Chen et al., 2025 ; Cornille et al., 2019 ; Julca et al., 2020 ; Wu et al., 2018 ). These studies have primarily focused on the coding regions of genes, whereas the roles of non-coding regions, particularly transposable elements (TEs; mobile DNA sequences capable of reshaping gene regulation and chromatin structure) ( Feschotte et al., 2002 ), remain largely unexplored. TEs can generate regulatory and structural diversity, influence epigenetic states, and create new cis-regulatory variants, but their population-level dynamics and evolutionary consequences during domestication are poorly understood (Bourgeois & Boissinot, 2019). Investigating how polymorphisms of TE insertions contribute to genome variation and adaptation is therefore essential to comprehensively understand the domestication of perennial plants. Among temperate fruit trees, the pear ( Pyrus L., Rosaceae) provides an excellent model for studying perennial evolution and domestication. The genus Pyrus comprises roughly 20–75 intercompatible wild species distributed across Eurasia ( Challice & Westwood, 1973 ; Zheng et al., 2014 ; Silva et al., 2014 ), forming two major evolutionary lineages: the Occidental and Oriental pears, each including both wild and cultivated representatives. The European pear ( Pyrus communis L.) represents the principal cultivated form of the Occidental lineage, while the cultivated forms of the Oriental lineage encompass several cultivated species (also called Asian pears)— P. × sinkiangensis T.T. Yu, P. ussuriensis Maxim., and P. pyrifolia (Burm. f.) Nakai. Among them, P. pyrifolia is the most widely cultivated and genetically diverse, comprising three major Asian cultivar groups: the White Pear Group, Sand Pear Group, and Japanese Pear Group ( Bao et al., 2008 ; Teng et al., 2021 ). The European and Asian pears differ markedly in terms of their fruit morphology and use: European pears ( P. communis ) produce soft, melting fruits after ripening, used for fresh consumption (“dessert”) or usually inedible fruits for fermentation (“perry”), whereas Asian pears ( P. pyrifolia ) bear crisp, often round fruits that are mainly consumed fresh without ripening, reflecting independent domestication trajectories in Europe and Asia ( Hiwasa et al., 2004 ; Mou et al., 2025 ; Silva et al., 2014 ). Despite their agronomic importance, the domestication history of pears remains unresolved for the Occidental lineage, due to the poor representation of the wild relatives, P. pyraster (L.) Burgsd. and P. caucasica Fed., of European pears, which are considered the most probable ancestors of the cultivated P. communis ( Asanidze et al., 2014 ), in population genomic studies ( Wagner & Wagner, 2025 ). In addition, while recent studies have greatly advanced the characterization of diversity among Oriental pears ( Sun et al., 2025 ; Wu, Wang, et al., 2018; Zhang et al., 2025 ), their analyzed samples were heavily biased toward Asian cultivars and lacked field-verified wild populations (e.g., Pyrus pashia, Buch.-Ham. ex D. Don, the Himalayan pear) ( Teng et al., 2018 ; Zheng et al., 2014 ), limiting inferences about the independent origins, demographic histories, and comparative selective pressures experienced by these two lineages, and the role of TEs in shaping their genomes. Here, we investigated the demographic and adaptive processes that shaped the genomes of the two major cultivated pear lineages, aiming to reconstruct the tempo and mode of pear domestication. Specifically, we asked (i) how many distinct gene pools exist among Occidental and Oriental pears, and how they genetically relate to local wild relatives; (ii) whether domestication occurred independently within each lineage; (iii) whether parallel selection targeted shared functional pathways or distinct genetic routes; and (iv) whether TEs contributed to adaptive evolution. We addressed these questions by combining new and publicly available whole-genome resequencing data from 396 non-clonal accessions spanning Eurasia. Using nucleotide and transposable element insertion polymorphisms (SNPs and TIPs, respectively) called from lineage-matched reference genomes for P. communis and P. pyrifolia , we reconstructed the population structure, demographic history, and genomic signatures of selection and genetic load. Our integrative analyses go beyond confirming the dual origins of Pyrus domestication to reveal contrasting demographic and adaptive pathways in Occidental and Oriental pears, illustrating independent adaptive trajectories in perennial crops, where long lifespan, self-incompatibility, and recurrent introgression shape distinctive genomic outcomes. Results Occidental and oriental pears form distinct gene pools A global analysis of 396 non-duplicate pear genomes representing 207 newly sequenced and 189 publicly available individuals revealed a strong genetic split between Occidental (incl. P. communis ) and Oriental (incl. P. pyrifolia ) lineages ( Fig. 1a,b ). Using ∼21.8K synonymous and unlinked SNPs derived from 17.7 M high-quality variants (Supplementary Table 1; Supplementary Figs. 1,2), fastSTRUCTURE, neighbor-net, and principal component analysis (PCA) consistently distinguished the two gene pools, with 136 of 396 individuals showing admixed ancestry ( Fig. 1a–g ; Supplementary Tables 2,3; Supplementary Figs. 3–8; Supplementary Note). The strongest genetic differentiation among Oriental pears suggests that they experienced a longer or more complex divergence history. Download figure Open in new tab Figure 1. Population genetic structure, differentiation, and variation in Occidental and Oriental pears ( Pyrus spp.). (a, b) Population structure of wild and cultivated pears ( N = 396 individuals) inferred with fastSTRUCTURE: (a) Occidental pears ( N = 130; 20,298 synonymous, unlinked SNPs) at K = 15 and (b) Oriental pears ( N = 266; 21,141 synonymous, unlinked SNPs) at K = 10. (Sub)species name, sampling region, and usage type were obtained from sampling records. Wild Occidental and Oriental lineages were defined based on geographical distribution, using the Tianshan-Hindu Kush Mountains as the boundary. Cultivar and rootstock groups were defined by their gene pools and planting locations. Region codes follow the ISO 3166-1 alpha-2 standard, with “xx” indicating an unknown region. “CN-SE”, “CN-SW”, and “CN-NE” refer to China Southeast, China Southwest, and China Northeast, respectively. Regions are ordered by geographical longitude or by usage category for cultivars. (c,d) Neighbor-Net tree for the 130 Occidental pears, based on 20,298 unlinked and synonymous SNPs mapped onto P. communis (c) , and the 266 Oriental pears based on 21,141 SNPs mapped onto P. pyrifolia (d) . Branch colors correspond to the major colors of the gene pools in the population structure plots. Admixed or uncertainly assigned individuals (maximal membership coefficient ≤ 0.8), also including one pure Occidental individual that appeared admixed when mapped onto P. pyrifolia ), are shown in gray. “D” and “P” indicate the two main uses of Occidental P. communis cultivars (also called the European pear): dessert and perry, respectively. Leaf labels include the abbreviated (sub)species name, with the final two underlined letters indicating the ISO country code of the sampling location. (e,f) Principal component analysis (PCA) of (e) 113 Occidental (20,263 synonymous and unlinked SNPs mapped onto P. communis ) and (f) 256 Oriental individuals (21,163 synonymous and unlinked SNPs mapped onto P. pyrifolia ), after excluding 17 and 10 “other” individuals, respectively. (g) PCA plot of Chinese cultivated P. pyrifolia sand and white pears, showing separation from more distantly related P. ussuriensis and P. betulifolia . Because P. communis and P. pyrifolia were genetically distinct (Supplementary Figs. 3–15), we analyzed each lineage separately using its respective reference genome to minimize mapping bias (Supplementary Figs. 16–21). Within P. communis , dessert and perry pears formed distinct clusters (Fisher’s exact test p = 1.04 × 10 −7 ), more closely related to wild P. pyraster than P. caucasica ( Fig. 1a,c ,e; Supplementary Note). Several admixed P. pyraster individuals likely represent orchard escapees (Supplementary Fig. 9–13; Supplementary Table 3). Among Oriental pears, we identified nine genetic clusters ( Fig. 1b,d ,f,g; Supplementary Figs. 19–21), corresponding to three wild species and six cultivated groups. The three wild Oriental pear species in China, namely P. pashia , P. ussuriensis , and P. betulifolia (used as rootstocks), possess distinct gene pools. Among these, P. pashia exhibited the highest genetic purity, showing no signs of admixture with any cultivated pear genetic group. P. ussuriensis , distributed in northeastern China, showed relatively low levels of admixture with other Chinese cultivar pear gene pools. By contrast, P. betulifolia showed extensive admixture with the gene pool of Chinese cultivated pears, likely due to its geographical overlap with the major production regions of cultivated pears in China. Among cultivated pears, the gene pools of the white pear and the Japanese pear displayed strong regional differentiation. All white pear accessions are distributed in Hebei, China, and their gene pool showed high admixture with other Oriental pear clusters (Supplementary Fig. 22). The CN-other pears distribute across nearly all production regions of China, overlapping with the other two sand pear clusters, suggesting it may represent the ancestral cluster of all regionally differentiated P. pyrifolia sand pears ( Fig. 1b ). Among Japanese pears, approximately one-third of individuals are admixed, primarily with the Chinese cultivar cluster referred to as CN-other ( Fig. 1b ). The gene pool of sand pears in Eastern China (e.g., Zhejiang Province) showed substantial admixture with that of Japanese pears ( Fig. 1b ; Supplementary Fig. 22). The admixture patterns in Chinese and Japanese pears likely reflect recent breeding activities ( Teng, 2011 ). Overall, population-structure analyses revealed deep divergence and limited admixture between Occidental and Oriental pears, supporting independent domestication histories. After excluding admixed and uncertainly assigned individuals ( Fig. 1c,d ) to minimize the effects of recent breeding-related hybridization and to remove potential escaped cultivars showing introgression into local wild populations, we retained 229 individuals representing 12 Occidental (five) and Oriental (eight) panmictic populations (with N ≥ 7 individuals per population) for demographic and selection analyses (Supplementary Table 4; Supplementary Note). Divergence and demographic histories of Oriental and Occidental pears We reconstructed the evolutionary relationships among the 12 pear populations using SVDQuartet ( Chifman & Kubatko, 2014 ), and the 21,237 SNPs mapped onto the P. pyrifolia reference genome ( Fig. 1a , Supplementary Table 4), and loquat ( Eriobotrya japonica (Thunb.) Lindl.) individuals as an outgroup ( Wang & Paterson, 2021 ). The phylogenetic reconstruction revealed a deep split between Occidental and Oriental pears, confirming that these lineages evolved independently and underwent separate domestication histories ( Fig. 2a ). Within the Occidental clade, P. caucasica formed a distinct branch from P. pyraster and the European pear, P. communis . Nodes within the P. pyraster–P. communis clade exhibited moderate bootstrap support, suggesting incomplete lineage sorting or historical gene flow between wild and cultivated populations. In the Oriental lineage, P. pashia and P. betulifolia were clearly separated from the cultivated P. pyrifolia complex, although relationships among the Asian pears (White, Sand, and Japanese pears) remained weakly resolved, likely reflecting recent divergence and recurrent introgression (see below). To further elucidate these relationships, we tested alternative divergence scenarios using demographic modeling. For this purpose, we first quantified historical gene flow among populations and reconstructed historical effective population size ( N e ) to provide a basis for model optimization. Download figure Open in new tab Figure 2. The demographic history of Occidental and Oriental pear populations. (a) Phylogenetic tree of pear populations under the coalescent model generated using SVDquartets. Standard bootstrap values are shown on the branches. (b,c) Heatmaps of f 4 -ratio statistics by the Dsuite with tree model, along with the corresponding p- value ( p < 0.01), for Occidental (b) and Oriental (c) pear populations. The reference topology trees from (a) shown beside the heatmaps were used as input for Dsuite to arrange the trios. (d,e) Historical changes in effective population size for Occidental (d) and Oriental (e) pear populations inferred using SMC++, assuming a generation time of 7.5 years and a mutation rate of 3.9 × 10 −8 per site per generation. (f,g) The most likely scenarios of domestication and divergence inferred for Occidental (f) and Oriental (g) pear populations. Arrows denote divergence events with associated time estimates; colored lines indicate gene flow, with line color representing the source population. Populations are color-coded based on their fastSTRUCTURE assignments (Supplementary Table 4). Split times were converted assuming a generation time of 7.5 years and are reported from the best-fitting models by AIC. When a split time was inferred in multiple rounds, the minimum–maximum range across the best-fitting model of each round was reported. Country names indicate approximate geographical origins only and do not imply any political position on territorial status. The basemap was obtained from NASA Visible Earth. We quantified historical gene flow using the f 4 -ratio and D -statistics (ABBA-BABA) implemented in Dsuite ( Malinsky et al., 2021 ) with tree mode using P. ussuriensis or P. caucasica as an outgroup for Occidental or Oriental pears, respectively ( Fig. 2b,c ; Supplementary Tables 5,6). Under strict isolation (no gene flow), these statistics approached zero, with divergence explained solely by drift ( Lipson, 2020 ; Reich et al., 2009 ). Significant non-zero values identified multiple episodes of gene flow. In Occidental pears, we detected gene flow between wild and the European pear ( P. pyraster and dessert P. communis ; P. caucasica and perry P. communis ) and between wild populations ( P. caucasica and P. pyraster ). In Oriental pears, we detected gene flow between P. pashia or P. ussuriensis and P. pyrifolia cultivars, but no gene flow between the two wild populations, P. ussuriensis (Ussurian pear) and P. pashia (Himalayan pear), consistent with their geographically distant and isolated distributions. Cultivar–cultivar introgression coincided with low phylogenetic bootstrap support ( Fig. 2a ). Elevated f 4 -ratios between P. betulifolia and white pears likely resulted from the high overlaps of their distribution, enabling recurrent gene flow. We estimated unbiased nucleotide diversity ( π ) for each population and pairwise F ST and d XY for population comparisons using Pixy ( Korunes & Samuk, 2021 ) with SNP and invariant sites data and estimated other demographic parameters using Stacks ( Catchen et al., 2013 ) with SNPs ( Table 1 ; Supplementary Figs. 23,24). In Occidental pears, cultivar populations (dessert and perry P. communis ; π = 5.661 × 10 −3 and 6.044 × 10 −3 ; Wilcoxon rank-sum test, two-sided, p < 0.01) had significantly higher diversity than wild populations ( P. pyraster and P. caucasica ; π = 5.358 × 10 −3 and 4.481× 10 −3 ; p < 0.01). In Oriental pears, P. ussuriensis ( π = 4.168 × 10 −3 ; p < 0.01) had the lowest diversity, while P. pashia ( π = 5.29 × 10 −3 , p < 0.01) was more diverse than white and Japanese pears ( π = 4.833 × 10 −3 and 4.905 × 10 −3 ; p 0.01), but less diverse than sand pears ( π = 5.879 × 10 −3 , 5.857× 10 −3 and 5.982× 10 −3 ; p 0.01). Wild P. betulifolia (represented in our dataset by accessions commonly used as rootstock) showed a relatively high diversity ( π = 5.575 × 10 −3 ; observed heterozygosity H o = 0.217), which is consistent with its wide distribution. The F ST and d XY results revealed a clear genetic differentiation between the Occidental and Oriental pear populations (Supplementary Fig. 24). We also observed variation in linkage disequilibrium (LD) decay rates among populations, as measured by the r ² statistic (Supplementary Fig. 25). Overall, the differences in π , H o , H e , and negative inbreeding coefficient ( F IS ) values suggest that substantial gene flow and only moderate bottleneck effects occurred in most domesticated pears. View this table: View inline View popup Download powerpoint Table 1. Genetic diversity estimates for each population of Occidental and Oriental pears. N = 76; 20,178 Occidental and N= 153; 21,141 Oriental SNPs mapped onto P. communis and P. pyrifolia, respectively, detected with fastSTRUCTURE (excluding 167 admixed individuals that could not be assigned to any cluster with a membership coefficient > 0.8, or non-consensus individuals whose genetic assignment did not match their taxonomic classification). Demographic reconstruction pointed to long-term declines predating domestication and only weak bottlenecks. We used SMC++ ( Terhorst et al., 2017 ) to infer historical N e ( Fig. 2e ). All populations showed prolonged N e declines between ∼1 and 100 thousand years ago (Kya), broadly coinciding with the Last Glacial Period (115–11.7 Kya) ( Corrick et al., 2020 ), followed by stabilization or recovery. The parallel N e trajectories in wild and cultivated populations indicate that domestication imposed at most weak bottlenecks. To reconstruct the domestication history of pear, we performed demographic simulations using fastsimcoal2 ( Excoffier et al., 2021 ) (Supplementary Figs. 26–29). For Occidental pears, the best-fitting model suggested that, following the divergence of the two wild populations ( P. pyraster and P. caucasica ), dessert P. communis was domesticated from P. pyraster , followed by the independent domestication for a specific end-use (i.e., fermentation) of the perry P. communis from the same wild population ( Fig. 2f ; Supplementary Note; Supplementary Fig. 28). The model also supports that continuous bidirectional gene flow occurred between the wild populations P. pyraster and P. caucasica , as well as introgression from the cultivated P. communis dessert pear back into the wild P. pyraster population. For Oriental pears, the best-fitting demographic models were concordant across five independent rounds, each using partially overlapping populations to avoid too complex modeling ( Fig. 2g ; Supplementary Note; Supplementary Fig. 27,29). Assuming that P. pashia (Himalayan pear) as the most ancestral wild species ( Liu et al., 2013 ; Teng et al., 2018 ; Zheng et al., 2014 ), we inferred that the P. pyrifolia sand CN-SW and sand CN-SE populations underwent regional post-domestication diversification from the cultivated P. pyrifolia sand CN-other, after the latter had been domesticated from P. pashia ( Fig. 2g ; Supplementary Fig. 29). This topology suggests that sand CN-other represents the most ancestral population among the three sand pear ( P. pyrifolia ) populations, even though sand CN-SW is geographically closest to the native region of P. pashia , the Himalayan pear. By contrast, the white pear population formed a relatively independent rise lineage branching alongside the sand CN-other population ( Fig. 2 ; Supplementary Figs. 27,29). Notably, we tested alternative models for the origin of Japanese P. pyrifolia , including divergence from the Chinese sand pear populations and direct domestication from P. pashia . The model with domestication from P. pashia received stronger support based on AIC values, indicating that Japanese pears were domesticated independently from P. pashia rather than derived from the Chinese sand pear P. pyrifolia ( Fig. 2g ; Supplementary Figs. 27,29). Simulations indicated that the divergence between Occidental cultivars and their wild relatives likely occurred approximately 502 generations ago, and that between Oriental cultivars and wild populations occurred 522–717 generations ago (Supplementary Table 7). Assuming an average generation time of 7.5 years and a Wright–Fisher population model while accounting for migration, these numbers correspond to divergence times roughly occurring 3.8 and 3.9–5.4 Kya, respectively. The Oriental pears were likely domesticated a bit earlier than the Occidental pears, but those estimates should be taken cautiously. Together, diversity estimates, phylogenetic analyses, and demographic modeling revealed that Pyrus evolution has involved deep divergence between Occidental and Oriental lineages, multiple domestication origins, long-term N e fluctuations predating domestication, and recurrent gene flow among wild and cultivated populations. Signatures of positive selection during domestication in the pear genomes Because pear cultivars were structured based on their use in European pears (dessert vs. perry P. communis ) and based on geography in Asian pears ( P. pyrifolia populations), and as domestication proceeded largely in parallel, and assuming that cultivar adaptation occurs mainly via domestication, we expected to detect population-specific sweeps with limited sharing across lineages. We investigated footprints of positive selection in the genomes of Occidental and Oriental pears using two complementary sweep statistics: ω (OmegaPlus) and unbiased Tajima’s D (Pixy) statistics ( Alachiotis et al., 2012 ; Bailey et al., 2025 ). Across the 12 populations, including wild and cultivar, we detected 371–640 candidate genes in selective-sweep regions ( Fig. 3 ; Supplementary Figs. 30–41 and Supplementary Tables 8–12). Download figure Open in new tab Figure 3. Signatures of positive selection in Occidental and Oriental pears and domestication footprints. (a) Population color key used across all panels. (b, c) Intersection counts of genes under positive selection within and among Occidental (b) and Oriental (c) pear populations; only intersections containing >3 genes are shown. (d–g) Genome-wide scans for selective sweeps in four representative populations: (d) P. communis ‘dessert’, (e) P. communis ‘perry’, (f) P. pyrifolia ‘white CN’, and (g) P. pyrifolia ‘Nashi JP’. Positive selection was inferred using Tajima’s D (Pixy; triangles) and ω (OmegaPlus; circles) statistics from SNPs mapped to the reference genome for each species. Centromeric and low-mappability regions were excluded to reduce false positives. Each point represents a statistic in a sliding window; horizontal lines indicate the optimized cutoffs (99.45th percentile for ω , 0.40th percentile for Tajima’s D ) determined by 1,000 permutations in regioneR. Tajima’s D values were rescaled for visualization. Points with extremely low μ or ω were omitted. For P. pyrifolia panels, chromosome numbers were reassigned to the P. communis reference using MCScanX and minimap2 synteny. Gene labels show official NCBI symbols when available; a white background indicates a gene shared with ≥1 other cultivar population, and an asterisk denotes a duplicated gene or gene family. Most positively selected genes were specific to a single population rather than shared with any other populations, as expected ( Fig. 3a,b ; Supplementary Figs. 40,41; Supplementary Tables 8,9). Among the relatively small subset of shared candidates, overlaps between closely related populations likely reflect ancestral polymorphisms that have been subject to selection. Notably, the wild species P. pashia shared most genes in selective sweep regions with P. pyrifolia cultivar populations, more than those P. betulifolia and P. ussuriensis shared with P. pyrifolia , suggesting that the wild Himalayan pear, P. pashia , located in Southwest China, might have contributed to the early domestication of Asian pears ( Fig. 3c ; Supplementary Fig. 41). In cultivated pears, selective-sweep regions encompassed genes involved in metabolism, fruit quality, use traits, and defense, as well as adaptation to biotic/abiotic stress ( Fig. 3d–g ). European and Asian pears mainly differ in postharvest ripening phenology and in fruit shape, supposedly involving distinct footprints of domestication. Gene Ontology of lineage-specific genes enrichment highlighted contrasting functional profiles between lineages, with Occidental pears being primarily enriched in growth, lipid metabolic, and fruit development processes (Supplementary Table 10), while Oriental pears exhibited a predominance of abiotic and oxidative stress–related terms (Supplementary Table 11). Despite their different end uses, dessert and perry P. communis populations shared 40 candidate genes within selective-sweep regions ( Fig. 3d,e ). These genes include BARELY ANY MERISTEM 3 ( BAM3 ; pycom05g17790) and GASSHO1 ( GSO1 ; pycom05g17800, pycom05g17770), encoding leucine-rich repeat receptor-like kinases that may affect fruit peel structure and contribute to disease resistance ( Tsuwamoto et al., 2008 ). Population-specific selective-sweep regions in the dessert P. communis contained genes implicated in flavor/texture pathways, including BETA GLUCOSIDASE ( BGLU3 ; pycom05g32120), BGLU13 (pycom08g12030), and LIPOXYGENASE 1 ( LOX1 ; pycom04g18070); Selective-sweep regions in the perry P. communis population comprised genes involved in cell-wall biosynthesis and modification, including the pectin biosynthetic gene GALACTURONOSYLTRANSFERASE 6 ( GAUT6 ; pycom07g00090), the cellulose synthase genes CSLC12 (pycom15g06110, pycom15g06120) ( Fig. 3e ). For Asian pears, we identified genes under selection associated with fruit quality and the footprint of adaptation to the abiotic environment in Japan ( Fig. 3f, g ). White pear sweep regions were enriched for cell-wall remodeling genes, which is consistent with their crisp texture and low stone cell content: EXPANSIN 8 ( EXPA8 ; GWHGBAOS027806), CINNAMYL ALCOHOL DEHYDROGENASE 1 ( CAD1 ; GWHGBAOS027804, GWHGBAOS027805). These regions also contained genes encoding regulators of pigment/phenolic contents: MYB113 (GWHGBAOS028351) and CYTOCHROME P450 97A3 ( CYP97A3 ; GWHGBAOS028374) ( Fig. 3f ). In Japanese pear, selective-sweep regions included genes involved in plant adaptation to humid, mild monsoon climates while maintaining fruit quality, such as genes related to hydraulics and osmotic regulation ( PLASMA MEMBRANE INTRINSIC PROTEIN 1 [ PIP1 ], GWHGBAOS012726; PHOSPHATIDYL INOSITOL MONOPHOSPHATE 5 KINASE 9 [ PIP5K9 ], GWHGBAOS008238) ( Fig. 3g ). Across both Asian and European pears, sweep intervals were enriched for genes encoding Nucleotide-binding site–leucine-rich repeat ( NBS-LRR ) ( Fig. 3d–g ). The genetic burden during pear domestication To assess whether domestication altered the burden of putatively deleterious variants, we annotated nonsynonymous SNPs in both lineage-matched references ( P. communis and P. pyrifolia ) using the ‘sorting intolerant from tolerant’ algorithm (SIFT4G) ( Vaser et al., 2016 ). Genome-wide, except for the perry P. communis population, cultivated populations carried a lower frequency of deleterious variants than their wild relatives. Within the Oriental lineage, wild populations exhibited the highest deleterious burden, whereas P. pyrifolia Japanese cultivars showed lower levels of deleterious variants than Chinese cultivars, consistent with the independent domestication trajectory of Japanese pears ( Fig. 4a ; Supplementary Table 13). These patterns run counter to the simple “cost-of-domestication” ( Lu et al., 2006 ) hypothesis and suggest that long-term gene flow and/or selection may have constrained the accumulation of mildly deleterious alleles in most cultivated pears. Download figure Open in new tab Figure 4. The genetic burden during pear domestication. (a) Number of deleterious mutations (SIFT score < 0.05; SNPs or fixed sites) per 100 kb of coding sequence in each population, using P. communis and P. pyrifolia as reference genomes for the Occidental and Oriental pear populations, respectively. Stars above boxplots indicate significant differences between cultivar and wild/rootstock populations. Different letters above boxplots indicate significant differences (Wilcoxon test, Holm-adjusted, p < 0.01) in the number of deleterious alleles among populations. Comparisons were performed separately for the Occidental and Oriental populations. (b) Comparison between selection sweep regions and control regions (the rest of the genome after masking low-mappability regions). (c) Comparison of deleterious mutations between homozygous and heterozygous (half-black boxes represent heterozygous mutations) states. (d) Comparison of homozygous deleterious mutations between selection sweep regions and control regions. Boxplot elements: center line, median; box limits, 25th and 75th percentiles; whiskers, extending to the most extreme data point within 1.5 × the interquartile range from the box; points, individual data. Source data are provided in Supplementary Table 12. Significance levels (Wilcoxon test): ns, p > 0.05 (not significant); * p ≤ 0.05; ** p ≤ 0.01; *** p≤ 0.001; **** p ≤ 0.0001. When we compared selective sweeps versus matched controls, in cultivated populations, selective-sweep regions harbored fewer deleterious variants than control regions (two-sided Wilcoxon tests; Fig. 4b ; Supplementary Table 13), which is consistent with the sweep of linked deleterious alleles during positive selection. By contrast, in wild populations, homozygous deleterious variants were enriched within sweep intervals relative to the controls. However, in dessert and perry P. communis populations and P. pyrifolia Japanese cultivars, homozygous deleterious variants were depleted within the sweep regions ( Fig. 4c ; Supplementary Table 13). These contrasting results indicate that selection episodes during cultivation reduced the local deleterious load at targeted loci relative to that in their wild backgrounds. Across all populations, heterozygous deleterious variants were more common than homozygous ones ( Fig. 4d ; Supplementary Table 13; Supplementary Fig. 42), as expected under purifying selection and outcrossing. The shift toward fewer homozygous deleterious genotypes in sweeps across cultivated populations further supports the notion that selection-associated purging occurred in these intervals. Overall, cultivated pears, apart from the perry P. communis , exhibited a lower deleterious burden than wild populations, and sweep regions in cultivars were depleted of deleterious variants relative to the controls. These results are consistent with the notion that positive selection reduced the number of linked deleterious alleles during domestication. Roles of transposable elements in pear domestication We detected 13,574 reference and 169,796 non-reference TIPs across the four Occidental populations, compared with 12,064 and 203,296, respectively, in the eight Oriental populations (Supplementary Fig. 43,44). Neutral unlinked and synonymous SNPs showed higher variation in Oriental pears (the first principal component was 46.4%) than in Occidental pears (18.1%), while TE insertions explained less variation (∼10%) in whatever the populations. These patterns suggest that population structure was mainly driven by neutral variation rather than by TEs. In both populations, the wild species ( P. caucasica in the Occidental lineage and P. ussuriensis in the Oriental lineage) formed well-defined clusters for both markers. Most admixed individuals were positioned close to the clusters of cultivated accessions in both Occidental and Oriental lineages. However, in the Occidental populations, admixed individuals particularly clustered near their wild relative P. pyraster in the TE-based PCA plot, suggesting that relatively recent introgression might have occurred between the wild and the cultivated species ( Wolko et al., 2014 ). By contrast, in the Oriental population, admixed individuals consistently grouped with cultivated species regardless of the marker used ( Figs. 5a , b). Download figure Open in new tab Figure 5: Shared and fixed transposable elements insertions in Occidental and Oriental pear populations. Throughout the figure, the left panels (a,c,e) correspond to Oriental populations, while the right panels (b,d,f) correspond to Occidental populations. (a, b) PCA plot based on TE insertions (left) and SNP variation computed with PLINK2 (right). (c, d) Heatmaps showing the ratio of shared versus fixed insertions for each TE order, grouped into Class I (retrotransposons) and Class II (DNA transposons). Each cell indicates the number of shared and fixed insertions within a population, with color gradients reflecting the shared/fixed ratio (0–1). Above each heatmap, phylogenetic trees depict relationships among populations from SVDquartets. Population colors represent wild (green), cultivated (blue), and rootstock (orange) accessions. (e, f) UpSet plots showing TE polymorphisms located 2 kb upstream of genes under positive selection. The distribution of Rho ( ρ ) represents an approximation of the recombination rate across the genome. The TE density was calculated using a 50-kb window (number of base pairs annotated as TE per window). To improve visualization clarity, the TE orders were divided into two separate panels. In the Oriental pear dataset, only the 20 largest intersections were displayed to enhance clarity. DIRS, Dictyostelium intermediate repeat sequence; LARD, Large Retrotransposon Derivative; LINE, Long Interspersed Nuclear Element; LTR, Long Terminal Repeat; SINE, Short Interspersed Nuclear Element; TRIM, Terminal repeat Retrotransposon in Miniature; Helitron, Helitron transposon; MITE, Miniature Inverted repeat Transposable Element; TIR, Terminal Inverted Repeat. Wild populations exhibited lower shared/fixed ratios across most TE orders ( Fig. 5c, d ), reflecting lineage-specific TE that likely inserted after the divergence of wild and cultivated populations. Conversely, cultivated populations showed elevated shared/fixed ratios ( Fig. 5c,d ), suggesting greater sharing of TE insertions among cultivars, either inherited from their progenitor or promoted more recently by hybridization and gene flow. Among TE orders, Large Retrotransposon Derivatives (LARDs) and Short Interspersed Nuclear Elements (SINEs) consistently displayed high shared/fixed ratios in both Occidental and Oriental pears, with slightly more pronounced ratios in the latter ( Fig. 5c,d ). This pattern aligns with their known biology: both are non-autonomous elements that rely on the enzymatic machinery of autonomous retrotransposons (Long Terminal Repeats and Long Interspersed Nuclear Elements; LTRs and LINEs, respectively), yet, whereas LARDs represent clear ancient relics, SINEs may include a mixture of old and more recently active elements (Weiner 2002; Kalender et al., 2004). Helitron insertions are more abundant in Oriental pears ( Figs. 5c-f ), where many appear recent and population-specific, which may reflect a lineage-specific accumulation or retention of these elements. We identified 2,596 TIPs located within the 2-kb regions upstream of genes under positive selection in the Occidental pear populations and 2,411 in the Oriental pear populations ( Figs. 5e,f ; Supplementary Tables 14,15), suggesting that TEs might have contributed to regulatory variation in domestication-related loci. Among these, 1,301 out of 2,155 positively selected genes in Occidental populations (60%) and 2,238 out of 3,527 in Oriental populations (63%) harbor at least one upstream TIPs. We then focused on immunity-related genes under positive selection, including the NBS-LRR loci ( Jia et al., 2015 ; Lv et al., 2022 ) and EF-TU RECEPTOR ( EFR ) loci (Vuong et al., 2022). The lowest proportion of immunity-related genes occurs in the intersection of TE insertions shared exclusively by perry and dessert P. communis ( Fig. 5e ; Supplementary Table 14), whereas the highest proportion is found in intersections of TE insertions that exclude perry P. communis ( Fig. 5e ; Supplementary Table 14). This pattern suggests that perry P. communis has lost multiple ancestral TE insertions upstream of immunity genes under positive selection, highlighting a distinct, lineage-specific evolutionary trajectory at these immunity loci. Dessert cultivars have historically been selected for fruit appearance, texture, and flavor rather than disease resistance (Bell et al., 2014), which may have influenced the selective landscape of some immunity loci. Discussion We leveraged whole-genome resequencing data from 396 pear accessions, combined with lineage-matched reference genomes for P. communis and P. pyrifolia , to reconstruct the mode and tempo of pear domestication. By integrating SNP- and TIP-based analyses, we refine the domestication narrative of this woody perennial crop, particularly the contrasting within-region domestication trajectories in Europe and Asia. Consistent with long-standing hypotheses, our results indeed confirm that cultivated Occidental and Oriental pears arose through independent domestication events ( Wu et al., 2018 ; Zheng et al., 2014 ). Beyond validating this bifurcated origin, our findings reveal multiple domestications within lineages accompanied by sustained gene flow with wild relatives, and population-specific adaptation targeting immunity, cell wall, carbohydrate metabolism, and ripening pathways. Recurrent independent domestications with extensive gene flow and no bottlenecks Our sampling offers a broad and balanced coverage of both wild and cultivated accessions from the two main domesticated lineages, comprising 130 Occidental and 266 Oriental accessions (including 42 wild Occidental and 51 wild Oriental pears). This sampling, together with coalescent-based modeling, adds a new layer of resolution to the independent domestication events between Occident and Orient. We revealed that pear domestication occurred under weak demographic bottlenecks, extensive wild–cultivated gene flow, and successive independent domestications within both Occidental and Oriental lineages. Historical N e estimates showed no severe or prolonged reductions, supporting the view that perennial domestication—characterized by vegetative propagation, long generation times, and continuous gene flow—did not erode genetic diversity as observed in annual crops ( Cornille et al., 2014 ; Gaut et al., 2015 ; Purugganan, 2019 ). The divergence between cultivated and wild pears occurred approximately 3.8–5.4 thousand years ago, consistent with archaeological and genetic evidence placing domestication between 2,000 and 4,000 years ago ( Silva et al., 2014 ; Teng et al., 2002 ; Zhang et al., 2021 ). These estimates likely reflect population separation rather than precise domestication times, as true wild progenitors remain uncertain and overlapping generations complicate temporal inference. Our results also indicate that wild P. pashia and P. pyraster were key contributors to the genomes of Asian and European pears, respectively. However, the identity of the true wild progenitors remains unresolved, and broader sampling of verified wild populations—now threatened by habitat loss and introgression ( Teng et al., 2018 ; Wagner & Wagner, 2025 )—will be required to confirm these relationships. So far, despite extensive field surveys over recent years, we have not identified any truly wild populations of P. bretschneideri or P. pyrifolia , implying that such wild forms may be extinct or no longer extant in nature. Our analyses also revealed genetic divergence related to use in the European pears, as seen in the apple tree ( Cornille et al., 2012 ). In the Oriental pear, the subdivision of P. pyrifolia into three cultivar populations—the White Pear, Sand Pear, and Japanese Pear ( Bao et al., 2008 ; Teng et al., 2021 ) —was well-founded, but has received insufficient attention from a genetic perspective up to our study. Our genome-wide analyses placed white pears within the P. pyrifolia complex, closely related to sand and Japanese pears. Comparison with previously published datasets revealed that the “wild P. bretschneideri ” reported by ( Li et al. 2019 ) is genetically admixed with white pear cultivars in our study, likely reflecting feral escapes from cultivation. Similarly, the “ P. bretschneideri ” accessions described by ( Wu et al. 2018 ) appear to be clonal to our P. pyrifolia samples, suggesting they represent the same cultivar types rather than a distinct species. While the taxonomic status of “Chinese white pear” has been debated, it is variously treated as P. bretschneideri or as a subgroup within P. pyrifolia ( Bao et al., 2008 ; Li et al., 2019 ; Wu et al., 2013 ). Our results, therefore, show that pear genomes are a genomic mosaic—a product of parallel domestication, with recurrent gene flow between wild and cultivated populations. The domestication pace was therefore gradual and spatially diffuse ( Allaby, 2010 ), rather than abrupt or centrally driven. Contrasting selection histories shaped by use and environments Our analyses disentangle the specific selective pressures within each lineage, revealing distinct drivers of domestication. In the European pears, domestication was primarily driven by use. The dessert and perry P. communis originated independently from P. pyraster , with the dessert type emerging first, followed by the perry type, which was adapted for fermentation ( Ripe, 2009 ). These lineages underwent divergent selective pressures: dessert pears showed selection on BGAL3 , BGLU , and LOX genes, which regulate fruit softening, sugar metabolism, and aroma ( Li et al., 2014 ; Mwaniki et al., 2005 ; Wang et al., 2022 ); perry pears displayed selection on the GAUT6 and CSLC genes, which control cell-wall biosynthesis and firmness ( Kim et al., 2020 ; Lund et al., 2020 ). Such patterns indicate functional specialization linked to fruit use and processing. European pears soften after harvest, developing a “melting” texture, whereas Asian pears remain crisp without further softening, often bearing round, apple-like fruits. We hypothesized that these differences arise from selection for developmental regulators. Indeed, selective-sweep regions in Occidental dessert P. communis contained β-GALACTOSIDASE 3 ( BGAL3 ; pycom08g01840), which is consistent with the known role of β-galactosidase in regulating fruit softening during ripening in pear ( Mwaniki et al., 2005 ). By contrast, selective-sweep regions in Oriental P. pyrifolia contained homologs of TONNEAU1-RECRUITING MOTIF ( TRM ; GWHGBAOS004556), which are key fruit-shape determinants in other crops (tomato [ Solanum lycopersicum ] and melon [ Cucumis melo ]) ( Wu et al., 2018 ). In the Oriental lineage, domestication was mostly geographically structured. Within P. pyrifolia , Chinese sand, white, and Japanese pears diverged through successive or independent domestication events, shaped by both environmental and human selection pressures. Japanese P. pyrifolia followed an independent domestication trajectory separate from Chinese P. pyrifolia , with selective sweeps involving PIP1 , AVP1 , and CRY3 —genes associated with water balance, osmotic regulation, and photoperiodic response ( Brini et al., 2007 ; Chaumont & Tyerman, 2014 ; Kleine et al., 2003 )—consistent with adaptation to Japan’s humid monsoon climate (Uchiyama et al., 2025). In contrast, Chinese sand and white pears exhibit genetic continuity with P. pashia but show evidence of introgression and successive domestication, reflected in texture- and pigment-related genes homologs such as EXPA , CAD , and MYB113, CYP97A3 ( Cheng et al., 2017 ; Gonzalez et al., 2008 ; Huang et al., 2024 ; Ireland et al., 2014 ; Yao et al., 2017 ). Occidental domestication emphasized human use and fruit quality, whereas Oriental domestication integrated both fruit quality and local ecological adaptation. Selection scans among Oriental and occidental pears converged on immunity and fruit-quality genes as well. Sweep intervals were enriched for NBS-LRR and receptor-like kinase genes in both the Occidental and Oriental lineages, which is consistent with recurrent selection for disease resistance under orchard conditions ( Jia et al., 2015 ; Lv et al., 2022 ). We detected lineage-specific selective sweeps, including TRM homologs (fruit-shape regulators) in Oriental P. pyrifolia aligning with its round fruit shape ( Wu et al., 2018 ); and BGAL3 (cell-wall remodeling/softening) in European dessert P. communis , consistent with the melting texture of dessert pears ( Mwaniki et al., 2005 ). These loci provide tractable targets for positive selection and functional validation in pear breeding. Genetic load and the absence of a cost of domestication Our analyses of genetic load further illustrate how perennial domestication diverges from annual models ( Gaut et al., 2018 ). Contrary to the “cost-of-domestication” hypothesis ( Lu et al., 2006 ), cultivated pears—except P. communis perry—harbored fewer deleterious variants than their wild relatives. Selective-sweep regions in Occidental cultivars contained fewer deleterious alleles than matched controls, implying that positive selection efficiently purged linked mutations. In Oriental pears, however, sweep regions harbored slightly higher burdens, suggesting that historical admixture may have weakened purifying selection. Both lineages displayed reduced homozygous deleterious genotypes, consistent with the maintenance of high heterozygosity through outcrossing and vegetative propagation. Overall, these results echo patterns in other perennials, such as apple, where gene flow and selection jointly reduce deleterious load ( Chen et al., 2025 ), reinforcing that perennial domestication can favor purging rather than accumulation of mutations. TE variations shaped by demography with limited adaptive impact Genome-wide variation in TEs was shaped primarily by demographic history, yet notable cases of TIPs occur within selective-sweep regions, suggesting a potential role in adaptation. A handful of loci illustrate the functional relevance of these insertions. A TE located near PE11 was shared across sand CN-other, Japanese, and white pear populations, suggesting an insertion event that potentially affects the function of PE11 protein that associates with pectin metabolism and fruit texture ( Hiwasa et al., 2004 ); functional validation will be necessary to confirm this link. Divergent insertions detected near the same NBS-LRR locus (∼21.5 kb apart) in distinct populations (white, sand CN-other, and sand CN-SW) further suggest independent TE histories that may alter local recombination dynamics or transcriptional regulation. Overall, TE insertions were found in proximity to genes under positive selection, which pinpoint a role, even minor, in the domestication of both P. communis and P. pyrifolia . Outcomes and perspectives Modern pears represent a genomic mosaic, shaped by parallel but relatively asynchronous domestication, and long-term exchange between wild and cultivated populations. The asymmetry in domestication pace—a bit older and geographically structured in Oriental pears, more recent and use-driven in Occidental ones—highlights that perennial domestication is a gradual, regionally diffuse process driven by both ecological adaptation and cultural selection. Rather than a single linear trajectory, pear domestication reflects a network of locally adapted events interconnected by gene flow and human selection. Our findings position pears ( Pyrus spp.) as a compelling model for studying independent adaptive evolution in perennial crops, where long lifespan, self-incompatibility, and recurrent introgression shape distinctive genomic outcomes ( Alam & Purugganan, 2024 ; Meyer et al., 2012 ; Miller & Gross, 2011 ). Future pangenome-scale resources ( Gao et al., 2021 ; Sun et al., 2025 ) will refine our understanding of the role of structural variants (beyond TEs) and the genomic architecture of introgressions in perennial domestication. Beyond pears, these results highlight how life history, demography, and genome variation collectively influence the evolution of long-lived fruit trees under both human and environmental selection. Methods DNA extraction and short-read sequencing of new genotypes Genomic DNA was extracted from the leaf tissues of 235 new Pyrus samples from 10 (sub-) species, representing wild and cultivated pears (Supplementary Table 1), using a commercial kit (Supplementary Note), followed by sequencing. In addition, raw short-read data for 439 Pyrus individuals were downloaded from the ENA (European Nucleotide Archive) database (Project Accession numbers: PRJNA381668, PRJNA724820, PRJNA563813, and PRJDB5584). In total, data from 674 pear individuals sequenced as short paired-end reads were used for SNP calling. Quality control of whole-genome sequencing data The bioinformatic analysis workflow is shown in Supplementary Fig. 1. To remove insufficient sequences or reads during downstream analysis from all 674 raw paired-end sequencing data sets, fastp version 0.21.0 ( Chen et al., 2018 ) was employed. Based on the fastp default filtering level, our additional targets of sequence trimming included several bases in front of the sequences based on the GC ratio, depending on specific FastQ files. The quality of clean reads was validated using FastQC v0.11.8 ( https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ) and MultiQC v1.18 ( Ewels et al., 2016 ). SNP calling and joint genotyping of invariant sites Clean reads (totaling 674 individuals) were aligned to the reference genome “ Pyrus pyrifolia Cuiguan Genome v1.0” ( Gao et al., 2021 ) using bwa-mem2 v2.2 ( Vasimuddin et al., 2019 ). This reference was chosen due to its highest quality. The read alignments were sorted using SAMtools v1.14 ( Danecek et al., 2021 ), and duplicate reads were marked using Genome Analysis Toolkit (GATK) v4.1.9.0 ( McKenna et al., 2010 ). All steps (read alignment, mapping, and duplicate marking) were automated in a custom wrapper script. Variant calling was performed using the GATK HaplotypeCaller Tool. Along with variant calling by GATK, invariant (monomorphic) sites data were also prepared and filtered to combine all datasets to calculate π and d XY . A set of 29,826,531 SNPs was ultimately obtained. Horizontal SNP filtering: removing low-quality markers The variant filtering strategy was designed to operate in two complementary dimensions: horizontal (filter out specific sites) and vertical (exclude entire individuals that fail quality thresholds). Horizontal filters were applied to the raw variant files using GATK VariantFiltration, GATK SelectVariants tools (GATK version 4.1.9.0), and bcftools filter command (version 1.14) ( Danecek et al., 2021 ) as described previously ( Chen et al., 2025 ). Variants were excluded if they met any of the following criteria: i) SNPs with a ReadPosRankSum score < −8.0 or InDels/mixed variants with a score 60.0 or Strand Odds Ratio (SOR) > 3.0, and InDels/mixed variants with FS > 200.0 or SOR > 10.0, were excluded, as these indicate potential sequencing or alignment artifacts. iii) SNPs with a Mapping Quality (MQ) score < 40.0 or an MQRankSum < −12.5 were removed, as they reflect poor or biased read mapping. iv) SNPs, InDels, or mixed variants with an overall quality (QUAL) score < 30.0 were excluded. Only biallelic SNPs were retained, assuming the pear individuals are diploid, and additional genotype-level filters were applied to ensure reliable calls. Specifically, for each genotype, sequencing depth (DP) had to be between 3- and 100-fold, genotype quality (GQ) had to be ≥ 20, and SNPs within 10 bp of any InDel were excluded. Equivalent filtering for invariant sites replaced GQ with the reference genotype quality score (RGQ ≥ 20). Vertical SNP filtering: removing individuals For vertical filtering, potential issues stemming from clones or closely related samples in our dataset were mitigated. Colonies, mutants, and synonyms are common phenomena in Pyrus germplasm and collections from herbaria, botanical gardens, and gene banks. However, previous studies have not adequately addressed these issues ( Wu et al., 2018 ; Zhang et al., 2021 ). Therefore, the pairwise KING kinship coefficients were computed, using Plink2 v2.0_alpha2 ( Manichaikul et al., 2010 ) for all sample pairs, and a pruning list was generated for samples based on a coefficient cutoff of 0.354. A custom script was used to improve this pruning list, prioritizing the removal of samples with a higher rate of missing variants between each pair of closely related samples. The objective was to ensure that all KING-robust coefficients for every pair of samples in our dataset remained below the cutoff. Samples with a missing rate >40% (indicating lower sequencing coverage) were also excluded (Supplementary Fig. 2). Moreover, individuals with ambiguous passport information were excluded from the dataset. After applying the vertical filtering procedures, an SNP dataset of 17,769,455 variants was obtained from 396 non-clone individuals (out of an initial 674), all with missing rates < 20%. Further filtering of SNPs: lowering LD and selection effects The full SNP dataset was further filtered to obtain a non-selected, unlinked set for population structure and demographic analyses. Variants under potential selection, including nonsynonymous and linked sites, were excluded. After applying a 5% minor allele frequency filter, removing nonsynonymous variants, and thinning to one SNP per 8 kb using PLINK v1.9 ( Purcell et al., 2007 ), 21,752 unlinked SNPs from 396 individuals mapped to the P. pyrifolia reference genome were retained. Variant annotation was performed with SnpEff v5.1 ( Cingolani et al., 2012 ). SNP markers mapped onto the Occidental pear genome To account for the pronounced genomic divergence between Occidental and Oriental pears (Supplementary Note), SNP calling and filtering were repeated for the 396 non-clonal individuals using the “ P. communis Bartlett DH v2” reference genome ( Linsmith et al., 2019 ). Sequencing depth, genome coverage, and heterozygosity ( H ₒ) were compared between the two lineages when reads were mapped to either reference (Supplementary Figs. 9, 10). Unless otherwise stated, analyses were based on lineage-matched reference assemblies. Inference of population genetic structure with passport information The (sub-)species names, regions, and type information (wild, cultivar, or rootstock) of pear samples were obtained from the samplers or from the original data sources. Wild (and rootstock) pears were classified as Occidental or Oriental according to their native distributions, with the Tianshan-Hindu Kush Mountains serving as the biogeographical boundary. Wild populations from Central Asia and regions further west, including Asia Minor, Europe, and the Mediterranean, were designated as Occidental, whereas those confined to East Asia were designated as Oriental. A more conservative approach was used for cultivated pears, assigning them to Occidental or Oriental lineages primarily based on their genetic affinities (derived from gene pool structure, phylogenetic, and PCA) rather than their current cultivation regions, which may reflect human-mediated dispersal (Supplementary Table 1). Population structure and admixture were inferred using the variational Bayesian framework fastSTRUCTURE ( Raj et al., 2014 ). The number of clusters ( K ) ranged from 2 to 16, with 30 replicates per K . Results were consolidated using CLUMPAK ( Kopelman et al., 2015 ) and visualized using PopHelper ( Francis, 2017 ) ( Fig. 1a,b ; Supplementary Figs. 4, 11, 16; Supplementary Tables 2,3). The optimal K was determined by inspecting cross-validation errors around the plateau (“elbow”) and by visually assessing cluster consistency across K values (Supplementary Figs. 4–6, 11–13, 16–18; Supplementary Note) rather than relying solely on Δ K ( Puechmaille, 2016 ). 1–IBS distance matrices were computed with PLINK v1.9, and Neighbor-Net trees were visualized using SplitsTree4 v4.18.3 ( Huson & Bryant, 2006 ) ( Fig. 1c,d ; Supplementary Figs. 7, 14). Principal component analysis (PCA) was performed in PLINK and the results plotted using ggplot2 ( Wickham, 2009 ) ( Fig. 1e–g ; Supplementary Figs. 8, 15). Consistent color schemes were used across analyses, with admixed individuals (membership < 0.8) shown in gray. Color palettes were carefully refined for accessibility using Adobe Color (Supplementary Fig. 3). Using fastSTRUCTURE, 14 genetic clusters were identified across Occidental and Oriental pears ( Fig. 1a,b ). Clusters with < 5 conspecific individuals were excluded, and discordant outliers between fastSTRUCTURE and Neighbor-Net were removed ( Fig. 1a–d ), yielding 12 well-supported populations. Occidental populations were cross-validated using SNPs mapped to both the P. communis and P. pyrifolia references (Supplementary Figs. 11–18; Supplementary Tables 2–4). After excluding hybrids and poorly documented accessions, 229 individuals with ≥ 80% ancestry assignment were retained for downstream population-level analyses ( Table 1 ; Supplementary Table 4). Estimating genomic diversity and differentiation Low-mappability and centromeric regions were masked prior to demographic inference. Mappability profiles for both reference genomes were generated with GenMap ( Pockrandt et al., 2020 ) using 140-bp k-mers ( k = 140, e = 0). Mean mappability was calculated in 100-kb windows (50-kb step) with a custom script; windows with mean > 0.9 were retained as high-mappability. These windows comprised 62% of the P. pyrifolia and 72% of the P. communis genomes. Centromeric regions inferred with CentIRE ( Xu et al., 2024 ) overlapped with low-mappability regions in both assemblies. Pairwise nucleotide diversity (π) ( Nei & Li, 1979 ), genetic distance ( d XY ) ( Nei and Li 1979 , Wakeley, 2016), and differentiation ( F ST ) (Weir and Cockerham 1984) were estimated using Pixy v1.2.7.beta1 ( Korunes & Samuk, 2021 ) on “all-sites” VCFs restricted to high-mappability windows (Supplementary Figs. 23,24). Normality was tested using Anderson–Darling and Shapiro–Wilk tests ( p < 0.05), and π differences among populations were tested using the Wilcoxon test ( p < 0.01). Genome-wide values were computed from total pairwise differences rather than window averages. Observed ( H ₒ) and expected ( H ₑ) heterozygosity (Nei, 1 973), along with the inbreeding coefficient ( F IS ), were calculated using Stacks Populations v2.65 ( Catchen et al., 2013 ). Phylogenetic species tree construction and historical demography inference The population-wide phylogenetic tree was revised using SVDquartets implemented in PAUP version 4.0a ( Chifman & Kubatko, 2014 , 2015 ) with standard bootstrap tests ( Fig. 2a ). The historical N e was analyzed using SMC++ ( Terhorst et al., 2017 ), assuming a mutation rate of 3.9×10 −8 mutations per site per generation and 7.5 years per generation ( Li et al., 2022 ), and multiple EM-iterations were performed 50 times ( Fig. 2d,e ). D -statistics (Patterson’s D , ABBA-BABA) and the f 4 -ratio test via DtriosParallel of Dsuit ( Malinsky et al., 2021 ) were used to estimate the genome introgression between pear populations. Demographic modeling based on site frequency spectrum (SFS) To investigate the demographic history of pear populations, fastsimcoal28 ( Excoffier et al., 2021 ) was employed, informed by the phylogenetic topology inferred from SVDquartets, Neighbour-net, F ST, d XY , and gene flow signals were identified based on D -statistics and f 4 -ratio. For Occidental pears, alternative divergence and gene flow scenarios were explored between wild and cultivated populations (Supplementary Fig. 26). Three divergence scenarios were designed covering the two cultivar populations (dessert and perry P. communis ). Under each scenario, a set of nine demographic models was constructed combining possible gene flow between wild P. pyraster and P. caucasica , with or without gene flow between wild and cultivar populations, yielding 30 alternative models (Supplementary Fig. 26). For Oriental pears, to keep the simulations computationally tractable, five rounds of analysis were performed, with each round containing four or five populations, to test candidate phylogenetic relationships and gene flow. In Rounds 1 and B1, sand CN-SW or sand CN-SE was modeled together with sand CN, P. pashia , and P. betulifolia to test the most ancestral sand pear ( P. pyrifolia ) population. In Rounds 2 and B2, based on the best-fitting model from the first two rounds, the Japanese cultivar population was added to test its origin and possible gene flow (Supplementary Fig. 27). In Round C1, various scenarios were tested, including white pear together with sand CN, P. pashia, and P. betulifolia. Each round included models with and without gene flow, resulting in a total of 111 alternative models (Supplementary Figs. 26,27). All the folded two-dimensional site frequency spectrums (SFS) were generated from SNPs using easySFS (option: - a) ( Coffman et al., 2016 ; Gutenkunst et al., 2009 ). Each model was optimized through 50 independent runs with parameters including 100,000 coalescent simulations per likelihood estimation (-n 100,000), 40 cycles of the conditional maximization algorithm (-L 40), and a minimum of 10 observed SFS entries for likelihood calculation (-C 10). The best-fitting model from these runs was identified based on Akaike’s information criterion (AIC) ( Akaike, 1974 ). Detection of positive selection signatures Positive selection during domestication leaves distinct genomic footprints in LD, the SFS, and patterns of diversity. Because selection can generate both peaks and troughs in diversity ( Jasper & Yeaman, 2024 ), complementary statistics were combined rather than relying solely on diversity-based measures (e.g., F ST , π ). Selective sweeps were detected using ω from OmegaPlus v3.0.3 ( Alachiotis et al., 2012 ) and unbiased Tajima’s D from Pixy v2.0.0beta8 ( Bailey et al., 2025 ). SNP datasets were mapped to lineage-matched references ( P. communis for Occidental, P. pyrifolia for Oriental), masking low-mappability and centromeric regions. For OmegaPlus, the grid number was set to one-thousandth of chromosome length (∼1 kb size), with 10–200-kb window limits. Candidate regions above the 95th–99.9th percentile of ω were retained after excluding regions with >20% overlap with low-mappability or centromeric regions (Supplementary Figs. 31–34). Pixy estimated Tajima’s D from “all-sites” VCFs in 1-kb windows, excluding sites with >20% missing data; outliers were defined from the 0.1–5% left tail (Supplementary Figs. 35,36). Candidate genes were defined as those whose coding or 1-kb upstream regions overlapped with outlier regions. Thresholds ( ω > 99.45th percentile; Tajima’s D < 0.40th percentile) were chosen based on 1,000 permutations with the R package regioneR ( Gel et al., 2016 ), yielding p < 0.001 across all populations (Supplementary Figs. 33,34,37,38). Gene annotation of the two reference genomes Gene structure predictions were obtained from previous reports ( Gao et al., 2021 ; Linsmith et al., 2019 ). Functional annotation was performed with eggNOG-mapper v2.1.12 ( Huerta-Cepas et al., 2019 ) using a custom Viridiplantae sub-database to assign Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To refine these annotations, Pyrus protein sequences were retrieved from UniProtKB and Arabidopsis thaliana models (version 20110103) from the Arabidopsis Information Resource (TAIR), and BLASTp v2.15.0 searches ( E -value < 1e−5) were conducted using both datasets. GO and KEGG identifiers were interpreted and enriched using Arabidopsis thaliana GO annotations (release 2024-11-03; Gene Ontology Consortium) and Pyrus × bretschneideri KEGG pathways ( https://www.kegg.jp ) (Supplementary Tables 7,8). Enrichment analyses were conducted with the R packages AnnotationForge, clusterProfiler, and enrichplot ( Wu et al., 2021 ) using p -value and q -value thresholds of 0.05 (Supplementary Tables 9–11). Mutation burden analysis To assess the deleterious genetic burden in the pear populations, the SIFT scores for the SNP sites were calculated using the “sorting intolerant from tolerant” (SIFT 4G) algorithm ( Vaser et al., 2016 ). A Singularity container recipe (SIFT4G_Create_Genomic_DB.def) was generated to facilitate installation of SIFT 4G and its dependencies without root access; this recipe is available on GitHub (see Data Availability). The SIFT genomic databases for both reference genome assemblies were precomputed against UniRef90 reference sequences (2025 release) ( Suzek et al., 2007 ). The resulting databases covered 98.8% and 99.9% of SNP positions with SIFT scores and 79.6% and 87.7% with high-confidence predictions, respectively. Using these databases, variants were annotated as synonymous, nonsynonymous, or loss-of-function using the SIFT 4G annotator. Nonsynonymous variants were further classified as deleterious (SIFT 3.5). A custom script was used to count allele numbers for each annotated variant per genotype and population and to distinguish homozygous from heterozygous states. TE library building, TE annotation, and TE polymorphism detection Two TE libraries were built de novo from each reference whole-genome assembly using the TEdenovo pipeline ( Flutre et al., 2011 ) from REPET v3.0 ( https://urgi.versailles.inra.fr/Tools/REPET ). The TE libraries were automatically curated using “the second TEannot process” ( Jamilloux et al., 2017 ). Each genome reference assembly was then annotated using TEannot from the REPET package v3.0 ( Quesneville et al., 2005 ). TE classification was carried out using PASTEC v2.0 ( Hoede et al., 2014 ). MEGAnE ( Kojima et al. 2022 ) was used to detect mobile element (ME) variants, specifically focusing on TEs. Providing this TE library using the - rep option ensured that MEGAnE specifically targeted TEs in the analysis. The TE GFF files of annotations from REPET were converted into RepeatMasker format to fit the MEGAnE tool. For the Occidental populations, the P. communis (PCOM) genome assembly was used as the reference, against which short reads from 102 samples (67 pure) were mapped with sequencing depths ranging from 18× to 50× (Supplementary Table 1,4). For the Oriental populations, the P. pyrifolia (PPY) whole-genome assembly served as the reference, and short reads from 114 samples (82 pure) were mapped with sequencing depths also ranging from 18× to 50× (Supplementary Table 1,4). In MEGAnE ( Kojima et al., 2023 ), the non-reference TE insertions (named mobile element insertions or MEIs in this tool) are encoded such that the alternative allele indicates the presence of a TE. Therefore, the genotype values can be used directly. By contrast, the reference TE insertions (named mobile element absences or MEAs) are encoded in the opposite manner: the reference allele indicates presence. To make the two datasets comparable, the MEA genotypes were inverted before counting, ensuring that in both cases, “presence” consistently represented a TE allele. Diploid genotypes with one missing allele were considered non-missing, e.g., 1/. was imputed as 1/0 and 0/. as 0/0. Detailed information on the visualization of TE genotypes is provided in the Supplementary Note “Analysis of TE polymorphisms”. Data availability The TE consensus sequences and annotations are available on RepetDB, https://urgi.versailles.inrae.fr/repetdb ( Amselem et al., 2019 ). All custom scripts developed and used in this study are freely available. All scripts, pipelines, and analysis workflows are hosted and maintained in the GitHub repository ( https://github.com/CornilleEclecticLab/pear-SNP ). Author contributions AC and YT obtained funding, and AC and YT designed the experiments; YN, XC, SL, YT, and AC prepared the materials for genome resequencing; YN, XC, JC, SS, and AC analyzed the data; all co-authors discussed the results; YN, XC, SS, and AC wrote the manuscript with critical input from other co-authors. Funding This research was funded by the ATIP-CNRS, Inserm, IDEEV, and LabEx BASC; by Tamkeen, under grant number AD454 from the New York University Abu Dhabi Research Institute led by AC, and by the Specialized Research Fund for Major Science and Technique of Zhejiang Province of China (2021C02066-5) led by YT. AC and YN acknowledge financial support from the China Scholarship Council (CSC) through a PhD scholarship. AR received funding through projects 88-PHE and BIORESGREEN (PN-IV-P8-8.1-PRE-HE-ORG-2024-0223, and PN23020401/7N/03.01.2023) from the MCDI. Acknowledgments We thank Pierre Baduel, Timothée Flutre, and Aurélie Hua-Van for helpful suggestions. We thank the Plant Bioinformatics Facility, BioinfOmics, INRAE, Université Paris-Saclay, the GenoToul bioinformatics facility, the France National Bioinformatics Infrastructure (IFB), and the New York University Abu Dhabi (NYUAD) High Performance Computing (HPC) Center for their generosity in providing computing resources. We thank Yves Hurand for help with sampling of P. pyraster that ended up being introgressed by P. communis . We thank Gayle Volk from the USDA for providing P. caucasica samples. The authors would like to thank the Biological Resource Center “RosePom - Pome Fruits and Roses” ( https://www6.angers-nantes.inrae.fr/irhs/Ressources-mutualisees/Ressources-genetiques/CRB-Fruits-a-pepins-et-rosier ) and associated staff for maintaining the plant material and associated datasets used in the present study. Funder Information Declared Tamkeen / NYU Abu Dhabi Research Institute , AD454 ATIP-CNRS, Inserm, IDEEV, LabEx BASC Specialized Research Fund for Major Science and Technique of Zhejiang Province of China , 2021C02066-5 China Scholarship Council, https://ror.org/04atp4p48 MCDI M-BM-^V Project 88-PHE MCDI M-BM-^V BIORESGREEN , PN-IV-P8-8.1-PRE-HE-ORG-2024-0223 , PN23020401/7N/03.01.2023 References ↵ Akaike , H . ( 1974 ). A new look at the statistical model identification . 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Share Contrasting genomic routes to domestication in Occidental and Oriental pears Yuqi Nie , Xilong Chen , Somia Saidi , Yann Bourgeois , Anthony Venon , Johann Confais , Aurélie Mesnil , Shuo Liu , Yuhao Gao , Junbei Ni , Songling Bai , Lijuan Gao , Guofang Li , Monika Hoefer , Nicolas Francillone , Anamaria Roman , Lehel Lukács , Caroline Denance , Takashi Akagi , Anush Nersesyan , Astghik Papikyan , Ivan George Gabrielyan , Hamid Abdollahi , Nahla Victor Bassil , Serena Steffensmeier , Karine Alix , Yuanwen Teng , Amandine Cornille bioRxiv 2025.11.17.687327; doi: https://doi.org/10.1101/2025.11.17.687327 Share This Article: Copy Citation Tools Contrasting genomic routes to domestication in Occidental and Oriental pears Yuqi Nie , Xilong Chen , Somia Saidi , Yann Bourgeois , Anthony Venon , Johann Confais , Aurélie Mesnil , Shuo Liu , Yuhao Gao , Junbei Ni , Songling Bai , Lijuan Gao , Guofang Li , Monika Hoefer , Nicolas Francillone , Anamaria Roman , Lehel Lukács , Caroline Denance , Takashi Akagi , Anush Nersesyan , Astghik Papikyan , Ivan George Gabrielyan , Hamid Abdollahi , Nahla Victor Bassil , Serena Steffensmeier , Karine Alix , Yuanwen Teng , Amandine Cornille bioRxiv 2025.11.17.687327; doi: https://doi.org/10.1101/2025.11.17.687327 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Genomics Subject Areas All Articles Animal Behavior and Cognition (7619) Biochemistry (17642) Bioengineering (13865) Bioinformatics (41863) Biophysics (21410) Cancer Biology (18548) Cell Biology (25437) Clinical Trials (138) Developmental Biology (13359) Ecology (19863) Epidemiology (2067) Evolutionary Biology (24288) Genetics (15587) Genomics (22467) Immunology (17704) Microbiology (40301) Molecular Biology (17142) Neuroscience (88447) Paleontology (666) Pathology (2825) Pharmacology and Toxicology (4815) Physiology (7634) Plant Biology (15109) Scientific Communication and Education (2042) Synthetic Biology (4285) Systems Biology (9812) Zoology (2268)