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Ndlovu N, Kachapur RM, Beyene Y, Das B, Ogugo V, Makumbi D, Spillane C, McKeown PC, Prasanna BM, Gowda M. Linkage mapping and genomic prediction of grain quality traits in tropical maize ( Zea mays L.). Front Genet 2024; 15:1353289. [PMID: 38456017 PMCID: PMC10918846 DOI: 10.3389/fgene.2024.1353289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/07/2024] [Indexed: 03/09/2024] Open
Abstract
The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.
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Affiliation(s)
- Noel Ndlovu
- Agriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Rajashekar M. Kachapur
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
- University of Agricultural Sciences, Dharwad, Karnataka, India
| | - Yoseph Beyene
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Biswanath Das
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Veronica Ogugo
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Dan Makumbi
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
| | - Charles Spillane
- Agriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland
| | - Peter C. McKeown
- Agriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland
| | | | - Manje Gowda
- International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya
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Kamal NM, Gorafi YSA, Tomemori H, Kim JS, Elhadi GMI, Tsujimoto H. Genetic variation for grain nutritional profile and yield potential in sorghum and the possibility of selection for drought tolerance under irrigated conditions. BMC Genomics 2023; 24:515. [PMID: 37660014 PMCID: PMC10474746 DOI: 10.1186/s12864-023-09613-w] [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: 03/28/2023] [Accepted: 08/22/2023] [Indexed: 09/04/2023] Open
Abstract
BACKGROUND Increasing grain nutritional value in sorghum (Sorghum bicolor) is a paramount breeding objective, as is increasing drought resistance (DR), because sorghum is grown mainly in drought-prone areas. The genetic basis of grain nutritional traits remains largely unknown. Marker-assisted selection using significant loci identified through genome-wide association study (GWAS) shows potential for selecting desirable traits in crops. This study assessed natural variation available in sorghum accessions from around the globe to identify novel genes or genomic regions with potential for improving grain nutritional value, and to study associations between DR traits and grain weight and nutritional composition. RESULTS We dissected the genetic architecture of grain nutritional composition, protein content, thousand-kernel weight (TKW), and plant height (PH) in sorghum through GWAS of 163 unique African and Asian accessions under irrigated and post-flowering drought conditions. Several QTLs were detected. Some were significantly associated with DR, TKW, PH, protein, and Zn, Mn, and Ca contents. Genomic regions on chromosomes 1, 2, 4, 8, 9, and 10 were associated with TKW, nutritional, and DR traits; colocalization patterns of these markers indicate potential for simultaneous improvement of these traits. In African accessions, markers associated with TKW were mapped to six regions also associated with protein, Zn, Ca, Mn, Na, and DR, suggesting the potential for simultaneous selection for higher grain nutrition and TKW. Our results indicate that it may be possible to select for increased DR on the basis of grain nutrition and weight potential. CONCLUSIONS This study provides a valuable resource for selecting landraces for use in plant breeding programs and for identifying loci that may contribute to grain nutrition and weight with the hope of producing cultivars that combine improved yield traits, nutrition, and DR.
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Affiliation(s)
- Nasrein Mohamed Kamal
- Arid Land Research Center, Tottori University, Tottori, 680-0001, Japan.
- Agricultural Research Corporation, PO Box 126, Wad Medani, Sudan.
| | - Yasir Serag Alnor Gorafi
- Agricultural Research Corporation, PO Box 126, Wad Medani, Sudan
- International Platform for Dryland Research and Education, Tottori University, Tottori, Japan
| | - Hisashi Tomemori
- Arid Land Research Center, Tottori University, Tottori, 680-0001, Japan
| | - June-Sik Kim
- RIKEN Center for Sustainable Resource Science, Yokohama, 230-0045, Japan
- Institute of Plant Science and Resources, Okayama University, Kurashiki, 710-0046, Japan
| | | | - Hisashi Tsujimoto
- Arid Land Research Center, Tottori University, Tottori, 680-0001, Japan.
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Sethi M, Saini DK, Devi V, Kaur C, Singh MP, Singh J, Pruthi G, Kaur A, Singh A, Chaudhary DP. Unravelling the genetic framework associated with grain quality and yield-related traits in maize ( Zea mays L.). Front Genet 2023; 14:1248697. [PMID: 37609038 PMCID: PMC10440565 DOI: 10.3389/fgene.2023.1248697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 07/26/2023] [Indexed: 08/24/2023] Open
Abstract
Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population's hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing.
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Affiliation(s)
- Mehak Sethi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Veena Devi
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Charanjeet Kaur
- Department of Basic Sciences and Humanities, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Mohini Prabha Singh
- Department of Floriculture and Landscaping, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Jasneet Singh
- Agricultural and Environmental Sciences, Macdonald Campus, McGill University, Montreal, QC, Canada
| | - Gomsie Pruthi
- Department of Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amanpreet Kaur
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Alla Singh
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
| | - Dharam Paul Chaudhary
- Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, India
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Wan W, Wu Y, Hu D, Ye F, Wu X, Qi X, Liang H, Zhou H, Xue J, Xu S, Zhang X. Genome-wide association analysis of kernel nutritional quality in two natural maize populations. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:18. [PMID: 37313300 PMCID: PMC10248675 DOI: 10.1007/s11032-023-01360-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 02/05/2023] [Indexed: 06/15/2023]
Abstract
As one of the three staple crops, nutritional traits in maize are important for human and animal nutrition. Grain quality-related traits are closely related to grain commercial value. Understanding the genetic basis of quality-related traits in maize would be helpful for breeding high-quality maize varieties. In this study, two association panels (AM122 and AM180) were subjected to genome-wide association analysis of grain quality-related traits, including protein content, oil content, starch content, and fiber content. In total, 98 SNPs (P < 1 × 10-4) were identified to be significantly associated with these four grain quality-related traits. By integrating two sets of public transcriptome data, 31 genes located in 200 kb regions flanking the associated SNP showed high expression during kernel development and were differentially expressed in two maize inbred lines, KA225 and KB035, with significantly different quality. These genes might regulate maize grain quality by participating in plant hormone processes, autophagy processes, and others. All these results could provide important reference information for breeding high‑quality maize varieties. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01360-w.
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Affiliation(s)
- Wenting Wan
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Ying Wu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Die Hu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Fan Ye
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Xiaopeng Wu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Xingyue Qi
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Hangyu Liang
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Haiyang Zhou
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
| | - Jiquan Xue
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Shutu Xu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
| | - Xinghua Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture and Rural Affairs, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre, Yangling, 712100 Shaanxi China
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Guo X, Ge Z, Wang M, Zhao M, Pei Y, Song X. Genome-wide association study of quality traits and starch pasting properties of maize kernels. BMC Genomics 2023; 24:59. [PMID: 36732681 PMCID: PMC9893588 DOI: 10.1186/s12864-022-09031-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 11/21/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Starch are the main nutritional components of maize (Zea mays L.), and starch pasting properties are widely used as essential indicators for quality estimation. Based on the previous studies, various genes related to pasting properties have been identified in maize. However, the loci underlying variations in starch pasting properties in maize inbred lines remain to be identified. RESULTS To investigate the genetic architecture of these traits, the starch pasting properties were examined based on 292 maize inbred lines, which were genotyped with the MaizeSNP50 BeadChip composed of 55,126 evenly spaced, random SNPs. A genome-wide association study (GWAS) implemented in the software package FarmCPU was employed to identify genomic loci for the starch pasting properties. 48 SNPs were found to be associated with pasting properties. Moreover, 37 candidate genes were correlated with pasting properties. Among the candidate genes, GRMZM2G143646 and GRMZM2G166407 were associated with breakdown and final viscosity significantly, and both genes encode PPR (Pentatricopeptide repeat) protein. We used GWAS to explore candidate genes of maize starch pasting properties in this study. The identified candidate genes will be useful for further understanding of the genetic architecture of starch pasting properties in maize. CONCLUSION This study showed a complex regulation network about maize quality trait and starch pasting properties. It may provide some useful markers for marker assisted selection and a basis for cloning the genes behind these SNPs.
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Affiliation(s)
- Xinmei Guo
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Qingdao, 266109 China
| | - Zhaopeng Ge
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Qingdao, 266109 China
| | - Ming Wang
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Qingdao, 266109 China
| | - Meiai Zhao
- grid.412608.90000 0000 9526 6338College of Life Sciences, Qingdao Agricultural University, Qingdao, 266109 China
| | - Yuhe Pei
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Qingdao, 266109 China
| | - Xiyun Song
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Qingdao, 266109 China
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Sa KJ, Park H, Jang SJ, Lee JK. Association Mapping of Amylose Content in Maize RIL Population Using SSR and SNP Markers. PLANTS (BASEL, SWITZERLAND) 2023; 12:239. [PMID: 36678952 PMCID: PMC9865990 DOI: 10.3390/plants12020239] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 12/27/2022] [Accepted: 12/28/2022] [Indexed: 06/17/2023]
Abstract
The ratio of amylose to amylopectin in maize kernel starch is important for the appearance, structure, and quality of food products and processing. This study aimed to identify quantitative trait loci (QTLs) controlling amylose content in maize through association mapping with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. The average value of amylose content for an 80-recombinant-inbred-line (RIL) population was 8.8 ± 0.7%, ranging from 2.1 to 15.9%. We used two different analyses-Q + K and PCA + K mixed linear models (MLMs)-and found 38 (35 SNP and 3 SSR) and 32 (29 SNP and 3 SSR) marker-trait associations (MTAs) associated with amylose content. A total of 34 (31 SNP and 3 SSR) and 28 (25 SNP and 3 SSR) MTAs were confirmed in the Q + K and PCA + K MLMs, respectively. This study detected some candidate genes for amylose content, such as GRMZM2G118690-encoding BBR/BPC transcription factor, which is used for the control of seed development and is associated with the amylose content of rice. GRMZM5G830776-encoding SNARE-interacting protein (KEULE) and the uncharacterized marker PUT-163a-18172151-1376 were significant with higher R2 value in two difference methods. GRMZM2G092296 were also significantly associated with amylose content in this study. This study focused on amylose content using a RIL population derived from dent and waxy inbred lines using molecular markers. Future studies would be of benefit for investigating the physical linkage between starch synthesis genes using SNP and SSR markers, which would help to build a more detailed genetic map and provide new insights into gene regulation of agriculturally important traits.
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Affiliation(s)
- Kyu Jin Sa
- Department of Applied Plant Sciences, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
| | - Hyeon Park
- Department of Applied Plant Sciences, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
- Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon 24341, Republic of Korea
| | - So Jung Jang
- Department of Applied Plant Sciences, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
- Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon 24341, Republic of Korea
| | - Ju Kyong Lee
- Department of Applied Plant Sciences, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea
- Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon 24341, Republic of Korea
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7
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Lu X, Zhou Z, Wang Y, Wang R, Hao Z, Li M, Zhang D, Yong H, Han J, Wang Z, Weng J, Zhou Y, Li X. Genetic basis of maize kernel protein content revealed by high-density bin mapping using recombinant inbred lines. FRONTIERS IN PLANT SCIENCE 2022; 13:1045854. [PMID: 36589123 PMCID: PMC9798238 DOI: 10.3389/fpls.2022.1045854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
Maize with a high kernel protein content (PC) is desirable for human food and livestock fodder. However, improvements in its PC have been hampered by a lack of desirable molecular markers. To identify quantitative trait loci (QTL) and candidate genes for kernel PC, we employed a genotyping-by-sequencing strategy to construct a high-resolution linkage map with 6,433 bin markers for 275 recombinant inbred lines (RILs) derived from a high-PC female Ji846 and low-PC male Ye3189. The total genetic distance covered by the linkage map was 2180.93 cM, and the average distance between adjacent markers was 0.32 cM, with a physical distance of approximately 0.37 Mb. Using this linkage map, 11 QTLs affecting kernel PC were identified, including qPC7 and qPC2-2, which were identified in at least two environments. For the qPC2-2 locus, a marker named IndelPC2-2 was developed with closely linked polymorphisms in both parents, and when tested in 30 high and 30 low PC inbred lines, it showed significant differences (P = 1.9E-03). To identify the candidate genes for this locus, transcriptome sequencing data and PC best linear unbiased estimates (BLUE) for 348 inbred lines were combined, and the expression levels of the four genes were correlated with PC. Among the four genes, Zm00001d002625, which encodes an S-adenosyl-L-methionine-dependent methyltransferase superfamily protein, showed significantly different expression levels between two RIL parents in the endosperm and is speculated to be a potential candidate gene for qPC2-2. This study will contribute to further research on the mechanisms underlying the regulation of maize PC, while also providing a genetic basis for marker-assisted selection in the future.
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Affiliation(s)
- Xin Lu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhiqiang Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunhe Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Ruiqi Wang
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Zhuanfang Hao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingshun Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Degui Zhang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongjun Yong
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jienan Han
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhenhua Wang
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Jianfeng Weng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yu Zhou
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Xinhai Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Zhang X, Wang M, Zhang C, Dai C, Guan H, Zhang R. Genetic dissection of QTLs for starch content in four maize DH populations. FRONTIERS IN PLANT SCIENCE 2022; 13:950664. [PMID: 36275573 PMCID: PMC9583244 DOI: 10.3389/fpls.2022.950664] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 06/30/2022] [Indexed: 05/17/2023]
Abstract
Starch is the principal carbohydrate source in maize kernels. Understanding the genetic basis of starch content (SC) benefits greatly in improving maize yield and optimizing end-use quality. Here, four double haploid (DH) populations were generated and were used to identify quantitative trait loci (QTLs) associated with SC. The phenotype of SC exhibited continuous and approximate normal distribution in each population. A total of 13 QTLs for SC in maize kernels was detected in a range of 3.65-16.18% of phenotypic variation explained (PVE). Among those, only some partly overlapped with QTLs previously known to be related to SC. Meanwhile, 12 genes involved in starch synthesis and metabolism located within QTLs were identified in this study. These QTLs will lay the foundation to explore candidate genes regulating SC in maize kernel and facilitate the application of molecular marker-assisted selection for a breeding program to cultivate maize varieties with a deal of grain quality.
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Affiliation(s)
- Xiaolei Zhang
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Min Wang
- Institute of Advanced Agricultural Technology, Qilu Normal University, Jinan, China
| | | | - Changjun Dai
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Haitao Guan
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Ruiying Zhang
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, China
- *Correspondence: Ruiying Zhang
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Hu S, Wang M, Zhang X, Chen W, Song X, Fu X, Fang H, Xu J, Xiao Y, Li Y, Bai G, Li J, Yang X. Genetic basis of kernel starch content decoded in a maize multi-parent population. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:2192-2205. [PMID: 34077617 PMCID: PMC8541773 DOI: 10.1111/pbi.13645] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/20/2021] [Accepted: 05/31/2021] [Indexed: 05/25/2023]
Abstract
Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome-wide association study in a multi-parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large-effect and many small-effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non-starch-pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway-driven analysis identified ZmTPS9, which encodes a trehalose-6-phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4-2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.
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Affiliation(s)
- Shuting Hu
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Min Wang
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Xuan Zhang
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Wenkang Chen
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Xinran Song
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
- Agronomy CollegeXinjiang Agricultural UniversityUrumqiChina
| | - Xiuyi Fu
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
- Maize Research CenterBeijing Academy of Agriculture & Forestry Sciences (BAAFS)BeijingChina
| | - Hui Fang
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Jing Xu
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Yingni Xiao
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
- Crop Research InstituteGuangdong Academy of Agricultural SciencesKey Laboratory of Crops Genetics and Improvement of Guangdong ProvinceGuangzhouChina
| | - Yaru Li
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Guanghong Bai
- Agronomy CollegeXinjiang Agricultural UniversityUrumqiChina
| | - Jiansheng Li
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
| | - Xiaohong Yang
- State Key Laboratory of Plant Physiology and BiochemistryNational Maize Improvement Center of ChinaMOA Key Lab of Maize BiologyChina Agricultural UniversityBeijingChina
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Singh RK, Prasad A, Muthamilarasan M, Parida SK, Prasad M. Breeding and biotechnological interventions for trait improvement: status and prospects. PLANTA 2020; 252:54. [PMID: 32948920 PMCID: PMC7500504 DOI: 10.1007/s00425-020-03465-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 09/12/2020] [Indexed: 05/06/2023]
Abstract
Present review describes the molecular tools and strategies deployed in the trait discovery and improvement of major crops. The prospects and challenges associated with these approaches are discussed. Crop improvement relies on modulating the genes and genomic regions underlying key traits, either directly or indirectly. Direct approaches include overexpression, RNA interference, genome editing, etc., while breeding majorly constitutes the indirect approach. With the advent of latest tools and technologies, these strategies could hasten the improvement of crop species. Next-generation sequencing, high-throughput genotyping, precision editing, use of space technology for accelerated growth, etc. had provided a new dimension to crop improvement programmes that work towards delivering better varieties to cope up with the challenges. Also, studies have widened from understanding the response of plants to single stress to combined stress, which provides insights into the molecular mechanisms regulating tolerance to more than one stress at a given point of time. Altogether, next-generation genetics and genomics had made tremendous progress in delivering improved varieties; however, the scope still exists to expand its horizon to other species that remain underutilized. In this context, the present review systematically analyses the different genomics approaches that are deployed for trait discovery and improvement in major species that could serve as a roadmap for executing similar strategies in other crop species. The application, pros, and cons, and scope for improvement of each approach have been discussed with examples, and altogether, the review provides comprehensive coverage on the advances in genomics to meet the ever-growing demands for agricultural produce.
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Affiliation(s)
- Roshan Kumar Singh
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Ashish Prasad
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Mehanathan Muthamilarasan
- Department of Plant Sciences, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, 500046, India
| | - Swarup K Parida
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India
| | - Manoj Prasad
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, 110067, India.
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Lin F, Zhou L, He B, Zhang X, Dai H, Qian Y, Ruan L, Zhao H. QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:1931-1941. [PMID: 30887095 DOI: 10.1007/s00122-019-03326-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 03/11/2019] [Indexed: 05/28/2023]
Abstract
A major QTL Qsta9.1 was identified on chromosome 9, combined with GWAS, and co-expression network analysis showed that GRMZM2G110929 and GRMZM5G852704 are the potential candidates for association with maize kernel starch content. Increasing maize kernel starch content may not only lead to higher maize kernel yields and qualities, but also help meet industry demands. By using the intermated B73 × Mo17 population, QTLs were mapped for starch content in this study. A major QTL Qsta9.1 was detected in a 1.7 Mb interval on chromosome 9 and validated by allele frequency analysis in extreme tails of a newly constructed segregating population. According to genome-wide association study (GWAS) based on genotyping of a natural population, we identified a significant SNP for starch content within the ORF region of GRMZM5G852704_T01 colocalized with QTL Qsta9.1. Co-expression network analysis was also conducted, and 28 modules were constructed during six seed developmental stages. Functional enrichment was performed for each module, and one module showed the most possibility for the association with carbohydrate-related processes. In this module, one transcripts GRMZM2G110929_T01 located in the Qsta9.1 assigned 1.7 Mb interval encoding GLABRA2 expression modulator. Its expression level in B73 was lower than that in Mo17 across all seed developmental stages, implying the possibility for the candidate gene of Qsta9.1. Our studies combined GWAS, mRNA profiling, and traditional QTL analyses to identify a major locus for controlling seed starch content in maize.
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Affiliation(s)
- Feng Lin
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Ling Zhou
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Bing He
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Xiaolin Zhang
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Huixue Dai
- Nanjing Institute of Vegetable Sciences, Nanjing, China
| | - Yiliang Qian
- Anhui Academy of Agricultural Sciences, Hefei, China
| | - Long Ruan
- Anhui Academy of Agricultural Sciences, Hefei, China
| | - Han Zhao
- Provincial Key Laboratory of Agrobiology, Institute of Crop Germplasm and Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing, China.
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Genetic architecture of kernel composition in global sorghum germplasm. BMC Genomics 2017; 18:15. [PMID: 28056770 PMCID: PMC5217548 DOI: 10.1186/s12864-016-3403-x] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Accepted: 12/09/2016] [Indexed: 12/30/2022] Open
Abstract
Background Sorghum [Sorghum bicolor (L.) Moench] is an important cereal crop for dryland areas in the United States and for small-holder farmers in Africa. Natural variation of sorghum grain composition (protein, fat, and starch) between accessions can be used for crop improvement, but the genetic controls are still unresolved. The goals of this study were to quantify natural variation of sorghum grain composition and to identify single-nucleotide polymorphisms (SNPs) associated with variation in grain composition concentrations. Results In this study, we quantified protein, fat, and starch in a global sorghum diversity panel using near-infrared spectroscopy (NIRS). Protein content ranged from 8.1 to 18.8%, fat content ranged from 1.0 to 4.3%, and starch content ranged from 61.7 to 71.1%. Durra and bicolor-durra sorghum from Ethiopia and India had the highest protein and fat and the lowest starch content, while kafir sorghum from USA, India, and South Africa had the lowest protein and the highest starch content. Genome-wide association studies (GWAS) identified quantitative trait loci (QTL) for sorghum protein, fat, and starch. Previously published RNAseq data was used to identify candidate genes within a GWAS QTL region. A putative alpha-amylase 3 gene, which has previously been shown to be associated with grain composition traits, was identified as a strong candidate for protein and fat variation. Conclusions We identified promising sources of genetic material for manipulation of grain composition traits, and several loci and candidate genes that may control sorghum grain composition. This survey of grain composition in sorghum germplasm and identification of protein, fat, and starch QTL contributes to our understanding of the genetic basis of natural variation in sorghum grain nutritional traits. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3403-x) contains supplementary material, which is available to authorized users.
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Xiao Y, Thatcher S, Wang M, Wang T, Beatty M, Zastrow-Hayes G, Li L, Li J, Li B, Yang X. Transcriptome analysis of near-isogenic lines provides molecular insights into starch biosynthesis in maize kernel. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2016; 58:713-23. [PMID: 26676690 DOI: 10.1111/jipb.12455] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2015] [Accepted: 12/14/2015] [Indexed: 05/21/2023]
Abstract
Starch is the major component in maize kernels, providing a stable carbohydrate source for humans and livestock as well as raw material for the biofuel industry. Increasing maize kernel starch content will help meet industry demands and has the potential to increase overall yields. We developed a pair of maize near-isogenic lines (NILs) with different alleles for a starch quantitative trait locus on chromosome 3 (qHS3), resulting in different kernel starch content. To investigate the candidate genes for qHS3 and elucidate their effects on starch metabolism, RNA-Seq was performed for the developing kernels of the NILs at 14 and 21 d after pollination (DAP). Analysis of genomic and transcriptomic data identified 76 genes with nonsynonymous single nucleotide polymorphisms and 384 differentially expressed genes (DEGs) in the introgressed fragment, including a hexokinase gene, ZmHXK3a, which catalyzes the conversion of glucose to glucose-6-phosphate and may play a key role in starch metabolism. The expression pattern of all DEGs in starch metabolism shows that altered expression of the candidate genes for qHS3 promoted starch synthesis, with positive consequences for kernel starch content. These results expand the current understanding of starch biosynthesis and accumulation in maize kernels and provide potential candidate genes to increase starch content.
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Affiliation(s)
- Yingni Xiao
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Shawn Thatcher
- DuPont Pioneer, 200 Powder Mill Road, Wilmington, DE 19880, USA
| | - Min Wang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
- College of Agronomy, Northwest Agricultural and Forest University, Yang Ling 712100, China
| | - Tingting Wang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | | | | | - Lin Li
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, Minnesota 55108, USA
| | - Jiansheng Li
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Bailin Li
- DuPont Pioneer, 200 Powder Mill Road, Wilmington, DE 19880, USA
| | - Xiaohong Yang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
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Wang T, Wang M, Hu S, Xiao Y, Tong H, Pan Q, Xue J, Yan J, Li J, Yang X. Genetic basis of maize kernel starch content revealed by high-density single nucleotide polymorphism markers in a recombinant inbred line population. BMC PLANT BIOLOGY 2015; 15:288. [PMID: 26654531 PMCID: PMC4676831 DOI: 10.1186/s12870-015-0675-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2015] [Accepted: 12/03/2015] [Indexed: 05/18/2023]
Abstract
BACKGROUND Starch from maize kernels has diverse applications in human and animal diets and in industry and manufacturing. To meet the demands of these applications, starch quantity and quality need improvement, which requires a clear understanding of the functional mechanisms involved in starch biosynthesis and accumulation. In this study, a recombinant inbred line (RIL) population was developed from a cross between inbred lines CI7 and K22. The RIL population, along with both parents, was grown in three environments, and then genotyped using the MaizeSNP50 BeadChip and phenotyped to dissect the genetic architecture of starch content in maize kernels. RESULTS Based on the genetic linkage map constructed using 2,386 bins as markers, six quantitative trait loci (QTLs) for starch content in maize kernels were detected in the CI7/K22 RIL population. Each QTL accounted for 4.7% (qSTA9-1) to 10.6% (qSTA4-1) of the starch variation. The QTL interval was further reduced using the bin-map method, with the physical distance of a single bin at the QTL peak ranging from 81.7 kb to 2.2 Mb. Based on the functional annotations and prior knowledge of the genes in the top bin, seven genes were considered as potential candidate genes for the identified QTLs. Three of the genes encode enzymes in non-starch metabolism but may indirectly affect starch biosynthesis, and four genes may act as regulators of starch biosynthesis. CONCLUSIONS A few large-effect QTLs, together with a certain number of minor-effect QTLs, mainly contribute to the genetic architecture of kernel starch content in our maize biparental linkage population. All of the identified QTLs, especially the large-effect QTL, qSTA4-1, with a small QTL interval, will be useful for improving the maize kernel starch content through molecular breeding.
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Affiliation(s)
- Tingting Wang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
| | - Min Wang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, China.
| | - Shuting Hu
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
| | - Yingni Xiao
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
| | - Hao Tong
- National Key Laboratory of Crop Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Qingchun Pan
- National Key Laboratory of Crop Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Jiquan Xue
- College of Agronomy, Northwest A&F University, Yangling, Shaanxi, 712100, China.
| | - Jianbing Yan
- National Key Laboratory of Crop Improvement, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
| | - Jiansheng Li
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
| | - Xiaohong Yang
- National Maize Improvement Center of China, Beijing Key Laboratory of Crop Genomics and Genetic Improvement, China Agricultural University, 100193, Beijing, China.
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Lee S, Mian MAR, Sneller CH, Wang H, Dorrance AE, McHale LK. Joint linkage QTL analyses for partial resistance to Phytophthora sojae in soybean using six nested inbred populations with heterogeneous conditions. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:429-44. [PMID: 24247235 DOI: 10.1007/s00122-013-2229-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2013] [Accepted: 10/31/2013] [Indexed: 05/10/2023]
Abstract
Partial resistance to Phytophthora sojae in soybean is controlled by multiple quantitative trait loci (QTL). With traditional QTL mapping approaches, power to detect such QTL, frequently of small effect, can be limited by population size. Joint linkage QTL analysis of nested recombinant inbred line (RIL) populations provides improved power to detect QTL through increased population size, recombination, and allelic diversity. However, uniform development and phenotyping of multiple RIL populations can prove difficult. In this study, the effectiveness of joint linkage QTL analysis was evaluated on combinations of two to six nested RIL populations differing in inbreeding generation, phenotypic assay method, and/or marker set used in genotyping. In comparison to linkage analysis in a single population, identification of QTL by joint linkage analysis was only minimally affected by different phenotypic methods used among populations once phenotypic data were standardized. In contrast, genotyping of populations with only partially overlapping sets of markers had a marked negative effect on QTL detection by joint linkage analysis. In total, 16 genetic regions with QTL for partial resistance against P. sojae were identified, including four novel QTL on chromosomes 4, 9, 12, and 16, as well as significant genotype-by-isolate interactions. Resistance alleles from PI 427106 or PI 427105B contributed to a major QTL on chromosome 18, explaining 10-45% of the phenotypic variance. This case study provides guidance on the application of joint linkage QTL analysis of data collected from populations with heterogeneous assay conditions and a genetic framework for partial resistance to P. sojae.
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Affiliation(s)
- Sungwoo Lee
- Department of Horticulture and Crop Science, The Ohio State University, 1680 Madison Avenue, Wooster, OH, 44691, USA,
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