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Yun P, Zhang C, Ma T, Xia J, Zhou K, Wang Y, Li Z. Identification of qGL4.1 and qGL4.2, two closely linked QTL controlling grain length in rice. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:11. [PMID: 38304382 PMCID: PMC10828150 DOI: 10.1007/s11032-024-01447-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 01/03/2024] [Indexed: 02/03/2024]
Abstract
Grain size is an important appearance quality trait in rice, which also affects grain yield. In this study, a recombinant inbred line (RIL) population derived from a cross between indica variety 9311 and japonica variety Cypress was constructed. And 181 out of 600 RILs were sequenced, and a high-density genetic map containing 2842 bin markers was constructed, with a total map length of 1500.6 cM. A total of 10 quantitative trait loci (QTL) related to grain length (GL), grain width (GW), grain length-to-width ratio (LWR), and 1000-grain weight (TGW) were detected under two environments. The genetic effect of qGL4, a minor QTL for GL and TGW, was validated using three heterogeneous inbred family (HIF) segregation populations. It was further dissected into two closed linked QTL, qGL4.1 and qGL4.2. By progeny testing, qGL4.1 and qGL4.2 were successfully delimited to intervals of 1304-kb and 423-kb, respectively. Our results lay the foundation for the map-based cloning of qGL4.1 and qGL4.2 and provide new gene resources for the improvement of grain yield and quality in rice. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01447-y.
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Affiliation(s)
- Peng Yun
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Caijuan Zhang
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Tingchen Ma
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Jiafa Xia
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Kunneng Zhou
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Yuanlei Wang
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Zefu Li
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
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Bhattarai G, Shi A, Mou B, Correll JC. Skim resequencing finely maps the downy mildew resistance loci RPF2 and RPF3 in spinach cultivars whale and Lazio. HORTICULTURE RESEARCH 2023; 10:uhad076. [PMID: 37323230 PMCID: PMC10261881 DOI: 10.1093/hr/uhad076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/10/2023] [Indexed: 06/17/2023]
Abstract
Commercial production of spinach (Spinacia oleracea L.) is centered in California and Arizona in the US, where downy mildew caused by Peronospora effusa is the most destructive disease. Nineteen typical races of P. effusa have been reported to infect spinach, with 16 identified after 1990. The regular appearance of new pathogen races breaks the resistance gene introgressed in spinach. We attempted to map and delineate the RPF2 locus at a finer resolution, identify linked single nucleotide polymorphism (SNP) markers, and report candidate downy mildew resistance (R) genes. Progeny populations segregating for RPF2 locus derived from resistant differential cultivar Lazio were infected using race 5 of P. effusa and were used to study for genetic transmission and mapping analysis in this study. Association analysis performed with low coverage whole genome resequencing-generated SNP markers mapped the RPF2 locus between 0.47 to 1.46 Mb of chromosome 3 with peak SNP (Chr3_1, 221, 009) showing a LOD value of 61.6 in the GLM model in TASSEL, which was within 1.08 Kb from Spo12821, a gene that encodes CC-NBS-LRR plant disease resistance protein. In addition, a combined analysis of progeny panels of Lazio and Whale segregating for RPF2 and RPF3 loci delineated the resistance section in chromosome 3 between 1.18-1.23 and 1.75-1.76 Mb. This study provides valuable information on the RPF2 resistance region in the spinach cultivar Lazio compared to RPF3 loci in the cultivar Whale. The RPF2 and RPF3 specific SNP markers, plus the resistant genes reported here, could add value to breeding efforts to develop downy mildew resistant cultivars in the future.
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Affiliation(s)
| | | | - Beiquan Mou
- USDA-ARS Crop Improvement and Protection Research Unit, Salinas, CA 93905, USA
| | - James C Correll
- Department of Plant Pathology, University of Arkansas, Fayetteville, AR 72701, USA
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3
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Liu X, Deng X, Kong W, Sun T, Li Y. The Pyramiding of Elite Allelic Genes Related to Grain Number Increases Grain Number per Panicle Using the Recombinant Lines Derived from Indica-japonica Cross in Rice. Int J Mol Sci 2023; 24:ijms24021653. [PMID: 36675168 PMCID: PMC9865901 DOI: 10.3390/ijms24021653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/08/2023] [Accepted: 01/10/2023] [Indexed: 01/19/2023] Open
Abstract
Indica(xian)-japonica(geng) hybrid rice has many heterosis traits that can improve rice yield. However, the traditional hybrid technology will struggle to meet future needs for the development of higher-yield rice. Available genomics resources can be used to efficiently understand the gene-trait association trait for rice breeding. Based on the previously constructed high-density genetic map of 272 high-generation recombinant inbred lines (RILs) originating from the cross of Luohui 9 (indica, as female) and RPY geng (japonica, as male) and high-quality genomes of parents, here, we further explore the genetic basis for an important complex trait: possible causes of grain number per panicle (GNPP). A total of 20 genes related to grains number per panicle (GNPP) with the differences of protein amino acid between LH9 and RPY were used to analyze genotype combinations, and PCA results showed a combination of PLY1, LAX1, DTH8 and OSH1 from the RPY geng with PYL4, SP1, DST and GNP1 from Luohui 9 increases GNPP. In addition, we also found that the combination of LAX1-T2 and GNP1-T3 had the most significant increase in GNPP. Notably, Molecular Breeding Knowledgebase (MBK) showed a few aggregated rice cultivars, LAX1-T2 and GNP1-T3, which may be a result of the natural geographic isolation between the two gene haplotypes. Therefore, we speculate that the pyramiding of japonica-type LAX-T2 with indica-type GNP1-T3 via hybridization can significantly improve rice yield by increasing GNPP.
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Affiliation(s)
- Xuhui Liu
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Xiaoxiao Deng
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Weilong Kong
- 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 518120, China
| | - Tong Sun
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
| | - Yangsheng Li
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, China
- Correspondence:
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Liang W, Du H, Pang B, Cheng J, He B, Hu F, Lv Y, Zhang Y. High-density genetic mapping identified QTLs for anaerobic germination tolerance in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1076600. [PMID: 36618635 PMCID: PMC9822775 DOI: 10.3389/fpls.2022.1076600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
The tolerance of rice anaerobic germination (AG) is the main limiting factor for direct seeding application, yet the genetics mechanism is still in its infancy. In the study, recombinant inbred lines population of TD70 Japonica cultivar and Kasalath Indica cultivar, was employed to construct a high-density genetic map by whole genome re-sequencing. As a result, a genetic map containing 12,328 bin-markers was constructed and a total of 50 QTLs were then detected for CL(coleoptile length), CD (coleoptile diameter), CSA (coleoptile surface area) and CV (coleoptile volume) related traits in the two stages of anaerobic treatment using complete interval mapping method (inclusive composite interval mapping, ICIM). Among the four traits associated with coleoptile, coleoptile volume had the largest number of QTLs (17), followed by coleoptile diameter (16), and coleoptile length had 5 QTLs. These QTLs could explain phenotypic contribution rates ranging from 0.34% to 11.17% and LOD values ranging from 2.52 to 11.57. Combined with transcriptome analysis, 31 candidate genes were identified. Furthermore, 12 stable QTLs were used to detect the aggregation effect analysis. Besides, It was found that individuals with more aggregation synergistic alleles had higher phenotypic values in different environments. Totally, high-density genetic map, QTL mapping and aggregation effect analysis of different loci related to the anaerobic germination of rice seeds were conducted to lay a foundation for the fine mapping of related genes in subsequent assisted breeding.
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Affiliation(s)
- Wenhua Liang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Hongyang Du
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
- Key Laboratory of Rice Genetic Breeding of Anhui Province, Rice Research Institute, Anhui Academy of Agricultural Science, Hefei, China
| | - Bingwen Pang
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Junjie Cheng
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Bing He
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Fengqin Hu
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Yuanda Lv
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Yadong Zhang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
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Liao N, Hu Z, Miao J, Hu X, Lyu X, Fang H, Zhou YM, Mahmoud A, Deng G, Meng YQ, Zhang K, Ma YY, Xia Y, Zhao M, Yang H, Zhao Y, Kang L, Wang Y, Yang JH, Zhou YH, Zhang MF, Yu JQ. Chromosome-level genome assembly of bunching onion illuminates genome evolution and flavor formation in Allium crops. Nat Commun 2022; 13:6690. [PMID: 36335132 PMCID: PMC9637129 DOI: 10.1038/s41467-022-34491-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
The Allium genus is cultivated globally as vegetables, condiments, or medicinal plants and is characterized by large genomes and strong pungency. However, the genome evolution and genomic basis underlying their unique flavor formation remain poorly understood. Herein, we report an 11.27-Gb chromosome-scale genome assembly for bunching onion (A. fistulosum). The uneven bursts of long-terminal repeats contribute to diversity in genome constituents, and dispersed duplication events largely account for gene expansion in Allium genomes. The extensive duplication and differentiation of alliinase and lachrymatory factor synthase manifest as important evolutionary events during flavor formation in Allium crops. Furthermore, differential selective preference for flavor-related genes likely lead to the variations in isoalliin content in bunching onions. Moreover, we reveal that China is the origin and domestication center for bunching onions. Our findings provide insights into Allium genome evolution, flavor formation and domestication history and enable future genome-assisted breeding of important traits in these crops.
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Affiliation(s)
- Nanqiao Liao
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Zhongyuan Hu
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Jinshan Miao
- grid.460150.60000 0004 1759 7077Horticultural Institute of Science and Technology, Weifang University of Science and Technology, 262700 Weifang, Shandong P. R. China
| | - Xiaodi Hu
- grid.410753.4Novogene Bioinformatics Institute, 100083 Beijing, P. R. China
| | - Xiaolong Lyu
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China ,grid.418524.e0000 0004 0369 6250Key Laboratory of Horticultural Plant Growth and Development, Ministry of Agriculture and Rural Affairs, 310058 Hangzhou, Zhejiang P. R. China ,grid.13402.340000 0004 1759 700XHainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, 572025 Sanya, Hainan P. R. China
| | - Haitian Fang
- grid.260987.20000 0001 2181 583XNingxia Key Laboratory for Food Microbial-applications Technology and Safety Control, School of Food & Wine, Ningxia University, 750021 Yinchuan, Ningxia P. R. China
| | - Yi-Mei Zhou
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Ahmed Mahmoud
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Guancong Deng
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Yi-Qing Meng
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Kejia Zhang
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Yu-Yuan Ma
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Yuelin Xia
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Meng Zhao
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Haiyang Yang
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China
| | - Yong Zhao
- grid.410753.4Novogene Bioinformatics Institute, 100083 Beijing, P. R. China
| | - Ling Kang
- grid.410753.4Novogene Bioinformatics Institute, 100083 Beijing, P. R. China
| | - Yiming Wang
- grid.410753.4Novogene Bioinformatics Institute, 100083 Beijing, P. R. China
| | - Jing-Hua Yang
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China ,grid.418524.e0000 0004 0369 6250Key Laboratory of Horticultural Plant Growth and Development, Ministry of Agriculture and Rural Affairs, 310058 Hangzhou, Zhejiang P. R. China ,grid.13402.340000 0004 1759 700XHainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, 572025 Sanya, Hainan P. R. China
| | - Yan-Hong Zhou
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China ,grid.418524.e0000 0004 0369 6250Key Laboratory of Horticultural Plant Growth and Development, Ministry of Agriculture and Rural Affairs, 310058 Hangzhou, Zhejiang P. R. China
| | - Ming-Fang Zhang
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China ,grid.418524.e0000 0004 0369 6250Key Laboratory of Horticultural Plant Growth and Development, Ministry of Agriculture and Rural Affairs, 310058 Hangzhou, Zhejiang P. R. China ,grid.13402.340000 0004 1759 700XHainan Institute of Zhejiang University, Yazhou Bay Science and Technology City, 572025 Sanya, Hainan P. R. China
| | - Jing-Quan Yu
- grid.13402.340000 0004 1759 700XInstitute of Vegetable Science, Zhejiang University, 310058 Hangzhou, Zhejiang P. R. China ,grid.418524.e0000 0004 0369 6250Key Laboratory of Horticultural Plant Growth and Development, Ministry of Agriculture and Rural Affairs, 310058 Hangzhou, Zhejiang P. R. China
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Profile of Dr. Qian Qian. SCIENCE CHINA. LIFE SCIENCES 2022; 65:2145-2147. [PMID: 35997918 DOI: 10.1007/s11427-022-2162-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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Bhattarai G, Olaoye D, Mou B, Correll JC, Shi A. Mapping and selection of downy mildew resistance in spinach cv. whale by low coverage whole genome sequencing. FRONTIERS IN PLANT SCIENCE 2022; 13:1012923. [PMID: 36275584 PMCID: PMC9583407 DOI: 10.3389/fpls.2022.1012923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
Spinach (Spinacia oleracea) is a popular leafy vegetable crop and commercial production is centered in California and Arizona in the US. The oomycete Peronospora effusa causes the most important disease in spinach, downy mildew. A total of nineteen races of P. effusa are known, with more than 15 documented in the last three decades, and the regular emergence of new races is continually overcoming the genetic resistance to the pathogen. This study aimed to finely map the downy mildew resistance locus RPF3 in spinach, identify single nucleotide polymorphism (SNP) markers associated with the resistance, refine the candidate genes responsible for the resistance, and evaluate the prediction performance using multiple machine learning genomic prediction (GP) methods. Segregating progeny population developed from a cross of resistant cultivar Whale and susceptible cultivar Viroflay to race 5 of P. effusa was inoculated under greenhouse conditions to determine downy mildew disease response across the panel. The progeny panel and the parents were resequenced at low coverage (1x) to identify genome wide SNP markers. Association analysis was performed using disease response phenotype data and SNP markers in TASSEL, GAPIT, and GENESIS programs and mapped the race 5 resistance loci (RPF3) to 1.25 and 2.73 Mb of Monoe-Viroflay chromosome 3 with the associated SNP in the 1.25 Mb region was 0.9 Kb from the NBS-LRR gene SOV3g001250. The RPF3 locus in the 1.22-1.23 Mb region of Sp75 chromosome 3 is 2.41-3.65 Kb from the gene Spo12821 annotated as NBS-LRR disease resistance protein. This study extended our understanding of the genetic basis of downy mildew resistance in spinach cultivar Whale and mapped the RPF3 resistance loci close to the NBS-LRR gene providing a target to pursue functional validation. Three SNP markers efficiently selected resistance based on multiple genomic selection (GS) models. The results from this study have added new genomic resources, generated an informed basis of the RPF3 locus resistant to spinach downy mildew pathogen, and developed markers and prediction methods to select resistant lines.
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Affiliation(s)
- Gehendra Bhattarai
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States
| | - Dotun Olaoye
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States
| | - Beiquan Mou
- Crop Improvement and Protection Research Unit, United States Department of Agriculture, Agricultural Research Service, Salinas, CA, United States
| | - James C. Correll
- Department of Plant Pathology, University of Arkansas, Fayetteville, AR, United States
| | - Ainong Shi
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States
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Yang Q, Liu T, Wu T, Lei T, Li Y, Wang X. GGDB: A Grameneae genome alignment database of homologous genes hierarchically related to evolutionary events. PLANT PHYSIOLOGY 2022; 190:340-351. [PMID: 35789395 PMCID: PMC9434254 DOI: 10.1093/plphys/kiac297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/01/2022] [Indexed: 06/15/2023]
Abstract
The genomes of Gramineae plants have been preferentially sequenced owing to their economic value. These genomes are often quite complex, for example harboring many duplicated genes, and are the main source of genetic innovation and often the result of recurrent polyploidization. Deciphering these complex genome structures and linking duplicated genes to specific polyploidization events are important for understanding the biology and evolution of plants. However, efforts have been hampered by the complexity of analyzing these genomes. Here, we analyzed 29 well-assembled and up-to-date Gramineae genome sequences by hierarchically relating duplicated genes in collinear regions to specific polyploidization or speciation events. We separated duplicated genes produced by each event, established lists of paralogous and orthologous genes, and ultimately constructed an online database, GGDB (http://www.grassgenome.com/). Homologous gene lists from each plant and between plants can be displayed, searched, and downloaded from the database. Interactive comparison tools are deployed to demonstrate homology among user-selected plants and to draw genome-scale or local alignment figures and gene-based phylogenetic trees corrected by exploiting gene collinearity. Using these tools and figures, users can easily detect structural changes in genomes and explore the effects of paleo-polyploidy on crop genome structure and function. The GGDB will provide a useful platform for improving our understanding of genome changes and functional innovation in Gramineae plants.
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Affiliation(s)
- Qihang Yang
- School of Life Science, North China University of Science and Technology, Tangshan, Hebei 063210, China
- Center for Genomics and Bio-computing, North China University of Science and Technology, Tangshan, Hebei 063210, China
| | - Tao Liu
- School of Life Science, North China University of Science and Technology, Tangshan, Hebei 063210, China
- College of Sciences, North China University of Science and Technology, Tangshan, Hebei 063210, China
| | - Tong Wu
- School of Life Science, North China University of Science and Technology, Tangshan, Hebei 063210, China
- Center for Genomics and Bio-computing, North China University of Science and Technology, Tangshan, Hebei 063210, China
| | - Tianyu Lei
- School of Life Science, North China University of Science and Technology, Tangshan, Hebei 063210, China
- Center for Genomics and Bio-computing, North China University of Science and Technology, Tangshan, Hebei 063210, China
| | - Yuxian Li
- School of Life Science, North China University of Science and Technology, Tangshan, Hebei 063210, China
- Center for Genomics and Bio-computing, North China University of Science and Technology, Tangshan, Hebei 063210, China
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Zhou Y, Zhang C, Zhang L, Ye Q, Liu N, Wang M, Long G, Fan W, Long M, Wing RA. Gene fusion as an important mechanism to generate new genes in the genus Oryza. Genome Biol 2022; 23:130. [PMID: 35706016 PMCID: PMC9199173 DOI: 10.1186/s13059-022-02696-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 05/30/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Events of gene fusion have been reported in several organisms. However, the general role of gene fusion as part of new gene origination remains unknown. RESULTS We conduct genome-wide interrogations of four Oryza genomes by designing and implementing novel pipelines to detect fusion genes. Based on the phylogeny of ten plant species, we detect 310 fusion genes across four Oryza species. The estimated rate of origination of fusion genes in the Oryza genus is as high as 63 fusion genes per species per million years, which is fixed at 16 fusion genes per species per million years and much higher than that in flies. By RNA sequencing analysis, we find more than 44% of the fusion genes are expressed and 90% of gene pairs show strong signals of purifying selection. Further analysis of CRISPR/Cas9 knockout lines indicates that newly formed fusion genes regulate phenotype traits including seed germination, shoot length and root length, suggesting the functional significance of these genes. CONCLUSIONS We detect new fusion genes that may drive phenotype evolution in Oryza. This study provides novel insights into the genome evolution of Oryza.
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Affiliation(s)
- Yanli Zhou
- Germplasm Bank of Wild species, Kunming Institute of Botany, Chinese Academy of Science, Kunming, Yunnan, 650201, China
| | - Chengjun Zhang
- Germplasm Bank of Wild species, Kunming Institute of Botany, Chinese Academy of Science, Kunming, Yunnan, 650201, China.
- Department of Ecology and Evolution, The University of Chicago, 1101 E. 57th Street, Chicago, IL, 60637, USA.
| | - Li Zhang
- Department of Ecology and Evolution, The University of Chicago, 1101 E. 57th Street, Chicago, IL, 60637, USA
- Chinese Institute for Brain Research, (CIBR), Beijing, 102206, China
| | - Qiannan Ye
- Germplasm Bank of Wild species, Kunming Institute of Botany, Chinese Academy of Science, Kunming, Yunnan, 650201, China
| | - Ningyawen Liu
- Germplasm Bank of Wild species, Kunming Institute of Botany, Chinese Academy of Science, Kunming, Yunnan, 650201, China
| | - Muhua Wang
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, 85721, USA
- State Key Laboratory for Biocontrol, School of Marine Sciences, Sun Yat-sen University, Zhuhai, 519000, China
| | - Guangqiang Long
- Key Laboratory of Medicinal Plant Biology of Yunnan Province, Yunnan Agricultural University, Kunming, Yunnan, 650201, China
| | - Wei Fan
- Key Laboratory of Medicinal Plant Biology of Yunnan Province, Yunnan Agricultural University, Kunming, Yunnan, 650201, China
| | - Manyuan Long
- Department of Ecology and Evolution, The University of Chicago, 1101 E. 57th Street, Chicago, IL, 60637, USA.
| | - Rod A Wing
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ, 85721, USA.
- Center for Desert Agriculture, King Abdullah University of Science & Technology, Thuwal, 23955-6900, Kingdom of Saudi Arabia.
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Singh A, Mathan J, Yadav A, K. Goyal A, Chaudhury A. Molecular and Transcriptional Regulation of Seed Development in Cereals: Present Status and Future Prospects. CEREAL GRAINS - VOLUME 1 2021. [DOI: 10.5772/intechopen.99318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
Abstract
Cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils and protein, making them the world’s most important source of nutrition. The influence of rising global population, as well as the emergence and spread of disease, has the major impact on cereal production. To meet the demand, there is a pressing need to increase cereal production. Optimal seed development is a key agronomical trait that contributes to crop yield. The seed development and maturation is a complex process that includes not only embryo and endosperm development, but also accompanied by huge physiological, biochemical, metabolic, molecular and transcriptional changes. This chapter discusses the growth of cereal seed and highlights the novel biological insights, with a focus on transgenic and new molecular breeding, as well as biotechnological intervention strategies that have improved crop yield in two major cereal crops, primarily wheat and rice, over the last 21 years (2000–2021).
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Gu Z, Zhu Z, Li Z, Zhan Q, Feng Q, Zhou C, Zhao Q, Zhao Y, Peng X, Dai B, Sun R, Li Y, Lu H, Zhang L, Huang T, Gong J, Lv D, Huang X, Han B. Cytoplasmic and nuclear genome variations of rice hybrids and their parents inform the trajectory and strategy of hybrid rice breeding. MOLECULAR PLANT 2021; 14:2056-2071. [PMID: 34390871 DOI: 10.1016/j.molp.2021.08.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 07/06/2021] [Accepted: 08/06/2021] [Indexed: 06/13/2023]
Abstract
The male sterility (MS) line is a prerequisite for efficient production of hybrid seeds in rice, a self-pollinating species. MS line breeding is pivotal for hybrid rice improvement. Understanding the historical breeding trajectory will help to improve hybrid rice breeding strategies. Maternally inherited cytoplasm is an appropriate tool for phylogenetic reconstruction and pedigree tracing in rice hybrids. In this study, we analyzed the cytoplasmic genomes of 1495 elite hybrid rice varieties and identified five major types of cytoplasm, which correspond to different hybrid production systems. As the cytoplasm donors for hybrids, 461 MS lines were also divided into five major types based on cytoplasmic and nuclear genomic architecture. Specific core accessions cooperating with different fertility-associated genes drove the sequence divergence of MS lines. Dozens to hundreds of convergent and divergent selective sweeps spanning several agronomic trait-associated genes were identified among different types of MS lines. We further analyzed the cross patterns between different types of MS lines and their corresponding restorers. This study systematically analyzed the cytoplasmic genomes of rice hybrids revealed their relationships with nuclear genomes of MS lines, and illustrated the trajectory of hybrid rice breeding and the strategies for breeding different types of MS lines providing new insights for future improvement of hybrid rice.
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Affiliation(s)
- Zhoulin Gu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhou Zhu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen Li
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; College of Life Sciences, Anhui Normal University, Wuhu, Anhui 241000, China
| | - Qilin Zhan
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Qi Feng
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Congcong Zhou
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Qiang Zhao
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Yan Zhao
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Xiaojian Peng
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; School of Life Sciences, Anhui Agricultural University, Hefei, Anhui 230036, China
| | - Bingxin Dai
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; School of Life Science and Technology, Shanghai Tech University, Shanghai 201210, China
| | - Rongrong Sun
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yan Li
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Hengyun Lu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Lei Zhang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Tao Huang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Junyi Gong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China
| | - Danfeng Lv
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Xuehui Huang
- College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Bin Han
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China.
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12
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Xing J, Zhang D, Yin F, Zhong Q, Wang B, Xiao S, Ke X, Wang L, Zhang Y, Zhao C, Lu Y, Chen L, Cheng Z, Chen L. Identification and Fine-Mapping of a New Bacterial Blight Resistance Gene, Xa47(t), in G252, an Introgression Line of Yuanjiang Common Wild Rice ( Oryza rufipogon). PLANT DISEASE 2021; 105:4106-4112. [PMID: 34261357 DOI: 10.1094/pdis-05-21-0939-re] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Bacterial blight (BB) disease caused by Xanthomonas oryzae pv. oryzae is a common, widespread, and highly devastating disease that affects rice yield. Breeding resistant cultivars is considered the most effective measure for controlling this disease. The introgression line G252 derived from Yuanjiang common wild rice (Oryza rufipogon) was highly resistant to all tested strains, including C5, C9, PXO99, PB, T7147Y8, Hzhj19, YM1, YM187, YJdp-2, and YJws-2. To identify the BB resistance gene(s) of G252, we developed an F2 population from the cross between G252 and 02428. A linkage analysis was performed for the phenotype and genotype of the population. A segregation ratio of 3:1 was observed between the resistant and susceptible individuals in the F2 progeny, indicating a dominant resistance gene, Xa47(t), in G252. The resistance gene was mapped within an approximately 26.24-kb physical region on chromosome 11 between two InDel markers, R13I14 and 13rbq-71. Moreover, one InDel marker, Hxjy-1, co-segregated with Xa47(t). Three genes were predicted within the target region, including a promising candidate gene encoding a nucleotide-binding domain and leucine-rich repeat (NLR) protein (LOC_Os11g46200) by combining the structure and expression analysis. Physical mapping data suggested that Xa47(t) is a new broad-spectrum BB resistance gene without identified allelic genes.
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Affiliation(s)
- Jiaxin Xing
- Rice Research Institute, Yunnan Agricultural University, Kunming, Yunnan 650201, P.R. China
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Dunyu Zhang
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Fuyou Yin
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Qiaofang Zhong
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Bo Wang
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Suqin Xiao
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Xue Ke
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Lingxian Wang
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Yun Zhang
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Caimei Zhao
- College of Life Science, Yunnan University, Kunming, Yunnan 650091, P.R. China
| | - Yuanda Lu
- College of Plant Protection, Yunnan Agricultural University, Kunming, Yunnan 650201, P.R. China
| | - Ling Chen
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Zaiquan Cheng
- Biotechnology and Germplasm Resources Institute, Yunnan Academy of Agricultural Sciences, Yunnan Provincial Key Lab of Agricultural Biotechnology, Key Lab of Southwestern Crop Gene Resources and Germplasm Innovation, Ministry of Agriculture, Kunming, Yunnan 650205, P.R. China
| | - Lijuan Chen
- Rice Research Institute, Yunnan Agricultural University, Kunming, Yunnan 650201, P.R. China
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13
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Iqbal Z, Iqbal MS, Khan MIR, Ansari MI. Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management. FRONTIERS IN PLANT SCIENCE 2021; 12:741419. [PMID: 34721467 PMCID: PMC8554098 DOI: 10.3389/fpls.2021.741419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 09/20/2021] [Indexed: 05/04/2023]
Abstract
Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-à-vis rice trait improvement and stress management are described.
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Affiliation(s)
- Zahra Iqbal
- Molecular Crop Research Unit, Department of Biochemistry, Chulalongkorn University, Bangkok, Thailand
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14
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Xu J, Shang L, Wang J, Chen M, Fu X, He H, Wang Z, Zeng D, Zhu L, Hu J, Zhang C, Chen G, Gao Z, Zou W, Ren D, Dong G, Shen L, Zhang Q, Li Q, Guo L, Qian Q, Zhang G. The SEEDLING BIOMASS 1 allele from indica rice enhances yield performance under low-nitrogen environments. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:1681-1683. [PMID: 34048114 PMCID: PMC8428826 DOI: 10.1111/pbi.13642] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 05/22/2021] [Indexed: 05/06/2023]
Affiliation(s)
- Jing Xu
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Lianguang Shang
- Lingnan Laboratory of Modern AgricultureGenome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Jiajia Wang
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Minmin Chen
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Xue Fu
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Huiying He
- Lingnan Laboratory of Modern AgricultureGenome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Zian Wang
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Dali Zeng
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Li Zhu
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Jiang Hu
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Chao Zhang
- Lingnan Laboratory of Modern AgricultureGenome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhenChina
| | - Guang Chen
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Zhenyu Gao
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Weiwei Zou
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Deyong Ren
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Guojun Dong
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Lan Shen
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Qiang Zhang
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Qing Li
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Longbiao Guo
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Qian Qian
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
| | - Guangheng Zhang
- State Key Laboratory of Rice BiologyChina National Rice Research InstituteHangzhouChina
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15
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Zhao J, Li H, Xu Y, Yin Y, Huang T, Zhang B, Wang Y, Li Y, Cao Y, An W. A consensus and saturated genetic map provides insight into genome anchoring, synteny of Solanaceae and leaf- and fruit-related QTLs in wolfberry (Lycium Linn.). BMC PLANT BIOLOGY 2021; 21:350. [PMID: 34303361 PMCID: PMC8306383 DOI: 10.1186/s12870-021-03115-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 06/22/2021] [Indexed: 06/02/2023]
Abstract
BACKGROUND Lycium Linn. (Solanaceae) is a genus of economically important plants producing fruits and leaves with high nutritional value and medicinal benefits. However, genetic analysis of this plant and molecular breeding for quality improvement are limited by the lack of sufficient molecular markers. RESULTS In this study, two parental strains, 'Ningqi No. 1' (Lycium barbarum L.) and 'Yunnan Gouqi' (Lycium yunnanense Kuang et A.M. Lu), and 200 F1 hybrid individuals were resequenced for genetic analysis. In total, 8,507 well-selected SNPs were developed, and a high-density genetic map (NY map) was constructed with a total genetic distance of 2,122.24 cM. A consensus genetic map was established by integrating the NY map and a previously published genetic map (NC map) containing 15,240 SNPs, with a total genetic distance of 3,058.19 cM and an average map distance of 0.21 cM. The 12 pseudochromosomes of the Lycium reference genome were anchored using this consensus genetic map, with an anchoring rate of 64.3%. Moreover, weak collinearities between the consensus map and the pepper, potato, and tomato genomes were observed. Twenty-five stable QTLs were identified for leaf- and fruit-related phenotypes, including fruit weight, fruit longitude, leaf length, the fruit index, and the leaf index; these stable QTLs were mapped to four different linkage groups, with LOD scores ranging from 2.51 to 19.37 and amounts of phenotypic variance explained from 6.2% to 51.9%. Finally, 82 out of 188 predicted genes underlying stable QTLs for fruit-related traits were differentially expressed according to RNA-seq analysis. CONCLUSIONS A chromosome-level assembly can provide a foundation for further functional genomics research for wolfberry. The genomic regions of these stably expressed QTLs could be used as targets for further fine mapping and development of molecular markers for marker-assisted selection (MAS). The present study provided valuable information on saturated SNP markers and reliable QTLs for map-based cloning of functional genes related to yield and morphological traits in Lycium spp.
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Affiliation(s)
- Jianhua Zhao
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Haoxia Li
- Desertification Control Research Institute, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, 750002 China
| | - Yuhui Xu
- Adsen Biotechnology Co., Ltd, Urumchi, 830022 China
| | - Yue Yin
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Ting Huang
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Bo Zhang
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Yajun Wang
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Yanlong Li
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Youlong Cao
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
| | - Wei An
- Wolfberry Science Research Institute, Ningxia Academy of Agriculture and Forestry Sciences/National Wolfberry Engineering Research Center, Yinchuan, 750002 China
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16
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Wei Z, Yuan Q, Lin H, Li X, Zhang C, Gao H, Zhang B, He H, Liu T, Jie Z, Gao X, Shi S, Wang B, Gao Z, Kong L, Qian Q, Shang L. Linkage analysis, GWAS, transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress. BMC PLANT BIOLOGY 2021; 21:85. [PMID: 33563229 DOI: 10.1186/s12870-021-02857-2852] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/26/2021] [Indexed: 05/26/2023]
Abstract
BACKGROUND Rice plants suffer from the rising temperature which is becoming more and more prominent. Mining heat-resistant genes and applying them to rice breeding is a feasible and effective way to solve the problem. RESULT Three main biomass traits, including shoot length, dry weight, and fresh weight, changed after abnormally high-temperature treatment in the rice seedling stage of a recombinant inbred lines and the natural indica germplasm population. Based on a comparison of the results of linkage analysis and genome-wide association analysis, two loci with lengths of 57 kb and 69 kb in qDW7 and qFW6, respectively, were associated with the rice response to abnormally high temperatures at the seedling stage. Meanwhile, based on integrated transcriptome analysis, some genes are considered as important candidate genes. Combining with known genes and analysis of homologous genes, it was found that there are eight genes in candidate intervals that need to be focused on in subsequent research. CONCLUSIONS The results indicated several relevant loci, which would help researchers to further discover beneficial heat-resistant genes that can be applied to rice heat-resistant breeding.
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Affiliation(s)
- Zhaoran Wei
- 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
- State Key Laboratory of Crop Biology, College of Agriculture, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Qiaoling Yuan
- 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
| | - Hai Lin
- 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
| | - Xiaoxia Li
- 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
| | - Chao Zhang
- 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
| | - Hongsheng Gao
- 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
| | - Bin Zhang
- 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
| | - Huiying He
- 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
| | - Tianjiao Liu
- 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
| | - Zhang Jie
- 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
| | - Xu Gao
- 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
| | - Shandang Shi
- 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
| | - Bo Wang
- 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
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Lingrang Kong
- State Key Laboratory of Crop Biology, College of Agriculture, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Qian Qian
- 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.
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
| | - Lianguang Shang
- 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.
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17
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Wei Z, Yuan Q, Lin H, Li X, Zhang C, Gao H, Zhang B, He H, Liu T, Jie Z, Gao X, Shi S, Wang B, Gao Z, Kong L, Qian Q, Shang L. Linkage analysis, GWAS, transcriptome analysis to identify candidate genes for rice seedlings in response to high temperature stress. BMC PLANT BIOLOGY 2021; 21:85. [PMID: 33563229 PMCID: PMC7874481 DOI: 10.1186/s12870-021-02857-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 01/26/2021] [Indexed: 05/28/2023]
Abstract
BACKGROUND Rice plants suffer from the rising temperature which is becoming more and more prominent. Mining heat-resistant genes and applying them to rice breeding is a feasible and effective way to solve the problem. RESULT Three main biomass traits, including shoot length, dry weight, and fresh weight, changed after abnormally high-temperature treatment in the rice seedling stage of a recombinant inbred lines and the natural indica germplasm population. Based on a comparison of the results of linkage analysis and genome-wide association analysis, two loci with lengths of 57 kb and 69 kb in qDW7 and qFW6, respectively, were associated with the rice response to abnormally high temperatures at the seedling stage. Meanwhile, based on integrated transcriptome analysis, some genes are considered as important candidate genes. Combining with known genes and analysis of homologous genes, it was found that there are eight genes in candidate intervals that need to be focused on in subsequent research. CONCLUSIONS The results indicated several relevant loci, which would help researchers to further discover beneficial heat-resistant genes that can be applied to rice heat-resistant breeding.
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Affiliation(s)
- Zhaoran Wei
- 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
- State Key Laboratory of Crop Biology, College of Agriculture, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Qiaoling Yuan
- 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
| | - Hai Lin
- 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
| | - Xiaoxia Li
- 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
| | - Chao Zhang
- 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
| | - Hongsheng Gao
- 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
| | - Bin Zhang
- 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
| | - Huiying He
- 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
| | - Tianjiao Liu
- 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
| | - Zhang Jie
- 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
| | - Xu Gao
- 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
| | - Shandang Shi
- 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
| | - Bo Wang
- 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
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Lingrang Kong
- State Key Laboratory of Crop Biology, College of Agriculture, Shandong Agricultural University, Tai'an, 271018, Shandong, China
| | - Qian Qian
- 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.
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
| | - Lianguang Shang
- 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.
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Wei X, Qiu J, Yong K, Fan J, Zhang Q, Hua H, Liu J, Wang Q, Olsen KM, Han B, Huang X. A quantitative genomics map of rice provides genetic insights and guides breeding. Nat Genet 2021; 53:243-253. [PMID: 33526925 DOI: 10.1038/s41588-020-00769-9] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 12/11/2020] [Indexed: 02/07/2023]
Abstract
Extensive allelic variation in agronomically important genes serves as the basis of rice breeding. Here, we present a comprehensive map of rice quantitative trait nucleotides (QTNs) and inferred QTN effects based on eight genome-wide association study cohorts. Population genetic analyses revealed that domestication, local adaptation and heterosis are all associated with QTN allele frequency changes. A genome navigation system, RiceNavi, was developed for QTN pyramiding and breeding route optimization, and implemented in the improvement of a widely cultivated indica variety. This work presents an efficient platform that bridges ever-increasing genomic knowledge and diverse improvement needs in rice.
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Affiliation(s)
- Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Jie Qiu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Kaicheng Yong
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Jiongjiong Fan
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Qi Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Hua Hua
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Jie Liu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Qin Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Kenneth M Olsen
- Department of Biology, Washington University in St Louis, St Louis, MO, USA
| | - Bin Han
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China.
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19
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Liu M, He W, Zhang A, Zhang L, Sun D, Gao Y, Ni P, Ma X, Cui Z, Ruan Y. Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2021; 303:110767. [PMID: 33487352 DOI: 10.1016/j.plantsci.2020.110767] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
In maize, the shank is a unique tissue linking the stem to the ear. Shank length (SL) mainly affects the transport of photosynthetic products to the ear and the dehydration of kernels via regulated husk morphology. The limited studies on SL revealed it is a highly heritable quantitative trait controlled by significant additive and additive-dominance effects. However, the genetic basis of SL remains unclear. In this study, we analyzed three maize recombinant inbred line (RIL) populations to elucidate the molecular mechanism underlying the SL. The data indicated the SL varied among the three RIL populations and was highly heritable. Additionally, the SL was positively correlated with the husk length (HL), husk number (HN), ear length (EL), and ear weight (EW) in the BY815/K22 (BYK) and CI7/K22 (CIK) RIL populations, but was negatively correlated with the husk width (HW) in the BYK RIL population. Moreover, 10 quantitative trait loci (QTL) for SL were identified in the three RIL populations, five of which were large-effect QTL. The percentage of the total phenotypic variation explained by the QTL for SL was 13.67 %, 20.45 %, and 30.81 % in the BY815/DE3 (BYD), BYK, and CIK RIL populations, respectively. Further analyses uncovered some genetic overlap between SL and EL, SL and ear row number (ERN), SL and cob weight (CW), and SL and HN. Unlike the large-effect QTL qSL BYK-2-2, which spanned the centromere, the other four large-effect QTL were delimited to a single peak bin via bin map. Furthermore, 2, 5, 6, and 12 genes associated with SL were identified for qSL BYK-2-1, qSL CIK-2-1, qSL CIK-9-1, and qSL CIK-9-2, respectively. Five of the candidate genes for SL may contribute to the hormone metabolism and sphingolipid biosynthesis regulating cell elongation, division, differentiation, and expansion. These results may be relevant for future studies on the genetic basis of SL and for the molecular breeding of maize based on marker-assisted selection to develop new varieties with an ideal SL.
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Affiliation(s)
- Meiling Liu
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Wenshu He
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China; Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Av. Alcalde Rovira Roure, Lleida, 25198, Spain
| | - Ao Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Lijun Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Daqiu Sun
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Yuan Gao
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Pengzun Ni
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Xinglin Ma
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Zhenhai Cui
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
| | - Yanye Ruan
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
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20
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Lin T, Zhou C, Chen G, Yu J, Wu W, Ge Y, Liu X, Li J, Jiang X, Tang W, Tian Y, Zhao Z, Zhu C, Wang C, Wan J. Heterosis-associated genes confer high yield in super hybrid rice. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:3287-3297. [PMID: 32852584 PMCID: PMC7567734 DOI: 10.1007/s00122-020-03669-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 08/11/2020] [Indexed: 05/13/2023]
Abstract
Heterosis QTLs, including qSS7 and qHD8, with dominance effects were identified through GBS and large-scale phenotyping of CSSLs and hybrid F1 populations in a paddy field. Heterosis has contributed immensely to agricultural production, but its genetic basis is unclear. We evaluated dominance effects by creating two hybrid populations: a B-homo set with a homozygous background and heterozygous chromosomal segments and a B-heter set with a heterozygous background and homozygous segments. This was achieved by crossing a set of 156 backcrossed-derived chromosome segment substitution lines (CSSLs) with their recurrent parent (9311), the male parent of the first super-high-yield hybrid Liangyoupei9 (LYP9), and with the female parent (PA64s) of the hybrid. The CSSLs were subjected to a genotyping-by-sequencing analysis to develop a genetic map of segments introduced from the PA64s. We evaluated the heterotic effects on eight yield-related traits in the hybrid variety and F1 populations in large-scale field experiments over 2 years. Using a linkage map consisting of high-density SNPs, we identified heterosis-associated genes in LYP9. Five candidate genes contributed to the high yield of LYP9, with qSS7 and qHD8 repeatedly detected in both B-hybrid populations. The heterozygous segments harboring qSS7 and qHD8 showed dominance effects that contributed to the heterosis of yield components in the hybrid rice variety Liangyoupei9.
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Affiliation(s)
- Tianzi Lin
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
- Zhenjiang Institute of Agricultural Sciences in Hilly Region of Jiangsu Province, Jurong, 212400, China
| | - Cong Zhou
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
- Key Laboratory of Biology, Genetics and Breeding of Japonica Rice in the Mid-lower Yangtze River, Ministry of Agriculture, Nanjing, 210095, China
- Jiangsu Plant Gene Engineering Research Center, Nanjing, 210095, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing, 210095, China
| | - Gaoming Chen
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jun Yu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Wei Wu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuwei Ge
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xiaolan Liu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Jin Li
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xingzhou Jiang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Weijie Tang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yunlu Tian
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Zhigang Zhao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Chengsong Zhu
- Department of Immunology, The University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Chunming Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China.
- Key Laboratory of Biology, Genetics and Breeding of Japonica Rice in the Mid-lower Yangtze River, Ministry of Agriculture, Nanjing, 210095, China.
- Jiangsu Plant Gene Engineering Research Center, Nanjing, 210095, China.
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing, 210095, China.
| | - Jianmin Wan
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China.
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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21
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Genomic diversity generated by a transposable element burst in a rice recombinant inbred population. Proc Natl Acad Sci U S A 2020; 117:26288-26297. [PMID: 33020276 PMCID: PMC7584900 DOI: 10.1073/pnas.2015736117] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Genomes of all characterized higher eukaryotes harbor examples of transposable element (TE) bursts-the rapid amplification of TE copies throughout a genome. Despite their prevalence, understanding how bursts diversify genomes requires the characterization of actively transposing TEs before insertion sites and structural rearrangements have been obscured by selection acting over evolutionary time. In this study, rice recombinant inbred lines (RILs), generated by crossing a bursting accession and the reference Nipponbare accession, were exploited to characterize the spread of the very active Ping/mPing family through a small population and the resulting impact on genome diversity. Comparative sequence analysis of 272 individuals led to the identification of over 14,000 new insertions of the mPing miniature inverted-repeat transposable element (MITE), with no evidence for silencing of the transposase-encoding Ping element. In addition to new insertions, Ping-encoded transposase was found to preferentially catalyze the excision of mPing loci tightly linked to a second mPing insertion. Similarly, structural variations, including deletion of rice exons or regulatory regions, were enriched for those with break points at one or both ends of linked mPing elements. Taken together, these results indicate that structural variations are generated during a TE burst as transposase catalyzes both the high copy numbers needed to distribute linked elements throughout the genome and the DNA cuts at the TE ends known to dramatically increase the frequency of recombination.
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22
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Chen Z, Li X, Lu H, Gao Q, Du H, Peng H, Qin P, Liang C. Genomic atlases of introgression and differentiation reveal breeding footprints in Chinese cultivated rice. J Genet Genomics 2020; 47:637-649. [DOI: 10.1016/j.jgg.2020.10.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 09/17/2020] [Accepted: 10/16/2020] [Indexed: 02/06/2023]
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23
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Cui Y, Hu X, Liang G, Feng A, Wang F, Ruan S, Dong G, Shen L, Zhang B, Chen D, Zhu L, Hu J, Lin Y, Guo L, Matsuoka M, Qian Q. Production of novel beneficial alleles of a rice yield-related QTL by CRISPR/Cas9. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:1987-1989. [PMID: 32115804 PMCID: PMC7540660 DOI: 10.1111/pbi.13370] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/06/2020] [Accepted: 02/17/2020] [Indexed: 05/04/2023]
Affiliation(s)
- Yongtao Cui
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Xingming Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- Bioscience and Biotechnology Center, Nagoya University, Nagoya, Japan
| | - Guohua Liang
- Jiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, China
| | - Anhui Feng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Fanmiao Wang
- Bioscience and Biotechnology Center, Nagoya University, Nagoya, Japan
| | - Shuang Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guojun Dong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Lan Shen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Dongdong Chen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Li Zhu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Jiang Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yongjun Lin
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Makoto Matsuoka
- Bioscience and Biotechnology Center, Nagoya University, Nagoya, Japan
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
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24
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Kumar A, Daware A, Kumar A, Kumar V, Gopala Krishnan S, Mondal S, Patra BC, Singh AK, Tyagi AK, Parida SK, Thakur JK. Genome-wide analysis of polymorphisms identified domestication-associated long low-diversity region carrying important rice grain size/weight quantitative trait loci. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 103:1525-1547. [PMID: 32432802 DOI: 10.1111/tpj.14845] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Revised: 05/01/2020] [Accepted: 05/12/2020] [Indexed: 05/02/2023]
Abstract
Rice grain size and weight are major determinants of grain quality and yield and so have been under rigorous selection since domestication. However, the genetic basis for contrasting grain size/weight trait among Indian germplasms and their association with domestication-driven evolution is not well understood. In this study, two long (LGG) and two short grain (SGG) genotypes were resequenced. LGG (LGR and PB 1121) differentiated from SGG (Sonasal and Bindli) by 504 439 single nucleotide polymorphisms (SNPs) and 78 166 insertion-and-deletion polymorphisms. The LRK gene cluster was different and a truncation mutation in the LRK8 kinase domain was associated with LGG. Phylogeny with 3000 diverse rice accessions revealed that the four sequenced genotypes belonged to the japonica group and were at the edge of the clades indicating them to be the potential source of genetic diversity available in Indian rice germplasm. Six SNPs were significantly associated with grain size/weight and the top four of these could be validated in mapping a population, suggesting this study as a valuable resource for high-throughput genotyping. A contiguous long low-diversity region (LDR) of approximately 6 Mb carrying a major grain weight quantitative trait loci (harbouring OsTOR gene) was identified on Chromosome 5. This LDR was identified as an evolutionary important site with significant positive selection and multiple selection sweeps, and showed association with many domestication-related traits, including grain size/weight. The aus population retained more allelic variations in the LDR than the japonica and indica populations, suggesting it to be one of the divergence loci. All the data and analyses can be accessed from the RiceSzWtBase database.
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Affiliation(s)
- Angad Kumar
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Anurag Daware
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Arvind Kumar
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Vinay Kumar
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - S Gopala Krishnan
- Division of Genetics, ICAR-Indian Agricultural Research Institute, Pusa, New Delhi, 110012, India
| | - Subhasish Mondal
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Bhaskar C Patra
- Crop Improvement Division, ICAR-National Rice Research Institute, Cuttack, 753006, India
| | - Ashok K Singh
- Division of Genetics, ICAR-Indian Agricultural Research Institute, Pusa, New Delhi, 110012, India
| | - Akhilesh K Tyagi
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India
| | - Swarup K Parida
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Jitendra K Thakur
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
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25
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Ruan B, Shang L, Zhang B, Hu J, Wang Y, Lin H, Zhang A, Liu C, Peng Y, Zhu L, Ren D, Shen L, Dong G, Zhang G, Zeng D, Guo L, Qian Q, Gao Z. Natural variation in the promoter of TGW2 determines grain width and weight in rice. THE NEW PHYTOLOGIST 2020; 227:629-640. [PMID: 32167575 DOI: 10.1111/nph.16540] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 03/03/2020] [Indexed: 05/10/2023]
Abstract
Understanding the genetic basis of natural variation in grain size among diverse rice varieties can help breeders develop high-yielding rice cultivars. Here, we report the discovery of qTGW2, a new semidominant quantitative trait locus for grain width and weight. The corresponding gene, TGW2, encodes CELL NUMBER REGULATOR 1 (OsCNR1) localized to the plasma membrane. A single nucleotide polymorphism (SNP) variation 1818 bp upstream of TGW2 is responsible for its different expression, leading to alteration in grain width and weight by influencing cell proliferation and expansion in glumes. TGW2 interacts with KRP1, a regulator of cell cycle in plants, to negatively regulate grain width and weight. Genetic diversity analysis of TGW2 in 141 rice accessions revealed it as a breeding target in a selective sweep region. Our findings provide new insights into the genetic mechanism underlying grain morphology and grain weight, and uncover a promising gene for improving rice yield.
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Affiliation(s)
- Banpu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Lianguang Shang
- 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, 518124, China
| | - Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, 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, 518124, China
| | - Jiang Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Yuexing Wang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Hai Lin
- 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, 518124, China
| | - Anpeng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Chaolei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Youlin Peng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Li Zhu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Deyong Ren
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Lan Shen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Guojun Dong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Guangheng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Dali Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, 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, 518124, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, Zhejiang, China
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26
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Zhang A, Gao Y, Li Y, Ruan B, Yang S, Liu C, Zhang B, Jiang H, Fang G, Ding S, Jahan N, Xie L, Dong G, Xu Z, Gao Z, Guo L, Qian Q. Genetic Analysis for Cooking and Eating Quality of Super Rice and Fine Mapping of a Novel Locus qGC10 for Gel Consistency. FRONTIERS IN PLANT SCIENCE 2020; 11:342. [PMID: 32265976 PMCID: PMC7105826 DOI: 10.3389/fpls.2020.00342] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 03/06/2020] [Indexed: 05/27/2023]
Abstract
Rice (Oryza sativa L.) is an important cereal that provides food for more than half of the world's population. Besides grain yield, improving grain quality is also essential to rice breeders. Amylose content (AC), gelatinization temperature (GT) and gel consistency (GC) are considered to be three indicators for cooking and eating quality in rice. Using a genetic map of RILs derived from the super rice Liang-You-Pei-Jiu with high-density SNPs, we detected 3 QTLs for AC, 3 QTLs for GT, and 8 QTLs for GC on chromosomes 3, 4, 5, 6, 10, and 12. Wx locus, an important determinator for AC and GC, resided in one QTL cluster for AC and GC, qAC6 and qGC6 here. And a novel major QTL qGC10 on chromosome 10 was identified in both Lingshui and Hangzhou. With the BC4F2 population derived from a CSSL harboring the segment for qGC10 from 93-11 in PA64s background, it was fine mapped between two molecular markers within 181 kb region with 27 annotated genes. Quantitative real-time PCR results showed that eight genes were differentially expressed in endosperm of two parents. After DNA sequencing, only LOC_Os10g04900, which encodes a F-box domain containing protein, has 2 bp deletion in the exon of PA64s, resulting in a premature stop codon. Therefore, LOC_Os10g04900 is considered to be the most likely candidate gene for qGC10 associated with gel consistency. Identification of qGC10 provides a new genetic resource for improvement of rice quality.
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Affiliation(s)
- Anpeng Zhang
- Rice Research Institute of Shenyang Agricultural University/Key Laboratory of Northern Japonica Rice Genetics and Breeding, Ministry of Education and Liaoning Province, Shenyang, China
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yang Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yuanyuan Li
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Banpu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Shenglong Yang
- Rice Research Institute of Shenyang Agricultural University/Key Laboratory of Northern Japonica Rice Genetics and Breeding, Ministry of Education and Liaoning Province, Shenyang, China
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Chaolei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Hongzhen Jiang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guonan Fang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Shilin Ding
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Noushin Jahan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Lihong Xie
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guojun Dong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Zhengjin Xu
- Rice Research Institute of Shenyang Agricultural University/Key Laboratory of Northern Japonica Rice Genetics and Breeding, Ministry of Education and Liaoning Province, Shenyang, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
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Liu C, Ding S, Zhang A, Hong K, Jiang H, Yang S, Ruan B, Zhang B, Dong G, Guo L, Zeng D, Qian Q, Gao Z. Development of nutritious rice with high zinc/selenium and low cadmium in grains through QTL pyramiding. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2020; 62:349-359. [PMID: 31957138 DOI: 10.1111/jipb.12909] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 01/17/2020] [Indexed: 06/10/2023]
Abstract
Enriching zinc (Zn) and selenium (Se) levels, while reducing cadmium (Cd) concentration in rice grains is of great benefit for human diet and health. Large natural variations in grain Zn, Se, and Cd concentrations in different rice accessions enable Zn/Se-biofortification and Cd-minimization through molecular breeding. Here, we report the development of new elite varieties by pyramiding major quantitative trait loci (QTLs) that significantly contribute to high Zn/Se and low Cd accumulation in grains. A chromosome segment substitution line CSSLGCC7 with the PA64s-derived GCC7 allele in the 93-11 background, exhibited steadily higher Mn and lower Cd concentrations in grains than those of 93-11. This elite chromosome segment substitution line (CSSL) was used as the core breeding material to cross with CSSLs harboring other major QTLs for essential mineral elements, especially CSSLGZC6 for grain Zn concentration and CSSLGSC5 for grain Se concentration. The CSSLGCC7+GZC6 and CSSLGCC7+GSC5 exhibited lower Cd concentration with higher Zn and Se concentrations in grains, respectively. Our study thus provides elite materials for rice breeding targeting high Zn/Se and low Cd concentrations in grains.
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Affiliation(s)
- Chaolei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Shilin Ding
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Anpeng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Kai Hong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Hongzhen Jiang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Shenglong Yang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Banpu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Guojun Dong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Dali Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
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28
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Liu CL, Gao ZY, Shang LG, Yang CH, Ruan BP, Zeng DL, Guo LB, Zhao FJ, Huang CF, Qian Q. Natural variation in the promoter of OsHMA3 contributes to differential grain cadmium accumulation between Indica and Japonica rice. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2020; 62:314-329. [PMID: 30791211 DOI: 10.1111/jipb.12794] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 02/18/2019] [Indexed: 05/18/2023]
Abstract
Rice is a major source of cadmium (Cd) intake for Asian people. Indica rice usually accumulates more Cd in shoots and grains than Japonica rice. However, underlying genetic bases for differential Cd accumulation between Indica and Japonica rice are still unknown. In this study, we cloned a quantitative trait locus (QTL) grain Cd concentration on chromosome 7 (GCC7) responsible for differential grain Cd accumulation between two rice varieties by performing QTL analysis and map-based cloning. We found that the two GCC7 alleles, GCC7PA64s and GCC793-11 , had different promoter activity of OsHMA3, leading to different OsHMA3 expression and different shoot and grain Cd concentrations. By analyzing the distribution of different haplotypes of GCC7 among diverse rice accessions, we discovered that the high and low Cd accumulation alleles, namely GCC793-11 and GCC7PA64s , were preferentially distributed in Indica and Japonica rice, respectively. We further showed that the GCC7PA64s allele can be used to replace the GCC793-11 allele in the super cultivar 93-11 to reduce grain Cd concentration without adverse effect on agronomic traits. Our results thus reveal that the QTL GCC7 with sequence variation in the OsHMA3 promoter is an important determinant controlling differential grain Cd accumulation between Indica and Japonica rice.
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Affiliation(s)
- Chao-Lei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
- Shanghai Center for Plant Stress Biology and National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence in Molecular Plant Sciences, the Chinese Academy of Sciences, Shanghai, 200032, China
| | - Zhen-Yu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Lian-Guang Shang
- Agricultural Genomics Institute, the Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
| | - Chang-Hong Yang
- Shanghai Center for Plant Stress Biology and National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence in Molecular Plant Sciences, the Chinese Academy of Sciences, Shanghai, 200032, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095, China
| | - Ban-Pu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Da-Li Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Long-Biao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, 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
| | - Chao-Feng Huang
- Shanghai Center for Plant Stress Biology and National Key Laboratory of Plant Molecular Genetics, CAS Center of Excellence in Molecular Plant Sciences, the Chinese Academy of Sciences, Shanghai, 200032, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
- Agricultural Genomics Institute, the Chinese Academy of Agricultural Sciences, Shenzhen, 518120, China
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29
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Liu J, Li M, Zhang Q, Wei X, Huang X. Exploring the molecular basis of heterosis for plant breeding. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2020; 62:287-298. [PMID: 30916464 DOI: 10.1111/jipb.12804] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 03/13/2019] [Indexed: 05/18/2023]
Abstract
Since approximate a century ago, many hybrid crops have been continually developed by crossing two inbred varieties. Owing to heterosis (hybrid vigor) in plants, these hybrids often have superior agricultural performances in yield or disease resistance succeeding their inbred parental lines. Several classical hypotheses have been proposed to explain the genetic causes of heterosis. During recent years, many new genetics and genomics strategies have been developed and used for the identifications of heterotic genes in plants. Heterotic effects of the heterotic loci and molecular functions of the heterotic genes are being investigated in many plants such as rice, maize, sorghum, Arabidopsis and tomato. More and more data and knowledge coming from the molecular studies of heterotic loci and genes will serve as a valuable resource for hybrid breeding by molecular design in future. This review aims to address recent advances in our understanding of the genetic and molecular mechanisms of heterosis in plants. The remaining scientific questions on the molecular basis of heterosis and the potential applications in breeding are also proposed and discussed.
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Affiliation(s)
- Jie Liu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Mengjie Li
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Qi Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
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30
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Scheben A, Chan CKK, Mansueto L, Mauleon R, Larmande P, Alexandrov N, Wing RA, McNally KL, Quesneville H, Edwards D. Progress in single-access information systems for wheat and rice crop improvement. Brief Bioinform 2020; 20:565-571. [PMID: 29659709 DOI: 10.1093/bib/bby016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Improving productivity of the staple crops wheat and rice is essential to feed the growing global population, particularly in the context of a changing climate. However, current rates of yield gain are insufficient to support the predicted population growth. New approaches are required to accelerate the breeding process, and many of these are driven by the application of large-scale crop data. To leverage the substantial volumes and types of data that can be applied for precision breeding, the wheat and rice research communities are working towards the development of integrated systems to access and standardize the dispersed, heterogeneous available data. Here, we outline the initiatives of the International Wheat Information System (WheatIS) and the International Rice Informatics Consortium (IRIC) to establish Web-based single-access systems and data mining tools to make the available resources more accessible, drive discovery and accelerate the production of new crop varieties. We discuss the progress of WheatIS and IRIC towards unifying specialized wheat and rice databases and building custom software platforms to manage and interrogate these data. Single-access crop information systems will strengthen scientific collaboration, optimize the use of public research funds and help achieve the required yield gains in the two most important global food crops.
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Affiliation(s)
- Armin Scheben
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
| | - Chon-Kit Kenneth Chan
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
| | - Locedie Mansueto
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Ramil Mauleon
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Pierre Larmande
- IRD, UMR DIADE (Plant Diversity Adaptation and Development Research unit) , 911 Avenue Agropolis, 34394 Montpellier, France
| | - Nickolai Alexandrov
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Rod A Wing
- Arizona Genomics Institute, University of Arizona, Tucson, Arizona, USA
| | - Kenneth L McNally
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | | | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
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Yu Y, Zhu M, Cui Y, Liu Y, Li Z, Jiang N, Xu Z, Xu Q, Sui G. Genome Sequence and QTL Analyses Using Backcross Recombinant Inbred Lines (BILs) and BILF 1 Lines Uncover Multiple Heterosis-related Loci. Int J Mol Sci 2020; 21:ijms21030780. [PMID: 31991733 PMCID: PMC7038202 DOI: 10.3390/ijms21030780] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 01/21/2020] [Accepted: 01/23/2020] [Indexed: 01/19/2023] Open
Abstract
: Heterosis is an interesting topic for both breeders and biologists due to its practical importance and scientific significance. Cultivated rice (Oryza sativa L.) consists of two subspecies, indica and japonica, and hybrid rice is the predominant form of indica rice in China. However, the molecular mechanism underlying heterosis in japonica remains unclear. The present study determined the genome sequence and conducted quantitative trait locus (QTL) analysis using backcross recombinant inbred lines (BILs) and BILF1 lines to uncover the heterosis-related loci for rice yield increase under a japonica genetic background. The BIL population was derived from an admixture variety Habataki and japonica variety Sasanishiki cross to improve the genetic diversity but maintain the genetic background close to japonica. The results showed that heterosis in F1 mainly involved grain number per panicle. The BILF1s showed an increase in grain number per panicle but a decrease in plant height compared with the BILs. Genetic analysis then identified eight QTLs for heterosis in the BILF1s; four QTLs were detected exclusively in the BILF1 population only, presenting a mode of dominance or super-dominance in the heterozygotes. An additional four loci overlapped with QTLs detected in the BIL population, and we found that Grains Height Date 7 (Ghd7) was correlated in days to heading in both BILs and BILF1s. The admixture genetic background of Habataki was also determined by subspecies-specific single nucleotide polymorphisms (SNPs). This investigation highlights the importance of high-throughput sequencing to elucidate the molecular mechanism of heterosis and provides useful germplasms for the application of heterosis in japonica rice production.
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Affiliation(s)
- Yahui Yu
- Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China; (Y.Y.)
- Liaoning Institute of Saline-Alkali Land Utilization, Panjin 124010, China
- Liaoning Academy of Agricultural Sciences, Shenyang 110866, China
| | - Mengmeng Zhu
- Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China; (Y.Y.)
| | - Yue Cui
- Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China; (Y.Y.)
| | - Yu Liu
- Liaoning Institute of Saline-Alkali Land Utilization, Panjin 124010, China
| | - Zhenyu Li
- Liaoning Institute of Saline-Alkali Land Utilization, Panjin 124010, China
| | - Nan Jiang
- Shenyang Research and Development Service Center of Modern Agriculture, Shenyang 110034, China
| | - Zhengjin Xu
- Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China; (Y.Y.)
| | - Quan Xu
- Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China; (Y.Y.)
- Correspondence: (Q.X.); (G.S.)
| | - Guomin Sui
- Liaoning Academy of Agricultural Sciences, Shenyang 110866, China
- Correspondence: (Q.X.); (G.S.)
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32
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Wen Y, Fang Y, Hu P, Tan Y, Wang Y, Hou L, Deng X, Wu H, Zhu L, Zhu L, Chen G, Zeng D, Guo L, Zhang G, Gao Z, Dong G, Ren D, Shen L, Zhang Q, Xue D, Qian Q, Hu J. Construction of a High-Density Genetic Map Based on SLAF Markers and QTL Analysis of Leaf Size in Rice. FRONTIERS IN PLANT SCIENCE 2020; 11:1143. [PMID: 32849702 PMCID: PMC7411225 DOI: 10.3389/fpls.2020.01143] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/14/2020] [Indexed: 05/02/2023]
Abstract
Leaf shape is an important agronomic trait for constructing an ideal plant type in rice, and high-density genetic map is facilitative in improving accuracy and efficiency for quantitative trait loci (QTL) analysis of leaf trait. In this study, a high-density genetic map contained 10,760 specific length amplified fragment sequencing (SLAF) markers was established based on 149 recombinant inbred lines (RILs) derived from the cross between Rekuangeng (RKG) and Taizhong1 (TN1), which exhibited 1,613.59 cM map distance with an average interval of 0.17 cM. A total of 24 QTLs were detected and explained the phenotypic variance ranged from 9% to 33.8% related to the leaf morphology across two areas. Among them, one uncloned major QTL qTLLW1 (qTLL1 and qTLLW1) involved in regulating leaf length and leaf width with max 33.8% and 22.5% phenotypic variance respectively was located on chromosome 1, and another major locus qTLW4 affecting leaf width accounted for max 25.3% phenotypic variance was mapped on chromosome 4. Fine mapping and qRT-PCR expression analysis indicated that qTLW4 may be allelic to NAL1 (Narrow leaf 1) gene.
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Affiliation(s)
- Yi Wen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- Rice Research Institute of Shenyang Agricultural University/Key Laboratory of Northern Japonica Rice Genetics and Breeding, Ministry of Education and Liaoning Province, Shenyang, China
| | - Yunxia Fang
- College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, China
| | - Peng Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yiqing Tan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yueying Wang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Linlin Hou
- College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, China
| | - Xuemei Deng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Hao Wu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Lixin Zhu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Li Zhu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guang Chen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Dali Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guangheng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Guojun Dong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Deyong Ren
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Lan Shen
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Qiang Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Dawei Xue
- College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- Rice Research Institute of Shenyang Agricultural University/Key Laboratory of Northern Japonica Rice Genetics and Breeding, Ministry of Education and Liaoning Province, Shenyang, China
- *Correspondence: Qian Qian, ; Jiang Hu,
| | - Jiang Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
- *Correspondence: Qian Qian, ; Jiang Hu,
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33
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Luo X, Xu L, Wang Y, Dong J, Chen Y, Tang M, Fan L, Zhu Y, Liu L. An ultra-high-density genetic map provides insights into genome synteny, recombination landscape and taproot skin colour in radish (Raphanus sativus L.). PLANT BIOTECHNOLOGY JOURNAL 2020; 18:274-286. [PMID: 31218798 PMCID: PMC6920339 DOI: 10.1111/pbi.13195] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 05/30/2019] [Accepted: 06/11/2019] [Indexed: 05/19/2023]
Abstract
High-density genetic map is a valuable tool for exploring novel genomic information, quantitative trait locus (QTL) mapping and gene discovery of economically agronomic traits in plant species. However, high-resolution genetic map applied to tag QTLs associated with important traits and to investigate genomic features underlying recombination landscape in radish (Raphanus sativus) remains largely unexplored. In this study, an ultra-high-density genetic map with 378 738 SNPs covering 1306.8 cM in nine radish linkage groups (LGs) was developed by a whole-genome sequencing-based approach. A total of 18 QTLs for 11 horticulture traits were detected. The map-based cloning data indicated that the R2R3-MYB transcription factor RsMYB90 was a crucial candidate gene determining the taproot skin colour. Comparative genomics analysis among radish, Brassica rapa and B. oleracea genome revealed several genomic rearrangements existed in the radish genome. The highly uneven distribution of recombination was observed across the nine radish chromosomes. Totally, 504 recombination hot regions (RHRs) were enriched near gene promoters and terminators. The recombination rate in RHRs was positively correlated with the density of SNPs and gene, and GC content, respectively. Functional annotation indicated that genes within RHRs were mainly involved in metabolic process and binding. Three QTLs for three traits were found in the RHRs. The results provide novel insights into the radish genome evolution and recombination landscape, and facilitate the development of effective strategies for molecular breeding by targeting and dissecting important traits in radish.
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Affiliation(s)
- Xiaobo Luo
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
- Guizhou Institute of BiotechnologyGuizhou Academy of Agricultural SciencesGuiyangChina
| | | | - Yan Wang
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
| | - Junhui Dong
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
| | - Yinglong Chen
- The UWA Institute of Agriculture, and School of Agriculture and EnvironmentThe University of Western AustraliaPerthWAAustralia
| | - Mingjia Tang
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
| | - Lianxue Fan
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
| | - Yuelin Zhu
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
| | - Liwang Liu
- National Key Laboratory of Crop Genetics and Germplasm EnhancementKey Laboratory of Horticultural Crop Biology and Genetic Improvement (East China) of MOA, College of HorticultureNanjing Agricultural UniversityNanjingChina
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34
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Rana N, Rahim MS, Kaur G, Bansal R, Kumawat S, Roy J, Deshmukh R, Sonah H, Sharma TR. Applications and challenges for efficient exploration of omics interventions for the enhancement of nutritional quality in rice (Oryza sativa L.). Crit Rev Food Sci Nutr 2019; 60:3304-3320. [DOI: 10.1080/10408398.2019.1685454] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Nitika Rana
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | | | - Gazaldeep Kaur
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Ruchi Bansal
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Surbhi Kumawat
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Joy Roy
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Rupesh Deshmukh
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Humira Sonah
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
| | - Tilak Raj Sharma
- National Agri-Food Biotechnology Institute (NABI), Mohali, Punjab, India
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35
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Wang H, Gao Y, Mao F, Xiong L, Mou T. Directional upgrading of brown planthopper resistance in an elite rice cultivar by precise introgression of two resistance genes using genomics-based breeding. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2019; 288:110211. [PMID: 31521227 DOI: 10.1016/j.plantsci.2019.110211] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/30/2019] [Accepted: 07/31/2019] [Indexed: 05/23/2023]
Abstract
Brown planthopper (BPH) is a devastating pest that threatens the food security of rice-producing countries. At present, most cultivars planted in farmers' paddies lack effective BPH resistance, which constitutes a potential threat to rice yield. Moreover, developing BPH-resistant rice varieties using traditional breeding approaches is time-consuming, labor-intensive, and unpredictable. In this study, we successfully enhanced BPH resistance of the elite rice cultivar Wushansimiao by introgressing the resistance genes BPH14 and BPH15 through positive selection, negative selection, and whole genome background selection. Through backcrossing, the introgression fragments were reduced to 428.3 kb for BPH14 and 413.1 kb for BPH15. Except for these two fragments, the residual genetic background of the selected near-isogenic lines (NILs) was nearly identical to that of the recurrent parent, with a genetic background recovery rate of 99.78%. As a result, the selected NILs exhibited much stronger BPH resistance at the seedling and adult stages compared to the recurrent parent. Moreover, field tests showed that grain yield, major agronomic traits, and grain quality of the five selected NILs were statistically indistinguishable from those of the recurrent parent. Our results provide an effective approach for directionally upgrading the target traits and will inform and facilitate rice breeding.
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Affiliation(s)
- Hongbo Wang
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yi Gao
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Fangming Mao
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Tongmin Mou
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China.
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36
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Tomkowiak A, Bocianowski J, Wolko Ł, Adamczyk J, Mikołajczyk S, Kowalczewski PŁ. Identification of Markers Associated with Yield Traits and Morphological Features in Maize ( Zea mays L.). PLANTS 2019; 8:plants8090330. [PMID: 31491958 PMCID: PMC6783969 DOI: 10.3390/plants8090330] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 08/30/2019] [Accepted: 09/03/2019] [Indexed: 12/05/2022]
Abstract
Association mapping is a powerful approach to detect associations between traits of interest and genetic markers based on linkage disequilibrium in molecular plant breeding. The aim of this study was the identification of single nucleotide polymorphisms (SNPs) and SilicoDArT markers associated with yield traits and morphological features in maize. Plant material constituted inbred lines. The field experiment with inbred lines was established on 10 m2 plots in a set of complete random blocks in three replicates. We observed 22 quantitative traits. Association mapping was performed in this study using a method based on the mixed linear model with the population structure estimated by eigenanalysis (principal component analysis applied to all markers) and modeled by random effects. As a result of mapping, 969 markers (346 SNPs and 623 SilocoDArT) were selected from 49,911 identified polymorphic molecular markers, which were significantly associated with the analyzed morphological features and yield structure traits. Markers associated with five or six traits were selected during further analyses, including SilicoDArT 4591115 (anthocyanin coloration of anthers, length of main axis above the highest lateral branch, cob length, number of grains per cob, weight of fresh grains per cob and weight of fresh grains per cob at 15% moisture), SilicoDArT 7059939 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, time of silk emergence—50% of flowering plants, anthocyanin coloration of anthers and cob diameter), SilicoDArT 5587991 (anthocyanin coloration of glumes of cob, time of anthesis—50% of flowering plants, anthocyanin coloration of anthers, curvature of lateral branches and number of rows of grain). The two genetic similarity dendrograms between the inbred lines were constructed based on all significant SNPs and SilicoDArT markers. On both dendrograms lines clustered according to the kernel structure (flint, dent) and origin. The selected markers may be useful in predicting hybrid formulas in a heterosis culture. The present study demonstrated that molecular SNP and Silico DArT markers could be used in this species to group lines in terms of origin and lines with incomplete origin data. They can also be useful in maize in predicting the hybrid formula and can find applications in the selection of parental components for heterosis crossings.
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Affiliation(s)
- Agnieszka Tomkowiak
- Department of Genetics and Plant Breeding, Poznań University of Life Sciences, 11 Dojazd St., 60-632 Poznań, Poland.
| | - Jan Bocianowski
- Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, 28 Wojska Polskiego St., 60-637 Poznań, Poland.
| | - Łukasz Wolko
- Department of Biochemistry and Biotechnology, Poznań University of Life Sciences, 11 Dojazd St., 60-632 Poznań, Poland.
| | - Józef Adamczyk
- Plant Breeding Smolice Ltd., Co., Smolice 146, 63-740 Kobylin, Poland.
| | - Sylwia Mikołajczyk
- Department of Genetics and Plant Breeding, Poznań University of Life Sciences, 11 Dojazd St., 60-632 Poznań, Poland.
| | - Przemysław Łukasz Kowalczewski
- Institute of Food Technology of Plant Origin, Poznań University of Life Sciences, 31 Wojska Polskiego St., 60-624 Poznań, Poland.
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Zhang B, Shang L, Ruan B, Zhang A, Yang S, Jiang H, Liu C, Hong K, Lin H, Gao Z, Hu J, Zeng D, Guo L, Qian Q. Development of Three Sets of High-Throughput Genotyped Rice Chromosome Segment Substitution Lines and QTL Mapping for Eleven Traits. RICE (NEW YORK, N.Y.) 2019; 12:33. [PMID: 31076960 PMCID: PMC6510774 DOI: 10.1186/s12284-019-0293-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 04/22/2019] [Indexed: 05/04/2023]
Abstract
BACKGROUND Detecting and mapping chromosomal regions that are related to quantitative phenotypic variation in chromosome segment substitution lines (CSSLs) provides an effective means to characterize the genetic basis of complex agronomic trait. CSSLs are also powerful tools for studying the effects of quantitative trait loci (QTLs) pyramiding and interaction on phenotypic variation. RESULTS Here, we developed three sets of CSSLs consisting of 81, 55, and 61 lines, which were derived from PA64s × 9311, Nipponbare × 9311 and PA64s × Nipponbare crosses, respectively. All of the 197 CSSLs were subjected to high-throughput genotyping by whole-genome resequencing to obtain accurate physical maps for the 3 sets of CSSLs. The 3 sets of CSSLs were used to analyze variation for 11 major agronomic traits in Hangzhou and Shenzhen and led to the detection of 71 QTLs with phenotypic effect that ranged from 7.6% to 44.8%. Eight QTLs were commonly detected under two environments for the same phenotype, and there were also 8 QTL clusters that were found. Combined with GWAS on grain length and expression profiles on young panicle tissues, qGL1 detected in CSSLs was fine mapped within a 119 kb region on chromosome 1 and LOC_Os01g53140 and LOC_Os01g53250 were the two most likely candidate genes. CONCLUSIONS Our results indicate that developing CSSLs genotyped by whole-genome resequencing are powerful tools for basic genetic research and provide a platform for the rational design of rice breeding. Meanwhile, the conjoint analysis of different CSSLs, natural population and expression profiles can facilitate QTL fine mapping.
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Affiliation(s)
- Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Lianguang Shang
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Banpu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Anpeng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Shenglong Yang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Hongzhen Jiang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Chaolei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Kai Hong
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Hai Lin
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Jiang Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Dali Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.
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Juanillas V, Dereeper A, Beaume N, Droc G, Dizon J, Mendoza JR, Perdon JP, Mansueto L, Triplett L, Lang J, Zhou G, Ratharanjan K, Plale B, Haga J, Leach JE, Ruiz M, Thomson M, Alexandrov N, Larmande P, Kretzschmar T, Mauleon RP. Rice Galaxy: an open resource for plant science. Gigascience 2019; 8:giz028. [PMID: 31107941 PMCID: PMC6527052 DOI: 10.1093/gigascience/giz028] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 08/29/2018] [Accepted: 02/12/2019] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers. FINDINGS The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented. CONCLUSIONS Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.
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Affiliation(s)
- Venice Juanillas
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
| | - Alexis Dereeper
- Institut de recherche pour le développement (IRD), University of Montpellier, DIADE, IPME, Montpellier, France
| | - Nicolas Beaume
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
| | - Gaetan Droc
- CIRAD, UMR AGAP, F-34398 Montpellier, France
| | - Joshua Dizon
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
| | - John Robert Mendoza
- Advanced Science and Technology Institute, Department of Science and Technology, Quezon City, Philippines
| | - Jon Peter Perdon
- Advanced Science and Technology Institute, Department of Science and Technology, Quezon City, Philippines
| | - Locedie Mansueto
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
| | - Lindsay Triplett
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO 80523-1177, USA
| | - Jillian Lang
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO 80523-1177, USA
| | - Gabriel Zhou
- Indiana University, 107 S Indiana Ave, Bloomington, IN 47405, USA
| | | | - Beth Plale
- Indiana University, 107 S Indiana Ave, Bloomington, IN 47405, USA
| | - Jason Haga
- National Institute of Advanced Industrial Science and Technology, AIST Tsukuba Central 1,1-1-1 Umezono, Tsukuba, Ibaraki 305-8560, Japan
| | - Jan E Leach
- Department of Bioagricultural Sciences and Pest Management, Colorado State University, Fort Collins, CO 80523-1177, USA
| | - Manuel Ruiz
- CIRAD, UMR AGAP, F-34398 Montpellier, France
| | - Michael Thomson
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
- Department of Soil and Crop Sciences, Texas A&M University, Houston, TX, USA
| | - Nickolai Alexandrov
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
| | - Pierre Larmande
- Institut de recherche pour le développement (IRD), University of Montpellier, DIADE, IPME, Montpellier, France
| | - Tobias Kretzschmar
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
- Southern Cross Plant Science, Southern Cross University, Lismore, Australia
| | - Ramil P Mauleon
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, Philippines
- Southern Cross Plant Science, Southern Cross University, Lismore, Australia
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Chen E, Huang X, Tian Z, Wing RA, Han B. The Genomics of Oryza Species Provides Insights into Rice Domestication and Heterosis. ANNUAL REVIEW OF PLANT BIOLOGY 2019; 70:639-665. [PMID: 31035826 DOI: 10.1146/annurev-arplant-050718-100320] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Here, we review recent progress in genetic and genomic studies of the diversity of Oryza species. In recent years, unlocking the genetic diversity of Oryza species has provided insights into the genomics of rice domestication, heterosis, and complex traits. Genome sequencing and analysis of numerous wild rice (Oryza rufipogon) and Asian cultivated rice (Oryza sativa) accessions have enabled the identification of genome-wide signatures of rice domestication and the unlocking of the origin of Asian cultivated rice. Moreover, similar studies on genome variations of African rice (Oryza glaberrima) cultivars and their closely related wild progenitor Oryza barthii accessions have provided strong evidence to support a theory of independent domestication in African rice. Integrated genomic approaches have efficiently investigated many heterotic loci in hybrid rice underlying yield heterosis advantages and revealed the genomic architecture of rice heterosis. We conclude that in-depth unlocking of genetic variations among Oryza species will further enhance rice breeding.
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Affiliation(s)
- Erwang Chen
- National Center of Plant Gene Research; Shanghai Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences; and CAS Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China;
- University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
| | - Xuehui Huang
- College of Life Sciences, Shanghai Normal University, Shanghai 200234, China;
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Rod A Wing
- Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, Arizona 85721, USA;
| | - Bin Han
- National Center of Plant Gene Research; Shanghai Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences; and CAS Center of Excellence for Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China;
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Huggins TD, Chen MH, Fjellstrom RG, Jackson AK, McClung AM, Edwards JD. Association Analysis of Three Diverse Rice ( Oryza sativa L.) Germplasm Collections for Loci Regulating Grain Quality Traits. THE PLANT GENOME 2019; 12:170085. [PMID: 30951092 DOI: 10.3835/plantgenome2017.09.0085] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Rice ( L.) end-use cooking quality is vital for producers and billions of consumers worldwide. Grain quality is a complex trait with interacting genetic and environmental factors. Deciphering the complex genetic architecture associated with grain quality provides essential information for improved breeding strategies to enhance desirable traits that are stable across variable climatic and environmental conditions. In this study, genome-wide association (GWA) analysis of three rice diversity panels, the USDA rice core subset (1364 accessions), the minicore (MC) (173 accessions after removing non-), and the high density rice array-MC (HDMC) (383 accessions), with simple sequence repeats, single nucleotide polymorphic markers, or both, revealed large- and small-effect loci associated with known genes and previously uncharacterized genomic regions. Clustering of the significant regions in the GWA results suggests that multiple grain quality traits are inherited together. The 11 novel candidate loci for grain quality traits and the seven candidates for grain chalk identified are involved in the starch biosynthesis pathway. This study highlights the intricate pleiotropic relationships that exist in complex genotype-phenotypic associations and gives a greater insight into effective breeding strategies for grain quality improvement.
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Gonda I, Ashrafi H, Lyon DA, Strickler SR, Hulse-Kemp AM, Ma Q, Sun H, Stoffel K, Powell AF, Futrell S, Thannhauser TW, Fei Z, Van Deynze AE, Mueller LA, Giovannoni JJ, Foolad MR. Sequencing-Based Bin Map Construction of a Tomato Mapping Population, Facilitating High-Resolution Quantitative Trait Loci Detection. THE PLANT GENOME 2019; 12:180010. [PMID: 30951101 DOI: 10.3835/plantgenome2018.02.0010] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Genotyping-by-sequencing (GBS) was employed to construct a highly saturated genetic linkage map of a tomato ( L.) recombinant inbred line (RIL) population, derived from a cross between cultivar NC EBR-1 and the wild tomato L. accession LA2093. A pipeline was developed to convert single nucleotide polymorphism (SNP) data into genomic bins, which could be used for fine mapping of quantitative trait loci (QTL) and identification of candidate genes. The pipeline, implemented in a python script named SNPbinner, adopts a hidden Markov model approach for calculation of recombination breakpoints followed by genomic bins construction. The total length of the newly developed high-resolution genetic map was 1.2-fold larger than previously estimated based on restriction fragment length polymorphism (RFLP) and polymerase chain reaction (PCR)-based markers. The map was used to verify and refine QTL previously identified for two fruit quality traits in the RIL population, fruit weight (FW) and fruit lycopene content (LYC). Two well-described FW QTL ( and ) were localized precisely at their known underlying causative genes, and the QTL intervals were decreased by two- to tenfold. A major QTL for LYC content () was verified at high resolution and its underlying causative gene was determined to be ζ (). The RIL population, the high resolution genetic map, and the easy-to-use genotyping pipeline, SNPbinner, are made publicly available.
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Jia X, Zhang Y, Zhang Q, Zhao Q, Traw MB, Wang L, Tian D, Wang C, Yang S. High-resolution insight into recombination events at the SD1 locus in rice. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2019; 97:683-692. [PMID: 30417595 DOI: 10.1111/tpj.14154] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 09/28/2018] [Accepted: 11/05/2018] [Indexed: 06/09/2023]
Abstract
Recombination during meiosis plays an important role in genome evolution by reshuffling existing genetic variations into fresh combinations with the possibility of recovery of lost ancestral genotypes. While crossover (CO) events have been well studied, gene conversion events (GCs), which represent non-reciprocal information transfer between chromosomes, are poorly documented and difficult to detect due to their relatively small converted tract size. Here, we document these GC events and their phenotypic effects at an important locus in rice containing the SD1 gene, where multiple defective alleles contributed to the semi-dwarf phenotype of rice in the 'Green Revolution' of the 1960s. Here, physical separation of two defects allows recombination to generate the wild-type SD1 gene, for which plant height can then be used as a reporter. By screening 18 000 F2 progeny from a cross between two semi-dwarf cultivars that carry these different defective alleles, we detected 24 GC events, indicating a conversion rate of ~3.3 × 10-4 per marker per generation in a single meiotic cycle in rice. Furthermore, our data show that indels and single-nucleotide polymorphisms (SNPs) do not differ significantly in GC rates, at least at the SD1 locus. Our results provide strong evidence that GC by itself can regain an ancestral phenotype that was lost through mutation. This GC detection approach is likely to be broadly applicable to natural or artificial alleles of other phenotype-related functional genes, which are abundant in other plant genomes.
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Affiliation(s)
- Xianqing Jia
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Yadong Zhang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Qijun Zhang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Qingyong Zhao
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Milton Brian Traw
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Long Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Dacheng Tian
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Cailin Wang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, China
| | - Sihai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
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Choi HK. Translational genomics and multi-omics integrated approaches as a useful strategy for crop breeding. Genes Genomics 2019; 41:133-146. [PMID: 30353370 PMCID: PMC6394800 DOI: 10.1007/s13258-018-0751-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 10/01/2018] [Indexed: 01/25/2023]
Abstract
Recent next generation sequencing-driven mass production of genomic data and multi-omics-integrated approaches have significantly contributed to broadening and deepening our knowledge on the molecular system of living organisms. Accordingly, translational genomics (TG) approach can play a pivotal role in creating an informational bridge between model systems and relatively less studied plants. This review focuses mainly on addressing recent advancement in omics-related technologies, a diverse array of bioinformatic resources and potential applications of TG for the crop breeding. To accomplish above objectives, information on omics data production, various DBs and high throughput technologies was collected, integrated, and used to analyze current status and future perspectives towards omics-assisted crop breeding. Various omics data and resources have been organized and integrated into the databases and/or bioinformatic infrastructures, and thereby serve as the ome's information center for cross-genome translation of biological data. Although the size of accumulated omics data and availability of reference genomes are different among plant families, translational approaches have been actively progressing to access particular biological characteristics. When multi-layered omics data are integrated in a synthetic manner, it will allow providing a stereoscopic view of dynamic molecular behavior and interacting networks of genes occurring in plants. Consequently, TG approach will lead us to broader and deeper insights into target traits for the plant breeding. Furthermore, such systems approach will renovate conventional breeding programs and accelerate precision crop breeding in the future.
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Affiliation(s)
- Hong-Kyu Choi
- Department of Molecular Genetics, College of Natural Resources and Life Science, Dong-A University, Nakdong-Daero 550-Beongil 37, Saha-Gu, Busan, 49315, Republic of Korea.
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Malmberg MM, Barbulescu DM, Drayton MC, Shinozuka M, Thakur P, Ogaji YO, Spangenberg GC, Daetwyler HD, Cogan NOI. Evaluation and Recommendations for Routine Genotyping Using Skim Whole Genome Re-sequencing in Canola. FRONTIERS IN PLANT SCIENCE 2018; 9:1809. [PMID: 30581450 PMCID: PMC6292936 DOI: 10.3389/fpls.2018.01809] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 11/21/2018] [Indexed: 05/25/2023]
Abstract
Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated in silico in 149 canola samples representative of global diversity. Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.
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Affiliation(s)
- M. Michelle Malmberg
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | | | - Michelle C. Drayton
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Maiko Shinozuka
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Preeti Thakur
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Yvonne O. Ogaji
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - German C. Spangenberg
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | - Hans D. Daetwyler
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
| | - Noel O. I. Cogan
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
- School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia
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Song S, Tian D, Zhang Z, Hu S, Yu J. Rice Genomics: over the Past Two Decades and into the Future. GENOMICS, PROTEOMICS & BIOINFORMATICS 2018; 16:397-404. [PMID: 30771506 PMCID: PMC6411948 DOI: 10.1016/j.gpb.2019.01.001] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 01/14/2019] [Accepted: 01/23/2019] [Indexed: 01/08/2023]
Abstract
Domestic rice (Oryza sativa L.) is one of the most important cereal crops, feeding a large number of worldwide populations. Along with various high-throughput genome sequencing projects, rice genomics has been making great headway toward direct field applications of basic research advances in understanding the molecular mechanisms of agronomical traits and utilizing diverse germplasm resources. Here, we briefly review its achievements over the past two decades and present the potential for its bright future.
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Affiliation(s)
- Shuhui Song
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Dongmei Tian
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhang Zhang
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Songnian Hu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jun Yu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Borrelli VMG, Brambilla V, Rogowsky P, Marocco A, Lanubile A. The Enhancement of Plant Disease Resistance Using CRISPR/Cas9 Technology. FRONTIERS IN PLANT SCIENCE 2018; 9:1245. [PMID: 30197654 PMCID: PMC6117396 DOI: 10.3389/fpls.2018.01245] [Citation(s) in RCA: 100] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Accepted: 08/06/2018] [Indexed: 05/03/2023]
Abstract
Genome editing technologies have progressed rapidly and become one of the most important genetic tools in the implementation of pathogen resistance in plants. Recent years have witnessed the emergence of site directed modification methods using meganucleases, zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindrome repeats (CRISPR)/CRISPR-associated protein 9 (Cas9). Recently, CRISPR/Cas9 has largely overtaken the other genome editing technologies due to the fact that it is easier to design and implement, has a higher success rate, and is more versatile and less expensive. This review focuses on the recent advances in plant protection using CRISPR/Cas9 technology in model plants and crops in response to viral, fungal and bacterial diseases. As regards the achievement of viral disease resistance, the main strategies employed in model species such as Arabidopsis and Nicotiana benthamiana, which include the integration of CRISPR-encoding sequences that target and interfere with the viral genome and the induction of a CRISPR-mediated targeted mutation in the host plant genome, will be discussed. Furthermore, as regards fungal and bacterial disease resistance, the strategies based on CRISPR/Cas9 targeted modification of susceptibility genes in crop species such as rice, tomato, wheat, and citrus will be reviewed. After spending years deciphering and reading genomes, researchers are now editing and rewriting them to develop crop plants resistant to specific pests and pathogens.
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Affiliation(s)
- Virginia M. G. Borrelli
- Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Vittoria Brambilla
- Department of Agricultural and Environmental Sciences – Production, Territory, Agroenergy, University of Milan, Milan, Italy
| | - Peter Rogowsky
- Laboratoire Reproduction et Développement des Plantes, Université de Lyon, École Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, Centre National de la Recherche Scientifique, Institut National de la Recherche Agronomique, Lyon, France
| | - Adriano Marocco
- Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Alessandra Lanubile
- Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Piacenza, Italy
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Li X, Yu H, Jiao Y, Shahid MQ, Wu J, Liu X. Genome-wide analysis of DNA polymorphisms, the methylome and transcriptome revealed that multiple factors are associated with low pollen fertility in autotetraploid rice. PLoS One 2018; 13:e0201854. [PMID: 30080873 PMCID: PMC6078310 DOI: 10.1371/journal.pone.0201854] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 07/23/2018] [Indexed: 12/17/2022] Open
Abstract
Autotetraploid rice is a useful germplasm with high biomass production; however, low fertility is the main barrier in commercial utilization. In our previous study, differential expression of meiosis-related miRNAs was found to be involved in the pollen sterility of autotetraploid rice. However, genome-wide DNA variations and methylomes associated with low fertility of autotetraploid rice are still poorly understood. Here, we measured both global DNA variations and the methylome and compared them with the transcriptome during pollen development in autotetraploid rice by high-throughput sequencing. A total of 34416 SNPs, 6993 InDels, 1003 SVs and 25 CNVs were detected, and 11367 and 41117 differentially methylated regions showed hypermethylation and hypomethylation in 02428-4x. In total, 1110 genes displayed differentially expression in 02428-4x during meiosis, of these six harbored CNVs, including four upregulated genes with gain CNVs, such as LOC_Os11g38620. We identified 122 genes by comparing with the previous data that might be associated with low fertility during pollen development in 02428-4x. Of the 122 gens, 98 were displayed methylation and differential expression, including OsMADS98, CYP703A3 and OsABCG26. The downregulation of these three genes were confirmed by qPCR during meiosis of 02428-4x, which played pivotal roles in pollen fertility. These results indicate that the low fertility of autotetraploid rice is not only caused by the differential expression of genes involved in pollen development, but also by sequence variation and differential methylation, suggesting that the reason for pollen sterility in autotetraploid rice is complex and might be affected by multiple factors.
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Affiliation(s)
- Xiang Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
| | - Hang Yu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
| | - Yamin Jiao
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
| | - Muhammad Qasim Shahid
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
| | - Jinwen Wu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
| | - Xiangdong Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, China
- College of Agriculture, South China Agricultural University, Guangzhou, China
- * E-mail:
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Zhang Y, Wang L, Gao Y, Li D, Yu J, Zhou R, Zhang X. Genetic dissection and fine mapping of a novel dt gene associated with determinate growth habit in sesame. BMC Genet 2018; 19:38. [PMID: 29902971 PMCID: PMC6003200 DOI: 10.1186/s12863-018-0614-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 04/18/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND As an important oil crop, growth habit of sesame (Sesamum indicum L.) is naturally indeterminate, which brings about asynchronous maturity of capsules and causes loss of yield. RESULTS The genetic basis of determinate growth habit in sesame was investigated by classical genetic analysis through multiple populations, results revealed that it was controlled by an unique recessive gene. The genotyping by sequencing (GBS) approach was employed for high-throughput SNP identification and genotyping in the F2 population, then a high density bin map was constructed, the map was 1086.403 cM in length, which consisted of 1184 bins (13,679 SNPs), with an average of 0.918 cM between adjacent bins. Based on bin mapping in conjunction with SSR markers analysis in targeted region, the novel sesame determinacy gene was mapped on LG09 in a genome region of 41 kb. CONCLUSIONS This study dissected genetic basis of determinate growth habit in sesame, constructed a new high-density bin map and mapped a novel determinacy gene. Results of this study demonstrate that we employed an optimized approach to get fine-accuracy, high-resolution and high-efficiency mapping result in sesame. The findings provided important foundation for sesame determinacy gene cloning and were expected to be applied in breeding for cultivars suited to mechanized production.
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Affiliation(s)
- Yanxin Zhang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Linhai Wang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Yuan Gao
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Donghua Li
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Jingyin Yu
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Rong Zhou
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China
| | - Xiurong Zhang
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No.2 Xudong 2nd Rd, Wuhan, 430062, China.
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Demirci S, Peters SA, de Ridder D, van Dijk ADJ. DNA sequence and shape are predictive for meiotic crossovers throughout the plant kingdom. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 95:686-699. [PMID: 29808512 DOI: 10.1111/tpj.13979] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 05/11/2018] [Accepted: 05/14/2018] [Indexed: 06/08/2023]
Abstract
A better understanding of genomic features influencing the location of meiotic crossovers (COs) in plant species is both of fundamental importance and of practical relevance for plant breeding. Using CO positions with sufficiently high resolution from four plant species [Arabidopsis thaliana, Solanum lycopersicum (tomato), Zea mays (maize) and Oryza sativa (rice)] we have trained machine-learning models to predict the susceptibility to CO formation. Our results show that CO occurrence within various plant genomes can be predicted by DNA sequence and shape features. Several features related to genome content and to genomic accessibility were consistently either positively or negatively related to COs in all four species. Other features were found as predictive only in specific species. Gene annotation-related features were especially predictive for maize, whereas in tomato and Arabidopsis propeller twist and helical twist (DNA shape features) and AT/TA dinucleotides were found to be the most important. In rice, high roll (another DNA shape feature) and low CA dinucleotide frequency in particular were found to be associated with CO occurrence. The accuracy of our models was sufficient for Arabidopsis and rice (area under receiver operating characteristic curve, AUROC > 0.5), and was high for tomato and maize (AUROC ≫ 0.5), demonstrating that DNA sequence and shape are predictive for meiotic COs throughout the plant kingdom.
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Affiliation(s)
- Sevgin Demirci
- Business Unit Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands
- Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands
| | - Sander A Peters
- Business Unit Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands
| | - Dick de Ridder
- Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands
| | - Aalt D J van Dijk
- Business Unit Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands
- Bioinformatics Group, Wageningen University and Research, Wageningen, the Netherlands
- Biometris, Wageningen University and Research, Wageningen, the Netherlands
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50
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Galpaz N, Gonda I, Shem-Tov D, Barad O, Tzuri G, Lev S, Fei Z, Xu Y, Mao L, Jiao C, Harel-Beja R, Doron-Faigenboim A, Tzfadia O, Bar E, Meir A, Sa'ar U, Fait A, Halperin E, Kenigswald M, Fallik E, Lombardi N, Kol G, Ronen G, Burger Y, Gur A, Tadmor Y, Portnoy V, Schaffer AA, Lewinsohn E, Giovannoni JJ, Katzir N. Deciphering genetic factors that determine melon fruit-quality traits using RNA-Seq-based high-resolution QTL and eQTL mapping. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2018; 94:169-191. [PMID: 29385635 DOI: 10.1111/tpj.13838] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Revised: 12/19/2017] [Accepted: 01/08/2018] [Indexed: 05/18/2023]
Abstract
Combined quantitative trait loci (QTL) and expression-QTL (eQTL) mapping analysis was performed to identify genetic factors affecting melon (Cucumis melo) fruit quality, by linking genotypic, metabolic and transcriptomic data from a melon recombinant inbred line (RIL) population. RNA sequencing (RNA-Seq) of fruit from 96 RILs yielded a highly saturated collection of > 58 000 single-nucleotide polymorphisms, identifying 6636 recombination events that separated the genome into 3663 genomic bins. Bin-based QTL analysis of 79 RILs and 129 fruit-quality traits affecting taste, aroma and color resulted in the mapping of 241 QTL. Thiol acyltransferase (CmThAT1) gene was identified within the QTL interval of its product, S-methyl-thioacetate, a key component of melon fruit aroma. Metabolic activity of CmThAT1-encoded protein was validated in bacteria and in vitro. QTL analysis of flesh color intensity identified a candidate white-flesh gene (CmPPR1), one of two major loci determining fruit flesh color in melon. CmPPR1 encodes a member of the pentatricopeptide protein family, involved in processing of RNA in plastids, where carotenoid and chlorophyll pigments accumulate. Network analysis of > 12 000 eQTL mapped for > 8000 differentially expressed fruit genes supported the role of CmPPR1 in determining the expression level of plastid targeted genes. We highlight the potential of RNA-Seq-based QTL analysis of small to moderate size, advanced RIL populations for precise marker-assisted breeding and gene discovery. We provide the following resources: a RIL population genotyped with a unique set of SNP markers, confined genomic segments that harbor QTL governing 129 traits and a saturated set of melon eQTLs.
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Affiliation(s)
- Navot Galpaz
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Itay Gonda
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
| | - Doron Shem-Tov
- NRGENE, Park HaMada Ness Ziona, Israel
- Department of Molecular Microbiology and Biotechnology, Tel-Aviv University, Tel-Aviv, Israel
| | | | - Galil Tzuri
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Shery Lev
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
- Institute of Life Science, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Zhangjun Fei
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
- USDA-ARS Robert W. Holley Center for Agriculture and Health, Ithaca, New York, USA
| | - Yimin Xu
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
| | - Linyong Mao
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
| | - Chen Jiao
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
| | - Rotem Harel-Beja
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Adi Doron-Faigenboim
- Department of Vegetable and Field Crops, Volcani Center, Agricultural Research Organization, Rishon LeZion, Israel
| | - Oren Tzfadia
- VIB Department of Plant Systems Biology, Ghent University, Gent, Belgium
| | - Einat Bar
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Ayala Meir
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Uzi Sa'ar
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Aaron Fait
- The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Eran Halperin
- Department of Molecular Microbiology and Biotechnology, Tel-Aviv University, Tel-Aviv, Israel
| | - Merav Kenigswald
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
- Institute of Life Science, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Postharvest Science of Fresh Produce, Volcani Center, Agricultural Research Organization, Rishon LeZion, Israel
| | - Elazar Fallik
- Department of Postharvest Science of Fresh Produce, Volcani Center, Agricultural Research Organization, Rishon LeZion, Israel
| | - Nadia Lombardi
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
- Department of Agricultural Sciences, University of Naples, Portici, Italy
| | - Guy Kol
- NRGENE, Park HaMada Ness Ziona, Israel
| | - Gil Ronen
- NRGENE, Park HaMada Ness Ziona, Israel
| | - Yosef Burger
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Amit Gur
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Ya'akov Tadmor
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Vitaly Portnoy
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - Arthur A Schaffer
- Department of Vegetable and Field Crops, Volcani Center, Agricultural Research Organization, Rishon LeZion, Israel
| | - Efraim Lewinsohn
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
| | - James J Giovannoni
- Boyce Thompson Institute for Plant Research, Cornell University, Ithaca, New York, USA
- USDA-ARS Robert W. Holley Center for Agriculture and Health, Ithaca, New York, USA
| | - Nurit Katzir
- Department of Vegetable and Field Crops, Newe Ya'ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
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