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Mbebi AJ, Mercado F, Hobby D, Tong H, Nikoloski Z. Advances in multi-trait genomic prediction approaches: classification, comparative analysis, and perspectives. Brief Bioinform 2025; 26:bbaf211. [PMID: 40358423 PMCID: PMC12070487 DOI: 10.1093/bib/bbaf211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2025] [Revised: 03/24/2025] [Accepted: 04/20/2025] [Indexed: 05/15/2025] Open
Abstract
Traits in any organism are not independent, but show considerable integration, observed in a form of couplings and trade-offs. Therefore, improvement in one trait may affect other traits, often in undesired direction. To account for this problem, crop breeding increasingly relies on multi-trait genomic prediction (MT-GP) approaches that leverage the availability of genetic markers from different populations along with advances in high-throughput precision phenotyping. While significant progress has been made to jointly model multiple traits using a variety of statistical and machine learning approaches, there is no systematic comparison of advantages and shortcomings of the existing classes of MT-GP models. Here, we fill this knowledge gap by first classifying the existing MT-GP models and briefly summarizing their general principles, modeling assumptions, and potential limitations. We then perform an extensive comparative analysis with 10 traits measured in an Oryza sativa diversity panel using cross-validation scenarios relevant in breeding practice. Finally, we discuss directions that can enable the building of next generation MT-GP models in addressing pressing challenges in crop breeding.
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Affiliation(s)
- Alain J Mbebi
- Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam-Golm, Brandenburg, Germany
- Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Brandenburg, Germany
| | - Facundo Mercado
- Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam-Golm, Brandenburg, Germany
| | - David Hobby
- Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam-Golm, Brandenburg, Germany
| | - Hao Tong
- Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam-Golm, Brandenburg, Germany
- Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Brandenburg, Germany
| | - Zoran Nikoloski
- Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam-Golm, Brandenburg, Germany
- Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Brandenburg, Germany
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Zhang J, Wang X, Dou G, Meng D, Tang C, Lv J, Wang N, Wang X, Li J, Bao Y, Zhang G, Huang T, Shi Y. Genome-wide identification of rice CXE gene family and mining of alleles for potential application in rice improvement. FRONTIERS IN PLANT SCIENCE 2024; 15:1435420. [PMID: 39483679 PMCID: PMC11524881 DOI: 10.3389/fpls.2024.1435420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 10/01/2024] [Indexed: 11/03/2024]
Abstract
Carboxylesterases (CXE, EC 3.1.1.1), a class of hydrolases with an α/β folding domain, play important roles in plant growth and development and stress response. Here, we identified 32, 63, 41, and 45 CXE genes in Oryza sativa Japonica (Nipponbare), Oryza sativa Indica (93-11), Oryza sativa Indica (Xian-1B1 var.IR64), and Oryza sativa Japonica (Geng-sbtrp var.ChaoMeo), respectively. Then, we analyzed the chromosomal location, physical and chemical properties, subcellular localization, collinearity, and selection pressure of CXE genes in four rice varieties. We also analyzed the functional interaction network, cis-regulatory elements, evolutionary relationship, and protein tertiary structure, and performed gene expression profiling and qPCR verification under abiotic stress, as well as diversity analysis of 3010 gene-CDS-haplotype (gcHap) rice samples, aiming to understand the potential function of the 32 OsCXE genes. Our results indicated that fragment replication is the main reason for amplification of the CXE gene family in rice, and the gene family has undergone strong purification selection. OsCXE3.1, OsCXE3.2, OsCXE3.3, OsCXE5.1, and OsCXE7.3 may be used to improve the tolerance of rice to abiotic stress. OsCXE play important roles in rice population differentiation and improvement, and the major gcHaps at most OsCXE locus are significantly associated with yield traits. Therefore, natural variations of most OsCXE locus have great potential value for improvement of rice productivity.
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Affiliation(s)
- Jinguo Zhang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Xinchen Wang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Guohui Dou
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Dezhuang Meng
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Chenghang Tang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Jiaqi Lv
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Nansheng Wang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Xingmeng Wang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Jianfeng Li
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Yaling Bao
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Guogeng Zhang
- School of Agronomy, Anhui Agricultural University, Hefei, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tao Huang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Yingyao Shi
- School of Agronomy, Anhui Agricultural University, Hefei, China
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Zhang J, Meng D, Li J, Bao Y, Yu P, Dou G, Guo J, Tang C, Lv J, Wang X, Wang X, Wu F, Shi Y. Analysis of the Rice Raffinose Synthase (OsRS) Gene Family and Haplotype Diversity. Int J Mol Sci 2024; 25:9815. [PMID: 39337301 PMCID: PMC11432550 DOI: 10.3390/ijms25189815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 09/03/2024] [Accepted: 09/09/2024] [Indexed: 09/30/2024] Open
Abstract
Based on the genome information of rice (Nipponbare), this study screened and identified six raffinose synthase (RS) genes and analyzed their physical and chemical properties, phylogenetic relationship, conserved domains, promoter cis-acting elements, and the function and genetic diversity of the gene-CDS-haplotype (gcHap). The results showed that these genes play key roles in abiotic stress response, such as OsRS5, whose expression in leaves changed significantly under high salt, drought, ABA, and MeJA treatments. In addition, the OsRS genes showed significant genetic variations in different rice populations. The main gcHaps of most OsRS loci had significant effects on key agronomic traits, and the frequency of these alleles varied significantly among different rice populations and subspecies. These findings provide direction for studying the RS gene family in other crops.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Yingyao Shi
- College of Agronomy, Anhui Agricultural University, Hefei 230036, China; (J.Z.); (D.M.); (J.L.); (Y.B.); (P.Y.); (G.D.); (J.G.); (C.T.); (J.L.); (X.W.); (X.W.); (F.W.)
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Zheng X, Yuan Z, Yu Y, Yu S, He H. OsCSD2 and OsCSD3 Enhance Seed Storability by Modulating Antioxidant Enzymes and Abscisic Acid in Rice. PLANTS (BASEL, SWITZERLAND) 2024; 13:310. [PMID: 38276765 PMCID: PMC10818270 DOI: 10.3390/plants13020310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 01/13/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024]
Abstract
Seed deterioration during storage poses a significant challenge to rice production, leading to a drastic decline in both edible quality and viability, thereby impacting overall crop yield. This study aimed to address this issue by further investigating candidate genes associated with two previously identified QTLs for seed storability through genome association analysis. Among the screened genes, two superoxide dismutase (SOD) genes, OsCSD2 (Copper/zinc Superoxide Dismutase 2) and OsCSD3, were selected for further study. The generation of overexpression and CRISPR/Cas9 mutant transgenic lines revealed that OsCSD2 and OsCSD3 play a positive regulatory role in enhancing rice seed storability. Subsequent exploration of the physiological mechanisms demonstrated that overexpression lines exhibited lower relative electrical conductivity, indicative of reduced cell membrane damage, while knockout lines displayed the opposite trend. Furthermore, the overexpression lines of OsCSD2 and OsCSD3 showed significant increases not only in SOD but also in CAT and POD activities, highlighting an augmented antioxidant system in the transgenic seeds. Additionally, hormone profiling indicated that ABA contributed to the improved seed storability observed in these lines. In summary, these findings provide valuable insights into the regulatory mechanisms of OsCSDs in rice storability, with potential applications for mitigating grain loss and enhancing global food security.
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Affiliation(s)
- Xiaohai Zheng
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (X.Z.); (Z.Y.); (Y.Y.); (S.Y.)
| | - Zhiyang Yuan
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (X.Z.); (Z.Y.); (Y.Y.); (S.Y.)
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuye Yu
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (X.Z.); (Z.Y.); (Y.Y.); (S.Y.)
- Beijing Bio Huaxing Gene Technology Co., Ltd., Beijing 102260, China
| | - Sibin Yu
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (X.Z.); (Z.Y.); (Y.Y.); (S.Y.)
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Hanzi He
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (X.Z.); (Z.Y.); (Y.Y.); (S.Y.)
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
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Wang X, Wu F, Zhang J, Bao Y, Wang N, Dou G, Meng D, Wang X, Li J, Shi Y. Identification of the CNGC Gene Family in Rice and Mining of Alleles for Application in Rice Improvement. PLANTS (BASEL, SWITZERLAND) 2023; 12:4089. [PMID: 38140416 PMCID: PMC10747058 DOI: 10.3390/plants12244089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/02/2023] [Accepted: 12/05/2023] [Indexed: 12/24/2023]
Abstract
Cyclic nucleotide-gated ion channel (CNGC) gene regulation plays important roles in plant immune and abiotic stress response. Here, we identified 16 CNGC genes in rice (Oryza sativa). Then, we analyzed their chromosomal location, physicochemical properties, subcellular localization, gene functional interaction network, cis-acting elements, phylogenetic relationships, collinearity, expression in tissues under normal conditions and abiotic stresses, and geng-cds-haplotype (gcHap) diversity in 3010 gcHaps. As a result, OsCNGC3 (Os06g0527300) was identified as a gene different from previous report, and OsCNGC genes were found to play important roles in rice population differentiation and rice improvement. Our results revealed their very strong differentiation between subspecies and populations, important roles in response to abiotic stresses, as well as strong genetic bottleneck effects and artificial selection of gcHap diversity in the modern breeding process of Xian (indica) and Geng (japonica) populations. The results also suggested that natural variations in most rice CNGC loci are potentially valuable for improving rice productivity and tolerance to abiotic stresses. The favorable alleles at the CNGC loci should be explored to facilitate their application in future rice improvement.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Yingyao Shi
- College of Agronomy, Anhui Agricultural University, Hefei 230036, China; (X.W.); (F.W.); (J.Z.); (Y.B.); (N.W.); (G.D.); (D.M.) (X.W.); (J.L.)
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Xia H, Pu X, Zhu X, Yang X, Guo H, Diao H, Zhang Q, Wang Y, Sun X, Zhang H, Zhang Z, Zeng Y, Li Z. Genome-Wide Association Study Reveals the Genetic Basis of Total Flavonoid Content in Brown Rice. Genes (Basel) 2023; 14:1684. [PMID: 37761824 PMCID: PMC10531027 DOI: 10.3390/genes14091684] [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: 07/22/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/29/2023] Open
Abstract
Flavonoids have anti-inflammatory, antioxidative, and anticarcinogenic effects. Breeding rice varieties rich in flavonoids can prevent chronic diseases such as cancer and cardio-cerebrovascular diseases. However, most of the genes reported are known to regulate flavonoid content in leaves or seedlings. To further elucidate the genetic basis of flavonoid content in rice grains and identify germplasm rich in flavonoids in grains, a set of rice core collections containing 633 accessions from 32 countries was used to determine total flavonoid content (TFC) in brown rice. We identified ten excellent germplasms with TFC exceeding 300 mg/100 g. Using a compressed mixed linear model, a total of 53 quantitative trait loci (QTLs) were detected through a genome-wide association study (GWAS). By combining linkage disequilibrium (LD) analysis, location of significant single nucleotide polymorphisms (SNPs), gene expression, and haplotype analysis, eight candidate genes were identified from two important QTLs (qTFC1-6 and qTFC9-7), among which LOC_Os01g59440 and LOC_Os09g24260 are the most likely candidate genes. We also analyzed the geographic distribution and breeding utilization of favorable haplotypes of the two genes. Our findings provide insights into the genetic basis of TFC in brown rice and could facilitate the breeding of flavonoid-rich varieties, which may be a prevention and adjuvant treatment for cancer and cardio-cerebrovascular diseases.
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Affiliation(s)
- Haijian Xia
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Xiaoying Pu
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences/Agricultural Biotechnology Key Laboratory of Yunnan Province, Kunming 650205, China; (X.P.)
| | - Xiaoyang Zhu
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Xiaomeng Yang
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences/Agricultural Biotechnology Key Laboratory of Yunnan Province, Kunming 650205, China; (X.P.)
| | - Haifeng Guo
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Henan Diao
- Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe 164300, China
| | - Quan Zhang
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Yulong Wang
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Xingming Sun
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Hongliang Zhang
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Zhanying Zhang
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
| | - Yawen Zeng
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences/Agricultural Biotechnology Key Laboratory of Yunnan Province, Kunming 650205, China; (X.P.)
| | - Zichao Li
- Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China; (H.X.)
- Sanya Institute, China Agricultural University, Sanya 572025, China
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Zhu X, Chen L, Zhang Z, Li J, Zhang H, Li Z, Pan Y, Wang X. Genetic-based dissection of resistance to bacterial leaf streak in rice by GWAS. BMC PLANT BIOLOGY 2023; 23:396. [PMID: 37596557 PMCID: PMC10436437 DOI: 10.1186/s12870-023-04412-7] [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: 06/28/2023] [Accepted: 08/14/2023] [Indexed: 08/20/2023]
Abstract
BACKGROUND Rice is the second-largest food crop in the world and vulnerable to bacterial leaf streak disease. A thorough comprehension of the genetic foundation of agronomic traits was essential for effective implementation of molecular marker-assisted selection. RESULTS Our study aimed to evaluate the vulnerability of rice to bacterial leaf streak disease (BLS) induced by the gram-negative bacterium Xanthomonas oryzae pv. oryzicola (Xoc). In order to accomplish this, we first analyzed the population structure of 747 accessions and subsequently assessed their phenotypes 20 days after inoculation with a strain of Xoc, GX01. We conducted genome-wide association studies (GWAS) on a population of 747 rice accessions, consisting of both indica and japonica subpopulations, utilizing phenotypic data on resistance to bacterial leaf streak (RBLS) and sequence data. We identified a total of 20 QTLs associated with RBLS in our analysis. Through the integration of linkage mapping, sequence analysis, haplotype analysis, and transcriptome analysis, we were able to identify five potential candidate genes (OsRBLS1-OsRBLS5) that possess the potential to regulate RBLS in rice. In order to gain a more comprehensive understanding of the genetic mechanism behind resistance to bacterial leaf streak, we conducted tests on these genes in both the indica and japonica subpopulations, ultimately identifying superior haplotypes that suggest the potential utilization of these genes in breeding disease-resistant rice varieties. CONCLUSIONS The findings of our study broaden our comprehension of the genetic mechanisms underlying RBLS in rice and offer significant insights that can be applied towards genetic improvement and breeding of disease-resistant rice in rapidly evolving environmental conditions.
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Affiliation(s)
- Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Lei Chen
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572025, People's Republic of China
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007, China
| | - Zhanying Zhang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Yinghua Pan
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572025, People's Republic of China.
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, 530007, China.
| | - Xueqiang Wang
- Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572025, People's Republic of China.
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, China.
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Zhang Q, Xie J, Zhu X, Ma X, Yang T, Khan NU, Zhang S, Liu M, Li L, Liang Y, Pan Y, Li D, Li J, Li Z, Zhang H, Zhang Z. Natural variation in Tiller Number 1 affects its interaction with TIF1 to regulate tillering in rice. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:1044-1057. [PMID: 36705337 PMCID: PMC10106862 DOI: 10.1111/pbi.14017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 12/15/2022] [Accepted: 01/23/2023] [Indexed: 05/04/2023]
Abstract
Tiller number per plant-a cardinal component of ideal plant architecture-affects grain yield potential. Thus, alleles positively affecting tillering must be mined to promote genetic improvement. Here, we report a Tiller Number 1 (TN1) protein harbouring a bromo-adjacent homology domain and RNA recognition motifs, identified through genome-wide association study of tiller numbers. Natural variation in TN1 affects its interaction with TIF1 (TN1 interaction factor 1) to affect DWARF14 expression and negatively regulate tiller number in rice. Further analysis of variations in TN1 among indica genotypes according to geographical distribution revealed that low-tillering varieties with TN1-hapL are concentrated in Southeast Asia and East Asia, whereas high-tillering varieties with TN1-hapH are concentrated in South Asia. Taken together, these results indicate that TN1 is a tillering regulatory factor whose alleles present apparent preferential utilization across geographical regions. Our findings advance the molecular understanding of tiller development.
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Affiliation(s)
- Quan Zhang
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Jianyin Xie
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Xiaoyang Zhu
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Xiaoqian Ma
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Tao Yang
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Najeeb Ullah Khan
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Shuyang Zhang
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Miaosong Liu
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Lin Li
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Yuntao Liang
- Guangxi Key Laboratory of Rice Genetics and BreedingRice Research Institute of Guangxi Academy of Agricultural SciencesNanningGuangxiChina
| | - Yinghua Pan
- Guangxi Key Laboratory of Rice Genetics and BreedingRice Research Institute of Guangxi Academy of Agricultural SciencesNanningGuangxiChina
| | - Danting Li
- Guangxi Key Laboratory of Rice Genetics and BreedingRice Research Institute of Guangxi Academy of Agricultural SciencesNanningGuangxiChina
| | - Jinjie Li
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Zichao Li
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
- Sanya Institute of China Agricultural UniversitySanyaChina
| | - Hongliang Zhang
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
- Sanya Institute of China Agricultural UniversitySanyaChina
- Sanya Nanfan Research Institute of Hainan UniversitySanyaChina
| | - Zhanying Zhang
- MOE Key Laboratory of Crop Heterosis and Utilization/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
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Assessment of allelic and genetic diversity, and population structure among farmers' rice varieties using microsatellite markers and morphological traits. GENE REPORTS 2022. [DOI: 10.1016/j.genrep.2022.101719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
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Wang X, Wang W, Tai S, Li M, Gao Q, Hu Z, Hu W, Wu Z, Zhu X, Xie J, Li F, Zhang Z, Zhi L, Zhang F, Ma X, Yang M, Xu J, Li Y, Zhang W, Yang X, Chen Y, Zhao Y, Fu B, Zhao X, Li J, Wang M, Yue Z, Fang X, Zeng W, Yin Y, Zhang G, Xu J, Zhang H, Li Z, Li Z. Selective and comparative genome architecture of Asian cultivated rice (Oryza sativa L.) attributed to domestication and modern breeding. J Adv Res 2022; 42:1-16. [PMID: 35988902 PMCID: PMC9788959 DOI: 10.1016/j.jare.2022.08.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 07/28/2022] [Accepted: 08/07/2022] [Indexed: 12/27/2022] Open
Abstract
INTRODUCTION Rice, Oryza sativa L. (Os), is one of the oldest domesticated cereals that has also gone through extensive improvement in modern breeding. OBJECTIVES How rice was domesticated and impacted by modern breeding. METHODS We performed comprehensive analyses of genomic sequences of 504 accessions of Os and 456 accessions of O. rufipogon/O. nivara (Or). RESULTS The natural selection on Or before domestication and the natural and artificial selection during domestication together shaped the well-differentiated genomes of two subspecies, geng(j) (japonica) and xian(i) (indica), while breeding has made apparent genomic imprints between landrace and modern varieties of each subspecies, and also between primary modern and advanced modern varieties of xian(i). Selection during domestication and breeding left genome-wide selective signals covering ∼ 22.8 % and ∼ 8.6 % of the Os genome, significantly reduced within-population genomic diversity by ∼ 22 % in xian(i) and ∼ 53 % in geng(j) plus more pronounced subspecific differentiation. Only ∼ 10 % reduction in the total genomic diversity was observed between the Os and Or populations, indicating domestication did not suffer severe genetic bottleneck. CONCLUSION Our results revealed clear differentiation of the Or accessions into three large populations, two of which correspond to the well-differentiated Os subspecies, geng(j) and xian(i). Improved productivity and common changes in the same suit of adaptive traits in xian(i) and geng(j) during domestication and breeding resulted apparently from compensatory and convergent selections for different genes/alleles acting in the common KEGG terms and/or same gene families, and thus maintaining or even increasing the within population diversity and subspecific differentiation of Os, while more genes/alleles of novel function were selected during domestication than modern breeding. Our results supported the multiple independent domestication of Os in Asia and suggest the more efficient utilization of the rich diversity within Os by exploiting inter-subspecific and among population diversity in future rice improvement.
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Affiliation(s)
- Xueqiang Wang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China,Institute of Crop Science, Plant Precision Breeding Academy, Zhejiang Provincial Key Laboratory of Crop Genetic Resources, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China,The College of Agronomy, Anhui Agricultural University, Hefei, China
| | | | - Min Li
- The College of Agronomy, Anhui Agricultural University, Hefei, China
| | - Qiang Gao
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Zhiqiang Hu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Wushu Hu
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Zhichao Wu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Jianyin Xie
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Fengmei Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Zhifang Zhang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Linran Zhi
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Fan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China,The College of Agronomy, Anhui Agricultural University, Hefei, China
| | - Xiaoqian Ma
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Ming Yang
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Jiabao Xu
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Yanhong Li
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Wenzhuo Zhang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Xiyu Yang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Ying Chen
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100193, China
| | - Yan Zhao
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Binying Fu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xiuqin Zhao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Miao Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Zhen Yue
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | | | - Wei Zeng
- The College of Agronomy, Anhui Agricultural University, Hefei, China
| | - Ye Yin
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Gengyun Zhang
- BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China,State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen 518083, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China,Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China,Corresponding authors at: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China (Z. Li).
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China,Corresponding authors at: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China (Z. Li).
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China,The College of Agronomy, Anhui Agricultural University, Hefei, China,Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China,Corresponding authors at: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China (Z. Li).
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11
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Hassan DA, Hama-Ali EO. Evaluation of gene flow and genetic diversity in rice accessions across Kurdistan region-iraq using SSR markers. Mol Biol Rep 2022; 49:1007-1016. [PMID: 34746989 PMCID: PMC8572534 DOI: 10.1007/s11033-021-06920-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 10/30/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND In recent years, farmers have complained that the only way to obtain seeds is to select plants that show good performance under local climate conditions in the region. This study aimed to investigate the diversity of rice accessions grown in the region to build a breeding program. METHODS AND RESULTS: A total of 62 accessions of rice from farmers and research stations were collected from the Kurdistan region, including short-grain and long-grain types, for molecular genetics and diversity analysis. In this study, 37 polymorphic simple sequence repeat (SSR) markers were selected with several molecular genetics software programs. The results show that these SSR markers are very effective for this investigation, generating a total of 152 observed alleles (Na), 75.166 Effective number of alleles (Ne) and an average of 4.1 and 2.03 alleles per locus, respectively. The average polymorphic information content (PIC) per locus was recorded as 0.404. The research presented here confirms two subpopulations, japonica (C1 and C2) and indica (C3), based on molecular genetics data analysis. Analysis of molecular variance revealed that the 72% variance was due to the variation among populations and 28% within the population. CONCLUSIONS Altogether, these results indicate that there is very low gene flow. These results show the importance of the study of genetic diversity and relationships for starting breeding and improvement programs for rice in the Kurdistan region.
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Affiliation(s)
- Diyar Ahmed Hassan
- Biotechnology and Crop Science Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaymaniyah, 46001, Iraq
| | - Emad Omer Hama-Ali
- Biotechnology and Crop Science Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaymaniyah, 46001, Iraq.
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12
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Yu S, Ali J, Zhou S, Ren G, Xie H, Xu J, Yu X, Zhou F, Peng S, Ma L, Yuan D, Li Z, Chen D, Zheng R, Zhao Z, Chu C, You A, Wei Y, Zhu S, Gu Q, He G, Li S, Liu G, Liu C, Zhang C, Xiao J, Luo L, Li Z, Zhang Q. From Green Super Rice to green agriculture: Reaping the promise of functional genomics research. MOLECULAR PLANT 2022; 15:9-26. [PMID: 34883279 DOI: 10.1016/j.molp.2021.12.001] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 11/30/2021] [Accepted: 12/03/2021] [Indexed: 06/13/2023]
Abstract
Producing sufficient food with finite resources to feed the growing global population while having a smaller impact on the environment has always been a great challenge. Here, we review the concept and practices of Green Super Rice (GSR) that have led to a paradigm shift in goals for crop genetic improvement and models of food production for promoting sustainable agriculture. The momentous achievements and global deliveries of GSR have been fueled by the integration of abundant genetic resources, functional gene discoveries, and innovative breeding techniques with precise gene and whole-genome selection and efficient agronomic management to promote resource-saving, environmentally friendly crop production systems. We also provide perspectives on new horizons in genomic breeding technologies geared toward delivering green and nutritious crop varieties to further enhance the development of green agriculture and better nourish the world population.
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Affiliation(s)
- Sibin Yu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Jauhar Ali
- International Rice Research Institute, DAPO Box 7777, Metro Manila, Philippines
| | - Shaochuan Zhou
- Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Guangjun Ren
- Sichuan Academy of Agricultural Sciences, Chengdu, China
| | - Huaan Xie
- Fujian Academy of Agricultural Sciences, Fuzhou, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinqiao Yu
- Shanghai Agrobiological Gene Center, Shanghai, China
| | - Fasong Zhou
- China National Seed Group Co., Ltd, Beijing, China
| | - Shaobing Peng
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Liangyong Ma
- China National Rice Research Institute, Hangzhou, China
| | | | - Zefu Li
- Anhui Academy of Agricultural Sciences, Hefei, China
| | - Dazhou Chen
- Jiangxi Academy of Agricultural Sciences, Nanchang, China
| | | | | | - Chengcai Chu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Aiqing You
- Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Yu Wei
- Guangxi Academy of Agricultural Sciences, Nanning, China
| | - Susong Zhu
- Guizhou Academy of Agricultural Sciences, Guiyang, China
| | - Qiongyao Gu
- Yunnan Academy of Agricultural Sciences, Kunming, China
| | | | - Shigui Li
- Sichuan Agricultural University, Chengdu, China
| | - Guifu Liu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Changhua Liu
- Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Chaopu Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinghua Xiao
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Lijun Luo
- Shanghai Agrobiological Gene Center, Shanghai, China.
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China.
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13
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Zhao Y, Yin Z, Wang X, Jiang C, Aslam MM, Gao F, Pan Y, Xie J, Zhu X, Dong L, Liu Y, Zhang H, Li J, Li Z. Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice. Sci Rep 2021; 11:13769. [PMID: 34215814 PMCID: PMC8253791 DOI: 10.1038/s41598-021-93170-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 06/15/2021] [Indexed: 11/25/2022] Open
Abstract
Genetic basis and network studies underlying synergistic biomass accumulation of roots and shoots (SBA) are conducive for rational design of high-biomass rice breeding. In this study, association signals for root weight, shoot weight, and the ratio of root-to-shoot mass (R/S) were identified using 666 rice accessions by genome-wide association study, together with their sub-traits, root length, root thickness and shoot length. Most association signals for root weight and shoot weight did not show association with their sub-traits. Based on the results, we proposed a top-to-bottom model for SBA, i.e. root weight, shoot weight and R/S were determined by their highest priority in contributing to biomass in the regulatory pathway, followed by a lower priority pathway for their sub-traits. Owing to 37 enriched clusters with more than two association signals identified, the relationship among the six traits could be also involved in linkage and pleiotropy. Furthermore, a discrimination of pleiotropy and LD at sequencing level using the known gene OsPTR9 for root weight, R/S and root length was provided. The results of given moderate correlation between traits and their corresponding sub-traits, and moderate additive effects between a trait and the accumulation of excellent alleles corresponding to its sub-traits supported a bottom-to-top regulation model for SBA. This model depicted each lowest-order trait (root length, root thickness and shoot length) was determined by its own regulation loci, and competition among different traits, as well as the pleiotropy and LD. All above ensure the coordinated development of each trait and the accumulation of the total biomass, although the predominant genetic basis of SBA is still indistinguishable. The presentation of the above two models and evidence of this study shed light on dissecting the genetic architecture of SBA.
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Affiliation(s)
- Yan Zhao
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China.,State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Zhigang Yin
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Conghui Jiang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Muhammad Mahran Aslam
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Fenghua Gao
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Yinghua Pan
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute of Guangxi Academy of Agricultural Sciences, Nanning, 530007, Guangxi, People's Republic of China
| | - Jianyin Xie
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Luhao Dong
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Yanhe Liu
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, and College of Agronomy and Biotechnology , China Agricultural University, Beijing, 100193, People's Republic of China.
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14
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Measurement of Genetic Mobility Using a Transposon-Based Marker System in Sorghum. Methods Mol Biol 2021. [PMID: 33900606 DOI: 10.1007/978-1-0716-1134-0_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Transposable elements (TEs) are ubiquitous repetitive components of eukaryotic organisms that show mobility in the genome against diverse stresses. TEs contribute considerably to the size, structure, and plasticity of genomes and also play an active role in genome evolution by helping their hosts adapt to novel conditions by conferring useful characteristics. We developed a simple and rapid method for investigation of genetic mobility and diversity among TEs in combination with a target region amplification polymorphism (TE-TRAP) marker system in gamma-irradiated sorghum mutants. The TE-TRAP marker system reveals a high level of genetic diversity, which provides a useful marker resource for genetic mobility research.
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15
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Zhang F, Wang C, Li M, Cui Y, Shi Y, Wu Z, Hu Z, Wang W, Xu J, Li Z. The landscape of gene-CDS-haplotype diversity in rice: Properties, population organization, footprints of domestication and breeding, and implications for genetic improvement. MOLECULAR PLANT 2021; 14:787-804. [PMID: 33578043 DOI: 10.1016/j.molp.2021.02.003] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 01/14/2021] [Accepted: 02/04/2021] [Indexed: 05/27/2023]
Abstract
Polymorphisms within gene coding regions represent the most important part of the overall genetic diversity of rice. We characterized the gene-coding sequence-haplotype (gcHap) diversity of 45 963 rice genes in 3010 rice accessions. With an average of 226 ± 390 gcHaps per gene in rice populations, rice genes could be classified into three main categories: 12 865 conserved genes, 10 254 subspecific differentiating genes, and 22 844 remaining genes. We found that 39 218 rice genes carry >255 179 major gcHaps of potential functional importance. Most (87.5%) of the detected gcHaps were specific to subspecies or populations. The inferred proto-ancestors of local landrace populations reconstructed from conserved predominant (ancient) gcHaps correlated strongly with wild rice accessions from the same geographic regions, supporting a multiorigin (domestication) model of Oryza sativa. Past breeding efforts generally increased the gcHap diversity of modern varieties and caused significant frequency shifts in predominant gcHaps of 14 266 genes due to independent selection in the two subspecies. Low frequencies of "favorable" gcHaps at most known genes related to rice yield in modern varieties suggest huge potential for rice improvement by mining and pyramiding of favorable gcHaps. The gcHap data were demonstrated to have greater power than SNPs for the detection of causal genes that affect complex traits. The rice gcHap diversity dataset generated in this study would facilitate rice basic research and improvement in the future.
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Affiliation(s)
- Fan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; College of Agronomy, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Chunchao Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Min Li
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Yanru Cui
- College of Agronomy, Hebei Agricultural University, Baoding, Hebei, 071001, China
| | - Yingyao Shi
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Zhichao Wu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
| | - Zhiqiang Hu
- Department of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; College of Agronomy, Anhui Agricultural University, Hefei, Anhui, 230036, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China.
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China; College of Agronomy, Anhui Agricultural University, Hefei, Anhui, 230036, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China.
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16
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Ma X, Li F, Zhang Q, Wang X, Guo H, Xie J, Zhu X, Ullah Khan N, Zhang Z, Li J, Li Z, Zhang H. Genetic architecture to cause dynamic change in tiller and panicle numbers revealed by genome-wide association study and transcriptome profile in rice. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1603-1616. [PMID: 33058400 DOI: 10.1111/tpj.15023] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 09/24/2020] [Accepted: 10/02/2020] [Indexed: 05/27/2023]
Abstract
Panicle number (PN) is one of the three yield components in rice. As one of the most unstable traits, the dynamic change in tiller number (DCTN) may determine the final PN. However, the genetic basis of DCTN and its relationship with PN remain unclear. Here, 377 deeply re-sequenced rice accessions were used to perform genome-wide association studies (GWAS) for tiller/PN. It was found that the DCTN pattern rather than maximum tiller number or effective tiller ratio is the determinant factor of high PN. The DCTN pattern that affords more panicles exhibits a period of stable tillering peak between 30 and 45 days after transplant (called DT30 and DT45, respectively), which was believed as an ideal pattern contributing to the steady transition from tiller development to panicle development (ST-TtP). Consistently, quantitative trait loci (QTL) expressed near DT30-DT45 were especially critical to the rice DCTN and in supporting the ST-TtP. The spatio-temporal expression analysis showed that the expression pattern of keeping relatively high expression in root at 24:00 (R24-P2) from about DT30 to DT45 is a typical expression pattern of cloned tiller genes, and the candidate genes with R24-P2 can facilitate the prediction of PN. Moreover, gene OsSAUR27 was identified by an integrated approach combining GWAS, bi-parental QTL mapping and transcription. These findings related to the genetic basis underlying the DCTN will provide the genetic theory in making appropriate decisions on field management, and in developing new varieties with high PN and ideal dynamic plant architecture.
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Affiliation(s)
- Xiaoqian Ma
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Fengmei Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
- School of Life Science and Technology, Xinxiang University, Henan, 453003, China
| | - Quan Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Haifeng Guo
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jianyin Xie
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Najeeb Ullah Khan
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhanying Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
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17
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Guo H, Zeng Y, Li J, Ma X, Zhang Z, Lou Q, Li J, Gu Y, Zhang H, Li J, Li Z. Differentiation, evolution and utilization of natural alleles for cold adaptability at the reproductive stage in rice. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:2491-2503. [PMID: 32490579 PMCID: PMC7680545 DOI: 10.1111/pbi.13424] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 04/28/2020] [Accepted: 05/19/2020] [Indexed: 05/16/2023]
Abstract
Genetic studies on cold tolerance at the reproductive stage in rice could lead to significant reductions in yield losses. However, knowledge about the genetic basis and adaptive differentiation, as well as the evolution and utilization of the underlying natural alleles, remains limited. Here, 580 rice accessions in two association panels were used to perform genome-wide association study, and 156 loci associated with cold tolerance at the reproductive stage were identified. Os01g0923600 and Os01g0923800 were identified as promising candidate genes in qCTB1t, a major associated locus. Through population genetic analyses, 22 and 29 divergent regions controlling cold adaptive differentiation inter-subspecies (Xian/Indica and Geng/Japonica) and intra-Geng, respectively, were identified. Joint analyses of four cloned cold-tolerance genes showed that they had different origins and utilizations under various climatic conditions. bZIP73 and OsAPX1 differentiating inter-subspecies evolved directly from wild rice, whereas the novel mutations CTB4a and Ctb1 arose in Geng during adaptation to colder climates. The cold-tolerant Geng accessions have undergone stronger selection under colder climate conditions than other accessions during the domestication and breeding processes. Additive effects of dominant allelic variants of four identified genes have been important in adaptation to cold in modern rice varieties. Therefore, this study provides valuable information for further gene discovery and pyramiding breeding to improve cold tolerance at the reproductive stage in rice.
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Affiliation(s)
- Haifeng Guo
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Yawen Zeng
- Biotechnology and Genetic Resources InstituteYunnan Academy of Agricultural SciencesKunmingChina
| | - Jilong Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
- State Key Laboratory of Systematic and Evolutionary BotanyInstitute of BotanyChinese Academy of SciencesBeijingChina
| | - Xiaoqian Ma
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Zhanying Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Qijin Lou
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Jin Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Yunsong Gu
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic ImprovementCollege of Agronomy and BiotechnologyChina Agricultural UniversityBeijingChina
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18
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Yuan J, Wang X, Zhao Y, Khan NU, Zhao Z, Zhang Y, Wen X, Tang F, Wang F, Li Z. Genetic basis and identification of candidate genes for salt tolerance in rice by GWAS. Sci Rep 2020; 10:9958. [PMID: 32561778 PMCID: PMC7305297 DOI: 10.1038/s41598-020-66604-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 04/24/2020] [Indexed: 12/29/2022] Open
Abstract
Soil salinity is a major factor affecting rice growth and productivity worldwide especially at seedling stage. Many genes for salt tolerance have been identified and applied to rice breeding, but the actual mechanism of salt tolerance remains unclear. In this study, seedlings of 664 cultivated rice varieties from the 3000 Rice Genome Project (3K-RG) were cultivated by hydroponic culture with 0.9% salt solution for trait identification. A genome-wide association study (GWAS) of salt tolerance was performed using different models of analysis. Twenty-one QTLs were identified and two candidate genes named OsSTL1 (Oryza sativa salt tolerance level 1) and OsSTL2 (Oryza sativa salt tolerance level 2) were confirmed using sequence analysis. Haplotype and sequence analysis revealed that gene OsSTL1 was a homolog of salt tolerance gene SRP1 (Stress associated RNA-binding protein 1) in Arabidopsis. The hap1 of OsSTL1 was identified as the superior haplotype and a non-synonymous SNP was most likely to be the functional site. We also determined that the level of salt tolerance was improved by combining haplotypes of different genes. Our study provides a foundation for molecular breeding and functional analysis of salt tolerance in rice seedlings.
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Affiliation(s)
- Jie Yuan
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.,Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yan Zhao
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Najeeb Ullah Khan
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhiqiang Zhao
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Yanhong Zhang
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xiaorong Wen
- Rice Experiment Stations in WenSu, Xinjiang Academy of Agricultural Sciences, Aksu, 843000, China
| | - Fusen Tang
- Rice Experiment Stations in WenSu, Xinjiang Academy of Agricultural Sciences, Aksu, 843000, China
| | - Fengbin Wang
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
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19
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Yuan J, Wang X, Zhao Y, Khan NU, Zhao Z, Zhang Y, Wen X, Tang F, Wang F, Li Z. Genetic basis and identification of candidate genes for salt tolerance in rice by GWAS. Sci Rep 2020. [PMID: 32561778 DOI: 10.1038/s41598-020-66604-66607] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023] Open
Abstract
Soil salinity is a major factor affecting rice growth and productivity worldwide especially at seedling stage. Many genes for salt tolerance have been identified and applied to rice breeding, but the actual mechanism of salt tolerance remains unclear. In this study, seedlings of 664 cultivated rice varieties from the 3000 Rice Genome Project (3K-RG) were cultivated by hydroponic culture with 0.9% salt solution for trait identification. A genome-wide association study (GWAS) of salt tolerance was performed using different models of analysis. Twenty-one QTLs were identified and two candidate genes named OsSTL1 (Oryza sativa salt tolerance level 1) and OsSTL2 (Oryza sativa salt tolerance level 2) were confirmed using sequence analysis. Haplotype and sequence analysis revealed that gene OsSTL1 was a homolog of salt tolerance gene SRP1 (Stress associated RNA-binding protein 1) in Arabidopsis. The hap1 of OsSTL1 was identified as the superior haplotype and a non-synonymous SNP was most likely to be the functional site. We also determined that the level of salt tolerance was improved by combining haplotypes of different genes. Our study provides a foundation for molecular breeding and functional analysis of salt tolerance in rice seedlings.
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Affiliation(s)
- Jie Yuan
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yan Zhao
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Najeeb Ullah Khan
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhiqiang Zhao
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Yanhong Zhang
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China
| | - Xiaorong Wen
- Rice Experiment Stations in WenSu, Xinjiang Academy of Agricultural Sciences, Aksu, 843000, China
| | - Fusen Tang
- Rice Experiment Stations in WenSu, Xinjiang Academy of Agricultural Sciences, Aksu, 843000, China
| | - Fengbin Wang
- Institute of Nuclear and Biological Technologies, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology / Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
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20
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Effect of multi-allele combination on rice grain size based on prediction of regression equation model. Mol Genet Genomics 2019; 295:465-474. [PMID: 31863176 DOI: 10.1007/s00438-019-01627-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 11/20/2019] [Indexed: 10/25/2022]
Abstract
Rice yield potential is partially affected by grain size and weight, which associates with a great number of genes and QTLs. However, it is still unclear that how multiple alleles in different genes take a combined effect on grain shape/size. Here, we investigated seven core grain size-related functional genes (GL7, GS3, GW8, GS5, TGW6, WTG1, and An-1) and observed a wide phenotypic variation for five agronomic traits (grain length, grain width, grain length-width ratio, grain thickness and thousand-grain weight) in 521 rice germplasm. The correlation analysis showed a strong association among these grain traits which have distinct impacts on determining the final rice grain size. Genotyping analysis demonstrated that a relatively small number of allele combinations were preserved in the diverse population and these allele combinations were significantly associated with differences in grain size. Furthermore, alleles were regarded as individual variables to develop the multiple regression equation. We found that B and C allelic types of GS3 and conventional type of WTG1 played relevant roles in grain size and thousand-grain weight, separately. The models would conduce to devise instructive approaches by selecting appropriate candidate alleles, which could fuel further research for breeding preferred grain shape and high-yielding crop.
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21
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Wei J, Xie W, Li R, Wang S, Qu H, Ma R, Zhou X, Jia Z. Analysis of trait heritability in functionally partitioned rice genomes. Heredity (Edinb) 2019; 124:485-498. [PMID: 31253955 DOI: 10.1038/s41437-019-0244-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Revised: 06/05/2019] [Accepted: 06/08/2019] [Indexed: 01/10/2023] Open
Abstract
Knowledge of the genetic architecture of importantly agronomical traits can speed up genetic improvement in cultivated rice (Oryza sativa L.). Many recent investigations have leveraged genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs), associated with agronomic traits in various rice populations. The reported trait-relevant SNPs appear to be arbitrarily distributed along the genome, including genic and nongenic regions. Whether the SNPs in different genomic regions play different roles in trait heritability and which region is more responsible for phenotypic variation remains opaque. We analyzed a natural rice population of 524 accessions with 3,616,597 SNPs to compare the genetic contributions of functionally distinct genomic regions for five agronomic traits, i.e., yield, heading date, plant height, grain length, and grain width. An analysis of heritability in the functionally partitioned rice genome showed that regulatory or intergenic regions account for the most trait heritability. A close look at the trait-associated SNPs (TASs) indicated that the majority of the TASs are located in nongenic regions, and the genetic effects of the TASs in nongenic regions are generally greater than those in genic regions. We further compared the predictabilities using the genetic variants from genic regions with those using nongenic regions. The results revealed that nongenic regions play a more important role than genic regions in trait heritability in rice, which is consistent with findings in humans and maize. This conclusion not only offers clues for basic research to disclose genetics behind these agronomic traits, but also provides a new perspective to facilitate genomic selection in rice.
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Affiliation(s)
- Julong Wei
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, Jiangsu, China.,Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Ruidong Li
- Department of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA
| | - Shibo Wang
- Department of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA
| | - Han Qu
- Department of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA
| | - Renyuan Ma
- Department of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.,Department of Mathematics, Bowdoin College, Brunswick, ME, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Zhenyu Jia
- Department of Botany & Plant Sciences, University of California (Riverside), Riverside, CA, USA.
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22
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Lee MK, Lyu JI, Hong MJ, Kim DG, Kim JM, Kim JB, Eom SH, Ha BK, Kwon SJ. Utility of TRAP markers to determine indel mutation frequencies induced by gamma-ray irradiation of faba bean ( Vicia faba L.) seeds. Int J Radiat Biol 2019; 95:1160-1171. [PMID: 30964373 DOI: 10.1080/09553002.2019.1605462] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Purpose: The aims were to determine the optimal gamma ray dose for faba bean (Vicia faba) and to identify genetic variation and indel mutation frequency among mutants using target region amplification polymorphism (TRAP) markers. Materials and methods: Seeds from 10 elite lines were irradiated with gamma rays (50-700 Gy), and germination, survival rate, and representative morphological traits were measured. The extent of DNA damage was investigated using comet assays, and TRAP markers were used to evaluate genetic variation, genetic diversity, and mutation frequencies. Results: Germination percentages significantly decreased at doses >100 Gy. Survival percentages and morphological traits decreased with elevation in dose. The comet assays revealed that high irradiation doses decreased head DNA levels. Phylogenetic and principal component analysis of 555 individual faba bean plants resolved eight major groups. Genetic variation between controls and mutants was limited to within groups. Mutation frequencies were associated with gamma dose in each mutant line. Conclusions: The optimal gamma dose was 100-150 Gy on the basis of survival percentage and morphological response analysis. The TRAP markers distinguished mutant lines and showed association between mutation frequency and gamma doses. This study will be useful for faba bean mutation breeding and may be applicable to other crops.
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Affiliation(s)
- Min-Kyu Lee
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea.,b Division of Plant Biotechnology, College of Agriculture and Life Sciences, Chonnam National University , Gwangju , Korea
| | - Jae Il Lyu
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea
| | - Min Jeong Hong
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea
| | - Dong-Gun Kim
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea.,c Department of Life-Resources, Graduate School, Sunchon National University , Sunchon , Korea
| | - Jung Min Kim
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea.,b Division of Plant Biotechnology, College of Agriculture and Life Sciences, Chonnam National University , Gwangju , Korea
| | - Jin-Baek Kim
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea
| | - Seok Hyun Eom
- d Department of Horticultural Biotechnology, College of Life Sciences, Kyung Hee University , Yongin , Korea
| | - Bo-Keun Ha
- b Division of Plant Biotechnology, College of Agriculture and Life Sciences, Chonnam National University , Gwangju , Korea
| | - Soon-Jae Kwon
- a Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute , Jeongeup , Korea
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23
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Yang M, Lu K, Zhao FJ, Xie W, Ramakrishna P, Wang G, Du Q, Liang L, Sun C, Zhao H, Zhang Z, Liu Z, Tian J, Huang XY, Wang W, Dong H, Hu J, Ming L, Xing Y, Wang G, Xiao J, Salt DE, Lian X. Genome-Wide Association Studies Reveal the Genetic Basis of Ionomic Variation in Rice. THE PLANT CELL 2018; 30:2720-2740. [PMID: 30373760 PMCID: PMC6305983 DOI: 10.1105/tpc.18.00375] [Citation(s) in RCA: 118] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 09/28/2018] [Accepted: 10/24/2018] [Indexed: 05/18/2023]
Abstract
Rice (Oryza sativa) is an important dietary source of both essential micronutrients and toxic trace elements for humans. The genetic basis underlying the variations in the mineral composition, the ionome, in rice remains largely unknown. Here, we describe a comprehensive study of the genetic architecture of the variation in the rice ionome performed using genome-wide association studies (GWAS) of the concentrations of 17 mineral elements in rice grain from a diverse panel of 529 accessions, each genotyped at ∼6.4 million single nucleotide polymorphism loci. We identified 72 loci associated with natural ionomic variations, 32 that are common across locations and 40 that are common within a single location. We identified candidate genes for 42 loci and provide evidence for the causal nature of three genes, the sodium transporter gene Os-HKT1;5 for sodium, Os-MOLYBDATE TRANSPORTER1;1 for molybdenum, and Grain number, plant height, and heading date7 for nitrogen. Comparison of GWAS data from rice versus Arabidopsis (Arabidopsis thaliana) also identified well-known as well as new candidates with potential for further characterization. Our study provides crucial insights into the genetic basis of ionomic variations in rice and serves as an important foundation for further studies on the genetic and molecular mechanisms controlling the rice ionome.
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Affiliation(s)
- Meng Yang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Kai Lu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
- Center of Applied Biotechnology, Wuhan Institute of Bioengineering, Wuhan 430415, China
| | - Fang-Jie Zhao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Priya Ramakrishna
- Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom
| | - Guangyuan Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Qingqing Du
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Limin Liang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Cuiju Sun
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Hu Zhao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Zhanyi Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Zonghao Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jingjing Tian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xin-Yuan Huang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
| | - Wensheng Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Huaxia Dong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jintao Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Luchang Ming
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jinhua Xiao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - David E Salt
- Centre for Plant Integrative Biology, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
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24
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Liang Y, Meng L, Lin X, Cui Y, Pang Y, Xu J, Li Z. QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice. PLoS One 2018; 13:e0200846. [PMID: 30222760 PMCID: PMC6141068 DOI: 10.1371/journal.pone.0200846] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 05/17/2018] [Indexed: 11/18/2022] Open
Abstract
Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC2 CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.
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Affiliation(s)
- Yuntao Liang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, China
| | - Lijun Meng
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xiuyun Lin
- Rice Research Institute, Jilin Academy of Agricultural Sciences, Jilin, China
| | - Yanru Cui
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunlong Pang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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25
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Zhao Y, Zhang H, Xu J, Jiang C, Yin Z, Xiong H, Xie J, Wang X, Zhu X, Li Y, Zhao W, Rashid MAR, Li J, Wang W, Fu B, Ye G, Guo Y, Hu Z, Li Z, Li Z. Loci and natural alleles underlying robust roots and adaptive domestication of upland ecotype rice in aerobic conditions. PLoS Genet 2018; 14:e1007521. [PMID: 30096145 PMCID: PMC6086435 DOI: 10.1371/journal.pgen.1007521] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 06/27/2018] [Indexed: 12/21/2022] Open
Abstract
A robust (long and thick) root system is characteristic of upland japonica rice adapted to drought conditions. Using deep sequencing and large scale phenotyping data of 795 rice accessions and an integrated strategy combining results from high resolution mapping by GWAS and linkage mapping, comprehensive analyses of genomic, transcriptomic and haplotype data, we identified large numbers of QTLs affecting rice root length and thickness (RL and RT) and shortlisted relatively few candidate genes for many of the identified small-effect QTLs. Forty four and 97 QTL candidate genes for RL and RT were identified, and five of the RL QTL candidates were validated by T-DNA insertional mutation; all have diverse functions and are involved in root development. This work demonstrated a powerful strategy for highly efficient cloning of moderate- and small-effect QTLs that is difficult using the classical map-based cloning approach. Population analyses of the 795 accessions, 202 additional upland landraces, and 446 wild rice accessions based on random SNPs and SNPs within robust loci suggested that there could be much less diversity in robust-root candidate genes among upland japonica accessions than in other ecotypes. Further analysis of nucleotide diversity and allele frequency in the robust loci among different ecotypes and wild rice accessions showed that almost all alleles could be detected in wild rice, and pyramiding of robust-root alleles could be an important genetic characteristic of upland japonica. Given that geographical distribution of upland landraces, we suggest that during domestication of upland japonica, the strongest pyramiding of robust-root alleles makes it a unique ecotype adapted to aerobic conditions. Asian cultivated rice is well-known for its rich-within-species diversity with two major subspecies, indica and japonica and subpopulation differentiation. A robust (long and thick) root system that is characteristic of upland japonica rice represents a predominant ecotype grown under aerobic and rain-fed conditions. In this study, we identified candidate genes for root length and root thickness, and validated five root length candidates by T-DNA insertional mutations. Further analyses of an Asian cultivated and wild rice population were performed based on random SNPs and SNPs within robust loci. The findings hold promise for application in improving drought resistance and also reveal the adaptive domestication history of upland rice as a unique Asian cultivated rice ecotype.
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Affiliation(s)
- Yan Zhao
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Hongliang Zhang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Jianlong Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Shenzhen Institute for Innovative Breeding, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Conghui Jiang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Zhigang Yin
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Haiyan Xiong
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Jianyin Xie
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Xueqiang Wang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Xiaoyang Zhu
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Yang Li
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Weipeng Zhao
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Muhammad Abdul Rehman Rashid
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- University of Agriculture Faisalabad, Sub-campus Burewala-Vehari, Pakistan
| | - Jinjie Li
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Wensheng Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Binying Fu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Guoyou Ye
- Shenzhen Institute for Innovative Breeding, Chinese Academy of Agricultural Sciences, Shenzhen, China
- International Rice Research Institute, Manila, Philippines
| | - Yan Guo
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Zhiqiang Hu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhikang Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Shenzhen Institute for Innovative Breeding, Chinese Academy of Agricultural Sciences, Shenzhen, China
- * E-mail: (ZhL); (ZL)
| | - Zichao Li
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- * E-mail: (ZhL); (ZL)
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26
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Zhao Y, Zhao W, Jiang C, Wang X, Xiong H, Todorovska EG, Yin Z, Chen Y, Wang X, Xie J, Pan Y, Rashid MAR, Zhang H, Li J, Li Z. Genetic Architecture and Candidate Genes for Deep-Sowing Tolerance in Rice Revealed by Non-syn GWAS. FRONTIERS IN PLANT SCIENCE 2018; 9:332. [PMID: 29616055 PMCID: PMC5864933 DOI: 10.3389/fpls.2018.00332] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 02/28/2018] [Indexed: 05/22/2023]
Abstract
Dry direct-seeding of rice is rapidly increasing in China, but variable planting depth associated with machine sowing can lead to low seedling emergence rates. Phenotype analysis of 621 rice accessions showed that mesocotyl length (ML) was induced by deep soil covering and was important in deep-sowing tolerance in the field. Here, we performed and compared GWAS using three types of SNPs (non-synonymous SNP, non-synonymous SNPs and SNPs within promoters and 3 million randomly selected SNPs from the entire set of SNPs) and found that Non-Syn GWAS (GWAS using non-synonyomous SNP) decreased computation time and eliminated confounding by other loci relative to GWAS using randomly selected SNPs. Thirteen QTLs were finally detected, and two new major-effect genes, named OsML1 and OsML2, were identified by an integrated analysis. There were 2 and 7 non-synonymous SNPs in OsML1 and OsML2, respectively, from which 3 and 4 haplotypes were detected in cultivated rice. Combinations of superior haplotypes of OsML1 and OsML2 increased ML by up to 4 cm, representing high emergence rate (85%) in the field with 10 cm of soil cover. The studies provide key loci and naturally occurring alleles of ML that can be used in improving tolerance to dry direct-seeding.
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Affiliation(s)
- Yan Zhao
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Weipeng Zhao
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Conghui Jiang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Xiaoning Wang
- Institute of Food Crops, Hainan Academy of Agricultural Sciences, Haikou, China
| | - Huaiyang Xiong
- Institute of Food Crops, Hainan Academy of Agricultural Sciences, Haikou, China
| | | | - Zhigang Yin
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Yanfa Chen
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Xin Wang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Jianyin Xie
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Yinghua Pan
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, China
| | - Muhammad A. R. Rashid
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- Plant Breeding and Genetics Lab, University of Agriculture Faisalabad, Vehari, Pakistan
| | - Hongliang Zhang
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
| | - Jinjie Li
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- *Correspondence: Jinjie Li
| | - Zichao Li
- Key Lab of Crop Heterosis and Utilization of Ministry of Education and Beijing Key Lab of Crop Genetic Improvement, China Agricultural University, Beijing, China
- Zichao Li
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27
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Metabolome-wide association studies for agronomic traits of rice. Heredity (Edinb) 2017; 120:342-355. [PMID: 29225351 DOI: 10.1038/s41437-017-0032-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Revised: 11/06/2017] [Accepted: 11/07/2017] [Indexed: 11/09/2022] Open
Abstract
Identification of trait-associated metabolites will advance the knowledge and understanding of the biosynthetic and catabolic pathways that are relevant to the complex traits of interest. In the past, the association between metabolites (treated as quantitative traits) and genetic variants (e.g., SNPs) has been extensively studied using metabolomic quantitative trait locus (mQTL) mapping. Nevertheless, the research on the association between metabolites with agronomic traits has been inadequate. In practice, the regular approaches for QTL mapping analysis may be adopted for metabolites-phenotypes association analysis due to the similarity in data structure of these two types of researches. In the study, we compared four regular QTL mapping approaches, i.e., simple linear regression (LR), linear mixed model (LMM), Bayesian analysis with spike-slab priors (Bayes B) and least absolute shrinkage and selection operator (LASSO), by testing their performances on the analysis of metabolome-phenotype associations. Simulation studies showed that LASSO had the higher power and lower false positive rate than the other three methods. We investigated the associations of 839 metobolites with five agronomic traits in a collection of 533 rice varieties. The results implied that a total of 25 metabolites were significantly associated with five agronomic traits. Literature search and bioinformatics analysis indicated that the identified 25 metabolites are significantly involved in some growth and development processes potentially related to agronomic traits. We also explored the predictability of agronomic traits based on the 839 metabolites through cross-validation, which showed that metabolomic prediction was efficient and its application in plant breeding has been justified.
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28
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Sun W, Gao D, Xiong Y, Tang X, Xiao X, Wang C, Yu S. Hairy Leaf 6, an AP2/ERF Transcription Factor, Interacts with OsWOX3B and Regulates Trichome Formation in Rice. MOLECULAR PLANT 2017; 10:1417-1433. [PMID: 28965833 DOI: 10.1016/j.molp.2017.09.015] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 09/19/2017] [Accepted: 09/25/2017] [Indexed: 05/02/2023]
Abstract
Trichome formation has been extensively studied as a mechanistic model for epidermal cell differentiation and cell morphogenesis in plants. However, the genetic and molecular mechanisms underlying trichome formation (i.e., initiation and elongation) in rice remain largely unclear. Here, we report an AP2/ERF transcription factor, Hairy Leaf 6 (HL6), which controls trichome formation in rice. Functional analyses revealed that HL6 transcriptionally regulates trichome elongation in rice, which is dependent on functional OsWOX3B, a homeodomain-containing protein that acts as a key regulator in trichome initiation. Biochemical and molecular genetic analyses demonstrated that HL6 physically interacts with OsWOX3B, and both of them regulate the expression of some auxin-related genes during trichome formation, in which OsWOX3B likely enhances the binding ability of HL6 with one of its direct target gene, OsYUCCA5. Population genetic analysis indicated that HL6 was under negative selection during rice domestication. Taken together, our findings provide new insights into the molecular regulatory network of trichome formation in rice.
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Affiliation(s)
- Wenqiang Sun
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Dawei Gao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yin Xiong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xinxin Tang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiongfeng Xiao
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Chongrong Wang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Sibin Yu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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29
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Yu J, Xiong H, Zhu X, Zhang H, Li H, Miao J, Wang W, Tang Z, Zhang Z, Yao G, Zhang Q, Pan Y, Wang X, Rashid MAR, Li J, Gao Y, Li Z, Yang W, Fu X, Li Z. OsLG3 contributing to rice grain length and yield was mined by Ho-LAMap. BMC Biol 2017; 15:28. [PMID: 28385155 PMCID: PMC5383996 DOI: 10.1186/s12915-017-0365-7] [Citation(s) in RCA: 83] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 03/10/2017] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Most agronomic traits in rice are complex and polygenic. The identification of quantitative trait loci (QTL) for grain length is an important objective of rice genetic research and breeding programs. RESULTS Herein, we identified 99 QTL for grain length by GWAS based on approximately 10 million single nucleotide polymorphisms from 504 cultivated rice accessions (Oryza sativa L.), 13 of which were validated by four linkage populations and 92 were new loci for grain length. We scanned the Ho (observed heterozygosity per locus) index of coupled-parents of crosses mapping the same QTL, based on linkage and association mapping, and identified two new genes for grain length. We named this approach as Ho-LAMap. A simulation study of six known genes showed that Ho-LAMap could mine genes rapidly across a wide range of experimental variables using deep-sequencing data. We used Ho-LAMap to clone a new gene, OsLG3, as a positive regulator of grain length, which could improve rice yield without influencing grain quality. Sequencing of the promoter region in 283 rice accessions from a wide geographic range identified four haplotypes that seem to be associated with grain length. Further analysis showed that OsLG3 alleles in the indica and japonica evolved independently from distinct ancestors and low nucleotide diversity of OsLG3 in indica indicated artificial selection. Phylogenetic analysis showed that OsLG3 might have much potential value for improvement of grain length in japonica breeding. CONCLUSIONS The results demonstrated that Ho-LAMap is a potential approach for gene discovery and OsLG3 is a promising gene to be utilized in genomic assisted breeding for rice cultivar improvement.
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Affiliation(s)
- Jianping Yu
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Haiyan Xiong
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Xiaoyang Zhu
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Hongliang Zhang
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jinli Miao
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zuoshun Tang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Zhanying Zhang
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Guoxin Yao
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Qiang Zhang
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Yinghua Pan
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
- Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning, Guangxi, China
| | - Xin Wang
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - M A R Rashid
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Jinjie Li
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Yongming Gao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weicai Yang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Xiangdong Fu
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Zichao Li
- Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China.
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30
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Genetic diversity of some upland and lowland rice cultivars in Bangladesh using RAPD, ISSR and SSR markers. THE NUCLEUS 2016. [DOI: 10.1007/s13237-015-0148-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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31
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Lv Y, Guo Z, Li X, Ye H, Li X, Xiong L. New insights into the genetic basis of natural chilling and cold shock tolerance in rice by genome-wide association analysis. PLANT, CELL & ENVIRONMENT 2016; 39:556-70. [PMID: 26381647 DOI: 10.1111/pce.12635] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2015] [Revised: 09/11/2015] [Accepted: 09/12/2015] [Indexed: 05/19/2023]
Abstract
In order to understand cold adaptability and explore additional genetic resources for the cold tolerance improvement of rice, we investigated the genetic variation of 529 rice accessions under natural chilling and cold shock stress conditions at the seedling stage using genome-wide association studies; a total of 132 loci were identified. Among them, 12 loci were common for both chilling and cold shock tolerance, suggesting that rice has a distinct and overlapping genetic response and adaptation to the two stresses. Haplotype analysis of a known gene OsMYB2, which is involved in cold tolerance, revealed indica-japonica differentiation and latitude tendency for the haplotypes of this gene. By checking the subpopulation and geographical distribution of accessions with tolerance or sensitivity under these two stress conditions, we found that the chilling tolerance group, which mainly consisted of japonica accessions, has a wider latitudinal distribution than the chilling sensitivity group. We conclude that the genetic basis of natural chilling stress tolerance in rice is distinct from that of cold shock stress frequently used for low-temperature treatment in the laboratory and the cold adaptability of rice is associated with the subpopulation and latitudinal distribution.
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Affiliation(s)
- Yan Lv
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Zilong Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiaokai Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Haiyan Ye
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Xianghua Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
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32
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Wang S, Gao LZ. Complete Chloroplast Genome Sequence and Annotation of the Tropical japonica Group of Asian Cultivated Rice (Oryza sativa L.). GENOME ANNOUNCEMENTS 2016; 4:e01703-15. [PMID: 26893422 PMCID: PMC4759069 DOI: 10.1128/genomea.01703-15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Accepted: 12/18/2015] [Indexed: 11/23/2022]
Abstract
We announce here the first complete chloroplast genome sequence of the tropical japonica rice, along with its genome structure and functional annotation. The plant was collected from Indonesia and deposited as a germplasm accession of the International Rice GenBank Collection (IRGC 66630) at the International Rice Research Institute (IRRI). This genome provides valuable data for the future utilization of the germplasm of rice.
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Affiliation(s)
- Shuo Wang
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
| | - Li-Zhi Gao
- Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, China Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
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33
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Leung H, Raghavan C, Zhou B, Oliva R, Choi IR, Lacorte V, Jubay ML, Cruz CV, Gregorio G, Singh RK, Ulat VJ, Borja FN, Mauleon R, Alexandrov NN, McNally KL, Sackville Hamilton R. Allele mining and enhanced genetic recombination for rice breeding. RICE (NEW YORK, N.Y.) 2015; 8:34. [PMID: 26606925 PMCID: PMC4659784 DOI: 10.1186/s12284-015-0069-y] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Accepted: 11/20/2015] [Indexed: 05/17/2023]
Abstract
Traditional rice varieties harbour a large store of genetic diversity with potential to accelerate rice improvement. For a long time, this diversity maintained in the International Rice Genebank has not been fully used because of a lack of genome information. The publication of the first reference genome of Nipponbare by the International Rice Genome Sequencing Project (IRGSP) marked the beginning of a systematic exploration and use of rice diversity for genetic research and breeding. Since then, the Nipponbare genome has served as the reference for the assembly of many additional genomes. The recently completed 3000 Rice Genomes Project together with the public database (SNP-Seek) provides a new genomic and data resource that enables the identification of useful accessions for breeding. Using disease resistance traits as case studies, we demonstrated the power of allele mining in the 3,000 genomes for extracting accessions from the GeneBank for targeted phenotyping. Although potentially useful landraces can now be identified, their use in breeding is often hindered by unfavourable linkages. Efficient breeding designs are much needed to transfer the useful diversity to breeding. Multi-parent Advanced Generation InterCross (MAGIC) is a breeding design to produce highly recombined populations. The MAGIC approach can be used to generate pre-breeding populations with increased genotypic diversity and reduced linkage drag. Allele mining combined with a multi-parent breeding design can help convert useful diversity into breeding-ready genetic resources.
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Affiliation(s)
- Hei Leung
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines.
| | - Chitra Raghavan
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Bo Zhou
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Ricardo Oliva
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Il Ryong Choi
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Vanica Lacorte
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Mona Liza Jubay
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Casiana Vera Cruz
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Glenn Gregorio
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Rakesh Kumar Singh
- Plant Breeding Genetics and Biotechnology Division and International Rice Research Institute, Los Banos, Philippines
| | - Victor Jun Ulat
- T.T. Chang Genetic Resource Center, International Rice Research Institute, Los Banos, Philippines
| | - Frances Nikki Borja
- T.T. Chang Genetic Resource Center, International Rice Research Institute, Los Banos, Philippines
| | - Ramil Mauleon
- T.T. Chang Genetic Resource Center, International Rice Research Institute, Los Banos, Philippines
| | - Nickolai N Alexandrov
- T.T. Chang Genetic Resource Center, International Rice Research Institute, Los Banos, Philippines
| | - Kenneth L McNally
- T.T. Chang Genetic Resource Center, International Rice Research Institute, Los Banos, Philippines
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34
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Xie W, Wang G, Yuan M, Yao W, Lyu K, Zhao H, Yang M, Li P, Zhang X, Yuan J, Wang Q, Liu F, Dong H, Zhang L, Li X, Meng X, Zhang W, Xiong L, He Y, Wang S, Yu S, Xu C, Luo J, Li X, Xiao J, Lian X, Zhang Q. Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection. Proc Natl Acad Sci U S A 2015; 112:E5411-9. [PMID: 26358652 PMCID: PMC4593105 DOI: 10.1073/pnas.1515919112] [Citation(s) in RCA: 132] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Intensive rice breeding over the past 50 y has dramatically increased productivity especially in the indica subspecies, but our knowledge of the genomic changes associated with such improvement has been limited. In this study, we analyzed low-coverage sequencing data of 1,479 rice accessions from 73 countries, including landraces and modern cultivars. We identified two major subpopulations, indica I (IndI) and indica II (IndII), in the indica subspecies, which corresponded to the two putative heterotic groups resulting from independent breeding efforts. We detected 200 regions spanning 7.8% of the rice genome that had been differentially selected between IndI and IndII, and thus referred to as breeding signatures. These regions included large numbers of known functional genes and loci associated with important agronomic traits revealed by genome-wide association studies. Grain yield was positively correlated with the number of breeding signatures in a variety, suggesting that the number of breeding signatures in a line may be useful for predicting agronomic potential and the selected loci may provide targets for rice improvement.
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Affiliation(s)
- Weibo Xie
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Meng Yuan
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wen Yao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Kai Lyu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Hu Zhao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Meng Yang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Pingbo Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xing Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jing Yuan
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Quanxiu Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Fang Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Huaxia Dong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Lejing Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xinglei Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangzhou Meng
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wan Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yuqing He
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Shiping Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Sibin Yu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Caiguo Xu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jie Luo
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xianghua Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jinghua Xiao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
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35
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Genetic Diversity and Population Structure of Basmati Rice (Oryza sativa L.) Germplasm Collected from North Western Himalayas Using Trait Linked SSR Markers. PLoS One 2015. [PMID: 26218261 PMCID: PMC4517777 DOI: 10.1371/journal.pone.0131858] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
One hundred forty one basmati rice genotypes collected from different geographic regions of North Western Himalayas were characterized using 40 traits linked microsatellite markers. Number of alleles detected by the abovementioned primers were 112 with a maximum and minimum frequency of 5 and 2 alleles, respectively. The maximum and minimum polymorphic information content values were found to be 0.63 and 0.17 for the primers RM206 and RM213, respectively. The genetic similarity coefficient for the most number of pairs ranged between of 0.2-0.9 with the average value of 0.60 for all possible combinations, indicating moderate genetic diversity among the chosen genotypes. Phylogenetic cluster analysis of the SSR data based on distance divided all genotypes into four groups (I, II, III and IV), whereas model based clustering method divided these genotypes into five groups (A, B, C, D and E). However, the result from both the analysis are in well agreement with each other for clustering on the basis of place of collection and geographic region, except the local basmati genotypes which clustered into three subpopulations in structure analysis comparison to two clusters in distance based clustering. The diverse genotypes and polymorphic trait linked microsatellites markers in the present study will be used for the identification of quantitative trait loci/genes for different economically important traits to be utilized in molecular breeding programme of rice in the future.
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Wang Q, Xie W, Xing H, Yan J, Meng X, Li X, Fu X, Xu J, Lian X, Yu S, Xing Y, Wang G. Genetic Architecture of Natural Variation in Rice Chlorophyll Content Revealed by a Genome-Wide Association Study. MOLECULAR PLANT 2015; 8:946-57. [PMID: 25747843 DOI: 10.1016/j.molp.2015.02.014] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2014] [Revised: 01/24/2015] [Accepted: 02/25/2015] [Indexed: 05/21/2023]
Abstract
Chlorophyll content is one of the most important physiological traits as it is closely related to leaf photosynthesis and crop yield potential. So far, few genes have been reported to be involved in natural variation of chlorophyll content in rice (Oryza sativa) and the extent of variations explored is very limited. We conducted a genome-wide association study (GWAS) using a diverse worldwide collection of 529 O. sativa accessions. A total of 46 significant association loci were identified. Three F2 mapping populations with parents selected from the association panel were tested for validation of GWAS signals. We clearly demonstrated that Grain number, plant height, and heading date7 (Ghd7) was a major locus for natural variation of chlorophyll content at the heading stage by combining evidence from near-isogenic lines and transgenic plants. The enhanced expression of Ghd7 decreased the chlorophyll content, mainly through down-regulating the expression of genes involved in the biosynthesis of chlorophyll and chloroplast. In addition, Narrow leaf1 (NAL1) corresponded to one significant association region repeatedly detected over two years. We revealed a high degree of polymorphism in the 5' UTR and four non-synonymous SNPs in the coding region of NAL1, and observed diverse effects of the major haplotypes. The loci or candidate genes identified would help to fine-tune and optimize the antenna size of canopies in rice breeding.
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Affiliation(s)
- Quanxiu Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Hongkun Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Ju Yan
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangzhou Meng
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xinglei Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangkui Fu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jiuyue Xu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Sibin Yu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China.
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Zhao H, Yao W, Ouyang Y, Yang W, Wang G, Lian X, Xing Y, Chen L, Xie W. RiceVarMap: a comprehensive database of rice genomic variations. Nucleic Acids Res 2014; 43:D1018-22. [PMID: 25274737 PMCID: PMC4384008 DOI: 10.1093/nar/gku894] [Citation(s) in RCA: 208] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Rice Variation Map (RiceVarMap, http:/ricevarmap.ncpgr.cn) is a database of rice genomic variations. The database provides comprehensive information of 6 551 358 single nucleotide polymorphisms (SNPs) and 1 214 627 insertions/deletions (INDELs) identified from sequencing data of 1479 rice accessions. The SNP genotypes of all accessions were imputed and evaluated, resulting in an overall missing data rate of 0.42% and an estimated accuracy greater than 99%. The SNP/INDEL genotypes of all accessions are available for online query and download. Users can search SNPs/INDELs by identifiers of the SNPs/INDELs, genomic regions, gene identifiers and keywords of gene annotation. Allele frequencies within various subpopulations and the effects of the variation that may alter the protein sequence of a gene are also listed for each SNP/INDEL. The database also provides geographical details and phenotype images for various rice accessions. In particular, the database provides tools to construct haplotype networks and design PCR-primers by taking into account surrounding known genomic variations. These data and tools are highly useful for exploring genetic variations and evolution studies of rice and other species.
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Affiliation(s)
- Hu Zhao
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wen Yao
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yidan Ouyang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wanneng Yang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Lingling Chen
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
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Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat Genet 2014; 46:714-21. [PMID: 24908251 DOI: 10.1038/ng.3007] [Citation(s) in RCA: 464] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 05/15/2014] [Indexed: 12/21/2022]
Abstract
Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.
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Abstract
Background Rice, Oryza sativa L., is the staple food for half the world’s population. By 2030, the production of rice must increase by at least 25% in order to keep up with global population growth and demand. Accelerated genetic gains in rice improvement are needed to mitigate the effects of climate change and loss of arable land, as well as to ensure a stable global food supply. Findings We resequenced a core collection of 3,000 rice accessions from 89 countries. All 3,000 genomes had an average sequencing depth of 14×, with average genome coverages and mapping rates of 94.0% and 92.5%, respectively. From our sequencing efforts, approximately 18.9 million single nucleotide polymorphisms (SNPs) in rice were discovered when aligned to the reference genome of the temperate japonica variety, Nipponbare. Phylogenetic analyses based on SNP data confirmed differentiation of the O. sativa gene pool into 5 varietal groups – indica, aus/boro, basmati/sadri, tropical japonica and temperate japonica. Conclusions Here, we report an international resequencing effort of 3,000 rice genomes. This data serves as a foundation for large-scale discovery of novel alleles for important rice phenotypes using various bioinformatics and/or genetic approaches. It also serves to understand the genomic diversity within O. sativa at a higher level of detail. With the release of the sequencing data, the project calls for the global rice community to take advantage of this data as a foundation for establishing a global, public rice genetic/genomic database and information platform for advancing rice breeding technology for future rice improvement.
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Li JY, Wang J, Zeigler RS. The 3,000 rice genomes project: new opportunities and challenges for future rice research. Gigascience 2014; 3:8. [PMID: 24872878 PMCID: PMC4035671 DOI: 10.1186/2047-217x-3-8] [Citation(s) in RCA: 179] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Accepted: 05/12/2014] [Indexed: 12/19/2023] Open
Abstract
Rice is the world's most important staple grown by millions of small-holder farmers. Sustaining rice production relies on the intelligent use of rice diversity. The 3,000 Rice Genomes Project is a giga-dataset of publically available genome sequences (averaging 14× depth of coverage) derived from 3,000 accessions of rice with global representation of genetic and functional diversity. The seed of these accessions is available from the International Rice Genebank Collection. Together, they are an unprecedented resource for advancing rice science and breeding technology. Our immediate challenge now is to comprehensively and systematically mine this dataset to link genotypic variation to functional variation with the ultimate goal of creating new and sustainable rice varieties that can support a future world population that will approach 9.6 billion by 2050.
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Affiliation(s)
- Jia-Yang Li
- Chinese Academy of Agricultural Sciences, 12 S. Zhong-Guan-Cun St, Beijing 100081, China
| | - Jun Wang
- BGI, Bei Shan Industrial Zone, Yantian District, Shenzhen 518083, China
| | - Robert S Zeigler
- International Rice Research Institute, DAPO 7777, Metro Manila 1301, Philippines
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Zhang F, Ma XF, Gao YM, Hao XB, Li ZK. Genome-wide response to selection and genetic basis of cold tolerance in rice (Oryza sativa L.). BMC Genet 2014; 15:55. [PMID: 24885138 PMCID: PMC4024214 DOI: 10.1186/1471-2156-15-55] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Accepted: 05/02/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cold stress is an important factor limiting rice yield in many areas of high latitude and altitude. Considerable efforts have been taken to genetically dissect cold tolerance (CT) in rice using DNA markers. Because of possible epistasis and gene × environment interactions associated with identified quantitative trait loci, the results of these genetic studies have unfortunately not been directly applicable to marker-assisted selection for improved rice CT. In this study, we demonstrated the utility of a selective introgression strategy for simultaneous improvement and genetic dissection of rice seedling CT. RESULTS A set of japonica introgression lines (ILs) with significantly improved seedling CT were developed from four backcross populations based on two rounds of selection. Genetic characterization of these cold-tolerant ILs revealed two important aspects of genome-wide responses to strong phenotypic selection for rice CT: (1) significant over-introgression of donor alleles at 57 loci in 29 functional genetic units (FGUs) across the rice genome and (2) pronounced non-random associations between or among alleles at many unlinked CT loci. Linkage disequilibrium analyses of the detected CT loci allowed us to construct putative genetic networks (multi-locus structures) underlying the seedling CT of rice. Each network consisted of a single FGU, with high introgression as the putative regulator plus two to three groups of highly associated downstream FGUs. A bioinformatics search of rice genomic regions harboring these putative regulators identified a small set of candidate regulatory genes that are known to be involved in plant stress response. CONCLUSIONS Our results suggest that CT in rice is controlled by multiple pathways. Genetic complementarity between parental-derived functional alleles at many loci within a given pathway provides an appropriate explanation for the commonly observed hidden diversity and transgressive segregation of CT and other complex traits in rice.
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Affiliation(s)
| | | | | | | | - Zhi-Kang Li
- Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
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Abstract
Drought is one of the most important environmental stresses affecting the productivity of most field crops. Elucidation of the complex mechanisms underlying drought resistance in crops will accelerate the development of new varieties with enhanced drought resistance. Here, we provide a brief review on the progress in genetic, genomic, and molecular studies of drought resistance in major crops. Drought resistance is regulated by numerous small-effect loci and hundreds of genes that control various morphological and physiological responses to drought. This review focuses on recent studies of genes that have been well characterized as affecting drought resistance and genes that have been successfully engineered in staple crops. We propose that one significant challenge will be to unravel the complex mechanisms of drought resistance in crops through more intensive and integrative studies in order to find key functional components or machineries that can be used as tools for engineering and breeding drought-resistant crops.
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Affiliation(s)
- Honghong Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China; ,
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Das B, Sengupta S, Parida SK, Roy B, Ghosh M, Prasad M, Ghose TK. Genetic diversity and population structure of rice landraces from Eastern and North Eastern States of India. BMC Genet 2013; 14:71. [PMID: 23945062 PMCID: PMC3765237 DOI: 10.1186/1471-2156-14-71] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2012] [Accepted: 08/12/2013] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Adaptations to different habitats across the globe and consequent genetic variation within rice have resulted in more than 120,000 diverse accessions including landraces, which are vital genetic resources for agronomic and quality traits. In India the rice landraces of the states West Bengal, Assam, Mizoram, Manipur and Nagaland are worthy candidates for genetic assessment. Keeping the above in view, the present study was conducted with the aim to (i) calculate the genetic distances among the accessions of 83 landraces collected from these states along with 8 check accessions (total 91 accessions) using 23 previously mapped SSR markers and (ii) examine the population structure among the accessions using model-based clustering approach. RESULTS Among the 91 accessions, 182 alleles were identified which included 51 rare and 27 null alleles. The average PIC value was 0.7467/marker. The non-aromatic landraces from West Bengal was most diverse with 154 alleles and an average PIC value of 0.8005/marker, followed by the aromatic landraces from West Bengal with 118 alleles and an average PIC value of 0.6524/marker, while the landraces from North East ranked third with 113 alleles and an average PIC value of 0.5745/marker. In the dendrogram distinct clusters consisting of predominantly aromatic landraces and predominantly North East Indian landraces were observed. The non-aromatic landraces from West Bengal were interspersed within these two clusters. The accessions were moderately structured, showing four sub-populations (A-D) with an Fst value of 0.398, 0.364, 0.206 and 0.281, respectively. The assigned clustering of accessions was well in agreement in both distance-based and model-based approaches. CONCLUSIONS Each of the accessions could be identified unequivocally by the SSR profiles. Genetically the non aromatic landraces from West Bengal were most diverse followed by the aromatic landraces from the same state. The North Eastern accessions ranked third. Further, grouping of accessions based on their agronomic traits may serve as a resource for future studies, leading to the improvement of rice. Moreover in-situ preservation of the landraces is also a means of protection of biodiversity and cultural heritage.
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Affiliation(s)
- Basabdatta Das
- Division of Plant Biology, Bose Institute, Main Campus, 93/1 A.P.C. Road, 700009 Kolkata, West Bengal, India
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Choudhary G, Ranjitkumar N, Surapaneni M, Deborah DA, Vipparla A, Anuradha G, Siddiq EA, Vemireddy LR. Molecular Genetic Diversity of Major Indian Rice Cultivars over Decadal Periods. PLoS One 2013; 8:e66197. [PMID: 23805204 PMCID: PMC3689748 DOI: 10.1371/journal.pone.0066197] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2012] [Accepted: 05/05/2013] [Indexed: 12/03/2022] Open
Abstract
Genetic diversity in representative sets of high yielding varieties of rice released in India between 1970 and 2010 was studied at molecular level employing hypervariable microsatellite markers. Of 64 rice SSR primer pairs studied, 52 showed polymorphism, when screened in 100 rice genotypes. A total of 184 alleles was identified averaging 3.63 alleles per locus. Cluster analysis clearly grouped the 100 genotypes into their respective decadal periods i.e., 1970s, 1980s, 1990s and 2000s. The trend of diversity over the decadal periods estimated based on the number of alleles (Na), allelic richness (Rs), Nei’s genetic diversity index (He), observed heterozygosity (Ho) and polymorphism information content (PIC) revealed increase of diversity over the periods in year of releasewise and longevitywise classification of rice varieties. Analysis of molecular variance (AMOVA) suggested more variation in within the decadal periods than among the decades. Pairwise comparison of population differentiation (Fst) among decadal periods showed significant difference between all the pairs except a few. Analysis of trends of appearing and disappearing alleles over decadal periods showed an increase in the appearance of alleles and decrease in disappearance in both the categories of varieties. It was obvious from the present findings, that genetic diversity was progressively on the rise in the varieties released during the decadal periods, between 1970s and 2000s.
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Affiliation(s)
- Gangaprasad Choudhary
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Nagireddy Ranjitkumar
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Malathi Surapaneni
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Dondapati Annekitty Deborah
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Abhilash Vipparla
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Ghanta Anuradha
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Ebrahimali Abubacker Siddiq
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
| | - Lakshminarayana Reddy Vemireddy
- Institute of Biotechnology, Acharya NG Ranga Agricultural University, Rajendranagar, Hyderabad, Andhra Pradesh, India
- * E-mail:
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Swamy BPM, Kumar A. Genomics-based precision breeding approaches to improve drought tolerance in rice. Biotechnol Adv 2013; 31:1308-18. [PMID: 23702083 DOI: 10.1016/j.biotechadv.2013.05.004] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2012] [Revised: 04/23/2013] [Accepted: 05/08/2013] [Indexed: 12/15/2022]
Abstract
Rice (Oryza sativa L.), the major staple food crop of the world, faces a severe threat from widespread drought. The development of drought-tolerant rice varieties is considered a feasible option to counteract drought stress. The screening of rice germplasm under drought and its characterization at the morphological, genetic, and molecular levels revealed the existence of genetic variation for drought tolerance within the rice gene pool. The improvements made in managed drought screening and selection for grain yield under drought have significantly contributed to progress in drought breeding programs. The availability of rice genome sequence information, genome-wide molecular markers, and low-cost genotyping platforms now makes it possible to routinely apply marker-assisted breeding approaches to improve grain yield under drought. Grain yield QTLs with a large and consistent effect under drought have been indentified and successfully pyramided in popular rice mega-varieties. Various rice functional genomics resources, databases, tools, and recent advances in "-omics" are facilitating the characterization of genes and pathways involved in drought tolerance, providing the basis for candidate gene identification and allele mining. The transgenic approach is successful in generating drought tolerance in rice under controlled conditions, but field-level testing is necessary. Genomics-assisted drought breeding approaches hold great promise, but a well-planned integration with standardized phenotyping is highly essential to exploit their full potential.
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Li ZK, Zhang F. Rice breeding in the post-genomics era: from concept to practice. CURRENT OPINION IN PLANT BIOLOGY 2013; 16:261-9. [PMID: 23571011 DOI: 10.1016/j.pbi.2013.03.008] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2013] [Revised: 03/15/2013] [Accepted: 03/16/2013] [Indexed: 05/02/2023]
Abstract
Future world food security requires continued and sustainable increase in rice production. Much of this increase has to come from new high yielding cultivars with resistances to multiple stresses. While future rice breeding in the post-genomics era has to build upon the progress in rice functional genomics research, great challenges remain in understanding the genetic/molecular systems underlying complex traits and linking the tremendous genome sequence diversity in the rice germplasm collections to the phenotypic variation of important traits. To meet the challenges in future rice improvement, a molecular breeding (MB) strategy has been practiced in China with significant progress in establishing the MB material and information platforms in the process of breeding, and in developing new varieties through two novel MB schemes. However, full implementation of this strategy requires tremendous investment to build capacities in high-throughput genotyping, reliable/precision phenotyping and in developing and adopting new genomics/genetic information-based analytic/application breeding tools, which are not in place in most of the public rice breeding institutions. Nevertheless, future advances and developments in these areas are expected to generate enormous knowledge of rice traits and application tools that enable breeders to deploy more efficient and effective breeding strategies to maximize rice productivity and resource use efficiencies in various ecosystems.
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Affiliation(s)
- Zhi-Kang Li
- Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.
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Chen H, He H, Zhou F, Yu H, Deng XW. Development of genomics-based genotyping platforms and their applications in rice breeding. CURRENT OPINION IN PLANT BIOLOGY 2013; 16:247-54. [PMID: 23706659 DOI: 10.1016/j.pbi.2013.04.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2012] [Revised: 03/29/2013] [Accepted: 04/25/2013] [Indexed: 05/26/2023]
Abstract
Breeding by design has been an aspiration of researchers in the plant sciences for a decade. With the rapid development of genomics-based genotyping platforms and available of hundreds of functional genes/alleles in related to important traits, however, it may now be possible to turn this enduring ambition into a practical reality. Rice has a relatively simple genome comparing to other crops, and its genome composition and genetic behavior have been extensively investigated. Recently, rice has been taken as a model crop to perform breeding by design. The essential process of breeding by design is to integrate functional genes/alleles in an ideal genetic background, which requires high throughput genotyping platforms to screen for expected genotypes. With large amount of genome resequencing data and high-throughput genotyping technologies available, quite a number of genomics-based genotyping platforms have been developed. These platforms are widely used in genetic mapping, integration of target traits via marker-assisted backcrossing (MABC), pyramiding, recurrent selection (MARS) or genomic selection (GS). Here, we summarize and discuss recent exciting development of rice genomics-based genotyping platforms and their applications in molecular breeding.
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Affiliation(s)
- Haodong Chen
- Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing 100871, China.
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Morphological and genetic diversity analysis of rice accessions (Oryza sativa L.) differing in iron toxicity tolerance. ACTA ACUST UNITED AC 2013. [DOI: 10.1007/s12892-012-0104-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Chakhonkaen S, Pitnjam K, Saisuk W, Ukoskit K, Muangprom A. Genetic structure of Thai rice and rice accessions obtained from the International Rice Research Institute. RICE (NEW YORK, N.Y.) 2012; 5:19. [PMID: 27234241 PMCID: PMC5520827 DOI: 10.1186/1939-8433-5-19] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Accepted: 06/13/2012] [Indexed: 05/22/2023]
Abstract
BACKGROUND Although the genetic structure of rice germplasm has been characterized worldwide, few studies investigated germplasm from Thailand, the world's largest exporter of rice. Thailand and the International Rice Research Institute (IRRI) have diverse collections of rice germplasm, which could be used to develop breeding lines with desirable traits. This study aimed to investigate the level of genetic diversity and structures of Thai and selected IRRI germplasm. Understanding the genetic structure and relationships among these germplasm will be useful for parent selection used in rice breeding programs. RESULTS From the 98 InDel markers tested for single copy and polymorphism, 19 markers were used to evaluate 43 Thai and 57 IRRI germplasm, including improved cultivars, breeding lines, landraces, and 5 other Oryza species. The Thai accessions were selected from all rice ecologies such as irrigated, deep water, upland, and rainfed lowland ecosystems. The IRRI accessions were groups of germplasm having agronomic desirable traits, including temperature-sensitive genetic male sterility (TGMS), new plant type, early flowering, and biotic and abiotic stress resistances. Most of the InDel markers were genes with diverse functions. These markers produced the total of 127 alleles for all loci, with a mean of 6.68 alleles per locus, and a mean Polymorphic Information Content (PIC) of 0.440. Genetic diversity of Thai rice were 0.3665, 0.4479 and 0.3972 for improved cultivars, breeding lines, and landraces, respectively, while genetic diversity of IRRI improved and breeding lines were 0.3272 and 0.2970, respectively. Cluster, structure, and differentiation analyses showed six distinct groups: japonica, TGMS, deep-water, IRRI germplasm, Thai landraces and breeding lines, and other Oryza species. CONCLUSIONS Thai and IRRI germplasm were significantly different. Thus, they can be used to broaden the genetic base and trait improvements. Cluster, structure, and differentiation analyses showed concordant results having six distinct groups, in agreement with their development, and ecologies.
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Affiliation(s)
- Sriprapai Chakhonkaen
- Laboratory of Plant Molecular Genetics, National Center for Genetic Engineering and Biotechnology, Pathum thani, 12120 Thailand
| | - Keasinee Pitnjam
- Laboratory of Plant Molecular Genetics, National Center for Genetic Engineering and Biotechnology, Pathum thani, 12120 Thailand
| | - Wachira Saisuk
- Department of Biotechnology, Faculty of Science and Technology, Thammasart University, Rangsit, Pathum thani, 12120 Thailand
| | - Kittipat Ukoskit
- Department of Biotechnology, Faculty of Science and Technology, Thammasart University, Rangsit, Pathum thani, 12120 Thailand
| | - Amorntip Muangprom
- Laboratory of Plant Molecular Genetics, National Center for Genetic Engineering and Biotechnology, Pathum thani, 12120 Thailand
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Chen H, He H, Zou Y, Chen W, Yu R, Liu X, Yang Y, Gao YM, Xu JL, Fan LM, Li Y, Li ZK, Deng XW. Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2011; 123:869-79. [PMID: 21681488 DOI: 10.1007/s00122-011-1633-5] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2011] [Accepted: 06/01/2011] [Indexed: 05/20/2023]
Abstract
Single nucleotide polymorphisms (SNPs) are the most abundant DNA markers in plant genomes. In this study, based on 54,465 SNPs between the genomes of two Indica varieties, Minghui 63 (MH63) and Zhenshan 97 (ZS97) and additional 20,705 SNPs between the MH63 and Nipponbare genomes, we identified and confirmed 1,633 well-distributed SNPs by PCR and Sanger sequencing. From these, a set of 372 SNPs were further selected to analyze the patterns of genetic diversity in 300 representative rice inbred lines from 22 rice growing countries worldwide. Using this set of SNPs, we were able to uncover the well-known Indica-Japonica subspecific differentiation and geographic differentiations within Indica and Japonica. Furthermore, our SNP results revealed some common and contrasting patterns of the haplotype diversity along different rice chromosomes in the Indica and Japonica accessions, which suggest different evolutionary forces possibly acting in specific regions of the rice genome during domestication and evolution of rice. Our results demonstrated that this set of SNPs can be used as anchor SNPs for large scale genotyping in rice molecular breeding research involving Indica-Japonica and Indica-Indica crosses.
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Affiliation(s)
- Haodong Chen
- Peking-Yale Joint Center for Plant Molecular Genetics and Agro-biotechnology, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, 100871 Beijing, China
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