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Surapaneni M, Balakrishnan D, Addanki K, Yadavalli VR, Kumar AP, Prashanthi P, Sundaram RM, Neelamraju S. Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2024; 30:1145-1160. [PMID: 39100880 PMCID: PMC11291809 DOI: 10.1007/s12298-024-01483-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 06/14/2024] [Accepted: 06/28/2024] [Indexed: 08/06/2024]
Abstract
Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-024-01483-0.
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Affiliation(s)
- Malathi Surapaneni
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | - Divya Balakrishnan
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | - Krishnamraju Addanki
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | | | - Arun Prem Kumar
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | - P. Prashanthi
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | - R. M. Sundaram
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
| | - Sarla Neelamraju
- ICAR-Indian Institute of Rice Research (ICAR-IIRR), Rajendranagar, Hyderabad, Telangana 500 030 India
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Sah RP, Nayak AK, Chandrappa A, Behera S, Azharudheen Tp M, Lavanya GR. cgSSR marker-based genome-wide association study identified genomic regions for panicle characters and yield in rice (Oryza sativa L.). JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:720-728. [PMID: 36054367 DOI: 10.1002/jsfa.12183] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/03/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND To improve production efficiency, positive alleles corresponding to yield-related attributes must be accumulated in a single elite background. We designed and used cgSSR markers, which are superior to random SSR markers in genome-wide association study, to identify genomic regions that contribute to panicle characters and grain yield in this study. RESULTS As evidenced by the high polymorphic information content value and gene diversity coefficient, the new cgSSR markers were determined to be highly informative. These cgSSR markers were employed to generate genotype data for an association panel evaluated for four panicle characters and grain yield over three seasons. For five traits, 17 significant marker-trait associations on six chromosomes were discovered. The percentage of phenotypic variance that could be explained ranged from 4% to 13%. Unrelated gene-derived markers had a strong association with target traits as well. CONCLUSION Trait-associated cgSSR markers derived from corresponding or related genes ensure their utility in direct allele selection, while other linked markers aid in allele selection indirectly by altering the phenotype of interest. Through a marker-assisted breeding approach, these marker-trait associations can be leveraged to accumulate favourable alleles for yield enhancement in rice. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Rameswar Prasad Sah
- Crop Improvement Division, ICAR - National Rice Research Institute, Cuttack, India
| | - Amrit Kumar Nayak
- Department of Genetics and Plant breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Prayagraj, India
| | - Anilkumar Chandrappa
- Crop Improvement Division, ICAR - National Rice Research Institute, Cuttack, India
| | - Sasmita Behera
- Crop Improvement Division, ICAR - National Rice Research Institute, Cuttack, India
| | | | - G Roopa Lavanya
- Department of Genetics and Plant breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences (SHUATS), Prayagraj, India
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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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Hu G, Wang B, Gong T, Li R, Guo X, Liu W, Yang Z, Liu C, Li WX, Ning H. Mapping additive and epistatic QTLs for forage quality and yield in soybean [ Glycine max (L.) Merri.] in two environments. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1932593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
Affiliation(s)
- Guofu Hu
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Bo Wang
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Ting Gong
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Ran Li
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Xin Guo
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Wei Liu
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Zouzhuan Yang
- Department of Pratacultural Science, Institute of Animal Science and Technology, Northeast Agricultural University, Harbin, PR China
| | - Chunyan Liu
- Heilongjiang Provincial Government Big Data Center, Harbin, PR China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Soybean Research Institute, Northeast Agricultural University, Harbin, PR China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Soybean Research Institute, Northeast Agricultural University, Harbin, PR China
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