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Zhang B, Huang Y, Zhang L, Zhou Z, Zhou S, Duan W, Yang C, Gao Y, Li S, Chen M, Li Y, Yang X, Zhang G, Huang D. Genome-Wide Association Study Unravels Quantitative Trait Loci and Genes Associated with Yield-Related Traits in Sugarcane. J Agric Food Chem 2023; 71:16815-16826. [PMID: 37856846 DOI: 10.1021/acs.jafc.3c02935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Sugarcane, a major sugar and energy crop worldwide faces an increasing demand for higher yields. Identifying yield-related markers and candidate genes is valuable for breeding high-yield varieties using molecular techniques. In this work, seven yield-related traits were evaluated in a diversity panel of 159 genotypes, derived from Tripidium arundinaceum, Saccharum spontaneum, and modern sugarcane genotypes. All traits exhibited significant genetic variance with high heritability and high correlations. Genetic diversity analysis reveals a genomic decay of 23 kb and an average single nucleotide polymorphism (SNP) number of 25,429 per genotype. These 159 genotypes were divided into 4 subgroups. Genome-wide association analysis identified 47 SNPs associated with brix, spanning 36 quantitative trait loci (QTLs), and 138 SNPs for other traits across 104 QTLs, covering all 32 chromosomes. Interestingly, 12 stable QTLs associated with yield-related traits were identified, which contained 35 candidate genes. This work provides markers and candidate genes for marker-assisted breeding to improve sugarcane yields.
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Affiliation(s)
- Baoqing Zhang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Yuxin Huang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Lijun Zhang
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China
| | - Zhongfeng Zhou
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Shan Zhou
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Weixing Duan
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Cuifang Yang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Yijing Gao
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Sicheng Li
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China
| | - Meiyan Chen
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China
| | - Yangrui Li
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Xiping Yang
- State Key Laboratory of Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China
| | - Gemin Zhang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
| | - Dongliang Huang
- Key Laboratory of Sugarcane Biotechnology and Genetic Improvement (Guangxi), Ministry of Agriculture and Rural Affairs, Guangxi Key Laboratory of Sugarcane Genetic Improvement, Sugarcane Research Institute, Guangxi Academy of Agricultural Sciences, Sugarcane Research Center, Chinese Academy of Agricultural Sciences, Nanning 530007, China
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Islam MS, Corak K, McCord P, Hulse-Kemp AM, Lipka AE. A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane. Front Plant Sci 2023; 14:1205999. [PMID: 37600177 PMCID: PMC10433174 DOI: 10.3389/fpls.2023.1205999] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 07/03/2023] [Indexed: 08/22/2023]
Abstract
The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.
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Affiliation(s)
| | - Keo Corak
- Genomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United States
| | - Per McCord
- Sugarcane Field Station, USDA-ARS, Canal Point, FL, United States
- Irrigated Agriculture Research and Extension Center, Washington State University, Prosser, WA, United States
| | - Amanda M. Hulse-Kemp
- Genomics and Bioinformatics Research Unit, USDA-ARS, Raleigh, NC, United States
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC, United States
| | - Alexander E. Lipka
- Department of Crop Sciences, University of Illinois, Urbana-Champaign, IL, United States
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Wang L, Yeo S, Lee M, Endah S, Alhuda NA, Yue GH. Combination of GWAS and F ST-based approaches identified loci associated with economic traits in sugarcane. Mol Genet Genomics 2023:10.1007/s00438-023-02040-2. [PMID: 37289230 DOI: 10.1007/s00438-023-02040-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 05/28/2023] [Indexed: 06/09/2023]
Abstract
Sugarcane is a globally important plant for both sugar and biofuel production. Although conventional breeding has played an important role in increasing the productivity of sugarcane, it takes a long time to achieve breeding goals such as high yield and resistant to diseases. Molecular breeding, including marker-assisted breeding and genomic selection, can accelerate genetic improvement by selecting elites at the seedling stage with DNA markers. However, only a few DNA markers associated with important traits were identified in sugarcane. The purpose of this study was to identify DNA markers associated with sugar content, stalk diameter, and sugarcane top borer resistance. The sugarcane samples with trait records were genotyped using the restriction site-associated DNA sequencing (RADseq) technology. Using FST analysis and genome-wide association study (GWAS), a total of 9, 23 and 9 DNA variants (single nucleotide polymorphisms (SNPs)/insertions and deletions (indels)) were associated with sugar content, stalk diameter, and sugarcane top borer resistance, respectively. The identified genetic variants were on different chromosomes, suggesting that these traits are complex and determined by multiple genetic factors. These DNA markers identified by both approaches have the potential to be used in selecting elite clones at the seeding stage in our sugarcane breeding program to accelerate genetic improvement. Certainly, it is essential to verify the reliability of the identified DNA markers associated with traits before they are used in molecular breeding in other populations.
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Affiliation(s)
- Le Wang
- Temasek Life Sciences Laboratory, National University of Singapore, 1 Research Link, Singapore, 117604, Singapore
| | - Shadame Yeo
- Temasek Life Sciences Laboratory, National University of Singapore, 1 Research Link, Singapore, 117604, Singapore
| | - May Lee
- Temasek Life Sciences Laboratory, National University of Singapore, 1 Research Link, Singapore, 117604, Singapore
| | - S Endah
- Research and Development, PT Gunung Madu Plantations, KM 90 Terusan Nunyai, Central Lampung, Lampung, 34167, Indonesia
| | - N A Alhuda
- Research and Development, PT Gunung Madu Plantations, KM 90 Terusan Nunyai, Central Lampung, Lampung, 34167, Indonesia
| | - G H Yue
- Temasek Life Sciences Laboratory, National University of Singapore, 1 Research Link, Singapore, 117604, Singapore.
- Department of Biological Sciences, National University of Singapore, 14 Science Drive, Singapore, 117543, Singapore.
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Liu G, Li Y, Sun X, Guo X, Jiang N, Fang Y, Chen J, Bao Z, Ma F. Association study of SNP locus for color related traits in herbaceous peony ( Paeonia lactiflora Pall.) using SLAF-seq. Front Plant Sci 2022; 13:1032449. [PMID: 36544869 PMCID: PMC9760751 DOI: 10.3389/fpls.2022.1032449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
Paeonia lactiflora Pall. (P. lactiflora) is a famous ornamental plant with showy and colorful flowers that has been domesticated in China for 4,000 years. However, the genetic basis of phenotypic variation and genealogical relationships in P. lactiflora population is poorly understood due to limited genetic information, which brings about bottlenecks in the application of effective and efficient breeding strategies. Understanding the genetic basis of color-related traits is essential for improving flower color by marker-assisted selection (MAS). In this study, a high throughput sequencing of 99 diploid P. lactiflora accessions via specific-locus amplified fragment sequencing (SLAF-seq) technology was performed. In total, 4,383,645 SLAF tags were developed from 99 P. lactiflora accessions with an average sequencing depth of 20.81 for each SLAF tag. A total of 2,954,574 single nucleotide polymorphisms (SNPs) were identified from all SLAF tags. The population structure and phylogenetic analysis showed that P. lactiflora population used in this study could be divided into six divergent groups. Through association study using Mixed linear model (MLM), we further identified 40 SNPs that were significantly positively associated with petal color. Moreover, a derived cleaved amplified polymorphism (dCAPS) marker that was designed based on the SLAF tag 270512F co-segregated with flower colors in P. lactiflora population. Taken together, our results provide valuable insights into the application of MAS in P. lactiflora breeding programs.
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Affiliation(s)
- Genzhong Liu
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai-An, Shandong, China
| | - Ying Li
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai-An, Shandong, China
| | - Xia Sun
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai-An, Shandong, China
| | - Xianfeng Guo
- College of Forestry, Shandong Agricultural University, Tai-An, Shandong, China
| | - Nannan Jiang
- Institute of ornamental plants, Shandong Academy of Forestry, Jinan, Shandong, China
| | - Yifu Fang
- Institute of ornamental plants, Shandong Academy of Forestry, Jinan, Shandong, China
| | - Junqiang Chen
- Institute of ornamental plants, Shandong Academy of Forestry, Jinan, Shandong, China
| | - Zhilong Bao
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai-An, Shandong, China
| | - Fangfang Ma
- State Key Laboratory of Crop Biology, College of Horticulture Science and Engineering, Shandong Agricultural University, Tai-An, Shandong, China
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O’Connell A, Deo J, Deomano E, Wei X, Jackson P, Aitken KS, Manimekalai R, Mohanraj K, Hemaprabha G, Ram B, Viswanathan R, Lakshmanan P. Combining genomic selection with genome-wide association analysis identified a large-effect QTL and improved selection for red rot resistance in sugarcane. Front Plant Sci 2022; 13:1021182. [DOI: 10.3389/fpls.2022.1021182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/29/2022] [Indexed: 11/13/2022]
Abstract
Red rot caused by the fungus Colletotrichum falcatum is the main disease limiting sugarcane productivity in several countries including the major producer India. The genetic basis for red rot resistance is unclear. We studied a panel of 305 sugarcane clones from the Australian breeding program for disease response phenotype and genotype using an Affymetrix® Axiom® array, to better understand the genetic basis of red rot resistance. SNP markers highly significantly associated with red rot response (≤ 10-8) were identified. Markers with largest effect were located in a single 14.6 Mb genomic region of sorghum (the closest diploid relative of sugarcane with a sequenced genome) suggesting the presence of a major-effect QTL. By genomic selection, the estimated selection accuracy was ~0.42 for red rot resistance. This was increased to ~0.5 with the addition of 29 highly significant SNPs as fixed effects. Analysis of genes nearby the markers linked to the QTL revealed many biotic stress responsive genes within this QTL, with the most significant SNP co-locating with a cluster of four chitinase A genes. The SNP markers identified here could be used to predict red rot resistance with high accuracy at any stage in the sugarcane breeding program.
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