Molecular Breeding最新文献

{"title":"Cytogenetic identification and molecular marker development of a novel wheat-tetraploid <i>Thinopyrum elongatum</i> small fragment translocation line with stripe rust resistance gene <i>Yr4EL</i>.","authors":"Linfeng Chen, Qianyi Guo, Linglin Liu, Hang Peng, Wei Zhu, Lili Xu, Jian Zeng, Yi Wang, Yiran Cheng, Xing Fan, Yinghui Li, Yonghong Zhou, Dandan Wu, Houyang Kang","doi":"10.1007/s11032-026-01714-0","DOIUrl":"10.1007/s11032-026-01714-0","url":null,"abstract":"<p><p>Tetraploid <i>Thinopyrum elongatum</i> (2<i>n</i> = 4<i>x</i> = 28, EEEE) is a valuable genetic resource for wheat improvement, harboring genes conferring resistance to multiple diseases, including stripe rust, powdery mildew, and <i>Fusarium</i> head blight. In our previous study, we developed the wheat-tetraploid <i>Thinopyrum elongatum</i> translocation line T4DS·4DL-4EL, which carries a 49.59 Mb terminal segment of chromosome 4EL containing the <i>Yr4EL</i> stripe rust resistance locus. In this study, the <i>ph1b</i> mutant was used to promote homoeologous recombination and reduce the size of the 4EL introgression. Four novel small-fragment T4DS·4DL-4EL translocation lines carrying terminal 4EL segments of 13.22 Mb, 1.99 Mb, 1.42 Mb, and 1.08 Mb were identified and characterized using GISH, FISH, and molecular markers. Stripe rust response evaluation showed that only T4DS·4DL-4EL#3 exhibited all-stage resistance to stripe rust, and genetic analysis demonstrated complete association between the 13.22 Mb 4EL introgression and resistance in the F₂ population. Two Kompetitive Allele-Specific PCR markers were developed to distinguish plants carrying the 13.22 Mb 4EL introgression and showed complete concordance with the resistance phenotype in the F₂ population. By integrating the breakpoint information from these translocation lines with our previously reported genetic mapping results, the candidate interval of <i>Yr4EL</i> was narrowed to approximately 0.8 Mb (610.2-611.0 Mb), flanked by the molecular markers <i>TTE4E-7767</i> and <i>TS4E-1915</i>. Three specific Sequence-Tagged Site markers co-segregating with this 0.8 Mb interval were also developed. Collectively, the small fragment translocation lines developed in this study provide new germplasm resources for gene cloning and breeding utilization.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01714-0.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"93"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of stable QTLs for spike length and density and development of KASP markers for wheat breeding.","authors":"Aoyan Zhang, Xin Zhang, Wensha Zhao, Xiaoran Guo, Shengjie Sun, Pengbo Song, Huiling Zhao, Yueyue Li, KeFeng Song, Yuanhang Xing, Jianhui Wu, Daojie Sun","doi":"10.1007/s11032-026-01713-1","DOIUrl":"10.1007/s11032-026-01713-1","url":null,"abstract":"<p><p>Spike length (SL) and spikelet density (SD) are core agronomic traits determining spike development and grain yield. Dissecting their genetic basis is crucial for high-yield wheat breeding. In this study, a population of 209 recombinant inbred lines (RILs) derived from the cross 'Lantian 26' × 'Luohan 6' was evaluated. Genetic loci controlling SL and SD were systematically explored using multi-environment phenotypic data and a high-density genetic map based on a 16 K SNP array. Consequently, two major, stable, and pleiotropic QTLs (<i>QSl/Sd.LT-4A.2</i> and <i>QSl/Sd.LT-5A</i>) were identified, consistently co-regulating both SL and SD across multiple environments. To facilitate marker-assisted selection (MAS), we successfully developed a functional KASP marker for the <i>QSl/Sd.LT-4A.2</i> interval, alongside gene-specific markers targeting sequence variations within the putative candidate genes for <i>QSl/Sd.LT-5A</i>. Validation in a diverse natural population confirmed that the favorable alleles at both loci significantly improve spike architecture and thousand-grain weight (TGW). Furthermore, pyramiding these two major loci exerted a significant additive effect, providing an effective genetic strategy to enhance wheat yield potential. The identified pleiotropic QTLs and the newly developed KASP markers offer useful genetic loci and practical diagnostic tools for high-yielding wheat breeding.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01713-1.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"92"},"PeriodicalIF":3.6,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13562465/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic dissection of plant height in the CIMMYT elite wheat germplasm through functional <i>Rht</i> allele profiling.","authors":"Yingjie Bian, Susanne Dreisigacker, Yachao Dong, Claudia Núñez Riso, Jindong Liu, Yong Zhang, Xiancun Xia, Shuanghe Cao, Zhonghu He","doi":"10.1007/s11032-026-01715-z","DOIUrl":"10.1007/s11032-026-01715-z","url":null,"abstract":"<p><p>Plant height strongly influences wheat yield potential and stability. The causal genes underlying seven <i>reduced height</i> (<i>Rht</i>) loci have already been cloned and gene-specific markers are available for their deployment in wheat breeding. As the birthplace of the wheat Green Revolution, the International Maize and Wheat Improvement Center (CIMMYT) has driven global yield gains through the widespread adoption of the dwarfing genes <i>Rht-B1b</i> and <i>Rht-D1b</i>, and maintains the world's largest open-access wheat germplasm collection. Here, diagnostic markers for the cloned <i>Rht</i> genes were evaluated in a panel of 369 elite wheat lines from CIMMYT's international screening nurseries. A breeder-friendly kompetitive allele-specific PCR (KASP) marker was developed to distinguish <i>Rht24a</i> and <i>Rht24b</i>. Genotyping revealed a strong predominance of <i>Rht-B1b</i> (100% frequency), while <i>Rht24b</i> and <i>Rht25d</i> were present at lower frequencies (13.9% and 6.7%, respectively). By contrast, the widely used <i>Rht-D1b</i> and <i>Rht8b</i> was nearly absent with 0.3% and 1.1%, respectively, and <i>Rht12b</i> were not detected in these CIMMYT wheat lines. Marker-trait association analyses showed no consistent or significant effects of the dwarfing alleles <i>Rht24b</i> and <i>Rht25d</i> on plant height across most of environments. Allelic combinations involving these loci were also rare; the most frequent combinations (<i>Rht-B1b</i>+<i>Rht24b</i>+<i>Rht25d</i>, and <i>Rht-B1b</i>+<i>Rht24b)</i> occurred at only 5.8% and 4.9%, respectively, and confer minimal differences in plant height relative to <i>Rht-B1b</i> alone. These results highlight the overwhelming dominance of <i>Rht-B1b</i> in CIMMYT germplasm and the limited contribution of other functional <i>Rht</i> alleles.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01715-z.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"91"},"PeriodicalIF":3.6,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13558526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148930553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A BLH12-KN1 transcriptional module regulates embryo size in maize.","authors":"Tao Yun, Xiaoxia Du, Wenkang Chen, Xiaowei Li, Xuan Zhang, Min Wang, Jianghua Guo, Sixuan Xu, Pengfei Yin, Huaijun Tang, Jiansheng Li, Yingni Xiao, Xiaohong Yang","doi":"10.1007/s11032-026-01716-y","DOIUrl":"10.1007/s11032-026-01716-y","url":null,"abstract":"<p><p>Embryo development is a critical determinant of plant growth and a major contributor to grain nutritional value in maize. In this study, we identified natural variations in <i>BLH12</i>, which encodes a BEL1-like homeodomain transcription factor, that is significantly associated with embryo size in maize. SNP-506, located in the 5' untranslated region, and SNP3670 (A-to-G), resulting in a glutamine-to-arginine substitution in the last exon, were shown to be the causal variants of <i>BLH12</i> for embryo size. Loss-of-function of <i>BLH12</i> reduced embryo length, width, and thickness, leading to decreased embryo size and weight. Histological analysis revealed that <i>BLH12</i> acts from the late embryo proper stage onward and sustains its regulatory activity throughout subsequent development. The knockout of KN1, an interacting partner of BLH12, exhibited comparable defects in embryo morphology and kernel traits. Transcriptomic profiling along with published KN1 ChIP-seq targets further revealed a potential cooperative regulatory relationship between BLH12 and KN1 during maize embryo development. These findings uncover <i>BLH12</i> as a key regulator of maize embryogenesis and provide a promising target for improving kernel nutrients in maize breeding.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01716-y.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"90"},"PeriodicalIF":3.6,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13550389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148912089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SNPoptimizer: a scalable genetic-algorithm framework to derive minimal discriminatory SNP panels from large genotyping datasets.","authors":"Salvatore Esposito, Nicola Scalzi, Samuela Palombieri, Walter Sanseverino, Francesco Sestili, Alessandra Stella, Raffaella Balestrini, Stefania Grillo, Ray Anthony Bressan, Giorgia Batelli","doi":"10.1007/s11032-026-01707-z","DOIUrl":"10.1007/s11032-026-01707-z","url":null,"abstract":"<p><p>The ability to efficiently discriminate genotypes is a critical step in genomics-assisted breeding, population genomics, biodiversity studies, traceability along food chains, and germplasm management. However, identifying the minimal and most informative subset of SNPs capable of uniquely distinguishing a large set of individuals remains a computationally challenging task. Here, we present SNPoptimizer, a user-friendly Shiny application that uses a genetic algorithm-based framework to optimally select discriminatory SNPs from large-scale genotyping datasets. By leveraging the evolutionary principles of selection, mutation, and crossover, SNPoptimizer iteratively identifies compact SNP panels that maximize genotype resolution. The application supports HapMap-formatted and VCF genotype files and includes an optional second-round optimization for resolving putative duplicates. We benchmarked SNPoptimizer across three independent datasets, including a tomato diversity panel, 820 Cauliflower genotypes, and a soybean diversity panel comprising 30 million variants across 1,511 samples. Across the three datasets, panels of 17-22 SNPs yielded R-VDP values ranging from 0.8744 to 0.9973, with complete discrimination obtained in Dataset III, demonstrating robust performance across different datasets. Cross-tool comparisons revealed complementary trade-offs among discriminatory power, panel size, runtime, and run-to-run reliability. SNPoptimizer provides a flexible solution for researchers seeking to reduce genotyping costs while maintaining high discriminative power.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01707-z.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"89"},"PeriodicalIF":3.6,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13525983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TaDEP1 regulates grain size and abiotic stress tolerance by interacting with TaMyb309 in bread wheat.","authors":"Chao Fu, Ying Zhou, Xing Zhang, Hao Chen, Mengyao Li, Li Yin, Xiangxu Ren, Hailiang Mao","doi":"10.1007/s11032-026-01710-4","DOIUrl":"10.1007/s11032-026-01710-4","url":null,"abstract":"<p><p><i>TaDEP1</i>, a heterotrimeric G protein γ subunit gene, was characterized as a positive regulator of grain size and thousand-grain weight (TGW) in bread wheat. Association analysis in 492 global wheat accessions and validation in a recombinant inbred line population identified a missense SNP (C/G) in <i>TaDEP1-5 A</i> that causes a cysteine to tryptophan substitution, with the <i>TaDEP1-5 A-C</i> allele significantly associated with increased grain width and TGW. This favorable allele has been preferentially selected during breeding, increasing from 15.10% in landraces to 45.20% in modern cultivars. CRISPR/Cas9 knockout of all three <i>TaDEP1</i> homoeologs reduced grain length (12.25-13.16%), grain width (15.01-18.25%), and TGW (42.31-45.67%). Notably, <i>tadep1</i> mutants exhibited enhanced tolerance to salt, drought, alkali, and heat stress, revealing a trade-off where <i>TaDEP1</i> promotes yield but represses stress tolerance. Yeast two-hybrid and luciferase complementation assays identified TaMyb309, a grain-specific MYB transcription factor, as a TaDEP1 interactor. BSMV-mediated CRISPR/Cas9 mutants of <i>TaMyb309</i> showed increased grain size and weight, indicating it acts as a negative regulator antagonistic to TaDEP1. Our findings establish TaDEP1 as a key regulator balancing grain yield and stress adaptation, possibly through interaction with TaMyb309. A functional KASP marker (KS17) developed for the elite <i>TaDEP1-5 A-C</i> haplotype provides a valuable tool for marker-assisted selection in wheat breeding.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01710-4.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"88"},"PeriodicalIF":3.6,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13525984/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing epistatic architecture to improve genomic selection accuracy for soybean pod number.","authors":"Lina Dong, Ruixin Zhang, Huixin Jiang, Xiaoyue Zhu, Meng Wang, Changhong Guo, Yongjun Shu","doi":"10.1007/s11032-026-01711-3","DOIUrl":"10.1007/s11032-026-01711-3","url":null,"abstract":"<p><p>Soybean (<i>Glycine max</i> [L.] Merr.) is a globally critical oilseed and protein crop, and pod number per plant (PN) is a core determinant of soybean grain yield. Conventional genomic selection (GS) for PN almost exclusively focuses on additive genetic effects, leading to low prediction accuracy, while traditional genome-wide epistasis analysis suffers from high false positive rates and insufficient biological validation. In this study, based on the Nongdadou2 reference genome and resequencing data of 477 soybean accessions, we performed pathway-level genome-wide epistasis analysis for PN via the BridGE pipeline, identified non-redundant favorable epistatic pairs, constructed epistatic interaction networks, and validated the biological authenticity of these pairs through AlphaFold2-based protein three-dimensional structure modeling and protein-protein interaction enrichment test, along with genotypic combination effect analysis. Integrating these validated favorable epistatic effects into six mainstream GS models achieved an average absolute improvement of 0.42 in PN prediction accuracy across all models. This study provides an effective strategy and practical technical framework for optimizing GS performance for soybean PN.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s11032-026-01711-3.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 9","pages":"87"},"PeriodicalIF":3.6,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522278/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148850935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven tri-typing in agriculture: Current advances, future frontiers.","authors":"Shabbir Hussain, Ishrat Naureen, Madiha Habib, Faisal Saeed Awan, Hasham Feroz Ghuman, Alam Sher, Muhammad Waheed Riaz, Hafiz Muhammad Usman, Saddam Hussain, Fanmei Kong, Xiaocun Zhang","doi":"10.1007/s11032-026-01705-1","DOIUrl":"10.1007/s11032-026-01705-1","url":null,"abstract":"<p><p>Sustainable crop improvement is urgently needed to ensure global food security, particularly for developing and densely populated countries. The integration of artificial intelligence (AI) and machine learning (ML) into crop science tri typing is reshaping the conventional agriculture practices into an era of high-throughput phenotyping (HTPP) data-driven modern agriculture. AI tools accelerate data generation, mining, imputation, storage, transfer, and optimal decision-making within agricultural systems. AI tools are paving the way for modern plant breeding strategies by uncovering genetic variability and bridging the genotype-to-phenotype (G2P) gap, thus enabling the future of predictive breeding. Plant genetic gains or phenotype (P), by and large, depend on the genotype (G), environment (E), and their interaction (GEI). This review will provide a comprehensive overview of the historical background, current status, and prospects for integrating AI and ML tools in agricultural tri-typing, encompassing genotyping, phenotyping, and envirotyping. We explore AI-driven tools for genome analysis, HTPP platforms, and environmental data integration, emphasizing how these technologies overcome persistent bottlenecks in predictive breeding. Furthermore, this review will offer the reader key insight into modern trends, including the paradigm shift in phenomics patent filings, global distribution of HTP phenomics facilities, the publications volume and related research over the last two decades, and individual institutions currently leading or prospectively will lead the world in plant phenomics. Similar to plant phenotyping, we also try to address the integration and application of AI/ML algorithms in plant genotyping and envirotyping.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11032-026-01705-1.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 8","pages":"81"},"PeriodicalIF":3.6,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13477464/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148758597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breaking the growth-defense trade-off in cereal crops: CRISPR/Cas and moonlighting proteins in biotic stress resistance.","authors":"Obaid Ullah","doi":"10.1007/s11032-026-01703-3","DOIUrl":"10.1007/s11032-026-01703-3","url":null,"abstract":"<p><p>Recurrent crop disease outbreaks linked to global warming pose challenges to sustainable food production. Conventional plant breeding techniques may become less effective at addressing these threats, as improving disease resistance often causes yield reduction. Amid these challenges, CRISPR/Cas-based gene editing offers targeted and tractable solutions. This review synthesizes recent approaches to uncoupling immunity from productivity in cereals. We show that susceptibility (S) gene disruption can provide resistance without activating costly defense mechanisms. We also discuss the generation of new alleles through targeted modifications that mitigate autoimmunity-associated fitness costs. Here, we propose CRISPR-mediated de-moonlighting, an approach for decoupling multifunctional protein activities. Multiplex editing of minor resistance loci, especially in polyploids such as wheat, offers long-lasting, broad-spectrum protection. These strategies converge on the manipulation of canonical moonlighting proteins, multifunctional signaling hubs, and pleiotropic regulators, which serve as regulatory nodes that link development and immunity. CRISPR-mediated precision modification of these regulators can fine-tune the growth-defense balance. Combining these approaches with systems biology, AI-driven design and advanced breeding pipelines can help develop high-yielding, disease-resistant cereals for sustainable agriculture.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 8","pages":"80"},"PeriodicalIF":3.6,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451465/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148697745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction and evaluation of 9311 resistance gene pyramiding lines with combined resistance to brown planthopper and rice blast.","authors":"Shiyuan Cheng, Mingsong Zhou, Wenjie Luo, Yuqing He, Guanjun Gao","doi":"10.1007/s11032-026-01702-4","DOIUrl":"10.1007/s11032-026-01702-4","url":null,"abstract":"<p><p>The brown planthopper (BPH, <i>Nilaparvata lugens</i>) and rice blast (<i>Magnaporthe oryzae</i>) are major constraints on rice production, causing extensive yield losses worldwide. Pyramiding multiple resistance genes is a key strategy for achieving durable and broad-spectrum protection against these pests and pathogens. We pyramided 13 resistance genes/QTLs (<i>Bph10</i>, <i>Bph14</i>, <i>Bph15</i>, <i>Bph17</i>, <i>Pi2</i>, <i>Bph20</i>, <i>Bph21</i>, <i>Bph6</i>, <i>QBph3</i>, <i>QBph4</i>, <i>Bph18</i>, <i>Bph9</i>, and <i>Bph24</i>) in the 9311 backgrounds through pairwise crossing, generating 30 pyramided lines, and true hybrids were identified by marker-assisted selection (MAS). Seedling-stage BPH resistance of the pyramided families was evaluated using the Standard Seedbox Screening Test (SSST), whereas leaf blast resistance of the selected lines was assessed by field evaluation of leaf blast. Most pyramided lines exhibited stronger resistance than their corresponding single-gene parental lines, and some also showed improved agronomic traits. These lines provide valuable breeding material for developing \"Green Super Rice\" with combined BPH and blast resistance and high, stable yield.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11032-026-01702-4.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"46 8","pages":"79"},"PeriodicalIF":3.6,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13447622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148689484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}