Theoretical and Applied Genetics最新文献

{"title":"Improving hybrid breeding efficiency in winter oilseed rape under sparse multi-environment testing.","authors":"Lars Erik Thomsen, Matthias Frisch, Christian Flachenecker, Amine Abbadi, Tobias Kox, Cyriakus Kulle, Carola Zenke-Philippi","doi":"10.1007/s00122-026-05341-3","DOIUrl":"10.1007/s00122-026-05341-3","url":null,"abstract":"<p><strong>Key message: </strong>Balanced, relationship-based omission, multi-environment predictions, and pedigree-genomic matrices improve genomic predictions, highlighting breeder's ability to influence performance through strategic training set design and model choice. Genomic prediction is increasingly applied in plant breeding, yet its robustness under sparse testing in hybrid breeding programs of winter oilseed rape (Brassica napus L.) lacks evidence. We evaluated the effects of data omission strategies, prediction schemes and models on genomic prediction accuracy and selection consistency. Seven omission scenarios were assessed for three traits with contrasting genetic architectures, using the correlation between observed and predicted phenotypes and Cohen's κ as complementary metrics for genomic prediction accuracy and selection consistency. Both declined systematically with increased data omission, although both metrics only correlated moderately. Balanced omission across environments outperformed unbalanced strategies by stabilizing variance estimation and preserving heritability. Our relationship-informed omission strategy further improved prediction performance, yielding higher and more stable prediction accuracies. Models based on combined pedigree-genomic relationship matrices enabled the inclusion of non-genotyped parental lines and further improved prediction performance. Multi-environment predictions using GCA + SCA models were consistently superior to per-environment predictions and GCA-only models; however, responses were trait-specific. Overall, our results demonstrate that informed omission strategies and model choices substantially influence the performance of genomic prediction under data reduction. Relationship-based balanced omission represents a promising selection approach that balances prediction performance with resource efficiency.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13469503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148724375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"TaGAD2 is a potential downstream effector of Rht5 in controlling wheat plant height.","authors":"Xianglan Kong, Yuxin Lei, Aozhe Wang, Xuefen Cai, Li Zhe, Chunge Cui, Qiumei Lu, Zhangchen Zhao, Altyn Shayahkhmetova, Linzhou Huang, Liang Chen, Yin-Gang Hu","doi":"10.1007/s00122-026-05338-y","DOIUrl":"10.1007/s00122-026-05338-y","url":null,"abstract":"<p><p>Plant height is a key determinant of wheat plant architecture that affect lodging resistance and grain yield. The GA-responsive (GAR) dwarfing gene Rht5 was previously shown to decrease plant height without compromise of wheat seedling vigor and considered as a promising candidate gene for breeding wheat varieties in water-limited conditions. However, the mechanisms underlying Rht5-mediated dwarfism are unclear. In this study, we investigated the genetic effects of Rht5 on wheat growth and development using recombinant inbred lines (RILs) and found that Rht5 reduces plant height through inhibition of cell proliferation while it promotes cell elongation. The dual functions of Rht5 on cell growth during wheat stem elongation were associated with the alteration of the homeostasis of endogenous growth-promoting phytohormones cytokinins and gibberellins. Transcriptome analysis of Rht5 RILs and their parental lines identified TaGAD2 (glutamate decarboxylase), encoding a functional glutamate decarboxylase localized at the plasma membrane that catalyzes γ-aminobutyric acid (GABA) biosynthesis, as a potential downstream regulator of Rht5-mediated dwarfism. Functional assays demonstrated that overexpression of TaGAD2 could reduce plant height while TaGAD2 knockdown increased plant height and improved lodging resistance, indicating a negative role of TaGAD2 in controlling wheat plant height. We also conducted haplotype analysis of TaGAD2 in a natural wheat population and identified TaGAD2^H1 as a potential favorable allele for wheat dwarfing breeding without compromising grain number. Our study provides new insights into the molecular mechanism of the Rht5-mediated plant height regulatory pathway and valuable gene resource for the genetic improvement of wheat plant architecture.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148723803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of NIRS and GWAS identifies GhMYB86 as a potential regulator of cottonseed protein content with pleiotropic effects on fiber strength in upland cotton.","authors":"Yiwen Huang, Xi Huang, Longyu Huang, Shouyang Fu, Yuzhen Wu, Dayun Zhou, Jun Peng, Yajun Liang, Meng Kuang","doi":"10.1007/s00122-026-05327-1","DOIUrl":"10.1007/s00122-026-05327-1","url":null,"abstract":"<p><strong>Key messages: </strong>High-accuracy NIRS models and GWAS identified a novel QTL qPO-A07-1. GhMYB86 was validated to enhance seed protein content and fiber strength, and a functional KASP marker was developed. Cottonseed is rich in protein and oil; improving its nutritional quality is vital for global food security. In this study, near-infrared spectroscopy (NIRS) models were developed for predicting cottonseed protein and oil content using least absolute shrinkage and selection operator (LASSO) regression, achieving validation R² of 0.969 (P < 0.01) and 0.972 (P < 0.01), respectively. Using these models, 249 upland cotton (Gossypium hirsutum L) accessions were phenotyped across five environments and subjected to a genome-wide association study (GWAS) based on a 10-K liquid-phase single-nucleotide polymorphism (SNP) array, resulting in the identification of 24 significant loci (P < 1 × 10^-4). A novel stable quantitative trait locus (QTL), qPO-A07-1, was detected, within which GhMYB86 was prioritized as a candidate gene. This gene exhibited higher expression in high-protein-content varieties during ovule development. Heterologous overexpression in Arabidopsis thaliana increased seed protein content by 2.61-3.34%, whereas expression in Saccharomyces cerevisiae increased protein content by 25.81% and reduced triglyceride content by 30.72% in comparison with the control. These results demonstrate that GhMYB86 positively regulates protein content while negatively affecting oil content. A kompetitive allele-specific PCR (KASP) marker targeting a promoter A/T polymorphism revealed that the AA allele was associated with higher-protein content, lower-oil content, and increased fiber strength across both mapping and validation populations. Furthermore, the protein content- and fiber strength-favorable allele has undergone positive selection during breeding. This study provides phenotyping tools, reliable genetic resources and a molecular marker for cottonseed nutritional quality breeding, laying a foundation for the improvement in cottonseed protein content and fiber strength.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 9","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148697977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic dissection of a key dynamic growth period QTL for source-sink-related traits and its breeding application potential in wheat.","authors":"Meng Yuan, Hongke Ding, Yunkai Yue, Chuanliang Zhang, Yuze Wang, Dandan Zhang, Shipeng Li, Ruiqi Nie, Jia Liu, Yanchuan Huang, Jinyu Han, Sufu Deng, Shengjie Liu, Chunlian Li, Weijun Zheng, Daojie Sun, Qiang Yao, Shouyang Liu, Shengwei Ma, Zifeng Guo, Jie Liu, Qingdong Zeng, Zhensheng Kang, Rui Yu, Dejun Han, Jianhui Wu","doi":"10.1007/s00122-026-05333-3","DOIUrl":"10.1007/s00122-026-05333-3","url":null,"abstract":"<p><p>Sustaining wheat yield gains requires optimizing the spatiotemporal coordination of source (leaves), transport (stems), and sink (spikes) organs. However, the physiological mechanisms and underlying genetic networks orchestrating the dynamic development of these critical structures remain largely uncharacterized. Here, we leveraged high-resolution time-series phenotyping across 590 wheat accessions evaluated across three year-site environments (comprising two locations and two growing seasons) to dissect the genetic architecture of these biomass partitioning trajectories. To fully capture this spatiotemporal regulation, our analysis explicitly integrated both the temporal tracking across five floret developmental stages (Z39-Z65) and the spatial partitioning among these organ-specific dynamic systems. We identified 36 multi-stage stable dynamic quantitative trait loci (QTL) regulating five source-sink-related traits. By constructing genetic association and epistatic interaction networks, we prioritized two pivotal dynamic QTL, namely Qa.nw-7B.848 and Qa.nw-1D.96. Multi-omics integration pinpointed TraesCS7B03G1340600 as a key candidate gene for Qa.nw-7B.848. Furthermore, haplotype analysis uncovered distinct selection footprints, demonstrating how specific allelic combinations have been differentially selected to optimize yield components across diverse geographical environments. Collectively, this study moves beyond static trait analysis, offering a dynamic genetic framework and specific epistatic targets to precision-design wheat architecture for enhanced productivity.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148680117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of oat chromosome rearrangements in advanced breeding lines and implications for genetic improvement.","authors":"Guilherme Oliveira, Wubishet Bekele, Françoise Dalprá Dariva, Sumandeep Bazzer, Jason Fiedler, Raja Sekhar Nandety, Jean-Luc Jannink, Melanie Caffe","doi":"10.1007/s00122-026-05332-4","DOIUrl":"10.1007/s00122-026-05332-4","url":null,"abstract":"<p><p>Large-scale chromosomal rearrangements or structural variants (SVs) have shaped the evolution of Avena species, driving domestication and adaptation in oats (Avena sativa L.). The legacy of these reorganizations, including translocations and inversions, remains evident, yet their frequency and impact on phenotypic and genotypic variability in oat breeding populations remain unclear. The objective of this study was to characterize chromosome rearrangements in 1230 oat breeding lines using genotyping-by-sequencing and to utilize this information in genomic loci discovery and prediction. Principal component analysis (PCA) based on single-nucleotide polymorphisms (SNPs) identified distinct clusters at the known locations of 1A/1C translocation, 3C inversion, 4C inversion, and 7D inversion. The distribution of the clusters of the four rearrangements in the genome-wide diversity space of our panel confirmed the role of SVs in population structure, with 1A/1C showing the most significant divergence. Suppression of recombination due to SVs was shown by higher linkage disequilibrium (LD) observed in all samples compared to lines within individual SV clusters. Genome-wide association studies (GWAS) identified markers for grain yield and agronomic traits, with some differences among cluster-based populations. Genomic prediction accuracies improved when cross-validation was performed within SV clusters rather than across the entire dataset. However, using SV clusters as covariates did not improve GWAS and prediction accuracies. These results suggest that SVs cause population stratification, reduce recombination rates, hinder gene discovery, and affect genomic prediction accuracy. Characterizing oat germplasm for SVs can improve breeding decisions, from optimizing parental selection to enhancing genomic predictions, accelerating genetic gains for key traits.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13447552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148685905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Discovery and mapping of a new gene in wheat for race-specific adult plant resistance to Puccinia striiformis f. sp. tritici.","authors":"R F Park, M Chhetri, K S Sandhu, L Ziems, D Singh","doi":"10.1007/s00122-026-05311-9","DOIUrl":"10.1007/s00122-026-05311-9","url":null,"abstract":"<p><p>Key message A non-durable adult plant stripe rust resistance gene in wheat was mapped to the distal region of chromosome 2DS and designated Yr88. Wheat stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most damaging fungal pathogens of wheat globally. Efforts to breed improved wheat cultivars have placed high priority on incorporating resistance to Pst. The resistances used are expressed at either all growth stages (all stage resistance; ASR) or at post-seedling growth stages (aka adult plant resistance; APR). Although APR has a reputation for being more durable than ASR examples have been documented of virulence for this type of resistance in the UK, Europe and in North America. Incursions of two genetically and pathogenically distinct pathotypes of Pst into Australia in 2017 and 2018 changed adult plant field stripe rust responses of many wheat cultivars grown in eastern Australia at that time. In some cases, changes in response could not be accounted for based on virulence on ASR genes, suggesting that the protective value of APR may have changed. This study reports the discovery of a new gene conferring race-specific APR to Pst pathotype 198 E16 A- J+ T+ 17+, a member of the internationally accepted multi-locus genotype (MLG) PstS13. The gene was mapped to the distal region of chromosome 2DS and designated Yr88. Evidence is provided for the presence of Yr88 in near isogenic genes carrying selected ASR and APR Yr genes, four Australian wheat cultivars (LRPB Hellfire, Sherriff CL Plus, Vixen, Wyalkatchem) plus the Mexican green revolution wheat cultivar Lerma Rojo 64 and the Pakistani wheat cultivar Moomal 2000.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148680059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Identifying marker-trait associations for wheat stem sawfly resistance.","authors":"Mik Hammers, Zachary J Winn, Brian Rice, Punya Nachappa, Katherine Frels, Geoff Morris, Richard Esten Mason","doi":"10.1007/s00122-026-05317-3","DOIUrl":"10.1007/s00122-026-05317-3","url":null,"abstract":"<p><strong>Key message: </strong>Two novel WSS resistance loci were identified on chromosomes 2B and 5A. Characterization of WSS resistance loci will improve breeders' ability to select to reduce yield loss due to WSS. Wheat stem sawfly (WSS) is a native grass feeding pest of winter wheat (Triticum aestivum L) which is difficult to control since most of its life cycle occurs within the stem of wheat plants. The only well-characterized genetic resistance to WSS is the solid stem locus (Sst1) on chromosome 3B, which exhibits environmental variability. It is critical to identify novel forms of genetic resistance outside of Sst1 to improve the overall resistance of wheat to WSS. In this study, genome-wide association studies (GWAS) were performed on lines in the Colorado State University wheat breeding program grown between 2014 and 2025 field seasons for three traits of interest: heading date (HD), WSS damage in the form of stem cutting (CUT), and stem solidity (SOLID). Significant marker trait associations (MTA) were identified on chromosomes 2B, 2D, 3A, 3B, 5A, and 5D for CUT and 2A, 3B, 4B, and 6A for SOLID. Significant MTA from these GWAS were used to identify beneficial allelic combinations (AC) for WSS resistance. The stem cutting ACs which had the lowest damage estimates were those in which lines possessed the resistant haplotype at every locus assessed (CUT = 2.35, error = 0.21, N = 56). Lines that had all resistant alleles in the stem solidity ACs showed the same superior estimate (SOLID = 14.7, error = 0.78, N = 22). The positive effects of the identified small-effect MTA on CUT and SOLID indicated the importance of including these loci when breeding for WSS resistance.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148680035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Prioritization of deleterious mutations informs genomic prediction and increases the rate of gain in common bean (Phaseolus vulgaris L.), a simulation study.","authors":"H Cordoba-Novoa, V Hoyos-Villegas","doi":"10.1007/s00122-026-05329-z","DOIUrl":"10.1007/s00122-026-05329-z","url":null,"abstract":"<p><strong>Key message: </strong>Predicted deleterious mutations (SNPs) have different distributions of effects compared to random SNPs based on population composition. Variant prioritization of markers based on deleterious scores can improve the prediction of yield. Favoring mating schemes between parents with fewer highly deleterious mutations can increase the rate of genetic gain. The study of mutations is fundamental to understanding evolution, domestication, and genetics. Characterizing mutations has potential to accelerate breeding programs through selection and purging deleterious mutations (DelMut). We investigated how predicting DelMut in breeding populations informs genomic prediction (GP) increasing the rate of genetic gain. DelMut were annotated in three independent common bean populations using a previously developed random forest (RF) model for common bean incorporating phylogenetic and protein information. Deleterious scores from the RF model were around 0.25, with the top 1% (highly DelMut) of variants scoring between 0.78 and 0.82 among populations. All populations showed variation in the number of highly DelMut per line (max. 13-197) and in genetic load. We assessed the impact of incorporating a priori information on DelMut for variant prioritization and weighting in GP models for yield and flowering time. Stochastic simulations were conducted to evaluate how designing mating schemes based on variable numbers of DelMut per parent can affect genetic gain. Variants with higher predicted scores had significantly different effect distributions compared to random or lower-scored markers. Simulated breeding cycles showed that selecting parents with fewer highly DelMut consistently increases the rate of genetic gain, and depending on the population, can be superior to phenotypic selection. These results highlight the potential of DelMut information for variant prioritization and the optimization of common bean breeding programs. The approaches we developed can be applied to other species to improve the efficacy of crop improvement.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13433502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148664579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"From QTL to candidate genes: a data-driven approach to unravel the genetic architecture of yellow rust resistance in central European wheat.","authors":"Jiaojiao Wang, Renate H Schmidt, Guoliang Li, Albrecht Serfling, Jochen C Reif, Yong Jiang","doi":"10.1007/s00122-026-05312-8","DOIUrl":"10.1007/s00122-026-05312-8","url":null,"abstract":"<p><p>Key message A data mining strategy capitalizing on high-resolution SNP information, sequence variant annotation and QTL information from three populations facilitated an efficient nomination of candidate genes for YR resistance, supported by Yr27 and functional annotations.Abstract Genome-wide association studies (GWAS) have become routine in many crops, but the prioritization of candidate genes remains challenging. Here, we developed a new approach to identify environment-specific quantitative trait loci (QTL) using GWAS and analyzed 5,840 wheat genotypes distributed over three experimental populations, including 5,243 single-cross hybrids and 597 elite lines. Resequencing the parental genotypes identified over 640,000 single-nucleotide polymorphisms (SNPs) after filtering. The hybrid panels were tested in 19 environments for susceptibility to Puccinia striiformis f. sp. tritici (Pst), a pathogen responsible for severe yellow rust (YR) epidemics especially after 2012. QTL patterns in diverse environments showed substantial differences, reflecting spatial and temporal dynamics. Combining high-resolution SNP information, sequence variant annotation and QTL information from different populations obtained via a novel GWAS approach enabled the efficient nomination of candidate genes for YR resistance loci of particular relevance for Central European wheat. The power of the developed strategy for mining data from different experimental populations was demonstrated as the validated resistance gene Yr27 was identified as sole candidate gene for one QTL region.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13423923/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148631459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Hyperspectral phenotyping and GWAS identify novel QTLs for soybean photosynthetic rate.","authors":"Li Wang, Ning Fu, Jinyu Zhang, Ao Shen, Yuanmeng Yu, Yanhong Wang, Xiaoli Guan, Dan Zhang, Fang Huang, Xiaoyong Yang, Deyue Yu, Zhongwen Huang, Yuming Yang","doi":"10.1007/s00122-026-05325-3","DOIUrl":"10.1007/s00122-026-05325-3","url":null,"abstract":"<p><p>Enhancing photosynthesis is an important approach to improve crop yields. Photosynthesis, as a key factor determining crop yield, is an important approach to increasing crop production and addressing global food security issues. Improving its efficiency is crucial in this regard. However, traditional photosynthetic phenotyping has long been a bottleneck in crop breeding due to time-consuming data collection. In this study, we simultaneously measured the spectral reflectance and the net photosynthetic rate (Pn) of soybean leaves to develop a high-precision model for estimating Pn based on hyperspectral data. By applying this model, we evaluated Pn in 219 soybean materials. A multi-environment genome-wide association study (GWAS) based on multi-environmental prediction Pn was carried out using the 3VmrMLM method, and 24 significant quantitative trait loci (QTLs) and four suggestive QTLs were identified. Among them, 24 QTLs overlapped with multiple previously reported QTL related to photosynthesis, chlorophyll content, quality, etc., or with genes related to key agronomic traits such as yield. Additionally, four new QTLs were discovered, and four candidate genes potentially associated with Pn were identified. Further, haplotype analysis identified their optimal haplotypes. This study presents a robust and nondestructive hyperspectral model for estimating the photosynthetic rate in soybeans, which is successfully applied to genetic analysis, yielding stable and biologically meaningful results. The approach offers an effective means to explore the genetic basis of photosynthesis and provides a solid theoretical foundation for large-scale, monitoring of soybean photosynthetic physiology.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"139 8","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148607575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}