QTL detection for grain yield and micro-nutrition contents in rice (Oryza sativa) using an interspecific backcross population derived from Dongxiang wild rice (Oryza rufipogon)
Liuying Duan A B # , Ting Wu B # , Xia Li B , Derun Huang C , Xiaobai Li D , Xixian Wen E * , Ping Chen B * , Jiankun Xie A * and Biaolin Hu
B *
+ Author Affiliations
- Author Affiliations
A College of Life Science, Jiangxi Normal University, Nanchang 330022, Jiangxi, China.
B Rice Research Institute, Jiangxi Academy of Agricultural Sciences/National Engineering Center for Rice (Nanchang), Nanchang 330200, China.
C State Key Laboratory of Rice Biology/Chinese National Center for Rice Improvement, China National Rice Research Institute, Hangzhou 310006, China.
D Zhejiang Academy of Agricultural Sciences, Hangzhou, China.
E Jiangxi Agricultural Technology Extension Center, Nanchang 330046, Jiangxi, China.
# These authors contributed equally to this paper
Handling Editor: Mohd. Kamran Khan
Crop & Pasture Science 73(11) 1253-1263 https://doi.org/10.1071/CP22039
Submitted: 1 February 2022 Accepted: 28 March 2022 Published: 24 May 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing
Abstract
Context: Enhancing grain yield and micro-nutrition contents in rice (Oryza sativa L.) through biofortification breeding is an efficient way to address micro-nutrient deficiencies in human.
Aims: QTL mapping for grain yield and micro-nutritional traits is prerequisite for developing new rice varieties.
Methods: QTLs for grain yield and micro-nutritional traits were identified using a backcross inbred lines (BIL) derived from an interspecific backcross of Xieqingzao B and Dongxiang wild rice (Oryza rufipogon Griff.).
Key results: A total of 16 and 29 QTLs were identified for grain Zn, Mn and Cu contents, including three for brown and milled rice, 10 for brown rice only, and three for milled rice only, and for grain related traits, respectively. Among grain micro-nutrient QTLs, three QTLs, qMn4, qMn6.2 and qZn6.2, showed genetic effects on both brown and milled rice.
Conclusion: Sixteen QTLs for grain related traits and eight QTLs for grain micro-nutrient content had O. rufipogon favourable alleles. A total 31 QTLs were clustered eight chromosomal regions. Importantly, two clusters, qZn4/qGW4 and qZn6.2/qMn6.2/qCu6.3/qGYP6.2, had the favourable wild alleles, suggesting that O. rufipogon alleles had synergistic effects on both yield component and micro-nutrient content.
Implications: These candidate QTLs could be useful for the improvement of grain yield and micro-nutrients through QTL pyramiding.
Keywords: backcross inbred lines, biofortification, brown rice, Dongxiang wild rice (Oryza rufipogon Griff.), grain yield and yield components, micro-nutritional contents, milled rice, QTLs.
References
Anuradha K, Agarwal S, Rao YV, Rao KV, Viraktamath BC, Sarla N (2012) Mapping QTLs and candidate genes for iron and zinc concentrations in unpolished rice of madhukar × Swarna RILs. Genes 508, 233–240.| Mapping QTLs and candidate genes for iron and zinc concentrations in unpolished rice of madhukar × Swarna RILs.Crossref | GoogleScholarGoogle Scholar |
Bashir K, Takahashi R, Akhtar S, Ishimaru Y, Nakanishi H, Nishizawa NK (2013) The knockdown of OsVIT2 and MIT affects iron localization in rice seed. Rice 6, 31
| The knockdown of OsVIT2 and MIT affects iron localization in rice seed.Crossref | GoogleScholarGoogle Scholar | 24280309PubMed |
Bashir K, Seki M, Nishizawa NK (2019) The transport of essential micronutrients in rice. Molecular Breeding 39, 168
| The transport of essential micronutrients in rice.Crossref | GoogleScholarGoogle Scholar |
Calayugan MIC, Formantes AK, Amparado A, Descalsota-Empleo GI, Nha CT, Inabangan-Asilo MA, Swe ZM, Hernandez JE, Borromeo TH, Lalusin AG, Mendioro MS, Diaz MGQ, Viña CBD, Reinke R, Swamy BPM (2020) Genetic analysis of agronomic traits and grain iron and zinc concentrations in a doubled haploid population of rice (Oryza sativa L.). Scientific Reports 10, 2283
| Genetic analysis of agronomic traits and grain iron and zinc concentrations in a doubled haploid population of rice (Oryza sativa L.).Crossref | GoogleScholarGoogle Scholar | 32042046PubMed |
Chan AN, Wang L-L, Zhu Y-J, Fan Y-Y, Zhuang J-Y, Zhang Z-H (2021) Identification through fine mapping and verification using CRISPR/Cas9-targeted mutagenesis for a minor QTL controlling grain weight in rice. Theoretical and Applied Genetics 134, 327–337.
| Identification through fine mapping and verification using CRISPR/Cas9-targeted mutagenesis for a minor QTL controlling grain weight in rice.Crossref | GoogleScholarGoogle Scholar | 33068118PubMed |
Cheng Z-Q, Huang X-Q, Zhang Y-Z, Qian J, Yang M-Z, Wu C-J, Liu J-F (2005) Diversity in the content of some nutritional components in husked seeds of three wild rice species and rice varieties in Yunnan province of China. Journal of Integrative Plant Biology 47, 1260–1270.
| Diversity in the content of some nutritional components in husked seeds of three wild rice species and rice varieties in Yunnan province of China.Crossref | GoogleScholarGoogle Scholar |
Descalsota-Empleo GI, Amparado A, Inabangan-Asilo MA, Tesoro F, Stangoulis J, Reinke R, Swamy BPM (2019) Genetic mapping of QTL for agronomic traits and grain mineral elements in rice. The Crop Journal 7, 560–572.
| Genetic mapping of QTL for agronomic traits and grain mineral elements in rice.Crossref | GoogleScholarGoogle Scholar |
Dixit S, Singh UM, Abbai R, Ram T, Singh VK, Paul A, Virk PS, Kumar A (2019) Identification of genomic region(s) responsible for high iron and zinc content in rice. Scientific Reports 9, 8136
| Identification of genomic region(s) responsible for high iron and zinc content in rice.Crossref | GoogleScholarGoogle Scholar | 31148549PubMed |
Du J, Zeng D, Wang B, Qian Q, Zheng S, Ling H-Q (2013) Environmental effects on mineral accumulation in rice grains and identification of ecological specific QTLs. Environmental Geochemistry and Health 35, 161–170.
| Environmental effects on mineral accumulation in rice grains and identification of ecological specific QTLs.Crossref | GoogleScholarGoogle Scholar | 22760687PubMed |
Garcia-Oliveira AL, Tan L, Fu Y, Sun C (2009) Genetic identification of quantitative trait loci for contents of mineral nutrients in rice grain. Journal of Integrative Plant Biology 51, 84–92.
| Genetic identification of quantitative trait loci for contents of mineral nutrients in rice grain.Crossref | GoogleScholarGoogle Scholar | 19166498PubMed |
Hu B-L, Huang D-R, Xiao Y-Q, Fan Y-Y, Chen D-Z, Zhuang J-Y (2016) Mapping QTLs for mineral element contents in brown and milled rice using an Oryza sativa × O. rufipogon backcross inbred line population. Cereal Research Communications 44, 57–68.
| Mapping QTLs for mineral element contents in brown and milled rice using an Oryza sativa × O. rufipogon backcross inbred line population.Crossref | GoogleScholarGoogle Scholar |
Hu B-l, Li X, Wu T, Huang D-r, Huang F-l, Yin J-h, Wu Y-s (2021) Identification and validation of QTLs for macronutrient contents in brown and milled rice using two backcross populations between Oryza sativa and O. rufipogon. BioMed Research International 2021, 5561734
| Identification and validation of QTLs for macronutrient contents in brown and milled rice using two backcross populations between Oryza sativa and O. rufipogon.Crossref | GoogleScholarGoogle Scholar | 34195268PubMed |
Huang DR, Chen J, Hou LJ, Fan YY, Zhuang JY (2008) Identification of QTLs for yield traits in the BC1F5 population of Xieqingzao B//Xieqingzao B/Dongxiang wild rice. Journal of Agricultural Biotechnology 16, 977–982.
Huang X-Y, Deng F, Yamaji N, Pinson SRM, Fujii-Kashino M, Danku J, Douglas A, Guerinot ML, Salt DE, Ma JF (2016) A heavy metal P-type ATPase OsHMA4 prevents copper accumulation in rice grain. Nature Communications 7, 12138
| A heavy metal P-type ATPase OsHMA4 prevents copper accumulation in rice grain.Crossref | GoogleScholarGoogle Scholar | 27387148PubMed |
Huang X-Y, Liu H, Zhu Y-F, Pinson SRM, Lin H-X, Guerinot ML, Zhao F-J, Salt DE (2019) Natural variation in a molybdate transporter controls grain molybdenum concentration in rice. New Phytologist 221, 1983–1997.
| Natural variation in a molybdate transporter controls grain molybdenum concentration in rice.Crossref | GoogleScholarGoogle Scholar | 30339276PubMed |
Ishikawa S, Abe T, Kuramata M, Yamaguchi M, Ando T, Yamamoto T, Yano M (2010) A major quantitative trait locus for increasing cadmium-specific concentration in rice grain is located on the short arm of chromosome 7. Journal of Experimental Botany 61, 923–934.
| A major quantitative trait locus for increasing cadmium-specific concentration in rice grain is located on the short arm of chromosome 7.Crossref | GoogleScholarGoogle Scholar | 20022924PubMed |
Ishikawa R, Iwata M, Taniko K, Monden G, Miyazaki N, Orn C, Tsujimura Y, Yoshida S, Ma JF, Ishii T (2017) Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice. PLoS ONE 12, e0187224
| Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice.Crossref | GoogleScholarGoogle Scholar | 29077764PubMed |
Jeong O-Y, Lee J-H, Jeong E-G, Chun A, Bombay M, Ancheta MB, Ahn SN (2020) Analysis of QTL responsible for grain iron and zinc content in doubled haploid lines of rice (Oryza sativa) derived from an intra-japonica cross. Plant Breeding 139, 344–355.
| Analysis of QTL responsible for grain iron and zinc content in doubled haploid lines of rice (Oryza sativa) derived from an intra-japonica cross.Crossref | GoogleScholarGoogle Scholar |
Jiang S, Shi C, Wu J (2009) Studies on mineral nutrition and safety of wild rice (Oryza L.). International Journal of Food Sciences and Nutrition 60, 139–147.
| Studies on mineral nutrition and safety of wild rice (Oryza L.).Crossref | GoogleScholarGoogle Scholar | 19462321PubMed |
Lander ES, Green P, Abrahamson J, Barlow A, Daley MJ, Lincoln SE, Newburg L (1987) MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1, 174–181.
| MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations.Crossref | GoogleScholarGoogle Scholar | 3692487PubMed |
Liu C, Chen G, Li Y, Peng Y, Zhang A, Hong K, Jiang H, Ruan B, Zhang B, Yang S, Gao Z, Qian Q (2017) Characterization of a major QTL for manganese accumulation in rice grain. Scientific Reports 7, 17704
| Characterization of a major QTL for manganese accumulation in rice grain.Crossref | GoogleScholarGoogle Scholar | 29255144PubMed |
Liu C, Ding S, Zhang A, Hong K, Jiang H, Yang S, Ruan B, Zhang B, Dong G, Guo L, Zeng D, Qian Q, Gao Z (2020) Development of nutritious rice with high zinc/selenium and low cadmium in grains through QTL pyramiding. Journal of Integrative Plant Biology 62, 349–359.
| Development of nutritious rice with high zinc/selenium and low cadmium in grains through QTL pyramiding.Crossref | GoogleScholarGoogle Scholar | 31957138PubMed |
Lukaski HC (2004) Vitamin and mineral status: effects on physical performance. Nutrition 20, 632–644.
| Vitamin and mineral status: effects on physical performance.Crossref | GoogleScholarGoogle Scholar | 15212745PubMed |
McCouch SR McCouch SR (2008) Gene nomenclature system for rice. Rice 1, 72–84.
| Gene nomenclature system for rice.Crossref | GoogleScholarGoogle Scholar |
Menguer PK, Sperotto RA, Ricachenevsky FK (2017) A walk on the wild side: Oryza species as source for rice abiotic stress tolerance. Genetics and Molecular Biology 40, 238–252.
| A walk on the wild side: Oryza species as source for rice abiotic stress tolerance.Crossref | GoogleScholarGoogle Scholar | 28323300PubMed |
Mu S, Yamaji N, Sasaki A, Luo L, Du B, Che J, Shi H, Zhao H, Huang S, Deng F, Shen Z, Guerinot ML, Zheng L, Ma JF (2021) A transporter for delivering zinc to the developing tiller bud and panicle in rice. The Plant Journal 105, 786–799.
| A transporter for delivering zinc to the developing tiller bud and panicle in rice.Crossref | GoogleScholarGoogle Scholar | 33169459PubMed |
Norton GJ, Deacon CM, Xiong L, Huang S, Meharg AA, Price AH (2010) Genetic mapping of the rice ionome in leaves and grain: identification of QTLs for 17 elements including arsenic, cadmium, iron and selenium. Plant and Soil 329, 139–153.
| Genetic mapping of the rice ionome in leaves and grain: identification of QTLs for 17 elements including arsenic, cadmium, iron and selenium.Crossref | GoogleScholarGoogle Scholar |
Norton GJ, Duan G-L, Lei M, Zhu Y-G, Meharg AA, Price AH (2012) Identification of quantitative trait loci for rice grain element composition on an arsenic impacted soil: influence of flowering time on genetic loci. Annals of Applied Biology 161, 46–56.
| Identification of quantitative trait loci for rice grain element composition on an arsenic impacted soil: influence of flowering time on genetic loci.Crossref | GoogleScholarGoogle Scholar |
Ogasawara M, Miyazaki N, Monden G, Taniko K, Lim S, Iwata M, Ishii T, Ma JF, Ishikawa R (2021) Role of qGZn9a in controlling grain zinc concentration in rice, Oryza sativa L. Theoretical and Applied Genetics 134, 3013–3022.
| Role of qGZn9a in controlling grain zinc concentration in rice, Oryza sativa L.Crossref | GoogleScholarGoogle Scholar | 34110432PubMed |
Pinson SRM, Tarpley L, Yan W, Yeater K, Lahner B, Yakubova E, Huang X-Y, Zhang M, Guerinot ML, Salt DE (2015) Worldwide genetic diversity for mineral element concentrations in rice grain. Crop Science 55, 294–311.
| Worldwide genetic diversity for mineral element concentrations in rice grain.Crossref | GoogleScholarGoogle Scholar |
Pradhan SK, Pandit E, Pawar S, Naveenkumar R, Barik SR, Mohanty SP, Nayak DK, Ghritlahre SK, Sanjiba RD, Reddy JN, Patnaik SSC (2020) Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding. BMC Plant Biology 20, 57
| Linkage disequilibrium mapping for grain Fe and Zn enhancing QTLs useful for nutrient dense rice breeding.Crossref | GoogleScholarGoogle Scholar | 32019504PubMed |
Ricachenevsky FK, Sperotto RA (2016) Into the wild: Oryza species as sources for enhanced nutrient accumulation and metal tolerance in rice. Frontiers in Plant Science 7, 974
| Into the wild: Oryza species as sources for enhanced nutrient accumulation and metal tolerance in rice.Crossref | GoogleScholarGoogle Scholar | 27446193PubMed |
Sands DC, Morris CE, Dratz EA, Pilgeram A (2009) Elevating optimal human nutrition to a central goal of plant breeding and production of plant-based foods. Plant Science 177, 377–389.
| Elevating optimal human nutrition to a central goal of plant breeding and production of plant-based foods.Crossref | GoogleScholarGoogle Scholar | 20467463PubMed |
Sasaki A, Yamaji N, Mitani-Ueno N, Kashino M, Ma JF (2015) A node-localized transporter OsZIP3 is responsible for the preferential distribution of Zn to developing tissues in rice. The Plant Journal 84, 374–384.
| A node-localized transporter OsZIP3 is responsible for the preferential distribution of Zn to developing tissues in rice.Crossref | GoogleScholarGoogle Scholar | 26332571PubMed |
Shen XH, Cao LY, Shao GS, Zhan XD, Chen SG, Wu WM, Cheng SH (2008) QTL mapping for the content of five trace elements in brown rice. Molecular Plant Breeding 6, 1061–1067.
Suman K, Neeraja CN, Madhubabu P, Rathod S, Bej S, Jadhav KP, Kumar JA, Chaitanya U, Pawar SC, Rani SH, Subbarao LV, Voleti SR (2021) Identification of promising RILs for high grain zinc through genotype × environment analysis and stable grain zinc QTL using SSRs and SNPs in rice (Oryza sativa L.). Frontiers in Plant Science 12, 587482
| Identification of promising RILs for high grain zinc through genotype × environment analysis and stable grain zinc QTL using SSRs and SNPs in rice (Oryza sativa L.).Crossref | GoogleScholarGoogle Scholar | 33679823PubMed |
Swamy BPM, Kaladhar K, Anuradha K, Batchu AK, Longvah T, Sarla N (2018) QTL analysis for grain iron and zinc concentrations in two O. nivara derived backcross populations. Rice Science 25, 197–207.
| QTL analysis for grain iron and zinc concentrations in two O. nivara derived backcross populations.Crossref | GoogleScholarGoogle Scholar |
Verma PK, Verma S, Chakrabarty D, Pandey N (2021) Biotechnological approaches to enhance zinc uptake and utilization efficiency in cereal crops. Journal of Soil Science and Plant Nutrition 21, 2412–2424.
| Biotechnological approaches to enhance zinc uptake and utilization efficiency in cereal crops.Crossref | GoogleScholarGoogle Scholar |
Wang S, Basten C, Zeng Z (2012) ‘Windows QTL cartographer 2.5’. (Department of Statistics, North Carolina State University, Raleigh, NC, USA) Available at http://statgen.ncsu.edu/qtlcart/WQTLCart.htm
Wang J, Xu H, Li N, Fan F, Wang L, Zhu Y, Li S (2015) Artificial selection of Gn1a plays an important role in improving rice yields across different ecological regions. Rice 8, 37
| Artificial selection of Gn1a plays an important role in improving rice yields across different ecological regions.Crossref | GoogleScholarGoogle Scholar | 26677125PubMed |
Wang C, Tang Z, Zhuang J-Y, Tang Z, Huang X-Y, Zhao F-J (2020) Genetic mapping of ionomic quantitative trait loci in rice grain and straw reveals OsMOT1;1 as the putative causal gene for a molybdenum QTL qMo8. Molecular Genetics and Genomics 295, 391–407.
| Genetic mapping of ionomic quantitative trait loci in rice grain and straw reveals OsMOT1;1 as the putative causal gene for a molybdenum QTL qMo8.Crossref | GoogleScholarGoogle Scholar | 31797032PubMed |
Wu T, Li X, Huang DR, Huang FL, Xiao YL, Hu BL (2020) QTL analysis for yield traits related to low nitrogen tolerance using backcrossing recombinant inbred lines derived from Dongxiang wild rice (Oryza rufipogon Griff.). Chinese Journal of Rice Science 34, 499–511.
Xu Q, Zheng T-Q, Hu X, Cheng L-R, Xu J-L, Shi Y-M, Li Z-K (2015) Examining two sets of introgression lines in rice (Oryza sativa L.) reveals favorable alleles that improve grain Zn and Fe concentrations. PLoS ONE 10, e0131846
| Examining two sets of introgression lines in rice (Oryza sativa L.) reveals favorable alleles that improve grain Zn and Fe concentrations.Crossref | GoogleScholarGoogle Scholar | 26161553PubMed |
Yang X, Huang J, Jiang Y, Zhang H-S (2009) Cloning and functional identification of two members of the ZIP (Zrt, Irt-like protein) gene family in rice (Oryza sativa L.). Journal of Molecular Biology 36, 281–287.
| Cloning and functional identification of two members of the ZIP (Zrt, Irt-like protein) gene family in rice (Oryza sativa L.).Crossref | GoogleScholarGoogle Scholar |
Yang M, Lu K, Zhao F-J, Xie W, Ramakrishna P, Wang G, Du Q, Liang L, Sun C, Zhao H, Zhang Z, Liu Z, Tian J, Huang X-Y, Wang W, Dong H, Hu J, Ming L, Xing Y, Wang G, Xiao J, Salt DE, Lian X (2018) Genome-wide association studies reveal the genetic basis of ionomic variation in rice. The Plant Cell 30, 2720–2740.
| Genome-wide association studies reveal the genetic basis of ionomic variation in rice.Crossref | GoogleScholarGoogle Scholar | 30373760PubMed |
Yu YY, Shao YF, Liu J, Fan YY, Sun CX, Cao ZY, Zhuang JY (2015) Mapping of quantitative trait loci for contents of macro- and microelements in milled rice (Oryza sativa L.). Journal of Agricultural and Food Chemistry 63, 7813–7818.
| Mapping of quantitative trait loci for contents of macro- and microelements in milled rice (Oryza sativa L.).Crossref | GoogleScholarGoogle Scholar |
Zhang FT, Xie JK (2014) Genes and QTLs resistant to biotic and abiotic stresses from wild rice and their applications in cultivar improvements. In ‘Rice-Germplasm, genetics and improvement’. (Eds W Yan, J Bao) pp. 59–78. (InTech Open: Rijeka, Croatia)
Zhang X, Zhang G, Guo L, Wang H, Zeng D, Dong G, Qian Q, Xue D (2011) Identification of quantitative trait loci for Cd and Zn concentrations of brown rice grown in Cd-polluted soils. Euphytica 180, 173–179.
| Identification of quantitative trait loci for Cd and Zn concentrations of brown rice grown in Cd-polluted soils.Crossref | GoogleScholarGoogle Scholar |
Zhang M, Pinson SRM, Tarpley L, Huang X-Y, Lahner B, Yakubova E, Baxter I, Guerinot ML, Salt DE (2014) Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain. Theoretical and Applied Genetics 127, 137–165.
| Mapping and validation of quantitative trait loci associated with concentrations of 16 elements in unmilled rice grain.Crossref | GoogleScholarGoogle Scholar | 24231918PubMed |
