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Sun S, Bakkeren G. A bird's-eye view: exploration of the flavin-containing monooxygenase superfamily in common wheat. FRONTIERS IN PLANT SCIENCE 2024; 15:1369299. [PMID: 38681221 PMCID: PMC11046709 DOI: 10.3389/fpls.2024.1369299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 02/19/2024] [Indexed: 05/01/2024]
Abstract
The Flavin Monooxygenase (FMO) gene superfamily in plants is involved in various processes most widely documented for its involvement in auxin biosynthesis, specialized metabolite biosynthesis, and plant microbial defense signaling. The roles of FMOs in defense signaling and disease resistance have recently come into focus as they may present opportunities to increase immune responses in plants including leading to systemic acquired resistance, but are not well characterized. We present a comprehensive catalogue of FMOs found in genomes across vascular plants and explore, in depth, 170 wheat TaFMO genes for sequence architecture, cis-acting regulatory elements, and changes due to Transposable Element insertions. A molecular phylogeny separates TaFMOs into three clades (A, B, and C) for which we further report gene duplication patterns, and differential rates of homoeologue expansion and retention among TaFMO subclades. We discuss Clade B TaFMOs where gene expansion is similarly seen in other cereal genomes. Transcriptome data from various studies point towards involvement of subclade B2 TaFMOs in disease responses against both biotrophic and necrotrophic pathogens, substantiated by promoter element analysis. We hypothesize that certain TaFMOs are responsive to both abiotic and biotic stresses, providing potential targets for enhancing disease resistance, plant yield and other important agronomic traits. Altogether, FMOs in wheat and other crop plants present an untapped resource to be exploited for improving the quality of crops.
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Affiliation(s)
- Sherry Sun
- Department of Botany, The University of British Columbia, Vancouver, BC, Canada
| | - Guus Bakkeren
- Agriculture and Agri-Food Canada, Summerland Research & Development Center, Summerland, BC, Canada
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2
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Advances in Metabolomics-Driven Diagnostic Breeding and Crop Improvement. Metabolites 2022; 12:metabo12060511. [PMID: 35736444 PMCID: PMC9228725 DOI: 10.3390/metabo12060511] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 02/04/2023] Open
Abstract
Climate change continues to threaten global crop output by reducing annual productivity. As a result, global food security is now considered as one of the most important challenges facing humanity. To address this challenge, modern crop breeding approaches are required to create plants that can cope with increased abiotic/biotic stress. Metabolomics is rapidly gaining traction in plant breeding by predicting the metabolic marker for plant performance under a stressful environment and has emerged as a powerful tool for guiding crop improvement. The advent of more sensitive, automated, and high-throughput analytical tools combined with advanced bioinformatics and other omics techniques has laid the foundation to broadly characterize the genetic traits for crop improvement. Progress in metabolomics allows scientists to rapidly map specific metabolites to the genes that encode their metabolic pathways and offer plant scientists an excellent opportunity to fully explore and rationally harness the wealth of metabolites that plants biosynthesize. Here, we outline the current application of advanced metabolomics tools integrated with other OMICS techniques that can be used to: dissect the details of plant genotype–metabolite–phenotype interactions facilitating metabolomics-assisted plant breeding for probing the stress-responsive metabolic markers, explore the hidden metabolic networks associated with abiotic/biotic stress resistance, facilitate screening and selection of climate-smart crops at the metabolite level, and enable accurate risk-assessment and characterization of gene edited/transgenic plants to assist the regulatory process. The basic concept behind metabolic editing is to identify specific genes that govern the crucial metabolic pathways followed by the editing of one or more genes associated with those pathways. Thus, metabolomics provides a superb platform for not only rapid assessment and commercialization of future genome-edited crops, but also for accelerated metabolomics-assisted plant breeding. Furthermore, metabolomics can be a useful tool to expedite the crop research if integrated with speed breeding in future.
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3
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Rajabihashjin M, Zeinalabedini M, Asghari A, Ghaffari MR, Salekdeh GH. Impact of environmental variables on yield related traits and bioactive compounds of the Persian fenugreek (Trigonella foenum-graecum L.) populations. Sci Rep 2022; 12:7359. [PMID: 35513472 PMCID: PMC9072307 DOI: 10.1038/s41598-022-10940-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 04/14/2022] [Indexed: 11/09/2022] Open
Abstract
Trigonella foenum-graecum is widely distributed worldwide and grown under a wide range of climatic conditions. The current research was conducted to study the effects of the environmental variables on yield related traits and metabolite contents of 50 different Persian fenugreeks at various geographical locations. Accordingly, multivariate statistical techniques including canonical correspondence analysis (CCA), hierarchical clustering on principal components, and partial least squares regression (PLSR) were applied to determine important proxy variables and establish a relevant model to predict bioactive compounds in fenugreeks. The interrelation of clustered groups emphasized the importance of functional groups of bioactive compounds and several yield related traits. The CCA indicated that two climatic variables of temperature and solar irradiation contributed prominently to 4-hydroxyisoleucine accumulation. The predicted model based on PLSR revealed climatic variables such as temperature, solar, and rain. The precursor of isoleucine was the predictive power for 4-hydroxyisoleucine accumulation while seed weight predicted trigonelline content. The current study's findings may provide helpful information for the breeding strategies of this multipurpose crop.
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Affiliation(s)
- Masoumeh Rajabihashjin
- Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran
- Systems and Synthetic Biology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Mehrshad Zeinalabedini
- Systems and Synthetic Biology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
| | - Ali Asghari
- Department of Agronomy and Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
| | - Mohammad Reza Ghaffari
- Systems and Synthetic Biology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
| | - Ghasem Hosseini Salekdeh
- Systems and Synthetic Biology Department, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
- Department of Molecular Sciences, Macquarie University, North Ryde, NSW, Australia
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4
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Medina-Lozano I, Díaz A. Applications of Genomic Tools in Plant Breeding: Crop Biofortification. Int J Mol Sci 2022; 23:3086. [PMID: 35328507 PMCID: PMC8950180 DOI: 10.3390/ijms23063086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 12/02/2022] Open
Abstract
Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.
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Affiliation(s)
- Inés Medina-Lozano
- Departamento de Ciencia Vegetal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Universidad de Zaragoza, Avda. Montañana 930, 50059 Zaragoza, Spain;
- Instituto Agroalimentario de Aragón—IA2, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Universidad de Zaragoza, 50013 Zaragoza, Spain
| | - Aurora Díaz
- Departamento de Ciencia Vegetal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Universidad de Zaragoza, Avda. Montañana 930, 50059 Zaragoza, Spain;
- Instituto Agroalimentario de Aragón—IA2, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Universidad de Zaragoza, 50013 Zaragoza, Spain
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5
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Păucean A, Mureșan V, Maria-Man S, Chiș MS, Mureșan AE, Șerban LR, Pop A, Muste S. Metabolomics as a Tool to Elucidate the Sensory, Nutritional and Safety Quality of Wheat Bread-A Review. Int J Mol Sci 2021; 22:ijms22168945. [PMID: 34445648 PMCID: PMC8396194 DOI: 10.3390/ijms22168945] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 01/20/2023] Open
Abstract
Wheat (Triticum aestivum) is one of the most extensively cultivated and used staple crops in human nutrition, while wheat bread is annually consumed in more than nine billion kilograms over the world. Consumers’ purchase decisions on wheat bread are largely influenced by its nutritional and sensorial characteristics. In the last decades, metabolomics is considered an effective tool for elucidating the information on metabolites; however, the deep investigations on metabolites still remain a difficult and longtime action. This review gives emphasis on the achievements in wheat bread metabolomics by highlighting targeted and untargeted analyses used in this field. The metabolomics approaches are discussed in terms of quality, processing and safety of wheat and bread, while the molecular mechanisms involved in the sensorial and nutritional characteristics of wheat bread are pointed out. These aspects are of crucial importance in the context of new consumers’ demands on healthy bakery products rich in bioactive compounds but, equally, with good sensorial acceptance. Moreover, metabolomics is a potential tool for assessing the changes in nutrient composition from breeding to processing, while monitoring and understanding the transformations of metabolites with bioactive properties, as well as the formation of compounds like toxins during wheat storage.
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Chen J, Xue M, Liu H, Fernie AR, Chen W. Exploring the genic resources underlying metabolites through mGWAS and mQTL in wheat: From large-scale gene identification and pathway elucidation to crop improvement. PLANT COMMUNICATIONS 2021; 2:100216. [PMID: 34327326 PMCID: PMC8299079 DOI: 10.1016/j.xplc.2021.100216] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 06/04/2021] [Accepted: 06/28/2021] [Indexed: 05/23/2023]
Abstract
Common wheat (Triticum aestivum L.) is a leading cereal crop, but has lagged behind with respect to the interpretation of the molecular mechanisms of phenotypes compared with other major cereal crops such as rice and maize. The recently available genome sequence of wheat affords the pre-requisite information for efficiently exploiting the potential molecular resources for decoding the genetic architecture of complex traits and identifying valuable breeding targets. Meanwhile, the successful application of metabolomics as an emergent large-scale profiling methodology in several species has demonstrated this approach to be accessible for reaching the above goals. One such productive avenue is combining metabolomics approaches with genetic designs. However, this trial is not as widespread as that for sequencing technologies, especially when the acquisition, understanding, and application of metabolic approaches in wheat populations remain more difficult and even arguably underutilized. In this review, we briefly introduce the techniques used in the acquisition of metabolomics data and their utility in large-scale identification of functional candidate genes. Considerable progress has been made in delivering improved varieties, suggesting that the inclusion of information concerning these metabolites and genes and metabolic pathways enables a more explicit understanding of phenotypic traits and, as such, this procedure could serve as an -omics-informed roadmap for executing similar improvement strategies in wheat and other species.
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Affiliation(s)
- Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Mingyun Xue
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hongbo Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Alisdair R. Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm 14476, Germany
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
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Kumar R, Sharma V, Suresh S, Ramrao DP, Veershetty A, Kumar S, Priscilla K, Hangargi B, Narasanna R, Pandey MK, Naik GR, Thomas S, Kumar A. Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples. Front Genet 2021; 12:637141. [PMID: 33889179 PMCID: PMC8055929 DOI: 10.3389/fgene.2021.637141] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 03/02/2021] [Indexed: 01/07/2023] Open
Abstract
In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.
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Affiliation(s)
- Rakesh Kumar
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | - Vinay Sharma
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
| | - Srinivas Suresh
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | | | - Akash Veershetty
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | - Sharan Kumar
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | - Kagolla Priscilla
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | | | - Rahul Narasanna
- Department of Life Science, Central University of Karnataka, Kalaburagi, India
| | - Manish Kumar Pandey
- International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
| | | | - Sherinmol Thomas
- Department of Biosciences & Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Anirudh Kumar
- Department of Botany, Indira Gandhi National Tribal University, Amarkantak, India
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8
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Gemmer MR, Richter C, Schmutzer T, Raorane ML, Junker B, Pillen K, Maurer A. Genome-wide association study on metabolite accumulation in a wild barley NAM population reveals natural variation in sugar metabolism. PLoS One 2021; 16:e0246510. [PMID: 33592061 PMCID: PMC7886226 DOI: 10.1371/journal.pone.0246510] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 01/20/2021] [Indexed: 12/03/2022] Open
Abstract
Metabolites play a key role in plants as they are routing plant developmental processes and are involved in biotic and abiotic stress responses. Their analysis can offer important information on the underlying processes. Regarding plant breeding, metabolite concentrations can be used as biomarkers instead of or in addition to genetic markers to predict important phenotypic traits (metabolic prediction). In this study, we applied a genome-wide association study (GWAS) in a wild barley nested association mapping (NAM) population to identify metabolic quantitative trait loci (mQTL). A set of approximately 130 metabolites, measured at early and late sampling dates, was analysed. For four metabolites from the early and six metabolites from the late sampling date significant mQTL (grouped as 19 mQTL for the early and 25 mQTL for the late sampling date) were found. Interestingly, all of those metabolites could be classified as sugars. Sugars are known to be involved in signalling, plant growth and plant development. Sugar-related genes, encoding mainly sugar transporters, have been identified as candidate genes for most of the mQTL. Moreover, several of them co-localized with known flowering time genes like Ppd-H1, HvELF3, Vrn-H1, Vrn-H2 and Vrn-H3, hinting on the known role of sugars in flowering. Furthermore, numerous disease resistance-related genes were detected, pointing to the signalling function of sugars in plant resistance. An mQTL on chromosome 1H in the region of 13 Mbp to 20 Mbp stood out, that alone explained up to 65% of the phenotypic variation of a single metabolite. Analysis of family-specific effects within the diverse NAM population showed the available natural genetic variation regarding sugar metabolites due to different wild alleles. The study represents a step towards a better understanding of the genetic components of metabolite accumulation, especially sugars, thereby linking them to biological functions in barley.
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Affiliation(s)
- Mathias Ruben Gemmer
- Institute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Chris Richter
- Institute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Thomas Schmutzer
- Institute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Manish L. Raorane
- Institute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Björn Junker
- Institute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Klaus Pillen
- Institute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Andreas Maurer
- Institute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany
- * E-mail:
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9
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Metabolomics Intervention Towards Better Understanding of Plant Traits. Cells 2021; 10:cells10020346. [PMID: 33562333 PMCID: PMC7915772 DOI: 10.3390/cells10020346] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 02/06/2023] Open
Abstract
The majority of the most economically important plant and crop species are enriched with the availability of high-quality reference genome sequences forming the basis of gene discovery which control the important biochemical pathways. The transcriptomics and proteomics resources have also been made available for many of these plant species that intensify the understanding at expression levels. However, still we lack integrated studies spanning genomics–transcriptomics–proteomics, connected to metabolomics, the most complicated phase in phenotype expression. Nevertheless, for the past few decades, emphasis has been more on metabolome which plays a crucial role in defining the phenotype (trait) during crop improvement. The emergence of modern high throughput metabolome analyzing platforms have accelerated the discovery of a wide variety of biochemical types of metabolites and new pathways, also helped in improving the understanding of known existing pathways. Pinpointing the causal gene(s) and elucidation of metabolic pathways are very important for development of improved lines with high precision in crop breeding. Along with other-omics sciences, metabolomics studies have helped in characterization and annotation of a new gene(s) function. Hereby, we summarize several areas in the field of crop development where metabolomics studies have made its remarkable impact. We also assess the recent research on metabolomics, together with other omics, contributing toward genetic engineering to target traits and key pathway(s).
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10
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Guo X, Sarup P, Jensen JD, Orabi J, Kristensen NH, Mulder FAA, Jahoor A, Jensen J. Genetic Variance of Metabolomic Features and Their Relationship With Malting Quality Traits in Spring Barley. FRONTIERS IN PLANT SCIENCE 2020; 11:575467. [PMID: 33193515 PMCID: PMC7604292 DOI: 10.3389/fpls.2020.575467] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 09/24/2020] [Indexed: 06/11/2023]
Abstract
Barley is the most common source for malt to be used in brewing beer and other alcoholic beverages. This involves converting the starch of barley into fermentable sugars a process that involves malting, that is germinating of the grains, and mashing, which is an enzymatic process. Numerous metabolic processes are involved in germination, where distinct and time-dependent alterations at the metabolite levels happen. In this study, 2,628 plots of 565 spring malting barley lines from Nordic Seed A/S were investigated. Phenotypic records were available for six malting quality (MQ) traits: filtering speed (FS), wort clearness (WCL), extract yield (EY), wort color (WCO), beta glucan (BG), and wort viscosity (WV). Each line had a set of dense genomic markers. In addition, 24,018 metabolomic features (MFs) were obtained for each sample from nuclear magnetic resonance (NMR) spectra for wort samples produced from each experimental plot. The genetic variation in the MFs was investigated using a univariate model, and the relationship between MFs and the MQ traits was studied using a bivariate model. Results showed that a total of 8,604 MFs had heritability estimates significantly larger than 0 and for all MQ traits, there were genetic correlations with up to 86.77% and phenotypic correlations with up to 90.07% of the significant heritable MFs. In conclusion, around one third of all MFs were significantly heritable, among which a considerable proportion had significant additive genetic and/or phenotypic correlations with the MQ traits (WCO, WV, and BG) in spring barley. The results from this study indicate that many of the MFs are heritable and MFs have great potential to be used in breeding barley for high MQ.
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Affiliation(s)
- Xiangyu Guo
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | | | | | | | | | - Frans A. A. Mulder
- Department of Chemistry and Interdisciplinary Nanoscience Center (iNANO), Aarhus University, Aarhus, Denmark
| | - Ahmed Jahoor
- Nordic Seed A/S, Odder, Denmark
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Just Jensen
- Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
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11
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Chen J, Hu X, Shi T, Yin H, Sun D, Hao Y, Xia X, Luo J, Fernie AR, He Z, Chen W. Metabolite-based genome-wide association study enables dissection of the flavonoid decoration pathway of wheat kernels. PLANT BIOTECHNOLOGY JOURNAL 2020; 18:1722-1735. [PMID: 31930656 PMCID: PMC7336285 DOI: 10.1111/pbi.13335] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 12/29/2019] [Indexed: 05/02/2023]
Abstract
The marriage of metabolomic approaches with genetic design has proven a powerful tool in dissecting diversity in the metabolome and has additionally enhanced our understanding of complex traits. That said, such studies have rarely been carried out in wheat. In this study, we detected 805 metabolites from wheat kernels and profiled their relative contents among 182 wheat accessions, conducting a metabolite-based genome-wide association study (mGWAS) utilizing 14 646 previously described polymorphic SNP markers. A total of 1098 mGWAS associations were detected with large effects, within which 26 candidate genes were tentatively designated for 42 loci. Enzymatic assay of two candidates indicated they could catalyse glucosylation and subsequent malonylation of various flavonoids and thereby the major flavonoid decoration pathway of wheat kernel was dissected. Moreover, numerous high-confidence genes associated with metabolite contents have been provided, as well as more subdivided metabolite networks which are yet to be explored within our data. These combined efforts presented the first step towards realizing metabolomics-associated breeding of wheat.
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Affiliation(s)
- Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Taotao Shi
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Huanran Yin
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Dongfa Sun
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
| | - Yuanfeng Hao
- National Wheat Improvement CenterInstitute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Xianchun Xia
- National Wheat Improvement CenterInstitute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Jie Luo
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
| | | | - Zhonghu He
- National Wheat Improvement CenterInstitute of Crop SciencesChinese Academy of Agricultural SciencesBeijingChina
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhanChina
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12
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Shi T, Zhu A, Jia J, Hu X, Chen J, Liu W, Ren X, Sun D, Fernie AR, Cui F, Chen W. Metabolomics analysis and metabolite-agronomic trait associations using kernels of wheat (Triticum aestivum) recombinant inbred lines. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2020; 103:279-292. [PMID: 32073701 PMCID: PMC7383920 DOI: 10.1111/tpj.14727] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/17/2020] [Accepted: 02/07/2020] [Indexed: 05/21/2023]
Abstract
Plants produce numerous metabolites that are important for their development and growth. However, the genetic architecture of the wheat metabolome has not been well studied. Here, utilizing a high-density genetic map, we conducted a comprehensive metabolome study via widely targeted LC-MS/MS to analyze the wheat kernel metabolism. We further combined agronomic traits and dissected the genetic relationship between metabolites and agronomic traits. In total, 1260 metabolic features were detected. Using linkage analysis, 1005 metabolic quantitative trait loci (mQTLs) were found distributed unevenly across the genome. Twenty-four candidate genes were found to modulate the levels of different metabolites, of which two were functionally annotated by in vitro analysis to be involved in the synthesis and modification of flavonoids. Combining the correlation analysis of metabolite-agronomic traits with the co-localization of methylation quantitative trait locus (mQTL) and phenotypic QTL (pQTL), genetic relationships between the metabolites and agronomic traits were uncovered. For example, a candidate was identified using correlation and co-localization analysis that may manage auxin accumulation, thereby affecting number of grains per spike (NGPS). Furthermore, metabolomics data were used to predict the performance of wheat agronomic traits, with metabolites being found that provide strong predictive power for NGPS and plant height. This study used metabolomics and association analysis to better understand the genetic basis of the wheat metabolism which will ultimately assist in wheat breeding.
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Affiliation(s)
- Taotao Shi
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Anting Zhu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Jingqi Jia
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Jie Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Wei Liu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Xifeng Ren
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Dongfa Sun
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
| | - Alisdair R. Fernie
- Max‐Planck‐Institute of Molecular Plant PhysiologyPotsdam‐Golm14476Germany
| | - Fa Cui
- Wheat Molecular Breeding Innovation Research GroupKey Laboratory of Molecular Module‐Based Breeding of High Yield and Abiotic Resistant Plants in Universities of ShandongSchool of AgricultureLudong UniversityYantaiChina
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhan430070China
- College of Plant Science and TechnologyHuazhong Agricultural UniversityWuhan430070China
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13
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Metabolomics: A Tool for Cultivar Phenotyping and Investigation of Grain Crops. AGRONOMY-BASEL 2020. [DOI: 10.3390/agronomy10060831] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The quality of plants is often enhanced for diverse purposes such as improved resistance to environmental pressures, better taste, and higher yields. Considering the world’s dependence on plants (nutrition, medicine, or biofuel), developing new cultivars with superior characteristics is of great importance. As part of the ‘omics’ approaches, metabolomics has been employed to investigate the large number of metabolites present in plant systems under well-defined environmental conditions. Recent advances in the metabolomics field have greatly expanded our understanding of plant metabolism, largely driven by potential application to agricultural systems. The current review presents the workflow for plant metabolome analyses, current knowledge, and future directions of such research as determinants of cultivar phenotypes. Furthermore, the value of metabolome analyses in contemporary crop science is illustrated. Here, metabolomics has provided valuable information in research on grain crops and identified significant biomarkers under different conditions and/or stressors. Moreover, the value of metabolomics has been redefined from simple biomarker identification to a tool for discovering active drivers involved in biological processes. We illustrate and conclude that the rapid advances in metabolomics are driving an explosion of information that will advance modern breeding approaches for grain crops and address problems associated with crop productivity and sustainable agriculture.
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Razzaq A, Sadia B, Raza A, Khalid Hameed M, Saleem F. Metabolomics: A Way Forward for Crop Improvement. Metabolites 2019; 9:E303. [PMID: 31847393 PMCID: PMC6969922 DOI: 10.3390/metabo9120303] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 12/02/2019] [Accepted: 12/11/2019] [Indexed: 12/15/2022] Open
Abstract
Metabolomics is an emerging branch of "omics" and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment-gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.
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Affiliation(s)
- Ali Razzaq
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38040, Pakistan; (A.R.); (B.S.)
| | - Bushra Sadia
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38040, Pakistan; (A.R.); (B.S.)
| | - Ali Raza
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Wuhan 430062, China;
| | - Muhammad Khalid Hameed
- School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China;
| | - Fozia Saleem
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad 38040, Pakistan; (A.R.); (B.S.)
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15
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Aliakbari A, Ehsani A, Vaez Torshizi R, Løvendahl P, Esfandyari H, Jensen J, Sarup P. Genetic variance of metabolomic features and their relationship with body weight and body weight gain in Holstein cattle1. J Anim Sci 2019; 97:3832-3844. [PMID: 31278866 PMCID: PMC6735847 DOI: 10.1093/jas/skz228] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 07/04/2019] [Indexed: 11/14/2022] Open
Abstract
In recent years, metabolomics has been used to clarify the biology underlying biological samples. In the field of animal breeding, investigating the magnitude of genetic control on the metabolomic profiles of animals and their relationships with quantitative traits adds valuable information to animal improvement schemes. In this study, we analyzed metabolomic features (MFs) extracted from the metabolomic profiles of 843 male Holstein calves. The metabolomic profiles were obtained using nuclear magnetic resonance (NMR) spectroscopy. We investigated 2 alternative methods to control for peak shifts in the NMR spectra, binning and aligning, to determine which approach was the most efficient for assessing genetic variance. Series of univariate analyses were implemented to elucidate the heritability of each MF. Furthermore, records on BW and ADG from 154 to 294 d of age (ADG154-294), 294 to 336 d of age (ADG294-336), and 154 to 336 d of age (ADG154-336) were used in a series of bivariate analyses to establish the genetic and phenotypic correlations with MFs. Bivariate analyses were only performed for MFs that had a heritability significantly different from zero. The heritabilities obtained in the univariate analyses for the MFs in the binned data set were low (<0.2). In contrast, in the aligned data set, we obtained moderate heritability (0.2 to 0.5) for 3.5% of MFs and high heritability (more than 0.5) for 1% of MFs. The bivariate analyses showed that ~12%, ~3%, ~9%, and ~9% of MFs had significant additive genetic correlations with BW, ADG154-294, ADG294-336, and ADG154-336, respectively. In all of the bivariate analyses, the percentage of significant additive genetic correlations was higher than the percentage of significant phenotypic correlations of the corresponding trait. Our results provided insights into the influence of the underlying genetic mechanisms on MFs. Further investigations in this field are needed for better understanding of the genetic relationship among the MFs and quantitative traits.
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Affiliation(s)
- Amir Aliakbari
- Department of Animal Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Alireza Ehsani
- Department of Animal Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Rasoul Vaez Torshizi
- Department of Animal Science, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran
| | - Peter Løvendahl
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Hadi Esfandyari
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Just Jensen
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Pernille Sarup
- Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
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16
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Witjes L, Kooke R, van der Hooft JJJ, de Vos RCH, Keurentjes JJB, Medema MH, Nijveen H. A genetical metabolomics approach for bioprospecting plant biosynthetic gene clusters. BMC Res Notes 2019; 12:194. [PMID: 30940198 PMCID: PMC6444639 DOI: 10.1186/s13104-019-4222-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 03/25/2019] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Plants produce a plethora of specialized metabolites to defend themselves against pathogens and insects, to attract pollinators and to communicate with other organisms. Many of these are also applied in the clinic and in agriculture. Genes encoding the enzymes that drive the biosynthesis of these metabolites are sometimes physically grouped on the chromosome, in regions called biosynthetic gene clusters (BGCs). Several algorithms have been developed to identify plant BGCs, but a large percentage of predicted gene clusters upon further inspection do not show coexpression or do not encode a single functional biosynthetic pathway. Hence, further prioritization is needed. RESULTS Here, we introduce a strategy to systematically evaluate potential functions of predicted BGCs by superimposing their locations on metabolite quantitative trait loci (mQTLs). We show the feasibility of such an approach by integrating automated BGC prediction with mQTL datasets originating from a recombinant inbred line (RIL) population of Oryza sativa and a genome-wide association study (GWAS) of Arabidopsis thaliana. In these data, we identified several links for which the enzyme content of the BGCs matches well with the chemical features observed in the metabolite structure, suggesting that this method can effectively guide bioprospecting of plant BGCs.
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Affiliation(s)
- Lotte Witjes
- Bioinformatics Group, Wageningen University & Research, Wageningen, The Netherlands
| | - Rik Kooke
- Laboratory of Genetics, Wageningen University & Research, Wageningen, The Netherlands.,Centre for BioSystems Genomics, Wageningen, The Netherlands
| | | | - Ric C H de Vos
- Business Unit Bioscience, Wageningen University & Research, Wageningen, The Netherlands.,Centre for BioSystems Genomics, Wageningen, The Netherlands.,Netherlands Metabolomics Centre, Utrecht, The Netherlands
| | - Joost J B Keurentjes
- Laboratory of Genetics, Wageningen University & Research, Wageningen, The Netherlands.,Centre for BioSystems Genomics, Wageningen, The Netherlands
| | - Marnix H Medema
- Bioinformatics Group, Wageningen University & Research, Wageningen, The Netherlands.
| | - Harm Nijveen
- Bioinformatics Group, Wageningen University & Research, Wageningen, The Netherlands.
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17
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Saia S, Fragasso M, De Vita P, Beleggia R. Metabolomics Provides Valuable Insight for the Study of Durum Wheat: A Review. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:3069-3085. [PMID: 30829031 DOI: 10.1021/acs.jafc.8b07097] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Metabolomics is increasingly being applied in various fields offering a highly informative tool for high-throughput diagnostics. However, in plant sciences, metabolomics is underused, even though plant studies are relatively easy and cheap when compared to those on humans and animals. Despite their importance for human nutrition, cereals, and especially wheat, remain understudied from a metabolomics point of view. The metabolomics of durum wheat has been essentially neglected, although its genetic structure allows the inference of common mechanisms that can be extended to other wheat and cereal species. This review covers the present achievements in durum wheat metabolomics highlighting the connections with the metabolomics of other cereal species (especially bread wheat). We discuss the metabolomics data from various studies and their relationships to other "-omics" sciences, in terms of wheat genetics, abiotic and biotic stresses, beneficial microbes, and the characterization and use of durum wheat as feed, food, and food ingredient.
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Affiliation(s)
- Sergio Saia
- Council for Agricultural Research and Economics (CREA) , Research Centre for Cereal and Industrial Crops (CREA-CI) , S.S. 673 , Km 25,200, 71122 Foggia , Italy
- Council for Agricultural Research and Economics (CREA) , Research Centre for Cereal and Industrial Crops (CREA-CI) , S.S. 11 per Torino , Km 2,5, 13100 Vercelli , Italy
| | - Mariagiovanna Fragasso
- Council for Agricultural Research and Economics (CREA) , Research Centre for Cereal and Industrial Crops (CREA-CI) , S.S. 673 , Km 25,200, 71122 Foggia , Italy
| | - Pasquale De Vita
- Council for Agricultural Research and Economics (CREA) , Research Centre for Cereal and Industrial Crops (CREA-CI) , S.S. 673 , Km 25,200, 71122 Foggia , Italy
| | - Romina Beleggia
- Council for Agricultural Research and Economics (CREA) , Research Centre for Cereal and Industrial Crops (CREA-CI) , S.S. 673 , Km 25,200, 71122 Foggia , Italy
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18
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Thorwarth P, Liu G, Ebmeyer E, Schacht J, Schachschneider R, Kazman E, Reif JC, Würschum T, Longin CFH. Dissecting the genetics underlying the relationship between protein content and grain yield in a large hybrid wheat population. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:489-500. [PMID: 30456718 DOI: 10.1007/s00122-018-3236-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Accepted: 11/07/2018] [Indexed: 05/13/2023]
Abstract
Additive and dominance effect QTL for grain yield and protein content display antagonistic pleiotropic effects, making genomic selection based on the index grain protein deviation a promising method to alleviate the negative correlation between these traits in wheat breeding. Grain yield and quality-related traits such as protein content and sedimentation volume are key traits in wheat breeding. In this study, we used a large population of 1604 hybrids and their 135 parental components to investigate the genetics and metabolomics underlying the negative relationship of grain yield and quality, and evaluated approaches for their joint improvement. We identified a total of nine trait-associated metabolites and show that prediction using genomic data alone resulted in the highest prediction ability for all traits. We dissected the genetic architecture of grain yield and quality-determining traits and show results of the first mapping of the derived trait grain protein deviation. Further, we provide a genetic analysis of the antagonistic relation of grain yield and protein content and dissect the mode of gene action (pleiotropy vs linkage) of identified QTL. Lastly, we demonstrate that the composition of the training set for genomic prediction is crucial when considering different quality classes in wheat breeding.
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Affiliation(s)
- Patrick Thorwarth
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany
| | - Guozheng Liu
- BASF Agricultural Solutions Seed GmbH, OT Gatersleben, Am Schwabeplan 8, 06466, Seeland, Germany
| | | | | | | | | | - Jochen Christoph Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Tobias Würschum
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany
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19
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Peng Y, Liu H, Chen J, Shi T, Zhang C, Sun D, He Z, Hao Y, Chen W. Genome-Wide Association Studies of Free Amino Acid Levels by Six Multi-Locus Models in Bread Wheat. FRONTIERS IN PLANT SCIENCE 2018; 9:1196. [PMID: 30154817 PMCID: PMC6103272 DOI: 10.3389/fpls.2018.01196] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Accepted: 07/26/2018] [Indexed: 05/02/2023]
Abstract
Genome-wide association studies (GWAS) have been widely used to dissect the complex biosynthetic processes of plant metabolome. Most studies have used single-locus GWAS approaches, such as mixed linear model (MLM), and little is known about more efficient algorithms to implement multi-locus GWAS. Here, we report a comprehensive GWAS of 20 free amino acid (FAA) levels in kernels of bread wheat (Triticumaestivum L.) based on 14,646 SNPs by six multi-locus models (FASTmrEMMA, FASTmrMLM, ISISEM-BLASSO, mrMLM, pKWmEB, and pLARmEB). Our results showed that 328 significant quantitative trait nucleotides (QTNs) were identified in total (38, 8, 92, 45, 117, and 28, respectively, for the above six models). Among them, 66 were repeatedly detected by more than two models, and 155 QTNs appeared only in one model, indicating the reliability and complementarity of these models. We also found that the number of significant QTNs for different FAAs varied from 8 to 41, which revealed the complexity of the genetic regulation of metabolism, and further demonstrated the necessity of the multi-locus GWAS. Around these significant QTNs, 15 candidate genes were found to be involved in FAA biosynthesis, and one candidate gene (TraesCS1D01G052500, annotated as tryptophan decarboxylase) was functionally identified to influence the content of tryptamine in vitro. Our study demonstrated the power and efficiency of multi-locus GWAS models in crop metabolome research and provided new insights into understanding FAA biosynthesis in wheat.
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Affiliation(s)
- Yanchun Peng
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Hongbo Liu
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, China
| | - Jie Chen
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Taotao Shi
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Chi Zhang
- School of Chemical Science and Engineering, Royal Institute of Technology, Stockholm, Sweden
| | - Dongfa Sun
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Zhonghu He
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuanfeng Hao
- Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wei Chen
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
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20
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Casartelli A, Riewe D, Hubberten HM, Altmann T, Hoefgen R, Heuer S. Exploring traditional aus-type rice for metabolites conferring drought tolerance. RICE (NEW YORK, N.Y.) 2018; 11:9. [PMID: 29372429 PMCID: PMC5785456 DOI: 10.1186/s12284-017-0189-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 11/22/2017] [Indexed: 05/07/2023]
Abstract
BACKGROUND Traditional varieties and landraces belonging to the aus-type group of rice (Oryza sativa L.) are known to be highly tolerant to environmental stresses, such as drought and heat, and are therefore recognized as a valuable genetic resource for crop improvement. Using two aus-type (Dular, N22) and two drought intolerant irrigated varieties (IR64, IR74) an untargeted metabolomics analysis was conducted to identify drought-responsive metabolites associated with tolerance. RESULTS The superior drought tolerance of Dular and N22 compared with the irrigated varieties was confirmed by phenotyping plants grown to maturity after imposing severe drought stress in a dry-down treatment. Dular and N22 did not show a significant reduction in grain yield compared to well-watered control plants, whereas the intolerant varieties showed a significant reduction in both, total spikelet number and grain yield. The metabolomics analysis was conducted with shoot and root samples of plants at the tillering stage at the end of the dry-down treatment. The data revealed an overall higher accumulation of N-rich metabolites (amino acids and nucleotide-related metabolites allantoin and uridine) in shoots of the tolerant varieties. In roots, the aus-type varieties were characterised by a higher reduction of metabolites representative of glycolysis and the TCA cycle, such as malate, glyceric acid and glyceric acid-3-phosphate. On the other hand, the oligosaccharide raffinose showed a higher fold increase in both, shoots and roots of the sensitive genotypes. The data further showed that, for certain drought-responsive metabolites, differences between the contrasting rice varieties were already evident under well-watered control conditions. CONCLUSIONS The drought tolerance-related metabolites identified in the aus-type varieties provide a valuable set of protective compounds and an entry point for assessing genetic diversity in the underlying pathways for developing drought tolerant rice and other crops.
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Affiliation(s)
- Alberto Casartelli
- School of Agriculture, Food and Wine, Waite Campus, The University of Adelaide, Adelaide, SA Australia
| | - David Riewe
- Julius Kühn-Institute (JKI), Federal Research Centre for Cultivated Plants, Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Berlin, Germany
| | | | - Thomas Altmann
- Julius Kühn-Institute (JKI), Federal Research Centre for Cultivated Plants, Institute for Ecological Chemistry, Plant Analysis and Stored Product Protection, Berlin, Germany
| | - Rainer Hoefgen
- Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany
| | - Sigrid Heuer
- School of Agriculture, Food and Wine, Waite Campus, The University of Adelaide, Adelaide, SA Australia
- Rothamsted Research, Harpenden, UK
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21
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Alomari DZ, Eggert K, von Wirén N, Pillen K, Röder MS. Genome-Wide Association Study of Calcium Accumulation in Grains of European Wheat Cultivars. FRONTIERS IN PLANT SCIENCE 2017; 8:1797. [PMID: 29163559 PMCID: PMC5663994 DOI: 10.3389/fpls.2017.01797] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 10/03/2017] [Indexed: 05/20/2023]
Abstract
Mineral concentrations in cereals are important for human health, especially for people who depend mainly on consuming cereal diet. In this study, we carried out a genome-wide association study (GWAS) of calcium concentrations in wheat (Triticum aestivum L.) grains using a European wheat diversity panel of 353 varieties [339 winter wheat (WW) plus 14 of spring wheat (SW)] and phenotypic data based on two field seasons. High genotyping densities of single-nucleotide polymorphism (SNP) markers were obtained from the application of the 90k iSELECT ILLUMINA chip and a 35k Affymetrix chip. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to measure the calcium concentrations of the wheat grains. Best linear unbiased estimates (BLUEs) for calcium were calculated across the seasons and ranged from 288.20 to 647.50 among the varieties (μg g-1 DW) with a mean equaling 438.102 (μg g-1 DW), and the heritability was 0.73. A total of 485 SNP marker-trait associations (MTAs) were detected in data obtained from grains cultivated in both of the two seasons and BLUE values by considering associations with a -log10 (P-value) ≥3.0. Among these SNP markers, we detected 276 markers with a positive allele effect and 209 markers with a negative allele effect. These MTAs were found on all chromosomes except chromosomes 3D, 4B, and 4D. The most significant association was located on chromosome 5A (114.5 cM) and was linked to a gene encoding cation/sugar symporter activity as a potential candidate gene. Additionally, a number of candidate genes for the uptake or transport of calcium were located near significantly associated SNPs. This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally variable traits in genetically highly diverse variety panels. The research demonstrates the feasibility of the GWAS approach for illuminating the genetic architecture of calcium-concentration in wheat grains and for identifying putative candidate genes underlying this trait.
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Affiliation(s)
- Dalia Z. Alomari
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Kai Eggert
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Nicolaus von Wirén
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Klaus Pillen
- Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Marion S. Röder
- Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
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22
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Fusari CM, Kooke R, Lauxmann MA, Annunziata MG, Enke B, Hoehne M, Krohn N, Becker FFM, Schlereth A, Sulpice R, Stitt M, Keurentjes JJB. Genome-Wide Association Mapping Reveals That Specific and Pleiotropic Regulatory Mechanisms Fine-Tune Central Metabolism and Growth in Arabidopsis. THE PLANT CELL 2017; 29:2349-2373. [PMID: 28954812 PMCID: PMC5774568 DOI: 10.1105/tpc.17.00232] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 08/30/2017] [Accepted: 09/25/2017] [Indexed: 05/18/2023]
Abstract
Central metabolism is a coordinated network that is regulated at multiple levels by resource availability and by environmental and developmental cues. Its genetic architecture has been investigated by mapping metabolite quantitative trait loci (QTL). A more direct approach is to identify enzyme activity QTL, which distinguishes between cis-QTL in structural genes encoding enzymes and regulatory trans-QTL. Using genome-wide association studies, we mapped QTL for 24 enzyme activities, nine metabolites, three structural components, and biomass in Arabidopsis thaliana We detected strong cis-QTL for five enzyme activities. A cis-QTL for UDP-glucose pyrophosphorylase activity in the UGP1 promoter is maintained through balancing selection. Variation in acid invertase activity reflects multiple evolutionary events in the promoter and coding region of VAC-INVcis-QTL were also detected for ADP-glucose pyrophosphorylase, fumarase, and phosphoglucose isomerase activity. We detected many trans-QTL, including transcription factors, E3 ligases, protein targeting components, and protein kinases, and validated some by knockout analysis. trans-QTL are more frequent but tend to have smaller individual effects than cis-QTL. We detected many colocalized QTL, including a multitrait QTL on chromosome 4 that affects six enzyme activities, three metabolites, protein, and biomass. These traits are coordinately modified by different ACCELERATED CELL DEATH6 alleles, revealing a trade-off between metabolism and defense against biotic stress.
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Affiliation(s)
- Corina M Fusari
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Rik Kooke
- Laboratory of Genetics, Wageningen University, 6708 PB Wageningen, The Netherlands
- Centre for Biosystems Genomics, Wageningen Campus, 6708 PB Wageningen, The Netherlands
| | - Martin A Lauxmann
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | | | - Beatrice Enke
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Melanie Hoehne
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Nicole Krohn
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Frank F M Becker
- Laboratory of Genetics, Wageningen University, 6708 PB Wageningen, The Netherlands
| | - Armin Schlereth
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Ronan Sulpice
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Mark Stitt
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Joost J B Keurentjes
- Laboratory of Genetics, Wageningen University, 6708 PB Wageningen, The Netherlands
- Centre for Biosystems Genomics, Wageningen Campus, 6708 PB Wageningen, The Netherlands
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