Chromosomal-level genome of the Pinus massoniana ‘Minlin WY36’

Chromosomal-level genome of the Pinus massoniana ‘Minlin WY36’ | 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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Xiaopei Wu , Dong-Hui Peng , Liang Ma , Zhi-Wen Wang , Wenfeng Lan , Huimin Chen , Shuangquan Zou , Wen-Chieh Tsai , Yves Van de Peer , View ORCID Profile Zhong-Jian Liu , Siren Lan doi: https://doi.org/10.1101/2025.06.23.660646 Wei-Hong Sun 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Feiping Zhang 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xuewei Zhao 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zhen Li 3 Department of Plant Biotechnology and Bioinformatics, Ghent University , 9052 Ghent, Belgium Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Zhen Li Ke-Wei Liu 4 Tsinghua-Berkeley Shenzhen Institute (TBSI), Center for Biotechnology and Biomedicine, Shenzhen Key Laboratory of Gene and Antibody Therapy, State Key Laboratory of Chemical Oncogenomics, State Key Laboratory of Health Sciences and Technology, Institute of Biopharmaceutical and Health Engineering (iBHE), Shenzhen International Graduate School, Tsinghua University , Shenzhen 518055, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Songqing Wu 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yajie Guo 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xia Hu 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mengyao Zeng 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Linying Wang 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cheng-Yuan Zhou 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Deqiang Chen 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ruiyue Zheng 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xiaopei Wu 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dong-Hui Peng 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Liang Ma 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zhi-Wen Wang 5 PubBio-Tech , Wuhan 430070, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Wenfeng Lan 6 Wuyi Forestry Farm of Fujian , Zhangping 364400, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Huimin Chen 6 Wuyi Forestry Farm of Fujian , Zhangping 364400, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shuangquan Zou 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zou{at}fafu.edu.cn tsaiwc{at}mail.ncku.edu.tw yves.vandepeer{at}psb.vib-ugent.be zjliu{at}fafu.edu.cn lkzx{at}fafu.edu.cn Wen-Chieh Tsai 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 7 Institute of Tropical Plant Sciences and Microbiology, National Cheng Kung University , Tainan 701, Taiwan 8 Orchid Research and Development Center, National Cheng Kung University , Tainan City 701, Taiwan Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zou{at}fafu.edu.cn tsaiwc{at}mail.ncku.edu.tw yves.vandepeer{at}psb.vib-ugent.be zjliu{at}fafu.edu.cn lkzx{at}fafu.edu.cn Yves Van de Peer 3 Department of Plant Biotechnology and Bioinformatics, Ghent University , 9052 Ghent, Belgium 9 College of Horticulture, Nanjing Agricultural University, Academy for Advanced Interdisciplinary Studies , Nanjing 210095, China 10 Centre for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria , Pretoria, South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zou{at}fafu.edu.cn tsaiwc{at}mail.ncku.edu.tw yves.vandepeer{at}psb.vib-ugent.be zjliu{at}fafu.edu.cn lkzx{at}fafu.edu.cn Zhong-Jian Liu 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Zhong-Jian Liu For correspondence: zou{at}fafu.edu.cn tsaiwc{at}mail.ncku.edu.tw yves.vandepeer{at}psb.vib-ugent.be zjliu{at}fafu.edu.cn lkzx{at}fafu.edu.cn Siren Lan 1 Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization at College of Landscape Architecture and Art, Fujian Agriculture and Forestry University , Fuzhou 350002, China 2 Fujian Colleges and Universities Engineering Research Institute of Conservation and Utilization of Natural Bioresources, College of Forestry, Fujian Agriculture and Forestry University , Fuzhou 350002, China Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: zou{at}fafu.edu.cn tsaiwc{at}mail.ncku.edu.tw yves.vandepeer{at}psb.vib-ugent.be zjliu{at}fafu.edu.cn lkzx{at}fafu.edu.cn Abstract Full Text Info/History Metrics Preview PDF Abstract Owing to conifers complex and large genomes, it is challenging to construct a comprehensive reference genome and conduct evolutionary and genomic research. Here, we present the chromosome-level assembly of Pinus massoniana ‘Minlin WY36’, a pioneering conifer species used for afforestation, timber production, and oleoresin extraction. The genome size was determined to be 23.41 Gb, with a contig N50 value of 1.15 Mb and a scaffold N50 value of 2.02 Gb. A total of 23.16 Gb of reads (98.93% of the assembled genome) were anchored and oriented onto 12 pseudochromosomes, with chromosome lengths from 1.47 to 2.29 Gb. A total of 32,144 protein-coding genes were predicted, of which 27,173 (84.54%) were functionally annotated. The P. massoniana ‘Minlin WY36’ genome consists of 79.41% (18.57 Gb) repetitive sequences, among which long terminal repeat sequences (LTR) were the most abundant. Through comparative genomic analysis, we found that the unique and significantly expanded genes in P. massoniana ‘Minlin WY36’ were enriched in the metabolism related to resin synthesis. This study offers valuable insights into conifer evolution and contributes resources for further investigations of conifer adaptation and developmental processes. Introduction Pines (genus Pinus ) belong to the coniferous family Pinaceae of gymnosperms, with approximately 110–120 species distributed across the Northern Hemisphere ( Gernandt et al ., 1999 ). Among these, Pinus massoniana is a unique conifer species endemic to China ( He et al ., 2023 ). Its planting area ranks first in the distribution of tree species in China, and is widely distributed in southern China. As a crucial species for afforestation, timber production, and oleoresin extraction, P. massoniana has extensive applications in construction, papermaking, and pharmaceutical industries and has important ecological and economic significance ( Peng et al . 2003 ; Zhang et al . 2013 ). In this study, we generated a high-quality P. massoniana ‘Minlin WY36’ genome sequence to elucidate the evolution of its genome structure and phylogenetic relationships within gymnosperms. This study offers profound insights into the evolution of conifers and serves as a foundation for the further exploration of their adaptive developmental strategies. Results and discussion Survey analysis revealed a high level of heterozygosity in the P. massoniana ‘Minlin WY36’ genome, accounting for 1.13% of the 23.38 Gb genome size determined by K -mer analysis. For de novo whole-genome sequencing of P. massoniana ‘Minlin WY36’, we obtained 2165.08 Gb of clean reads with an average length of 12.47 Kb using PacBio technology. The final assembled genome amounted to 25.37 Gb with a contig N50 value of 1.15 Mb ( Table 1 ). High-throughput and high-resolution chromosome conformation capture (Hi-C) technology was used to obtain a chromosome-level genome. Based on the Hi-C data, the genome was assembled to a total size of 23.41 Gb with a scaffold N50 value of 2.02 Gb ( Table 1 ). A total of 23.16 Gb reads were mapped to 12 chromosomes, with the chromosome lengths ranging from 1.47 to 2.29 Gb ( Table 2 ). View this table: View inline View popup Download powerpoint Table 1. The statistic of genome assembly of P. massoniana ‘Minlin WY36’ View this table: View inline View popup Download powerpoint Table 2. The length of chromosome by Hi-C assemble of P. massoniana ‘Minlin WY36’ To predict gene models, we used a combination of de novo prediction, homology-based searches, and RNA-sequencing data, resulting in the prediction of 32,144 protein-coding genes in P. massoniana ‘Minlin WY36’ genome. The primary gene models exhibited a mean length of 37,832.39 bp, with an average exon length of 263.80 bp and an average intron length of 12,804.88 bp. Similar to other gymnosperms with large genomes, extremely long introns were also predicted in P. massoniana ‘Minlin WY36’ ( Figure 1A ). This indicates that the accumulation of long introns has led to a significant expansion of the genome ( Nystedt et al ., 2013 ). On the basis of a Benchmarking Universal Single-Copy Orthologs (BUSCO) assessment, the completeness of the gene annotations was approximately 81.75%. We functionally annotated the protein-coding genes using various databases, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Swiss-Prot, and others, an over 84.54% of the genes could be mapped to corresponding functional items. These analyses indicate a relatively comprehensive structural annotation of the reference genome. A total of 113 microRNAs (miRNAs), 730 small nuclear RNA (snRNAs), 2,011 transfer RNAs (tRNAs), and 3,307 ribosomal RNAs (rRNA) were identified in the P. massoniana ‘Minlin WY36’ genome ( Table 3 ). We estimated that 79.41% (18.57 Gb) of the P. massoniana genome was composed of repetitive sequences, among which transposable elements (TE) sequences were relatively abundant, with a long terminal repeat (LTR) accounting for 70.94%, followed by LINE accounting for 4.88%, and DNA accounting for 2.34%. We used complete LTR-Copia and LTR-Gypsy elements from P. massoniana ‘Minlin WY36’ to investigate further the timing of conifer transposable element insertions and found that insertions appear to have occurred tens of millions of years ago ( Figure 1B ). Download figure Open in new tab Figure 1. Assembly and genome features of Pinus massoniana . A . Intron length. B . Long terminal repeat insertion time in P. massoniana ‘Minlin WY36’. C . Phylogenetic tree showing divergence times and evolution of the gene family size in the 20 species. Green and red numbers indicate the number of expanded and contracted gene families, respectively. The blue portions of the pie charts represent gene families with constant copy number. D . KEGG enrichment of genes unique to P. massoniana ‘Minlin WY36’. E . KEGG enrichment of significantly expanded genes in P. massoniana ‘Minlin WY36’. View this table: View inline View popup Download powerpoint Table 3. Statistics on the annotation of non-coding RNA of the P. massoniana ‘Minlin WY36’genome. The phylogenetic relationships among the major lineages of existing gymnosperms, particularly Ginkgo and Gnetales, remain a subject of ongoing debate ( Stull et al ., 2021 ). On the basis of the 46 low-copy gene families derived from ten gymnosperms, five angiosperms, and five seedless vascular plants, we constructed phylogenetic tree ( Figure 1C ). The results support Gnetales as a basal lineage within gymnosperms, diverging from other gymnosperms approximately 249.7 million years ago (Mya). Ginko biloba and Cycas panzhihuaensis form a sister group to conifers, with these two major evolutionary branches diverging around 177.3 Mya. Taxus wallichiana – Cunninghamia lanceolata diverged from Pinaceae approximately 160.4 Mya. Approximately 51 Mya, Pinaceae rapidly diversified into other species, and P. massoniana ‘Minlin WY36’ diverged around 12.6 Mya. A comparative analysis of orthologous genes among P. massoniana ‘Minlin WY36’ and the genomes of 19 species revealed that 1,011 gene families (including 3,074 genes) were unique to the P. massoniana ‘Minlin WY36’ genome. Enrichment analyses found that these genes are especially enriched in the Kyoto Encyclopedia of Genes and Genomes (KEGG) terms of ‘plant-pathogen interaction’, ‘Flavonoid biosynthesis’, ‘isoflavanoid biosynthesis’, ‘Fatty acid biosynthesis’, and ‘Fatty acid degradation’, ‘Fatty acid elongation’ ( Figure 1D ). Analysis of orthologous gene family expansion and contraction indicated 2,022 expanded gene families in the P. massoniana ‘Minlin WY36’ genome, of which 370 (including 3,868 genes) exhibited significant expansion ( P <0.01). Additionally, 467 gene families were contracted, with 108 gene families (including 663 genes) showing a significant contraction ( Figure 1C ). Enrichment analyses revealed that the significantly expanded gene families were enriched the KEGG pathways related to ‘terpenoid backbone biosynthesis’, ‘diterpenoid biosynthesis’, ‘flavone and flavonol biosynthesis’, and ‘plant-pathogen interaction’, ‘fatty acid degradation’ ( Figure 1E ). Resin is a major metabolite of pine plants and serves as a physical and chemical defense barrier against insect and pathogen attacks ( Liu et al ., 2021 ). Resin mainly consist of terpenoids, flavonoids, lignin-like compounds, and phenolic compounds, among which terpenoids are the predominant components ( Li et al ., 2013 ). The genes that are specific and significantly expanded in P. massoniana ‘Minlin WY36’ are enriched in pathways related to plant-pathogen interactions, terpenoid metabolism, and flavonoid metabolism. Methods DNA extraction and sequencing All genome-sequencing materials used in this study were collected from adult P. massoniana ‘Minlin WY36’ grown in Youxi County, Fujian Province, China. Total genomic DNA was extracted from young leaves using the cetyltrimethylammonium bromide method (CTAB) for Illumina and PacBio sequencing. We used the PacBio Sequel II platform to perform 26-cell single-molecule real-time DNA sequencing. Genome size estimate Before genome assembly, filtered Illumina reads were used to estimate the genome size, heterozygosity, and repeat content of P. massoniana ‘Minlin WY36’. Then, a genome survey was performed through K -mer analysis using Jellyfish v2.1.4 ( Marçais and Kingsford, 2011 ) and GenomeScope ( Vurture et al ., 2017 ). Genome assembly and Hi-C scaffolding Assemble P. massoniana ‘Minlin WY36’ genome using PacBio data. Canu v1.9 ( https://github.com/marbl/canu ) ( Koren et al ., 2017 ) was used to correct the error of the PacBio clean data. We assembled the corrected data using Smartdenovo v1.0 ( Ruan, 2016 ). The Contig-level assembly results were aligned to the genome using Juicer ( Kent, 2002 ), and the alignment results were filtered to remove incorrectly aligned reads. Next, 3D-DNA ( Ruan, 2016 ) was used to perform preliminary clustering, ordering, and orientation of the genomic sequences. To prevent excessive fragmentation of the genomic sequences, we manually adjusted the preliminary clustering results from 3D-DNA using visualization software Juicebox ( https://github.com/aidenlab/Juicebox ). This manual adjustment involved removing redundancies, repositioning, and re-clustering, as necessary. The final pseudochromosomes were manually constructed and adjusted. To evaluate the results of the Hi-C assembly, we constructed an interaction heat map of Hi-C assembly chromosome. Gene prediction and annotation Annotation information from five closely related species ( Amborella trichopoda, G. biloba, G. monatum, P. abies , and P. taeda ) was used for homology-based predictions. From the structurally intact genes obtained through homology-based prediction, we randomly selected 5,000 genes to train the de novo models of the target species using the ab initio prediction software, Augustus and SNAP ( Johnson et al ., 2008 ). Simultaneously, the RNA-seq data were aligned to the genome using HISAT v2.1.0 ( Kim et al ., 2015 ) and the resulting transcripts were assembled using StringTie v1.3.4d ( Pertea et al ., 2015 ). Finally, Maker v2.31.8 ( Holt and Yandell, 2011 ) software was used to integrate homology-based predictions. In addition, the gene sets obtained from gene structure annotation were aligned with known protein databases and other databases such as SwissProt (Boeckmann, 2005) ( http://www.uniprot.org/ ), TrEMBL ( http://www.uniprot.org/ ) (Boeckmann, 2005), KEGG ( Kanehisa and Goto, 2000 ) ( http://www.genome.jp/kegg/ ), and InterPro ( https://www.ebi.ac.uk/interpro/ ) ( Zdobnov and Apweiler, 2001 ) and were aligned using Blast v2.2.26 ( Altschul et al ., 1990 ). Identification of non-coding RNA, and repetitive sequences Non-coding RNAs include RNA with a variety of known functions, such as microRNAs (miRNAs), ribosomal RNA (rRNA), and transfer RNA (tRNA). Based on the structural characteristics of tRNA, software tRNAscan-SE 1.3.1 ( http://lowelab.ucsc.edu/tRNAscan-SE/ ) ( Lowe and Eddy, 1997 ) was used to search for tRNA sequences in the genome. Owing to the high conservation of rRNA, rRNA sequences from closely related species was selected as reference sequences, and BLASTN alignment was used to search for rRNA sequences in the genome. Additionally, covariance models from the Rfam family ( Sam et al ., 2005 ), along with the INFERNAL software ( http://infernal.janelia.org/ ) provided by Rfam, can be used to predict miRNA and snRNA sequence information in the genome. The process involved identifying sequences similar to known repetitive sequences based on the RepBase v21.12 ( Jurka et al ., 2005 ) database ( http://www.girinst.org/repbase ) using RepeatMasker v4.0.7 ( http://www.repeatmasker.org ) and RepeatProteinMask v4.0.7 ( http://www.repeatmasker.org ). De novo prediction, on the other hand, is based on self-sequence alignment, where a de novo ( Price et al ., 2005 ) repetitive sequence library was first established using RepeatModeler ( http://www.repeatmasker.org ) and LTR_FINDER v1.06 ( http://tlife.fudan.edu.cn/ltr_ ) ( Benson, 1997 ). This library was then used for prediction using the RepeatMasker software. Additionally, Tandem Repeats Finder v4.09 ( http://tandem.bu.edu/trf/trf.html ) ( Price et al ., 2005 ) was used to search for tandem repeats within the genome. Ortholog detection Single/low-copy and multicopy gene families can be obtained by identifying orthologous genes and cluster analysis of gene families. A protein dataset that included ten gymnosperms, five angiosperms, and five seedless vascular plants was constructed. Pairwise BLASTP ( Altschul et al ., 1990 ) alignments were performed on the protein dataset, followed by a clustering analysis using OrthoFinder ( Emms and Kelly, 2015 ). Phylogenetic reconstruction We constructed a species phylogenetic tree using low-copy gene families from P. massoniana ‘Minlin WY36’ and 19 other plants and identified 46 low-copy families among the 20 species. Then, the dataset used for phylogenetic analysis was employed in the MCMCTree program within PAML4.9 ( Ziheng, 2007 ) to estimate the divergence times. The nucleotide substitution model was set as the GTR model and the molecular clock model was set as the independent rate model. The MCMC process included 500,000 burn-in iterations and 1,500,000 sampling iterations, with sampling conducted every 150 iterations. The same parameters were run twice to obtain stable results. The phylogeny was calibrated using various fossil records or molecular divergence estimates by placing soft bounds on the split nodes of G. montanum – G. biloba (230–282 Ma), Arabidopsis thaliana – G. montanum (289–330 Ma), Azolla pinnata – A. thaliana (392–422 Ma), and Physcomitrella patens – A. thaliana (465–533 Ma). Gene family expansion and contraction For the well-clustered gene families and the constructed phylogenetic tree structures, we performed gene family contraction and expansion analysis on the selected 20 species using CAFÉ 4 (De Bie et al ., 2006 ). We conducted KEGG and GO enrichment analyses focusing on genes belonging to the notably expanded gene family within the P. massoniana ‘Minlin WY36’ genome. Competing interests The authors declare no competing interests. Acknowledgments This project was supported by the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University (72202200205), the National Key Research and Development Program of China (No. 2203YFD1600504), and Fujian Forestry Science and Technology Program (No.2020-9). Funder Information Declared Fujian Agriculture and Forestry University , 72202200205 , No. 2203YFD1600504 , No. 2020-9 Footnotes Update the Acknowledgments to show the project support received for this research: This project was supported by the Forestry Peak Discipline Construction Project of Fujian Agriculture and Forestry University (72202200205), the National Key Research and Development Program of China (No. 2203YFD1600504), and Fujian Forestry Science and Technology Program (No.2020-9). And competing interests: The authors declare no competing interests. Reference ↵ Altschul , S. F. et al. Basic local alignment search tool . 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Share Chromosomal-level genome of the Pinus massoniana ‘Minlin WY36’ Wei-Hong Sun , Feiping Zhang , Xuewei Zhao , Zhen Li , Ke-Wei Liu , Songqing Wu , Yajie Guo , Xia Hu , Mengyao Zeng , Linying Wang , Cheng-Yuan Zhou , Deqiang Chen , Ruiyue Zheng , Xiaopei Wu , Dong-Hui Peng , Liang Ma , Zhi-Wen Wang , Wenfeng Lan , Huimin Chen , Shuangquan Zou , Wen-Chieh Tsai , Yves Van de Peer , Zhong-Jian Liu , Siren Lan bioRxiv 2025.06.23.660646; doi: https://doi.org/10.1101/2025.06.23.660646 Share This Article: Copy Citation Tools Chromosomal-level genome of the Pinus massoniana ‘Minlin WY36’ Wei-Hong Sun , Feiping Zhang , Xuewei Zhao , Zhen Li , Ke-Wei Liu , Songqing Wu , Yajie Guo , Xia Hu , Mengyao Zeng , Linying Wang , Cheng-Yuan Zhou , Deqiang Chen , Ruiyue Zheng , Xiaopei Wu , Dong-Hui Peng , Liang Ma , Zhi-Wen Wang , Wenfeng Lan , Huimin Chen , Shuangquan Zou , Wen-Chieh Tsai , Yves Van de Peer , Zhong-Jian Liu , Siren Lan bioRxiv 2025.06.23.660646; doi: https://doi.org/10.1101/2025.06.23.660646 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 (7617) Biochemistry (17633) Bioengineering (13856) Bioinformatics (41840) Biophysics (21398) Cancer Biology (18529) Cell Biology (25422) Clinical Trials (138) Developmental Biology (13352) Ecology (19860) Epidemiology (2067) Evolutionary Biology (24281) Genetics (15582) Genomics (22461) Immunology (17700) Microbiology (40289) Molecular Biology (17138) Neuroscience (88413) Paleontology (666) Pathology (2823) Pharmacology and Toxicology (4813) Physiology (7632) Plant Biology (15107) Scientific Communication and Education (2042) Synthetic Biology (4283) Systems Biology (9807) Zoology (2267)