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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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2
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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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Huang Y, Wang H, Zhu Y, Huang X, Li S, Wu X, Zhao Y, Bao Z, Qin L, Jin Y, Cui Y, Ma G, Xiao Q, Wang Q, Wang J, Yang X, Liu H, Lu X, Larkins BA, Wang W, Wu Y. THP9 enhances seed protein content and nitrogen-use efficiency in maize. Nature 2022; 612:292-300. [PMID: 36385527 DOI: 10.1038/s41586-022-05441-2] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 10/12/2022] [Indexed: 11/17/2022]
Abstract
Teosinte, the wild ancestor of maize (Zea mays subsp. mays), has three times the seed protein content of most modern inbreds and hybrids, but the mechanisms that are responsible for this trait are unknown1,2. Here we use trio binning to create a contiguous haplotype DNA sequence of a teosinte (Zea mays subsp. parviglumis) and, through map-based cloning, identify a major high-protein quantitative trait locus, TEOSINTE HIGH PROTEIN 9 (THP9), on chromosome 9. THP9 encodes an asparagine synthetase 4 enzyme that is highly expressed in teosinte, but not in the B73 inbred, in which a deletion in the tenth intron of THP9-B73 causes incorrect splicing of THP9-B73 transcripts. Transgenic expression of THP9-teosinte in B73 significantly increased the seed protein content. Introgression of THP9-teosinte into modern maize inbreds and hybrids greatly enhanced the accumulation of free amino acids, especially asparagine, throughout the plant, and increased seed protein content without affecting yield. THP9-teosinte seems to increase nitrogen-use efficiency, which is important for promoting a high yield under low-nitrogen conditions.
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Affiliation(s)
- Yongcai Huang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China
| | - Haihai Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China
| | - Yidong Zhu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China.,University of the Chinese Academy of Sciences, Beijing, China
| | - Xing Huang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China.,University of the Chinese Academy of Sciences, Beijing, China
| | - Shuai Li
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Xingguo Wu
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Yao Zhao
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Tai'an, China
| | - Zhigui Bao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Li Qin
- Institute of Molecular Breeding for Maize, Qilu Normal University, Jinan, China
| | - Yongbo Jin
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Yahui Cui
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Guangjin Ma
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China.,University of the Chinese Academy of Sciences, Beijing, China
| | - Qiao Xiao
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China.,University of the Chinese Academy of Sciences, Beijing, China
| | - Qiong Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China
| | - Jiechen Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China
| | - Xuerong Yang
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Tai'an, China
| | - Hongjun Liu
- State Key Laboratory of Crop Biology, Shandong Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Tai'an, China
| | - Xiaoduo Lu
- Institute of Molecular Breeding for Maize, Qilu Normal University, Jinan, China
| | - Brian A Larkins
- School of Plant Sciences, University of Arizona, Tucson, AZ, USA
| | - Wenqin Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, College of Life Sciences, Shanghai Normal University, Shanghai, China.
| | - Yongrui Wu
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology Chinese Academy of Sciences, Shanghai, China.
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Lewis JA, Morran LT. Advantages of laboratory natural selection in the applied sciences. J Evol Biol 2021; 35:5-22. [PMID: 34826161 DOI: 10.1111/jeb.13964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 11/29/2022]
Abstract
In the past three decades, laboratory natural selection has become a widely used technique in biological research. Most studies which have utilized this technique are in the realm of basic science, often testing hypotheses related to mechanisms of evolutionary change or ecological dynamics. While laboratory natural selection is currently utilized heavily in this setting, there is a significant gap with its usage in applied studies, especially when compared to the other selection experiment methodologies like artificial selection and directed evolution. This is despite avenues of research in the applied sciences which seem well suited to laboratory natural selection. In this review, we place laboratory natural selection in context with other selection experiments, identify the characteristics which make it well suited for particular kinds of applied research and briefly cover key examples of the usefulness of selection experiments within applied science. Finally, we identify three promising areas of inquiry for laboratory natural selection in the applied sciences: bioremediation technology, identifying mechanisms of drug resistance and optimizing biofuel production. Although laboratory natural selection is currently less utilized in applied science when compared to basic research, the method has immense promise in the field moving forward.
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Affiliation(s)
- Jordan A Lewis
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA
| | - Levi T Morran
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA.,Department of Biology, Emory University, Atlanta, Georgia, USA
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Palacios-Rojas N, McCulley L, Kaeppler M, Titcomb TJ, Gunaratna NS, Lopez-Ridaura S, Tanumihardjo SA. Mining maize diversity and improving its nutritional aspects within agro-food systems. Compr Rev Food Sci Food Saf 2020; 19:1809-1834. [PMID: 33337075 DOI: 10.1111/1541-4337.12552] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 02/05/2020] [Accepted: 02/09/2020] [Indexed: 12/16/2022]
Abstract
Agro-food systems are undergoing rapid innovation in the world and the system's continuum is promoted at different scales with one of the main outcomes to improve nutrition of consumers. Consumer knowledge through educational outreach is important to food and nutrition security and consumer demands guide breeding efforts. Maize is an important part of food systems. It is a staple food and together with rice and wheat, they provide 60% of the world's caloric intake. In addition to being a major contributor to global food and nutrition security, maize forms an important part of the culinary culture in many areas of Africa, the Americas, and Asia. Maize genetics are being exploited to improve human nutrition with the ultimate outcome of improving overall health. By impacting the health of maize consumers, market opportunities will be opened for maize producers with unique genotypes. Although maize is a great source of macronutrients, it is also a source of many micronutrients and phytochemicals purported to confer health benefits. The process of biofortification through traditional plant breeding has increased the protein, provitamin A carotenoid, and zinc contents of maize. The objective of this paper is to review the innovations developed and promoted to improve the nutritional profiles of maize and outcomes of the maize agro-food system.
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Affiliation(s)
| | - Laura McCulley
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin
| | - Mikayla Kaeppler
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin
| | - Tyler J Titcomb
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin
| | | | | | - Sherry A Tanumihardjo
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin
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Xu Y, Liu X, Fu J, Wang H, Wang J, Huang C, Prasanna BM, Olsen MS, Wang G, Zhang A. Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants. PLANT COMMUNICATIONS 2020; 1:100005. [PMID: 33404534 PMCID: PMC7747995 DOI: 10.1016/j.xplc.2019.100005] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Although long-term genetic gain has been achieved through increasing use of modern breeding methods and technologies, the rate of genetic gain needs to be accelerated to meet humanity's demand for agricultural products. In this regard, genomic selection (GS) has been considered most promising for genetic improvement of the complex traits controlled by many genes each with minor effects. Livestock scientists pioneered GS application largely due to livestock's significantly higher individual values and the greater reduction in generation interval that can be achieved in GS. Large-scale application of GS in plants can be achieved by refining field management to improve heritability estimation and prediction accuracy and developing optimum GS models with the consideration of genotype-by-environment interaction and non-additive effects, along with significant cost reduction. Moreover, it would be more effective to integrate GS with other breeding tools and platforms for accelerating the breeding process and thereby further enhancing genetic gain. In addition, establishing an open-source breeding network and developing transdisciplinary approaches would be essential in enhancing breeding efficiency for small- and medium-sized enterprises and agricultural research systems in developing countries. New strategies centered on GS for enhancing genetic gain need to be developed.
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Affiliation(s)
- Yunbi Xu
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- CIMMYT-China Tropical Maize Research Center, Foshan University, Foshan 528231, China
- CIMMYT-China Specialty Maize Research Center, Shanghai Academy of Agricultural Sciences, Shanghai 201400, China
| | - Xiaogang Liu
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Junjie Fu
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Hongwu Wang
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jiankang Wang
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Changling Huang
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Boddupalli M. Prasanna
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Michael S. Olsen
- CIMMYT (International Maize and Wheat Improvement Center), ICRAF Campus, United Nations Avenue, Nairobi, Kenya
| | - Guoying Wang
- Institute of Crop Science/CIMMYT-China, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Aimin Zhang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
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Vanous A, Gardner C, Blanco M, Martin-Schwarze A, Wang J, Li X, Lipka AE, Flint-Garcia S, Bohn M, Edwards J, Lübberstedt T. Stability Analysis of Kernel Quality Traits in Exotic-Derived Doubled Haploid Maize Lines. THE PLANT GENOME 2019; 12. [PMID: 30951103 DOI: 10.3835/plantgenome2017.12.0114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Variation in kernel composition across maize ( L.) germplasm is affected by a combination of the plant's genotype, the environment in which it is grown, and the interaction between these two elements. Adapting exotic germplasm to the US Corn Belt is highly dependent on the plant's genotype, the environment where it is grown, and the interaction between these components. Phenotypic plasticity is ill-defined when specific exotic germplasm is moved over large latitudinal distances and for the adapted variants being created. Reduced plasticity (or stability) is desired for the adapted variants, as it allows for a more rapid implementation into breeding programs throughout the Corn Belt. Here, doubled haploid lines derived from exotic maize and adapted through backcrossing exotic germplasm to elite adapted lines were used in conjunction with genome-wide association studies to explore stability in four kernel composition traits. Genotypes demonstrated a response to environments that paralleled the mean response of all genotypes used across all traits, with protein content and kernel density exhibiting the highest levels of Type II stability. Genes such as , , and were identified as potential candidates within quantitative trait locus regions. The findings within this study aid in validating previously identified genomic regions and identified novel genomic regions affecting kernel quality traits.
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Butts-Wilmsmeyer CJ, Mumm RH, Bohn MO. Concentration of Beneficial Phytochemicals in Harvested Grain of U.S. Yellow Dent Maize (Zea mays L.) Germplasm. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2017; 65:8311-8318. [PMID: 28874047 DOI: 10.1021/acs.jafc.7b02034] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Although previous studies have examined the concentration of various nutritional compounds in maize, little focus has been devoted to the study of commercial maize hybrids or their inbred parents. In this study, a genetically and phenotypically diverse set of maize hybrids and inbreds relevant to U.S. commercial maize germplasm was evaluated for its variability in phytochemical content. Total protein, unsaturated fatty acids, tocopherols, soluble phenolics, and insoluble-bound phenolics were evaluated in this study. Of these compounds, only soluble and insoluble-bound phenolic acids exhibited means and variances that were at least as large as the means and variances reported for other sets of germplasm. This suggests that selection for high phenolic acid content is possible in current U.S. commercial germplasm. In contrast, while the total protein, unsaturated fatty acid, or tocopherol content could possibly be improved using current U.S. commercial germplasm, the results of this study indicate that the incorporation of more diverse sources of germplasm would most likely result in quicker genetic gains.
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Affiliation(s)
- Carrie J Butts-Wilmsmeyer
- Department of Crop Sciences, University of Illinois at Urbana-Champaign , 1102 South Goodwin Avenue, Urbana, Illinois 61801, United States
| | - Rita H Mumm
- Department of Crop Sciences, University of Illinois at Urbana-Champaign , 1102 South Goodwin Avenue, Urbana, Illinois 61801, United States
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign , 1102 South Goodwin Avenue, Urbana, Illinois 61801, United States
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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: 30] [Impact Index Per Article: 4.3] [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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Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations. G3-GENES GENOMES GENETICS 2016; 6:2523-30. [PMID: 27317774 PMCID: PMC4978905 DOI: 10.1534/g3.116.030155] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.
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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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Chen M, Rao RSP, Zhang Y, Zhong C, Thelen JJ. Metabolite variation in hybrid corn grain from a large-scale multisite study. ACTA ACUST UNITED AC 2016. [DOI: 10.1016/j.cj.2016.03.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Liu N, Xue Y, Guo Z, Li W, Tang J. Genome-Wide Association Study Identifies Candidate Genes for Starch Content Regulation in Maize Kernels. FRONTIERS IN PLANT SCIENCE 2016; 7:1046. [PMID: 27512395 PMCID: PMC4961707 DOI: 10.3389/fpls.2016.01046] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Accepted: 07/04/2016] [Indexed: 05/18/2023]
Abstract
Kernel starch content is an important trait in maize (Zea mays L.) as it accounts for 65-75% of the dry kernel weight and positively correlates with seed yield. A number of starch synthesis-related genes have been identified in maize in recent years. However, many loci underlying variation in starch content among maize inbred lines still remain to be identified. The current study is a genome-wide association study that used a set of 263 maize inbred lines. In this panel, the average kernel starch content was 66.99%, ranging from 60.60 to 71.58% over the three study years. These inbred lines were genotyped with the SNP50 BeadChip maize array, which is comprised of 56,110 evenly spaced, random SNPs. Population structure was controlled by a mixed linear model (MLM) as implemented in the software package TASSEL. After the statistical analyses, four SNPs were identified as significantly associated with starch content (P ≤ 0.0001), among which one each are located on chromosomes 1 and 5 and two are on chromosome 2. Furthermore, 77 candidate genes associated with starch synthesis were found within the 100-kb intervals containing these four QTLs, and four highly associated genes were within 20-kb intervals of the associated SNPs. Among the four genes, Glucose-1-phosphate adenylyltransferase (APS1; Gene ID GRMZM2G163437) is known as an important regulator of kernel starch content. The identified SNPs, QTLs, and candidate genes may not only be readily used for germplasm improvement by marker-assisted selection in breeding, but can also elucidate the genetic basis of starch content. Further studies on these identified candidate genes may help determine the molecular mechanisms regulating kernel starch content in maize and other important cereal crops.
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Affiliation(s)
- Na Liu
- College of Biological Engineering, Henan University of TechnologyZhengzhou, China
- State Key Laboratory of Wheat and Maize Crop Science/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural UniversityZhengzhou, China
| | - Yadong Xue
- State Key Laboratory of Wheat and Maize Crop Science/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural UniversityZhengzhou, China
| | - Zhanyong Guo
- State Key Laboratory of Wheat and Maize Crop Science/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural UniversityZhengzhou, China
| | - Weihua Li
- State Key Laboratory of Wheat and Maize Crop Science/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural UniversityZhengzhou, China
| | - Jihua Tang
- State Key Laboratory of Wheat and Maize Crop Science/Collaborative Innovation Center of Henan Grain Crops, Henan Agricultural UniversityZhengzhou, China
- Hubei Collaborative Innovation Center for Grain Industry, Yangtze UniversityJinzhou, China
- *Correspondence: Jihua Tang,
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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: 22] [Impact Index Per Article: 2.4] [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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Saripalli G, Gupta PK. AGPase: its role in crop productivity with emphasis on heat tolerance in cereals. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1893-916. [PMID: 26152573 DOI: 10.1007/s00122-015-2565-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Accepted: 06/16/2015] [Indexed: 05/11/2023]
Abstract
AGPase, a key enzyme of starch biosynthetic pathway, has a significant role in crop productivity. Thermotolerant variants of AGPase in cereals may be used for developing cultivars, which may enhance productivity under heat stress. Improvement of crop productivity has always been the major goal of plant breeders to meet the global demand for food. However, crop productivity itself is influenced in a large measure by a number of abiotic stresses including heat, which causes major losses in crop productivity. In cereals, crop productivity in terms of grain yield mainly depends upon the seed starch content so that starch biosynthesis and the enzymes involved in this process have been a major area of investigation for plant physiologists and plant breeders alike. Considerable work has been done on AGPase and its role in crop productivity, particularly under heat stress, because this enzyme is one of the major enzymes, which catalyses the rate-limiting first committed key enzymatic step of starch biosynthesis. Keeping the above in view, this review focuses on the basic features of AGPase including its structure, regulatory mechanisms involving allosteric regulators, its sub-cellular localization and its genetics. Major emphasis, however, has been laid on the genetics of AGPases and its manipulation for developing high yielding cultivars that will have comparable productivity under heat stress. Some important thermotolerant variants of AGPase, which mainly involve specific amino acid substitutions, have been highlighted, and the prospects of using these thermotolerant variants of AGPase in developing cultivars for heat prone areas have been discussed. The review also includes a brief account on transgenics for AGPase, which have been developed for basic studies and crop improvement.
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Affiliation(s)
- Gautam Saripalli
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch.Charan Singh University, Meerut, 250004, India
| | - Pushpendra Kumar Gupta
- Molecular Biology Laboratory, Department of Genetics and Plant Breeding, Ch.Charan Singh University, Meerut, 250004, India.
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Farfan IDB, De La Fuente GN, Murray SC, Isakeit T, Huang PC, Warburton M, Williams P, Windham GL, Kolomiets M. Genome wide association study for drought, aflatoxin resistance, and important agronomic traits of maize hybrids in the sub-tropics. PLoS One 2015; 10:e0117737. [PMID: 25714370 PMCID: PMC4340625 DOI: 10.1371/journal.pone.0117737] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2013] [Accepted: 12/31/2014] [Indexed: 11/24/2022] Open
Abstract
The primary maize (Zea mays L.) production areas are in temperate regions throughout the world and this is where most maize breeding is focused. Important but lower yielding maize growing regions such as the sub-tropics experience unique challenges, the greatest of which are drought stress and aflatoxin contamination. Here we used a diversity panel consisting of 346 maize inbred lines originating in temperate, sub-tropical and tropical areas testcrossed to stiff-stalk line Tx714 to investigate these traits. Testcross hybrids were evaluated under irrigated and non-irrigated trials for yield, plant height, ear height, days to anthesis, days to silking and other agronomic traits. Irrigated trials were also inoculated with Aspergillus flavus and evaluated for aflatoxin content. Diverse maize testcrosses out-yielded commercial checks in most trials, which indicated the potential for genetic diversity to improve sub-tropical breeding programs. To identify genomic regions associated with yield, aflatoxin resistance and other important agronomic traits, a genome wide association analysis was performed. Using 60,000 SNPs, this study found 10 quantitative trait variants for grain yield, plant and ear height, and flowering time after stringent multiple test corrections, and after fitting different models. Three of these variants explained 5-10% of the variation in grain yield under both water conditions. Multiple identified SNPs co-localized with previously reported QTL, which narrows the possible location of causal polymorphisms. Novel significant SNPs were also identified. This study demonstrated the potential to use genome wide association studies to identify major variants of quantitative and complex traits such as yield under drought that are still segregating between elite inbred lines.
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Affiliation(s)
- Ivan D. Barrero Farfan
- Department of Soil and Crop Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Gerald N. De La Fuente
- Department of Soil and Crop Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Seth C. Murray
- Department of Soil and Crop Sciences, Texas A&M University, College Station, Texas, United States of America
| | - Thomas Isakeit
- Department of Plant Pathology, Texas A&M University, College Station, Texas, United States of America
| | - Pei-Cheng Huang
- Department of Plant Pathology, Texas A&M University, College Station, Texas, United States of America
| | - Marilyn Warburton
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, Mississippi, United States of America
| | - Paul Williams
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, Mississippi, United States of America
| | - Gary L. Windham
- USDA ARS Corn Host Plant Resistance Research Unit, Mississippi State, Mississippi, United States of America
| | - Mike Kolomiets
- Department of Plant Pathology, Texas A&M University, College Station, Texas, United States of America
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Liu Y, Wang L, Sun C, Zhang Z, Zheng Y, Qiu F. Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:1019-37. [PMID: 24553962 DOI: 10.1007/s00122-014-2276-0] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2013] [Accepted: 01/26/2014] [Indexed: 05/11/2023]
Abstract
Twelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement. Kernel size and weight are important target traits in maize (Zea mays L.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F2:3 families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02-1.03, 1.04-1.06, 2.05-2.07, 4.07-4.08 and 9.03-9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.
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Affiliation(s)
- Ying Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
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18
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Zhang Z, Liu Z, Hu Y, Li W, Fu Z, Ding D, Li H, Qiao M, Tang J. QTL analysis of Kernel-related traits in maize using an immortalized F2 population. PLoS One 2014; 9:e89645. [PMID: 24586932 PMCID: PMC3938492 DOI: 10.1371/journal.pone.0089645] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2013] [Accepted: 01/25/2014] [Indexed: 01/08/2023] Open
Abstract
Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04-6.06, 7.02-7.03, and 10.06-10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%).
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Affiliation(s)
- Zhanhui Zhang
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Zonghua Liu
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Yanmin Hu
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Weihua Li
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Zhiyuan Fu
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Dong Ding
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Haochuan Li
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
| | - Mengmeng Qiao
- Department of Biological Sciences, Michigan Technological University, Houghton, Michigan, United States of America
| | - Jihua Tang
- College of Agronomy/Key Laboratory of Physiological Ecology and Genetic Improvement of Food Crops in Henan Province, Henan Agricultural University, Zhengzhou, China
- * E-mail:
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19
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Identification of unconditional and conditional QTL for oil, protein and starch content in maize. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.cj.2013.07.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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20
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Causse M, Santoni S, Damerval C, Maurice A, Charcosset A, Deatrick J, Vienne D. A composite map of expressed sequences in maize. Genome 2012; 39:418-32. [PMID: 18469903 DOI: 10.1139/g96-053] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
A maize genetic map based mainly on expressed sequences has been constructed. The map incorporates data from four segregating populations. Three recombinant inbred line populations were derived from the nonreciprocal crosses between three inbred lines. A map derived from an independent F2 progeny from one of the crosses was also used. With a total of 521 genotyped individuals, accuracy in gene order is expected. Five sources of markers were used: (i) 109 loci corresponding to 69 genes of known function, (ii) 39 loci controlling protein position shifts revealed by two-dimensional electrophoresis, (iii) 8 isozyme loci, (iv) 17 loci corresponding to 14 sequenced cDNAs for which no homology was found in gene banks, and (v) 102 loci corresponding to 81 anonymous probes. As many loci were common to all maps, we tested heterogeneity between recombination fractions. The comparison of recombination fractions revealed: (i) a good correspondence between the maps derived from the same cross, (ii) few significant differences in interval distances, and (iii) global differences, which can reach 20% of the total map length. A composite map of 275 loci covering 1765 cM has been constructed. Key words : Zea mays L., RFLP, genetic map, molecular markers, proteins.
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21
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Toward an understanding of the molecular basis of quantitative disease resistance in rice. J Biotechnol 2012; 159:283-90. [DOI: 10.1016/j.jbiotec.2011.07.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2011] [Revised: 06/08/2011] [Accepted: 07/06/2011] [Indexed: 11/22/2022]
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22
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Cook JP, McMullen MD, Holland JB, Tian F, Bradbury P, Ross-Ibarra J, Buckler ES, Flint-Garcia SA. Genetic architecture of maize kernel composition in the nested association mapping and inbred association panels. PLANT PHYSIOLOGY 2012; 158:824-34. [PMID: 22135431 PMCID: PMC3271770 DOI: 10.1104/pp.111.185033] [Citation(s) in RCA: 126] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2011] [Accepted: 11/28/2011] [Indexed: 05/18/2023]
Abstract
The maize (Zea mays) kernel plays a critical role in feeding humans and livestock around the world and in a wide array of industrial applications. An understanding of the regulation of kernel starch, protein, and oil is needed in order to manipulate composition to meet future needs. We conducted joint-linkage quantitative trait locus mapping and genome-wide association studies (GWAS) for kernel starch, protein, and oil in the maize nested association mapping population, composed of 25 recombinant inbred line families derived from diverse inbred lines. Joint-linkage mapping revealed that the genetic architecture of kernel composition traits is controlled by 21-26 quantitative trait loci. Numerous GWAS associations were detected, including several oil and starch associations in acyl-CoA:diacylglycerol acyltransferase1-2, a gene that regulates oil composition and quantity. Results from nested association mapping were verified in a 282 inbred association panel using both GWAS and candidate gene association approaches. We identified many beneficial alleles that will be useful for improving kernel starch, protein, and oil content.
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Affiliation(s)
| | | | | | | | | | | | | | - Sherry A. Flint-Garcia
- Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211 (J.P.C., M.D.M., S.A.F.-G.); United States Department of Agriculture-Agricultural Research Service, Columbia, Missouri 65211 (M.D.M., S.A.F.-G.); United States Department of Agriculture-Agricultural Research Service, Raleigh, North Carolina 27695 (J.B.H.); United States Department of Agriculture-Agricultural Research Service, Ithaca, New York 14853 (P.B., E.S.B.); Department of Crop Science, North Carolina State University, Raleigh, North Carolina 27695 (J.B.H.); Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853 (F.T., P.B., E.S.B.); Department of Plant Sciences, University of California, Davis, California 95616 (J.R.-I.)
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23
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Peng B, Li Y, Wang Y, Liu C, Liu Z, Tan W, Zhang Y, Wang D, Shi Y, Sun B, Song Y, Wang T, Li Y. QTL analysis for yield components and kernel-related traits in maize across multi-environments. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2011; 122:1305-20. [PMID: 21286680 DOI: 10.1007/s00122-011-1532-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2010] [Accepted: 01/06/2011] [Indexed: 05/18/2023]
Abstract
Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F(2:3) populations derived from crosses Qi319 × Huangzaosi (Q/H, 230 families) and Ye478 × Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2 years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL × environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2 years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.
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Affiliation(s)
- Bo Peng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 100081, China,
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24
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Figueiredo LFDA, Sine B, Chantereau J, Mestres C, Fliedel G, Rami JF, Glaszmann JC, Deu M, Courtois B. Variability of grain quality in sorghum: association with polymorphism in Sh2, Bt2, SssI, Ae1, Wx and O2. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2010; 121:1171-85. [PMID: 20567801 DOI: 10.1007/s00122-010-1380-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2009] [Accepted: 06/03/2010] [Indexed: 05/08/2023]
Abstract
To ensure food security in Africa and Asia, developing sorghum varieties with grain quality that matches consumer demand is a major breeding objective that requires a better understanding of the genetic control of grain quality traits. The objective of this targeted association study was to assess whether the polymorphism detected in six genes involved in synthesis pathways of starch (Sh2, Bt2, SssI, Ae1, and Wx) or grain storage proteins (O2) could explain the phenotypic variability of six grain quality traits [amylose content (AM), protein content (PR), lipid content (LI), hardness (HD), endosperm texture (ET), peak gelatinization temperature (PGT)], two yield component traits [thousand grain weight (TGW) and number of grains per panicle (NBG)], and yield itself (YLD). We used a core collection of 195 accessions which had been previously phenotyped and for which polymorphic sites had been identified in sequenced segments of the six genes. The associations between gene polymorphism and phenotypic traits were analyzed with Tassel. The percentages of admixture of each accession, estimated using 60 RFLP probes, were used as cofactors in the analyses, decreasing the proportion of false-positive tests (70%) due to population structure. The significant associations observed matched generally well the role of the enzymes encoded by the genes known to determine starch amount or type. Sh2, Bt2, Ae1, and Wx were associated with TGW. SssI and Ae1 were associated with PGT, a trait influenced by amylopectin amount. Sh2 was associated with AM while Wx was not, possibly because of the absence of waxy accessions in our collection. O2 and Wx were associated with HD and ET. No association was found between O2 and PR. These results were consistent with QTL or association data in sorghum and in orthologous zones of maize. This study represents the first targeted association mapping study for grain quality in sorghum and paves the way for marker-aided selection.
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25
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Wei F, Stein JC, Liang C, Zhang J, Fulton RS, Baucom RS, De Paoli E, Zhou S, Yang L, Han Y, Pasternak S, Narechania A, Zhang L, Yeh CT, Ying K, Nagel DH, Collura K, Kudrna D, Currie J, Lin J, Kim H, Angelova A, Scara G, Wissotski M, Golser W, Courtney L, Kruchowski S, Graves TA, Rock SM, Adams S, Fulton LA, Fronick C, Courtney W, Kramer M, Spiegel L, Nascimento L, Kalyanaraman A, Chaparro C, Deragon JM, Miguel PS, Jiang N, Wessler SR, Green PJ, Yu Y, Schwartz DC, Meyers BC, Bennetzen JL, Martienssen RA, McCombie WR, Aluru S, Clifton SW, Schnable PS, Ware D, Wilson RK, Wing RA. Detailed analysis of a contiguous 22-Mb region of the maize genome. PLoS Genet 2009; 5:e1000728. [PMID: 19936048 PMCID: PMC2773423 DOI: 10.1371/journal.pgen.1000728] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2009] [Accepted: 10/16/2009] [Indexed: 12/20/2022] Open
Abstract
Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on approximately 1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses.
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Affiliation(s)
- Fusheng Wei
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Joshua C. Stein
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Chengzhi Liang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Jianwei Zhang
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Robert S. Fulton
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Regina S. Baucom
- Department of Genetics, University of Georgia, Athens, Georgia, United States of America
| | - Emanuele De Paoli
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, Delaware, United States of America
| | - Shiguo Zhou
- Laboratory for Molecular and Computational Genomics, Department of Chemistry, Laboratory of Genetics, University of Wisconsin Madison, Madison, Wisconsin, United States of America
| | - Lixing Yang
- Department of Genetics, University of Georgia, Athens, Georgia, United States of America
| | - Yujun Han
- Department of Plant Biology, University of Georgia, Athens, Georgia, United States of America
| | - Shiran Pasternak
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Apurva Narechania
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Lifang Zhang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Cheng-Ting Yeh
- Department of Agronomy and Center for Plant Genomics, Iowa State University, Ames, Iowa, United States of America
| | - Kai Ying
- Department of Agronomy and Center for Plant Genomics, Iowa State University, Ames, Iowa, United States of America
| | - Dawn H. Nagel
- Department of Plant Biology, University of Georgia, Athens, Georgia, United States of America
| | - Kristi Collura
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - David Kudrna
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Jennifer Currie
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Jinke Lin
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - HyeRan Kim
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Angelina Angelova
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Gabriel Scara
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Marina Wissotski
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Wolfgang Golser
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - Laura Courtney
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Scott Kruchowski
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Tina A. Graves
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Susan M. Rock
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Stephanie Adams
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Lucinda A. Fulton
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Catrina Fronick
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - William Courtney
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Melissa Kramer
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Lori Spiegel
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Lydia Nascimento
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Ananth Kalyanaraman
- School of Electrical Engineering and Computer Science, Washington State University, Pullman, Washington, United States of America
| | - Cristian Chaparro
- Université de Perpignan Via Domitia, CNRS UMR 5096, Perpignan, France
| | - Jean-Marc Deragon
- Université de Perpignan Via Domitia, CNRS UMR 5096, Perpignan, France
| | - Phillip San Miguel
- Department of Horticulture and Landscape Architecture, Purdue University, West Lafayette, Indiana, United States of America
| | - Ning Jiang
- Department of Horticulture, Michigan State University, East Lansing, Michigan, United States of America
| | - Susan R. Wessler
- Department of Plant Biology, University of Georgia, Athens, Georgia, United States of America
| | - Pamela J. Green
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, Delaware, United States of America
| | - Yeisoo Yu
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
| | - David C. Schwartz
- Laboratory for Molecular and Computational Genomics, Department of Chemistry, Laboratory of Genetics, University of Wisconsin Madison, Madison, Wisconsin, United States of America
| | - Blake C. Meyers
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, Delaware, United States of America
| | - Jeffrey L. Bennetzen
- Department of Genetics, University of Georgia, Athens, Georgia, United States of America
| | - Robert A. Martienssen
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - W. Richard McCombie
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Srinivas Aluru
- Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, United States of America
| | - Sandra W. Clifton
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Patrick S. Schnable
- Department of Agronomy and Center for Plant Genomics, Iowa State University, Ames, Iowa, United States of America
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Richard K. Wilson
- The Genome Center and Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Rod A. Wing
- Arizona Genomics Institute, School of Plant Sciences and Department of Ecology and Evolutionary Biology, BIO5 Institute for Collaborative Research, University of Arizona, Tucson, Arizona, United States of America
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Wei M, Fu J, Li X, Wang Y, Li Y. Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize. J Appl Genet 2009; 50:225-34. [DOI: 10.1007/bf03195676] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Manicacci D, Camus-Kulandaivelu L, Fourmann M, Arar C, Barrault S, Rousselet A, Feminias N, Consoli L, Francès L, Méchin V, Murigneux A, Prioul JL, Charcosset A, Damerval C. Epistatic interactions between Opaque2 transcriptional activator and its target gene CyPPDK1 control kernel trait variation in maize. PLANT PHYSIOLOGY 2009; 150:506-20. [PMID: 19329568 PMCID: PMC2675748 DOI: 10.1104/pp.108.131888] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2008] [Accepted: 03/23/2009] [Indexed: 05/18/2023]
Abstract
Association genetics is a powerful method to track gene polymorphisms responsible for phenotypic variation, since it takes advantage of existing collections and historical recombination to study the correlation between large genetic diversity and phenotypic variation. We used a collection of 375 maize (Zea mays ssp. mays) inbred lines representative of tropical, American, and European diversity, previously characterized for genome-wide neutral markers and population structure, to investigate the roles of two functionally related candidate genes, Opaque2 and CyPPDK1, on kernel quality traits. Opaque2 encodes a basic leucine zipper transcriptional activator specifically expressed during endosperm development that controls the transcription of many target genes, including CyPPDK1, which encodes a cytosolic pyruvate orthophosphate dikinase. Using statistical models that correct for population structure and individual kinship, Opaque2 polymorphism was found to be strongly associated with variation of the essential amino acid lysine. This effect could be due to the direct role of Opaque2 on either zein transcription, zeins being major storage proteins devoid of lysine, or lysine degradation through the activation of lysine ketoglutarate reductase. Moreover, we found that a polymorphism in the Opaque2 coding sequence and several polymorphisms in the CyPPDK1 promoter nonadditively interact to modify both lysine content and the protein-versus-starch balance, thus revealing the role in quantitative variation in plants of epistatic interactions between a transcriptional activator and one of its target genes.
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Affiliation(s)
- Domenica Manicacci
- University Paris-Sud, UMR 0320/UMR 8120 Génétique Végétale, F-91190 Gif sur Yvette, France.
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28
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QTL identification of grain protein concentration and its genetic correlation with starch concentration and grain weight using two populations in maize (Zea mays L.). J Genet 2009; 88:61-7. [DOI: 10.1007/s12041-009-0008-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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29
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Yanyang L, Yongbin D, Suzhen N, Dangqun C, Yanzhao W, Mengguan W, Xuehui L, Jiafeng F, Zhongwei Z, Huanqing C, Yuling L. QTL identification of kernel composition traits with popcorn using both F2:3 and BC2F2 populations developed from the same cross. J Cereal Sci 2008. [DOI: 10.1016/j.jcs.2008.02.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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30
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Chander S, Meng Y, Zhang Y, Yan J, Li J. Comparison of nutritional traits variability in selected eighty-seven inbreds from Chinese maize (Zea mays L.) germplasm. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2008; 56:6506-6511. [PMID: 18620402 DOI: 10.1021/jf7037967] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Among cereals, only maize has not only a high amount of carotenoids, tocopherols, and oil content but also is rich in starch and protein content compared with other major food crops, such as rice and wheat. The present investigation was made primarily to assess the genetic variability for nutritionally important traits in 87 elite maize inbreds representing major heterotic groups in China. Carotenoid and tocopherol fractions were measured by high-performance liquid chromatography (HPLC), whereas oil, starch, and protein contents were detected by a VECTER22/N near-infrared analyzer. Significant interactions between genotypes and years were observed for all the traits. The pooled mean values of beta-carotene, beta-cryptoxanthin, alpha-carotene, lutein, zeaxanthin, and total carotenoids were 0.449, 0.876, 0.121, 5.803, 3.048, and 10.298 microg g (-1), respectively, whereas the combined mean performance of alpha-tocopherol, gamma-tocopherol, delta-tocopherol, and total tocopherols were 23.98, 32.90, 2.189, and 59.55 microg g (-1), respectively. The average protein, starch, and oil contents were observed to be 12.28, 64.51, and 3.55%, respectively. High level of heritability estimates were observed for all the traits and ranged from 65.6% (protein content) to 92.5% (alpha/gamma-tocopherol ratio). Most of the traits studied in this experiment were either significantly positive correlated or independent. The present finding exhibits substantial opportunities to the breeders for improvement of these traits in maize cultivars and also suggests further exploration of a new source of elite breeding stocks containing a high level of these nutritionally important compounds. Finally, these findings may also help in biofortification of maize.
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Affiliation(s)
- Subhash Chander
- National Maize Improvement Centre of China, China Agricultural University, Yuanmingyuan West Road, Haidian, 100094, Beijing, China
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31
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Smith AM. Prospects for increasing starch and sucrose yields for bioethanol production. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2008; 54:546-58. [PMID: 18476862 DOI: 10.1111/j.1365-313x.2008.03468.x] [Citation(s) in RCA: 84] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
In the short term, the production of bioethanol as a liquid transport fuel is almost entirely dependent on starch and sugars from existing food crops. The sustainability of this industry would be enhanced by increases in the yield of starch/sugar per hectare without further inputs into the crops concerned. Efforts to achieve increased yields of starch over the last three decades, in particular via manipulation of the enzyme ADPglucose pyrophosphorylase, have met with limited success. Other approaches have included manipulation of carbon partitioning within storage organs in favour of starch synthesis, and attempts to manipulate source-sink relationships. Some of the most promising results so far have come from manipulations that increase the availability of ATP for starch synthesis. Future options for achieving increased starch contents could include manipulation of starch degradation in organs in which starch turnover is occurring, and introduction of starch synthesis into the cytosol. Sucrose accumulation is much less well understood than starch synthesis, but recent results from research on sugar cane suggest that total sugar content can be greatly increased by conversion of sucrose into a non-metabolizable isomer. A better understanding of carbohydrate storage and turnover in relation to carbon assimilation and plant growth is required, both for improvement of starch and sugar crops and for attempts to increase biomass production in second-generation biofuel crops.
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Affiliation(s)
- Alison M Smith
- Department of Metabolic Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK.
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32
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Manicacci D, Falque M, Le Guillou S, Piégu B, Henry AM, Le Guilloux M, Damerval C, De Vienne D. Maize Sh2 gene is constrained by natural selection but escaped domestication. J Evol Biol 2007; 20:503-16. [PMID: 17305816 DOI: 10.1111/j.1420-9101.2006.01264.x] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In Zea mays L., we studied the molecular evolution of Shrunken2 (Sh2), a gene that encodes the large subunits of a major enzyme in endosperm starch biosynthesis, ADP-glucose pyrophosphorylase. We compared 4669 bp of the Sh2 coding region on 50 accessions of maize and teosinte. Very few nucleotide polymorphisms were found when compared with other genes in Z. mays, revealing an effect of purifying selection in the whole species that predates domestication. Additionally, the comparison of Sh2 sequences in all Z. mays subspecies and outgroups Z. diploperennis and Tripsacum dactyloides suggests the occurrence of an ancient selective sweep in the Sh2 3' region. The amount and nature of nucleotide diversity are similar in both maize and teosinte, confirming previous results that suggested that Sh2 has not been involved in maize domestication. The very low level of nucleotide diversity as well as the highly conserved protein sequence suggest that natural selection retained effective Sh2 allele(s) long before agriculture started, making human selection inefficient on this gene.
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Affiliation(s)
- D Manicacci
- UMR de Génétique Végétale (8120), Ferme du Moulon, F91 190 Gif sur Yvette, France.
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33
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Upadyayula N, da Silva HS, Bohn MO, Rocheford TR. Genetic and QTL analysis of maize tassel and ear inflorescence architecture. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2006; 112:592-606. [PMID: 16395569 DOI: 10.1007/s00122-005-0133-x] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2005] [Accepted: 10/10/2005] [Indexed: 05/04/2023]
Abstract
Maize (Zea mays L.) ear inflorescence architecture is directly relevant to grain yield components, and tassel architecture is relevant to hybrid seed production. The objectives of this study were to (1) determine heritabilities and correlations of a comprehensive set of tassel and ear inflorescence architecture traits in a set of (Illinois Low ProteinxB73) B73 S1 families, (2) identify chromosomal positions of QTL affecting tassel and ear architecture, and (3) identify possible candidate genes associated with these QTL. For tassel traits, the number of detected QTL ranged from one to five, and explained between 6.5 and 35.9% of phenotypic variation. For ear traits, the number of detected QTL ranged from one to nine and phenotypic variation explained by those QTL varied between 7.9 and 53.0%. We detected QTL for tassel architecture traits that required calculation of ratios from measured traits. Some of these calculated traits QTL were detected in regions that did not show QTL for the measured traits, suggesting that calculation of ratios may reveal developmentally relevant patterns of tassel architecture. We detected a QTL on chromosome 7 for tassel branch number near the gene ramosa1 (ra1), which is known to control tassel branch number, making ra1 a candidate gene for tassel branch number. We detected QTL for several traits on chromosomes 6, 8, and 9, where no inflorescence architecture genes have been mapped, thus providing initial information towards new gene discovery for control of inflorescence architecture.
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Affiliation(s)
- N Upadyayula
- Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA.
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34
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Moose SP, Dudley JW, Rocheford TR. Maize selection passes the century mark: a unique resource for 21st century genomics. TRENDS IN PLANT SCIENCE 2004; 9:358-364. [PMID: 15231281 DOI: 10.1016/j.tplants.2004.05.005] [Citation(s) in RCA: 98] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The Illinois Long-Term Selection Experiment for grain protein and oil concentration in maize (Zea mays) is the longest continuous genetics experiment in higher plants. A total of 103 cycles of selection have produced nine related populations that exhibit phenotypic extremes for grain composition and a host of correlated traits. The use of functional genomics tools in this unique genetic resource provides exciting opportunities not only to discover the genes that contribute to phenotypic differences but also to investigate issues such as the response of plant genomes to artificial selection, the genetic architecture of quantitative traits and the source of continued genetic variation within domesticated crop genomes.
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Affiliation(s)
- Stephen P Moose
- Department of Crop Sciences, University of Illinois, 1102 S. Goodwin Avenue, Urbana, IL 61801, USA.
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35
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Kjaer B, Jensen J. The Inheritance of Nitrogen and Phosphorus Content in Barley Analysed by Genetic Markers. Hereditas 2004. [DOI: 10.1111/j.1601-5223.1995.t01-1-00109.x] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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36
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Paul C, Naidoo G, Forbes A, Mikkilineni V, White D, Rocheford T. Quantitative trait loci for low aflatoxin production in two related maize populations. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2003; 107:263-270. [PMID: 12677406 DOI: 10.1007/s00122-003-1241-0] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2002] [Accepted: 11/14/2002] [Indexed: 05/24/2023]
Abstract
Aflatoxin B(1) formed by Aspergillus flavus Fr:Link has been associated with animal disease and liver cancer in humans. We performed genetic studies in progenies derived from maize inbred Tex6, associated with relatively low levels of aflatoxin production, crossed with the historically important inbred B73. (Tex6 x B73) x B73 BC(1)S(1) and Tex6 x B73 F(2:3) mapping populations were produced and evaluated in 1996 and 1997 in Champaign, Ill. Ears were inoculated 20 to 24 days after midsilk using a pinboard method and a mixture of conidia of A. flavus Link:Fr. isolates. Aflatoxin B(1) levels in harvested ears were determined using an indirect competitive ELISA. Molecular markers were assayed on the populations and used to generate maps. Molecular marker - QTL associations for lower levels of aflatoxin production were determined using multiple regression (MR) and composite interval analysis with multiple regression (CIM MR). MR revealed sets of markers associated with lower aflatoxin production in 1996 and 1997, and CIM MR detected a smaller subset of loci significant in 1997. QTLs for lower aflatoxin were attributed to both Tex6 and B73 parental sources. Environment strongly influenced the detection of QTLs for lower aflatoxin production in different years. There were very few chromosome regions associated with QTLs in more than 1 year or population with MR analysis, and none with CIM MR analysis. In 1997, QTLs for lower aflatoxin were detected with CIM MR in bins 5.01-2 and 5.04-5 in the BC(1)S(1) population, and in bins 3.05-6, 4.07-8 and 10.05-10.07 in the F(2:3) population. These QTL associations appear the most promising for further study.
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Affiliation(s)
- C Paul
- Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
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37
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Trognitz F, Manosalva P, Gysin R, Niñio-Liu D, Simon R, del Herrera MR, Trognitz B, Ghislain M, Nelson R. Plant defense genes associated with quantitative resistance to potato late blight in Solanum phureja x dihaploid S. tuberosum hybrids. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2002; 15:587-97. [PMID: 12059107 DOI: 10.1094/mpmi.2002.15.6.587] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Markers corresponding to 27 plant defense genes were tested for linkage disequilibrium with quantitative resistance to late blight in a diploid potato population that had been used for mapping quantitative trait loci (QTLs) for late blight resistance. Markers were detected by using (i) hybridization probes for plant defense genes, (ii) primer pairs amplifying conserved domains of resistance (R) genes, (iii) primers for defense genes and genes encoding transcriptional regulatory factors, and (iv) primers allowing amplification of sequences flanking plant defense genes by the ligation-mediated polymerase chain reaction. Markers were initially screened by using the most resistant and susceptible individuals of the population, and those markers showing different allele frequencies between the two groups were mapped. Among the 308 segregating bands detected, 24 loci (8%) corresponding to six defense gene families were associated with resistance at chi2 > or = 13, the threshold established using the permutation test at P = 0.05. Loci corresponding to genes related to the phenylpropanoid pathway (phenylalanine ammonium lyase [PAL], chalcone isomerase [CHI], and chalcone synthase [CHS]), loci related to WRKY regulatory genes, and other -defense genes (osmotin and a Phytophthora infestans-induced cytochrome P450) were significantly associated with quantitative disease resistance. A subset of markers was tested on the mapping population of 94 individuals. Ten defense-related markers were clustered at a QTL on chromosome III, and three defense-related markers were located at a broad QTL on chromosome XII. The association of candidate genes with QTLs is a step toward understanding the molecular basis of quantitative resistance to an important plant disease.
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38
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Yamaya T, Obara M, Nakajima H, Sasaki S, Hayakawa T, Sato T. Genetic manipulation and quantitative-trait loci mapping for nitrogen recycling in rice. JOURNAL OF EXPERIMENTAL BOTANY 2002; 53:917-25. [PMID: 11912234 DOI: 10.1093/jexbot/53.370.917] [Citation(s) in RCA: 105] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Immunocytological studies in this laboratory have suggested that NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in developing organs of rice (Oryza sativa L. cv. Sasanishiki) is involved in the utilization of glutamine remobilized from senescing organs through the phloem. Because most of the indica cultivars contained less NADH-GOGAT in their sink organs than japonica cultivars, over-expression of NADH-GOGAT gene from japonica rice was investigated using Kasalath, an indica cultivar. Several T0 transgenic Kasalath lines over-producing NADH-GOGAT under the control of a NADH-GOGAT promoter of Sasanishiki, a japonica rice, showed an increase in grain weight (80% as a maximum), indicating that NADH-GOGAT is indeed a key step for nitrogen utilization and grain filling in rice. A genetic approach using 98 backcross-inbred lines (BC(1)F(6)) developed between Nipponbare (a japonica rice) and Kasalath were employed to detect putative quantitative trait loci (QTLs) associated with the contents of cytosolic glutamine synthetase (GS1; EC 6.3.1.2), which is probably involved in the export of nitrogen from senescing organs and those of NADH-GOGAT. Immunoblotting analyses showed transgressive segregations toward lower or greater contents of these enzyme proteins in these BC(1)F(6). Seven chromosomal QTL regions were detected for GS1 protein content and six for NADH-GOGAT. Some of these QTLs were located in QTL regions for various biochemical and agronomic traits affected by nitrogen recycling. The relationships between the genetic variability of complex agronomic traits and traits for these two enzymes are discussed.
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Affiliation(s)
- Tomoyuki Yamaya
- Graduate School of Agricultural Science, Tohoku University, 1-1 Tsutsumidori-Amamiyamachi, Sendai 981-8555, Japan.
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Hervé D, Fabre F, Berrios EF, Leroux N, Al Chaarani G, Planchon C, Sarrafi A, Gentzbittel L. QTL analysis of photosynthesis and water status traits in sunflower (Helianthus annuus L.) under greenhouse conditions. JOURNAL OF EXPERIMENTAL BOTANY 2001; 52:1857-64. [PMID: 11520874 DOI: 10.1093/jexbot/52.362.1857] [Citation(s) in RCA: 42] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
The identification of QTL for several physiological traits in sunflower is described. Traits related to photosynthesis (leaf chlorophyll concentration, net photosynthesis and internal CO(2) concentration) and water status (stomatal conductance, transpiration, predawn leaf water potential, and relative water content) were evaluated in a population of recombinant inbred lines under greenhouse conditions. Narrow-sense heritabilities were low to average. Using an AFLP linkage map, 19 QTL were detected explaining 8.8-62.9% of the phenotypic variance for each trait. Among these, two major QTL for net photosynthesis were identified on linkage group IX. One QTL co-location was found on linkage group VIII for stomatal movements and water status. Coincident locations for QTL regulating photosynthesis, transpiration and leaf water potential were described on linkage group XIV. These results lead to the first description of the organization of genomic regions related to yield in sunflower.
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Affiliation(s)
- D Hervé
- Laboratoire de Biotechnologie et Amélioration des Plantes, INP/ENSAT, Pôle de Biotechnologie Végétale, Chemin de Borde-Rouge, Auzeville, BP107, F-31326 Castanet-Tolosan cedex, France
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Obara M, Kajiura M, Fukuta Y, Yano M, Hayashi M, Yamaya T, Sato T. Mapping of QTLs associated with cytosolic glutamine synthetase and NADH-glutamate synthase in rice (Oryza sativa L.). JOURNAL OF EXPERIMENTAL BOTANY 2001; 52:1209-1217. [PMID: 11432939 DOI: 10.1093/jexbot/52.359.1209] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Ninety-eight backcross inbred lines (BC1F6) developed between Nipponbare, a japonica rice, and Kasalath, an indica rice were employed to detect putative quantitative trait loci (QTLs) associated with the contents of cytosolic glutamine synthetase (GS1; EC 6.3.1.2) and NADH-glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in leaves. Immunoblotting analyses showed transgressive segregations toward lower or greater contents of these enzyme proteins in these backcross inbred lines. Seven chromosomal QTL regions for GS1 protein content and six for NADH-GOGAT protein content were detected. Some of these QTLs were located in QTL regions for various biochemical and physiological traits affected by nitrogen recycling. These findings suggested that the variation in GS1 and NADH-GOGAT protein contents in this population is related to the changes in the rate of nitrogen recycling from senescing organs to developing organs, leading to changes in these physiological traits. Furthermore, a structural gene for GS1 was mapped between two RFLP markers, C560 and C1408, on chromosome 2 and co-located in the QTL region for one-spikelet weight. A QTL region for NADH-GOGAT protein content was detected at the position mapped for the NADH-GOGAT structural gene on chromosome 1. A QTL region for soluble protein content in developing leaves was also detected in this region. Although fine mapping is required to identify individual genes in the future, QTL analysis could be a useful post-genomic tool to study the gene functions for regulation of nitrogen recycling in rice.
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Affiliation(s)
- M Obara
- Department of Applied Plant Science, Graduate School of Agricultural Sciences, Tohoku University, 1-1 Tsutsumidori-Amamiyamachi, Aoba-ku, Sendai 981-8555, Japan
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Pflieger S, Lefebvre V, Caranta C, Blattes A, Goffinet B, Palloix A. Disease resistance gene analogs as candidates for QTLs involved in pepper-pathogen interactions. Genome 1999. [DOI: 10.1139/g99-067] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Whereas resistance genes (R-genes) governing qualitative resistance have been isolated and characterized, the biological roles of genes governing quantitative resistance (quantitave trait loci, QTLs) are still unknown. We hypothesized that genes at QTLs could share homologies with cloned R-genes. We used a PCR-based approach to isolate R-gene analogs (RGAs) with consensus primers corresponding with conserved domains of cloned R-genes: (i) the nucleotide binding site (NBS) and hydrophobic domain, and (ii) the kinase domain. PCR-amplified fragments were sequenced and mapped on a pepper intraspecific map. NBS-containing sequences of pepper, most similar to the N gene of tobacco, were classified into seven families and all mapped in a unique region covering 64 cM on the Noir chromosome. Kinase domain containing sequences and cloned R-gene homologs (Pto, Fen, Cf-2) were mapped on four different linkage groups. A QTL involved in partial resistance to cucumber mosaic virus (CMV) with an additive effect was closely linked or allelic to one NBS-type family. QTLs with epistatic effects were also detected at several RGA loci. The colocalizations between NBS-containing sequences and resistance QTLs suggest that the mechanisms of qualitative and quantitative resistance may be similar in some cases.Key words: Capsicum annuum, candidate gene, nucleotide binding site, kinase domain, quantitative trait loci.
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Melchinger AE, Utz HF, Schön CC. Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics 1998; 149:383-403. [PMID: 9584111 PMCID: PMC1460144 DOI: 10.1093/genetics/149.1.383] [Citation(s) in RCA: 233] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The efficiency of marker-assisted selection (MAS) depends on the power of quantitative trait locus (QTL) detection and unbiased estimation of QTL effects. Two independent samples N = 344 and 107 of F2 plants were genotyped for 89 RFLP markers. For each sample, testcross (TC) progenies of the corresponding F3 lines with two testers were evaluated in four environments. QTL for grain yield and other agronomically important traits were mapped in both samples. QTL effects were estimated from the same data as used for detection and mapping of QTL (calibration) and, based on QTL positions from calibration, from the second, independent sample (validation). For all traits and both testers we detected a total of 107 QTL with N = 344, and 39 QTL with N = 107, of which only 20 were in common. Consistency of QTL effects across testers was in agreement with corresponding genotypic correlations between the two TC series. Most QTL displayed no significant QTL x environment nor epistatic interactions. Estimates of the proportion of the phenotypic and genetic variance explained by QTL were considerably reduced when derived from the independent validation sample as opposed to estimates from the calibration sample. We conclude that, unless QTL effects are estimated from an independent sample, they can be inflated, resulting in an overly optimistic assessment of the efficiency of MAS.
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Affiliation(s)
- A E Melchinger
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70593 Stuttgart, Germany.
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Dijkhuizen A, Dudley JW, Rocheford TR, Haken AE, Eckhoff SR. Near-Infrared Reflectance Correlated to 100-g Wet-Milling Analysis in Maize. Cereal Chem 1998. [DOI: 10.1094/cchem.1998.75.2.266] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- A. Dijkhuizen
- Department of Crop Sciences, University of Illinois, Urbana 61801
| | - J. W. Dudley
- Department of Crop Sciences, University of Illinois, Urbana 61801
- Corresponding author. Phone: 217/333-9640. E-mail:
| | - T. R. Rocheford
- Department of Crop Sciences, University of Illinois, Urbana 61801
| | - A. E. Haken
- Department of Agricultural Engineering, University of Illinois, Urbana IL 61801
| | - S. R. Eckhoff
- Department of Agricultural Engineering, University of Illinois, Urbana IL 61801
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Azanza F, Tadmor Y, Klein BP, Rocheford TR, Juvik JA. Quantitative trait loci influencing chemical and sensory characteristics of eating quality in sweet corn. Genome 1996; 39:40-50. [DOI: 10.1139/g96-006] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
This study was conducted to ascertain the chromosomal location and magnitude of effect of quantitative trait loci (QTL) associated with the chemical and sensory properties of sweet corn (Zea mays L.) eating quality. Eighty-eight RFLPs, 3 cloned genes (sh1, sh2, and dhn1), and 2 morphological markers (a2 and se1) distributed throughout the sweet corn genome were scored in 214 F2:3families derived from a cross between the inbreds W6786su1Se1 and IL731Asu1se1. Kernel properties associated with eating quality (kernel tenderness and starch, phytoglycogen, sucrose, and dimethyl sulfide concentrations) were quantified on F2:3sib-pollinated ears harvested at 20 days after pollination. Sensory evaluation was conducted on a subset of 103 F2:3families to determine intensity of attributes associated with sweet corn eating quality (corn aroma, grassy aroma, sweetness, starchiness, grassy flavor, crispness, tenderness, and juiciness) and overall liking. Single factor analysis of variance revealed significant QTL for all these traits, which accounted for from 3 to 42% of the total phenotypic variation. A proportion of the RFLP markers associated with human sensory response were also found to be associated with kernel characteristics. To our knowledge this is the first report of the identification of QTL associated with human flavor preferences in any food crop. Key words : sweet corn, RFLP, quantitative trait loci, eating quality, sensory evaluation.
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Abstract
Maize has been used effectively as a model organism in the development and evaluation of molecular markers for the identification, mapping and manipulation of major genes affecting the expression of quantitative traits in plants. Although quantitative geneticists have recognized the possibility of major loci, the general dogma had emerged that quantitative traits were controlled by many loci, each with a small effect. This interpretation sent a quantitative traits because it would be essentially impossible to isolate a gene responsible for the trait. Recent results from numerous mapping studies have shown that quantitative traits are controlled by, at least some, factors with major effects, and have given credibility to the conclusion that major loci exist and that one might be able to study them. Positive results from marker-facilitated selection and introgression studies have further strengthened this conclusion.
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Affiliation(s)
- C W Stuber
- US Department of Agriculture, Agricultural Research Service, Department of Genetics, State University, Raleigh, NC 27695-7614, USA
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Goldman IL, Paran I, Zamir D. Quantitative trait locus analysis of a recombinant inbred line population derived from a Lycopersicon esculentum x Lycopersicon cheesmanii cross. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 1995; 90:925-932. [PMID: 24173046 DOI: 10.1007/bf00222905] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/1994] [Accepted: 09/22/1994] [Indexed: 06/02/2023]
Abstract
Quantitative trait loci influencing fruit traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato, Lycopersicon esculentum with a related wild species Lycopersicon cheesmanii. One hundred thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 F8 RIL families. Fruit weight and soluble solids were measured in replicated trials during 1991 and 1992. Seed weight was measured in 1992. Significant (P<0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. A total of 73 significant marker locus-trait associations were detected for the three traits measured. Fifty-three of these associations were for fruit weight and soluble solids, many of which involved marker loci signficantly associated with both traits. QTL with large effects on all three traits were detected on chromosome 6. Greater homozygosity at many loci in the RIL population as compared to F2 populations and greater genomic coverage resulted in increased precision in the estimation of QTL effects, and large proportions of the total phenotypic variance were explained by marker class variation at significant marker loci for many traits. The RIL population was effective in detecting and discriminating among QTL for these traits previously identified in other investigations despite skewed segregation ratios at many marker loci. Large additive effects were measured at significant marker loci. Lower fruit weight, higher soluble solids, and lower seed weight were generally associated with RFLP alleles from theL. cheesmanii parent.
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Affiliation(s)
- I L Goldman
- Department of Horticulture, University of Wisconsin-Madison, 1575 Linden Drive, 53706, Madison, WI, USA
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