Plant Genome最新文献

{"title":"Genome-wide association studies for identifying SNPs and candidate genes associated with grain quality traits in rice (Oryza sativa L.).","authors":"Shivani Darmagaru, Abdul Fiyaz Rahaman, Farzana Jabeen, Aravind Kumar Jukanti, Chaithanya Kasarla, Dileep Kumar Gowdru Dhananjaya, Arivelarasan Tamilarasu, LellaVenkata Subba Rao, Supriya Kallakuri, Shoba Venkatanagappa, Raman Meenakshi Sundaram","doi":"10.1002/tpg2.70190","DOIUrl":"10.1002/tpg2.70190","url":null,"abstract":"<p><p>Ensuring superior quality is of paramount objective in modern rice (Oryza sativa L.) breeding program and investigating quality traits is crucial for developing superior rice varieties. The current study aimed for identifying single nucleotide polymorphisms (SNPs) and potential candidate genes for eleven quality traits, namely, hulling %, milling %, kernel length, kernel breadth, kernel length to breadth ratio, grain type, head rice recovery, chalkiness, amylose content, alkali spreading value, and gel consistency, using genome-wide association studies (GWASs) on diverse germplasm sourced from various rice-growing regions around the world. Phenotypic evaluation revealed significant genetic diversity among germplasm, with substantial natural variation observed across 10 quality-related traits. GWAS using 7K SNP chip identified 31 SNPs significantly linked to grain quality traits, of which 20 were novel and 11 had been previously reported, including two co-localized SNPs (GS3 and SNP-6.6652023) associated with multiple traits. In addition, 121 candidate genes related with these traits were identified and categorized into seven molecular functions, four cellular components, and nine biological processes. Notably, 17 putative grain quality-related genes were identified, viz., GS3 (Grain size regulator), Wx (granule-bound starch synthase), OsZIP7 (ZIP family protein), OsRING4 (RING-type E3 ubiquitin ligase), OsMKK3 (Mitogen-activated protein kinase), OsSSIV-2, OsSSIIa/SSII-3 (ALK; soluble starch synthase), and OsbZIP58 (bZIP transcription factor). The identified SNPs and potential candidate genes represent a valuable genomic resource for accelerating rice breeding programs focused on the enhancement of key quality traits.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70190"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13058673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634880","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 genomic analyses reveal candidate genes for the Ur-3 and Ur-7 rust resistance loci in common bean.","authors":"Alvaro Soler-Garzón, Giseli Valentini, Marcial Pastor-Corrales, Ruifeng He, Phillip N Miklas","doi":"10.1002/tpg2.70253","DOIUrl":"10.1002/tpg2.70253","url":null,"abstract":"<p><p>Bean rust, caused by Uromyces appendiculatus, severely limits the productivity of common bean (Phaseolus vulgaris L.), an essential source of protein and micronutrients in human diets worldwide. Durable disease management relies primarily on host resistance; however, the molecular architecture of several key rust resistance loci remains unresolved. We sought to characterize the genomic structure of the Ur-3 and Ur-7 loci and develop associated molecular markers. An integrative genomic framework combining high-resolution long-read genome assemblies, recombinant inbred line populations, and single-nucleotide polymorphism-based and k-mer-based genome-wide association studies was used to fine-map both loci. Extensive structural variation was revealed for the Ur-3 locus at the distal end of chromosome Pv11, whereas Ur-7 localized to a low-recombination pericentromeric region of the same chromosome. A coiled-coil nucleotide-binding leucine-rich repeat gene embedded within an NB-ARC-rich cluster was identified as the most likely candidate underlying Ur-3 (Pv11: 50,205,868-50,209,452 bases; USDA Rattler reference). In contrast, the refined Ur-7 interval contained a toll/interleukin-1 receptor NLR gene as the leading candidate (Pv11: 36,604,755-36,611,252; UI 111 reference). Gene-based markers developed from these candidates showed complete correspondence with rust phenotypes. Marker-assisted selection for Ur-3 and Ur-7 will contribute to the development of durable rust resistance against the highly variable bean rust pathogen U. appendiculatus.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 2","pages":"e70253"},"PeriodicalIF":4.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13492622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148007260","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":"Harnessing genomic resources for passion fruit improvement: Progress and prospects.","authors":"Khushboo Fulara, Vanika Garg, Xinhang Sun, Rebecca Ford, Natalie Dillon, Bruce Topp, Robert J Henry, Mobashwer Alam, Rajeev K Varshney","doi":"10.1002/tpg2.70213","DOIUrl":"10.1002/tpg2.70213","url":null,"abstract":"<p><p>Passion fruit (Passiflora edulis) is a highly nutritious horticultural crop cultivated widely across tropical and subtropical regions. Despite decades of breeding efforts that have led to the release of a few high-yielding cultivars, on-farm productivity remains suboptimal, and several existing cultivars are showing signs of declining vigor. To ensure the development of cultivars with stable and enhanced yields under both optimal and stress-prone conditions, there is a growing impetus to improve breeding efficiency. Integrating advanced genomics technologies into conventional breeding pipelines offers a promising path forward. Over the past decade, substantial genomic resources have been developed, including genome-wide markers, marker-trait associations, reference genomes, and resequencing datasets. Some of these tools are already being deployed in breeding programs to enhance yield and consumer-preferred traits. Emerging approaches such as genomic selection, speed breeding, and high-throughput phenotyping hold further potential to accelerate genetic gains. Realizing the full benefits of these tools will require strategic utilization of diverse and targeted genetic resources, coupled with streamlined cultivar delivery systems. Addressing the technical and operational bottlenecks that hinder the translation of genomic advances to field-ready cultivars will be key to securing the future of passion fruit improvement.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70213"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12993108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147469740","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 mirage of DNA methylation in transcriptional regulation of plants.","authors":"Peter Civan, Iris Sammarco, Meriem Banouh","doi":"10.1002/tpg2.70208","DOIUrl":"10.1002/tpg2.70208","url":null,"abstract":"<p><p>\"Cytosine methylation plays an important role in the regulation of gene expression in plants.\" Some iteration of this statement can be found in most papers centered on plant epigenetics and has become a widely accepted textbook claim. However, our generalized understanding of how DNA methylation exerts control over transcription is now challenged by observations demonstrating that transcriptional levels of most genes are unresponsive to DNA methylation changes. On a genome-wide scale, associations between DNA methylation and transcription are usually statistically weak. Even when correlations are found, the cause and effect can be difficult to identify, as methylation changes sometimes follow rather than precede transcriptional changes. While a growing number of studies explore a possible connection between differentially expressed genes (DEGs) and differentially methylated genes (DMGs), we demonstrate here that DEG-DMG overlaps are often significantly smaller than what could be expected by chance. This indicates that, contrary to expectations, changes in DNA methylation and changes in transcription sometimes avoid one another. Here, we discuss such observations and their implications for the hypothesis of a widespread control of gene expression directly by DNA methylation. While there are well-documented examples where DNA methylation regulates transcription, we argue that such cases represent a minority of genes, and we opine that approaches of reverse epigenetics are therefore unlikely to find broad application in breeding.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70208"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12953739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345546","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":"Randomization across breeding cohorts improves the accuracy of conventional and genomic selection.","authors":"Arlyn Ackerman, Jessica Rutkoski","doi":"10.1002/tpg2.70218","DOIUrl":"10.1002/tpg2.70218","url":null,"abstract":"<p><p>Breeding programs conventionally evaluate cohorts in separate trials; however, environmental differences across testing areas can be confounded with genetic differences between cohorts, potentially reducing the accuracy of breeding value estimation. We test whether the conventional approach of restricting randomization of cohorts to within trials reduces genomic and conventional selection accuracy when compared to the complete randomization of all cohorts across a trial, using in silico simulation with marker data from University of Illinois winter wheat breeding lines. We evaluated selection accuracy for conventional best linear unbiased prediction (BLUP), genomic BLUP (GBLUP), and genomic-enabled sparse testing across a comprehensive simulation space spanning narrow-sense heritabilities of 0.2-0.8, genetic correlations between testing areas from 0.2 to 1.0, and three replication levels. Difference-in-differences (DiD) analysis established causal inference by comparing design performance as conditions deteriorated from an optimal baseline where both designs performed equivalently. Complete randomization improved BLUP accuracy by 11.7%, reaching 15.7% under low replication and low genetic correlation between areas. Genomic data largely eliminated this design effect, with GBLUP showing no significant DiD interaction effect. However, genomic-enabled sparse testing revealed a significant DiD effect and an improvement in selection accuracy of 1.5% that increased to a 5.5% advantage under challenging conditions. While heritability had the strongest main effect on selection accuracy, genetic correlation between areas showed the largest interaction with randomization scheme, with design performance diverging significantly only as this parameter decreased. Programs with genomic data and balanced phenotypic data can use either restricted or complete randomization, but those with other circumstances can benefit from complete randomization.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70218"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12993266/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147469826","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":"Genome-wide association analysis to identify QTLs and candidate genes associated with grain yield and its related traits under low light conditions in rice (Oryza sativa L.).","authors":"Swagatika Das, Soumya Mohanty, Darshan Panda, Nalini K Choudhury, Baneeta Mishra, Ranjan K Jena, Devanna Bn, Reshmiraj Kr, Awadesh Kumar, Khirod K Sahoo, Anil Kumar C, Rameswar P Sah, Sharat K Pradhan, Sanghamitra Samantray, Mirza J Baig, Lambodar Behera","doi":"10.1002/tpg2.70191","DOIUrl":"10.1002/tpg2.70191","url":null,"abstract":"<p><p>Low-light (LL) stress caused by persistent cloud cover during the Kharif season significantly reduces rice (Oryza sativa L.) grain yield (GY) by limiting photosynthesis, impairing assimilate production, and affecting reproductive development. To dissect the genetic basis of LL tolerance, 192 diverse rice genotypes were evaluated across contrasting light environments (LL and normal light under Rabi and Kharif seasons) and genotyped using a high-density 44K single nucleotide polymorphism array. Integrating phenotypic and genomic data enabled a multi-tiered analysis from quantitative trait locus (QTL) discovery to gene identification and haplotype dissection. Genome-wide association analysis identified 305 QTLs associated with GY and 11 related traits, including 148 LL-specific and 32 stable QTLs expressed across both seasons. Forty-two candidate genes were localized within major QTL intervals, and 12 were identified as hub genes based on their key roles in photosynthesis, light perception, hormone signaling, and starch biosynthesis. These included Gn1a, OsPsbS1, OsAGPL2, OsLhcb1, OsAUX1, OsSBDCP1, OsNPF5.16, OsPHYA, OsPHYB, OsGIF1, HY5, and OsYUC11. Expression profiling confirmed stronger induction of OsPHYA (∼2.5-fold) and OsPsbS1 (∼2.8-fold) in LL-tolerant genotypes like Purnendu and Swarnaprabha compared to susceptible lines. Haplotype analysis revealed several superior alleles, such as PHYA-Hap2 and OsPsbS1-Hap3, that were consistently associated with higher spikelet fertility, greater grain number, increased biomass, and improved GY under LL, with top-performing haplotypes enhancing yield by 12%-18%. Genotypes carrying these haplotypes (e.g., Purnendu, Swarnaprabha, and Chamarmani) represent valuable breeding donors. Overall, this study provides the first genome-wide identification of LL-specific haplotypes in rice, together with biologically validated hub genes. These findings offer actionable genomic targets and donor resources for developing LL-resilient, high-yielding cultivars suited to changing climate and light-limited environments.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70191"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12961260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147356773","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":"Integrated GWAS and Fst analysis identify flowering-time regulatory genes in maize.","authors":"Dong Wang, Zhuoya Gao, Mengyue Dong, Tuan Li, Wenjing Zhou, Jialei Ou, Shiya Zhang, Shuaishuai Zhang, Xian Dong, Yalan Li, Caihui Zhang, Jiahao Tie, Yinuo Wang, Gaoyang Sun, Huiling Xie, Weihua Li, Jihua Tang, Pengshuai Yan","doi":"10.1002/tpg2.70185","DOIUrl":"10.1002/tpg2.70185","url":null,"abstract":"<p><p>Flowering time in maize is a complex quantitative trait regulated by multiple genes, and its genetic variation mechanisms remain to be fully elucidated. In this study, we phenotypically evaluated flowering-related traits (days to tasseling, days to pollen shedding, days to silking) across six different environments using an association population comprising 368 maize varieties. Genome-wide association studies were employed to dissect the genetic basis of these traits. A total of 261 significant association single nucleotide polymorphisms (SNPs; logarithm of odds > 5.5) were detected, among which 23 SNPs were consistently identified across multiple environments or traits. By integrating population fixation index, we further screened 41 potential candidate genes, including Zm00001d006213, Zm00001d027394, and Zm00001d027395, which are likely key regulators of flowering time. These findings provide both theoretical insights into the genetic regulatory network of maize flowering time and valuable gene resources for molecular breeding.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70185"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12825026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146020255","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":"Impact of environmental covariates summarization on predictive ability in genomic selection.","authors":"Vitor Seiti Sagae, Moysés Nascimento, Ana Carolina Campana Nascimento, Felipe Lopes da Silva, Diego Jarquin","doi":"10.1002/tpg2.70194","DOIUrl":"10.1002/tpg2.70194","url":null,"abstract":"<p><p>Integrating genomic and environmental information holds the potential for enhancing the predictive power of genomic prediction models when accounting for the genotype-by-environment interactions. Hence, incorporating environmental covariates (EC) into these models can significantly influence their predictive accuracy. In this study, we utilized 1379 genotypes from the SoyNAM dataset, evaluated across four environments and genotyped with 4611 single-nucleotide polymorphism markers, to compare models incorporating genotype-by-environment and genotype-by-environmental covariate interactions using different covariance matrices. We evaluated four approaches: summarizing EC by averaging (AVG), filtering ECs based on a coefficient of determination criterion (FILT), segmenting ECs by crop phenology (STG), and a naïve approach that utilized all available information (ALL). Predictive ability was assessed as the Pearson's correlation between the genomic estimated breeding values and the adjusted phenotypes considering 10 replicates of three cross-validation scenarios (CV2: predicting tested genotypes in observed environments; CV1: untested genotypes in observed environments; CV0: tested genotypes in novel environments). Incorporating EC information into the models increased average predictive ability from 0.42 to 0.56 for CV1 and CV2. In these cases, the predictive ability was lower when EC information was averaged to compute the environmental kinship matrix, with slight differences observed with respect to the other approaches. Regarding the CV0 scheme, the model incorporating only genotype-by-environment information performed better (0.33). The naïve method, which utilized all available EC information (ALL), proved to be a promising approach, as it effectively improved the results in these scenarios while eliminating the need for additional steps in selecting variables.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70194"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12849757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146053970","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":"Dissecting multi-rust resistance in wheat through genome-wide association study, haplotype analysis, and marker validation.","authors":"Thamaraikannan Sivakumar, Divya Sharma, V K Vikas, Neeraj Budhlakoti, O P Gangwar, Pramod Prasad, Ankita Mohapatra, Sathishkumar R, Deepak Singh Bisht, Priyanka Jain, Ritu Sharma, Bonipas Antony John, Reyazul Rouf Mir, Farkhandah Jan, Dwijesh C Mishra, Satinder Kaur, Amit Kumar Singh, G P Singh, Sundeep Kumar","doi":"10.1002/tpg2.70188","DOIUrl":"10.1002/tpg2.70188","url":null,"abstract":"<p><p>Wheat is a major global staple food affected by three diseases: leaf rust (LR), stem rust (SR), and stripe rust (YR), all of which can cause substantial yield losses. Identifying genotypes with broad-spectrum resistance to diverse pathotypes of all three rusts remains a major challenge. In this study, we examined the genomic basis of resistance to three rust diseases LR, SR, and YR in a diverse panel of 346 bread wheat (Triticum aestivum) accessions. The seedling stage phenotypic evaluation was performed for 2 years using prevalent and virulent pathotypes. Based on best linear unbiased estimators, LR and YR displayed right-skewed distributions, whereas SR showed a bimodal pattern. Genotyping with the 35K Axiom Wheat Breeders Array, followed by quality control, yielded 11,910 high-quality single nucleotide polymorphisms (SNPs). Population structure analysis revealed five subpopulations and a whole genome linkage disequilibrium decay of 3.49 Mb. Multi-trait genome-wide association studies identified 11 significant SNPs distributed on chromosomes 3A, 3B, 3D, and 7B, which were associated with 47 disease resistance genes, 22 of which were highly expressed in at least one condition. The haplotype analysis revealed eight different haplotypes, where H006 and H007 were superior in terms of multiple rust resistance (MRR). Note that 17 elite accessions, including IC427824 and HGP1-359, were selected using multi-trait genotype ideotype distance index analysis. Three key Kompetitive allele specific polymerase chain reaction (KASP) markers, AX94381808, AX94874313, and AX94807942 were developed and validated. This integrated genomic approach advances the identification process and can accelerate the breeding of wheat cultivars with durable MRR.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70188"},"PeriodicalIF":4.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12919733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146221604","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":"Correction to \"Exon disruptive variants in Populus trichocarpa associated with wood properties exhibit distinct gene expression patterns\".","authors":"","doi":"10.1002/tpg2.70225","DOIUrl":"10.1002/tpg2.70225","url":null,"abstract":"","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"19 1","pages":"e70225"},"PeriodicalIF":3.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13169224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147488195","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}