Theoretical and Applied Genetics最新文献

{"title":"Deciphering the regulatory network of carbon isotope discrimination in bread wheat through genome-wide association studies and genomic prediction.","authors":"Qingfeng Dong, Shan Lu, Hao Ren, Dezheng Liu, Shen-Ao Gao, Xuefen Cai, Shanshan Zhang, Muhammad Ateeq, Liang Chen, Yin-Gang Hu","doi":"10.1007/s00122-025-04980-2","DOIUrl":"10.1007/s00122-025-04980-2","url":null,"abstract":"<p><strong>Key message: </strong>A total of 125 QTL regions and 33 candidate genes associated with carbon isotope discrimination (CID) were identified in wheat, and genomic prediction (GP) achieved high accuracy (Pearson correlation coefficient, PCC = 0.665), providing valuable tools for reeding drought-resilient varieties. Carbon isotope discrimination (CID) is a critical physiological trait that serves as an indicator of water use efficiency (WUE) and drought tolerance in wheat. In this study, the genetic basis of CID was analyzed through genome-wide association studies (GWAS) and genomic prediction (GP) using a diverse panel of 238 wheat varieties. High-density genotyping identified 125 significant quantitative trait loci (QTL) regions and 33 candidate genes, primarily involved in stomatal regulation, drought tolerance, chloroplast development, chlorophyll metabolism, leaf development, and light signaling pathways. Bayesian ridge regression was used to predict CID under normal water (CID_NW), water-limited (CID_WL), rain-fed conditions (CID_RF), and a combined environment (CID_BLUE). The model showed stable performance across environments, with the highest accuracy (Pearson correlation coefficient, PCC = 0.665 for CID_RF) achieved using a genotype matrix containing the SNP with the lowest p-value from each QTL. These findings provide novel insights into the genetic architecture of CID and its potential role in enhancing drought tolerance in wheat. The identified QTL, candidate genes, and predictive models offer a strong foundation for marker-assisted selection (MAS) and genome-wide selection (GS) in wheat breeding programs. These results contribute to the development of drought-resilient wheat varieties, addressing key challenges in global wheat production and food security.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"212"},"PeriodicalIF":4.2,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144837790","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":"Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome-environment association studies.","authors":"Che-Wei Chang, Karl Schmid","doi":"10.1007/s00122-025-05003-w","DOIUrl":"10.1007/s00122-025-05003-w","url":null,"abstract":"<p><p>Genome-environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limited by missing geographic origin data. To address this limitation, we explored the use of neural networks to predict the geographic origins of barley accessions and integrate imputed environmental data into GEA. Neural networks demonstrated high accuracy in cross-validation but occasionally produced ecologically implausible predictions as models solely considered geographical proximity. For example, some predicted origins were located within non-arable regions, such as the Mediterranean Sea. Using barley flowering time genes as benchmarks, GEA integrating imputed environmental data ( <math><mrow><mi>N</mi> <mo>=</mo> <mn>11</mn> <mo>,</mo> <mn>032</mn></mrow> </math> ) displayed partially concordant yet complementary detection of genomic regions near flowering time genes compared to regular GEA ( <math><mrow><mi>N</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>626</mn></mrow> </math> ), highlighting the potential of GEA with imputed data to complement regular GEA in uncovering novel adaptive loci. Also, contrary to our initial hypothesis anticipating a significant improvement in GEA performance by increasing sample size, our simulations yield unexpected insights. Our study suggests potential limitations in the sensitivity of GEA approaches to the considerable expansion in sample size achieved through predicting missing geographical data. Overall, our study provides insights into leveraging incomplete geographical origin data by integrating deep learning with GEA. Our findings indicate the need for further development of GEA approaches to optimize the use of imputed environmental data, such as incorporating regional GEA patterns instead of solely focusing on global associations between allele frequencies and environmental gradients across large-scale landscapes.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"211"},"PeriodicalIF":4.2,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12343745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822602","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":"CRISPR/Cas system-mediated transgene-free or DNA-free genome editing in plants.","authors":"Rongxiao Cai, Nan Chai, Jiekun Zhang, Jiantao Tan, Yao-Guang Liu, Qinlong Zhu, Dongchang Zeng","doi":"10.1007/s00122-025-04990-0","DOIUrl":"https://doi.org/10.1007/s00122-025-04990-0","url":null,"abstract":"<p><p>CRISPR/Cas-based genome-editing technology serves as a powerful and versatile tool for genome modification. It has been broadly utilized in crop breeding to enhance traits such as yield, various quality attributes, and biotic and abiotic stress tolerance. Because of public safety concerns over genetically modified organisms (GMOs), many countries have established stringent regulatory policies for genetically modified plants, dramatically limiting the application of related products. However, genome editing in stably transformed plants can result in transgene-free progeny through self-pollination or hybridization or yield DNA-free gene-edited plants via transient transformation. These edited plants materially differ from GMOs and are referred to as genome-edited organisms (GEOs). GEOs have the potential to alleviate regulatory burdens and aid in commercialization. Various methods have been developed to expedite the creation of transgene-free or DNA-free GEOs. This review summarizes the various strategies for creating these types of GEOs based on the CRISPR/Cas systems. It also covers the advantages and drawbacks of these strategies. Additionally, we examine off-target effects and mitigation strategies for plant genome editing and outline regulatory policies for gene-edited crops in selected countries and regions. We hope this review offers valuable references for the advancement of transgene-free and DNA-free GEOs.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"210"},"PeriodicalIF":4.2,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144822601","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":"Integrated transcriptome and BSA-seq analysis identifies a novel QTL for Meloidogyne graminicola resistance in rice HuaHang31.","authors":"Zhuhong Yang, Qingyan Xiao, Yao Wang, Yingjun Zhang, Shan Ye, Pingyong Sun, Wuhan Zhang, Huafeng Deng, Shiming Liu, Zhong Ding","doi":"10.1007/s00122-025-04999-5","DOIUrl":"https://doi.org/10.1007/s00122-025-04999-5","url":null,"abstract":"<p><strong>Key message: </strong>A novel QTL on chromosome 11 with 7 candidate genes regulating nematode resistance was identified by RNA-seq-based transcriptome and BSA-seq combination analyses, revealing the possible interactions between nematodes and plants. The resistant rice germplasms against Meloidogyne graminicola, which is a plant-parasitic nematode posing a significant threat to rice production, are very limited. Here, we identified HuaHang31 (HH31), an indica rice variety, as a novel source of high resistance against to M. graminicola through large-scale screening of 297 rice accessions using PF-127 assays. Histopathological and histochemical analyses revealed that HH31 significantly reduced nematode penetration, delayed juvenile development, and triggered reactive oxygen species accumulation and hypersensitive response in root tip cells post-infection. RNA-seq-based transcriptome profiling of HH31 and susceptible IR64 roots at 3-, 7-, and 12-days post-inoculation (dpi) highlighted the up-regulation of phenylpropanoid, flavonoid, lignin biosynthesis, and phytohormone signaling pathways (jasmonic acid, salicylic acid, ethylene) in HH31, suggesting their pivotal roles in nematode resistance. Additionally, bulk segregant analysis of two F₂ populations derived from HH31 crosses with susceptible varieties mapped a novel quantitative trait locus (QTL) on chromosome 11 (4.7-8.2 Mb). Within this region, seven nonsynonymous nucleotide-binding site-leucine-rich repeat genes exhibited root-specific expression and responsiveness to nematode infection, implicating their roles in resistance. Importantly, this QTL represents a distinct genomic region compared to previously reported resistance loci, highlighting its novelty. This study provides a new understanding of the genetic basis of nematode resistance and a valuable source for the development of nematode-resistant rice varieties, offering a sustainable strategy to mitigate yield losses caused by this pervasive pathogen.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"208"},"PeriodicalIF":4.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144817549","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":"Insight into the rutin biosynthesis in the unique flavonol synthesis pathway of Tartary buckwheat based on the enzymatic functions of FLSs.","authors":"Chenglei Li, Jiayi Sun, Guanlan Shi, Xuerong Zhao, Jun Gu, Jiaqi Shi, Qihan Ma, Daoping Zeng, Tao Wang, Zizhong Tang, Tongliang Bu, Hui Chen, Huala Wu, Qi Wu, Haixia Zhao, An'hu Wang","doi":"10.1007/s00122-025-04997-7","DOIUrl":"10.1007/s00122-025-04997-7","url":null,"abstract":"<p><strong>Key message: </strong>The homologous genes of FtFLS1-3 are crucial for rutin synthesis in Tartary buckwheat, with FtFLS1 playing a dominant role. The flavonol biosynthesis branch generates the main flavonoids in Tartary buckwheat (TB), with rutin serving as a representative flavonol compound. Flavonol synthase (FLS) is a vital enzyme involved in this metabolic pathway. Out of the five known FLS genes in the TB genome, FtFLS1 is the only gene identified, while information about the remaining four genes is limited. In this study, we cloned the five FtFLS genes from TB and performed molecular identification. The results showed that FtFLS1-3 exhibit high homology and similar molecular characteristics, categorizing them as FLS-like enzymes, while FtFLS4 and FtFLS5 show a certain degree of similarity to other 2-oxoglutarate-dependent dioxygenases. Further investigation revealed a significant correlation between expression of FtFLS1 and the rutin content during the flowering stage of TB (p < 0.05). The promoter sequences of FtFLS1-3 (P_FtFLS1-3) displayed distinctive cis-elements, transcriptional activities, and expression patterns, exhibiting different sensitivities to cold, UV-B, and drought stresses. The overexpression of FtFLS1-3 in Arabidopsis led to a significant elevation in total flavonoid and rutin levels, providing evidence for the FLS activity of FtFLS1-3 in plants. The enzymatic analysis showed that the recombinant FtFLS1-3 were capable of catalyzing the formation of their respective products from dihydroflavanols. FtFLS1 exhibited a superior specific activity, V_max and affinity for dihydroquercetin in terms of enzyme catalytic characteristics compared to FtFLS2 and FtFLS3. In summary, our study establishes the FLS activity of FtFLS1-3 and suggests that the metabolic flow of the flavonol biosynthesis branch in TB involves the conversion from dihydrokaempferol to dihydroquercetin and subsequently to quercetin, ultimately glycosylated to rutin. In this process, FtFLS1 plays a predominant role.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"209"},"PeriodicalIF":4.2,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144817548","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":"McATL43 encoding a RING-H2 finger E3 ubiquitin ligase is responsible for Shark teeth (St) fruit wart in bitter gourd (Momordica charantia L.).","authors":"Feifan Chen, Yuehong Ding, Yiwei Wen, Xuzhen Li, Silin Wu, Xuanyu Chen, Shihan Zeng, Xiaobin Zhang, Jiayu Liu, Libo Tian, Sang Shang","doi":"10.1007/s00122-025-04995-9","DOIUrl":"https://doi.org/10.1007/s00122-025-04995-9","url":null,"abstract":"<p><strong>Key message: </strong>Fine mapping and cloning identified a 2-bp deletion within the McATL43 gene, which encodes a RING-H2 finger E3 ubiquitin ligase, resulting in a loss-of-function mutation and smooth fruit wart phenotype in bitter gourd. Fruit wart morphology, defined by the size and arrangement of ridges and tubercles, significantly affects the commercial value of bitter gourd (Momordica charantia L.). Through QTL mapping using accessions that differ in fruit wart feature, we previously identified two major loci, fwf4.1 and fwf6.1, which together explain most of the phenotypic variation. Here, we show that fwf6.1 dominantly controls a tooth-shaped wart pattern, and therefore is named Shark teeth (St). Using a segregating BC₁F₂ population, we narrowed the St locus to a 19.23-kb interval containing six annotated genes. Among them, McATL43, encoding a RING-H2 finger E3 ubiquitin ligase, emerged as the best candidate. A 2-bp deletion in the single exon of the smooth-wart allele causes a frameshift and premature stop codon, likely disrupting the C-terminal substrate recognition domain. A diagnostic marker based on this deletion accurately distinguishes St and smooth-wart (wild-type, WT) alleles across 40 diverse accessions, indicating its potential use for marker-assisted selection. Subcellular localization showed that McATL43 is present in both the plasma membrane and cytosol. Phylogenic analysis also revealed that its homologs in cucurbits contain a cucurbit-specific signal peptide. Transcriptome profiling of homozygous BC₁F₃ plants indicated that McATL43-associated networks are involved in stimulus responses, auxin signaling, and transcriptional regulation. These findings provide a molecular basis for the genetic control of fruit wart morphology in bitter gourd and offer a valuable tool for breeding programs targeting improved fruit appearance.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"206"},"PeriodicalIF":4.2,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804910","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":"Dissecting the genetic and phenotypic basis of salinity tolerance in mungbean: insights from multi-stage phenotyping, GWAS and genomic prediction.","authors":"Md Shahin Iqbal, Candy M Taylor, Lukasz Kotula, Al Imran Malik, William Erskine","doi":"10.1007/s00122-025-04983-z","DOIUrl":"10.1007/s00122-025-04983-z","url":null,"abstract":"<p><strong>Key message: </strong>Mungbean germplasm collection showed diverse responses to salinity stress at vegetative and reproductive stages. GWAS identified stage-specific genetic associations and candidate genes in the first genetic study of salinity tolerance in mungbean across these stages. Mungbean is an important grain legume widely grown in rice-based farming systems of South and Southeast Asia. Salinity stress severely limits mungbean growth and yield, with cultivars differing widely in susceptibility. This study evaluated phenotypic responses and genetic diversity for salinity tolerance in a mungbean mini-core germplasm collection at early vegetative, late vegetative and reproductive stages, grown in soil-filled pots exposed to control (non-saline) and 75 mM NaCl treatments in a temperature-controlled glasshouse. Salinity stress significantly reduced growth, seed yield and related traits, highlighting distinct phenotypic and genotypic responses across growth stages. Genome-wide association studies and genomic prediction (GP) were performed using two SNP datasets: 5991 DArTseq SNPs and 198,474 Illumina whole-genome resequencing (WGRS) SNPs. A range of 18-22 significant genetic associations were identified in the three growth stages, but none were common across these stages. Both SNP datasets showed distinct genomic regions associated with salinity tolerance traits. GP showed potential to predict salinity tolerance-associated traits. Despite their lower genome-wide density, DArTseq SNPs performed similarly to high-density WGRS SNPs in association analyses and GP accuracy, highlighting their potential as a cost-effective genotyping system for efficient and practical commercial breeding applications. Evaluating the effects of significant SNPs revealed seven functional SNPs linked with seven candidate genes encoding callose synthase, ethylene receptor, dynamin-related protein, cytochrome P450, bHLH-type transcription factor and Kinesin-10-type motor protein. The findings demonstrate need for stage-specific breeding approaches and highlight novel genetic resources (including markers and germplasm) for enhancing salinity tolerance in mungbean.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"207"},"PeriodicalIF":4.2,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12335406/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144812435","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":"Integration of crop modeling and sensing into molecular breeding for nutritional quality and stress tolerance.","authors":"Jonathan Berlingeri, Abelina Fuentes, Earl Ranario, Heesup Yun, Ellen Y Rim, Oscar Garrett, Alexander Howard, Mary-Francis LaPorte, Sassoum Lo, Duke Pauli, Jenna Hershberger, Mason Earles, Allen Van Deynze, Edward Charles Brummer, Richard Michelmore, Christopher Y S Wong, Troy S Magney, Pamela C Ronald, Daniel E Runcie, Brian N Bailey, Christine H Diepenbrock","doi":"10.1007/s00122-025-04984-y","DOIUrl":"10.1007/s00122-025-04984-y","url":null,"abstract":"<p><p>Integrating innovative technologies into plant breeding is critical to bolster food and nutritional security under biotic and abiotic stresses in changing climates. While breeding efforts have focused primarily on yield and stress tolerance, emerging evidence highlights the need to also prioritize nutritional quality. Advanced molecular breeding approaches have enhanced our ability to develop improved crop varieties and could be substantially informed by the routine integration of crop modeling and remote sensing technologies. This review article discusses the potential of combining crop modeling and sensing with molecular breeding to address the dual challenge of nutritional quality and stress tolerance. We provide overviews of stress response strategies, challenges in breeding for quality traits, and the use of environmental data in genomic prediction. We also describe the status of crop modeling and sensing technologies in grain legumes, rice, and leafy greens, alongside the status of -omics tools in these crops and the use of AI with directed evolution to identify novel resistance genes. We describe the pairwise and three-way integration of AI-enabled sensing and biophysically and empirically constrained crop modeling into breeding to enable prediction of phenotypic and breeding values and dissection of genotype-by-environment-by-management interactions with increasing fidelity, efficiency, and temporal/spatial resolution to inform selection decisions. This article highlights current initiatives and future trends that focus on leveraging these advancements to develop more climate-resilient and nutritionally dense crops, ultimately enhancing the effectiveness of molecular breeding.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"205"},"PeriodicalIF":4.2,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12334538/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144804909","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":"AdaptiveGS: an explainable genomic selection framework based on adaptive stacking ensemble machine learning.","authors":"Zhen Yang, Mei Song, Xianggeng Huang, Quanrui Rao, Shanghui Zhang, Zhongzheng Zhang, Chenyang Wang, Wenjia Li, Ran Qin, Chunhua Zhao, Yongzhen Wu, Han Sun, Guangchen Liu, Fa Cui","doi":"10.1007/s00122-025-04991-z","DOIUrl":"https://doi.org/10.1007/s00122-025-04991-z","url":null,"abstract":"<p><strong>Key message: </strong>We developed an adaptive and unified stacking genomic selection framework and designed a model interpretation strategy to identify the candidate significant SNPs of target traits. Genomic selection (GS) is an important technique in modern molecular breeding. As a powerful machine learning (ML) GS approach, stacking ensemble learning (SEL) combines multiple basic models (base learners, BLs) and effectively blends the strengths of different models to precisely depict the complex relationships between phenotypes and genotypes. However, in the key step of the SEL, there is currently a lack of an effective and unified framework for the selection of BLs. We developed adaptiveGS, an adaptive and explainable data-driven BLs selection strategy for the first time, to pre-screen the optimal BLs for stacking GS framework and improve the prediction accuracy. The adaptiveGS is performed based on the PR index, leveraging the Pearson correlation coefficient (PCC) and the normalized root mean square error (NRMSE), and the top 3 out of 7 (or self-setting) ML are tailored to be BLs via the PR index. We compared the adaptiveGS with 13 other GS algorithms based on a total of 21 traits (datasets) from 4 species. The results showed that adaptiveGS outperformed the 13 models on most of the 21 traits, with the average prediction accuracy (PCC) reaching 0.703, an average improvement of 14.4%, demonstrating superior predictive accuracy and robustness. Furthermore, the SHapley Additive exPlanations (SHAP) technique was utilized to interpret the adaptiveGS and identify significant SNPs for trait variations and potential interaction effects between SNPs. The adaptiveGS provides an operable and unified solution for stacking GS users to improve prediction accuracy in the breeding field. The adaptiveGS package is accessible at https://github.com/yangzhen0117/adaptiveGS .</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"204"},"PeriodicalIF":4.2,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795554","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":"Chlorophyll deficient 5 encodes a DNA helicase and is essential for chloroplast development in rice.","authors":"Weichi Liu, Xiaonan Han, Jiaxin Wei, Jie Yang, Yingchun Wan, Hongxia Yang, Yao Deng, Nan Wang, Ping Feng, Wenqiang Shen","doi":"10.1007/s00122-025-04994-w","DOIUrl":"https://doi.org/10.1007/s00122-025-04994-w","url":null,"abstract":"<p><strong>Key message: </strong>A novel gene CDE5 controlling leaf color was identified. Its causal gene LOC_Os06g45980 was verified by complementation transgenic, expression analysis, RNA sequencing, enzyme activity tests. Leaf color is a critical trait influencing plant biosynthesis, as it directly impacts photosynthesis and dry matter production. Despite intensive research, the molecular mechanisms of leaf color still remain to be elucidated. In the present study, we characterized a rice chlorophyll deficient 5 (cde5) mutant, which was defective in chloroplast development and exhibited albino leaves throughout the overall growth period. Map-based cloning revealed that CDE5 encodes a DNA helicase which has not been previously reported to be associated with albino leaf in plants. The cde5 mutant exhibited abnormal chloroplast structures and decreased chlorophyll contents. Further expression analyses showed that CDE5 expressed in variety of tissues, and in situ hybridization results showed CDE5 expressed in mesophyll cell. Subcellular localization analysis demonstrated that CDE5 was localized in the chloroplast and mitochondrion. RNA sequencing and RT-qPCR showed that several genes involved in chlorophyll synthesis, chloroplast development and photosynthesis were significantly altered due to loss of CDE5. Enzyme activity experiments further demonstrated that CDE5 exhibits ATPase activity, while the ATPase activity of the cde5 mutant protein is significantly reduced. Taken together, these findings suggest that CDE5 plays an important role in leaf color regulation, thus shedding new light on the function of DNA helicase in rice.</p>","PeriodicalId":22955,"journal":{"name":"Theoretical and Applied Genetics","volume":"138 9","pages":"203"},"PeriodicalIF":4.2,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144795555","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}