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Prodhan ZH, Samonte SOPB, Sanchez DL, Talukder SK. Profiling and Improvement of Grain Quality Traits for Consumer Preferable Basmati Rice in the United States. PLANTS (BASEL, SWITZERLAND) 2024; 13:2326. [PMID: 39204762 PMCID: PMC11359321 DOI: 10.3390/plants13162326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 08/10/2024] [Accepted: 08/20/2024] [Indexed: 09/04/2024]
Abstract
Basmati rice is a premium aromatic rice that consumers choose primarily because of its distinct aroma and excellent grain quality. The grain quality of Basmati rice (GQBR) reflects the perspectives of producers, processors, sellers, and consumers related to the production, processing, marketing, and consumption of Basmati rice. Consumers, an invaluable part of the production demand and value chain of the Basmati rice industry, have the freedom to choose from different types of aromatic rice. Consumers expect their preferred Basmati rice to possess all superior rice grain qualities, including the physical, biochemical, and physiological properties. Gene functional analysis explained that a 10-base pair deletion in the promoter region of the OsSPL16 gene causes the slender grains in Basmati rice, whereas an 8-base-pair deletion in exon 7 of the OsBadh2 gene (located in the fgr region on rice chromosome 8) results in the distinct aroma. Furthermore, a combination of the genetic characteristics of the gw8 and gs3 genes has led to the creation of a long-grain Basmati-type rice cultivar. It has also been demonstrated that agricultural, genetic, and environmental conditions significantly influence GQBR. Hence, research on improving GQBR requires a multidimensional approach and sophisticated elements due to the complexity of its nature and preference diversity. This review covers the basic definitions of grain quality traits, consumer preference criteria, influencing factors, and strategies for producing superior-quality Basmati rice in the United States. This knowledge will be useful in improving the grain quality of Basmati and Basmati-type rice, as well as developing appropriate breeding programs that will meet the preferences of different countries and cultures.
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Affiliation(s)
- Zakaria Hossain Prodhan
- Texas A&M AgriLife Research Center, 1509 Aggie Drive, Beaumont, TX 77713, USA; (D.L.S.); (S.K.T.)
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Pandey S. Agronomic potential of plant-specific Gγ proteins. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2024; 30:337-347. [PMID: 38623166 PMCID: PMC11016034 DOI: 10.1007/s12298-024-01428-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 01/17/2024] [Accepted: 02/28/2024] [Indexed: 04/17/2024]
Abstract
The vascular plant-specific type III Gγ proteins have emerged as important targets for biotechnological applications. These proteins are exemplified by Arabidopsis AGG3, rice Grain Size 3 (GS3), Dense and Erect Panicle 1 (DEP1), and GGC2 and regulate plant stature, seed size, weight and quality, nitrogen use efficiency, and multiple stress responses. These Gγ proteins are an integral component of the plant heterotrimeric G-protein complex and differ from the canonical Gγ proteins due to the presence of a long, cysteine-rich C-terminal region. Most cereal genomes encode three or more of these proteins, which have similar N-terminal Gγ domains but varying lengths of the C-terminal domain. The C-terminal domain is hypothesized to give specificity to the protein function. Intriguingly, many accessions of cultivated cereals have natural deletion of this region in one or more proteins, but the mechanistic details of protein function remain perplexing. Distinct, sometimes contrasting, effects of deletion of the C-terminal region have been reported in different crops or under varying environmental conditions. This review summarizes the known roles of type III Gγ proteins, the possible action mechanisms, and a perspective on what is needed to comprehend their full agronomic potential.
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Affiliation(s)
- Sona Pandey
- Donald Danforth Plant Science Center, 975 N. Warson Road, St. Louis, MO 63132 USA
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3
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Jin X, Chen J, Khan A, Chen Z, Gao R, Lu Y, Zheng X. Triacylglycerol lipase, OsSG34, plays an important role in grain shape and appearance quality in rice. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 117:840-855. [PMID: 37938788 DOI: 10.1111/tpj.16532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 11/09/2023]
Abstract
Optimal grain-appearance quality is largely determined by grain size. To date, dozens of grain size-related genes have been identified. However, the regulatory mechanism of slender grain formation is not fully clear. We identified the OsSG34 gene by map-based cloning. A 9-bp deletion on 5'-untranslated region of OsSG34, which resulted in the expression difference between the wild-type and sg34 mutant, led to the slender grains and good transparency in sg34 mutant. OsSG34 as an α/β fold triacylglycerol lipase affected the triglyceride content directly, and the components of cell wall indirectly, especially the lignin between the inner and outer lemmas in rice grains, which could affect the change in grain size by altering cell proliferation and expansion, while the change in starch content and starch granule arrangement in endosperm could affect the grain-appearance quality. Moreover, the OsERF71 was identified to directly bind to cis-element on the mutant site, thereby regulating the OsSG34 expression. Knockout of three OsSG34 homologous genes resulted in slender grains as well. The study demonstrated OsSG34, involved in lipid metabolism, affected grain size and quality. Our findings suggest that the OsSG34 gene could be used in rice breeding for high yield and good grain-appearance quality via marker-assisted selection and gene-editing approaches.
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Affiliation(s)
- Xiaoli Jin
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Jian Chen
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Asadullah Khan
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Ziyan Chen
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Rui Gao
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Yingying Lu
- The Key Laboratory for Crop Germplasm Resource of Zhejiang Province, the Advanced Seed Institute, Zhejiang University, Hangzhou, 310058, China
| | - Xi Zheng
- Analysis Center of Agrobiology and Environmental Sciences, Zhejiang University, Hangzhou, 310058, China
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Mohanasundaram B, Pandey S. Moving beyond the arabidopsis-centric view of G-protein signaling in plants. TRENDS IN PLANT SCIENCE 2023; 28:1406-1421. [PMID: 37625950 DOI: 10.1016/j.tplants.2023.07.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 07/24/2023] [Accepted: 07/28/2023] [Indexed: 08/27/2023]
Abstract
Heterotrimeric G-protein-mediated signaling is a key mechanism to transduce a multitude of endogenous and environmental signals in diverse organisms. The scope and expectations of plant G-protein research were set by pioneering work in metazoans. Given the similarity of the core constituents, G-protein-signaling mechanisms were presumed to be universally conserved. However, because of the enormous diversity of survival strategies and endless forms among eukaryotes, the signal, its interpretation, and responses vary even among different plant groups. Earlier G-protein research in arabidopsis (Arabidopsis thaliana) has emphasized its divergence from Metazoa. Here, we compare recent evidence from diverse plant lineages with the available arabidopsis G-protein model and discuss the conserved and novel protein components, signaling mechanisms, and response regulation.
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Affiliation(s)
| | - Sona Pandey
- Donald Danforth Plant Science Center, 975 N. Warson Road, St Louis, MO 63132, USA.
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5
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Alam M, Wang Y, Chen J, Lou G, Yang H, Zhou Y, Luitel S, Jiang G, He Y. QTL detection for rice grain storage protein content and genetic effect verifications. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:89. [PMID: 38059164 PMCID: PMC10695898 DOI: 10.1007/s11032-023-01436-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 11/21/2023] [Indexed: 12/08/2023]
Abstract
Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating-cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions-albumins, globulins, prolamins, glutelin, and grain protein content-were evaluated by exploiting two BC3F2 mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01436-7.
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Affiliation(s)
- Mufid Alam
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - YingYing Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Jianxian Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Guangming Lou
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Hanyuan Yang
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Yin Zhou
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Saurav Luitel
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Gonghao Jiang
- College of Life Science, Heilongjiang University, Haerbin, 150080 Heilongjiang China
| | - Yuqing He
- National Key Laboratory of Crop Genetic Improvement and National Center of Crop Molecular Breeding, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, 430070 Hubei China
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Yang X, Pan Y, Xia X, Qing D, Chen W, Nong B, Zhang Z, Zhou W, Li J, Li D, Dai G, Deng G. Molecular basis of genetic improvement for key rice quality traits in Southern China. Genomics 2023; 115:110745. [PMID: 37977332 DOI: 10.1016/j.ygeno.2023.110745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 11/06/2023] [Accepted: 11/12/2023] [Indexed: 11/19/2023]
Abstract
Grain qualities including milling quality, appearance quality, eating and cooking quality, and nutritional quality are important indicators in rice breeding. Significant achievements in genetic improvement of rice quality have been made. In this study, we analyzed the variation patterns of 16 traits in 1570 rice varieties and found significant improvements in appearance quality and eating and cooking quality, particularly in hybrid rice. Through genome-wide association study and allelic functional nucleotide polymorphisms analysis of quality trait genes, we found that ALK, FGR1, FLO7, GL7/GW7, GLW7, GS2, GS3, ONAC129, OsGRF8, POW1, WCR1, and Wx were associated with the genetic improvement of rice quality traits in Southern China. Allelic functional nucleotide polymorphisms analysis of 13 important rice quality genes, including fragrance gene fgr, were performed using the polymerase chain reaction amplification refractory mutation system technology. The results showed that Gui516, Gui569, Gui721, Ryousi, Rsimiao, Rbasi, and Yuehui9802 possessed multiple superior alleles. This study elucidates the phenotypic changes and molecular basis of key quality traits of varieties in Southern China. The findings will provide guidance for genetic improvement of rice quality and the development of new varieties.
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Affiliation(s)
- Xinghai Yang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Yinghua Pan
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Xiuzhong Xia
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Dongjin Qing
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Weiwei Chen
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Baoxuan Nong
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Zongqiong Zhang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Weiyong Zhou
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Jingcheng Li
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China
| | - Danting Li
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
| | - Gaoxing Dai
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
| | - Guofu Deng
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi 530007, China.
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Kumar A, Thomas J, Gill N, Dwiningsih Y, Ruiz C, Famoso A, Pereira A. Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress. Sci Rep 2023; 13:4880. [PMID: 36966148 PMCID: PMC10039871 DOI: 10.1038/s41598-023-31399-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 03/10/2023] [Indexed: 03/27/2023] Open
Abstract
Elevated nighttime temperatures resulting from climate change significantly impact the rice crop worldwide. The rice (Oryza sativa L.) plant is highly sensitive to high nighttime temperature (HNT) during grain-filling (reproductive stage). HNT stress negatively affects grain quality traits and has a major impact on the value of the harvested rice crop. In addition, along with grain dimensions determining rice grain market classes, the grain appearance and quality traits determine the rice grain market value. During the last few years, there has been a major concern for rice growers and the rice industry over the prevalence of rice grains opacity and the reduction of grain dimensions affected by HNT stress. Hence, the improvement of heat-stress tolerance to maintain grain quality of the rice crop under HNT stress will bolster future rice value in the market. In this study, 185 F12-recombinant inbred lines (RILs) derived from two US rice cultivars, Cypress (HNT-tolerant) and LaGrue (HNT-sensitive) were screened for the grain quality traits grain length (GL), grain width (GW), and percent chalkiness (%chalk) under control and HNT stress conditions and evaluated to identify the genomic regions associated with the grain quality traits. In total, there were 15 QTLs identified; 6 QTLs represented under control condition explaining 3.33% to 8.27% of the phenotypic variation, with additive effects ranging from - 0.99 to 0.0267 on six chromosomes and 9 QTLs represented under HNT stress elucidating 6.39 to 51.53% of the phenotypic variation, with additive effects ranging from - 8.8 to 0.028 on nine chromosomes for GL, GW, and % chalk. These 15 QTLs were further characterized and scanned for natural genetic variation in a japonica diversity panel (JDP) to identify candidate genes for GL, GW, and %chalk. We found 6160 high impact single nucleotide polymorphisms (SNPs) characterized as such depending on their type, region, functional class, position, and proximity to the gene and/or gene features, and 149 differentially expressed genes (DEGs) in the 51 Mbp genomic region comprising of the 15 QTLs. Out of which, 11 potential candidate genes showed high impact SNP associations. Therefore, the analysis of the mapped QTLs and their genetic dissection in the US grown Japonica rice genotypes at genomic and transcriptomic levels provide deep insights into genetic variation beneficial to rice breeders and geneticists for understanding the mechanisms related to grain quality under heat stress in rice.
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Affiliation(s)
- Anuj Kumar
- Departemnt of Crop, Soil, & Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA
| | - Julie Thomas
- Departemnt of Crop, Soil, & Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA
| | - Navdeep Gill
- Department of Biological Sciences, Nova Southeastern University, Fort Lauderdale, FL, 33314, USA
| | - Yheni Dwiningsih
- Departemnt of Crop, Soil, & Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA
| | - Charles Ruiz
- Departemnt of Crop, Soil, & Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA
| | - Adam Famoso
- H. Rouse Caffey Rice Research Station, Louisiana State University Agricultural Center, Rayne, LA, 70578, USA
| | - Andy Pereira
- Departemnt of Crop, Soil, & Environmental Sciences, University of Arkansas, Fayetteville, AR, 72701, USA.
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Wang C, Feng X, Yuan Q, Lin K, Zhang X, Yan L, Nan J, Zhang W, Wang R, Wang L, Xue Q, Yang X, Liu Z, Lin S. Upgrading the genome of an elite japonica rice variety Kongyu 131 for lodging resistance improvement. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:419-432. [PMID: 36382925 PMCID: PMC9884016 DOI: 10.1111/pbi.13963] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/08/2022] [Accepted: 11/10/2022] [Indexed: 06/16/2023]
Abstract
Developing a new rice variety requires tremendous efforts and years of input. To improve the defect traits of the excellent varieties becomes more cost and time efficient than breeding a completely new variety. Kongyu 131 is a high-performing japonica variety with early maturity, high yield, wide adaptability and cold resistance, but the poor-lodging resistance hinders the industrial production of Kongyu 131 in the Northeastern China. In this study, we attempted to improve the lodging resistance of Kongyu 131 from perspectives of both gene and trait. On the one hand, by QTL analysis and fine mapping we discovered the candidate gene loci. The following CRISPR/Cas9 and transgenic complementation study confirmed that Sd1 dominated the lodging resistance and favourable allele was mined for precise introduction and improvement. On the other hand, the Sd1 allelic variant was identified in Kongyu 131 by sequence alignment, then introduced another excellent allelic variation by backcrossing. Then, the two new resulting Kongyu 131 went through the field evaluation under different environments, planting densities and nitrogen fertilizer conditions. The results showed that the plant height of upgraded Kongyu 131 was 17%-26% lower than Kongyu 131 without penalty in yield. This study demonstrated a precise and targeted way to update the rice genome and upgrade the elite rice varieties by improving only a few gene defects from the perspective of breeding.
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Affiliation(s)
- Chen Wang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Xiaomin Feng
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
- Rice Research Institute, Guangdong Academy of Agricultural SciencesGuangzhouChina
- Guangdong Key Laboratory of New Technology in Rice BreedingGuangzhouChina
| | - Qingbo Yuan
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Kangxue Lin
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Xiaohui Zhang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Li Yan
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Jianzong Nan
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Wenqi Zhang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Rongsheng Wang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Lihong Wang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Qian Xue
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Xiaowen Yang
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
| | - Zhixia Liu
- Rice Research Institute, Guangdong Academy of Agricultural SciencesGuangzhouChina
- Guangdong Key Laboratory of New Technology in Rice BreedingGuangzhouChina
| | - Shaoyang Lin
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesBeijingChina
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Zhao N, Yuan R, Usman B, Qin J, Yang J, Peng L, Mackon E, Liu F, Qin B, Li R. Detection of QTLs Regulating Six Agronomic Traits of Rice Based on Chromosome Segment Substitution Lines of Common Wild Rice ( Oryza rufipogon Griff.) and Mapping of qPH1.1 and qLMC6.1. Biomolecules 2022; 12:biom12121850. [PMID: 36551278 PMCID: PMC9775987 DOI: 10.3390/biom12121850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/06/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
Wild rice is a primary source of genes that can be utilized to generate rice cultivars with advantageous traits. Chromosome segment substitution lines (CSSLs) are consisting of a set of consecutive and overlapping donor chromosome segments in a recipient's genetic background. CSSLs are an ideal genetic population for mapping quantitative traits loci (QTLs). In this study, 59 CSSLs from the common wild rice (Oryza rufipogon Griff.) accession DP15 under the indica rice cultivar (O. sativa L. ssp. indica) variety 93-11 background were constructed through multiple backcrosses and marker-assisted selection (MAS). Through high-throughput whole genome re-sequencing (WGRS) of parental lines, 12,565 mapped InDels were identified and designed for polymorphic molecular markers. The 59 CSSLs library covered 91.72% of the genome of common wild rice accession DP15. The DP15-CSSLs displayed variation in six economic traits including grain length (GL), grain width (GW), thousand-grain weight (TGW), grain length-width ratio (GLWR), plant height (PH), and leaf margin color (LMC), which were finally attributed to 22 QTLs. A homozygous CSSL line and a purple leave margin CSSL line were selected to construct two secondary genetic populations for the QTLs mapping. Thus, the PH-controlling QTL qPH1.1 was mapped to a region of 4.31-Mb on chromosome 1, and the LMC-controlling QTL qLMC6.1 was mapped to a region of 370-kb on chromosome 6. Taken together, these identified novel QTLs/genes from common wild rice can potentially promote theoretical knowledge and genetic applications to rice breeders worldwide.
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Affiliation(s)
- Neng Zhao
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
| | - Ruizhi Yuan
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
| | - Babar Usman
- Graduate School of Green-Bio Science and Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea
| | - Jiaming Qin
- Maize Research Institute, Guangxi Academy of Agricultural Science, Nanning 530007, China
| | - Jinlian Yang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
| | - Liyun Peng
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530005, China
| | - Enerand Mackon
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, College of Life Science and Technology, Guangxi University, Nanning 530005, China
| | - Fang Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
| | - Baoxiang Qin
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
| | - Rongbai Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, Nanning 530004, China
- Correspondence:
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10
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Kulkarni SR, Balachandran SM, Ulaganathan K, Balakrishnan D, Prasad ASH, Rekha G, Kousik MBVN, Hajira SK, Kale RR, Aleena D, Anila M, Punniakoti E, Dilip T, Pranathi K, Das MA, Shaik M, Chaitra K, Sinha P, Sundaram RM. Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population. 3 Biotech 2021; 11:513. [PMID: 34926111 DOI: 10.1007/s13205-021-03045-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 10/29/2021] [Indexed: 11/30/2022] Open
Abstract
A doubled haploid (DH) population consisting of 125 DHLs derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R) was utilized for Quantitative Trait Loci (QTL) mapping to identify novel genomic regions associated with yield related traits. A genetic map was constructed with 126 polymorphic SSR and EST derived markers, which were distributed across rice genome. QTL analysis using inclusive composite interval mapping (ICIM) method identified a total of 24 major and minor effect QTLs. Among them, twelve major effect QTLs were identified for days to fifty percent flowering (qDFF12-1), total grain yield/plant (qYLD3-1 and qYLD6-1), test (1,000) grain weight (qTGW6-1 and qTGW7-1), panicle weight (qPW9-1), plant height (qPH12-1), flag leaf length (qFLL6-1), flag leaf width (qFLW4-1), panicle length (qPL3-1 and qPL6-1) and biomass (qBM4-1), explaining 29.95-56.75% of the phenotypic variability with LOD scores range of 2.72-16.51. Chromosomal regions with gene clusters were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1) and on chromosome 6 for total grain yield/plant (qYLD6-1), flag leaf length (qFLL6-1) and panicle length (qPL6-1). Majority of the QTLs identified were observed to be co-localized with the previously reported QTL regions. Five novel, major effect QTLs associated with panicle weight (qPW9-1), plant height (qPH12-1), flag leaf width (qFLW4-1), panicle length (qPL3-1) and biomass (qBM4-1) and three novel minor effect QTLs for panicle weight (qPW3-1 and qPW8-1) and fertile grains per panicle (qFGP5-1) were identified. These QTLs can be used in breeding programs aimed to yield improvement after their validation in alternative populations. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s13205-021-03045-7.
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Affiliation(s)
- Swapnil Ravindra Kulkarni
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - S M Balachandran
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - K Ulaganathan
- Centre for Plant Molecular Biology (CPMB), Osmania University, Hyderabad, 500007 India
| | - Divya Balakrishnan
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - A S Hari Prasad
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - G Rekha
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - M B V N Kousik
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - S K Hajira
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - Ravindra Ramarao Kale
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - D Aleena
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - M Anila
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - E Punniakoti
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - T Dilip
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - K Pranathi
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - M Ayyappa Das
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - Mastanbee Shaik
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - K Chaitra
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - Pragya Sinha
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
| | - R M Sundaram
- Biotechnology Department, ICAR-Indian Institute of Rice Research, Rajendranagar, Hyderabad, Telangana State (TS) 500030 India
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11
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Zhang L, Ma B, Bian Z, Li X, Zhang C, Liu J, Li Q, Liu Q, He Z. Grain Size Selection Using Novel Functional Markers Targeting 14 Genes in Rice. RICE (NEW YORK, N.Y.) 2020; 13:63. [PMID: 32902771 PMCID: PMC7481322 DOI: 10.1186/s12284-020-00427-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/02/2020] [Indexed: 05/19/2023]
Abstract
BACKGROUND Grain size is an extremely important aspect of rice breeding, affecting both grain yield and quality traits. It is controlled by multiple genes and tracking these genes in breeding schemes should expedite selection of lines with superior grain yield and quality, thus it is essential to develop robust, efficient markers. RESULT In this study, 14 genes related to grain size (GW2, GS2, qLGY3, GS3, GL3.1, TGW3, GS5, GW5, GS6, TGW6, GW6a, GLW7, GL7 and GW8) were selected for functional marker development. Twenty-one PCR-gel-based markers were developed to genotype the candidate functional nucleotide polymorphisms (FNPs) of these genes, and all markers can effectively recognize the corresponding allele types. To test the allele effects of different FNPs, a global collection of rice cultivars including 257 accessions from the Rice Diversity Panel 1 was used for allele mining, and four grain-size-related traits were investigated at two planting locations. Three FNPs for GW2, GS2 and GL3.1 were genotyped as rare alleles only found in cultivars with notably large grains, and the allele contributions of the remaining FNPs were clarified in both the indica and japonica subspecies. Significant trait contributions were found for most of the FNPs, especially GS3, GW5 and GL7. Of note, GW5 could function as a key regulator to coordinate the performance of other grain size genes. The allele effects of several FNPs were also tested by QTL analysis using an F2 population, and GW5 was further identified as the major locus with the largest contribution to grain width and length to width ratio. CONCLUSIONS The functional markers are robust for genotyping different cultivars and may facilitate the rational design of grain size to achieve a balance between grain yield and quality in future rice breeding efforts.
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Affiliation(s)
- Lin Zhang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding /Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Bin Ma
- School of Life Science and Technology, Shanghai Tech University, Shanghai, 201210 China
| | - Zhong Bian
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding /Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou, 225009 China
| | - Xiaoyuan Li
- School of Life Science and Technology, Shanghai Tech University, Shanghai, 201210 China
| | - Changquan Zhang
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Jiyun Liu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology & Ecology, Chinese Academy of Sciences, Shanghai, 200032 China
| | - Qun Li
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology & Ecology, Chinese Academy of Sciences, Shanghai, 200032 China
| | - Qiaoquan Liu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding /Joint International Research Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Zuhua He
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology & Ecology, Chinese Academy of Sciences, Shanghai, 200032 China
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12
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Kulkarni SR, Balachandran SM, Ulaganathan K, Balakrishnan D, Praveen M, Prasad ASH, Fiyaz RA, Senguttuvel P, Sinha P, Kale RR, Rekha G, Kousik MBVN, Harika G, Anila M, Punniakoti E, Dilip T, Hajira SK, Pranathi K, Das MA, Shaik M, Chaitra K, Rao PK, Gangurde SS, Pandey MK, Sundaram RM. Molecular mapping of QTLs for yield related traits in recombinant inbred line (RIL) population derived from the popular rice hybrid KRH-2 and their validation through SNP genotyping. Sci Rep 2020; 10:13695. [PMID: 32792551 PMCID: PMC7427098 DOI: 10.1038/s41598-020-70637-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Accepted: 07/10/2020] [Indexed: 01/27/2023] Open
Abstract
The study was undertaken to identify the quantitative trait loci (QTLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23–22.76% of the phenotypic variance with LOD scores range of 6.5–10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.
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Affiliation(s)
- Swapnil Ravindra Kulkarni
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - S M Balachandran
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India.
| | - K Ulaganathan
- Centre for Plant Molecular Biology (CPMB), Osmania University, Hyderabad, India
| | - Divya Balakrishnan
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - M Praveen
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - A S Hari Prasad
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - R A Fiyaz
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - P Senguttuvel
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - Pragya Sinha
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - Ravindra R Kale
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - G Rekha
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - M B V N Kousik
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - G Harika
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - M Anila
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - E Punniakoti
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - T Dilip
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - S K Hajira
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - K Pranathi
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - M Ayyappa Das
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - Mastanbee Shaik
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - K Chaitra
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - P Koteswara Rao
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India
| | - Sunil S Gangurde
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Manish K Pandey
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - R M Sundaram
- Crop Improvement Section, ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, 500030, India.
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13
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Gouda G, Gupta MK, Donde R, Mohapatra T, Vadde R, Behera L. Marker-assisted selection for grain number and yield-related traits of rice ( Oryza sativa L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2020; 26:885-898. [PMID: 32377039 PMCID: PMC7196572 DOI: 10.1007/s12298-020-00773-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/11/2020] [Accepted: 02/13/2020] [Indexed: 05/11/2023]
Abstract
Continuous rise in the human population has resulted in an upsurge in food demand, which in turn demand grain yield enhancement of cereal crops, including rice. Rice yield is estimated via the number of tillers, grain number per panicles, and the number of spikes present per panicle. Marker-assisted selection (MAS) serve as one of the best ways to introduce QTLs/gene associated with yield in the rice plant. MAS has also been employed effectively in dissecting several other complex agricultural traits, for instance, drought, cold tolerance, salinity, etc. in rice plants. Thus, in this review, authors attempted to collect information about various genes/QTLs associated with high yield, including grain number, in rice and how different scheme of MAS can be employed to introduce them in rice (Oryza sativa L.) plant, which in turn will enhance rice yield. Information obtained to date suggest that, numerous QTLs, e.g., Gn1a, Dep1, associated with grain number and yield-related traits, have been identified either via mapping or cloning approaches. These QTLs have been successfully introduced into rice plants using various schemes of MAS for grain yield enhancement in rice. However, sometimes, MAS does not perform well in breeding, which might be due to lack of resources, skilled labors, reliable markers, and high costs associated with MAS. Thus, by overcoming these problems, we can enhance the application of MAS in plant breeding, which, in turn, may help us in increasing yield, which subsequently may help in bridging the gap between demand and supply of food for the continuously growing population.
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Affiliation(s)
- Gayatri Gouda
- ICAR-National Rice Research Institute, Cuttack, Odisha 753 006 India
| | - Manoj Kumar Gupta
- Department of Biotechnology and Bioinformatics, Yogi Vemana University, Kadapa, Andhra Pradesh 516 005 India
| | - Ravindra Donde
- ICAR-National Rice Research Institute, Cuttack, Odisha 753 006 India
| | - Trilochan Mohapatra
- Secretary (DARE) and Director General (ICAR), Government of India, New Delhi, India
| | - Ramakrishna Vadde
- Department of Biotechnology and Bioinformatics, Yogi Vemana University, Kadapa, Andhra Pradesh 516 005 India
| | - Lambodar Behera
- ICAR-National Rice Research Institute, Cuttack, Odisha 753 006 India
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14
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Li X, Chen Z, Zhang G, Lu H, Qin P, Qi M, Yu Y, Jiao B, Zhao X, Gao Q, Wang H, Wu Y, Ma J, Zhang L, Wang Y, Deng L, Yao S, Cheng Z, Yu D, Zhu L, Xue Y, Chu C, Li A, Li S, Liang C. Analysis of genetic architecture and favorable allele usage of agronomic traits in a large collection of Chinese rice accessions. SCIENCE CHINA-LIFE SCIENCES 2020; 63:1688-1702. [PMID: 32303966 DOI: 10.1007/s11427-019-1682-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 03/16/2020] [Indexed: 12/31/2022]
Abstract
Genotyping and phenotyping large natural populations provide opportunities for population genomic analysis and genome-wide association studies (GWAS). Several rice populations have been re-sequenced in the past decade; however, many major Chinese rice cultivars were not included in these studies. Here, we report large-scale genomic and phenotypic datasets for a collection mainly comprised of 1,275 rice accessions of widely planted cultivars and parental hybrid rice lines from China. The population was divided into three indica/Xian and three japonica/Geng phylogenetic subgroups that correlate strongly with their geographic or breeding origins. We acquired a total of 146 phenotypic datasets for 29 agronomic traits under multi-environments for different subpopulations. With GWAS, we identified a total of 143 significant association loci, including three newly identified candidate genes or alleles that control heading date or amylose content. Our genotypic analysis of agronomically important genes in the population revealed that many favorable alleles are underused in elite accessions, suggesting they may be used to provide improvements in future breeding efforts. Our study provides useful resources for rice genetics research and breeding.
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Affiliation(s)
- Xiuxiu Li
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhuo Chen
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guomin Zhang
- Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Hongwei Lu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China.,University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Peng Qin
- Rice Research Institute, State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ming Qi
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Ying Yu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Bingke Jiao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xianfeng Zhao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Qiang Gao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Hao Wang
- Rice Research Institute, State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yunyu Wu
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou, 225009, China.,Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing, 210095, China
| | - Juntao Ma
- Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Liyan Zhang
- Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Yongli Wang
- Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Lingwei Deng
- Biotechnology Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Shanguo Yao
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhukuang Cheng
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Diqiu Yu
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, Yunnan University, Kunming, 650091, China
| | - Lihuang Zhu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yongbiao Xue
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chengcai Chu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China
| | - Aihong Li
- Lixiahe Agricultural Research Institute of Jiangsu Province, Yangzhou, 225009, China. .,Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing, 210095, China.
| | - Shigui Li
- Rice Research Institute, State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China.
| | - Chengzhi Liang
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 100101, China. .,University of Chinese Academy of Sciences, Beijing, 100049, China.
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15
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Chun Y, Fang J, Zafar SA, Shang J, Zhao J, Yuan S, Li X. MINI SEED 2 (MIS2) Encodes a Receptor-like Kinase that Controls Grain Size and Shape in Rice. RICE (NEW YORK, N.Y.) 2020; 13:7. [PMID: 32006119 PMCID: PMC6994593 DOI: 10.1186/s12284-020-0368-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 01/20/2020] [Indexed: 05/22/2023]
Abstract
BACKGROUND Grain size is a key agronomic trait that is directly associated with grain yield in rice. Although several genes related to grain size in rice have been identified, our understanding of the mechanism of grain development is still limited. RESULTS In this study, we reported the characterization of a novel seed size mutant mini seed 2 (mis2), in which the grain showed reduced length, width and thickness along with wrinkled surface. Microscopic analysis revealed that the spikelet epidermal cell size was reduced but the cell number was increased in the mis2 mutant, suggesting that MIS2 controls grain size by coordinately regulating epidermal cell size and cell number. Map-based cloning revealed that MIS2 encodes a receptor-like kinase CRINKLY4 (CR4) which showed the highest expression in developing panicles. The MIS2 protein is localized primarily on the plasma membrane along with the endosome. However, the Arg258Gln mutation located in extracellular domain in the mis2 mutant disturbed its subcellular localization. Additionally, three major haplotypes of MIS2 were identified in the japonica, indica and aus rice cultivars. The 18-bp InDel (insertion and deletion) in the 5'-UTR (untranslated region) caused different expression level of MIS2 in haplotypes. CONCLUSIONS We reported a key role of OsCR4 in controlling grain size and shape by coordinately regulating epidermal cell size and cell number. The Arg258 in the extracellular seven-repeat domain is essential for the correct subcellular behavior and function of the OsCR4 protein.
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Affiliation(s)
- Yan Chun
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jingjing Fang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Syed Adeel Zafar
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jiangyuan Shang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jinfeng Zhao
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | | | - Xueyong Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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16
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Yang D, Tang J, Yang D, Chen Y, Ali J, Mou T. Improving rice blast resistance of Feng39S through molecular marker-assisted backcrossing. RICE (NEW YORK, N.Y.) 2019; 12:70. [PMID: 31502096 PMCID: PMC6733936 DOI: 10.1186/s12284-019-0329-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 08/30/2019] [Indexed: 05/13/2023]
Abstract
BACKGROUND Rice blast caused by Magnaporthe oryzae is one of the most widespread biotic constraints that threaten rice production. Using major resistance genes for rice blast resistance improvement is considered to be an efficient and technically feasible approach to achieve optimal grain yield. RESULTS We report here the introgression of the broad-spectrum blast resistance gene Pi2 into the genetic background of an elite PTGMS line, Feng39S, for enhancing it and its derived hybrid blast resistance through marker-assisted backcrossing (MABC) coupled with genomics-based background selection. Two PTGMS lines, designated as DB16206-34 and DB16206-38, stacking homozygous Pi2 were selected, and their genetic background had recurrent parent genome recovery of 99.67% detected by the SNP array RICE6K. DB16206-34 and DB16206-38 had high resistance frequency, with an average of 94.7%, when infected with 57 blast isolates over 2 years, and the resistance frequency of their derived hybrids ranged from 68.2% to 95.5% under inoculation of 22 blast isolates. The evaluation of results under natural blast epidemic field conditions showed that the selected PTGMS lines and their derived hybrids were resistant against leaf and neck blast. The characterizations of the critical temperature point of fertility-sterility alternation of the selected PTGMS lines, yield, main agronomic traits, and rice quality of the selected PTGMS lines and their hybrids were identical to those of the recurrent parent and its hybrids. DB16206-34/9311 or DB16206-38/9311 can be used as a blast-resistant version to replace the popular hybrid Fengliangyou 4. Likewise, DB16206-34/FXH No.1 or DB16206-38/FXH No.1 can also be used as a blast-resistant version to replace another popular hybrid Fengliangyou Xiang 1. CONCLUSIONS Our evaluation is the first successful case to apply MABC with genomics-based background selection to improve the blast resistance of PTGMS lines for two-line hybrid rice breeding.
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Affiliation(s)
- Dabing Yang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Jianhao Tang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Di Yang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Ying Chen
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
| | - Jauhar Ali
- Rice Breeding Platform, International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
| | - Tongmin Mou
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China
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Wang Q, Sun G, Ren X, Du B, Cheng Y, Wang Y, Li C, Sun D. Dissecting the Genetic Basis of Grain Size and Weight in Barley ( Hordeum vulgare L.) by QTL and Comparative Genetic Analyses. FRONTIERS IN PLANT SCIENCE 2019; 10:469. [PMID: 31105718 PMCID: PMC6491919 DOI: 10.3389/fpls.2019.00469] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 03/28/2019] [Indexed: 05/23/2023]
Abstract
Grain size and weight are crucial components of barley yield and quality and are the target characteristics of domestication and modern breeding. Despite this, little is known about the genetic and molecular mechanisms of grain size and weight in barley. Here, we evaluated nine traits determining grain size and weight, including thousand grain weight (Tgw), grain length (Gl), grain width (Gw), grain length-width ratio (Lwr), grain area (Ga), grain perimeter (Gp), grain diameter (Gd), grain roundness (Gr), and factor form density (Ffd), in a double haploid (DH) population for three consecutive years. Using five mapping methods, we successfully identified 60 reliable QTLs and 27 hotspot regions that distributed on all chromosomes except 6H which controls the nine traits of grain size and weight. Moreover, we also identified 164 barley orthologs of 112 grain size/weight genes from rice, maize, wheat and 38 barley genes that affect grain yield. A total of 45 barley genes or orthologs were identified as potential candidate genes for barley grain size and weight, including 12, 20, 9, and 4 genes or orthologs for barley, rice, maize, and wheat, respectively. Importantly, 20 of them were located in the 14 QTL hotspot regions on chromosome 1H, 2H, 3H, 5H, and 7H, which controls barley grain size and weight. These results indicated that grain size/weight genes of other cereal species might have the same or similar functions in barley. Our findings provide new insights into the understanding of the genetic basis of grain size and weight in barley, and new information to facilitate high-yield breeding in barley. The function of these potential candidate genes identified in this study are worth exploring and studying in detail.
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Affiliation(s)
- Qifei Wang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Genlou Sun
- Department of Biology, Saint Mary’s University, Halifax, NS, Canada
| | - Xifeng Ren
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Binbin Du
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yun Cheng
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yixiang Wang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Chengdao Li
- School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA, Australia
| | - Dongfa Sun
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Hubei Collaborative Innovation Centre for Grain Industry, Yangtze University, Jingzhou, China
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Bazrkar-Khatibani L, Fakheri BA, Hosseini-Chaleshtori M, Mahender A, Mahdinejad N, Ali J. Genetic Mapping and Validation of Quantitative Trait Loci (QTL) for the Grain Appearance and Quality Traits in Rice ( Oryza sativa L.) by Using Recombinant Inbred Line (RIL) Population. Int J Genomics 2019; 2019:3160275. [PMID: 30931320 PMCID: PMC6410440 DOI: 10.1155/2019/3160275] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 01/16/2019] [Accepted: 01/22/2019] [Indexed: 01/22/2023] Open
Abstract
Rice grain shape and nutritional quality traits have high economic value for commercial production of rice and largely determine the market price, besides influencing the global food demand for high-quality rice. In order to understand the genetic components of grain appearance traits in paddy, brown, and head rice, 15 traits were evaluated by using 157 recombinant inbred lines (RILs) derived from a cross between two Iranian rice cultivars Ali-Kazemi (A) and Kadous (K). A significant variation was observed and showed transgressive segregation among the RILs. Correlations between the visual appearances of grain traits were studied. A linkage map with 65 polymorphic SSR markers was constructed, which covered 1517.32 cM of the rice genome. A total of seven QTLs were identified on four chromosomes, 1, 6, 9, and 12, associated with four traits, which are explained by the total phenotypic variation of 44.27% and LOD score of 32.77 in 2014 and 2015, respectively. Among these, four QTLs for two traits were consistently flanked by RM23904 and RM24432 on chromosome 9. Single QTL for head grain length (HGL) expressed in both the years on chromosomes 1 and 9. A major QTL for seed weight was detected on chromosome 9, which explained 10.18% of the phenotypic variation. The additive effect of all the QTLs was positively contributed by Ali-Kazemi allele, except one QTL on chromosome 6 (qBGL_6) that showed a negative additive effect being contributed by the Kadous allele. The study also validated the identified QTLs with the polymorphic SSR markers that were previously reported. Novel QTLs were identified on chromosomes 6 and 9, and many of the polymorphic markers were found to be associated with milling processing of grain quality, cooking, and nutraceutical properties of rice by extensive literature and database analysis. Therefore, these validated QTLs and marker information could be utilized in the marker-assisted selection to improve grain appearance and nutritional grain quality traits in rice.
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Affiliation(s)
| | | | - Maryam Hosseini-Chaleshtori
- Rice Research Institute of Iran (RRII), Agricultural Research, Education and Extension Organization, Rasht 1658, Iran
| | - Anumalla Mahender
- Rice Breeding Platform, International Rice Research Institute (IRRI), Los Baños, Laguna 4031, Philippines
| | | | - Jauhar Ali
- Rice Breeding Platform, International Rice Research Institute (IRRI), Los Baños, Laguna 4031, Philippines
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