Plant Genome最新文献

{"title":"Hybrid kernels integrating genomic and multispectral data improve wheat genomic prediction accuracy.","authors":"Osval A Montesinos-López, Joel A Martínez-Regalado, Cintia Leonora Murillo-Avalos, Andrew W Herr, Abelardo Montesinos-López, Iván Delgado-Enciso, Jaime Cuevas, José Crossa, Arron H Carter","doi":"10.1002/tpg2.70171","DOIUrl":"10.1002/tpg2.70171","url":null,"abstract":"<p><p>Genomic selection (GS) is transforming plant breeding by enabling more accurate and efficient identification of superior genotypes. However, its practical implementation remains challenging, as achieving high prediction accuracy is critical for its success. Several factors-including sample size, the degree of relatedness among individuals, and the complexity of target traits-significantly affect the predictive performance of GS models. To address these limitations, recent studies have explored the integration of genomic and phenomic information to enhance prediction accuracy. This integrated approach has shown promising results and continues to gain empirical support. In this study, we propose an alternative strategy to improve the efficiency and accuracy of GS by constructing hybrid kernels that combine genomic and phenomic information. Specifically, we generate two new kernels by combining the original genomic and phenomic kernels, aiming to capture complementary and previously unexploited sources of variation. We applied this approach to multi-year data from the winter wheat (Triticum aestivum L.) breeding program at Washington State University, using phenomic data collected via unmanned aerial vehicles (UAVs). Our results provide empirical evidence that integrating genomic and UAV-derived phenomic data through hybrid kernel modeling enhances the prediction accuracy of GS models. This approach achieved average improvements of 17.52%, 30.36%, 28.94%, and 16.73% in terms of Pearson's correlation, normalized root mean square error, and the percentage of correctly identified lines within the top 10% and 20%, respectively, compared with the conventional integration of genomic and phenomic information (M4 and M5). These findings highlight the potential of this method as a valuable and scalable tool for modern plant breeding programs.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70171"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12750128/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145858680","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":"GWAS-assisted genomic selection for achieving high-precision early sex prediction in Populus deltoides.","authors":"Xinglu Zhou, Min Zhang, Lei Zhang, Jianjun Hu","doi":"10.1002/tpg2.70175","DOIUrl":"10.1002/tpg2.70175","url":null,"abstract":"<p><p>Poplar (Populus spp.) breeding programs increasingly prioritize the development of male varieties due to the environmental issues caused by female catkins. Therefore, there is an urgent need for a reliable technique for early sex identification in Populus. Genomic selection (GS), as an efficient predictive method, offers a promising solution for early sex identification in poplar. In this study, we conducted genomic prediction for sex in Populus deltoides. Using five full-sib families of P. deltoides as the reference population, we identified 801 sex-associated loci through GWAS and precisely localized the sex determination region at the telomeric end of chromosome 19. We evaluated 14 GS statistical models using fivefold cross-validation under six marker densities. The results showed significant differences in prediction accuracy (PA) among different statistical models, ranging from 0.19 to 0.79, with the gradient boosting decision tree exhibiting the highest accuracy and stability. Notably, single nucleotide polymorphisms selected through GWAS significantly improved PA compared to random markers, achieving a corrected accuracy of 0.999. Using the optimal model and markers, we predicted the sex of 505 progenies from 27 full-sib families, with over 90% of the predictions being accurate. Overall, this study achieved high-accuracy sex prediction in P. deltoides through genome prediction, providing a novel and efficient method for poplar sex identification.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70175"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12823031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145991489","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":"Molecular mechanisms associated with rootstock-scion interactions in rubber trees.","authors":"Wanderson Lima Cunha, Vinicius Mandolesi Rios, Alexandre Hild Aono, Danilo Augusto Sforça, Aline Da Costa Lima Moraes, Milene Silvestrini, Jose Marcos Dias Ferreira Junior, Antonio Lucio Mello Martins, Elaine Cristine Piffer Gonçalves, Paulo de Souza Gonçalves, Felipe Roberto Francisco, Anete Pereira de Souza","doi":"10.1002/tpg2.70147","DOIUrl":"10.1002/tpg2.70147","url":null,"abstract":"<p><p>Hevea brasiliensis (rubber tree) is the main source of natural rubber worldwide. In commercial plantations, high-yield rubber tree clones are propagated by grafting onto seedling rootstocks. In this study, the transcriptomes of the RRIM 600 clone grafted on different rootstocks in southeastern Brazil were evaluated. Exclusively expressed genes (EEGs) and differentially expressed genes linked to quantitative trait loci and coexpression networks were identified. The combination of an RRIM 600 scion (clone) with a non-clonal PB 235 rootstock resulted in the highest mean yield (76.03 g/tree dry rubber), followed by non-clonal IAN 873 rootstock (64.30 g/tree dry rubber). In the non-clonal IAN 873 rootstock combination, we identified the RPD3b gene, an EEG associated with the jasmonate pathway, which increases latex production. This effect was not detected in the non-clonal RRIM 600 and nonselected seed (NSS) rootstock combination, which resulted in decreased latex production. Distinct coexpression patterns were observed, with scion condition (RRIM 600): PB 235 showing stronger gene aggregation, indicating more synergistic interactions among the rubber-related genes Hevea rubber transferase, rubber elongation factor, and small rubber particle protein. In contrast, the NSS rootstocks presented a more dispersed pattern and low latex yield. Our findings highlight the importance of initiating rootstock-breeding programs to improve the production of rubber trees and provide valuable insights into the complex interactions between scions and rootstocks and their impact on latex yield in rubber trees.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70147"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12750404/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145858690","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":"Quick creation and mapping of EMS-induced maize kernel mutants identifies classical gene ZmBT1 and novel gene ZmTOP6A.","authors":"Haixiao Dong, Hao Chen, Yuan Jiang, Jingzhe Zhang, Chaoyue Wang, Zhili Sun, Shengzhong Su, Shipeng Li, Hongkui Liu, Xiaohui Shan, Yaping Yuan","doi":"10.1002/tpg2.70210","DOIUrl":"10.1002/tpg2.70210","url":null,"abstract":"<p><p>Maize (Zea mays L.) kernel mutants are valuable tools for investigating kernel development. In this study, we employed ethyl methanesulfonate (EMS) mutagenesis of pollen on five inbred lines, which displayed varying performance after treatment. Over 400 independent kernel mutants were generated, showing a wide range of defects in both type and severity. Bulked segregant analysis (BSA) combined with whole-genome sequencing was employed to map two representative mutants. For a shrunken kernel mutant, a missense mutation (P155L) was identified in the classical ZmBT1 gene, which encodes an ADP-glucose transporter. For a small kernel mutant, a start-lost mutation (M1?) was discovered in the ZmTOP6A gene, which encodes the DNA topoisomerase VI subunit A. Allelic verification of ZmBT1 and ZmTOP6A confirmed their association with the mutant phenotypes. Furthermore, we analyzed the protein conservation, expression patterns, and subcellular localization of both genes. Our study highlights the effectiveness of combining EMS mutagenesis with BSA for mining maize kernel genes. The mutants and the identified genes will advance our understanding of maize kernel development.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70210"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12927126/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147272499","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":"First genome and transcription factor profile for Asimina triloba, a native North American fruit tree.","authors":"Gabdiel E Yulfo-Soto, Hannah Toth, Sarah E Francino, Jason Leung, Lyndel W Meinhardt, G Matt Davies, Jonathan M Jacobs, Stephen P Cohen","doi":"10.1002/tpg2.70181","DOIUrl":"10.1002/tpg2.70181","url":null,"abstract":"<p><p>Pawpaw (Asimina triloba) is the only fruit-producing tree of the soursop (custard apple) family Annonaceae that is native to temperate North America. Pawpaws are extensively cultivated in the northeast United States, but to date, there are few genetic resources and no publicly available genome assemblies. Here, we present the first high-quality genome assembly and annotation of pawpaw (cultivar Mango), derived from high-fidelity third-generation sequencing. The 851.7-Mbp assembly consists of 68 contigs with a scaffold N50 of 28.5 Mbp, guanine-cytosine content of 37%, and a 96.1% benchmarking universal single-copy ortholog completeness score (eudicots). We profiled agronomically relevant transcription factors in the transcription factor family with the DNA-binding WRKY amino acid domain and no apical meristem/Arabidopsis transcription activation factor/cup-shaped cotyledon transcription factor families, which have functions related to environmental and pathogen immunity responses and regulation of fruit traits. Our resource facilitates future genetic and breeding research for this culturally important fruiting tree, expanding its economic and commercial potential.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70181"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12961255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147356321","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":"Genomics in wheat improvement: Progress and perspectives.","authors":"Shaoshuai Liu, Shuaifeng Geng, Susanne Dreisigacker","doi":"10.1002/tpg2.70176","DOIUrl":"10.1002/tpg2.70176","url":null,"abstract":"<p><p>Bread wheat (Triticum aestivum) remains a major source of food and calories globally, yet its vast genome, polyploidy, and high number of repetitive sequences make genomic research challenging in this crop. In this review, we discuss the progress and future perspectives of genome research in wheat. Current efforts focus on the establishment of genome assemblies, advances in functional genomics, advances in epigenetics, translational genetics, and CRISPR-Cas9 genome editing offers a powerful tool for site-specific genome editing for wheat improvement and functional genetic analysis. These approaches have elucidated the genetic basis of many important agronomic traits such as grain yield, biotic and abiotic stress, and wheat quality. Future aims are expected to expand to pan-genomics, the mechanism of wheat domestication, funnel the outputs of functional genomics for deployment in wheat breeding, multi-omics studies facilitate genetic dissection, and the era of big data: creation, integration and utilization, and artificial intelligence breeding.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70176"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12996428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147475883","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":"Integrative machine learning approach for identifying genes associated with quantitative traits: A soybean (Glycine max) yield case study.","authors":"Wei Zhou, Haoyong Ouyang, Zhengxiao Yan, Jiayi Song, Yichan Li, Zhou Tang, Chang Zhao","doi":"10.1002/tpg2.70178","DOIUrl":"10.1002/tpg2.70178","url":null,"abstract":"<p><p>To improve the identification of minor-effect molecular markers and genes associated with quantitative traits, addressing inefficiencies in traditional molecular marker mining and the limited impact of these markers in practical breeding, we analyzed over 15,000 soybean (Glycine max) genotypes across nine maturity groups using an AI-driven genomic approach, uncovering 2513 key genetic markers and 393 genes associated with yield. These included stable determinants unaffected by environmental variability and others with environment-dependent effects. The light gradient boosting machine (LightGBM) model was applied, and model performance was assessed using multiple evaluation metrics across the total datasets by fivefold cross-validation, yielding a mean squared error of 0.0862 and an R² of 0.8369, which demonstrates a strong alignment between predicted and observed yield values. To further validate prediction accuracy, a t-test comparing predicted and actual yields produced a T-statistic of 0.5236 with a p-value of 0.60054, indicating no statistically significant difference between the two distributions. These results confirm the reliability and robustness of the LightGBM approach for yield prediction and underscore its potential utility in breeding programs focused on enhancing agricultural productivity. Our maturity group-based analysis revealed region-specific marker distributions, providing refined targets for precision breeding. Three key principles for marker-assisted selection (MAS) in quantitative trait breeding were introduced: marker complementarity, regional specificity, and quantification. Breeding programs should employ comprehensive sets of region-specific markers, while the effectiveness of MAS can be measured based on the number and SHapley Additive exPlanations value of markers utilized. Our approach to assessing marker sensitivity across environments offers valuable perspectives on genotype-by-environment interactions.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70178"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12834258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042175","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":"Integrative chromosome-scale genome analysis of cupuassu provides insights into witches' broom disease resistance and expands genomic resources for Theobroma.","authors":"Vinicius A C de Abreu, Rafael Moysés Alves, Mauro de Medeiros Oliveira, Vitor Trinca, Loeni Ludke Falcão, Lucilia Helena Marcellino, Antonio Figueira, Douglas S Domingues, Alessandro M Varani","doi":"10.1002/tpg2.70196","DOIUrl":"10.1002/tpg2.70196","url":null,"abstract":"<p><p>Cupuassu (Theobroma grandiflorum) is a fruit tree native to the Brazilian Amazon and increasingly relevant to regional bioeconomies. Its cultivation is severely affected by witches' broom disease (WBD), caused by Moniliophthora perniciosa. While a chromosome-scale genome of the susceptible genotype C1074 is available, the lack of a resistant reference has limited investigation into the genomic basis of resistance. Here, we present the first chromosome-scale assembly of the WBD-resistant genotype C174 (415.8 Mb) and a comparative analysis with C1074 integrating structural variant detection, gene-duplication profiling, transposable-element (TE) annotation, and time-resolved host-pathogen transcriptomics. C174 exhibits distinctive tandem and dispersed duplications, genotype-specific TE insertions, and coordinated defense-gene expression, together with higher heterozygosity indicative of broader allelic diversity. Genome-wide, TEs show differential expression and spatial proximity to immune loci, suggesting potential regulatory importance. Although C1074 encodes more nucleotide-binding domain leucine-rich repeat receptors (541 vs. 434), most remain transcriptionally inactive, whereas C174 shows sequential activation of pattern-recognition receptors, mitogen-activated protein kinase components, transcription factors, and pathogenesis-related proteins. Within the Chromosome 6 previously identified resistance quantitative trait locus, two duplicated DUF4220/DUF594 genes (where DUF is domain of unknown function) unique to C174-orthologous to a maize gene implicated in fungal response before-are infection-induced and display signatures of episodic positive selection. Together, these results establish a high-quality genomic framework for exploring the molecular architecture of WBD response in T. grandiflorum. The datasets generated here-including the C174 and C1074 reference genomes, immune-related variant catalog, and prioritized defense-gene lists-constitute a comprehensive open resource for evolutionary, functional, and breeding research of Theobroma species.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70196"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12834259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042169","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":"Optimizing genomic predictions in maize using a diversity panel and a multiparental population.","authors":"A López-Malvar, R Santiago, A Butrón, R A Malvar, N Gesteiro","doi":"10.1002/tpg2.70206","DOIUrl":"10.1002/tpg2.70206","url":null,"abstract":"<p><p>Genomic selection allows the prediction of genetic values using SNP markers distributed across the genome. Its effectiveness depends on factors such as trait heritability, genetic similarity between training and validation sets, and population structure. Although results in homogeneous populations have been promising, its application in diverse germplasm remains a challenge. This study evaluates the predictive capacity of genomic best linear unbiased prediction models applied to agronomic and biochemical-structural traits related to stover quality in two maize populations: a diversity panel and a multiparental advanced generation inter-cross (MAGIC) population. Higher heritability was observed in the panel, especially for flowering traits (h² ≥ 0.88), with high intra-population predictive abilities (PA = 0.15-0.75) for most traits, compared to MAGIC (PA = 0.14-0.37). However, when applying the models from one population to another (cross-population prediction), the predictive ability was drastically reduced for most traits (PA < 0.05), possibly due to differences in allele frequencies and phases of linkage disequilibrium. Combining both populations in a single training set did not improve prediction (PA = 0.13-0.74) and even reduced it in some cases. These results indicate that genetic heterogeneity and differences in linkage disequilibrium between populations compromise the stability of marker effects. Therefore, it is critical to optimize the training set composition by considering genetic relatedness and population structure to improve the efficiency of genomic selection in diverse germplasm.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70206"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12935694/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147311676","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":"Introgression of wild barley alleles improves seedlings salinity tolerance in the nested association mapping HEB-400 population.","authors":"Matías Schierenbeck, Radwa Y Helmi, Andreas Maurer, Rasha A Tarawneh, Doaa H Ali, Hannah M Schneider, Andreas Börner, Klaus Pillen, Helmy M Youssef","doi":"10.1002/tpg2.70217","DOIUrl":"10.1002/tpg2.70217","url":null,"abstract":"<p><p>Climate change is intensifying the frequency and severity of abiotic stresses that threaten global food security by reducing crop productivity. Among these, saline stress poses a serious threat to barley (Hordeum vulgare L.) production. These conditions are increasingly prevalent in arid and semiarid regions, as well as in regions with limited access to freshwater resources, making the identification of salt tolerance genes essential for breeding resilient varieties. In this study, we evaluated 400 genotypes from the barley nested association mapping population HEB-25 under control conditions and 40% seawater irrigation to simulate moderate-to-high salinity stress. A genome-wide association study (GWAS) was conducted to identify alleles from wild barley [H. vulgare L. subsp. spontaneum (C. Koch) Thell.] associated with enhanced salt tolerance. Phenotypic evaluation included germination percentage (Ger%), shoot length (SL), root length (RL), root-shoot length ratio, seedling fresh weight, seedling dry weight, and salt tolerance index of the different traits. The HEB-25 families exhibited significant variation in seedling responses to seawater-induced salinity, with contrasting effects on SL, RL, and dry weight. Compared to the elite parental Barke, several genotypes demonstrated high tolerance under seawater stress, maintaining stable Ger% and exhibiting the highest tolerance indices. Moreover, GWAS results identified 60 highly significant single nucleotide polymorphisms associated with seedling growth parameters under both conditions. These findings underscore the value of the HEB-400 panel as a genetic resource for dissecting salinity tolerance mechanisms, identifying stress-adaptive alleles lost during domestication and a source of pre-breeding material for developing genotypes with enhanced salinity tolerance.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70217"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12989094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464205","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}