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"Biofortification"

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"Biofortification"

Research Articles
Screening and Breeding for Biofortification of Rice with Protein and High Lysine Contents
Ji-Yun Lee, Ju-Won Kang, Su-Min Jo, Young-Ho Kwon, So-Myeong Lee, Sais-Beul Lee, Dong-Jin Shin, Dong-Soo Park, Jong-Hee Lee, Jong-Min Ko, Jun-Hyeon Cho
Plant Breed. Biotech. 2021;9(3):199-212.   Published online September 1, 2021
DOI: https://doi.org/10.9787/PBB.2021.9.3.199

A total of 134 domestic and foreign genetic resources were analyzed for their protein and amino acids contents in order to identify breeding lines with high lysine content to improve nutritional components of rice. The protein contents ranged between 6.7% and 14.8%, with an average of 8.7%. The Dharial mutant-derived lines had relatively high protein content with the highest amino acids content of 130.16 mg/g and the highest lysine content of 3.86 mg/g which is about 5 times higher than that of the parent. In the case of mutant-derived lines with high floury endosperm such as Goami2, Dodamssal, Milyang320 and LA1, the total amino acids content was as low as 72.61-82.0 mg/g; however, lysine content ranged high between 2.64-3.35 mg/g with lysine ratio to the total amino acids was 3.6%-4.1% which is higher than the average lysine content ratio of 3.0%. Furthermore, correlation analysis revealed a very strong positive correlation between the total amino acids and total protein contents. In contrast, lysine content showed no significant correlation neither with total amino acids nor with protein contents. The lysine content of Milyang320, which was grown in 5 regions across Korea was 0.33%, showing an increase of about 22% compared to that recorded in Nampyeong (0.27%). Therefore, these data suggest that lysine content of Milyang320 is controlled genetically and could be serve as a source in high lysine rice breeding program.

Citations

Citations to this article as recorded by  
  • Lysine Matters: Genetic and Biotechnological Innovations to Combat Protein Malnutrition
    Varinder Singh, Manjari Mishra, Sneh Lata Singla‐Pareek, Joy K. Roy, Ashwani Pareek
    Plant, Cell & Environment.2026; 49(3): 1509.     CrossRef
  • Assessing two decades of breeding for biofortified rice with zinc, iron or protein
    Gogineni S.V. Prasad, Chilukuri S. Rao, Kalambur Muralidharan, Ranganathan Sridhar, Ebrahim A. Siddiq
    Journal of Agriculture and Food Research.2025; 24: 102317.     CrossRef
  • Biofortification as a solution for addressing nutrient deficiencies and malnutrition
    Bindu Naik, Vijay Kumar, Sheikh Rizwanuddin, Sadhna Mishra, Vivek Kumar, Per Erik Joakim Saris, Naresh Khanduri, Akhilesh Kumar, Piyush Pandey, Arun Kumar Gupta, Javed Masood Khan, Sarvesh Rustagi
    Heliyon.2024; 10(9): e30595.     CrossRef
  • Analysis of volatile compounds of several rice varieties according to endosperm type using an electronic nose
    Chae-Min Han, Jong-Hee Shin, Sang-Kuk Kim, Jung-Gi Ryu
    Journal of Crop Science and Biotechnology.2023; 26(3): 359.     CrossRef
  • Rice Storage Proteins: Focus on Composition, Distribution, Genetic Improvement and Effects on Rice Quality
    Long Xinkang, Guan Chunmin, Wang Lin, Jia Liting, Fu Xiangjin, Lin Qinlu, Huang Zhengyu, Liu Chun
    Rice Science.2023; 30(3): 207.     CrossRef
  • Comparative Proteome-wide Characterization of Three Different Tissues of High-Protein Mutant and Wild Type Unravels Protein Accumulation Mechanisms in Rice Seeds
    Cheol Woo Min, Ravi Gupta, Ju-Young Jung, Randeep Rakwal, Ju-Won Kang, Jun-Hyeon Cho, Jong-Seong Jeon, Sun Tae Kim
    Journal of Agricultural and Food Chemistry.2023; 71(32): 12357.     CrossRef
  • GWAS to spot candidate genes associated with grain quality traits in diverse rice accessions of North East India
    Rahul K. Verma, S. K. Chetia, Vinay Sharma, Samindra Baishya, Himanshu Sharma, M. K. Modi
    Molecular Biology Reports.2022; 49(6): 5365.     CrossRef
  • Comparison of physicochemical properties of pollen substitute diet for honey bee (Apis mellifera)
    Hyun Jee Kim, Jinseok Hwang, Zakir Ullah, Bilal Mustafa, Hyung Wook Kwon
    Journal of Asia-Pacific Entomology.2022; 25(4): 101967.     CrossRef
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Genetic Analysis Reveals a Major Effect QTL Associated with High Grain Zinc Content in Rice (Oryza sativa L.)
Shaikh J. Mohiuddin, Ashraful Haque, Manjurul Haque, Tofazzal Islam, Partha S. Biswas
Plant Breed. Biotech. 2020;8(4):327-340.   Published online December 1, 2020
DOI: https://doi.org/10.9787/PBB.2020.8.4.327

Molecular mapping and application of quantitative trait loci (QTL) associated with a higher level of grain Zinc is a viable option to enhance zinc content in rice through breeding. An F2 population derived from a cross between a high yielding variety, BRRI dhan28, and a locally adapted Zn enriched cultivar, Kalobokri was used to map QTLs associated with higher levels of Zn in rice grain. The F2:3 progenies varied significantly (P < 0.0001) in Zinc contents with a mean value remarkably higher than those in the superior parent. Through marker by trait analysis using IciMapping, we detected a large-effect QTL, qGZn3 on chromosome 3 between RM5419 and RM1164 spanning 1.83 Mb interval at the 0.05 level of significance with a threshold LOD of 10.61. This QTL showed a 21.1% (R2 value) contribution to the total phenotypic variation for zinc content in the unpolished rice grains with 4.68 μg/g additive effect of Kalobokri alleles. We also detected 11 metal homeostasis related genes within the interval of qGZn3. In-silico analysis showed that four expressed sequence tags of one candidate gene (LOC_Os03g22810) encoding Cu/Zn superoxide dismutase, a metal-binding protein, are highly active in the endosperm as well as in the embryonic tissue of rice grain. Taken together, our results suggest that qGZn3 is a major QTL associated with high grain Zn content in the F2 progenies of rice. Our findings offer valuable genetic resources to facilitate breeding for high yielding and Zinc-enriched rice variety.

Citations

Citations to this article as recorded by  
  • Precision breeding strategy to enrich iron and zinc in rice
    Rajvir Kaur, Rupinder Kaur, Renu Khanna, Gurjeet Singh, Dinesh Kumar Saini, Amandeep, Kumari Neelam, Navjot Sidhu, Ranvir Singh Gill
    Cereal Research Communications.2026; 54(1): 657.     CrossRef
  • Genomic Insights into the Genetic Control of Iron and Zinc Content in Rice: A Meta-analysis of Key Hotspots
    Om Prakash Raigar, Gaurav Augustine, Rupinder Kaur, Nitika Sandhu
    Journal of Plant Growth Regulation.2025;[Epub]     CrossRef
  • Association analysis of grain zinc and iron content with agro-morphological traits in segregating population of rice
    Rahul Singh, Anand Kumar, Mankesh Kumar, Sweta Sinha, Sareeta Nahakpam, Sunil Kumar, Shashikant, Satyendra, SP Singh
    Oryza-An International Journal on Rice.2024; 61(4): 283.     CrossRef
  • Genomic prediction and QTL analysis for grain Zn content and yield in Aus-derived rice populations
    Tapas Kumer Hore, C. H. Balachiranjeevi, Mary Ann Inabangan-Asilo, C. A. Deepak, Alvin D. Palanog, Jose E. Hernandez, Glenn B. Gregorio, Teresita U. Dalisay, Maria Genaleen Q. Diaz, Roberto Fritsche Neto, Md. Abdul Kader, Partha Sarathi Biswas, B. P. Mall
    Journal of Plant Biochemistry and Biotechnology.2024; 33(2): 216.     CrossRef
  • QTL mapping reveals different set of candidate genes governing stable and location specific QTLs enhancing zinc and iron content in rice
    Sonali Vijay Habde, Shravan Kumar Singh, Dhirendra Kumar Singh, Arun Kumar Singh, Rameswar Prasad Sah, Mounika Korada, Amrutlal R. Khaire, Prasanta Kumar Majhi, Uma Maheshwar Singh, Vikas Kumar Singh, Arvind Kumar
    Euphytica.2024;[Epub]     CrossRef
  • Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map
    Mark Ian C. Calayugan, Tapas Kumer Hore, Alvin D. Palanog, Amery Amparado, Mary Ann Inabangan-Asilo, Gaurav Joshi, Balachiranjeevi Chintavaram, B. P. Mallikarjuna Swamy
    Scientific Reports.2024;[Epub]     CrossRef
  • Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents
    P. Senguttuvel, Padmavathi G, Jasmine C, Sanjeeva Rao D, Neeraja CN, Jaldhani V, Beulah P, Gobinath R, Aravind Kumar J, Sai Prasad SV, Subba Rao LV, Hariprasad AS, Sruthi K, Shivani D, Sundaram RM, Mahalingam Govindaraj
    Frontiers in Plant Science.2023;[Epub]     CrossRef
  • QTL Mapping of Mineral Element Contents in Rice Using Introgression Lines Derived from an Interspecific Cross
    Cheryl Adeva, Yeo-Tae Yun, Kyu-Chan Shim, Ngoc Ha Luong, Hyun-Sook Lee, Ju-Won Kang, Hyun-Jung Kim, Sang-Nag Ahn
    Agronomy.2022; 13(1): 76.     CrossRef
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QTL Analysis for Fe and Zn Concentrations in Rice Grains Using a Doubled Haploid Population Derived from a Cross Between Rice (Oryza sativa) Cultivar 93-11 and Milyang 352
So-Myeong Lee, Ju-Won Kang, Ji-Yoon Lee, Jeonghwan Seo, Dongjin Shin, Jun-Hyeon Cho, Sumin Jo, You-Chun Song, Dong-Soo Park, Jong-Min Ko, Hee-Jong Koh, Jong-Hee Lee
Plant Breed. Biotech. 2020;8(1):69-76.   Published online March 1, 2020
DOI: https://doi.org/10.9787/PBB.2020.8.1.69

Biofortification is a cost-effective method for increasing the availability of micronutrients. Rice breeding for high levels of micronutrients is one of the best approaches to solve the problem of malnutrition. In this study, we developed a doubled haploid (DH) population derived from a cross between the rice cultivars 93-11 and Milyang 352 and evaluated QTLs for grain micronutrients and grain shape. Two co-localized QTLs, qFe3-1 and qZn3-1, were identified in the interval between ah03002520 and cmb0336.5 on chromosome 3, which explained 17.6% and 10.5% of the phenotypic variation, respectively. Correlation analysis between agronomic and micronutrient traits showed positive correlations between grain Fe and Zn contents but a negative correlation between grain Fe content and length-to-width ratio. This indicated the possibility of simultaneously increasing both Fe and Zn content in rice grains for improving the micronutrient profile of rice. We selected some promising lines by recombinant selection using linked markers on chromosome 3. The co-localized QTLs qFe3-1 and qZn3-1 might be useful for the improvement of biofortified rice breeding by marker-assisted selection and gene pyramiding.

Citations

Citations to this article as recorded by  
  • Precision breeding strategy to enrich iron and zinc in rice
    Rajvir Kaur, Rupinder Kaur, Renu Khanna, Gurjeet Singh, Dinesh Kumar Saini, Amandeep, Kumari Neelam, Navjot Sidhu, Ranvir Singh Gill
    Cereal Research Communications.2026; 54(1): 657.     CrossRef
  • Genomic Insights into the Genetic Control of Iron and Zinc Content in Rice: A Meta-analysis of Key Hotspots
    Om Prakash Raigar, Gaurav Augustine, Rupinder Kaur, Nitika Sandhu
    Journal of Plant Growth Regulation.2025;[Epub]     CrossRef
  • Analysis of quantitative trait loci and candidate gene exploration associated with cold tolerance in rice (Oryza sativa L.) during the seedling stage
    Sumin Jo, Seong-Gyu Jang, Sais-Beul Lee, Ji-Yoon Lee, Jun-Hyeon Cho, Ju-Won Kang, Yeongho Kwon, So-Myeong Lee, Dong-Soo Park, Soon-Wook Kwon, Jong-Hee Lee
    Frontiers in Plant Science.2025;[Epub]     CrossRef
  • Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map
    Mark Ian C. Calayugan, Tapas Kumer Hore, Alvin D. Palanog, Amery Amparado, Mary Ann Inabangan-Asilo, Gaurav Joshi, Balachiranjeevi Chintavaram, B. P. Mallikarjuna Swamy
    Scientific Reports.2024;[Epub]     CrossRef
  • Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents
    P. Senguttuvel, Padmavathi G, Jasmine C, Sanjeeva Rao D, Neeraja CN, Jaldhani V, Beulah P, Gobinath R, Aravind Kumar J, Sai Prasad SV, Subba Rao LV, Hariprasad AS, Sruthi K, Shivani D, Sundaram RM, Mahalingam Govindaraj
    Frontiers in Plant Science.2023;[Epub]     CrossRef
  • Genome-wide association study (GWAS) with high-throughput SNP chip DNA markers identified novel genetic factors for mesocotyl elongation and seedling emergence in rice (Oryza sativa L.) using multiple GAPIT models
    Nkulu Rolly Kabange, Simon Alibu, Youngho Kwon, So-Myeong Lee, Ki-Won Oh, Jong-Hee Lee
    Frontiers in Genetics.2023;[Epub]     CrossRef
  • Genetic variability, G × E interaction and stability for iron and zinc content in sorghum grains in advanced breeding lines
    R. Madhusudhana, K. Hariprasanna, C. Aruna, Gowri M. Sajjanar, N.G. Hanamaratti, S. Sameera, Vilas A. Tonapi
    Journal of Cereal Science.2023; 110: 103653.     CrossRef
  • Improvement of Selection Efficiency of Haploid Maize Seeds Using Fluorescence Imaging
    Younguk Kim, Jeong Heon Han, Jaeyoung Kim, Yeongtae Kim, Nyunhee Kim, Chaewon Lee, Seoyeoun Lee, Song Lim Kim, Moon Jong Kim, Si Hwan Ryu, Hongro Lee, Hyeonso Ji, Kyung-Hwan Kim, Jeongho Baek
    Korean Journal of Breeding Science.2022; 54(4): 276.     CrossRef
  • QTL Analysis of Rice Grain Size Using Segregating Populations Derived from the Large Grain Line
    Ja-Hong Lee, Jeonghwan Seo, San Mar Lar, Seong-Gyu Jang, Hongjia Zhang, Ah-Rim Lee, Fang-Yuan Cao, Na-Eun Kim, Joohyun Lee, Soon-Wook Kwon
    Agriculture.2021; 11(6): 565.     CrossRef
  • Transcriptional Changes in the Developing Rice Seeds Under Salt Stress Suggest Targets for Manipulating Seed Quality
    Choonseok Lee, Chong-Tae Chung, Woo-Jong Hong, Yang-Seok Lee, Jong-Hee Lee, Hee-Jong Koh, Ki-Hong Jung
    Frontiers in Plant Science.2021;[Epub]     CrossRef
  • Iron Biofortification in Rice: An Update on Quantitative Trait Loci and Candidate Genes
    B. P. Mallikarjuna Swamy, Balram Marathi, Ana I. F. Ribeiro-Barros, Mark Ian C. Calayugan, Felipe Klein Ricachenevsky
    Frontiers in Plant Science.2021;[Epub]     CrossRef
  • Combined Linkage Mapping and Genome-Wide Association Study Identified QTLs Associated with Grain Shape and Weight in Rice (Oryza sativa L.)
    Ju-Won Kang, Nkulu Rolly Kabange, Zarchi Phyo, So-Yeon Park, So-Myeong Lee, Ji-Yun Lee, Dongjin Shin, Jun Hyeon Cho, Dong-Soo Park, Jong-Min Ko, Jong-Hee Lee
    Agronomy.2020; 10(10): 1532.     CrossRef
  • Identification of a Novel QTL for Chlorate Resistance in Rice (Oryza sativa L.)
    Nkulu Rolly Kabange, So-Yeon Park, Dongjin Shin, So-Myeong Lee, Su-Min Jo, Youngho Kwon, Jin-Kyung Cha, You-Chun Song, Jong-Min Ko, Jong-Hee Lee
    Agriculture.2020; 10(8): 360.     CrossRef
  • Genetic Manipulation for Improved Nutritional Quality in Rice
    Priyanka Das, Sanghamitra Adak, Arun Lahiri Majumder
    Frontiers in Genetics.2020;[Epub]     CrossRef
  • STUDY OF ALLELIC VARIATION AT GENOME WIDE SSR LOCI IN PARENTS OF MAPPING POPULATION FOR HIGH GRAIN ZINC IN RICE (Oryza sativa L.)
    Sonali Habde, S. K. Singh, Korada Mounika, Amrutlal Khaire, D. K. Singh, Prasanta Kumar Majhi
    Journal of Experimental Biology and Agricultural Sciences.2020; 8(5): 558.     CrossRef
  • QTL Analysis of Heading Date Using 93-11×Milyang352 Doubled Haploid Lines in Rice
    So-Myeong Lee, Ju-Won Kang, Jun-Hyeon Cho, Ji-Yoon Lee, Dongjin Shin, Young-Ho Kwon, Jin-Kyung Cha, Sais-Beul Lee, Jong-Min Ko, Jong-Hee Lee
    Korean Journal of Breeding Science.2020; 52(4): 332.     CrossRef
  • Genetic Analysis Reveals a Major Effect QTL Associated with High Grain Zinc Content in Rice (Oryza sativaL.)
    Shaikh J. Mohiuddin, Md. Ashraful Haque, Md. Manjurul Haque, Md. Tofazzal Islam, Partha S. Biswas
    Plant Breeding and Biotechnology.2020; 8(4): 327.     CrossRef
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  • 17 Crossref