Quantitative trait locus (QTL) analysis is a powerful approach for identifying variants associated with the phenotypic variation of complex traits. However, selecting optimal methods and pre-processing steps require considerable time and effort. In this study, we demonstrated applicability and replicability of machine learning (ML) models in QTL analysis by evaluating their performance in comparison with conventional QTL analysis methods using 142 recombinant inbred lines derived from two japonica rice cultivars, Koshihikari and Baegilmi. Random forest and gradient boosting models showed the highest predictive accuracy, and consistently identified three QTLs associated with heading date: qDTH3, qDTH6, and qDTH7. Moreover, ML-based QTL analysis detected minor-effect qDTH10, where Koshihikari allele promoted heading date when combined with Koshihikari alleles of qDTH6 and qDTH7. These results demonstrate the applicability of ML models in QTL analysis on bi-parental mapping population in rice.

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• Machine Learning Method to Select Single Nucleotide Polymorphism Markers for Protein Content, Grain Filling Rate, Height, and Panicle Length in Korean Rice
  Jeong-Gu Kim, Minwoo Kim, Gyu-Hwang Park, Jinhyun Kim, Jinho Jung, Tae-Ho Lee
  Korean Journal of Breeding Science.2025; 57(4): 403.     CrossRef

Understanding the genetics underlying heading date and yield-related traits is essential in wheat breeding for maximizing productivity under different environments. Using doubled haploid lines derived from two Korean wheat cultivars, we identified seven stable quantitative trait loci (QTLs) for yield-related traits, i.e., days to heading date (QDhd.jbnu-3B, QDhd.jbnu-6B, and QDhd.jbnu-7D), culm length (QCl.jbnu-6A), thousand kernel weight (QTkw.jbnu-6A), kernels per spike (QKps.jbnu-3B) and test weight (QTw.jbnu-1A). Compared to the lines carrying the allele for late heading, those carrying the allele for early heading at QDhd.jbnu-3B, QDhd.jbnu-6B, and QDhd.jbnu-7D headed 3.1, 2.0, and 1.7 days earlier, respectively. Interestingly, when the alleles for early heading at the three QTLs were accumulated, heading date was accelerated by approximately one week, indicating that these QTLs provide useful genetic resources to fine-tune heading date. However, as the alleles for early heading at all three QTLs were associated with decreased kernels per spike, caution is required when deploying them to minimize the negative impacts on yield. Our study provides useful information for developing wheat cultivars with optimal heading date and enhanced productivity.

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• Variations in Major Agronomic Traits of Durum Wheat Germplasm Under Different Nitrogen Fertilization Levels
  Hosun Cheon, Sun-Hwa Kwak, Sieun Choi, Sukyeung Lee, Jinhee Park, Kyung-Min Kim, Chul Soo Park, Youngjun Mo
  Korean Journal of Breeding Science.2024; 56(3): 281.     CrossRef

Flowering time (heading date) of the rice plant is considered an important agronomic trait for environmental adaptation and grain yield. It is controlled by multiple genes and is regulated by different environmental factors, such as day length, temperature, soil moisture, etc. So far, approximately 125 genes regulating flowering process and floral organ identity or development directly or indirectly have been reported in rice. Among these genes, Heading date 3a (Hd3a), RICE FLOWERING LOCUS T1 (RFT1), Heading date 5 (Hd5), MORF-RELATED GENE702 (MRG702), Casein kinases, CKI and CK2α, Pseudo-Response Regulator 37 (PRR37), Hd gene family have been reported as the key genes regulating flowering time in rice; however, their functions are mostly inter-related. Hd3a and RFT1 that encode florigens, are known as the floral transition genes in rice. In rice, florigen immediately induces downstream genes in the shoot apical meristem (SAM) to start the transition from vegetative to reproductive phase. RFT1 gene regulates flowering time with pivotal action while Hd3a, regulates under long day conditions. The Hd5 gene regulates flowering time in variation of early heading for adaptation depending on environmental signals. MRG702, a reader protein, promotes flowering. Casein kinases, CKI and CK2α directly influence the function of the early heading regulator PRR37. Hd16/CKI hinders flowering time in the Ehd1-concerned pathway through phosphorylation of Ghd7 and PRR37. Natural variants of Hd1, PRR37, Ghd7, DTH8, Hd6, and Hd16 were found in the rice varieties that are cultivated presently in Asia and Europe, and their variants play significant roles in the down streaming of Ehd1 expression to delay flowering time in natural long day (LD) conditions.

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• Exogenous and Endogenous Signals: Critical Factors for Regulation of Flowering Time and Grain Yield in Rice
  E. Kariali, S. Panigrahi, P. K. Suna, P. K. Senapati, R. Das, P. Dwivedi
  Russian Journal of Plant Physiology.2025;[Epub]     CrossRef
• CRISPR-Cas technology based genome editing for modification of salinity stress tolerance responses in rice (Oryza sativa L.)
  Ibrahim Khan, Sikandar Khan, Yong Zhang, Jianping Zhou, Maryam Akhoundian, Sohail Ahmad Jan
  Molecular Biology Reports.2021; 48(4): 3605.     CrossRef

Functional stay-green (FSG) delays leaf yellowing, maintaining photosynthetic competence, whereas nonfunctional stay-green (NFSG) retains only leaf greenness without sustaining photosynthetic activity. Retention of chlorophylls and photosynthetic capacity is important for increasing crop yield. We determined the main-effect quantitative trait loci (QTLs) for FSG traits in the japonica rice SNU-SG1 and isolated candidate genes. To identify QTLs influencing FSG, we analyzed eight traits: (1) 1 day after heading-degree of chlorophyll content of flag leaf, (2) 1 day after heading-degree of chlorophyll content of second leaf, (3) 1 day after heading-degree of chlorophyll content of flag and second leaves, (4) 50 day after heading-degree of chlorophyll content of flag leaf, (5) 50 day after heading-degree of chlorophyll content of second leaf, (6) 50 day after heading-degree of chlorophyll content of flag and second leaves, (7) relative decline degree of chlorophyll content of flag and second leaves, and (8) flowering time. We carried out QTL analysis with F₇ RIL from a cross of japonica rice ‘SNU-SG1’ and indica rice ‘Milyang23 (M23)’. Using 131 molecular markers, we identified 18 QTLs for the eight traits with a threshold LOD value > 2.8. Sequence analysis identified 16 candidate genes for 10 main-effect QTLs. Of these, we have chosen seven strong candidate genes for the 10 main-effect QTLs. These genetic resources will be useful for breeding high-yielding rice cultivars.

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• Quantitative trait loci for stay‐greenness and agronomic traits provide new insights into chlorophyll homeostasis and nitrogen use in rice
  Ramakrishnappa Archana, Kunnummal Kurungara Vinod, Subbaiyan Gopala Krishnan, Elangovan Devi Chandra Vadhana, Prolay Kumar Bhowmick, Vikram Jeet Singh, Ranjith Kumar Ellur, Lekshmy Sathee, Pranab Kumar Mandal, Haritha Bollinedi, Shekharappa Nanda Kumar,
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• Integrated transcriptomics and miRNAomics provide insights into the complex multi-tiered regulatory networks associated with coleoptile senescence in rice
  Jyothish Madambikattil Sasi, Cheeni VijayaKumar, Bharti Kukreja, Roli Budhwar, Rohit Nandan Shukla, Manu Agarwal, Surekha Katiyar-Agarwal
  Frontiers in Plant Science.2022;[Epub]     CrossRef
• Genetic analysis of stay‐green, yield, and agronomic traits in spring wheat
  J. P. Cook, R. K. Acharya, J. M. Martin, N. K. Blake, I. J. Khan, H.‐Y. Heo, K. D. Kephart, J. Eckhoff, L. E. Talbert, J. D. Sherman
  Crop Science.2021; 61(1): 383.     CrossRef
• Unraveling candidate genomic regions responsible for delayed leaf senescence in rice
  Uma Maheshwar Singh, Pallavi Sinha, Shilpi Dixit, Ragavendran Abbai, Challa Venkateshwarlu, Annapurna Chitikineni, Vikas Kumar Singh, Rajeev K. Varshney, Arvind Kumar, Reyazul Rouf Mir
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• Photosynthetic Metabolism under Stressful Growth Conditions as a Bases for Crop Breeding and Yield Improvement
  Fermín Morales, María Ancín, Dorra Fakhet, Jon González-Torralba, Angie L. Gámez, Amaia Seminario, David Soba, Sinda Ben Mariem, Miguel Garriga, Iker Aranjuelo
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• QTL Mapping for Grain Yield, Flowering Time, and Stay‐Green Traits in Sorghum with Genotyping‐by‐Sequencing Markers
  Sivakumar Sukumaran, Xin Li, Xianran Li, Chengsong Zhu, Guihua Bai, Ramasamy Perumal, Mitchell R. Tuinstra, P.V. Vara Prasad, Sharon E. Mitchell, Tesfaye T. Tesso, Jianming Yu
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