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Horsnell R, Leigh FJ, Wright TIC, Burridge AJ, Ligeza A, Przewieslik-Allen AM, Howell P, Uauy C, Edwards KJ, Bentley AR. A wheat chromosome segment substitution line series supports characterization and use of progenitor genetic variation. THE PLANT GENOME 2024; 17:e20288. [PMID: 36718796 DOI: 10.1002/tpg2.20288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 10/20/2022] [Indexed: 06/18/2023]
Abstract
Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery, and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat (Triticum aestivum L.) chromosome segment substitution lines (CSSLs) generated to systematically capture genetic variation from tetraploid (T. turgidum ssp. dicoccoides) and diploid (Aegilops tauschii) progenitor species. Generated in a common genetic background over four generations of backcrossing, this is a base resource for the mapping and characterization of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterized using a high-density genotyping array and a range of agronomic and grain traits assessed to demonstrate the potential use of the populations for trait localization in wheat.
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Affiliation(s)
- Richard Horsnell
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
| | - Fiona J Leigh
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
| | - Tally I C Wright
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
| | | | - Aleksander Ligeza
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
| | | | - Philip Howell
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
| | - Cristobal Uauy
- John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK
| | | | - Alison R Bentley
- The John Bingham Laboratory, NIAB, 93 Lawrence Weaver Road, Cambridge, UK
- International Maize and Wheat Improvement Center (CIMMYT), El Batan, Mexico
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Nagata K, Nonoue Y, Matsubara K, Mizobuchi R, Ono N, Shibaya T, Ebana K, Ogiso-Tanaka E, Tanabata T, Sugimoto K, Taguchi-Shiobara F, Yonemaru JI, Uga Y, Fukuda A, Ueda T, Yamamoto SI, Yamanouchi U, Takai T, Ikka T, Kondo K, Hoshino T, Yamamoto E, Adachi S, Sun J, Kuya N, Kitomi Y, Iijima K, Nagasaki H, Shomura A, Mizubayashi T, Kitazawa N, Hori K, Ando T, Yamamoto T, Fukuoka S, Yano M. Development of 12 sets of chromosome segment substitution lines that enhance allele mining in Asian cultivated rice. BREEDING SCIENCE 2023; 73:332-342. [PMID: 37840983 PMCID: PMC10570878 DOI: 10.1270/jsbbs.23006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/12/2023] [Indexed: 10/17/2023]
Abstract
Many agronomic traits that are important in rice breeding are controlled by multiple genes. The extensive time and effort devoted so far to identifying and selecting such genes are still not enough to target multiple agronomic traits in practical breeding in Japan because of a lack of suitable plant materials in which to efficiently detect and validate beneficial alleles from diverse genetic resources. To facilitate the comprehensive analysis of genetic variation in agronomic traits among Asian cultivated rice, we developed 12 sets of chromosome segment substitution lines (CSSLs) with the japonica background, 11 of them in the same genetic background, using donors representing the genetic diversity of Asian cultivated rice. Using these materials, we overviewed the chromosomal locations of 1079 putative QTLs for seven agronomic traits and their allelic distribution in Asian cultivated rice through multiple linear regression analysis. The CSSLs will allow the effects of putative QTLs in the highly homogeneous japonica background to be validated.
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Affiliation(s)
- Kazufumi Nagata
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Yasunori Nonoue
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Kazuki Matsubara
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Ritsuko Mizobuchi
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Nozomi Ono
- Institute of the Society for Techno-innovation of Agriculture, Forestry and Fisheries, 446-1 Ippaizuka, Kamiyokoba, Tsukuba, Ibaraki 305-0854, Japan
| | - Taeko Shibaya
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Kaworu Ebana
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Eri Ogiso-Tanaka
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Takanari Tanabata
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Kazuhiko Sugimoto
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Fumio Taguchi-Shiobara
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Jun-ichi Yonemaru
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Yusaku Uga
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Atsunori Fukuda
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Tadamasa Ueda
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Shin-ichi Yamamoto
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Utako Yamanouchi
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Toshiyuki Takai
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Takashi Ikka
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Katsuhiko Kondo
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Tomoki Hoshino
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Eiji Yamamoto
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Shunsuke Adachi
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Jian Sun
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Noriyuki Kuya
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Yuka Kitomi
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Ken Iijima
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Hideki Nagasaki
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Ayahiko Shomura
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Tatsumi Mizubayashi
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Noriyuki Kitazawa
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Kiyosumi Hori
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Tsuyu Ando
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Toshio Yamamoto
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Shuichi Fukuoka
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
| | - Masahiro Yano
- National Agriculture and Food Research Organization, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8518, Japan
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Ma M, Lei E, Wang T, Meng H, Zhang W, Lu B. Genetic Diversity and Association Mapping of Grain-Size Traits in Rice Landraces from the Honghe Hani Rice Terraces System in Yunnan Province. PLANTS (BASEL, SWITZERLAND) 2023; 12:1678. [PMID: 37111901 PMCID: PMC10146266 DOI: 10.3390/plants12081678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 03/31/2023] [Accepted: 04/15/2023] [Indexed: 06/19/2023]
Abstract
The Honghe Hani Rice Terraces System (HHRTS) of Yunnan Province is an important agricultural and cultural heritage landscape. Until now, a large number of local rice landraces have been planted. Mining excellent genes contained in these landraces provides a reference for variety improvement and new variety breeding. In this study, 96 rice landraces collected from the Hani terraces were planted in Honghe Mengzi, Yunnan Province, in 2013, 2014, 2015, and 2021, and five major grain traits were measured and analyzed. The genomic variation of 96 rice landraces was scanned by 201 simple sequence repeat (SSR) markers. The genetic diversity, population structure, and genetic relationships of the natural population were analyzed. The mixed linear model (MLM) method of the TASSEL software was used to analyze the associations between markers and traits. A total of 936 alleles were amplified by 201 pairs of SSR primers. The average number of observed alleles (Na), the effective number of alleles (Ne), Shannon's information index (I), heterozygosity (H), and the polymorphism information content (PIC) per marker were 4.66, 2.71, 1.08, 0.15, and 0.55, respectively. Ninety-six landraces were divided into two groups by population structure, clustering, and principal component analysis, and indica rice was the main group. The coefficients of variation of the five traits ranged from 6.80 to 15.24%, and their broad heritabilities were more than 70%. In addition, there were positive correlations among the same grain traits between different years. Through MLM analysis, 2, 36, 7, 7, and 4 SSR markers were significantly associated with grain length (GL), grain width (GW), grain thickness (GT), grain length-width ratio (LWR), and thousand-grain weight (TGW), respectively. The explanation rates of phenotypic variation were 16.31 (RM449, Chr. 1)-23.51% (RM316, Chr. 9), 10.84 (RM523, Chr. 3; RM161/RM305, Chr. 5)-43.01% (RM5496, Chr. 1), 11.98 (RM161/RM305, Chr. 5)-24.72% (RM275, Chr. 6), 12.68 (RM126, Chr. 8)-36.96% (RM5496, Chr. 1), and 17.65 (RM4499, Chr. 2)-26.32% (RM25, Chr. 8), respectively. The associated markers were distributed on 12 chromosomes of the genome.
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Affiliation(s)
- Mengli Ma
- Key Laboratory for Research and Utilization of Characteristic Biological Resources in Southern Yunnan, Honghe University, Mengzi 661199, China
- College of Biological and Agricultural Sciences, Honghe University, Mengzi 661199, China
| | - En Lei
- College of Biological and Agricultural Sciences, Honghe University, Mengzi 661199, China
| | - Tiantao Wang
- Key Laboratory for Research and Utilization of Characteristic Biological Resources in Southern Yunnan, Honghe University, Mengzi 661199, China
| | - Hengling Meng
- Key Laboratory for Research and Utilization of Characteristic Biological Resources in Southern Yunnan, Honghe University, Mengzi 661199, China
| | - Wei Zhang
- College of Biological and Agricultural Sciences, Honghe University, Mengzi 661199, China
| | - Bingyue Lu
- Key Laboratory for Research and Utilization of Characteristic Biological Resources in Southern Yunnan, Honghe University, Mengzi 661199, China
- College of Biological and Agricultural Sciences, Honghe University, Mengzi 661199, China
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Yadavalli VR, Balakrishnan D, Surapaneni M, Addanki K, Mesapogu S, Beerelli K, Desiraju S, Voleti SR, Neelamraju S. Mapping QTLs for yield and photosynthesis-related traits in three consecutive backcross populations of Oryza sativa cultivar Cottondora Sannalu (MTU1010) and Oryza rufipogon. PLANTA 2022; 256:71. [PMID: 36070104 DOI: 10.1007/s00425-022-03983-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 08/25/2022] [Indexed: 06/15/2023]
Abstract
Identification of trait enhancing QTLs for yield and photosynthesis-related traits in rice using interspecific mapping population and chromosome segment substitution lines derived from a cross between Oryza sativa and Oryza rufipogon. Wild rice contains novel genes which can help in improving rice yield. Common wild rice Oryza rufipogon is a known source for enhanced photosynthesis and yield-related traits. We developed BC2F2:3:4 mapping populations using O. rufipogon IC309814 with high photosynthetic rate as donor, and elite cultivar MTU1010 as recurrent parent. Evaluation of 238 BC2F2 families for 13 yield-related traits and 208 BC2F2 families for seven photosynthesis-related physiological traits resulted in identification of significantly different lines which performed better than MTU1010 for various yield contributing traits. 49 QTLs were identified for 13 yield traits and 7 QTLs for photosynthesis-related traits in BC2F2. In addition, 34 QTLs in BC2F3 and 26 QTLs in BC2F4 were also detected for yield traits.11 common QTLs were identified in three consecutive generations and their trait-increasing alleles were derived from O. rufipogon. Significantly, one major effect common QTL qTGW3.1 for thousand grain weight with average phenotypic variance 8.1% and one novel QTL qBM7.1 for biomass were identified. Photosynthesis-related QTLs qPN9.1, qPN12.1, qPN12.2 qSPAD1.1 and qSPAD6.1 showed additive effect from O. rufipogon. A set of 145 CSSLs were identified in BC2F2 which together represented 87% of O. rufipogon genome. In addition, 87 of the 145 CSSLs were significantly different than MTU1010 for at least one trait. The major effect QTLs can be fine mapped for gene discovery. CSSLs developed in this study are a good source of novel alleles from O. rufipogon in the background of Cottondora Sannalu for rapid improvement of any trait in rice.
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Affiliation(s)
- Venkateswara Rao Yadavalli
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Divya Balakrishnan
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
- Department of Plant Breeding and Genetics, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Malathi Surapaneni
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Krishnamraju Addanki
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Sukumar Mesapogu
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Kavitha Beerelli
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Subrahmanyam Desiraju
- Department of Plant Physiology, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Sitapati Rao Voleti
- Department of Plant Physiology, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India
| | - Sarla Neelamraju
- ICAR National Professor Project, ICAR-Indian Institute of Rice Research, Hyderabad, 500030, Telangana, India.
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Fine Mapping of qTGW7b, a Minor Effect QTL for Grain Weight in Rice (Oryza sativa L.). Int J Mol Sci 2022; 23:ijms23158296. [PMID: 35955422 PMCID: PMC9368273 DOI: 10.3390/ijms23158296] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/25/2022] [Accepted: 07/26/2022] [Indexed: 02/06/2023] Open
Abstract
Grain weight is a key trait that determines rice quality and yield, and it is primarily controlled by quantitative trait loci (QTL). Recently, attention has been paid to minor QTLs. A minor effect QTL qTGW7 that controls grain weight was previously identified in a set of chromosomal fragment substitution lines (CSSLs) derived from Nipponbare (NPB)/93-11. Compared to NPB, the single segment substitution line (SSSL) N83 carrying the qTGW7 introgression exhibited an increase in grain length and width and a 4.5% increase in grain weight. Meanwhile, N83 was backcrossed to NPB to create a separating population, qTGW7b, a QTL distinct from qTGW7, which was detected between markers G31 and G32. Twelve near-isogenic lines (NILs) from the BC9F3 population and progeny of five NILs from the BC9F3:4 population were genotyped and phenotyped, resulting in the fine mapping of the minor effect QTL qTGW7b to the approximately 86.2-kb region between markers G72 and G32. Further sequence comparisons and expression analysis confirmed that five genes, including Os07g39370, Os07g39430, Os07g39440, Os07g39450, and Os07g39480, were considered as the candidate genes underlying qTGW7b. These results provide a crucial foundation for further cloning of qTGW7b and molecular breeding design in rice.
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Li C, Lu C, Zou B, Yang M, Wu G, Wang P, Cheng Q, Wang Y, Zhong Q, Huang S, Huang T, He H, Bian J. Genome-Wide Association Study Reveals a Genetic Mechanism of Salt Tolerance Germinability in Rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2022; 13:934515. [PMID: 35909718 PMCID: PMC9335074 DOI: 10.3389/fpls.2022.934515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Salt stress is one of the factors that limits rice production, and an important task for researchers is to cultivate rice with strong salt tolerance. In this study, 211 rice accessions were used to determine salt tolerance germinability (STG) indices and conduct a genome-wide association study (GWAS) using 36,727 SNPs. The relative germination energy (RGE), relative germination index (RGI), relative vigor index (RVI), relative mean germination time (RMGT), relative shoot length (RSL), and relative root length (RRL) were used to determine the STG indices in rice. A total of 43 QTLs, including 15 for the RGE, 6 for the RGI, 7 for the RVI, 3 for the RMGT, 1 for the RSL, and 11 for the RRL, were identified on nine chromosome regions under 60 and 100 mM NaCl conditions. For these STG-related QTLs, 18 QTLs were co-localized with previous studies, and some characterized salt-tolerance genes, such as OsCOIN, OsHsp17.0, and OsDREB2A, are located in these QTL candidates. Among the 25 novel QTLs, qRGE60-1-2 co-localized with qRGI60-1-1 on chromosome 1, and qRGE60-3-1 and qRVI60-3-1 co-localized on chromosome 3. According to the RNA-seq database, 16 genes, including nine for qRGE60-1-2 (qRGI60-1-1) and seven for qRGE60-3-1 (qRVI60-3-1), were found to show significant differences in their expression levels between the control and salt treatments. Furthermore, the expression patterns of these differentially expressed genes were analyzed, and nine genes (five for qRGE60-1-2 and four for qRGE60-3-1) were highly expressed in embryos at the germination stage. Haplotype analysis of these nine genes showed that the rice varieties with elite haplotypes in the LOC_Os03g13560, LOC_Os03g13840, and LOC_Os03g14180 genes had high STG. GWAS validated the known genes underlying salt tolerance and identified novel loci that could enrich the current gene pool related to salt tolerance. The resources with high STG and significant loci identified in this study are potentially useful in breeding for salt tolerance.
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Affiliation(s)
- Caijing Li
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Changsheng Lu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Baoli Zou
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Mengmeng Yang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Guangliang Wu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Peng Wang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Qin Cheng
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Yanning Wang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Qi Zhong
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Shiying Huang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Tao Huang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Haohua He
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
| | - Jianmin Bian
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, China
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7
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Zhang B, Ma L, Wu B, Xing Y, Qiu X. Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice ( Oryza sativa L.). FRONTIERS IN PLANT SCIENCE 2022; 13:863789. [PMID: 35557720 PMCID: PMC9087921 DOI: 10.3389/fpls.2022.863789] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/01/2022] [Indexed: 05/14/2023]
Abstract
The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.
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Affiliation(s)
- Bo Zhang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Ling Ma
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Bi Wu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Xianjin Qiu
- College of Agriculture, Yangtze University, Jingzhou, China
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Zhang Y, Zhou J, Xu P, Li J, Deng X, Deng W, Yang Y, Yu Y, Pu Q, Tao D. A Genetic Resource for Rice Improvement: Introgression Library of Agronomic Traits for All AA Genome Oryza Species. FRONTIERS IN PLANT SCIENCE 2022; 13:856514. [PMID: 35401612 PMCID: PMC8992386 DOI: 10.3389/fpls.2022.856514] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 02/07/2022] [Indexed: 05/20/2023]
Abstract
Rice improvement depends on the availability of genetic variation, and AA genome Oryza species are the natural reservoir of favorable alleles that are useful for rice breeding. To systematically evaluate and utilize potentially valuable traits of new QTLs or genes for the Asian cultivated rice improvement from all AA genome Oryza species, 6,372 agronomic trait introgression lines (ILs) from BC2 to BC6 were screened and raised based on the variations in agronomic traits by crossing 170 accessions of 7 AA genome species and 160 upland rice accessions of O. sativa as the donor parents, with three elite cultivars of O. sativa, Dianjingyou 1 (a japonica variety), Yundao 1 (a japonica variety), and RD23 (an indica variety) as the recurrent parents, respectively. The agronomic traits, such as spreading panicle, erect panicle, dense panicle, lax panicle, awn, prostrate growth, plant height, pericarp color, kernel color, glabrous hull, grain size, 1,000-grain weight, drought resistance and aerobic adaption, and blast resistance, were derived from more than one species. Further, 1,401 agronomic trait ILs in the Dianjingyou 1 background were genotyped using 168 SSR markers distributed on the whole genome. A total of twenty-two novel allelic variations were identified to be highly related to the traits of grain length (GL) and grain width (GW), respectively. In addition, allelic variations for the same locus were detected from the different donor species, which suggest that these QTLs or genes were conserved and the different haplotypes of a QTL (gene) were valuable resources for broadening the genetic basis in Asian cultivated rice. Thus, this agronomic trait introgression library from multiple species and accessions provided a powerful resource for future rice improvement and genetic dissection of agronomic traits.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Dayun Tao
- Yunnan Key Laboratory for Rice Genetic Improvement, Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
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Li C, Liu J, Bian J, Jin T, Zou B, Liu S, Zhang X, Wang P, Tan J, Wu G, Chen Q, Wang Y, Zhong Q, Huang S, Yang M, Huang T, He H, Bian J. Identification of cold tolerance QTLs at the bud burst stage in 211 rice landraces by GWAS. BMC PLANT BIOLOGY 2021; 21:542. [PMID: 34800993 PMCID: PMC8605578 DOI: 10.1186/s12870-021-03317-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 11/04/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Rice is a crop that is very sensitive to low temperature, and its morphological development and production are greatly affected by low temperature. Therefore, understanding the genetic basis of cold tolerance in rice is of great significance for mining favorable genes and cultivating excellent rice varieties. However, there have been limited studies focusing on cold tolerance at the bud burst stage; therefore, considerable attention should be given to the genetic basis of cold tolerance at this stage. RESULTS In this study, a natural population consisting of 211 rice landraces collected from 15 provinces in China and other countries was used for the first time to evaluate cold tolerance at the bud burst stage. Population structure analysis showed that this population was divided into two groups and was rich in genetic diversity. Our evaluation results confirmed that japonica rice was more tolerant to cold at the bud burst stage than indica rice. A genome-wide association study (GWAS) was performed with the phenotypic data of 211 rice landraces and a 36,727 SNP dataset under a mixed linear model. Twelve QTLs (P < 0.0001) were identified for the seedling survival rate (SR) after treatment at 4 °C, in which there were five QTLs (qSR2-2, qSR3-1, qSR3-2, qSR3-3 and qSR9) that were colocalized with those from previous studies and seven QTLs (qSR2-1, qSR3-4, qSR3-5, qSR3-6, qSR3-7, qSR4 and qSR7) that were reported for the first time. Among these QTLs, qSR9, harboring the most significant SNP, explained the most phenotypic variation. Through bioinformatics analysis, five genes (LOC_Os09g12440, LOC_Os09g12470, LOC_Os09g12520, LOC_Os09g12580 and LOC_Os09g12720) were identified as candidates for qSR9. CONCLUSION This natural population consisting of 211 rice landraces combined with high-density SNPs will serve as a better choice for identifying rice QTLs/genes in the future, and the detected QTLs associated with cold tolerance at the bud burst stage in rice will be conducive to further mining favorable genes and breeding rice varieties under cold stress.
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Affiliation(s)
- Caijing Li
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Jindong Liu
- Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518000 Guangdong Province China
| | - Jianxin Bian
- Peking University Institute of Advanced Agricultural Sciences, Weifang, 261325 Shandong Province China
| | - Tao Jin
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Baoli Zou
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Shilei Liu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Xiangyu Zhang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Peng Wang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Jingai Tan
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Guangliang Wu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Qin Chen
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Yanning Wang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Qi Zhong
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Shiying Huang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Mengmeng Yang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Tao Huang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Haohua He
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
| | - Jianmin Bian
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang, 330045 Jiangxi Province China
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Nanchang, 330045 Jiangxi Province China
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Wang X, Li H, Gao Z, Wang L, Ren Z. Localization of quantitative trait loci for cucumber fruit shape by a population of chromosome segment substitution lines. Sci Rep 2020; 10:11030. [PMID: 32620915 PMCID: PMC7334212 DOI: 10.1038/s41598-020-68312-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 05/29/2020] [Indexed: 12/04/2022] Open
Abstract
Cucumber fruit shape, a significant agronomic trait, is controlled by quantitative trait loci (QTLs). Feasibility of chromosome segment substitution lines (CSSLs) is well demonstrated to map QTLs, especially the minor-effect ones. To detect and identify QTLs with CSSLs can provide new insights into the underlying mechanisms regarding cucumber fruit shape. In the present study, 71 CSSLs were built from a population of backcross progeny (BC4F2) by using RNS7 (a round-fruit cucumber) as the recurrent parent and CNS21 (a long-stick-fruit cucumber) as the donor parent in order to globally detect QTLs for cucumber fruit shape. With the aid of 114 InDel markers covering the whole cucumber genome, 21 QTLs were detected for fruit shape-related traits including ovary length, ovary diameter, ovary shape index, immature fruit length, immature fruit diameter, immature fruit shape index, mature fruit length, mature fruit diameter and mature fruit shape index, and 4 QTLs for other traits including fruit ground and flesh color, and seed size were detected as well. Together our results provide important resources for the subsequent theoretical and applied researches on cucumber fruit shape and other traits.
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Affiliation(s)
- Xiangfei Wang
- State Key Laboratory of Crop Biology; Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huang-Huai Region, Ministry of Agriculture; College of Horticulture Science and Engineering, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Hao Li
- State Key Laboratory of Crop Biology; Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huang-Huai Region, Ministry of Agriculture; College of Horticulture Science and Engineering, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Zhihui Gao
- State Key Laboratory of Crop Biology; Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huang-Huai Region, Ministry of Agriculture; College of Horticulture Science and Engineering, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China
| | - Lina Wang
- State Key Laboratory of Crop Biology; Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huang-Huai Region, Ministry of Agriculture; College of Horticulture Science and Engineering, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China.
| | - Zhonghai Ren
- State Key Laboratory of Crop Biology; Shandong Collaborative Innovation Center of Fruit & Vegetable Quality and Efficient Production; Key Laboratory of Biology and Genetic Improvement of Horticultural Crops in Huang-Huai Region, Ministry of Agriculture; College of Horticulture Science and Engineering, Shandong Agricultural University, Tai'an, 271018, Shandong, People's Republic of China.
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11
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Sakoda K, Kaga A, Tanaka Y, Suzuki S, Fujii K, Ishimoto M, Shiraiwa T. Two novel quantitative trait loci affecting the variation in leaf photosynthetic capacity among soybeans. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2020; 291:110300. [PMID: 31928682 DOI: 10.1016/j.plantsci.2019.110300] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 10/01/2019] [Accepted: 10/03/2019] [Indexed: 05/13/2023]
Abstract
There is a large variation in CO2 assimilation rate per unit of leaf area (A) within or among crop species, which can be exploited to improve A by elucidating the mechanisms underlying such variation. The objective of the present study is to elucidate the genetic factors affecting the variation in leaf photosynthetic capacity among soybeans. Here, we conducted field experiments over three years, using Enrei, a leading variety in Japan, Peking, a landrace from China and the chromosome segment substitution lines derived from their progenies. The gas exchange measurements were conducted to evaluate A among soybean. Peking showed higher A than Enrei after the flowering in all the years. The genetic analysis identified two novel quantitative trait loci (QTLs) related to variation in A, which were located on chromosome 13 (qLPC13) and 20 (qLPC20). The Peking allele at qLPC13 increased A by 8.3 % in the Enrei genetic background, while the Peking allele at qLPC20 decreased A by 15.3 %. The present study is the first report on QTLs affecting a genotypic variation in leaf photosynthetic capacity among field-grown soybeans. The identification of the causal genes in these QTLs can provide a novel strategy to enhance leaf photosynthetic capacity with soybean breeding.
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Affiliation(s)
- Kazuma Sakoda
- Crop Science Laboratory, Graduate School of Agriculture, Kyoto University, Kyoto-city, Kyoto 606-8502, Japan; Research Fellow of Japan Society for the Promotion of Science, Japan.
| | - Akito Kaga
- Soybean and Field Crop Applied Genomics Research Unit, Institute of Crop Science, National Agriculture and Food Research Organization (NARO), Tsukuba-city, Ibaraki, Japan.
| | - Yu Tanaka
- Crop Science Laboratory, Graduate School of Agriculture, Kyoto University, Kyoto-city, Kyoto 606-8502, Japan; JST, PRESTO, Kitashirakawa Oiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan.
| | - Seita Suzuki
- Crop Science Laboratory, Graduate School of Agriculture, Kyoto University, Kyoto-city, Kyoto 606-8502, Japan.
| | - Kenichiro Fujii
- Soybean and Field Crop Applied Genomics Research Unit, Institute of Crop Science, National Agriculture and Food Research Organization (NARO), Tsukuba-city, Ibaraki, Japan.
| | - Masao Ishimoto
- Division of Basic Research, Institute of Crop Science, National Agriculture and Food Research Organization (NARO), Tsukuba, Ibaraki 305-8518, Japan.
| | - Tatsuhiko Shiraiwa
- Crop Science Laboratory, Graduate School of Agriculture, Kyoto University, Kyoto-city, Kyoto 606-8502, Japan.
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12
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Pratap A, Das A, Kumar S, Gupta S. Current Perspectives on Introgression Breeding in Food Legumes. FRONTIERS IN PLANT SCIENCE 2020; 11:589189. [PMID: 33552095 PMCID: PMC7858677 DOI: 10.3389/fpls.2020.589189] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 12/03/2020] [Indexed: 05/22/2023]
Abstract
Food legumes are important for defeating malnutrition and sustaining agri-food systems globally. Breeding efforts in legume crops have been largely confined to the exploitation of genetic variation available within the primary genepool, resulting in narrow genetic base. Introgression as a breeding scheme has been remarkably successful for an array of inheritance and molecular studies in food legumes. Crop wild relatives (CWRs), landraces, and exotic germplasm offer great potential for introgression of novel variation not only to widen the genetic base of the elite genepool for continuous incremental gains over breeding cycles but also to discover the cryptic genetic variation hitherto unexpressed. CWRs also harbor positive quantitative trait loci (QTLs) for improving agronomic traits. However, for transferring polygenic traits, "specialized population concept" has been advocated for transferring QTLs from CWR into elite backgrounds. Recently, introgression breeding has been successful in developing improved cultivars in chickpea (Cicer arietinum), pigeonpea (Cajanus cajan), peanut (Arachis hypogaea), lentil (Lens culinaris), mungbean (Vigna radiata), urdbean (Vigna mungo), and common bean (Phaseolus vulgaris). Successful examples indicated that the usable genetic variation could be exploited by unleashing new gene recombination and hidden variability even in late filial generations. In mungbean alone, distant hybridization has been deployed to develop seven improved commercial cultivars, whereas in urdbean, three such cultivars have been reported. Similarly, in chickpea, three superior cultivars have been developed from crosses between C. arietinum and Cicer reticulatum. Pigeonpea has benefited the most where different cytoplasmic male sterility genes have been transferred from CWRs, whereas a number of disease-resistant germplasm have also been developed in Phaseolus. As vertical gene transfer has resulted in most of the useful gene introgressions of practical importance in food legumes, the horizontal gene transfer through transgenic technology, somatic hybridization, and, more recently, intragenesis also offer promise. The gains through introgression breeding are significant and underline the need of bringing it in the purview of mainstream breeding while deploying tools and techniques to increase the recombination rate in wide crosses and reduce the linkage drag. The resurgence of interest in introgression breeding needs to be capitalized for development of commercial food legume cultivars.
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Affiliation(s)
- Aditya Pratap
- ICAR-Indian Institute of Pulses Research, Kanpur, India
| | - Arpita Das
- Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, India
| | - Shiv Kumar
- International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat Office, Rabat, Morocco
- *Correspondence: Sanjeev Gupta,
| | - Sanjeev Gupta
- ICAR-Indian Institute of Pulses Research, Kanpur, India
- Shiv Kumar,
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13
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Zhang B, Shang L, Ruan B, Zhang A, Yang S, Jiang H, Liu C, Hong K, Lin H, Gao Z, Hu J, Zeng D, Guo L, Qian Q. Development of Three Sets of High-Throughput Genotyped Rice Chromosome Segment Substitution Lines and QTL Mapping for Eleven Traits. RICE (NEW YORK, N.Y.) 2019; 12:33. [PMID: 31076960 PMCID: PMC6510774 DOI: 10.1186/s12284-019-0293-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 04/22/2019] [Indexed: 05/04/2023]
Abstract
BACKGROUND Detecting and mapping chromosomal regions that are related to quantitative phenotypic variation in chromosome segment substitution lines (CSSLs) provides an effective means to characterize the genetic basis of complex agronomic trait. CSSLs are also powerful tools for studying the effects of quantitative trait loci (QTLs) pyramiding and interaction on phenotypic variation. RESULTS Here, we developed three sets of CSSLs consisting of 81, 55, and 61 lines, which were derived from PA64s × 9311, Nipponbare × 9311 and PA64s × Nipponbare crosses, respectively. All of the 197 CSSLs were subjected to high-throughput genotyping by whole-genome resequencing to obtain accurate physical maps for the 3 sets of CSSLs. The 3 sets of CSSLs were used to analyze variation for 11 major agronomic traits in Hangzhou and Shenzhen and led to the detection of 71 QTLs with phenotypic effect that ranged from 7.6% to 44.8%. Eight QTLs were commonly detected under two environments for the same phenotype, and there were also 8 QTL clusters that were found. Combined with GWAS on grain length and expression profiles on young panicle tissues, qGL1 detected in CSSLs was fine mapped within a 119 kb region on chromosome 1 and LOC_Os01g53140 and LOC_Os01g53250 were the two most likely candidate genes. CONCLUSIONS Our results indicate that developing CSSLs genotyped by whole-genome resequencing are powerful tools for basic genetic research and provide a platform for the rational design of rice breeding. Meanwhile, the conjoint analysis of different CSSLs, natural population and expression profiles can facilitate QTL fine mapping.
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Affiliation(s)
- Bin Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Lianguang Shang
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Banpu Ruan
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Anpeng Zhang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Shenglong Yang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Hongzhen Jiang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Chaolei Liu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Kai Hong
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Hai Lin
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China
| | - Zhenyu Gao
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Jiang Hu
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Dali Zeng
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Longbiao Guo
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China
| | - Qian Qian
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, 310006, China.
- Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, China.
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Balakrishnan D, Surapaneni M, Mesapogu S, Neelamraju S. Development and use of chromosome segment substitution lines as a genetic resource for crop improvement. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1-25. [PMID: 30483819 DOI: 10.1007/s00122-018-3219-y] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Accepted: 10/24/2018] [Indexed: 05/27/2023]
Abstract
CSSLs are a complete library of introgression lines with chromosomal segments of usually a distant genotype in an adapted background and are valuable genetic resources for basic and applied research on improvement of complex traits. Chromosome segment substitution lines (CSSLs) are genetic stocks representing the complete genome of any genotype in the background of a cultivar as overlapping segments. Ideally, each CSSL has a single chromosome segment from the donor with a maximum recurrent parent genome recovered in the background. CSSL development program requires population-wide backcross breeding and genome-wide marker-assisted selection followed by selfing. Each line in a CSSL library has a specific marker-defined large donor segment. CSSLs are evaluated for any target phenotype to identify lines significantly different from the parental line. These CSSLs are then used to map quantitative trait loci (QTLs) or causal genes. CSSLs are valuable prebreeding tools for broadening the genetic base of existing cultivars and harnessing the genetic diversity from the wild- and distant-related species. These are resources for genetic map construction, mapping QTLs, genes or gene interactions and their functional analysis for crop improvement. In the last two decades, the utility of CSSLs in identification of novel genomic regions and QTL hot spots influencing a wide range of traits has been well demonstrated in food and commercial crops. This review presents an overview of how CSSLs are developed, their status in major crops and their use in genomic studies and gene discovery.
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Affiliation(s)
- Divya Balakrishnan
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Malathi Surapaneni
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sukumar Mesapogu
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India
| | - Sarla Neelamraju
- ICAR- National Professor Project, ICAR- Indian Institute of Rice Research, Hyderabad, India.
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15
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Okada S, Onogi A, Iijima K, Hori K, Iwata H, Yokoyama W, Suehiro M, Yamasaki M. Identification of QTLs for rice grain size using a novel set of chromosomal segment substitution lines derived from Yamadanishiki in the genetic background of Koshihikari. BREEDING SCIENCE 2018; 68:210-218. [PMID: 29875604 PMCID: PMC5982188 DOI: 10.1270/jsbbs.17112] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 11/13/2017] [Indexed: 05/20/2023]
Abstract
Grain size is important for brewing-rice cultivars, but the genetic basis for this trait is still unclear. This paper aims to identify QTLs for grain size using novel chromosomal segment substitution lines (CSSLs) harboring chromosomal segments from Yamadanishiki, an excellent sake-brewing rice, in the genetic background of Koshihikari, a cooking cultivar. We developed a set of 49 CSSLs. Grain length (GL), grain width (GWh), grain thickness (GT), 100-grain weight (GWt) and days to heading (DTH) were evaluated, and a CSSL-QTL analysis was conducted. Eighteen QTLs for grain size and DTH were identified. Seven (qGL11, qGWh5, qGWh10, qGWt6-2, qGWt10-2, qDTH3, and qDTH6) that were detected in F2 and recombinant inbred lines (RILs) from Koshihikari/Yamadanishiki were validated, suggesting that they are important for large grain size and heading date in Yamadanishiki. Additionally, QTL reanalysis for GWt showed that qGWt10-2 was only detected in early-flowering RILs, while qGWt5 (in the same region as qGWh5) was only detected in late-flowering RILs, suggesting that these QTLs show different responses to the environment. Our study revealed that grain size in the Yamadanishiki cultivar is determined by a complex genetic mechanism. These findings could be useful for the breeding of both cooking and brewing rice.
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Affiliation(s)
- Satoshi Okada
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
| | - Akio Onogi
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo,
Yayoi, Bunkyo-Ku, Tokyo 113-8657,
Japan
| | - Ken Iijima
- Institute of Crop Science, National Agriculture and Food Research Organization,
Tsukuba, Ibaraki 305-8518,
Japan
| | - Kiyosumi Hori
- Institute of Crop Science, National Agriculture and Food Research Organization,
Tsukuba, Ibaraki 305-8518,
Japan
| | - Hiroyoshi Iwata
- Department of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo,
Yayoi, Bunkyo-Ku, Tokyo 113-8657,
Japan
| | - Wakana Yokoyama
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
| | - Miki Suehiro
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
| | - Masanori Yamasaki
- Food Resources Education and Research Center, Graduate School of Agricultural Science, Kobe University,
Kasai, Hyogo 675-2103,
Japan
- Corresponding author (e-mail: )
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16
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Yang H, Wang W, He Q, Xiang S, Tian D, Zhao T, Gai J. Chromosome segment detection for seed size and shape traits using an improved population of wild soybean chromosome segment substitution lines. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2017; 23:877-889. [PMID: 29158636 PMCID: PMC5671450 DOI: 10.1007/s12298-017-0468-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 06/22/2017] [Accepted: 09/01/2017] [Indexed: 05/15/2023]
Abstract
Size and shape of soybean seeds are closely related to seed yield and market value. Annual wild soybeans have the potential to improve cultivated soybeans, but their inferior seed characteristics should be excluded. To detect quantitative trait loci (QTLs)/segments of seed size and shape traits in annual wild soybean, its chromosome segment substitution lines (CSSLs) derived from NN1138-2 (recurrent parent, Glycine max) and N24852 (donor parent, Glycine soja) and then modified 2 iterations (coded SojaCSSLP3) were improved further to contain more lines (diagonal segments) and less heterozygous and missing portions. The new population (SojaCSSLP4) composed of 195 CSSLs was evaluated under four environments, and 11, 13, 7, 15 and 14 QTLs/segments were detected for seed length (SL), seed width (SW), seed roundness (SR), seed perimeter (SP) and seed cross section area (SA), respectively, with all 60 wild allele effects negative. Among them, 16 QTLs/segments were shared by 2-5 traits, respectively, but 0-3 segments for each of the 5 traits were independent. The non-shared Satt274 and shared Satt305, Satt540 and Satt239 were major segments, along with other segments composed of two different but related sets of genetic systems for SR and the other 4 traits, respectively. Compared with the literature, 7 SL, 5 SW and 2 SR QTLs/segments were also detected in cultivated soybeans; allele distinction took place between cultivated and wild soybeans, and also among cultivated parents. The present mapping is understood as macro-segment mapping, the segments may be further dissected into smaller segments as well as corresponding QTLs/genes.
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Affiliation(s)
- Hongyan Yang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
| | - Wubin Wang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
| | - Qingyuan He
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
| | - Shihua Xiang
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
| | - Dong Tian
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
| | - Tuanjie Zhao
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
| | - Junyi Gai
- Soybean Research Institute, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
- National Center for Soybean Improvement, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Nanjing, 210095 Jiangsu China
- National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095 Jiangsu China
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Jiang N, Shi S, Shi H, Khanzada H, Wassan GM, Zhu C, Peng X, Yu Q, Chen X, He X, Fu J, Hu L, Xu J, Ouyang L, Sun X, Zhou D, He H, Bian J. Mapping QTL for Seed Germinability under Low Temperature Using a New High-Density Genetic Map of Rice. FRONTIERS IN PLANT SCIENCE 2017; 8:1223. [PMID: 28747923 PMCID: PMC5506081 DOI: 10.3389/fpls.2017.01223] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 06/28/2017] [Indexed: 05/05/2023]
Abstract
Mapping major quantitative trait loci (QTL) responsible for rice seed germinability under low temperature (GULT) can provide valuable genetic source for improving cold tolerance in rice breeding. In this study, 124 rice backcross recombinant inbred lines (BRILs) derived from a cross indica cv. Changhui 891 and japonica cv. 02428 were genotyped through re-sequencing technology. A bin map was generated which includes 3057 bins covering distance of 1266.5 cM with an average of 0.41 cM between markers. On the basis of newly constructed high-density genetic map, six QTL were detected ranging from 40 to 140 kb on Nipponbare genome. Among these, two QTL qCGR8 and qGRR11 alleles shared by 02428 could increase GULT and seed germination recovery rate after cold stress, respectively. However, qNGR1 and qNGR4 may be two major QTL affecting indica Changhui 891germination under normal condition. QTL qGRR1 and qGRR8 affected the seed germination recovery rate after cold stress and the alleles with increasing effects were shared by the Changhui 891 could improve seed germination rate after cold stress dramatically. These QTL could be a highly valuable genetic factors for cold tolerance improvement in rice lines. Moreover, the BRILs developed in this study will serve as an appropriate choice for mapping and studying genetic basis of rice complex traits.
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Affiliation(s)
- Ningfei Jiang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Shilai Shi
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Huan Shi
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Hira Khanzada
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
| | - Ghulam M. Wassan
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
| | - Changlan Zhu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops in ChinaChangsha, China
| | - Xiaosong Peng
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Qiuying Yu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
| | - Xiaorong Chen
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Xiaopeng He
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Junru Fu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Lifang Hu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops in ChinaChangsha, China
| | - Jie Xu
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Linjuan Ouyang
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Xiaotang Sun
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops in ChinaChangsha, China
| | - Dahu Zhou
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
| | - Haohua He
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops in ChinaChangsha, China
- *Correspondence: Jianmin Bian, Haohua He,
| | - Jianmin Bian
- Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Jiangxi Agricultural UniversityNanchang, China
- College of Agronomy, Jiangxi Agricultural UniversityNanchang, China
- Southern Regional Collaborative Innovation Center for Grain and Oil Crops in ChinaChangsha, China
- *Correspondence: Jianmin Bian, Haohua He,
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Qiao W, Qi L, Cheng Z, Su L, Li J, Sun Y, Ren J, Zheng X, Yang Q. Development and characterization of chromosome segment substitution lines derived from Oryza rufipogon in the genetic background of O. sativa spp. indica cultivar 9311. BMC Genomics 2016; 17:580. [PMID: 27507407 PMCID: PMC4979106 DOI: 10.1186/s12864-016-2987-5] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 08/02/2016] [Indexed: 12/25/2022] Open
Abstract
Background Wild rice (Oryza rufipogon) constitutes a primary gene source for rice breed improvement. Chromosome segment substitution line (CSSL) for O. rufipogon is a powerful tool for fine mapping of quantitative traits, new gene discovery, and marker-assisted breeding. Thus, they provide a basis for a wide range of genomic and genetic studies. Results In this study, a set of 198 CSSLs were developed from a cross between recurrent parent indica var. 9311 and an O. rufipogon donor parent; these were then genotyped using 313 polymorphic SSR markers evenly distributed across the 12 rice chromosomes. On average, each CSSL carried 2.16 introgressed segments, and the genetic distance of each segment was about 6 cM. The segments collectively covered 84.9 % of the wild rice genome. Based on these CSSLs, 25 QTLs involved in 10 agronomic traits were identified. Seven CSSLs were subjected to a whole-genome single nucleotide polymorphism chip assay and two QTLs, qSH4-1 and qDTH10-1, detected. In addition, a new QTL associated with the heading date was detected in a 78-Kb region on chromosome 10, thus proving the ability of these CSSLs to identify new QTLs and genes. Conclusions The newly developed CSSL population proved a useful tool for both gene identification and whole-genome research of wild rice. These CSSL materials will provide a foundation for rice variety improvement. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2987-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Weihua Qiao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Lan Qi
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China.,Institute of Cereal Crop Science, Hainan Academy of Agricultural Sciences, 14 Xingdan Road, Haikou, Hainan, 571100, China
| | - Zhijun Cheng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Long Su
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Jing Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Yan Sun
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Junfang Ren
- Institute of Tropical Horticulture, Hainan Academy of Agricultural Sciences, 14 Xingdan Road, Haikou, Hainan, 571100, China
| | - Xiaoming Zheng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China
| | - Qingwen Yang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, Haidian, 100081, China.
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Prince SJ, Beena R, Gomez SM, Senthivel S, Babu RC. Mapping Consistent Rice (Oryza sativa L.) Yield QTLs under Drought Stress in Target Rainfed Environments. RICE (NEW YORK, N.Y.) 2015; 8:53. [PMID: 26206756 PMCID: PMC4513014 DOI: 10.1186/s12284-015-0053-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 05/22/2015] [Indexed: 05/26/2023]
Abstract
BACKGROUND Drought stress is a major limitation to rainfed rice production and yield stability. Identifying yield-associated quantitative trait loci (QTLs) that are consistent under drought stress predominant in target production environments, as well as across different genetic backgrounds, will help to develop high-yielding rice cultivars suitable for water-limited environments through marker-assisted breeding (MAB). Considerable progress has been made in mapping QTLs for drought resistance traits in rice; however, few have been successfully used in MAB. RESULTS Recombinant inbred lines of IR20 × Nootripathu, two indica cultivars adapted to rainfed target populations of environments (TPEs), were evaluated in one and two seasons under managed stress and in a rainfed target drought stress environment, respectively. In the managed stress environment, the severity of the stress meant that measurements could be made only on secondary traits and biomass. In the target environment, the lines experienced varying timings, durations, and intensities of drought stress. The rice recombinant inbred lines exhibited significant genotypic variation for physio-morphological, phenological, and plant production traits under drought. Nine and 24 QTLs for physio-morphological and plant production traits were identified in managed and natural drought stress conditions in the TPEs, respectively. Yield QTLs that were consistent in the target environment over seasons were identified on chromosomes 1, 4, and 6, which could stabilize the productivity in high-yielding rice lines in a water-limited rainfed ecosystem. These yield QTLs also govern highly heritable key secondary traits, such as leaf drying, canopy temperature, panicle harvest index and harvest index. CONCLUSION Three QTL regions on chromosome 1 (RM8085), chromosome 4 (I12S), and chromosome 6 (RM6836) harbor significant additive QTLs for various physiological and yield traits under drought stress. The similar chromosomal region on 4 and 6 were found to harbor QTLs for canopy temperature and leaf drying under drought stress conditions. Thus, the identified large effect yield QTLs could be introgressed to develop rice lines with stable yields under varying natural drought stress predominant in TPEs.
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Affiliation(s)
- Silvas J Prince
- Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University (TNAU), Coimbatore, 641 003 India
| | - R Beena
- Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University (TNAU), Coimbatore, 641 003 India
| | - S Michael Gomez
- International Center for Tropical Agriculture (CIAT), Colombia, 6713 Colombia
| | - S Senthivel
- Agricultural Research Station, Tamil Nadu Agricultural University (TNAU), Paramakudi, 623707 India
| | - R Chandra Babu
- Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University (TNAU), Coimbatore, 641 003 India
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20
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QTL mapping and correlation analysis for 1000-grain weight and percentage of grains with chalkiness in rice. J Genet 2013; 92:281-7. [DOI: 10.1007/s12041-013-0267-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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