Plant Genome最新文献

{"title":"Integrating genomic selection into potato breeding: A comparison of genotyping platforms and cross-environmental predictions.","authors":"Rakshya Dhakal, Marco Antonio Peixoto, Leo Hoffmann, Bonny Michael Oloka, Mark Clough, Gabriel de Siqueira Gesteira, Lincoln Zotarelli, Jeffrey B Endelman, G Craig Yencho, Marcio F R Resende","doi":"10.1002/tpg2.70293","DOIUrl":"10.1002/tpg2.70293","url":null,"abstract":"<p><p>Genomic selection (GS) is a powerful tool for accelerating genetic gain in potato (Solanum tuberosum L.) breeding, particularly for complex traits. In this study, three practical aspects of GS implementation in a potato breeding program were examined. First, the predictive ability of GS models was evaluated for three key traits (total yield, marketable yield, and specific gravity) using two elite potato populations with shared ancestry, tested across seven location-year environments. Two cross-validation strategies were used to reflect practical breeding scenarios: predicting unphenotyped lines in known environments and predicting clonal performance in unknown environments. Four models were evaluated, two of which included genotype-by-environment interactions. Tuber specific gravity showed higher and more consistent prediction accuracy across environments, supporting the evidence that it is a more stable trait. Second, the impact of genotyping platforms and marker density on GS performance were examined, as the two populations were genotyped using two different targeted sequencing platforms: Flex-seq (22K loci) and DArTag (4K loci), sharing ∼4K common loci, that allowed direct comparison. Prediction accuracies were comparable across platforms, indicating that both are suitable for GS implementation, with the choice depending on breeding goals, cost, and throughput considerations. Finally, the long-term impact of GS on genetic gain was assessed through stochastic simulation of a 30-year breeding pipeline, comparing conventional phenotypic selection with GS-assisted selection scenarios. GS scenarios achieved higher long-term genetic gains, though practical deployment should consider both cost and breeding objectives. Our findings for the three aspects of this study support the integration of GS into potato breeding programs, while highlighting key considerations for its effective implementation.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70293"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13493692/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148799835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic and evolutionary analysis reveals dynamic variations of MKK3 gene, a key regulator for seed dormancy in barley.","authors":"Lydia G Tressel, Ann M Caspersen, Jason G Walling, Dongying Gao","doi":"10.1002/tpg2.70299","DOIUrl":"10.1002/tpg2.70299","url":null,"abstract":"<p><p>Barley (Hordeum vulgare L.) is an important crop in the world, and its seed dormancy is primarily controlled by a mitogen-activated protein kinase kinase 3 (MKK3) gene. Although kinase activity of MKK3 and its roles in barley post-domestication have been widely studied, the pre-domestication evolution of MKK3 and the spread of nondormant alleles among global barley varieties remain largely unexplored. In this study, we analyzed MKK3 sequences in barley and its wild progenitor (Hordeum spontaneum K. Koch) and identified two polymorphic miniature inverted-repeat transposable elements (MITEs). Comparative analyses indicated that the insertions/excision of the MITEs predated the current estimates of barley domestication. Examination of the barley pangenomes coupled with droplet digital polymerase chain reaction revealed extensive copy number variation of MKK3 and suggested that transposons likely contributed to tandem amplification of the MKK3 gene on chromosome 5H. Additionally, approximately 1-Kb MKK3 sequences were found on chromosomes 1H and 6H. Further analysis indicated that these short MKK3 sequences were captured by a CACTA transposon that also contained fragments from four other expressed genes. The acquisition of MKK3 was estimated to be between 1.9 and 2.5 million years ago. Together, these findings illuminate the dynamic pre-domestication evolution of the MKK3 gene and identify three divergent MKK3 haplotype groups including a unique lineage predominant in Ethiopian germplasm. This study highlights the contribution of transposons to structural diversification and evolutionary differentiation of the MKK3 locus and provides helpful information for understanding the complex history of MKK3 gene in barley and also for improving preharvest sprouting tolerant varieties under distinct natural conditions.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70299"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13534570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sparse phenotyping for wheat grain yield enabled by multiomics prediction.","authors":"Guillermo Gerard, Velu Govindan, Susanne Dreisigacker, Keith Gardner, Flavio Breseghello, Leonardo Crespo-Herrera, Matthew Reynolds, Jose Crossa, Paolo Vitale","doi":"10.1002/tpg2.70298","DOIUrl":"10.1002/tpg2.70298","url":null,"abstract":"<p><p>Grain yield is a central target in wheat breeding, yet accurately predicting it remains challenging because it depends on many genes and responds strongly to environmental variation. Genomic selection (GS) has improved breeding efficiency by enabling genome-based prediction of genetic merit, but predictability (PA) for grain yield is often limited under stress environments. At the same time, advances in high-throughput phenotyping (HTP) using unmanned aerial vehicles (UAVs) provide phenomic data that capture environment-responsive plant performance and may complement genomic information. In this study, we evaluated genomic and phenomic models for predicting grain yield in elite bread wheat lines across irrigated, drought, and heat-stress environments. Using a sparse phenotyping framework, we compared parametric and non-parametric models. PA was evaluated within environments and under cross-environment sparse phenotyping scenarios. Genomic models provided a stable baseline and enabled effective information sharing across environments when phenotypic data were incomplete. Phenomics-only models captured environment-specific plant responses but were more sensitive to environmental context. Multiomics models that integrated genomic and phenomic information consistently achieved the highest PA, with the largest gains observed under stress conditions. Overall, our results demonstrate that integrating genomics and UAV-based phenomics within sparse phenotyping designs offers a practical and scalable approach to improve grain yield prediction in wheat.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70298"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13547598/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148901341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic prediction of agronomic traits in a switchgrass (Panicum virgatum L.) half-sib progeny panel evaluated across multiple environments.","authors":"Jazib Ali Irfan, Chanaka Roshan Abeyratne, Hari Bahadur Chhetri, Doug Hyatt, Shiva Om Makaju, Chris Daum, Diane Bauer, Anna Lipzen, Kerrie Barry, Daniel Jacobson, Mitra Mazarei, Charles Neal Stewart, Ali Mekki Missaoui","doi":"10.1002/tpg2.70306","DOIUrl":"10.1002/tpg2.70306","url":null,"abstract":"<p><p>Switchgrass (Panicum virgatum L.) improvement requires selection methods that remain effective across environments. Biomass yield is strongly influenced by genotype-by-environment (G × E) interaction. We evaluated genomic prediction models for biomass yield, spring emergence (SE), and flowering time (FT) in half-sibs at three southeastern US locations (Watkinsville, GA; Tifton, GA; and Knoxville, TN). Predictive performance was assessed within each site-year using five-fold cross-validation, comparing a parental general combining ability (GCA) baseline with Bayesian models, genomic BLUP (GBLUP), and a dominance model (GBLUPD). We further quantified the sensitivity of yield prediction to single-nucleotide polymorphism (SNP) density. Predictive abilities as Pearson correlation coefficient (PCC) increased as the SNP number rose from the minimum of 100 to 2500-5000 SNPs, with only minimal gains observed up to 10,000 SNPs and beyond. Genomic models consistently outperformed parental GCA baseline for yield, with the highest PCC of 0.45-0.55 in 2022 for Georgia, followed by declines (PCC = 0.25-0.35) in 2024. This indicated stronger G × E (where E represents combined year-location) impacts on mature switchgrass stands. FT showed higher predictive ability than yield, with PCC > 0.50 in Georgia and PCC > 0.28-0.33 in Tennessee. SE exhibited intermediate-to-high PCC of 0.65-0.70 in Georgia during 2022-2023 and a PCC of 0.45-0.47 in Tennessee. The GBLUPD provided small repeatable gains for yield and SE in comparison to GBLUP. FT exhibited genetic correlations exceeding 0.90 at Knoxville, which showed it as a transferable predictor for multi-environment selection. Collectively, these results indicate that modest SNP sets can be sufficient for yield prediction and highlight environment-dependent model performance.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70306"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13591432/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics insights into salinity tolerance in African bermudagrass.","authors":"Prabha Adhikari, Shuhao Yu, Mingying Xiang, Yanqi Wu, Felipe Cevallos, Charles Fontanier, Justin Moss, Dennis Martin","doi":"10.1002/tpg2.70302","DOIUrl":"10.1002/tpg2.70302","url":null,"abstract":"<p><p>African bermudagrass (Cynodon transvaalensis Burtt-Davy) is a key parent species used to produce interspecific hybrid bermudagrass (Cynodon dactylon × C. transvaalensis). Due to the increasing use of non-potable water for landscape irrigation, salt stress has become a major concern in the turfgrass industry. While variation in salt tolerance is known within bermudagrass, the molecular basis of this trait is not well understood, particularly in African bermudagrass. In this study, we aimed to identify the molecular mechanisms associated with salt tolerance in African bermudagrass. The first-generation selfed (S₁) population derived from African bermudagrass genotype OKC1163 was evaluated for salt stress response in controlled-environment conditions in 2024 and 2025. Phenotypic data for visual leaf firing and percent green cover were collected weekly. Using a preexisting high-density linkage map, 15 quantitative trait loci (QTLs) associated with salt response were identified on seven linkage groups. Four QTLs were consistently identified as associated with salt response across years. A total of 1261 upregulated genes, 150 upregulated metabolites, and 60 upregulated lipids were identified under salt stress using the genotype OKC1163. Combining genomic and omics analyses, several candidate genes were identified to be involved in the synthesis of abscisic acid and maltose, alteration of the salicylic acid signaling pathway, and the ABC (ATP-binding cassette) transporter pathway. The results of this study elucidated the molecular mechanisms of African bermudagrass response to salt stress and provide a foundation for future marker-assisted selection and gene function validation.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70302"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13590823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149013046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic insights into bacterial wilt resistance using genomic prediction and association mapping in blueberry.","authors":"Lushan Ghimire, Norma Flor, Paul Adunola, Philip F Harmon, Felix Enciso-Rodriguez, Juliana Benevenuto, Luis Felipe V Ferrão, Patricio R Munoz","doi":"10.1002/tpg2.70283","DOIUrl":"10.1002/tpg2.70283","url":null,"abstract":"<p><p>Bacterial wilt, caused by Ralstonia spp., poses a major threat to blueberry (Vaccinium corymbosum) production due to its persistence and rapid spread through soil and infected stock, highlighting the need for genetic insights to guide breeding strategies. This study investigated the genetic basis of bacterial wilt resistance in blueberry using a genome-wide association study (GWAS) across two populations comprising 401 advanced selections from the University of Florida Blueberry Breeding and Genomics Program. A high-throughput screening assay was developed to evaluate southern highbush blueberry responses to bacterial wilt based on leaf wilting severity and stem necrosis. Capture sequencing identified 38,379 single-nucleotide polymorphisms. Moderate narrow-sense heritability estimates were observed for leaf severity (0.26) and stem necrosis (0.20), and GWAS identified five small-effect quantitative trait loci on chromosomes 1, 2, 5, and 11, each explaining 4.0%-7.4% of the phenotypic variance. Candidate gene analysis revealed putative pentatricopeptide repeat (PPR), serine/threonine protein kinase, and MYB-related proteins for leaf severity, and Mlo genes and polysaccharide biosynthesis genes for stem necrosis. Genomic selection (GS) analyses demonstrated potential for improving bacterial wilt resistance, with the GS de novo GWAS approach achieving the highest predictive ability by leveraging two key markers on chromosomes 1 and 11. These results elucidate the genetic architecture of bacterial wilt resistance in blueberries and provide resources for molecular breeding strategies to enhance resistance and ensure sustainable production.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70283"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13493699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148800494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting the foundation era of plant genomics with a commentary on the pioneering contributions of Prof. Chittaranjan Kole.","authors":"Madhugiri Nageswara-Rao, Sarita Pandey, Poulami Bhattacharjee, Dinesh Kumar Saini, Jaya R Soneji, Bashasab Fakrudin, Lohithaswa Hirenallur Chandappa, Amir Ali Khoddamzadeh, Daniel A Tucker, Jinfa Zhang, Shamseldeen Eltaher, Jauhar Ali, Robert Henry, Ilga Mercedes Porth, Aleksandra Radanović, Kiyosumi Hori, Maria Stefanie Dwiyanti, Ferdinando Branca, Shalini Tiwari, Matthew Blair, Yong Pyo Lim, Renate Horn, Olga Danilevskaya, Sunita Adhikari","doi":"10.1002/tpg2.70276","DOIUrl":"10.1002/tpg2.70276","url":null,"abstract":"<p><p>The evolution of plant genomics has been shaped by several pioneering milestones, beginning with the introduction of restriction fragment length polymorphism-based genetic linkage maps in the mid-1980s. Among the global contributors, Prof. Chittaranjan Kole stands as a distinguished figure whose work fundamentally shifted the trajectory of plant genomics and molecular breeding. This tribute highlights his scientific journey and groundbreaking contributions, from being the first Indian scientist to physically map and sequence a plant gene in barley to establishing the foundations of molecular cytogenetics, comparative genomics, and molecular evolution and phylogenetic relationships in plants. His landmark research on Brassica genomics, including high-resolution mapping, Mendelization of quantitative trait loci (QTLs), and innovative use of recombinant inbred lines, enabled unprecedented insights into trait evolution, stress biology, and genome homology between Brassica species and Arabidopsis. Prof. Kole's work on mapping genes and QTLs associated with flowering time, biotic stress resistance, abiotic stress tolerance, and genome evolution has provided a framework now integral to marker-assisted selection, genomic breeding, and climate-resilient crop development. This article offers a scholarly reflection on his pioneering contributions, establishing Prof. Kole as a founding architect of plant genomics research in India and one of its most influential contributors globally.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70276"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13338916/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148399727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Plant Genome special section: Multi-omics prediction in plant breeding.","authors":"Diego Jarquin, Caio Canella Vieira, Carlos Messina","doi":"10.1002/tpg2.70280","DOIUrl":"10.1002/tpg2.70280","url":null,"abstract":"","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70280"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13389544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148551004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"History of near-isogenic lines carrying genes for resistance to bacterial blight and blast in rice (Oryza sativa L.).","authors":"Van Schepler-Luu, Mary Jeanie Telebanco-Yanoria, Hiroki Saito, Casiana M Vera Cruz","doi":"10.1002/tpg2.70300","DOIUrl":"10.1002/tpg2.70300","url":null,"abstract":"<p><p>Bacterial blight and blast, caused by Xanthomonas oryzae pv. oryzae and Magnaporthe oryzae, respectively, are the two most devastating diseases of rice (Oryza sativa L.). Although the diseases were first documented in the 17th-19th centuries, systematic research on their pathology and host resistance began in the early 20th century and was significantly accelerated following the development of near-isogenic lines (NILs) carrying single resistance genes in universally susceptible backgrounds in the 1980s. Sets of NILs for bacterial blight (IRBB) and International Rice Research Institute (IRRI)-bred Blast-resistant Line (IRBL) were developed through a long-term collaboration between the IRRI and the Japan International Research Center for Agricultural Sciences. Over the years, these materials have been widely distributed for pathogen population monitoring, studying the molecular mechanisms of resistance, assessing the synergistic effect of multiple resistance genes, and developing new resistant varieties, thereby benefiting millions of rice farmers worldwide. In this article, we describe the historical development of the IRBB and IRBL lines, highlight their global impact, and provide perspectives on their relevance not only for bacterial blight and blast but also for emerging rice diseases that could benefit from this approach.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70300"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13570268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chromosome-scale assembly of wheat cultivar Sumai 3, a major germplasm source for Fusarium head blight resistance.","authors":"Rubylyn D Mijan, Bikash Poudel, Sittal Thapa, Oluwatayo Ajayi-Moses, Thomas Lux, Raz Avni, Steven Xu, Manuel Spannagl, Martin Mascher, Jeff Maughan, Jason D Fiedler","doi":"10.1002/tpg2.70285","DOIUrl":"10.1002/tpg2.70285","url":null,"abstract":"<p><p>Fusarium head blight (FHB) is a devastating disease that severely impacts global wheat (Triticum aestivum L.) production. Sumai 3, a wheat cultivar widely used in breeding programs for its strong FHB resistance, has not been fully resolved at the chromosome level. Here, we present a high-quality chromosome-scale assembly of Sumai 3 using PacBio HiFi reads and chromosome conformation capture sequencing. The 14.6 Gb assembly consists of 832 contigs, with the longest contig being 245.2 Mb and a contig N50 of 41.90 Mb, which were scaffolded into 21 pseudomolecules. De novo annotation identified 104,620 high-confidence protein-coding genes and found 92.67% of the genome to consist of repetitive sequences. Synteny analysis showed strong collinearity between Sumai 3 and the wheat reference sequence Chinese Spring IWGSC RefSeq v2.1 (CS). Structural variant analysis identified chromosome 2A with the highest number of deletions (2773) and insertions (2645), while chromosome 3B had the most inversions (359). Duplications were most frequent on 2A (337), and contractions on 5B (122). The gene content of the major resistance quantitative trait loci on 3B, Fhb1, largely validates previous annotations for CS, although we discovered two new genes at approximately 12.4 Mb, including an additional copy of a terpene synthase, further suggesting homology with CS 3D over 3B. Differential expression analysis highlighted up-regulation of three genes coding pore-forming toxin-like protein, sina superfamily protein, and plastid-lipid-associated proteins potentially involved in FHB resistance. This assembly provides critical insights into FHB resistance and offers a valuable genomic resource for wheat breeding programs.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 3","pages":"e70285"},"PeriodicalIF":4.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13459071/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148707894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}