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Lin P, Chai J, Wang A, Zhong H, Wang K. High-Density Genetic Map Construction and Quantitative Trait Locus Analysis of Fruit- and Oil-Related Traits in Camellia oleifera Based on Double Digest Restriction Site-Associated DNA Sequencing. Int J Mol Sci 2024; 25:8840. [PMID: 39201527 PMCID: PMC11354348 DOI: 10.3390/ijms25168840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 08/09/2024] [Accepted: 08/12/2024] [Indexed: 09/02/2024] Open
Abstract
Camellia oleifera, an important tree species and source of edible oil in China, has received significant attention owing to the oil's high unsaturated fatty acid content, which has benefits for human health. However, the mechanisms underlying C. oleifera yield and oil quality are largely unknown. In this study, 180 F1 progenies were obtained from two parents with obvious differences in fruit- and oil-related traits. We constructed a high-density genetic map using a double digest restriction site-associated DNA sequencing (ddRAD-Seq) strategy in C. oleifera. This map spanned 3327 cM and anchored 2780 markers in 15 linkage groups (LGs), with an average marker interval of 1.20 cM. A total of 221 quantitative trait loci (QTLs) associated with fruit- and oil-related traits were identified across three years' worth of phenotypic data. Nine QTLs were detected simultaneously in at least two different years, located on LG02, LG04, LG05, LG06, and LG11, and explained 8.5-16.6% of the phenotypic variation in the corresponding traits, respectively. Seventeen major QTLs were obtained that explained 13.0-16.6% of the phenotypic variance. Eleven and five flanking SNPs of major QTLs for fruit- and oil-related traits were detected which could be used for marker-assisted selection in C. oleifera breeding programs. Furthermore, 202 potential candidate genes in QTL regions were identified based on the collinearity of the genetic map and the C. oleifera "CON" genome. A potential regulatory network controlling fruit development and oil biosynthesis was constructed to dissect the complex mechanism of oil accumulation. The dissection of these QTLs will facilitate the gene cloning underlying lipid synthesis and increase our understanding in order to enhance C. oleifera oil yield and quality.
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Affiliation(s)
- Ping Lin
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; (P.L.); (J.C.); (A.W.); (H.Z.)
- Zhejiang Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Jingyu Chai
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; (P.L.); (J.C.); (A.W.); (H.Z.)
- Zhejiang Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Anni Wang
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; (P.L.); (J.C.); (A.W.); (H.Z.)
- Zhejiang Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Huiqi Zhong
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; (P.L.); (J.C.); (A.W.); (H.Z.)
- Zhejiang Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
| | - Kailiang Wang
- State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China; (P.L.); (J.C.); (A.W.); (H.Z.)
- Zhejiang Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
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Han K, Wang Z, Shen L, Du X, Lian S, Li Y, Li Y, Tang C, Li H, Zhang L, Wang J. Mapping of dynamic quantitative trait loci for plant height in a RIL population of foxtail millet ( Setaria italica L.). FRONTIERS IN PLANT SCIENCE 2024; 15:1418328. [PMID: 39114469 PMCID: PMC11303304 DOI: 10.3389/fpls.2024.1418328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 07/01/2024] [Indexed: 08/10/2024]
Abstract
Plant height (PH) is a crucial trait for strengthening lodging resistance and boosting yield in foxtail millet. To identify quantitative trait loci (QTL) and candidate genes associated with PH, we first developed a genetic map using a recombinant inbred line (RIL) population derived from a cross between Aininghuang and Jingu 21. Then, PH phenotyping data and four variations of best linear unbiased prediction (BLUP) were collected from nine environments and three development stages. Next, QTL mapping was conducted using both unconditional and conditional QTL methods. Subsequently, candidate genes were predicted via transcriptome analysis of parental samples at three developmental stages. The results revealed that the genetic map, based on re-sequencing, consisted of 4,360 bin markers spanning 1,016.06 cM with an average genetic distance of 0.23 cM. A total of 19 unconditional QTL, accounting for 5.23%-35.36% of the phenotypic variation explained (PVE), which included 7 major and 4 stable QTL, were identified. Meanwhile, 13 conditional QTL, explaining 5.88%-40.35% of PVE, including 5 major and 3 stable QTL, were discovered. Furthermore, four consistent and stable QTL were identified. Finally, eight candidate genes were predicted through RNA-seq and weighted gene co-expression network analysis (WGCNA). Those findings provide a crucial foundation for understanding the genetic mechanisms underlying PH development and facilitate molecular marker-assisted breeding of ideal plant types in foxtail millet.
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Affiliation(s)
- Kangni Han
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Zhilan Wang
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
- College of Agriculture, Shanxi Agricultural University, Taigu, China
| | - Lin Shen
- College of Agriculture, Shanxi Agricultural University, Taigu, China
| | - Xiaofen Du
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
- College of Agriculture, Shanxi Agricultural University, Taigu, China
| | - Shichao Lian
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Yuxin Li
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Yanfang Li
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Chuchu Tang
- College of Agriculture, Shanxi Agricultural University, Taigu, China
| | - Huixia Li
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Linyi Zhang
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
| | - Jun Wang
- Hou Ji Laboratory in Shanxi Province, Millet Research Institute, Shanxi Agricultural University, Changzhi, China
- College of Agriculture, Shanxi Agricultural University, Taigu, China
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Iwasa M, Chigira K, Nomura T, Adachi S, Asami H, Nakamura T, Motobayashi T, Ookawa T. Identification of Genomic Regions for Deep-Water Resistance in Rice for Efficient Weed Control with Reduced Herbicide Use. RICE (NEW YORK, N.Y.) 2023; 16:53. [PMID: 38006407 PMCID: PMC10676340 DOI: 10.1186/s12284-023-00671-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: 09/25/2023] [Accepted: 11/19/2023] [Indexed: 11/27/2023]
Abstract
Deep-water (DW) management in rice fields is a promising technique for efficient control of paddy weeds with reduced herbicide use. Maintaining a water depth of 10-20 cm for several weeks can largely suppress the weed growth, though it also inhibits rice growth because the DW management is usually initiated immediately after transplanting. Improving the DW resistance of rice during the initial growth stage is essential to avoid suppressing growth. In this study, we demonstrate a large genetic variation in the above-ground biomass (AGB) after the end of DW management among 165 temperate japonica varieties developed in Japan. Because the AGB closely correlated with plant length (PL) and tiller number (TN) at the early growth stage, we analyzed genomic regions associated with PL and TN by conducting a genome-wide association study. For PL, a major peak was detected on chromosome 3 (qPL3), which includes a gene encoding gibberellin biosynthesis, OsGA20ox1. The rice varieties with increased PL had a higher expression level of OsGA20ox1 as reported previously. For TN, a major peak was detected on chromosome 4 (qTN4), which includes NAL1 gene associated with leaf morphological development and panicle number. Although there was less difference in the expression level of NAL1 between genotypes, our findings suggest that an amino acid substitution in the exon region is responsible for the phenotypic changes. We also found that the rice varieties having alternative alleles of qPL3 and qTN4 showed significantly higher AGB than the varieties with the reference alleles. Our results suggest that OsGA20ox1 and NAL1 are promising genes for improving DW resistance in rice.
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Affiliation(s)
- Marina Iwasa
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan
| | - Koki Chigira
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan
| | - Tomohiro Nomura
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan
| | - Shunsuke Adachi
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan
| | - Hidenori Asami
- NARO Western Region Agricultural Research Center, 6-12-1 Nishifukatsu-cho, Fukuyama, Hiroshima, 721-8514, Japan
| | - Tetsuya Nakamura
- Yukimai Design Co. Ltd, 2-24-16 Nakamachi, Koganei, Tokyo, 184-0012, Japan
| | - Takashi Motobayashi
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan
| | - Taiichiro Ookawa
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan.
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Effects of Fermented Seaweed Fertilizer Treatment on Paddy Amino Acid Content and Rhizosphere Microbiome Community. FERMENTATION-BASEL 2022. [DOI: 10.3390/fermentation8090420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Seaweed has often been reported on for it potential bioresources for fertilizers to improve crop productivity and reduce the use of chemical fertilizers (CF). However, little is known about the nutritional status of the crop grown with the implementation of seaweed fertilizers (SF). In this study, the amino acid content of rice produced by SF implementation was evaluated. Furthermore, the rhizosphere bacterial community was also investigated. The paddy seedlings were divided into five groups, control (C0), chemical fertilizer (CF), seaweed fertilizer (SF), chemical and seaweed fertilizer combination 25:75 (CFSF1), and chemical and fertilizer combination 50:50 (CFSF2). The CFSF2 group shown significantly better growth characteristics compared to other groups. Based on the concentration of macronutrients (N, P, K) in paddy leaf, CFSF2 also shown the best results. This also correlates with the abundant amino acid composition in CFSF2 in almost all tested amino acids, namely, serine, phenylalanine, isoleucine, valine, glycine, tyrosine, proline, threonine, histidine, and arginine. Interestingly, beneficial bacteria Rhizobiales were significantly higher in CFSF2-treated soil (58%) compared to CF (29%). Another important group, Vicinamibacterales, was also significantly higher in CFSF2 (58%) compared to CF (7%). Hence, these potentially contributed to the high rice amino acid content and yield in the CFSF2-treated paddy. However, further field-scale studies are needed to confirm the bioindustrial application of seaweed in agricultural systems.
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Fu Y, Zhao H, Huang J, Zhu H, Luan X, Bu S, Liu Z, Wang X, Peng Z, Meng L, Liu G, Zhang G, Wang S. Dynamic analysis of QTLs on plant height with single segment substitution lines in rice. Sci Rep 2022; 12:5465. [PMID: 35361859 PMCID: PMC8971505 DOI: 10.1038/s41598-022-09536-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 03/24/2022] [Indexed: 01/22/2023] Open
Abstract
Dynamic regulation of QTLs remains mysterious. Single segment substitution lines (SSSLs) and conditional QTL mapping and functional QTL mappings are ideal materials and methods to explore dynamics of QTLs for complex traits. This paper analyzed the dynamics of QTLs on plant height with SSSLs in rice. Five SSSLs were verified with plant height QTLs first. All five QTLs had significant positive effects at one or more developmental stages except QTL1. They interacted each other, with negative effects before 49 d after transplanting and positive effects since then. The five QTLs selectively expressed in specific periods, mainly in the periods from 35 to 42 d and from 49 to 56 d after transplanting. Expressions of epistasis were dispersedly in various periods, negative effects appearing mainly before 35 d. The five QTLs brought the inflexion point ahead of schedule, accelerated growth and degradation, and changed the peak plant height, while their interactions had the opposite effects. The information will be helpful to understand the genetic mechanism for developmental traits.
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Affiliation(s)
- Yu Fu
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Hongyuan Zhao
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Jiongkai Huang
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Haitao Zhu
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Xin Luan
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Suhong Bu
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Zupei Liu
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Xiaoling Wang
- National Engineering Research Center of Rice (Nanchang), Rice Research Institute, Jiangxi Academy of Agricultural Sciences, Nanchang, 330299, People's Republic of China
| | - Zhiqin Peng
- National Engineering Research Center of Rice (Nanchang), Rice Research Institute, Jiangxi Academy of Agricultural Sciences, Nanchang, 330299, People's Republic of China
| | - Lijun Meng
- Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 440307, People's Republic of China.
| | - Guifu Liu
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
| | - Guiquan Zhang
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
| | - Shaokui Wang
- Guangdong Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
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Ren M, Huang M, Qiu H, Chun Y, Li L, Kumar A, Fang J, Zhao J, He H, Li X. Genome-Wide Association Study of the Genetic Basis of Effective Tiller Number in Rice. RICE (NEW YORK, N.Y.) 2021; 14:56. [PMID: 34170442 PMCID: PMC8233439 DOI: 10.1186/s12284-021-00495-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 05/17/2021] [Indexed: 05/14/2023]
Abstract
BACKGROUND Effective tiller number (ETN) has a pivotal role in determination of rice (Oryza sativa L.) grain yield. ETN is a complex quantitative trait regulated by both genetic and environmental factors. Despite multiple tillering-related genes have been cloned previously, few of them have been utilized in practical breeding programs. RESULTS In this study, we conducted a genome-wide association study (GWAS) for ETN using a panel of 490 rice accessions derived from the 3 K rice genomes project. Thirty eight ETN-associated QTLs were identified, interestingly, four of which colocalized with the OsAAP1, DWL2, NAL1, and OsWRKY74 gene previously reported to be involved in rice tillering regulation. Haplotype (Hap) analysis revealed that Hap5 of OsAAP1, Hap3 and 6 of DWL2, Hap2 of NAL1, and Hap3 and 4 of OsWRKY74 are favorable alleles for ETN. Pyramiding favorable alleles of all these four genes had more enhancement in ETN than accessions harboring the favorable allele of only one gene. Moreover, we identified 25 novel candidate genes which might also affect ETN, and the positive association between expression levels of the OsPILS6b gene and ETN was validated by RT-qPCR. Furthermore, transcriptome analysis on data released on public database revealed that most ETN-associated genes showed a relatively high expression from 21 days after transplanting (DAT) to 49 DAT and decreased since then. This unique expression pattern of ETN-associated genes may contribute to the transition from vegetative to reproductive growth of tillers. CONCLUSIONS Our results revealed that GWAS is a feasible way to mine ETN-associated genes. The candidate genes and favorable alleles identified in this study have the potential application value in rice molecular breeding for high ETN and grain yield.
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Affiliation(s)
- Mengmeng Ren
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Minghan Huang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871 China
- Peking University Institute of Advanced Agricultural Sciences, Weifang, 261325 Shandong China
| | - Haiyang Qiu
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Yan Chun
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Lu Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Ashmit Kumar
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jingjing Fang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jinfeng Zhao
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Hang He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871 China
- Peking University Institute of Advanced Agricultural Sciences, Weifang, 261325 Shandong China
| | - Xueyong Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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Ma X, Li F, Zhang Q, Wang X, Guo H, Xie J, Zhu X, Ullah Khan N, Zhang Z, Li J, Li Z, Zhang H. Genetic architecture to cause dynamic change in tiller and panicle numbers revealed by genome-wide association study and transcriptome profile in rice. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1603-1616. [PMID: 33058400 DOI: 10.1111/tpj.15023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 09/24/2020] [Accepted: 10/02/2020] [Indexed: 05/27/2023]
Abstract
Panicle number (PN) is one of the three yield components in rice. As one of the most unstable traits, the dynamic change in tiller number (DCTN) may determine the final PN. However, the genetic basis of DCTN and its relationship with PN remain unclear. Here, 377 deeply re-sequenced rice accessions were used to perform genome-wide association studies (GWAS) for tiller/PN. It was found that the DCTN pattern rather than maximum tiller number or effective tiller ratio is the determinant factor of high PN. The DCTN pattern that affords more panicles exhibits a period of stable tillering peak between 30 and 45 days after transplant (called DT30 and DT45, respectively), which was believed as an ideal pattern contributing to the steady transition from tiller development to panicle development (ST-TtP). Consistently, quantitative trait loci (QTL) expressed near DT30-DT45 were especially critical to the rice DCTN and in supporting the ST-TtP. The spatio-temporal expression analysis showed that the expression pattern of keeping relatively high expression in root at 24:00 (R24-P2) from about DT30 to DT45 is a typical expression pattern of cloned tiller genes, and the candidate genes with R24-P2 can facilitate the prediction of PN. Moreover, gene OsSAUR27 was identified by an integrated approach combining GWAS, bi-parental QTL mapping and transcription. These findings related to the genetic basis underlying the DCTN will provide the genetic theory in making appropriate decisions on field management, and in developing new varieties with high PN and ideal dynamic plant architecture.
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Affiliation(s)
- Xiaoqian Ma
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Fengmei Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
- School of Life Science and Technology, Xinxiang University, Henan, 453003, China
| | - Quan Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Haifeng Guo
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jianyin Xie
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Najeeb Ullah Khan
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhanying Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
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Gouda G, Gupta MK, Donde R, Kumar J, Parida M, Mohapatra T, Dash SK, Pradhan SK, Behera L. Characterization of haplotypes and single nucleotide polymorphisms associated with Gn1a for high grain number formation in rice plant. Genomics 2020; 112:2647-2657. [PMID: 32087244 DOI: 10.1016/j.ygeno.2020.02.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2019] [Revised: 01/07/2020] [Accepted: 02/18/2020] [Indexed: 01/03/2023]
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9
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Jia X, Yu L, Tang M, Tian D, Yang S, Zhang X, Traw MB. Pleiotropic changes revealed by in situ recovery of the semi-dwarf gene sd1 in rice. JOURNAL OF PLANT PHYSIOLOGY 2020; 248:153141. [PMID: 32143117 DOI: 10.1016/j.jplph.2020.153141] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 02/10/2020] [Accepted: 02/11/2020] [Indexed: 06/10/2023]
Abstract
The "Green Revolution" that dramatically reduced cultivar heights and sharply boosted rice production mid-century was achieved in large part through introgression of defective alleles of Semi-Dwarf 1 (SD1), which encodes a GA20ox oxidase involved in the final steps of the synthesis of bioactive gibberellin in rice. Here, we ask whether converting the defective sd1 version in a modern semi-dwarf cultivar back to wild-type SD1 in situ recovers ancestral plant traits, and more broadly, what it reveals about pleiotropic effects of this gene. We assess these effects of SD1 restoration in three independent recombinant lines recovered from F2 progeny of a cross between 93-11 and PA64s. We then used RNA-seq to dissect gene network changes that accompanied SD1 restoration. We report that this in situ restoration of wild-type SD1 nearly doubles plant height, increases total grain yield per panicle, and elongates the second-leaf length. Comparison of expression profiles reveals changes in key nodes of the gibberellin pathway, such as OsKO1 and OsGA2ox3, and more broadly in genes related to metabolic networks, defense response, and catabolic processes. Two JA-induced genes, RIR1b and OsPR1b, are extremely down-regulated after SD1 restoration, suggesting that SD1 restoration alters the balance between GA and JA to plant growth, at the cost of degrading the defense response. This in situ approach at the SD1 locus also provides a model example that is applicable to other systems and will further understanding of gene networks underlying high-yield traits in crops.
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Affiliation(s)
- Xianqing Jia
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Luyao Yu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Menglu Tang
- 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
| | - Sihai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Xiaohui Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China.
| | - M Brian Traw
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China.
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Xue H, Tian X, Zhang K, Li W, Qi Z, Fang Y, Li X, Wang Y, Song J, Li WX, Ning H. Mapping developmental QTL for plant height in soybean [Glycine max (L.) Merr.] using a four-way recombinant inbred line population. PLoS One 2019; 14:e0224897. [PMID: 31747415 PMCID: PMC6867651 DOI: 10.1371/journal.pone.0224897] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 10/23/2019] [Indexed: 12/03/2022] Open
Abstract
Plant height (PH) is an important trait in soybean, as taller plants may have higher yields but may also be at risk for lodging. Many genes act jointly to influence PH throughout development. To map the quantitative trait loci (QTL) controlling PH, we used the unconditional variable method (UVM) and conditional variable method (CVM) to analyze PH data for a four-way recombinant inbred line (FW-RIL) population derived from the cross of (Kenfeng14 × Kenfeng15) × (Heinong48 × Kenfeng19). We identified 7, 8, 16, 19, 15, 27, 17, 27, 22, and 24 QTL associated with PH at 10 developmental stages, respectively. These QTL mapped to 95 genomic regions. Among these QTL, 9 were detected using UVM and CVM, and 89 and 66 were only detected by UVM or CVM, respectively. In total, 36 QTL controlling PH were detected at multiple developmental stages and these made unequal contributions to genetic variation throughout development. Among 19 novel regions discovered in our study, 7 could explain over 10% of the phenotypic variation and contained only one single QTL. The unconditional and conditional QTL detected here could be used in molecular design breeding across the whole developmental procedure.
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Affiliation(s)
- Hong Xue
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
- Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Keshan,Heilongjiang, China
| | - Xiaocui Tian
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Kaixin Zhang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Wenbin Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Zhongying Qi
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Yanlong Fang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Xiyu Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Yue Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Jie Song
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
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11
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Zhang R, Yang H, Zhou Z, Shen B, Xiao J, Wang B. A high-density genetic map of Schima superba based on its chromosomal characteristics. BMC PLANT BIOLOGY 2019; 19:41. [PMID: 30683049 PMCID: PMC6347745 DOI: 10.1186/s12870-019-1655-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 01/16/2019] [Indexed: 05/31/2023]
Abstract
BACKGROUND Schima superba (Theaceae) is a popular woody tree in China. The obscure chromosomal characters of this species are a limitation in the development of high-density genetic linkage maps, which are valuable resources for molecular breeding and functional genomics. RESULTS We determined the chromosome number and the karyotype of S. superba as 2n = 36 = 36 m, which is consistent with the tribe Schimeae (n = 18). A high-density genetic map was constructed using genotyping by sequencing (GBS). A F1 full-sib with 116 individuals and their parents (LC31 × JO32) were sequenced on the Illumina HiSeq™ platform. Overall, 343.3 Gb of raw data containing 1,191,933,474 paired-end reads were generated. Based on this, 99,966 polymorphic SNP markers were developed from the parents, and 2209 markers were mapped onto the integrated genetic linkage map after data filtering and SNP genotyping. The map spanned 2076.24 cM and was distributed among 18 linkage groups. The average marker interval was 0.94 cM. A total of 168 quantitative trait loci (QTLs) for 14 growth traits were identified. CONCLUSIONS The chromosome number and karyotype of S. superba was 2n = 36 = 36 m and a linkage map with 2209 SNP markers was constructed to identify QTLs for growth traits. Our study provides a basis for molecular-assisted breeding and genomic studies, which will contribute towards the future research and genetic improvement of S. superba.
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Affiliation(s)
- Rui Zhang
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, 311400, China.
- Zhejiang Provincial Key Laboratory of Tree Breeding, Hangzhou, 311400, China.
| | - Hanbo Yang
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, 311400, China
- Zhejiang Provincial Key Laboratory of Tree Breeding, Hangzhou, 311400, China
- Sichuan Academy of Forestry, Chengdu, 610081, China
| | - Zhichun Zhou
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, 311400, China.
- Zhejiang Provincial Key Laboratory of Tree Breeding, Hangzhou, 311400, China.
| | - Bin Shen
- Longquan Academy of Forestry, Zhejiang, 323700, China
| | - Jijun Xiao
- Longquan Academy of Forestry, Zhejiang, 323700, China
| | - Bangshun Wang
- Longquan Academy of Forestry, Zhejiang, 323700, China
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12
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Chen GF, Wu RG, Li DM, Yu HX, Deng Z, Tian JC. Genomewide association study for seeding emergence and tiller number using SNP markers in an elite winter wheat population. J Genet 2017; 96:177-186. [PMID: 28360404 DOI: 10.1007/s12041-016-0731-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Seeding emergence and tiller number are the most important traits for wheat (Triticum aestivum L.) yield, but the inheritance of seeding emergence and tillering is poorly understood. We conducted a genomewide association study focussing on seeding emergence and tiller number at different growth stages with a panel of 205 elite winter wheat accessions. The population was genotyped with a high-density Illumina iSelect 90K SNPs assay. A total of 31 loci were found to be associated with seeding emergence rate (SER) and tiller number in different growth stages. Loci distributed among 12 chromosomes accounted for 5.35 to 11.33% of the observed phenotypic variation. With this information, 10 stable SNPs were identified for eventual development of cleaved amplified polymorphic sequence markers for SER and tiller number in different growth stages. Additionally, a set of elite alleles were identified, such as Ra_c14761_1348-T, which may increase SER by 13.35%, and Excalibur_c11045_236-A and BobWhite_c8436_391-T, which may increase the rate of available tillering by 14.78 and 8.47%, respectively. These results should provide valuable information for marker-assisted selection and parental selection in wheat breeding programmes.
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Affiliation(s)
- Guang Feng Chen
- State Key Laboratory of Crop Biology, Group of Quality Wheat Breeding of Shandong Agricultural University, Tai'an 271018, People's Republic of China.
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13
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Zhang N, Fan X, Cui F, Zhao C, Zhang W, Zhao X, Yang L, Pan R, Chen M, Han J, Ji J, Liu D, Zhao Z, Tong Y, Zhang A, Wang T, Li J. Characterization of the temporal and spatial expression of wheat (Triticum aestivum L.) plant height at the QTL level and their influence on yield-related traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2017; 130:1235-1252. [PMID: 28349175 DOI: 10.1007/s00122-017-2884-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 02/21/2017] [Indexed: 05/05/2023]
Abstract
The temporal and spatial expression patterns of stable QTL for plant height and their influences on yield were characterized. Plant height (PH) is a complex trait in wheat (Triticum aestivum L.) that includes the spike length (SL) and the internode lengths from the first to the fifth internode, which are counted from the top and abbreviated as FIRITL, SECITL, THIITL, FOUITL, and FIFITL, respectively. This study identified eight putative additive quantitative trait loci (QTL) for PH. In addition, unconditional and conditional QTL mapping were used to analyze the temporal and spatial expression patterns of five stable QTL for PH. qPh-3A mainly regulated SL, FIRITL, and FIFITL to affect PH during the booting-heading stage (BS-HS); qPh-3D regulated all internode lengths to affect PH, especially during the BS-HS; before HS, qPh-4B mainly affected FIRITL, SECITL, THIITL, and FOUITL and qPh-5A.1 mainly affected SECITL, THIITL, and FOUITL to regulate PH; and qPh-6B mainly regulated FIRITL to affect the PH after the booting stage (BS). qPhdv-4B, a QTL for the response of PH to nitrogen stress, was stable and co-localized with qPh-4B. All five stable QTL, except for qPh-3A, were related to the 1000 kernel weight and yield per plant. Regions of qPh-3A, qPh-3D, qPh-4B, qPh-5A.1, and qPh-6B showed synteny to parts of rice chromosomes 1, 1, 3, 9, and 2, respectively. Based on comparative genomics analysis, Rht-B1b was cloned and mapped in the CI of qPh-4B. This report provides useful information for fine mapping of the stable QTL for PH and the genetic improvement of wheat plant type.
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Affiliation(s)
- Na Zhang
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
- University of Chinese Academy of Sciences, Beijing, 10049, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Fa Cui
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China.
- Genetic Improvement Centre of Agricultural and Forest Crops, College of Agriculture, Ludong University, Yantai, 264025, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Chunhua Zhao
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
| | - Wei Zhang
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xueqiang Zhao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Lijuan Yang
- Xinxiang Academy of Agricultural Sciences, Xinxiang, 453000, China
| | - Ruiqing Pan
- University of Chinese Academy of Sciences, Beijing, 10049, China
| | - Mei Chen
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
- University of Chinese Academy of Sciences, Beijing, 10049, China
| | - Jie Han
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
- University of Chinese Academy of Sciences, Beijing, 10049, China
| | - Jun Ji
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Dongcheng Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zongwu Zhao
- Xinxiang Academy of Agricultural Sciences, Xinxiang, 453000, China
| | - Yiping Tong
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Aimin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Junming Li
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050022, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Chinese Academy of Sciences, Beijing, 100101, China.
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14
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Sasaki K, Fujita D, Koide Y, Lumanglas PD, Gannaban RB, Tagle AG, Obara M, Fukuta Y, Kobayashi N, Ishimaru T. Fine mapping of a quantitative trait locus for spikelet number per panicle in a new plant type rice and evaluation of a near-isogenic line for grain productivity. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2693-2702. [PMID: 28582550 PMCID: PMC5853308 DOI: 10.1093/jxb/erx128] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Accepted: 04/13/2017] [Indexed: 05/20/2023]
Abstract
Total spikelet number per panicle (TSN) is one of the determinants of grain productivity in rice (Oryza sativa L.). In this study, we attempted to detect quantitative trait loci (QTLs) for TSN in the introgression lines with high TSN, derived from the cross of Indica Group variety IR 64 with new plant type lines. Two QTLs were detected on the long arm of chromosome 12: qTSN12.1 in the BC4F2 population of YTH63/IR 64 and qTSN12.2 in the BC4F3 population of YTH83/IR 64. TSN of the main tiller was significantly higher in near-isogenic lines (NILs) for qTSN12.1 (IR 64-NIL1; 188.6) and for qTSN12.2 (IR 64-NIL12; 199.4) than in IR 64 (141.2), owing to a significant increase in both primary and secondary branch numbers. These results suggest the critical function of these QTLs in the promotion of rachis branching at the panicle formation stage. Fine mapping of qTSN12.2 revealed six candidate genes in a 92-kb region of the Nipponbare reference genome sequence between flanking markers RM28746 and RM28753. Detailed phenotyping of agronomic traits of IR 64-NIL12 carrying qTSN12.2 showed drastic changes in plant architecture: this line had lower panicle number, longer culm, and longer and wider leaves compared with IR 64. Percentage of fertility and 1000-grain weight tended to be greater, and grain yield per square meter was also greater in IR 64-NIL12 than in IR 64. The newly identified QTLs will be useful for genetic improvement of the yield potential of Indica Group varieties. The markers tightly linked to qTSN12.2 are available for marker-assisted breeding.
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Affiliation(s)
- Kazuhiro Sasaki
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
- Graduate School of Agricultural and Life Sciences, Institute of Sustainable Agro-ecosystem Services (ISAS), The University of Tokyo, Midoricho, Nishitokyo, Tokyo, Japan
| | - Daisuke Fujita
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
- Faculty of Agriculture, Saga University, Honjo-machi, Saga, Japan
| | - Yohei Koide
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
- Research Faculty of Agriculture, Hokkaido University, Kita-9 Nishi-9, Kita-ku, Sapporo, Japan
| | | | - Ritchel B Gannaban
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
| | - Analiza G Tagle
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
| | - Mitsuhiro Obara
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
| | - Yoshimichi Fukuta
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
| | - Nobuya Kobayashi
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
- National Institute of Crop Science (NICS), NARO, Kannondai, Tsukuba, Ibaraki, Japan
| | - Tsutomu Ishimaru
- Japan International Research Center for Agricultural Sciences (JIRCAS), Ohwashi, Tsukuba, Ibaraki, Japan
- International Rice Research Institute (IRRI), DA, Metro Manila, Philippines
- Central Region Agricultural Research Center (CARC), National Agriculture and Food Research Organization (NARO), Inada, Joetsu, Niigata, Japan
- Correspondence:
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15
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Yang D, Li M, Liu Y, Chang L, Cheng H, Chen J, Chai S. Identification of Quantitative Trait Loci and Water Environmental Interactions for Developmental Behaviors of Leaf Greenness in Wheat. FRONTIERS IN PLANT SCIENCE 2016; 7:273. [PMID: 27014298 PMCID: PMC4782216 DOI: 10.3389/fpls.2016.00273] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Accepted: 02/21/2016] [Indexed: 05/30/2023]
Abstract
The maintenance of leaf greenness in wheat, highly responsible for yield potential and resistance to drought stress, has been proved to be quantitatively inherited and susceptible to interact with environments by traditional genetic analysis. In order to further dissect the developmental genetic behaviors of flag leaf greenness under terminal drought, unconditional and conditional QTL mapping strategies were performed with a mixed linear model in 120 F8-derived recombinant inbred lines (RILs) from two Chinese common wheat cultivars (Longjian 19 × Q9086) in different water environments. A total of 65 additive QTLs (A-QTLs) and 42 pairs of epistatic QTLs (AA-QTLs) were identified as distribution on almost all 21 chromosomes except 5A, explaining from 0.24 to 3.29 % of the phenotypic variation. Of these, 22 A-QTLs and 25 pairs of AA-QTLs were common in two sets of mapping methods but the others differed. These putative QTLs were essentially characteristic of time- and environmentally-dependent expression patterns. Indeed some loci were expressed at two or more stages, while no single QTL was continually active through whole measuring duration. More loci were detected in early growth periods but most of QTL × water environment interactions (QEIs) happened in mid-anaphase, where drought stress was more conducted with negative regulation on QTL expressions. Compared to other genetic components, epistatic effects and additive QEIs effects could be predominant in regulating phenotypic variations during the ontogeny of leaf greenness. Several QTL cluster regions were suggestive of tight linkage or expression pleiotropy in the inheritance of these traits. Some reproducibly-expressed QTLs or common loci consistent with previously detected would be useful to the genetic improvement of staygreen types in wheat through MAS, especially in water-deficit environments.
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Affiliation(s)
- Delong Yang
- Gansu Provincial Key Lab of Aridland Crop Science/School of Life Science and Technology, Gansu Agricultural UniversityLanzhou, China
| | - Mengfei Li
- Gansu Provincial Key Lab of Aridland Crop Science/School of Life Science and Technology, Gansu Agricultural UniversityLanzhou, China
| | - Yuan Liu
- Gansu Provincial Key Lab of Aridland Crop Science/School of Life Science and Technology, Gansu Agricultural UniversityLanzhou, China
| | - Lei Chang
- School of Agronomy, Gansu Agricultural UniversityLanzhou, China
| | - Hongbo Cheng
- Gansu Provincial Key Lab of Aridland Crop Science/School of Life Science and Technology, Gansu Agricultural UniversityLanzhou, China
| | - Jingjing Chen
- Gansu Provincial Key Lab of Aridland Crop Science/School of Life Science and Technology, Gansu Agricultural UniversityLanzhou, China
| | - Shouxi Chai
- School of Agronomy, Gansu Agricultural UniversityLanzhou, China
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16
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Wang X, Wang H, Long Y, Liu L, Zhao Y, Tian J, Zhao W, Li B, Chen L, Chao H, Li M. Dynamic and comparative QTL analysis for plant height in different developmental stages of Brassica napus L. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1175-92. [PMID: 25796183 DOI: 10.1007/s00122-015-2498-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Accepted: 03/10/2015] [Indexed: 05/04/2023]
Abstract
This report describes a dynamic QTL analysis for plant height at various stages using a large doubled haploid population and performs a QTL comparison between different populations in Brassica napus. Plant height (PH) not only plays an important role in determining plant architecture, but is also an important character related to yield. The process of determining PH occurs through a series of steps; however, no studies have focused on developmental behavior factors affecting PH in Brassica napus. In the present study, KN DH, a large doubled haploid population containing 348 lines was used for a dynamic quantitative trait locus (QTL) analysis for PH in six experiments. In all, 20 QTLs were identified at maturity, whereas 50 QTLs were detected by conditional m apping method and the same number was identified by unconditional mapping strategies. Interestingly, five unconditional QTLs ucPH.A2-2, ucPH.A3-2, ucPH.C5-1, ucPH.C6-2 and ucPH.C6-3 were identified that were consistent over the all growth stages of one or two particular experiments, and one conditional QTL cPH.A2-3 was expressed throughout the entire growth process in one experiment. A total of 70 QTLs were obtained after combining QTLs identified at maturity, by conditional and unconditional mapping strategies, in which 25 showed opposite genetic effects in different periods/stages and experiments. A consensus map containing 1357 markers was constructed to compare QTLs identified in the KN population with five previously mapped populations. Alignment of the QTLs detected in different populations onto the consensus map showed that 27 were repeatedly detected in different genetic backgrounds. These findings will enhance our understanding of the genetic control of PH regulation in B. napus, and will be useful for rapeseed genetic manipulation through molecular marker-assisted selection.
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Affiliation(s)
- Xiaodong Wang
- College of Life Science and Technology, Key Laboratory of Molecular Biology, Physics of Ministry of Education, Huazhong University of Science and Technology, Wuhan, 430074, China
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17
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Pootakham W, Jomchai N, Ruang-Areerate P, Shearman JR, Sonthirod C, Sangsrakru D, Tragoonrung S, Tangphatsornruang S. Genome-wide SNP discovery and identification of QTL associated with agronomic traits in oil palm using genotyping-by-sequencing (GBS). Genomics 2015; 105:288-95. [PMID: 25702931 DOI: 10.1016/j.ygeno.2015.02.002] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Revised: 02/03/2015] [Accepted: 02/12/2015] [Indexed: 11/24/2022]
Abstract
Oil palm has become one of the most important oil crops in the world. Marker-assisted selections have played a pivotal role in oil palm breeding programs. Here, we report the use of genotyping-by-sequencing (GBS) approach for a large-scale SNP discovery and genotyping of a mapping population. Reduced representation libraries of 108 F2 progeny were sequenced and a total of 524 million reads were obtained. We detected 21,471 single nucleotide substitutions, most of which (62.6%) represented transition events. Of 3417 fully informative SNP markers, we were able to place 1085 on a linkage map, which spanned 1429.6 cM and had an average of one marker every 1.26 cM. Three QTL affecting trunk height were detected on LG 10, 14 and 15, whereas a single QTL associated with fruit bunch weight was identified on LG 3. The use of GBS approach proved to be rapid, cost-effective and highly reproducible in this species.
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Affiliation(s)
- Wirulda Pootakham
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Nukoon Jomchai
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Panthita Ruang-Areerate
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Jeremy R Shearman
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Chutima Sonthirod
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Duangjai Sangsrakru
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Somvong Tragoonrung
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
| | - Sithichoke Tangphatsornruang
- National Center for Genetic Engineering and Biotechnology, 113 Thailand Science Park, Pathum Thani 12120, Thailand.
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18
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Zhang P, Liu X, Tong H, Lu Y, Li J. Association mapping for important agronomic traits in core collection of rice (Oryza sativa L.) with SSR markers. PLoS One 2014; 9:e111508. [PMID: 25360796 PMCID: PMC4216065 DOI: 10.1371/journal.pone.0111508] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 09/30/2014] [Indexed: 12/25/2022] Open
Abstract
Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.
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Affiliation(s)
- Peng Zhang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Xiangdong Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
| | - Hanhua Tong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yonggen Lu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
| | - Jinquan Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
- Department of Plant Breeding and Genetics, Max Planck Institute for Plant Breeding Research, Cologne, Germany
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Tan C, Han Z, Yu H, Zhan W, Xie W, Chen X, Zhao H, Zhou F, Xing Y. QTL scanning for rice yield using a whole genome SNP array. J Genet Genomics 2013; 40:629-38. [PMID: 24377869 DOI: 10.1016/j.jgg.2013.06.009] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Revised: 05/29/2013] [Accepted: 06/20/2013] [Indexed: 01/04/2023]
Abstract
High-throughput SNP genotyping is widely used for plant genetic studies. Recently, a RICE6K SNP array has been developed based on the Illumina Bead Array platform and Infinium SNP assay technology for genome-wide evaluation of allelic variations and breeding applications. In this study, the RICE6K SNP array was used to genotype a recombinant inbred line (RIL) population derived from the cross between the indica variety, Zhenshan 97, and the japonica variety, Xizang 2. A total of 3324 SNP markers of high quality were identified and were grouped into 1495 recombination bins in the RIL population. A high-density linkage map, consisting of the 1495 bins, was developed, covering 1591.2 cM and with average length of 1.1 cM per bin. Segregation distortions were observed in 24 regions of the 11 chromosomes in the RILs. One half of the distorted regions contained fertility genes that had been previously reported. A total of 23 QTLs were identified for yield. Seven QTLs were firstly detected in this study. The positive alleles from about half of the identified QTLs came from Zhenshan 97 and they had lower phenotypic values than Xizang 2. This indicated that favorable alleles for breeding were dispersed in both parents and pyramiding favorable alleles could develop elite lines. The size of the mapping population for QTL analysis using high throughput SNP genotyping platform is also discussed.
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Affiliation(s)
- Cong Tan
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhongmin Han
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Huihui Yu
- Life Science and Technology Center, China National Seed Group Co., Ltd., Wuhan 430075, China
| | - Wei Zhan
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Xun Chen
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Hu Zhao
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Fasong Zhou
- Life Science and Technology Center, China National Seed Group Co., Ltd., Wuhan 430075, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China.
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20
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Xu H, Zhu J. Statistical approaches in QTL mapping and molecular breeding for complex traits. ACTA ACUST UNITED AC 2012. [DOI: 10.1007/s11434-012-5107-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Li Z, Peng T, Xie Q, Han S, Tian J. Mapping of QTL for tiller number at different stages of growth in wheat using double haploid and immortalized F2 populations. J Genet 2011; 89:409-15. [PMID: 21273691 DOI: 10.1007/s12041-010-0059-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Effective tiller number is one of the most important traits for wheat (Triticum aestivum L.) yield, but the inheritance of tillering is poorly understood. A set of 168 doubled haploid (DH) lines derivatives of a cross between two winter wheat cultivars (Huapei 3 and Yumai 57), and an immortalized F(2) (IF(2)) population generated by randomly permutated intermating of these DHs were investigated, and QTLs of tillering related to the maximum tillering of pre-winter (MTW), maximum tillering in spring (MTS), and effective tillering in harvest (ETH) were mapped. Phenotypic data were collected for the two populations from two different environments. Using inclusive composite interval mapping (ICIM), a total of 9 and 18 significant QTL were detected across environments for tillering in the DH and IF(2) populations, respectively. Four QTLs were common between two populations. A major QTL located on the 5D chromosome with the allele originating from Yumai 57 was detected and increased 1.92 and 3.55 tillers in MTW and MTS, respectively. QTLs (QMts6D, QEth6D) having a neighbouring marker interval at Xswes679.1 and Xcfa2129 on chromosome 6D was detected in MTS and ETH. These results provide a better understanding of the genetic factors for selectively expressing the control of tiller number in different growth stages and facilitate marker-assisted selection strategy in breeding.
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Affiliation(s)
- Zhuokun Li
- State Key Laboratory of Crop Biology, Shandong Agricultural University, No. 61, Daizong Road, Tai'an 271018, People's Republic of China
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Wu X, Wang Z, Chang X, Jing R. Genetic dissection of the developmental behaviours of plant height in wheat under diverse water regimes. JOURNAL OF EXPERIMENTAL BOTANY 2010; 61:2923-37. [PMID: 20497970 PMCID: PMC3298886 DOI: 10.1093/jxb/erq117] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2009] [Revised: 04/03/2010] [Accepted: 04/07/2010] [Indexed: 05/18/2023]
Abstract
Plant height (PH), a crucial trait related to yield potential in crop plants, is known to be typically quantitatively inherited. However, its full expression can be inhibited by a limited water supply. In this study, the genetic basis of the developmental behaviour of PH was assessed in a 150-line wheat (Triticum aestivum L.) doubled haploid population (Hanxuan 10 x Lumai 14) grown in 10 environments (year x site x water regime combinations) by unconditional and conditional quantitative trait locus (QTL) analyses in a mixed linear model. Genes that were expressed selectively during ontogeny were identified. No single QTL was continually active in all periods of PH growth, and QTLs with additive effects (A-QTLs) expressed in the period S1|S0 (the period from the original point to the jointing stage) formed a foundation for PH development. Additive main effects (a effects), which were mostly expressed in S1|S0, were more important than epistatic main effects (aa effects) or QTL x environment interaction (QE) effects, suggesting that S1|S0 was the most significant development period affecting PH growth. A few QTLs, such as QPh.cgb-6B.7, showed high adaptability for water-limited environments. Many QTLs, including four A-QTLs (QPh.cgb-2D.1, QPh.cgb-4B.1, QPh.cgb-4D.1, and QPh.cgb-5A.7) coincident with previously identified reduced height (Rht) genes (Rht8, Rht1, Rht2, and Rht9), interacted with more than one other QTL, indicating that the genetic architecture underlying PH development is a network of genes with additive and epistatic effects. Therefore, based on multilocus combinations in S1|S0, superior genotypes were predicted for guiding improvements in breeding for PH.
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Affiliation(s)
| | | | | | - Ruilian Jing
- National Key Facility for Crop Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm and Biotechnology, Ministry of Agriculture/Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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