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Yoon DK, Choi I, Won YJ, Shin Y, Cheon KS, Oh H, Lee C, Lee S, Cho MH, Jun S, Kim Y, Kim SL, Baek J, Jeong H, Lyu JI, Lee GS, Kim KH, Ji H. QTL Mapping of Tiller Number in Korean Japonica Rice Varieties. Genes (Basel) 2023; 14:1593. [PMID: 37628644 PMCID: PMC10454613 DOI: 10.3390/genes14081593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 07/25/2023] [Accepted: 08/02/2023] [Indexed: 08/27/2023] Open
Abstract
Tiller number is an important trait associated with yield in rice. Tiller number in Korean japonica rice was analyzed under greenhouse conditions in 160 recombinant inbred lines (RILs) derived from a cross between the temperate japonica varieties Odae and Unbong40 to identify quantitative trait loci (QTLs). A genetic map comprising 239 kompetitive allele-specific PCR (KASP) and 57 cleaved amplified polymorphic sequence markers was constructed. qTN3, a major QTL for tiller number, was identified at 132.4 cm on chromosome 3. This QTL was also detected under field conditions in a backcross population; thus, qTN3 was stable across generations and environments. qTN3 co-located with QTLs associated with panicle number per plant and culm diameter, indicating it had pleiotropic effects. The qTN3 regions of Odae and Unbong40 differed in a known functional variant (4 bp TGTG insertion/deletion) in the 5' UTR of OsTB1, a gene underlying variation in tiller number and culm strength. Investigation of variation in genotype and tiller number revealed that varieties with the insertion genotype had lower tiller numbers than those with the reference genotype. A high-resolution melting marker was developed to enable efficient marker-assisted selection. The QTL qTN3 will therefore be useful in breeding programs developing japonica varieties with optimal tiller numbers for increased yield.
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Affiliation(s)
- Dong-Kyung Yoon
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Inchan Choi
- Department of Agricultural Engineering, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54875, Republic of Korea;
| | - Yong Jae Won
- Cheorwon Branch, National Institute of Crop Science, Rural Development Administration (RDA), Cheorwon 24010, Republic of Korea;
| | - Yunji Shin
- Genecell Biotech Inc., Wanju 55322, Republic of Korea;
| | - Kyeong-Seong Cheon
- Department of Forest Bioresources, National Institute of Forest Science, Suwon 16631, Republic of Korea;
| | - Hyoja Oh
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Chaewon Lee
- Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration (RDA), Suwon 16429, Republic of Korea;
| | - Seoyeon Lee
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Mi Hyun Cho
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Soojin Jun
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Yeongtae Kim
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Song Lim Kim
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Jeongho Baek
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - HwangWeon Jeong
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Jae Il Lyu
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Gang-Seob Lee
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Kyung-Hwan Kim
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
| | - Hyeonso Ji
- Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration (RDA), Jeonju 54874, Republic of Korea; (D.-K.Y.); (H.O.); (S.L.); (M.H.C.); (S.J.); (Y.K.); (S.L.K.); (J.B.); (H.J.); (J.I.L.); (G.-S.L.); (K.-H.K.)
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Zhao DD, Park JR, Jang YH, Kim EG, Du XX, Farooq M, Yun BJ, Kim KM. Identification of One Major QTL and a Novel Gene OsIAA17q5 Associated with Tiller Number in Rice Using QTL Analysis. PLANTS (BASEL, SWITZERLAND) 2022; 11:538. [PMID: 35214873 PMCID: PMC8875189 DOI: 10.3390/plants11040538] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/16/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
Rice tillers are one of the most important traits for the yield and development of rice, although little is known about its mode of inheritance. Tiller numbers were recorded every 7 days a total of nine times, starting 30 days after transplantation. Quantitative trait locus (QTL) based analysis on a set of double haploid population derivatives of a cross between the Cheongcheong and Nagdong varieties identified a major effect of locus RM18130-RM3381 on chromosome 5, which was expressed in eight different growth stages. Within the target region RM18130-RM3381 (physical distance: 2.08 Mb), 61 candidate genes were screened by annotation. Among the candidate genes, Os05g0230700 (named OsIAA17q5), which belongs to the family of auxin-responsive genes, was selected as a target. Auxin promotes cell division and meristem maintenance and is an effective plant regulator which influences plant growth and development by altering the expression of various genes. OsIAA17q5 is expected to control the number of tillers. The present study provides further understanding of the basic genetic mechanisms that selectively express the control of tiller numbers in different growth stages, as well as provides valuable information for future research aimed at cloning the target gene. These results may contribute to developing a comprehensive understanding of the basic genetic processes regulating the developmental behavior of tiller numbers in rice.
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Affiliation(s)
- Dan-Dan Zhao
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
| | - Jae-Ryoung Park
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
- Crop Breeding Division, National Institute of Crop Science, Rural Development Administration, Wanju 55365, Korea
| | - Yoon-Hee Jang
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
| | - Eun-Gyeong Kim
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
| | - Xiao-Xuan Du
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu 41566, Korea;
- Biosafety Division, National Institute of Agricultural Science, Jeonju 54874, Korea
| | - Muhammad Farooq
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
| | - Byoung-Ju Yun
- School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Korea
| | - Kyung-Min Kim
- Division of Plant Biosciences, School of Applied Biosciences, College of Agriculture and Life Science, Kyungpook National University, Daegu 41566, Korea; (D.-D.Z.); (J.-R.P.); (Y.-H.J.); (E.-G.K.); (M.F.)
- Coastal Agriculture Research Institute, Kyungpook National University, Daegu 41566, Korea;
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Ren M, Huang M, Qiu H, Chun Y, Li L, Kumar A, Fang J, Zhao J, He H, Li X. Genome-Wide Association Study of the Genetic Basis of Effective Tiller Number in Rice. RICE (NEW YORK, N.Y.) 2021; 14:56. [PMID: 34170442 PMCID: PMC8233439 DOI: 10.1186/s12284-021-00495-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 05/17/2021] [Indexed: 05/14/2023]
Abstract
BACKGROUND Effective tiller number (ETN) has a pivotal role in determination of rice (Oryza sativa L.) grain yield. ETN is a complex quantitative trait regulated by both genetic and environmental factors. Despite multiple tillering-related genes have been cloned previously, few of them have been utilized in practical breeding programs. RESULTS In this study, we conducted a genome-wide association study (GWAS) for ETN using a panel of 490 rice accessions derived from the 3 K rice genomes project. Thirty eight ETN-associated QTLs were identified, interestingly, four of which colocalized with the OsAAP1, DWL2, NAL1, and OsWRKY74 gene previously reported to be involved in rice tillering regulation. Haplotype (Hap) analysis revealed that Hap5 of OsAAP1, Hap3 and 6 of DWL2, Hap2 of NAL1, and Hap3 and 4 of OsWRKY74 are favorable alleles for ETN. Pyramiding favorable alleles of all these four genes had more enhancement in ETN than accessions harboring the favorable allele of only one gene. Moreover, we identified 25 novel candidate genes which might also affect ETN, and the positive association between expression levels of the OsPILS6b gene and ETN was validated by RT-qPCR. Furthermore, transcriptome analysis on data released on public database revealed that most ETN-associated genes showed a relatively high expression from 21 days after transplanting (DAT) to 49 DAT and decreased since then. This unique expression pattern of ETN-associated genes may contribute to the transition from vegetative to reproductive growth of tillers. CONCLUSIONS Our results revealed that GWAS is a feasible way to mine ETN-associated genes. The candidate genes and favorable alleles identified in this study have the potential application value in rice molecular breeding for high ETN and grain yield.
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Affiliation(s)
- Mengmeng Ren
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Minghan Huang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871 China
- Peking University Institute of Advanced Agricultural Sciences, Weifang, 261325 Shandong China
| | - Haiyang Qiu
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Yan Chun
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Lu Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Ashmit Kumar
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jingjing Fang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Jinfeng Zhao
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
| | - Hang He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871 China
- Peking University Institute of Advanced Agricultural Sciences, Weifang, 261325 Shandong China
| | - Xueyong Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081 China
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Zhao S, Jang S, Lee YK, Kim DG, Jin Z, Koh HJ. Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies. PLANTS 2020; 9:plants9121695. [PMID: 33276582 PMCID: PMC7761586 DOI: 10.3390/plants9121695] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 11/27/2020] [Accepted: 11/29/2020] [Indexed: 11/16/2022]
Abstract
A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, HD1 was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination (R2) of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.
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Affiliation(s)
- Shuyu Zhao
- Department of Plant Science, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea; (S.Z.); (S.J.); (Y.K.L.)
- Department of Agronomy, College of Agriculture, Northeast Agricultural University, Harbin 150030, China;
| | - Su Jang
- Department of Plant Science, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea; (S.Z.); (S.J.); (Y.K.L.)
| | - Yoon Kyung Lee
- Department of Plant Science, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea; (S.Z.); (S.J.); (Y.K.L.)
| | - Dong-Gwan Kim
- Department of Bioindustry and Bioresource Engineering, Department of Molecular Biology and Plant Engineering Research Institute, Sejong University, Seoul 05006, Korea;
| | - Zhengxun Jin
- Department of Agronomy, College of Agriculture, Northeast Agricultural University, Harbin 150030, China;
| | - Hee-Jong Koh
- Department of Plant Science, Plant Genomics and Breeding Institute, Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea; (S.Z.); (S.J.); (Y.K.L.)
- Correspondence:
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Tanase DM, Gosav EM, Neculae E, Costea CF, Ciocoiu M, Hurjui LL, Tarniceriu CC, Maranduca MA, Lacatusu CM, Floria M, Serban IL. Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies. Nutrients 2020; 12:nu12123719. [PMID: 33276482 PMCID: PMC7760723 DOI: 10.3390/nu12123719] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 11/27/2020] [Accepted: 11/30/2020] [Indexed: 12/12/2022] Open
Abstract
A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, HD1 was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination (R2) of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.
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Affiliation(s)
- Daniela Maria Tanase
- Department of Internal Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iasi, Romania; (D.M.T.); (M.F.)
- Internal Medicine Clinic, “St. Spiridon” County Clinical Emergency Hospital Iasi, 700115 Iasi, Romania
| | - Evelina Maria Gosav
- Department of Internal Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iasi, Romania; (D.M.T.); (M.F.)
- Internal Medicine Clinic, “St. Spiridon” County Clinical Emergency Hospital Iasi, 700115 Iasi, Romania
- Correspondence:
| | - Ecaterina Neculae
- Department of Gastroenterology, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
- Institute of Gastroenterology and Hepatology, “St. Spiridon” County Clinical Emergency Hospital Iasi, 700111 Iasi, Romania
| | - Claudia Florida Costea
- Department of Ophthalmology, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
- 2nd Ophthalmology Clinic, “Nicolae Oblu” Emergency Clinical Hospital, 700309 Iași, Romania
| | - Manuela Ciocoiu
- Department of Pathophysiology, Faculty of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
| | - Loredana Liliana Hurjui
- Department of Morpho-Functional Sciences II, Physiology Discipline, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (L.L.H.); (M.A.M.); (I.L.S.)
- Hematology Laboratory, “St. Spiridon” County Clinical Emergency Hospital, 700111 Iasi, Romania
| | - Claudia Cristina Tarniceriu
- Department of Morpho-Functional Sciences I, Discipline of Anatomy, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
- Hematology Clinic, “St. Spiridon” County Clinical Emergency Hospital, 700111 Iasi, Romania
| | - Minela Aida Maranduca
- Department of Morpho-Functional Sciences II, Physiology Discipline, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (L.L.H.); (M.A.M.); (I.L.S.)
| | - Cristina Mihaela Lacatusu
- Unit of Diabetes, Nutrition and Metabolic Diseases, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania;
- Clinical Center of Diabetes, Nutrition and Metabolic Diseases, “St. Spiridon” County Clinical Emergency Hospital, 700111 Iasi, Romania
| | - Mariana Floria
- Department of Internal Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iasi, Romania; (D.M.T.); (M.F.)
- Internal Medicine Clinic, Emergency Military Clinical Hospital, 700483 Iasi, Romania
| | - Ionela Lacramioara Serban
- Department of Morpho-Functional Sciences II, Physiology Discipline, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania; (L.L.H.); (M.A.M.); (I.L.S.)
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Ma X, Li F, Zhang Q, Wang X, Guo H, Xie J, Zhu X, Ullah Khan N, Zhang Z, Li J, Li Z, Zhang H. Genetic architecture to cause dynamic change in tiller and panicle numbers revealed by genome-wide association study and transcriptome profile in rice. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 104:1603-1616. [PMID: 33058400 DOI: 10.1111/tpj.15023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 09/24/2020] [Accepted: 10/02/2020] [Indexed: 05/27/2023]
Abstract
Panicle number (PN) is one of the three yield components in rice. As one of the most unstable traits, the dynamic change in tiller number (DCTN) may determine the final PN. However, the genetic basis of DCTN and its relationship with PN remain unclear. Here, 377 deeply re-sequenced rice accessions were used to perform genome-wide association studies (GWAS) for tiller/PN. It was found that the DCTN pattern rather than maximum tiller number or effective tiller ratio is the determinant factor of high PN. The DCTN pattern that affords more panicles exhibits a period of stable tillering peak between 30 and 45 days after transplant (called DT30 and DT45, respectively), which was believed as an ideal pattern contributing to the steady transition from tiller development to panicle development (ST-TtP). Consistently, quantitative trait loci (QTL) expressed near DT30-DT45 were especially critical to the rice DCTN and in supporting the ST-TtP. The spatio-temporal expression analysis showed that the expression pattern of keeping relatively high expression in root at 24:00 (R24-P2) from about DT30 to DT45 is a typical expression pattern of cloned tiller genes, and the candidate genes with R24-P2 can facilitate the prediction of PN. Moreover, gene OsSAUR27 was identified by an integrated approach combining GWAS, bi-parental QTL mapping and transcription. These findings related to the genetic basis underlying the DCTN will provide the genetic theory in making appropriate decisions on field management, and in developing new varieties with high PN and ideal dynamic plant architecture.
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Affiliation(s)
- Xiaoqian Ma
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Fengmei Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
- School of Life Science and Technology, Xinxiang University, Henan, 453003, China
| | - Quan Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xueqiang Wang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Haifeng Guo
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jianyin Xie
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Xiaoyang Zhu
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Najeeb Ullah Khan
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhanying Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Jinjie Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zichao Li
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Hongliang Zhang
- State Key Laboratory of Agrobiotechnology/Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
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Wang T, Song H, Li P, Wei Y, Hu N, Chen Z, Wang W, Liu J, Zhang B, Peng R. Transcriptome Analysis Provides Insights into Grain Filling in Foxtail Millet ( Setaria italica L.). Int J Mol Sci 2020; 21:ijms21145031. [PMID: 32708737 PMCID: PMC7403974 DOI: 10.3390/ijms21145031] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 07/08/2020] [Accepted: 07/13/2020] [Indexed: 12/16/2022] Open
Abstract
Grain filling is an importantly developmental process which is associated with the yield and quality of foxtail millet (Setaria italic L.). However, the molecular mechanisms of grain filling are rarely reported in foxtail millet. In our study, RNA-seq was performed to investigate the transcriptional dynamics and identify the key genes involved in grain filling in foxtail millet at five different developmental stages. A total of 11,399 differentially expressed genes (DEGs), including 902 transcription factors (TFs), were identified. Certain important genes involved in grain filling were discovered through a function annotation and temporal expression patterns analysis. These genes included genes associated with starch biosynthesis, cell-wall invertases, hormone signal transduction, and polyamine metabolism pathways. The expression levels of seven randomly selected DEGs were validated by a quantitative real-time polymerase chain reaction (qRT-PCR). This study provides the first insight into the changes in the gene expression of grain filling at different developmental stages in foxtail millet. These results could help understand the complex molecular mechanisms of the panicle formation in foxtail millet and other cereal crops.
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Affiliation(s)
- Tao Wang
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
- Innovation and Practice Base for Postdoctors, Anyang Institute of Technology, Anyang 455000, China
| | - Hui Song
- Anyang Academy of Agriculture Sciences, Anyang 455000, China; (H.S.); (J.L.)
| | - Pengtao Li
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
| | - Yangyang Wei
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
| | - Nan Hu
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
| | - Zhenwen Chen
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
| | - Weiqi Wang
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
| | - Jinrong Liu
- Anyang Academy of Agriculture Sciences, Anyang 455000, China; (H.S.); (J.L.)
| | - Baohong Zhang
- Department of Biology, East Carolina University, Greenville, NC 27858, USA
- Correspondence: (B.Z.); (R.P.); Tel.: +1-252-328-2021 (B.Z.); +86-372-2909279 (R.P.)
| | - Renhai Peng
- College of Biology and Food Engineering, Anyang Institute of Technology, Anyang 455000, China; (T.W.); (P.L.); (Y.W.); (N.H.); (Z.C.); (W.W.)
- Correspondence: (B.Z.); (R.P.); Tel.: +1-252-328-2021 (B.Z.); +86-372-2909279 (R.P.)
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Mapping dynamic QTL dissects the genetic architecture of grain size and grain filling rate at different grain-filling stages in barley. Sci Rep 2019; 9:18823. [PMID: 31827117 PMCID: PMC6906516 DOI: 10.1038/s41598-019-53620-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 08/31/2019] [Indexed: 02/07/2023] Open
Abstract
Grain filling is an important growth process in formation of yield and quality for barley final yield determination. To explore the grain development behavior during grain filling period in barley, a high-density genetic map with 1962 markers deriving from a doubled haploid (DH) population of 122 lines was used to identify dynamic quantitative trait locus (QTL) for grain filling rate (GFR) and five grain size traits: grain area (GA), grain perimeter (GP), grain length (GL), grain width (GW) and grain diameter (GD). Unconditional QTL mapping is to detect the cumulative effect of genetic factors on a phenotype from development to a certain stage. Conditional QTL mapping is to detect a net effect of genetic factors on the phenotype at adjacent time intervals. Using unconditional, conditional and covariate QTL mapping methods, we successfully detected 34 major consensus QTLs. Moreover, certain candidate genes related to grain size, plant height, yield, and starch synthesis were identified in six QTL clusters, and individual gene was specifically expressed in different grain filling stages. These findings provide useful information for understanding the genetic basis of the grain filling dynamic process and will be useful for molecular marker-assisted selection in barley breeding.
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Xue H, Tian X, Zhang K, Li W, Qi Z, Fang Y, Li X, Wang Y, Song J, Li WX, Ning H. Mapping developmental QTL for plant height in soybean [Glycine max (L.) Merr.] using a four-way recombinant inbred line population. PLoS One 2019; 14:e0224897. [PMID: 31747415 PMCID: PMC6867651 DOI: 10.1371/journal.pone.0224897] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 10/23/2019] [Indexed: 12/03/2022] Open
Abstract
Plant height (PH) is an important trait in soybean, as taller plants may have higher yields but may also be at risk for lodging. Many genes act jointly to influence PH throughout development. To map the quantitative trait loci (QTL) controlling PH, we used the unconditional variable method (UVM) and conditional variable method (CVM) to analyze PH data for a four-way recombinant inbred line (FW-RIL) population derived from the cross of (Kenfeng14 × Kenfeng15) × (Heinong48 × Kenfeng19). We identified 7, 8, 16, 19, 15, 27, 17, 27, 22, and 24 QTL associated with PH at 10 developmental stages, respectively. These QTL mapped to 95 genomic regions. Among these QTL, 9 were detected using UVM and CVM, and 89 and 66 were only detected by UVM or CVM, respectively. In total, 36 QTL controlling PH were detected at multiple developmental stages and these made unequal contributions to genetic variation throughout development. Among 19 novel regions discovered in our study, 7 could explain over 10% of the phenotypic variation and contained only one single QTL. The unconditional and conditional QTL detected here could be used in molecular design breeding across the whole developmental procedure.
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Affiliation(s)
- Hong Xue
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
- Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Keshan,Heilongjiang, China
| | - Xiaocui Tian
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Kaixin Zhang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Wenbin Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Zhongying Qi
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Yanlong Fang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Xiyu Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Yue Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Jie Song
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Harbin, China
- Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Harbin, China
- College of Crop Science, Northeast Agricultural University, Harbin, Heilongjiang province, China
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Makumbi D, Alvarado G, Crossa J, Burgueño J. SASHAYDIALL: A SAS Program for Hayman's Diallel Analysis. CROP SCIENCE 2018; 58:1605-1615. [PMID: 33343012 PMCID: PMC7680942 DOI: 10.2135/cropsci2018.01.0047] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2018] [Accepted: 04/17/2018] [Indexed: 05/18/2023]
Abstract
Different methods of diallel crossing are commonly used in plant breeding. The diallel cross analysis method proposed by Hayman is particularly useful because it provides information, among others, on additive and dominance effects of genes, average degree of dominance, proportion of dominance, direction of dominance, distribution of genes, maternal and reciprocal effects, number of groups of genes that control a trait and exhibit dominance, ratio of dominant to recessive alleles in all the parents, and broad-sense and narrow-sense heritability. In this paper, we fully describe a SAS-based software SASHAYDIALL for performing a complete diallel cross analysis based on Hayman's model with or without reciprocals. We demonstrate the use of SASHAYDIALL with two data sets; one is a published diallel cross data set with reciprocals in cabbage (Brassica oleracea L.), and the second is a data set from a multilocation diallel cross trial in maize (Zea mays L.) without reciprocals. With SASHAYDIALL, diallel experiments conducted in single sites can be analyzed to estimate various genetic parameters, and this analysis is extended over locations or environments to assess genetic effect × environment interaction. SASHAYDIALL is user-friendly software that provides detailed genetic information from diallel crosses involving any number of parents and locations.
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Affiliation(s)
- Dan Makumbi
- International Maize and Wheat Improvement Center (CIMMYT), PO Box 1041-00621, Nairobi, Kenya
- Corresponding author (). Assigned to Associate Editor Natalia de Leon
| | - Gregorio Alvarado
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico DF, Mexico
| | - José Crossa
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico DF, Mexico
| | - Juan Burgueño
- Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico DF, Mexico
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11
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Wang X, Wang H, Long Y, Liu L, Zhao Y, Tian J, Zhao W, Li B, Chen L, Chao H, Li M. Dynamic and comparative QTL analysis for plant height in different developmental stages of Brassica napus L. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1175-92. [PMID: 25796183 DOI: 10.1007/s00122-015-2498-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Accepted: 03/10/2015] [Indexed: 05/04/2023]
Abstract
This report describes a dynamic QTL analysis for plant height at various stages using a large doubled haploid population and performs a QTL comparison between different populations in Brassica napus. Plant height (PH) not only plays an important role in determining plant architecture, but is also an important character related to yield. The process of determining PH occurs through a series of steps; however, no studies have focused on developmental behavior factors affecting PH in Brassica napus. In the present study, KN DH, a large doubled haploid population containing 348 lines was used for a dynamic quantitative trait locus (QTL) analysis for PH in six experiments. In all, 20 QTLs were identified at maturity, whereas 50 QTLs were detected by conditional m apping method and the same number was identified by unconditional mapping strategies. Interestingly, five unconditional QTLs ucPH.A2-2, ucPH.A3-2, ucPH.C5-1, ucPH.C6-2 and ucPH.C6-3 were identified that were consistent over the all growth stages of one or two particular experiments, and one conditional QTL cPH.A2-3 was expressed throughout the entire growth process in one experiment. A total of 70 QTLs were obtained after combining QTLs identified at maturity, by conditional and unconditional mapping strategies, in which 25 showed opposite genetic effects in different periods/stages and experiments. A consensus map containing 1357 markers was constructed to compare QTLs identified in the KN population with five previously mapped populations. Alignment of the QTLs detected in different populations onto the consensus map showed that 27 were repeatedly detected in different genetic backgrounds. These findings will enhance our understanding of the genetic control of PH regulation in B. napus, and will be useful for rapeseed genetic manipulation through molecular marker-assisted selection.
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Affiliation(s)
- Xiaodong Wang
- College of Life Science and Technology, Key Laboratory of Molecular Biology, Physics of Ministry of Education, Huazhong University of Science and Technology, Wuhan, 430074, China
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12
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Liu G, Zhu H, Zhang G, Li L, Ye G. Dynamic analysis of QTLs on tiller number in rice (Oryza sativa L.) with single segment substitution lines. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2012; 125:143-53. [PMID: 22350178 DOI: 10.1007/s00122-012-1822-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2012] [Accepted: 02/03/2012] [Indexed: 05/05/2023]
Abstract
Twelve single segment substitution lines (SSSLs) in rice, which contain quantitative trait loci (QTLs) for tiller number detected previously, were used to study dynamic expression of the QTLs in this study. These SSSLs and their recipient, Hua-Jing-Xian 74 (HJX74), were used to produce 78 crossing combinations first, and then these combinations and their parents were grown in two planting seasons with three cropping densities. Tiller number was measured at seven developmental stages. QTL effects including main effects (additive, dominance and epistasis), QTL × season and QTL × density interaction effects were analyzed at each measured stage. The additive, dominant and epistatic effects of the 12 QTLs as well as their interaction effects with the seasons and with the densities all display dynamic changes with the development. Eight QTLs are detected with significant additive effects and/or additive × season and/or additive × density interaction effects at least at one developmental stage, and all QTLs have significant dominant and epistatic effects and/or interaction effects involved in. For most of the QTLs dominant effects are much bigger than additive effects, showing overdominance. Each QTL interacts at least with eight other QTLs. Additive and dominant effects of these QTLs are mostly positive while epistatic effects are negative and minor. Most of the QTLs show significant interactions with planting seasons and cropping densities, but the additive effects of QTLs Tn3-1 and Tn3-2, the dominant effects of QTL Tn7 and Tn8, and the epistatic effects of 14 pairs of QTLs are stable across seasons and the dominant effect of QTL Tn3-3 and the epistatic effects of QTL pairs Tn2-1/Tn6-2, Tn2-1/Tn9 and Tn3-3/Tn6-3 are nearly consistent across cropping densities. This paper is the first report of dynamics on dominances and epistasis of QTLs for tiller number in rice and provides abundant information, which is useful to improve rice tiller number via heterosis and/or QTL pyramiding.
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Affiliation(s)
- Guifu Liu
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People's Republic of China
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13
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Functional mapping of quantitative trait loci associated with rice tillering. Mol Genet Genomics 2010; 284:263-71. [PMID: 20690030 DOI: 10.1007/s00438-010-0566-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2010] [Accepted: 07/22/2010] [Indexed: 10/19/2022]
Abstract
Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang-Lan-Ding mathematical model. Four biologically meaningful parameters in this model--the potential maximum for tiller number (K), the optimum tiller time (t(0)), and the increased rate (r), or the reduced rate (c) at the time of deviation from t(0)--were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49-8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.
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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: 30] [Impact Index Per Article: 2.1] [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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Liu G, Zeng R, Zhu H, Zhang Z, Ding X, Zhao F, Li W, Zhang G. Dynamic expression of nine QTLs for tiller number detected with single segment substitution lines in rice. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2009; 118:443-53. [PMID: 18949451 DOI: 10.1007/s00122-008-0911-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2008] [Accepted: 10/02/2008] [Indexed: 05/05/2023]
Abstract
Nine single segment substitution lines (SSSLs) in rice, which contain quantitative trait loci (QTLs) for tiller number on substituted segments detected in previous studies, were selected as materials to analyse dynamic expression of the QTLs in this study. These SSSLs and their recipient parent, Hua-jing-xian 74 (HJX74), were grown in four different environments and were measured for tiller number at nine different growth stages. An indirect methodology was applied in QTL mapping through analyzing multi-environment phenotypic data. Dynamics of three types of effects (including total effect, main effect, and QE interaction effect) of QTLs was released. It was shown that nine QTLs exhibited statistically significant effects only at certain stages. Effects of a QTL, although insignificant at certain stages, displayed dynamic change with the growth of rice plants. Two common features of nine QTLs were detected, one is no expression within 7 days after transplanting, and the other is opposite expression existed during the whole growth period. Nine QTLs largely focused on expression in certain stages, and accordingly were suggested to partition into three types, expression in prophase, both in prophase and in anaphase, and evenly during the whole stage. It may be reasonable explanation that dynamics of main effects of QTLs are likely due to gene expression selectly at certain times, while dynamics of QE interaction effects of QTLs might attribute to the subrogation of environmental factors. Examination of the association between QE interaction effect and specified environmental factors across stages may provide useful information on how an environmental factor regulates QTL expression.
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Affiliation(s)
- Guifu Liu
- Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, 510642, Guangzhou, People's Republic of China
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Wu J, McCarty JC, Saha S, Jenkins JN, Hayes R. Genetic changes in plant growth and their associations with chromosomes from Gossypium barbadense L. in G. hirsutum L. Genetica 2009; 137:57-66. [PMID: 19153810 DOI: 10.1007/s10709-008-9350-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2008] [Accepted: 12/22/2008] [Indexed: 11/29/2022]
Abstract
Cotton (Gossypium spp.) plant growth is an important time-specific agronomic character that supports the development of squares, flowers, boll retention, and yield. With the use of a mixed linear model approach, we investigated 14 cotton chromosome substitution (CS-B) lines and their chromosome-specific F(2) hybrids for genetic changes in plant growth that was measured during the primary flowering time under two environments. The changes in additive and dominance variances for plant height and number of mainstem nodes are reported, showing that additive effects for these two traits were a key genetic component after initial flowering occurred in the field. Time-specific genetic variance components were also detected where phenotypic values observed at time t were conditioned on the events occurring at time t - 1, demonstrating new genetic variations arising at several time intervals during plant growth. Results also revealed that plant height and number of nodes shared some common influence due to additive effects during plant development. With the comparative analyzes, chromosomes associated with the genetic changes in plant growth were detected. Therefore, these results should add new understanding of the genetics underlying these time-specific traits.
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Affiliation(s)
- Jixiang Wu
- Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762, USA.
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Tang J, Zeng W, Wang W, Ma B, Liu Y, Li H, Xia H, Li P, Zhu L. Genetic analysis and gene mapping of a rice few-tillering mutant in early backcross populations (Oryza sativa L.). SCIENCE IN CHINA. SERIES C, LIFE SCIENCES 2008; 44:570-5. [PMID: 18763097 DOI: 10.1007/bf02879350] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2001] [Indexed: 11/28/2022]
Abstract
A rice mutant, G069, characteristic of few tiller numbers, was found in anther culture progeny from the F(1) hybrid between an indica-japonica cross, Gui630x02428. The mutant has another two major features: delayed tillering development and yellowing apex and margin on the mature leaves. As a donor parent, G069 was further backcrossed with the recurrent parent,02428, for two turns to develop aBC (2)F(2) population. Genetic analysis in the BC (2)F(2) population showed that the traits of few-tillering and yellowing apex and margin on the mature leaves were controlled by one recessive gene. A pool of equally mixed genomic DNA, from few-tillering individual plants in BC (2)F(2), was constructed to screen polymorphism with simple sequence repeat (SSR) markers in comparison with the 02428 genome. One SSR marker and three restriction fragment length polymorphism (RFLP) markers were found possibly linked with the recessive gene. By using these markers, the gene of few-tillering was mapped on chromosome 2 between RFLP marker C424 and S13984 with a genetic distance of 2.4 cM and 0.6 cM, respectively. The gene is designated ft1.
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Affiliation(s)
- J Tang
- Rice Research Institute, Sichuan Agricultural University, Chengdu, China
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18
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Jiang ZX, Wang SQ, Deng QM, He TH, Li P. Genetic analysis and molecular tagging on a novel excessive tillering mutant in rice. ACTA ACUST UNITED AC 2006; 33:339-44. [PMID: 16625832 DOI: 10.1016/s0379-4172(06)60059-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A rice (Oryza sativa L.) mutant with an excessive tiller number, designated ext-M1B, was found in the F2 progenies generated from the cross between M1B and GMS-1 (a genetic male sterile), whose number of tillers was 121. The excessive tillering mutant also resulted in significant changes in plant height, flag leaf, stem, filled grains per panicle, and productive panicles per plant. The inbreeding progenies of ext-M1B exhibited the same mutant phenotype. The crosses from ext-M1B/M1B, M1B/ext-M1B, 2480B/ext-M1B, D62B/ext-M1B, G46B/ext-M1B, and G683B/ext-M1B expressed normal tillering in F1, and segregated into two different phenotypes of normal tillering type and excessive tillering type in a ratio of 3:1 in F2. Inheritance analysis indicated that the excessive tillering character was controlled by a single recessive nucleic gene. By BSA (bulked segregants analysis) and microsatellite makers with the F2 population of 2480B/ext-M1B as the mapping population, RM197, RM584, and RM225, all of which were located on the short arm of rice chromosome 6, were identified to be linked with the excessive tillering gene with genetic distance of 3.8 cM, 5.1 cM, and 5.2 cM, respectively. This gene is probably a new excessive tillering gene in rice and is designated tentatively ext-M1B (t).
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Affiliation(s)
- Zhao-Xue Jiang
- Rice Research Institute, Sichuan Agricultural University, Chengdu, China.
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Wu WR, Li WM, Tang DZ, Lu HR, Worland AJ. Time-related mapping of quantitative trait loci underlying tiller number in rice. Genetics 1999; 151:297-303. [PMID: 9872968 PMCID: PMC1460454 DOI: 10.1093/genetics/151.1.297] [Citation(s) in RCA: 110] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Using time-related phenotypic data, methods of composite interval mapping and multiple-trait composite interval mapping based on least squares were applied to map quantitative trait loci (QTL) underlying the development of tiller number in rice. A recombinant inbred population and a corresponding saturated molecular marker linkage map were constructed for the study. Tiller number was recorded every 4 or 5 days for a total of seven times starting at 20 days after sowing. Five QTL were detected on chromosomes 1, 3, and 5. These QTL explained more than half of the genetic variance at the final observation. All the QTL displayed an S-shaped expression curve. Three QTL reached their highest expression rates during active tillering stage, while the other two QTL achieved this either before or after the active tillering stage.
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Affiliation(s)
- W R Wu
- College of Crop Sciences, Fujian Agricultural University, Fuzhou, Fujian 350002, People's Republic of China.
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Yan J, Zhu J, He C, Benmoussa M, Wu P. Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.). Genetics 1998; 150:1257-65. [PMID: 9799277 PMCID: PMC1460389 DOI: 10.1093/genetics/150.3.1257] [Citation(s) in RCA: 128] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A doubled haploid population of 123 lines from IR64/Azucena was used to dissect the developmental behavior and genotype by environment interaction for plant height by conditional and unconditional quantitative trait loci (QTL) mapping methods in rice. It was shown that the number of QTL detected was different at various measuring stages. Some QTL could be detected at all stages and some only at one or several stages. More QTL could be found on the basis of time-dependent measures of different stages. By conditional QTL mapping of time-dependent measures, it is possible to reveal dynamic gene expression for quantitative traits. Mapping QTL for genetic main effects and GE interaction effects could help us in understanding the nature of QTL x environment interaction for the development of quantitative traits.
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Affiliation(s)
- J Yan
- Department of Agronomy, Zhejiang Agricultural University, Hangzhou, 310029, China
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