1
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Veisi S, Sabouri A, Abedi A. Meta-analysis of QTLs and candidate genes associated with seed germination in rice ( Oryza sativa L.). PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2022; 28:1587-1605. [PMID: 36389095 PMCID: PMC9530108 DOI: 10.1007/s12298-022-01232-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 08/18/2022] [Accepted: 09/16/2022] [Indexed: 06/12/2023]
Abstract
Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination. Supplementary Information The online version contains supplementary material available at 10.1007/s12298-022-01232-1.
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Affiliation(s)
- Sheida Veisi
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Atefeh Sabouri
- Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran
| | - Amin Abedi
- Department of Plant Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
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2
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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: 1.3] [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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3
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Morota G, Jarquin D, Campbell MT, Iwata H. Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data. Methods Mol Biol 2022; 2539:269-296. [PMID: 35895210 DOI: 10.1007/978-1-0716-2537-8_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new technologies also bring new challenges in quantitative genetics, namely, a need for the development of robust frameworks that can accommodate these high-dimensional data. In this chapter, we describe methods for the statistical analysis of high-throughput phenotyping (HTP) data with the goal of enhancing the prediction accuracy of genomic selection (GS). Following the Introduction in Sec. 1, Sec. 2 discusses field-based HTP, including the use of unoccupied aerial vehicles and light detection and ranging, as well as how we can achieve increased genetic gain by utilizing image data derived from HTP. Section 3 considers extending commonly used GS models to integrate HTP data as covariates associated with the principal trait response, such as yield. Particular focus is placed on single-trait, multi-trait, and genotype by environment interaction models. One unique aspect of HTP data is that phenomics platforms often produce large-scale data with high spatial and temporal resolution for capturing dynamic growth, development, and stress responses. Section 4 discusses the utility of a random regression model for performing longitudinal modeling. The chapter concludes with a discussion of some standing issues.
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Affiliation(s)
- Gota Morota
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
| | - Diego Jarquin
- Agronomy Department, University of Florida, Gainesville, FL, USA
| | - Malachy T Campbell
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
| | - Hiroyoshi Iwata
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan
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4
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Li G, Yang Q, Li D, Zhang T, Yang L, Qin J, Tang B, Guo X, Cao Y, You S, Li Z, Luo J, Wan X, Liu Y, Huang F, Guo L, Jiang K, Zheng J. Genome‐wide SNP discovery and QTL mapping for economic traits in a recombinant inbred line of
Oryza sativa. Food Energy Secur 2021. [DOI: 10.1002/fes3.274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Gengmi Li
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Qianhua Yang
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Deqiang Li
- Rice Research Institute/College of Agronomy Sichuan Agricultural University Chengdu China
| | - Tao Zhang
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Li Yang
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Jian Qin
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Bin Tang
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Xiaojiao Guo
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Yingjiang Cao
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Shumei You
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Zhaoxiang Li
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Jing Luo
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Xianqi Wan
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Ying Liu
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Fu Huang
- Rice Research Institute/College of Agronomy Sichuan Agricultural University Chengdu China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology China National Rice Research Institute, Chinese Academy of Agricultural Sciences Hangzhou China
| | - Kaifeng Jiang
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
| | - Jiakui Zheng
- Key Laboratory of Southwest Rice Biology and Genetic Breeding, Ministry of Agriculture/Luzhou Branch of National Rice Improvement Center Rice and Sorghum Research Institute, Sichuan Academy of Agricultural Sciences Deyang China
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Zhou H, Yang W, Ma S, Luan X, Zhu H, Wang A, Huang C, Rong B, Dong S, Meng L, Wang S, Zhang G, Liu G. Unconditional and conditional analysis of epistasis between tillering QTLs based on single segment substitution lines in rice. Sci Rep 2020; 10:15912. [PMID: 32985566 PMCID: PMC7523009 DOI: 10.1038/s41598-020-73047-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 09/07/2020] [Indexed: 11/08/2022] Open
Abstract
Epistasis plays an important role in manipulating rice tiller number, but epistatic mechanism still remains a challenge. Here we showed the process of epistatic analysis between tillering QTLs. A half diallel mating scheme was conducted based on 6 single segment substitution lines and 9 dual segment pyramiding lines to allow the analysis of 4 epistatic components. Additive-additive, additive-dominance, dominance-additive, and dominance-dominance epistatic effects were estimated at 9 stages of development via unconditional QTL analysis simultaneously. Unconditional QTL effect (QTL cumulative effect before a certain stage) was then divided into several conditional QTL components (QTL net effect in a certain time interval). The results indicated that epistatic interaction was prevalent, all QTL pairs harboring epistasis and one QTL always interacting with other QTLs in various component ways. Epistatic effects were dynamic, occurring mostly within 14d and 21-35d after transplant and exhibited mainly negative effects. The genetic and developmental mechanism on several tillering QTLs was further realized and perhaps was useful for molecular pyramiding breeding and heterosis utilization for improving plant architecture.
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Affiliation(s)
- Huaqian Zhou
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Weifeng Yang
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Shuaipeng Ma
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
- Guangzhou Experimental Station, Chinese Academy of Tropical Agricultural Sciences, Guangzhou, 510642, People's Republic of China
| | - Xin Luan
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Haitao Zhu
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
| | - Aimin Wang
- Zhuhai Modern Agriculture Development Center, Zhuhai, 519000, People's Republic of China
| | - Congling Huang
- Zhuhai Modern Agriculture Development Center, Zhuhai, 519000, People's Republic of China
| | - Biao Rong
- Zhuhai Modern Agriculture Development Center, Zhuhai, 519000, People's Republic of China
| | - Shangzhi Dong
- Zhuhai Modern Agriculture Development Center, Zhuhai, 519000, People's Republic of China
| | - Lijun Meng
- Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 440307, People's Republic of China.
| | - Shaokui Wang
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
| | - Guiquan Zhang
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
| | - Guifu Liu
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China.
- Zhuhai Modern Agriculture Development Center, Zhuhai, 519000, People's Republic of China.
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6
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Dimaano NGB, Ali J, Mahender A, Sta. Cruz PC, Baltazar AM, Diaz MGQ, Pang YL, Acero BL, Li Z. Identification of quantitative trait loci governing early germination and seedling vigor traits related to weed competitive ability in rice. EUPHYTICA: NETHERLANDS JOURNAL OF PLANT BREEDING 2020; 216:159. [PMID: 33029032 PMCID: PMC7510932 DOI: 10.1007/s10681-020-02694-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Accepted: 09/04/2020] [Indexed: 05/10/2023]
Abstract
Weed competitive ability (WCA) is vital for the improvement of grain yield under direct-seeded and aerobic rice ecosystems where weeds are a major limiting factor. Early seed germination (ESG) and early seedling vigor (ESV) are the crucial traits for WCA. This study attempted to map the quantitative trait loci (QTLs) and hotspot regions governing ESG and ESV traits. A total of 167 BC1F5 selective introgression lines developed from an early backcross population involving Weed Tolerant Rice 1 (WTR-1) as the recipient parent and Y-134 as the donor parent were phenotyped for ESG and ESV traits. Analysis of variance revealed significant differences in ESG-related traits except for root length and in ESV-related traits except for plant height at 7 days after sowing. A total of 677-high quality single nucleotide polymorphism (SNP) markers were used to analyze the marker-trait association from a 6 K SNP genotyping array. Forty-three QTLs were identified on all chromosomes, except on chromosomes 4 and 8. Thirty QTLs were contributed by a desirable allele from Y-134, whereas 13 QTLs were from WTR-1. Twenty-eight of the identified genetic loci associated with ESG and ESV traits were novel. Two QTL hotspot regions were mapped on chromosomes 11 and 12. The genomic regions of QTL hotspots were fine-tuned and a total of 13 putative candidate genes were discovered on chromosomes 11 and 12 collectively. The mapped QTLs will be useful in advancing the marker aided-selection schemes and breeding programs for the development of rice cultivars with WCA traits.
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Affiliation(s)
| | - Jauhar Ali
- Rice Breeding Platform, International Rice Research Institute (IRRI), 4031 Los Baños, Laguna Philippines
| | - Anumalla Mahender
- Rice Breeding Platform, International Rice Research Institute (IRRI), 4031 Los Baños, Laguna Philippines
| | - Pompe C. Sta. Cruz
- University of the Philippines Los Baños, 4031 Los Baños, Laguna Philippines
| | - Aurora M. Baltazar
- University of the Philippines Los Baños, 4031 Los Baños, Laguna Philippines
| | | | - Yun Long Pang
- State Key Laboratory of Crop Biology, College of Agronomy, Shandong Agricultural University, Taian, 271018 People’s Republic of China
| | - Bart L. Acero
- Rice Breeding Platform, International Rice Research Institute (IRRI), 4031 Los Baños, Laguna Philippines
| | - Zhikang Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081 People’s Republic of China
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7
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Miao C, Xu Y, Liu S, Schnable PS, Schnable JC. Increased Power and Accuracy of Causal Locus Identification in Time Series Genome-wide Association in Sorghum. PLANT PHYSIOLOGY 2020; 183:1898-1909. [PMID: 32461303 PMCID: PMC7401099 DOI: 10.1104/pp.20.00277] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 05/20/2020] [Indexed: 05/18/2023]
Abstract
The phenotypes of plants develop over time and change in response to the environment. New engineering and computer vision technologies track these phenotypic changes. Identifying the genetic loci regulating differences in the pattern of phenotypic change remains challenging. This study used functional principal component analysis (FPCA) to achieve this aim. Time series phenotype data were collected from a sorghum (Sorghum bicolor) diversity panel using a number of technologies including conventional color photography and hyperspectral imaging. This imaging lasted for 37 d and centered on reproductive transition. A new higher density marker set was generated for the same population. Several genes known to control trait variation in sorghum have been previously cloned and characterized. These genes were not confidently identified in genome-wide association analyses at single time points. However, FPCA successfully identified the same known and characterized genes. FPCA analyses partitioned the role these genes play in controlling phenotypes. Partitioning was consistent with the known molecular function of the individual cloned genes. These data demonstrate that FPCA-based genome-wide association studies can enable robust time series mapping analyses in a wide range of contexts. Moreover, time series analysis can increase the accuracy and power of quantitative genetic analyses.
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Affiliation(s)
- Chenyong Miao
- Quantitative Life Science Initiative, Center for Plant Science Innovation, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska 68588
| | - Yuhang Xu
- Department of Applied Statistics and Operations Research, Bowling Green State University, Bowling Green, Ohio 43403
| | - Sanzhen Liu
- Department of Plant Pathology, Kansas State University, Manhattan, Kansas 66506
| | | | - James C Schnable
- Quantitative Life Science Initiative, Center for Plant Science Innovation, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, Nebraska 68588
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8
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Yu L, Gao B, Li Y, Tan W, Li M, Zhou L, Peng C, Xiao L, Liu Y. The synthesis of strigolactone is affected by endogenous ascorbic acid in transgenic rice for l-galactono-1, 4-lactone dehydrogenase suppressed or overexpressing. JOURNAL OF PLANT PHYSIOLOGY 2020; 246-247:153139. [PMID: 32114415 DOI: 10.1016/j.jplph.2020.153139] [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: 08/28/2019] [Revised: 02/16/2020] [Accepted: 02/17/2020] [Indexed: 06/10/2023]
Abstract
Rice tillering, which determines the panicle number per plant, is an important agronomic trait for grain production. In higher plants, ascorbic acid (Asc) plays a major role in ROS-scavenging activity. l-Galactono-1, 4-lactone dehydrogenase (GalLDH, EC1.3.2.3) is an enzyme that catalyzes the last step of Asc biosynthesis in plants. Previously, we have reported that homozygous L-GalLDH-suppressed transgenic rice plants (GI) display a reduced tiller number and a lower level of foliar carotenoids (Car) compared with wild type. Strigolactones (SL), which play an important role in the suppression of shoot branching, are synthesized in the roots of rice plant using Car as substrates. In this paper, the relationship between Asc, SL, the accumulation of H2O2, changes in antioxidant capacity, enzyme activities, and gene transcriptions related to the synthesis of SL were analyzed in transgenic rice plants for L-GalLDH suppressed (GI-1 and GI-2) and overexpressing (GO-2). The results showed that the altered level of Asc in the L-GalLDH transgenic rice plants leads to a change in redox homeostasis, resulting in a marked accumulation of H2O2 and decreased antioxidant capacity in GI-1 and GI-2, but lower H2O2 content and increased antioxidant capacity in GO-2. Meanwhile, the altered level of Asc also leads to altered enzyme activities and gene transcript abundances related to SL synthesis in L-GalLDH transgenics. These observations support the conclusion that Asc influences tiller number in the L-GalLDH transgenics by affecting H2O2 accumulation and antioxidant capacity, and altering those enzyme activities and gene transcript abundances related to SL synthesis.
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Affiliation(s)
- Le Yu
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Bin Gao
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Yelin Li
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Weijian Tan
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Mingkang Li
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Liping Zhou
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China
| | - Changlian Peng
- College of Life Sciences, South China Normal University, 510631, Guangzhou, China
| | - Langtao Xiao
- Hunan Provincial Key Laboratory of Phytohormones and Growth Development, Hunan Agricultural University, Changsha, Hunan, 410128, China
| | - Yonghai Liu
- College of Life Sciences, Zhaoqing University, Zhaoqing, 526061, Guangdong, China.
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9
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Dong Q, Zhang K, Sun X, Tian X, Qi Z, Fang Y, Li X, Wang Y, Song J, Wang J, Yang C, Jiang S, Li WX, Ning H. Mapping QTL underlying plant height at three development stages and its response to density in soybean [ Glycine max (L.) Merri.]. BIOTECHNOL BIOTEC EQ 2020. [DOI: 10.1080/13102818.2020.1758594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
Affiliation(s)
- Quanzhong Dong
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
- Soybean Research Institute, Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Keshan, Heilongjiang, PR China
| | - Kaixin Zhang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Xu Sun
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Xiaocui Tian
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Zhongying Qi
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Yanlong Fang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Xiyu Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Yue Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Jie Song
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Jiajing Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Chang Yang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Sitong Jiang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Department of Agronomy, Soybean Research Institute, Northeast Agricultural University, Harbin, Heilongjiang, PR China
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10
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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: 1.8] [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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Chen J, Zhang L, Zhu M, Han L, Lv Y, Liu Y, Li P, Jing H, Cai H. Non-dormant Axillary Bud 1 regulates axillary bud outgrowth in sorghum. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2018; 60:938-955. [PMID: 29740955 DOI: 10.1111/jipb.12665] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 05/04/2018] [Indexed: 06/08/2023]
Abstract
Tillering contributes to grain yield and plant architecture and therefore is an agronomically important trait in sorghum (Sorghum bicolor). Here, we identified and functionally characterized a mutant of the Non-dormant Axillary Bud 1 (NAB1) gene from an ethyl methanesulfonate-mutagenized sorghum population. The nab1 mutants have increased tillering and reduced plant height. Map-based cloning revealed that NAB1 encodes a carotenoid-cleavage dioxygenase 7 (CCD7) orthologous to rice (Oryza sativa) HIGH-TILLERING DWARF1/DWARF17 and Arabidopsis thaliana MORE AXILLARY BRANCHING 3. NAB1 is primarily expressed in axillary nodes and tiller bases and NAB1 localizes to chloroplasts. The nab1 mutation causes outgrowth of basal axillary buds; removing these non-dormant basal axillary buds restored the wild-type phenotype. The tillering of nab1 plants was completely suppressed by exogenous application of the synthetic strigolactone analog GR24. Moreover, the nab1 plants had no detectable strigolactones and displayed stronger polar auxin transport than wild-type plants. Finally, RNA-seq showed that the expression of genes involved in multiple processes, including auxin-related genes, was significantly altered in nab1. These results suggest that NAB1 functions in strigolactone biosynthesis and the regulation of shoot branching via an interaction with auxin transport.
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Affiliation(s)
- Jun Chen
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Limin Zhang
- Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
| | - Mengjiao Zhu
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Lijie Han
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Ya Lv
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Yishan Liu
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Pan Li
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
| | - Haichun Jing
- Key Laboratory of Plant Resources, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- Inner Mongolia Research Centre for Practaculture, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hongwei Cai
- Department of Plant Genetics, Breeding and Seed Science, China Agricultural University; Beijing Key Laboratory of Crop Genetic Improvement; Laboratory of Crop Heterosis and Utilization, MOE; Beijing 100193, China
- Forage Crop Research Institute, Japan Grassland Agricultural and Forage Seed Association, 388-5 Higashiakada, Nasushiobara, Tochigi 329-2742, Japan
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12
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Liu C, Zheng S, Gui J, Fu C, Yu H, Song D, Shen J, Qin P, Liu X, Han B, Yang Y, Li L. Shortened Basal Internodes Encodes a Gibberellin 2-Oxidase and Contributes to Lodging Resistance in Rice. MOLECULAR PLANT 2018; 11:288-299. [PMID: 29253619 DOI: 10.1016/j.molp.2017.12.004] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Revised: 12/08/2017] [Accepted: 12/08/2017] [Indexed: 05/05/2023]
Abstract
Breeding semi-dwarf varieties to improve lodging resistance has been proven to be enormously successful in increasing grain yield since the advent of the "green revolution." However, the breeding of the majority of semi-dwarf rice varieties in Asia has been dependent mainly on genetic introduction of the mutant alleles of SD1, which encodes a gibberellin (GA) 20-oxidase, OsGA20ox2, for catalyzing GA biosynthesis. Here, we report a new rice lodging-resistance gene, Shortened Basal Internodes (SBI), which encodes a gibberellin 2-oxidase and specifically controls the elongation of culm basal internodes through deactivating GA activity. SBI is predominantly expressed in culm basal internodes. Genetic analyses indicate that SBI is a semi-dominant gene affecting rice height and lodging resistance. SBI allelic variants display different activities and are associated with the height of rice varieties. Breeding with higher activity of the SBI allele generates new rice varieties with improved lodging resistance and increased yield. The discovery of the SBI provides a desirable gene resource for producing semi-dwarf rice phenotypes and offers an effective strategy for breeding rice varieties with enhanced lodging resistance and high yield.
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Affiliation(s)
- Chang Liu
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Shuai Zheng
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Jinshan Gui
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Chenjian Fu
- Yuan Longping Agriculture High-Tech Co., Ltd., Hunan 410001, China
| | - Hasi Yu
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Dongliang Song
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Junhui Shen
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Peng Qin
- Yuan Longping Agriculture High-Tech Co., Ltd., Hunan 410001, China
| | | | - Bin Han
- National Center of Plant Gene Research and CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200233, China
| | - Yuanzhu Yang
- Yuan Longping Agriculture High-Tech Co., Ltd., Hunan 410001, China; Hunan Ava Seed Research Institute, Hunan 410119, China; Hunan Engineering Laboratory for Disease and Insect-Resistant Rice Breeding, Hunan 410119, China.
| | - Laigeng Li
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China.
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13
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Feldman MJ, Paul RE, Banan D, Barrett JF, Sebastian J, Yee MC, Jiang H, Lipka AE, Brutnell TP, Dinneny JR, Leakey ADB, Baxter I. Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria. PLoS Genet 2017. [PMID: 28644860 PMCID: PMC5507400 DOI: 10.1371/journal.pgen.1006841] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed six controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The non-destructive nature of plant height measurements has enabled us to monitor height throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development. Growth is a dynamic process that responds to a changing environment. Most of the methods that we have for measuring are static and collecting information throughout an organisms lifecycle is labor and cost prohibitive. Advances in imaging and robotics technology have enabled novel approaches to understanding how plants adapt to the environment. Using the model grass Setaria and new methods for measuring parameters from images, we investigate the genetic architecture of plant height in response to water availability and planting density. Height is one of the most influential components of plant architecture, determining tradeoffs between competition and resource allocation and is an important trait for boosting yields. The non-destructive nature of plant height measurements has enabled us to monitor growth throughout the plant life cycle in both field and controlled environments. We identified several loci controlling height in a population derived from a wild strain of Setaria viridis and its domesticated relative Setaria italica, as well as the developmental time in which these loci act. In this population, alleles inherited from the wild parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated parent collectively act to increase plant height later in development.
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Affiliation(s)
- Max J. Feldman
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
| | - Rachel E. Paul
- Department of Plant Biology and Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Darshi Banan
- Department of Plant Biology and Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Jennifer F. Barrett
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
| | - Jose Sebastian
- Carnegie Institution for Science, Department of Plant Biology, Stanford, California, United States of America
| | - Muh-Ching Yee
- Carnegie Institution for Science, Department of Plant Biology, Stanford, California, United States of America
| | - Hui Jiang
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
| | - Alexander E. Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Thomas P. Brutnell
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
| | - José R. Dinneny
- Carnegie Institution for Science, Department of Plant Biology, Stanford, California, United States of America
| | - Andrew D. B. Leakey
- Department of Plant Biology and Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America
| | - Ivan Baxter
- Donald Danforth Plant Science Center, St. Louis, Missouri, United States of America
- USDA-ARS, Plant Genetics Research Unit, St. Louis, Missouri, United States of America
- * E-mail:
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14
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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: 36] [Impact Index Per Article: 4.5] [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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15
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Muraya MM, Chu J, Zhao Y, Junker A, Klukas C, Reif JC, Altmann T. Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2017; 89:366-380. [PMID: 27714888 DOI: 10.1111/tpj.13390] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Revised: 09/14/2016] [Accepted: 09/19/2016] [Indexed: 05/02/2023]
Abstract
Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase-specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non-invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome-wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker-trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non-parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage-specific growth affecting genes to elucidate important processes operating at different developmental phases.
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Affiliation(s)
- Moses M Muraya
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
- Department of Plant Sciences, Chuka University, P.O. Box 109 - 60400, Chuka, Kenya
| | - Jianting Chu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
| | - Astrid Junker
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
| | - Christian Klukas
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
| | - Thomas Altmann
- Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, D-06466, Seeland, Germany
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16
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De Leon TB, Linscombe S, Subudhi PK. Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map. RICE (NEW YORK, N.Y.) 2016; 9:52. [PMID: 27696287 PMCID: PMC5045836 DOI: 10.1186/s12284-016-0125-2] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Accepted: 09/23/2016] [Indexed: 05/23/2023]
Abstract
BACKGROUND Salinity is one of the many abiotic stresses limiting rice production worldwide. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated to salinity tolerance. However, due to large confidence interval for the position of QTLs, utility of reported QTLs and the associated markers has been limited in rice breeding programs. The main objective of this study is to construct a high-density rice genetic map for identification QTLs and candidate genes for salinity tolerance at seedling stage. RESULTS We evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K+ concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance mechanisms. CONCLUSION The saturation of SNP markers in our linkage map increased the resolution of QTL mapping. Our study offers new insights on salinity tolerance and presents useful candidate genes that will help in marker-assisted gene pyramiding to develop salt tolerant rice varieties.
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Affiliation(s)
- Teresa B De Leon
- School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA
| | - Steven Linscombe
- Rice Research Station, Louisiana State University Agricultural Center, Rayne, LA, USA
| | - Prasanta K Subudhi
- School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA, USA.
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17
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Gu L, Wu Y, Jiang M, Si W, Zhang X, Tian D, Yang S. Dissimilar Manifestation of Heterosis in Superhybrid Rice at Early-Tillering Stage under Nutrient-Deficient and Nutrient-Sufficient Condition. PLANT PHYSIOLOGY 2016; 172:1142-1153. [PMID: 27540108 PMCID: PMC5047080 DOI: 10.1104/pp.16.00579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Accepted: 08/14/2016] [Indexed: 05/13/2023]
Abstract
Heterosis has long been exploited for crop breeding; however, the genetic mechanisms, particularly the initial establishment of heterosis during the early vegetative growth phase, remain elusive. The biggest challenge for that is to exclude noise genes from the identified heterosis-related candidates. Herein, we use nutrient-deficient hybrid with no measurable growth heterosis as control. After filtering these irrelevant genes, only 336 differentially expressed genes (DEGs), which is significantly lower than in previous reports, were identified as heterosis-related genes in a superhybrid rice of Liang-You-Pei-Jiu (LYP9) at early-tillering stage. Among the DEGs that could be mapped to quantitative trait loci (QTL), approximately 72.8% could be covered by yield or growth vigor-related QTL, thereby suggesting that our DEGs were reliable and may have potential value to rice breeding. Among the 336 DEGs identified, a majority showed intermediate expression relative to that of its parental lines (i.e. additive effects), particularly, expression was frequently more similar to the paternal line rather than the maternal line (44.1% versus 32.7%); the remaining 27.1% were exclusively up- or down-regulated between the hybrid and either parent. Interestingly, up-regulated genes encoded various enzymes, whereas down-regulated genes were enriched in responses to stress, indicating that hybrids may benefit from both activating metabolism-related pathways and alleviating fitness cost through allelic interactions. Furthermore, a significantly larger proportion of divergent genes and higher nonsynonymous substitutions rates were detected in these DEGs, suggesting a potential contribution to the establishment of heterosis in superhybrid rice LYP9.
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Affiliation(s)
- Longjiang Gu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Ying Wu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Mengmeng Jiang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Weina Si
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Xiaohui Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Dacheng Tian
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
| | - Sihai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China (L.G., M.J., X.Z., D.T., S.Y.); Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland 20850 (Y.W.); and National Engineering Laboratory of Crop Stress Resistance breeding, Anhui Agricultural University, Hefei 230036, China (L.G., W.S.)
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Wang X, Jia MH, Ghai P, Lee FN, Jia Y. Genome-Wide Association of Rice Blast Disease Resistance and Yield-Related Components of Rice. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2015; 28:1383-92. [PMID: 26284908 DOI: 10.1094/mpmi-06-15-0131-r] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Robust disease resistance may require an expenditure of energy that may limit crop yield potential. In the present study, a subset of a United States Department of Agriculture rice core collection consisting of 151 accessions was selected using a major blast resistance (R) gene, Pi-ta, marker and was genotyped with 156 simple sequence repeat (SSR) markers. Disease reactions to Magnaporthe oryzae, the causal agent of rice blast disease, were evaluated under greenhouse and field conditions, and heading date, plant height, paddy and brown seed weight in two field environments were analyzed, using an association mapping approach. A total of 21 SSR markers distributed among rice chromosomes 2 to 12 were associated with blast resistance, and 16 SSR markers were associated with seed weight, heading date, and plant height. Most noticeably, shorter plants were significantly correlated with resistance to blast, rice genomes with Pi-ta were associated with lighter seed weights, and the susceptible alleles of RM171 and RM6544 were associated with heavier seed weight. These findings unraveled a complex relationship between disease resistance and yield-related components.
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Affiliation(s)
- Xueyan Wang
- 1 Rice Research and Extension Center, University of Arkansas, Stuttgart, AR 72160, U.S.A
- 2 USDA Agricultural Research Service Dale Bumpers National Rice Research Center, Stuttgart
- 3 College of life science, China Jiliang University, Hangzhou 310018, China
| | - Melissa H Jia
- 2 USDA Agricultural Research Service Dale Bumpers National Rice Research Center, Stuttgart
| | - Pooja Ghai
- 2 USDA Agricultural Research Service Dale Bumpers National Rice Research Center, Stuttgart
- 4 Department of Biological Sciences, Arkansas State University, Jonesboro, AR 72401, U.S.A
| | - Fleet N Lee
- 1 Rice Research and Extension Center, University of Arkansas, Stuttgart, AR 72160, U.S.A
| | - Yulin Jia
- 2 USDA Agricultural Research Service Dale Bumpers National Rice Research Center, Stuttgart
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19
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Wu B, Mao D, Liu T, Li Z, Xing Y. Two quantitative trait loci for grain yield and plant height on chromosome 3 are tightly linked in coupling phase in rice. MOLECULAR BREEDING 2015; 35:156. [PMID: 0 DOI: 10.1007/s11032-015-0345-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
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20
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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: 3.3] [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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Mahender A, Anandan A, Pradhan SK. Early seedling vigour, an imperative trait for direct-seeded rice: an overview on physio-morphological parameters and molecular markers. PLANTA 2015; 241:1027-50. [PMID: 25805338 DOI: 10.1007/s00425-015-2273-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 03/04/2015] [Indexed: 05/04/2023]
Abstract
Rapid uniform germination and accumulation of biomass during initial phase of seedling establishment is an essential phenotypic trait considered as early seedling vigour for direct seeded situation in rice irrespective of environment. Enhanced role of carbohydrate, amylase, growth hormones, antioxidant enzymes and ascorbic acid brings changes in vigour and phenotype of seedling. Early establishment and demanding life form dominate the surroundings. Crop plant that has better growth overdrives the weed plant and suppresses its growth. Seedling early vigour is the characteristic of seed quality and describes the rapid, uniform germination and the establishment of strong seedlings in any environmental condition. The phenotype of modern rice varieties has been changed into adaptable for transplanted rice with thirst toward water and selection pressure for semi-dwarf architecture resulting in reduced early vigour. Decreasing freshwater availability and rising labour cost drives the search for a suitable alternative management system to enhance grain yield productivity for the burgeoning world population. In view of these issues, much attention has been focused on dry direct-seeded rice, because it demands low input. A rice cultivar with a strong seedling vigour trait is desirable in case of direct seeding. However, seedling vigour has not been selected in crop improvement programmes in conventional breeding due to its complex nature and quantitative inheritance. Molecular markers have been proven effective in increasing selection efficiency, particularly for quantitative traits that are simply inherited. Marker-assisted selection approach has facilitated efficient and precise transfer of genes/QTL(s) into many crop species and suggests a speedy and efficient technique over conventional breeding and selection methods. In this review, we present the findings and investigations in the field of seedling vigour in rice that includes the nature of inheritance of physio-morphological and biochemical traits and QTLs to assist plant breeders who work for direct-seeded rice.
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Affiliation(s)
- A Mahender
- Division of Crop Improvement, Central Rice Research Institute, Cuttack, 753006, Odisha, India
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22
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Liang Q, Li P, Hu C, Hua H, Li Z, Rong Y, Wang K, Hua J. Dynamic QTL and epistasis analysis on seedling root traits in upland cotton. J Genet 2015; 93:63-78. [PMID: 24840824 DOI: 10.1007/s12041-014-0341-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Roots are involved in acquisition of water and nutrients, as well as in providing structural support to plant. The root system provides a dynamic model for developmental analysis. Here, we investigated quantitative trait loci (QTL), dynamic conditional QTL and epistatic interactions for seedling root traits using an upland cotton F2 population and a constructed genetic map. Totally, 37 QTLs for root traits, 35 dynamic conditional QTLs based on the net increased amount of root traits (root tips, forks, length, surface area and volume) (i) after transplanting 10 days compared to 5 days, and (ii) after transplanting 15 days to 10 days were detected. Obvious dynamic characteristic of QTL and dynamic conditional QTL existed at different developmental stages of root because QTL and dynamic conditional QTL had not been detected simultaneously. We further confirmed that additive and dominance effects of QTL qRSA-chr1-1 in interval time 5 to 10 DAT (days after transplant) offset the effects in 10 to 15 DAT. Lots of two-locus interactions for root traits were identified unconditionally or dynamically, and a few epistatic interactions were only detected simultaneously in interval time of 5-10 DAT and 10-15 DAT, suggesting different interactive genetic mechanisms on root development at different stages. Dynamic conditional QTL and epistasis effects provide new attempts to understand the dynamics of roots and provide clues for root architecture selection in upland cotton.
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Affiliation(s)
- Qingzhi Liang
- College of Agronomy and Biotechnology, Key Laboratory of Crop Heterosis and Utilization of Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, People's Republic of China.
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Adult plant development in triticale (× triticosecale wittmack) is controlled by dynamic genetic patterns of regulation. G3-GENES GENOMES GENETICS 2014; 4:1585-91. [PMID: 25237110 PMCID: PMC4169150 DOI: 10.1534/g3.114.012989] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Many biologically and agronomically important traits are dynamic and show temporal variation. In this study, we used triticale (× Triticosecale Wittmack) as a model crop to assess the genetic dynamics underlying phenotypic plasticity of adult plant development. To this end, a large mapping population with 647 doubled haploid lines derived from four partially connected families from crosses among six parents was scored for developmental stage at three different time points. Using genome-wide association mapping, we identified main effect and epistatic quantitative trait loci (QTL) at all three time points. Interestingly, some of these QTL were identified at all time points, whereas others appear to only contribute to the genetic architecture at certain developmental stages. Our results illustrate the temporal contribution of QTL to the genetic control of adult plant development and more generally, the temporal genetic patterns of regulation that underlie dynamic traits.
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Xing J, Gao H, Wu Y, Wu Y, Li H, Yang R. Generalized linear model for mapping discrete trait loci implemented with LASSO algorithm. PLoS One 2014; 9:e106985. [PMID: 25210765 PMCID: PMC4161361 DOI: 10.1371/journal.pone.0106985] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2013] [Accepted: 08/12/2014] [Indexed: 11/30/2022] Open
Abstract
Generalized estimating equation (GEE) algorithm under a heterogeneous residual variance model is an extension of the iteratively reweighted least squares (IRLS) method for continuous traits to discrete traits. In contrast to mixture model-based expectation–maximization (EM) algorithm, the GEE algorithm can well detect quantitative trait locus (QTL), especially large effect QTLs located in large marker intervals in the manner of high computing speed. Based on a single QTL model, however, the GEE algorithm has very limited statistical power to detect multiple QTLs because of ignoring other linked QTLs. In this study, the fast least absolute shrinkage and selection operator (LASSO) is derived for generalized linear model (GLM) with all possible link functions. Under a heterogeneous residual variance model, the LASSO for GLM is used to iteratively estimate the non-zero genetic effects of those loci over entire genome. The iteratively reweighted LASSO is therefore extended to mapping QTL for discrete traits, such as ordinal, binary, and Poisson traits. The simulated and real data analyses are conducted to demonstrate the efficiency of the proposed method to simultaneously identify multiple QTLs for binary and Poisson traits as examples.
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Affiliation(s)
- Jun Xing
- Department of Gastroenterology, Tumor Hospital of Harbin Medical University, Harbin, People's Republic of China
| | - Huijiang Gao
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, People's Republic of China
| | - Yang Wu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, People's Republic of China
| | - Yani Wu
- School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Hongwang Li
- School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, People's Republic of China
| | - Runqing Yang
- Research Centre for Fisheries Resource and Environment, Chinese Academy of Fishery Sciences, Beijing, People's Republic of China
- * E-mail:
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Xie L, Tan Z, Zhou Y, Xu R, Feng L, Xing Y, Qi X. Identification and fine mapping of quantitative trait loci for seed vigor in germination and seedling establishment in rice. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2014; 56:749-59. [PMID: 24571491 DOI: 10.1111/jipb.12190] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 02/24/2014] [Indexed: 05/04/2023]
Abstract
Seed vigor is an index of seed quality that is used to describe the rapid and uniform germination and the establishment of strong seedlings in any environmental conditions. Strong seed vigor in low-temperature germination conditions is particularly important in direct-sowing rice production systems. However, seed vigor has not been selected as an important breeding trait in traditional breeding programs due to its quantitative inherence. In this study, we identified and mapped eight quantitative trait loci (QTLs) for seed vigor by using a recombinant inbred population from a cross between rice (Oryza sativa L. ssp. indica) cultivars ZS97 and MH63. Conditional QTL analysis identified qSV-1, qSV-5b, qSV-6a, qSV-6b, and qSV-11 influenced seedling establishment and that qSV-5a, qSV-5c, and qSV-8 influenced only germination. Of these, qSV-1, qSV-5b, qSV-6a, qSV-6b, and qSV-8 were low-temperature-specific QTLs. Two major-effective QTLs, qSV-1, and qSV-5c were narrowed down to 1.13-Mbp and 400-kbp genomic regions, respectively. The results provide tightly linked DNA markers for the marker-assistant pyramiding of multiple positive alleles for increased seed vigor in both normal and low-temperature germination environments.
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Affiliation(s)
- Lixia Xie
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, the Chinese Academy of Sciences, Beijing, 100093, China; University of Chinese Academy of Sciences, Beijing, 100049, China
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26
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Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations. J Genet 2014; 92:213-31. [PMID: 23970077 DOI: 10.1007/s12041-013-0253-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
For discovering the quantitative trait loci (QTLs) contributing to early seedling growth and drought tolerance during germination, conditional and unconditional analyses of 12 traits of wheat seedlings: coleoptile length, seedling height, longest root length, root number, seedling fresh weight, stem and leaves fresh weight, root fresh weight, seedling dry weight, stem and leaves dry weight, root dry weight, root to shoot fresh weight ratio, root-to-shoot dry weight ratio, were conducted under two water conditions using two F8:9 recombinant inbred line (RIL) populations. The results of unconditional analysis are as follows: 88 QTLs accounting for 3.33-77.01% of the phenotypic variations were detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B and 7D. Among these QTLs, 19 were main-effect QTLs with a contribution rate greater than 10%. The results of the conditional QTL analysis of 12 traits under osmotic stress on normal water conditions were as follows: altogether 22 QTLs concerned with drought tolerance were detected on chromosomes 1B, 2A, 2B, 3B, 4A, 5D, 6A, 6D, 7B, and 7D. Of these QTLs, six were main-effect QTLs. These 22 QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis. The finding of these QTLs has an important significance for fine-mapping technique, map-based cloning, and molecular marker-assisted selection of early seedling traits, such as growth and drought tolerance.
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27
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Liu W, Gowda M, Reif JC, Hahn V, Ruckelshausen A, Weissmann EA, Maurer HP, Würschum T. Genetic dynamics underlying phenotypic development of biomass yield in triticale. BMC Genomics 2014; 15:458. [PMID: 24916962 PMCID: PMC4070554 DOI: 10.1186/1471-2164-15-458] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 06/06/2014] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The nature of dynamic traits with their phenotypic plasticity suggests that they are under the control of a dynamic genetic regulation. We employed a precision phenotyping platform to non-invasively assess biomass yield in a large mapping population of triticale at three developmental stages. RESULTS Using multiple-line cross QTL mapping we identified QTL for each of these developmental stages which explained a considerable proportion of the genotypic variance. Some QTL were identified at each developmental stage and thus contribute to biomass yield throughout the studied developmental phases. Interestingly, we also observed QTL that were only identified for one or two of the developmental stages illustrating a temporal contribution of these QTL to the trait. In addition, epistatic QTL were detected and the epistatic interaction landscape was shown to dynamically change with developmental progression. CONCLUSIONS In summary, our results reveal the temporal dynamics of the genetic architecture underlying biomass accumulation in triticale and emphasize the need for a temporal assessment of dynamic traits.
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Affiliation(s)
| | | | | | | | | | | | | | - Tobias Würschum
- State Plant Breeding Institute, University of Hohenheim, 70599 Stuttgart, Germany.
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28
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Dang X, Thi TGT, Dong G, Wang H, Edzesi WM, Hong D. Genetic diversity and association mapping of seed vigor in rice (Oryza sativa L.). PLANTA 2014; 239:1309-19. [PMID: 24668487 DOI: 10.1007/s00425-014-2060-z] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2013] [Accepted: 03/06/2014] [Indexed: 05/20/2023]
Abstract
Seed vigor is closely related to direct seeding in rice (Oryza sativa L.). Previous quantitative trait locus (QTL) studies for seed vigor were mainly derived from bi-parental segregating populations and no report from natural populations. In this study, association mapping for seed vigor was performed on a selected sample of 540 rice cultivars (419 from China and 121 from Vietnam). Population structure was estimated on the basis of 262 simple sequence repeat (SSR) markers. Seed vigor was evaluated by root length (RL), shoot length (SL) and shoot dry weight in 2011 and 2012. Abundant phenotypic and genetic diversities were found in the studied population. The population was divided into seven subpopulations, and the levels of linkage disequilibrium (LD) ranged from 10 to 80 cM. We identified 27 marker-trait associations involving 18 SSR markers for three traits. According to phenotypic effects for alleles of the detected QTLs, elite alleles were mined. These elite alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the elite alleles per QTL (apart from possible epistatic effects). Our results demonstrate that association mapping can complement and enhance previous QTL information for marker-assisted selection and breeding by design.
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Affiliation(s)
- Xiaojing Dang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
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Würschum T, Liu W, Busemeyer L, Tucker MR, Reif JC, Weissmann EA, Hahn V, Ruckelshausen A, Maurer HP. Mapping dynamic QTL for plant height in triticale. BMC Genet 2014; 15:59. [PMID: 24885543 PMCID: PMC4040121 DOI: 10.1186/1471-2156-15-59] [Citation(s) in RCA: 38] [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: 04/14/2014] [Accepted: 05/08/2014] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Plant height is a prime example of a dynamic trait that changes constantly throughout adult development. In this study we utilised a large triticale mapping population, comprising 647 doubled haploid lines derived from 4 families, to phenotype for plant height by a precision phenotyping platform at multiple time points. RESULTS Using multiple-line cross QTL mapping we identified main effect and epistatic QTL for plant height for each of the time points. Interestingly, some QTL were detected at all time points whereas others were specific to particular developmental stages. Furthermore, the contribution of the QTL to the genotypic variance of plant height also varied with time as exemplified by a major QTL identified on chromosome 6A. CONCLUSIONS Taken together, our results in the small grain cereal triticale reveal the importance of considering temporal genetic patterns in the regulation of complex traits such as plant height.
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Affiliation(s)
- Tobias Würschum
- State Plant Breeding Institute, University of Hohenheim, Stuttgart 70599, Germany
| | - Wenxin Liu
- Crop Genetics and Breeding Department, China Agricultural University, Beijing 100193, China
| | - Lucas Busemeyer
- Competence Centre of Applied Agricultural Engineering COALA, University of Applied Sciences Osnabrück, Osnabrück 49076, Germany
| | - Matthew R Tucker
- ARC Centre of Excellence for Plant Cell Walls, University of Adelaide, Waite Campus, Urrbrae, SA 5064, Australia
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben 06466, Germany
| | | | - Volker Hahn
- State Plant Breeding Institute, University of Hohenheim, Stuttgart 70599, Germany
| | - Arno Ruckelshausen
- Competence Centre of Applied Agricultural Engineering COALA, University of Applied Sciences Osnabrück, Osnabrück 49076, Germany
| | - Hans Peter Maurer
- State Plant Breeding Institute, University of Hohenheim, Stuttgart 70599, Germany
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Sun L, Ye M, Hao H, Wang N, Wang Y, Cheng T, Zhang Q, Wu R. A model framework for identifying genes that guide the evolution of heterochrony. Mol Biol Evol 2014; 31:2238-47. [PMID: 24817546 DOI: 10.1093/molbev/msu156] [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] [Indexed: 12/21/2022] Open
Abstract
Heterochrony, the phylogenic change in the time of developmental events or rate of development, has been thought to play an important role in producing phenotypic novelty during evolution. Increasing evidence suggests that specific genes are implicated in heterochrony, guiding the process of developmental divergence, but no quantitative models have been instrumented to map such heterochrony genes. Here, we present a computational framework for genetic mapping by which to characterize and locate quantitative trait loci (QTLs) that govern heterochrony described by four parameters, the timing of the inflection point, the timing of maximum acceleration of growth, the timing of maximum deceleration of growth, and the length of linear growth. The framework was developed from functional mapping, a dynamic model derived to map QTLs for the overall process and pattern of development. By integrating an optimality algorithm, the framework allows the so-called heterochrony QTLs (hQTLs) to be tested and quantified. Specific pipelines are given for testing how hQTLs control the onset and offset of developmental events, the rate of development, and duration of a particular developmental stage. Computer simulation was performed to examine the statistical properties of the model and demonstrate its utility to characterize the effect of hQTLs on population diversification due to heterochrony. By analyzing a genetic mapping data in rice, the framework identified an hQTL that controls the timing of maximum growth rate and duration of linear growth stage in plant height growth. The framework provides a tool to study how genetic variation translates into phenotypic innovation, leading a lineage to evolve, through heterochrony.
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Affiliation(s)
- Lidan Sun
- Beijing Key Laboratory of Ornamental Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing, China
| | - Meixia Ye
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China
| | - Han Hao
- Center for Statistical Genetics, The Pennsylvania State University
| | - Ningtao Wang
- Center for Statistical Genetics, The Pennsylvania State University
| | - Yaqun Wang
- Center for Statistical Genetics, The Pennsylvania State University
| | - Tangren Cheng
- Beijing Key Laboratory of Ornamental Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing, China
| | - Qixiang Zhang
- Beijing Key Laboratory of Ornamental Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, College of Landscape Architecture, Beijing Forestry University, Beijing, China
| | - Rongling Wu
- Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, ChinaCenter for Statistical Genetics, The Pennsylvania State University
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Qi T, Jiang B, Zhu Z, Wei C, Gao Y, Zhu S, Xu H, Lou X. Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits. Heredity (Edinb) 2014; 113:224-32. [PMID: 24619175 DOI: 10.1038/hdy.2014.17] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2013] [Accepted: 11/25/2013] [Indexed: 11/09/2022] Open
Abstract
The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F2 (IF2) to the two parents, from random-cross of IF2 or from selfing of IF2 population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF2 population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.
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Affiliation(s)
- T Qi
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - B Jiang
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - Z Zhu
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - C Wei
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - Y Gao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, PR China
| | - S Zhu
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - H Xu
- Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, PR China
| | - X Lou
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
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Wang L, Cui F, Wang J, Jun L, Ding A, Zhao C, Li X, Feng D, Gao J, Wang H. Conditional QTL mapping of protein content in wheat with respect to grain yield and its components. J Genet 2013; 91:303-12. [PMID: 23271016 DOI: 10.1007/s12041-012-0190-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.
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Affiliation(s)
- Lin Wang
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian Subcenter of National Wheat Improvement Center, College of Agronomy, Shandong Agricultural University, Taian 271018, PR China.
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33
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Osman KA, Tang B, Wang Y, Chen J, Yu F, Li L, Han X, Zhang Z, Yan J, Zheng Y, Yue B, Qiu F. Dynamic QTL analysis and candidate gene mapping for waterlogging tolerance at maize seedling stage. PLoS One 2013; 8:e79305. [PMID: 24244474 PMCID: PMC3828346 DOI: 10.1371/journal.pone.0079305] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2013] [Accepted: 09/22/2013] [Indexed: 11/19/2022] Open
Abstract
Soil waterlogging is one of the major abiotic stresses adversely affecting maize growth and yield. To identify dynamic expression of genes or quantitative trait loci (QTL), QTL associated with plant height, root length, root dry weight, shoot dry weight and total dry weight were identified via conditional analysis in a mixed linear model and inclusive composite interval mapping method at three respective periods under waterlogging and control conditions. A total of 13, 19 and 23 QTL were detected at stages 3D|0D (the period during 0-3 d of waterlogging), 6D|3D and 9D|6D, respectively. The effects of each QTL were moderate and distributed over nine chromosomes, singly explaining 4.14-18.88% of the phenotypic variation. Six QTL (ph6-1, rl1-2, sdw4-1, sdw7-1, tdw4-1 and tdw7-1) were identified at two consistent stages of seedling development, which could reflect a continuous expression of genes; the remaining QTL were detected at only one stage. Thus, expression of most QTL was influenced by the developmental status. In order to provide additional evidence regarding the role of corresponding genes in waterlogging tolerance, mapping of Expressed Sequence Tags markers and microRNAs were conducted. Seven candidate genes were observed to co-localize with the identified QTL on chromosomes 1, 4, 6, 7 and 9, and may be important candidate genes for waterlogging tolerance. These results are a good starting point for understanding the genetic basis for selectively expressing of QTL in different stress periods and the common genetic control mechanism of the co-localized traits.
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Affiliation(s)
- Khalid A. Osman
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Bin Tang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yaping Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Juanhua Chen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Feng Yu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Liu Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xuesong Han
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zuxin Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jianbin Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yonglian Zheng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Bing Yue
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Fazhan Qiu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
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34
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Identification of unconditional and conditional QTL for oil, protein and starch content in maize. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.cj.2013.07.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Wang Z, Pang X, Wu W, Wang J, Wang Z, Wu R. MODELING PHENOTYPIC PLASTICITY IN GROWTH TRAJECTORIES: A STATISTICAL FRAMEWORK. Evolution 2013; 68:81-91. [DOI: 10.1111/evo.12263] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 08/10/2013] [Indexed: 12/17/2022]
Affiliation(s)
- Zhong Wang
- Center for Computational Biology; Beijing Forestry University; Beijing 100083 China
| | - Xiaoming Pang
- Center for Computational Biology; Beijing Forestry University; Beijing 100083 China
| | - Weimiao Wu
- Center for Computational Biology; Beijing Forestry University; Beijing 100083 China
| | - Jianxin Wang
- Center for Computational Biology; Beijing Forestry University; Beijing 100083 China
| | - Zuoheng Wang
- Division of Biostatistics; Yale University; New Haven Connecticut 06510
| | - Rongling Wu
- Center for Computational Biology; Beijing Forestry University; Beijing 100083 China
- Center for Statistical Genetics; Pennsylvania State University; Hershey Pennsylvania 17033
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36
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Zhang H, Cui F, Wang L, Li J, Ding A, Zhao C, Bao Y, Yang Q, Wang H. Conditional and unconditional QTL mapping of drought-tolerance-related traits of wheat seedling using two related RIL populations. J Genet 2013. [PMID: 23970077 DOI: 10.1007/s12041‐013‐0253‐z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
For discovering the quantitative trait loci (QTLs) contributing to early seedling growth and drought tolerance during germination, conditional and unconditional analyses of 12 traits of wheat seedlings: coleoptile length, seedling height, longest root length, root number, seedling fresh weight, stem and leaves fresh weight, root fresh weight, seedling dry weight, stem and leaves dry weight, root dry weight, root to shoot fresh weight ratio, root-to-shoot dry weight ratio, were conducted under two water conditions using two F8:9 recombinant inbred line (RIL) populations. The results of unconditional analysis are as follows: 88 QTLs accounting for 3.33-77.01% of the phenotypic variations were detected on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6B, 6D, 7A, 7B and 7D. Among these QTLs, 19 were main-effect QTLs with a contribution rate greater than 10%. The results of the conditional QTL analysis of 12 traits under osmotic stress on normal water conditions were as follows: altogether 22 QTLs concerned with drought tolerance were detected on chromosomes 1B, 2A, 2B, 3B, 4A, 5D, 6A, 6D, 7B, and 7D. Of these QTLs, six were main-effect QTLs. These 22 QTLs were all special loci directly concerned with drought tolerance and most of them could not be detected by unconditional analysis. The finding of these QTLs has an important significance for fine-mapping technique, map-based cloning, and molecular marker-assisted selection of early seedling traits, such as growth and drought tolerance.
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Affiliation(s)
- Hong Zhang
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, Taian Subcenter of National Wheat Improvement Center, College of Agronomy, Shandong Agricultural University, Taian 271018, People's Republic of China
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37
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Zhang B, Shi W, Li W, Chang X, Jing R. Efficacy of pyramiding elite alleles for dynamic development of plant height in common wheat. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2013; 32:327-338. [PMID: 23976874 PMCID: PMC3748324 DOI: 10.1007/s11032-013-9873-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2013] [Accepted: 04/18/2013] [Indexed: 05/28/2023]
Abstract
Plant height is an important botanical feature closely related to yield. Two populations consisting of 118 and 262 accessions respectively were used to identify elite alleles for plant height and to validate their allelic effects. Plant height was measured from the early booting to the flowering stages. Simple sequence repeat markers for candidate quantitative trait locus (QTL) regions with large effects identified in a doubled haploid (DH) population (Hanxuan 10 × Lumai 14) were selected for further verification by association analysis. Nine loci significantly (P < 0.001) associated with plant height were detected 13 times in the population with 118 accessions. Three loci (Xgwm11-1B, Xwmc349-4B and Xcfd23-4D) were identified in three, two and two periods of plant height growth, respectively. Markers Xbarc168-2D, Xgwm249-2D, Xwmc349-4B, Xcfd23-4D and Xgwm410-5A located at or near additive QTL regions in the DH population proved to coincide with known Rht loci. The results showed a consistency between linkage analysis and association mapping, and also confirmed the value of fine mapping of QTL through combined linkage and association analyses. For final plant height, the alleles Xgwm11-1B208 , Xwmc349-4B103 and Xcfd23-4D202 exhibited negative effects, i.e. reducing plant height; Xwmc349-4B101 and Xcfd23-4D205 showed significant positive effects. A second larger population (262 accessions) was used to validate the effects of these large-effect alleles and the efficacy of pyramiding in eight environments (year × site × water regime combinations). Strong correlations between final plant height and numbers of large-effect alleles indicated that the alleles contributed additively to plant height. The additive effects showed that pyramiding elite alleles for target traits has significant potential for wheat breeding.
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Affiliation(s)
- Bin Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Wei Shi
- National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Weiyu Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Xiaoping Chang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Ruilian Jing
- National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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38
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Genetic dissection of developmental behavior of grain weight in wheat under diverse temperature and water regimes. Genetica 2012; 140:393-405. [PMID: 23132048 DOI: 10.1007/s10709-012-9688-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2012] [Accepted: 10/26/2012] [Indexed: 10/27/2022]
Abstract
As a quantitatively inherited trait related to high yield potential, grain weight (GW) development in wheat is constrained by abiotic stresses such as limited water supply and high temperature. Data from a doubled haploid population, derived from a cross of (Hanxuan 10 × Lumai 14), grown in four environments were used to explore the genetic basis of GW developmental behavior in unconditional and conditional quantitative trait locus (QTL) analyses using a mixed linear model. Thirty additive QTLs and 41 pairs of epistatic QTLs were detected, and were more frequently observed on chromosomes 1B, 2A, 2D, 4A, 4B and 7B. No single QTL was continually active during all stages or periods of grain growth. The QTLs with additive effects (A-QTLs) expressed in the period S1|S0 (the period from the flowering to the seventh day after) formed a foundation for GW development. GW development at these stages can be used as an index for screening superior genotypes under diverse abiotic stresses in a wheat breeding program. One QTL, i.e. Qgw.cgb-6A.2, showed high adaptability for water-limited and heat-stress environments. Many A-QTLs interacted with more than one other QTL in the two genetic models, such as Qgw.cgb-4B.2 interacted with five QTLs, showing that the genetic architecture underlying GW development involves a collective expression of genes with additive and epistatic effects.
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39
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Chen G, Zhu Z, Zhang F, Zhu J. Quantitative genetic analysis station for the genetic analysis of complex traits. CHINESE SCIENCE BULLETIN-CHINESE 2012. [DOI: 10.1007/s11434-012-5108-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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40
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Pang X, Wang Z, Yap JS, Wang J, Zhu J, Bo W, Lv Y, Xu F, Zhou T, Peng S, Shen D, Wu R. A statistical procedure to map high-order epistasis for complex traits. Brief Bioinform 2012; 14:302-14. [PMID: 22723459 DOI: 10.1093/bib/bbs027] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Genetic interactions or epistasis have been thought to play a pivotal role in shaping the formation, development and evolution of life. Previous work focused on lower-order interactions between a pair of genes, but it is obviously inadequate to explain a complex network of genetic interactions and pathways. We review and assess a statistical model for characterizing high-order epistasis among more than two genes or quantitative trait loci (QTLs) that control a complex trait. The model includes a series of start-of-the-art standard procedures for estimating and testing the nature and magnitude of QTL interactions. Results from simulation studies and real data analysis warrant the statistical properties of the model and its usefulness in practice. High-order epistatic mapping will provide a routine procedure for charting a detailed picture of the genetic regulation mechanisms underlying the phenotypic variation of complex traits.
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41
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Li J, Lindqvist-Kreuze H, Tian Z, Liu J, Song B, Landeo J, Portal L, Gastelo M, Frisancho J, Sanchez L, Meijer D, Xie C, Bonierbale M. Conditional QTL underlying resistance to late blight in a diploid potato population. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2012; 124:1339-1350. [PMID: 22274766 DOI: 10.1007/s00122-012-1791-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2011] [Accepted: 01/11/2012] [Indexed: 05/31/2023]
Abstract
A large number of quantitative trait loci (QTL) for resistance to late blight of potato have been reported with a "conventional" method in which each phenotypic trait reflects the cumulative genetic effects for the duration of the disease process. However, as genes controlling response to disease may have unique contributions with specific temporal features, it is important to consider the phenotype as dynamic. Here, using the net genetic effects evidenced at consecutive time points during disease development, we report the first conditional mapping of QTL underlying late blight resistance in potato under five environments in Peru. Six conditional QTL were mapped, one each on chromosome 2, 7 and 12 and three on chromosome 9. These QTL represent distinct contributions to the phenotypic variation at different stages of disease development. By comparison, when conventional mapping was conducted, only one QTL was detected on chromosome 9. This QTL was the same as one of the conditional QTL. The results imply that conditional QTL reflect genes that function at particular stages during the host-pathogen interaction. The dynamics revealed by conditional QTL mapping could contribute to the understanding of the molecular mechanism of late blight resistance and these QTL could be used to target genes for marker development or manipulation to improve resistance.
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Affiliation(s)
- Jingcai Li
- Key Laboratory of Horticultural Plant Biology, Huazhong Agricultural University, Ministry of Education, National Center for Vegetable Improvement, Huazhong Agricultural University, Wuhan, Hubei 430070, People's Republic of China
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42
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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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43
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Yano K, Takashi T, Nagamatsu S, Kojima M, Sakakibara H, Kitano H, Matsuoka M, Aya K. Efficacy of microarray profiling data combined with QTL mapping for the identification of a QTL gene controlling the initial growth rate in rice. PLANT & CELL PHYSIOLOGY 2012; 53:729-39. [PMID: 22419825 DOI: 10.1093/pcp/pcs027] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Seedling vigor, which is controlled by many quantitative trait loci (QTLs), is one of several important agronomic traits for direct-seedling rice systems. However, isolating these QTL genes is laborious and expensive. Here, we combined QTL mapping and microarray profiling to identify QTL genes for seedling vigor. By performing QTL mapping using 82 backcross inbred lines (BILs) of the Koshihikari (japonica) and Habataki (indica) cultivars for the rice initial growth, we identified two QTLs, early-stage plant development1/2 (qEPD1 and qEPD2), whose Koshihikari alleles promote plant height and/or leaf sheath length. Phenotypic analysis of the two substituted lines carrying the Habataki qEPD1 or qEPD2 allele revealed that qEPD2 functioned more dominantly for the initial growth of rice. From the microarray experiment, 55 and 45 candidate genes were found in the qEPD1 and qEPD2 genomic regions, which are expressed differentially between each substitution line (SL) and Koshihikari. Gibberellin 20 oxidase-2 (OsGA20ox2), which is identical to Semi Dwarf1 (SD1), was included among the 55 candidate genes of qEPD1, whereas its paralog, OsGA20ox1, was included among the 45 candidate genes of qEPD2. Consistently, introduction of the Koshihikari OsGA20ox1 allele into SL(qEPD2) increaseed its plant height and leaf sheath length significantly relative to the introduction of the Habataki OsGA20ox1 allele. Therefore, microarray profiling could be useful for rapidly screening QTL candidate genes. We concluded that OsGA20ox1 and OsGA20ox2 (SD1) function during the initial growth of rice, but OsGA20ox1 plays a dominant role in increasing plant height and leaf sheath length at the initial growth stage.
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Affiliation(s)
- Kenji Yano
- Bioscience and Biotechnology Center, Nagoya University, Nagoya, Japan
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44
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Zhang J, Hao C, Ren Q, Chang X, Liu G, Jing R. Association mapping of dynamic developmental plant height in common wheat. PLANTA 2011; 234:891-902. [PMID: 21647605 DOI: 10.1007/s00425-011-1434-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2010] [Accepted: 05/09/2011] [Indexed: 05/04/2023]
Abstract
Drought as a major abiotic stress often occurs from stem elongation to the grain filling stage of wheat in northern China. Plant height (PH) is a suitable trait to model the dissection of drought tolerance. The purposes of the present study were to validate molecular markers for PH developmental behavior and identify elite alleles of molecular markers. After the phenotyping of 154 accessions for PH dynamic development under well-watered (WW) and drought stressed (DS) conditions, and the genotyping of 60 SSR markers from six candidate chromosome regions related to PH found in our previous linkage mapping studies, both parameters PH and drought tolerance coefficient (DTC) calculated by the conditional analysis were used for association mapping. A total of 46 significant association signals (P < 0.01) were identified in 23 markers, and phenotypic variation ranged from 7 to 50%. Among them, four markers Xgwm261-2D, Xgwm495-4B, Xbarc109-4B and Xcfd23-4D were detected under both water regimes. Furthermore, 10 markers were associated with DTC, and four with both parameters PH and DTC at the same plant development stage. The results revealed different allelic effects of associated markers; for example, the 155 bp Xgwm495-4B allele was associated with a reduced height of -11.2 cm under DS and -15.3 cm under WW, whereas the 167 bp allele exhibited increased height effects of 3.9 and 8.1 cm, respectively. This study demonstrates a strong power of joint association analysis and linkage mapping for the identification of important genes in wheat.
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Affiliation(s)
- Jianan Zhang
- Key Laboratory of Crop Germplasm Resources and Utilization, Ministry of Agriculture / The 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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45
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Molecular dissection of plant height QTLs using recombinant inbred lines from hybrids between common wheat (Triticum aestivum L.) and spelt wheat (Triticum spelta L.). CHINESE SCIENCE BULLETIN-CHINESE 2011. [DOI: 10.1007/s11434-011-4506-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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46
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Han Y, Xie D, Teng W, Zhang S, Chang W, Li W. Dynamic QTL analysis of linolenic acid content in different developmental stages of soybean seed. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2011; 122:1481-8. [PMID: 21344183 DOI: 10.1007/s00122-011-1547-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2010] [Accepted: 02/02/2011] [Indexed: 05/30/2023]
Abstract
Linolenic acid (LN) in soybean (Glycine max L. Merr.) seed mainly contributes to the undesirable odors and flavors commonly associated with poor oil quality. LN deposition at various stages of soybean seed development had not been reported by 2010. The objects of this study were (1) to identify and measure quantitative trait loci (QTL) underlying LN content and (2) to estimate the QTL effects expressed from earlier seed developmental stages to drying seed of soybean. One hundred and twenty-five F(5:8) and F(5:9) recombinant inbred lines derived from the cross of soybean cultivars 'Hefeng 25' and 'Dongnong L5' were used for the identification of QTL underlying LN content from the 37 day (D) to 86D stages after flowering, at Harbin in 2008 and 2009. QTL × Environment interactions (QE) effects were evaluated using a mixed genetic model (Zhu in J Zhejiang Univ (Natural Science) 33:327-335, 1999). Twelve unconditional QTL and 12 conditional QTL associated with LN content were identified at different developmental stages. Most of the QTL explained <10% of phenotypic variation of LN content. Unconditional QTL QLNF-1, QLNC2-1, QLND1b-1, QLNA2-1 and QLNH-1 influenced LN content across different development stages and environments. Conditional QTL QLNF-1, QLNC2-1 and QLNH-1 were identified in multiple developmental stages and environments. Conditional and unconditional QTL clustered in neighboring intervals on linkage groups A2, C2 and D1b. Ten QTL with conditional additive main effects (a) and/or conditional additive × environment interaction effects (ae) at specific developmental stage were identified on nine linkage groups. Of them, six QTL only possessed additive main effects and seven QTL had significant ae effects in different developmental stages. A total of 13 epistatic pairwise QTL were identified by conditional mapping in different developmental stages. Two pairs of QTL only showed aa effects and five pairs of QTL only showed aae effects at different developmental stages. QTL with aa effects, as well as their environmental interaction effects, appeared to vary at different developmental stages.
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Affiliation(s)
- Yingpeng Han
- Soybean Research Institute (Key Laboratory of Soybean Biology in Chinese Ministry of Education), Northeast Agricultural University, Harbin, China
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47
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Xu L, Henke M, Zhu J, Kurth W, Buck-Sorlin G. A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes. ANNALS OF BOTANY 2011; 107:817-28. [PMID: 21247905 PMCID: PMC3077984 DOI: 10.1093/aob/mcq264] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2010] [Revised: 06/07/2010] [Accepted: 11/29/2010] [Indexed: 05/04/2023]
Abstract
BACKGROUND AND AIMS Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. METHODS The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. KEY RESULTS Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. CONCLUSIONS We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.
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Affiliation(s)
- Lifeng Xu
- Institute of Bioinformatics, Zhejiang University, 310029 Hangzhou, P.R. China
- Department of Ecoinformatics, Biometrics and Forest Growth, Georg-August-University Göttingen, Büsgenweg 4, 37077 Göttingen, Germany
| | - Michael Henke
- Department of Ecoinformatics, Biometrics and Forest Growth, Georg-August-University Göttingen, Büsgenweg 4, 37077 Göttingen, Germany
| | - Jun Zhu
- Institute of Bioinformatics, Zhejiang University, 310029 Hangzhou, P.R. China
| | - Winfried Kurth
- Department of Ecoinformatics, Biometrics and Forest Growth, Georg-August-University Göttingen, Büsgenweg 4, 37077 Göttingen, Germany
| | - Gerhard Buck-Sorlin
- Wageningen UR, Department Biometris, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
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48
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Unconditional and conditional QTL mapping for the developmental behavior of tiller number in rice (Oryza sativa L.). Genetica 2010; 138:885-93. [PMID: 20623365 DOI: 10.1007/s10709-010-9471-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2009] [Accepted: 06/28/2010] [Indexed: 10/19/2022]
Abstract
A single segment substitution population of 26 lines and their recipient parent Hua-jing-xian 74 (HJX74) were selected as experimental materials for analyzing the developmental behavior of tiller number in rice. By the unconditional QTL (quantitative trait locus) mapping method, a total number of 14 SSSLs were detected with QTLs controlling rice tiller number. The number of QTLs significantly affecting tiller number and their effect values estimated differed across measuring stages. More QTLs could be detected based on time-dependent measures of different stages. By the conditional QTL mapping method, it is possible to reveal net expression of gene in a time interval. 14 QTLs on tiller number expressed their effects in dynamic patterns of themselves during whole ontogeny. They exhibited mainly negative effects within 7 days after transplanting. During 7-21 days, QTLs were in active status and expressed larger positive effects. In the mid-period of 21-35 days, they had opposite genetic effects to wither tillers. Since then these QTLs expressed positive effects again to cause the appearance of noneffective tillers. The dynamics of QTL effects was in agreement with the actual change of tillers. Mapping QTL combining unconditional with conditional analysis for time-dependent measures is helpful to understand roundly the genetic bases for the development of quantitative traits.
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49
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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: 48] [Impact Index Per Article: 3.2] [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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50
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Min L, Yang R, Wang X, Wang B. Bayesian analysis for genetic architecture of dynamic traits. Heredity (Edinb) 2010; 106:124-33. [PMID: 20332806 DOI: 10.1038/hdy.2010.20] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The dissection of the genetic architecture of quantitative traits, including the number and locations of quantitative trait loci (QTL) and their main and epistatic effects, has been an important topic in current QTL mapping. We extend the Bayesian model selection framework for mapping multiple epistatic QTL affecting continuous traits to dynamic traits in experimental crosses. The extension inherits the efficiency of Bayesian model selection and the flexibility of the Legendre polynomial model fitting to the change in genetic and environmental effects with time. We illustrate the proposed method by simultaneously detecting the main and epistatic QTLs for the growth of leaf age in a doubled-haploid population of rice. The behavior and performance of the method are also shown by computer simulation experiments. The results show that our method can more quickly identify interacting QTLs for dynamic traits in the models with many numbers of genetic effects, enhancing our understanding of genetic architecture for dynamic traits. Our proposed method can be treated as a general form of mapping QTL for continuous quantitative traits, being easier to extend to multiple traits and to a single trait with repeat records.
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Affiliation(s)
- L Min
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, PR China
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