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He X, Wang D, Jiang Y, Li M, Delgado-Baquerizo M, McLaughlin C, Marcon C, Guo L, Baer M, Moya YAT, von Wirén N, Deichmann M, Schaaf G, Piepho HP, Yang Z, Yang J, Yim B, Smalla K, Goormachtig S, de Vries FT, Hüging H, Baer M, Sawers RJH, Reif JC, Hochholdinger F, Chen X, Yu P. Heritable microbiome variation is correlated with source environment in locally adapted maize varieties. Nat Plants 2024; 10:598-617. [PMID: 38514787 DOI: 10.1038/s41477-024-01654-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 02/15/2024] [Indexed: 03/23/2024]
Abstract
Beneficial interactions with microorganisms are pivotal for crop performance and resilience. However, it remains unclear how heritable the microbiome is with respect to the host plant genotype and to what extent host genetic mechanisms can modulate plant-microbiota interactions in the face of environmental stresses. Here we surveyed 3,168 root and rhizosphere microbiome samples from 129 accessions of locally adapted Zea, sourced from diverse habitats and grown under control and different stress conditions. We quantified stress treatment and host genotype effects on the microbiome. Plant genotype and source environment were predictive of microbiome abundance. Genome-wide association analysis identified host genetic variants linked to both rhizosphere microbiome abundance and source environment. We identified transposon insertions in a candidate gene linked to both the abundance of a keystone bacterium Massilia in our controlled experiments and total soil nitrogen in the source environment. Isolation and controlled inoculation of Massilia alone can contribute to root development, whole-plant biomass production and adaptation to low nitrogen availability. We conclude that locally adapted maize varieties exert patterns of genetic control on their root and rhizosphere microbiomes that follow variation in their home environments, consistent with a role in tolerance to prevailing stress.
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Affiliation(s)
- Xiaoming He
- College of Resources and Environment, and Academy of Agricultural Sciences, Southwest University (SWU), Chongqing, People's Republic of China
- Emmy Noether Group Root Functional Biology, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Danning Wang
- Emmy Noether Group Root Functional Biology, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Yong Jiang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Meng Li
- Department of Plant Science, Pennsylvania State University, State College, PA, USA
| | - Manuel Delgado-Baquerizo
- Laboratorio de Biodiversidad y Funcionamiento Ecosistémico, Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Sevilla, Spain
| | - Chloee McLaughlin
- Department of Plant Science, Pennsylvania State University, State College, PA, USA
| | - Caroline Marcon
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Li Guo
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Marcel Baer
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Yudelsy A T Moya
- Department of Physiology and Cell Biology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Nicolaus von Wirén
- Department of Physiology and Cell Biology, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Marion Deichmann
- Plant Nutrition, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Gabriel Schaaf
- Plant Nutrition, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | | | - Zhikai Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - Bunlong Yim
- Institute for Epidemiology and Pathogen Diagnostics, Julius Kühn-Institut - Federal Research Centre for Cultivated Plants (JKI), Braunschweig, Germany
| | - Kornelia Smalla
- Institute for Epidemiology and Pathogen Diagnostics, Julius Kühn-Institut - Federal Research Centre for Cultivated Plants (JKI), Braunschweig, Germany
| | - Sofie Goormachtig
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Center for Plant Systems Biology, VIB, Ghent, Belgium
| | - Franciska T de Vries
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands
| | - Hubert Hüging
- Crop Science Group, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | - Mareike Baer
- Institute of Nutrition and Food Sciences, Department of Food Microbiology and Hygiene, University of Bonn, Bonn, Germany
| | - Ruairidh J H Sawers
- Department of Plant Science, Pennsylvania State University, State College, PA, USA.
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
| | - Frank Hochholdinger
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany.
| | - Xinping Chen
- College of Resources and Environment, and Academy of Agricultural Sciences, Southwest University (SWU), Chongqing, People's Republic of China.
| | - Peng Yu
- Emmy Noether Group Root Functional Biology, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany.
- Crop Functional Genomics, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany.
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2
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Berkner MO, Weise S, Reif JC, Schulthess AW. Genomic prediction reveals unexplored variation in grain protein and lysine content across a vast winter wheat genebank collection. Front Plant Sci 2024; 14:1270298. [PMID: 38273944 PMCID: PMC10808176 DOI: 10.3389/fpls.2023.1270298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/31/2023] [Indexed: 01/27/2024]
Abstract
Globally, wheat (Triticum aestivum L.) is a major source of proteins in human nutrition despite its unbalanced amino acid composition. The low lysine content in the protein fraction of wheat can lead to protein-energy-malnutrition prominently in developing countries. A promising strategy to overcome this problem is to breed varieties which combine high protein content with high lysine content. Nevertheless, this requires the incorporation of yet undefined donor genotypes into pre-breeding programs. Genebank collections are suspected to harbor the needed genetic diversity. In the 1970s, a large-scale screening of protein traits was conducted for the wheat genebank collection in Gatersleben; however, this data has been poorly mined so far. In the present study, a large historical dataset on protein content and lysine content of 4,971 accessions was curated, strictly corrected for outliers as well as for unreplicated data and consolidated as the corresponding adjusted entry means. Four genomic prediction approaches were compared based on the ability to accurately predict the traits of interest. High-quality phenotypic data of 558 accessions was leveraged by engaging the best performing prediction model, namely EG-BLUP. Finally, this publication incorporates predicted phenotypes of 7,651 accessions of the winter wheat collection. Five accessions were proposed as donor genotypes due to the combination of outstanding high protein content as well as lysine content. Further investigation of the passport data suggested an association of the adjusted lysine content with the elevation of the collecting site. This publicly available information can facilitate future pre-breeding activities.
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Affiliation(s)
- Marcel O. Berkner
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Stephan Weise
- Genebank Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Jochen C. Reif
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Albert W. Schulthess
- Breeding Research Department, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
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3
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Muqaddasi QH, Muqaddasi RK, Ebmeyer E, Korzun V, Argillier O, Mirdita V, Reif JC, Ganal MW, Röder MS. Genetic control and prospects of predictive breeding for European winter wheat's Zeleny sedimentation values and Hagberg-Perten falling number. Theor Appl Genet 2023; 136:229. [PMID: 37874400 PMCID: PMC10598174 DOI: 10.1007/s00122-023-04450-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 08/16/2023] [Indexed: 10/25/2023]
Abstract
KEY MESSAGE Sedimentation values and falling number in the last decades have helped maintain high baking quality despite rigorous selection for grain yield in wheat. Allelic combinations of major loci sustained the bread-making quality while improving grain yield. Glu-D1, Pinb-D1, and non-gluten proteins are associated with sedimentation values and falling number in European wheat. Zeleny sedimentation values (ZSV) and Hagberg-Perten falling number (HFN) are among the most important parameters that help determine the baking quality classes of wheat and, thus, influence the monetary benefits for growers. We used a published data set of 372 European wheat varieties evaluated in replicated field trials in multiple environments. ZSV and HFN traits hold a wide and significant genotypic variation and high broad-sense heritability. The genetic correlations revealed positive and significant associations of ZSV and HFN with each other, grain protein content (GPC) and grain hardness; however, they were all significantly negatively correlated with grain yield. Besides, GPC appeared to be the major predictor for ZSV and HFN. Our genome-wide association analyses based on high-quality SSR, SNP, and candidate gene markers revealed a strong quantitative genetic nature of ZSV and HFN by explaining their total genotypic variance as 41.49% and 38.06%, respectively. The association of known Glutenin (Glu-1) and Puroindoline (Pin-1) with ZSV provided positive analytic proof of our studies. We report novel candidate loci associated with globulins and albumins-the non-gluten monomeric proteins in wheat. In addition, predictive breeding analyses for ZSV and HFN suggest using genomic selection in the early stages of breeding programs with an average prediction accuracy of 81 and 59%, respectively.
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Affiliation(s)
- Quddoos H Muqaddasi
- European Wheat Breeding Center, BASF Agricultural Solutions GmbH, Am Schwabeplan 8, 06466, Stadt Seeland OT Gatersleben, Germany.
- KWS SAAT SE & Co. KGaA, Einbeck, 37574, Germany.
| | - Roop Kamal Muqaddasi
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, 06466, Stadt Seeland OT Gatersleben, Germany
| | | | | | | | - Vilson Mirdita
- European Wheat Breeding Center, BASF Agricultural Solutions GmbH, Am Schwabeplan 8, 06466, Stadt Seeland OT Gatersleben, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, 06466, Stadt Seeland OT Gatersleben, Germany
| | - Martin W Ganal
- TraitGenetics GmbH, Am Schwabeplan 1B, 06466, Stadt Seeland OT Gatersleben, Germany
| | - Marion S Röder
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, 06466, Stadt Seeland OT Gatersleben, Germany
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4
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El Hanafi S, Jiang Y, Kehel Z, Schulthess AW, Zhao Y, Mascher M, Haupt M, Himmelbach A, Stein N, Amri A, Reif JC. Genomic predictions to leverage phenotypic data across genebanks. Front Plant Sci 2023; 14:1227656. [PMID: 37701801 PMCID: PMC10493331 DOI: 10.3389/fpls.2023.1227656] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 08/07/2023] [Indexed: 09/14/2023]
Abstract
Genome-wide prediction is a powerful tool in breeding. Initial results suggest that genome-wide approaches are also promising for enhancing the use of the genebank material: predicting the performance of plant genetic resources can unlock their hidden potential and fill the information gap in genebanks across the world and, hence, underpin prebreeding programs. As a proof of concept, we evaluated the power of across-genebank prediction for extensive germplasm collections relying on historical data on flowering/heading date, plant height, and thousand kernel weight of 9,344 barley (Hordeum vulgare L.) plant genetic resources from the German Federal Ex situ Genebank for Agricultural and Horticultural Crops (IPK) and of 1,089 accessions from the International Center for Agriculture Research in the Dry Areas (ICARDA) genebank. Based on prediction abilities for each trait, three scenarios for predictive characterization were compared: 1) a benchmark scenario, where test and training sets only contain ICARDA accessions, 2) across-genebank predictions using IPK as training and ICARDA as test set, and 3) integrated genebank predictions that include IPK with 30% of ICARDA accessions as a training set to predict the rest of ICARDA accessions. Within the population of ICARDA accessions, prediction abilities were low to moderate, which was presumably caused by a limited number of accessions used to train the model. Interestingly, ICARDA prediction abilities were boosted up to ninefold by using training sets composed of IPK plus 30% of ICARDA accessions. Pervasive genotype × environment interactions (GEIs) can become a potential obstacle to train robust genome-wide prediction models across genebanks. This suggests that the potential adverse effect of GEI on prediction ability was counterbalanced by the augmented training set with certain connectivity to the test set. Therefore, across-genebank predictions hold the promise to improve the curation of the world's genebank collections and contribute significantly to the long-term development of traditional genebanks toward biodigital resource centers.
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Affiliation(s)
- Samira El Hanafi
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Zakaria Kehel
- International Center for Agricultural Research in Dry Areas (ICARDA), Rabat, Morocco
| | - Albert W. Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Max Haupt
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August-University, Göttingen, Germany
| | - Ahmed Amri
- International Center for Agricultural Research in Dry Areas (ICARDA), Rabat, Morocco
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
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Würschum T, Zhu X, Zhao Y, Jiang Y, Reif JC, Maurer HP. Maximization through optimization? On the relationship between hybrid performance and parental genetic distance. Theor Appl Genet 2023; 136:186. [PMID: 37572118 PMCID: PMC10423127 DOI: 10.1007/s00122-023-04436-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/31/2023] [Indexed: 08/14/2023]
Abstract
Heterosis is the improved performance of hybrids compared with their parental components and is widely exploited in agriculture. According to quantitative genetic theory, genetic distance between parents at heterotic quantitative trait loci is required for heterosis, but how heterosis varies with genetic distance has remained elusive, despite intensive research on the topic. Experimental studies have often found a positive association between heterosis and genetic distance that, however, varied in strength. Most importantly, it has remained unclear whether heterosis increases continuously with genetic distance or whether there is an optimum genetic distance after which heterosis declines again. Here, we revisit the relationship between heterosis and genetic distance and provide perspectives on how to maximize heterosis and hybrid performance in breeding, as well as the consequences for the design of heterotic groups and the utilization of more exotic material and genetic resources.
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Affiliation(s)
- Tobias Würschum
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70599, Stuttgart, Germany.
| | - Xintian Zhu
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, 70599, Stuttgart, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Hans Peter Maurer
- State Plant Breeding Institute, University of Hohenheim, 70599, Stuttgart, Germany
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6
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Tian Y, Li D, Wang X, Zhang H, Wang J, Yu L, Guo C, Luan X, Liu X, Li H, Reif JC, Li YH, Qiu LJ. Deciphering the genetic basis of resistance to soybean cyst nematode combining IBD and association mapping. Theor Appl Genet 2023; 136:50. [PMID: 36912956 PMCID: PMC10011322 DOI: 10.1007/s00122-023-04268-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 12/07/2022] [Indexed: 06/18/2023]
Abstract
IBD analysis clarified the dynamics of chromosomal recombination during the ZP pedigree breeding process and identified ten genomic regions resistant to SCN race3 combining association mapping. Soybean cyst nematode (SCN, Heterodera glycines Ichinohe) is one of the most devastating pathogens for soybean production worldwide. The cultivar Zhongpin03-5373 (ZP), derived from SCN-resistant progenitor parents, Peking, PI 437654 and Huipizhi Heidou, is an elite line with high resistance to SCN race3. In the current study, a pedigree variation map was generated for ZP and its ten progenitors using 3,025,264 high-quality SNPs identified from an average of 16.2 × re-sequencing for each genome. Through identity by decent (IBD) tracking, we showed the dynamic change of genome and detected important IBD fragments, which revealed the comprehensively artificial selection of important traits during ZP breeding process. A total of 2,353 IBD fragments related to SCN resistance including SCN-resistant genes rhg1, rhg4 and NSFRAN07 were identified based on the resistant-related genetic paths. Moreover, 23 genomic regions underlying resistance to SCN race3 were identified by genome-wide association study (GWAS) in 481 re-sequenced cultivated soybeans. Ten common loci were found by both IBD tracking and GWAS analysis. Haplotype analysis of 16 potential candidate genes suggested a causative SNP (C/T, - 1065) located in the promoter of Glyma.08G096500 and encoding a predicted TIFY5b-related protein on chr8 was highly correlated with SCN race3 resistance. Our results more thoroughly elucidated the dynamics of genomic fragments during ZP pedigree breeding and the genetic basis of SCN resistance, which will provide useful information for gene cloning and the development of resistant soybean cultivars using a marker-assisted selection approach.
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Affiliation(s)
- Yu Tian
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China
| | - Delin Li
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China
| | - Xueqing Wang
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China
| | - Hao Zhang
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China
| | - Jiajun Wang
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Lijie Yu
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Heilongjiang Province, Harbin, China
| | - Changhong Guo
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Heilongjiang Province, Harbin, China
| | - Xiaoyan Luan
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Xinlei Liu
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Hongjie Li
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Ying-Hui Li
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China.
| | - Li-Juan Qiu
- The National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Institute of Crop Sciences, Chinese Academy of Agricultural Science, Beijing, 100081, People's Republic of China.
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7
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Hinterberger V, Douchkov D, Lueck S, Reif JC, Schulthess AW. High-throughput imaging of powdery mildew resistance of the winter wheat collection hosted at the German Federal ex situ Genebank for Agricultural and Horticultural Crops. Gigascience 2022; 12:7068386. [PMID: 36869695 PMCID: PMC9984986 DOI: 10.1093/gigascience/giad007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/28/2022] [Accepted: 02/02/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Genebanks worldwide are transforming into biodigital resource centers, providing access not only to the plant material itself but also to its phenotypic and genotypic information. Adding information for relevant traits will help boost plant genetic resources' usage in breeding and research. Resistance traits are vital for adapting our agricultural systems to future challenges. FINDINGS Here we provide phenotypic data for the resistance against Blumeria graminis f. sp. tritici, the causal agent of wheat powdery mildew-a substantial risk to our agricultural production. Using a modern high-throughput phenotyping system, we infected and photographed a total of 113,638 wheat leaves of 7,320 winter wheat (Triticum aestivum L.) plant genetic resources of the German Federal ex situ Genebank for Agricultural and Horticultural Crops and 154 commercial genotypes. We quantified the resistance reaction captured by images and provide them here, along with the raw images. CONCLUSION This massive amount of phenotypic data, combined with already published genotypic data, also provides a valuable and unique training dataset for the development of novel genotype-based predictions as well as mapping methods.
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Affiliation(s)
- Valentin Hinterberger
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Breeding Research, D-06466, Seeland, Germany
| | - Dimitar Douchkov
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Breeding Research, D-06466, Seeland, Germany
| | - Stefanie Lueck
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Breeding Research, D-06466, Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Breeding Research, D-06466, Seeland, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Department of Breeding Research, D-06466, Seeland, Germany
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8
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Schulthess AW, Kale SM, Zhao Y, Gogna A, Rembe M, Philipp N, Liu F, Beukert U, Serfling A, Himmelbach A, Oppermann M, Weise S, Boeven PHG, Schacht J, Longin CFH, Kollers S, Pfeiffer N, Korzun V, Fiebig A, Schüler D, Lange M, Scholz U, Stein N, Mascher M, Reif JC. Large-scale genotyping and phenotyping of a worldwide winter wheat genebank for its use in pre-breeding. Sci Data 2022; 9:784. [PMID: 36572688 PMCID: PMC9792552 DOI: 10.1038/s41597-022-01891-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/07/2022] [Indexed: 12/27/2022] Open
Abstract
Plant genetic resources (PGR) stored at genebanks are humanity's crop diversity savings for the future. Information on PGR contrasted with modern cultivars is key to select PGR parents for pre-breeding. Genotyping-by-sequencing was performed for 7,745 winter wheat PGR samples from the German Federal ex situ genebank at IPK Gatersleben and for 325 modern cultivars. Whole-genome shotgun sequencing was carried out for 446 diverse PGR samples and 322 modern cultivars and lines. In 19 field trials, 7,683 PGR and 232 elite cultivars were characterized for resistance to yellow rust - one of the major threats to wheat worldwide. Yield breeding values of 707 PGR were estimated using hybrid crosses with 36 cultivars - an approach that reduces the lack of agronomic adaptation of PGR and provides better estimates of their contribution to yield breeding. Cross-validations support the interoperability between genomic and phenotypic data. The here presented data are a stepping stone to unlock the functional variation of PGR for European pre-breeding and are the basis for future breeding and research activities.
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Affiliation(s)
- Albert W. Schulthess
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Sandip M. Kale
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany ,grid.418674.80000 0004 0533 4528Present Address: Carlsberg Research Laboratory, Copenhagen, Denmark
| | - Yusheng Zhao
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Abhishek Gogna
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Maximilian Rembe
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Norman Philipp
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Fang Liu
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany ,grid.9227.e0000000119573309Present Address: Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China
| | - Ulrike Beukert
- grid.13946.390000 0001 1089 3517Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Albrecht Serfling
- grid.13946.390000 0001 1089 3517Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Axel Himmelbach
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Markus Oppermann
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Stephan Weise
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | | | | | - C. Friedrich H. Longin
- grid.9464.f0000 0001 2290 1502State Plant Breeding Institute, University of Hohenheim, Stuttgart, Germany
| | - Sonja Kollers
- grid.425691.dKWS SAAT SE & Co. KGaA, Einbeck, Germany
| | | | - Viktor Korzun
- grid.425691.dKWS SAAT SE & Co. KGaA, Einbeck, Germany
| | - Anne Fiebig
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Danuta Schüler
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Matthias Lange
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Uwe Scholz
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Nils Stein
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany ,grid.7450.60000 0001 2364 4210Center for Integrated Breeding Research (CiBreed), Georg-August-University, Göttingen, Germany
| | - Martin Mascher
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany ,grid.421064.50000 0004 7470 3956German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Jochen C. Reif
- grid.418934.30000 0001 0943 9907Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
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9
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Berkner MO, Schulthess AW, Zhao Y, Jiang Y, Oppermann M, Reif JC. Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model. Theor Appl Genet 2022; 135:4391-4407. [PMID: 36182979 PMCID: PMC9734214 DOI: 10.1007/s00122-022-04227-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/17/2022] [Indexed: 06/16/2023]
Abstract
Genomic prediction of genebank accessions benefits from the consideration of additive-by-additive epistasis and subpopulation-specific marker effects. Wheat (Triticum aestivum L.) and other species of the Triticum genus are well represented in genebank collections worldwide. The substantial genetic diversity harbored by more than 850,000 accessions can be explored for their potential use in modern plant breeding. Characterization of these large number of accessions is constrained by the required resources, and this fact limits their use so far. This limitation might be overcome by engaging genomic prediction. The present study compared ten different genomic prediction approaches to the prediction of four traits, namely flowering time, plant height, thousand grain weight, and yellow rust resistance, in a diverse set of 7745 accession samples from Germany's Federal ex situ genebank at the Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben. Approaches were evaluated based on prediction ability and robustness to the confounding influence of strong population structure. The authors propose the wide application of extended genomic best linear unbiased prediction due to the observed benefit of incorporating additive-by-additive epistasis. General and subpopulation-specific additive ridge regression best linear unbiased prediction, which accounts for subpopulation-specific marker-effects, was shown to be a good option if contrasting clusters are encountered in the analyzed collection. The presented findings reaffirm that the trait's genetic architecture as well as the composition and relatedness of the training set and test set are major driving factors for the accuracy of genomic prediction.
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Affiliation(s)
- Marcel O Berkner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Markus Oppermann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany.
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10
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Rembe M, Zhao Y, Wendler N, Oldach K, Korzun V, Reif JC. The Potential of Genome-Wide Prediction to Support Parental Selection, Evaluated with Data from a Commercial Barley Breeding Program. Plants 2022; 11:plants11192564. [PMID: 36235430 PMCID: PMC9571379 DOI: 10.3390/plants11192564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/18/2022] [Accepted: 09/23/2022] [Indexed: 11/29/2022]
Abstract
Parental selection is at the beginning and contributes significantly to the success of any breeding work. The value of a cross is reflected in the potential of its progeny population. Breeders invest substantial resources in evaluating progeny to select the best performing genotypes as candidates for variety development. Several proposals have been made to use genomics to support parental selection. These have mostly been evaluated using theoretical considerations or simulation studies. However, evaluations using experimental data have rarely been conducted. In this study, we tested the potential of genomic prediction for predicting the progeny mean, variance, and usefulness criterion using data from an applied breeding population for winter barley. For three traits with genetic architectures at varying levels of complexity, ear emergence, plant height, and grain yield, progeny mean, variance, and usefulness criterion were predicted and validated in scenarios resembling situations in which the described tools shall be used in plant breeding. While the population mean could be predicted with moderate to high prediction abilities amounting to 0.64, 0.21, and 0.39 in ear emergence, plant height, and grain yield, respectively, the prediction of family variance appeared difficult, as reflected in low prediction abilities of 0.41, 0.11, and 0.14, for ear emergence, plant height, and grain yield, respectively. We have shown that identifying superior crosses remains a challenging task and suggest that the success of predicting the usefulness criterion depends strongly on the complexity of the underlying trait.
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Affiliation(s)
- Maximilian Rembe
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Neele Wendler
- KWS LOCHOW GmbH, Ferdinand-von-Lochow-Str. 5, 29303 Bergen, Germany
| | - Klaus Oldach
- KWS LOCHOW GmbH, Ferdinand-von-Lochow-Str. 5, 29303 Bergen, Germany
| | - Viktor Korzun
- KWS SAAT SE & Co. KGaA, Grimsehlstr. 31, 37574 Einbeck, Germany
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
- Correspondence:
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11
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Gogna A, Schulthess AW, Röder MS, Ganal MW, Reif JC. Gabi wheat a panel of European elite lines as central stock for wheat genetic research. Sci Data 2022; 9:538. [PMID: 36056030 PMCID: PMC9440043 DOI: 10.1038/s41597-022-01651-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 08/18/2022] [Indexed: 12/20/2022] Open
Abstract
In plant sciences, curation and availability of interoperable phenotypic and genomic data is still in its infancy and represents an obstacle to rapid scientific discoveries in this field. To that end, supplementing the efforts being made to generate open access wheat genome, pan wheat genome and other bioinformatic resources, we present the GABI-WHEAT panel of elite European cultivars comprising 358 winter and 14 summer wheat varieties released between 1975 to 2007. The panel has been genotyped with SNP arrays of increasing density to investigate several important agronomic, quality and disease resistance traits. The robustness of investigated traits and interoperability of genomic and phenotypic data was assessed in the current publication with the aim to transform this panel into a public data resource for future genetic research in wheat. Consecutively, the phenotypic data was formatted to comply with FAIR principles and linked to online databases to substantiate panel origin information and quality. Thus, we were able to make a valuable resource available for plant science in a sustainable way. Measurement(s) | agronomic, quality and disease traits | Technology Type(s) | manual measurement in the field | Sample Characteristic - Organism | Triticum aestivum L. |
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Affiliation(s)
- Abhishek Gogna
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Marion S Röder
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany
| | - Martin W Ganal
- SGS Institut Fresenius GmbH, TraitGenetics Section, Am Schwabeplan 1b, 06466, Stadt Seeland OT Gatersleben, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Stadt Seeland, Germany.
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12
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Kale SM, Schulthess AW, Padmarasu S, Boeven PHG, Schacht J, Himmelbach A, Steuernagel B, Wulff BBH, Reif JC, Stein N, Mascher M. A catalogue of resistance gene homologs and a chromosome-scale reference sequence support resistance gene mapping in winter wheat. Plant Biotechnol J 2022; 20:1730-1742. [PMID: 35562859 PMCID: PMC9398310 DOI: 10.1111/pbi.13843] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/06/2022] [Accepted: 04/23/2022] [Indexed: 06/15/2023]
Abstract
A resistance gene atlas is an integral component of the breeder's arsenal in the fight against evolving pathogens. Thanks to high-throughput sequencing, catalogues of resistance genes can be assembled even in crop species with large and polyploid genomes. Here, we report on capture sequencing and assembly of resistance gene homologs in a diversity panel of 907 winter wheat genotypes comprising ex situ genebank accessions and current elite cultivars. In addition, we use accurate long-read sequencing and chromosome conformation capture sequencing to construct a chromosome-scale genome sequence assembly of cv. Attraktion, an elite variety representative of European winter wheat. We illustrate the value of our resource for breeders and geneticists by (i) comparing the resistance gene complements in plant genetic resources and elite varieties and (ii) conducting genome-wide associations scans (GWAS) for the fungal diseases yellow rust and leaf rust using reference-based and reference-free GWAS approaches. The gene content under GWAS peaks was scrutinized in the assembly of cv. Attraktion.
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Affiliation(s)
- Sandip M. Kale
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
| | - Albert W. Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
| | - Sudharsan Padmarasu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
| | | | | | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
| | | | - Brande B. H. Wulff
- John Innes CentreNorwich Research ParkNorwichUK
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division (BESE)King Abdullah University of Science and Technology (KAUST)ThuwalSaudi Arabia
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
- Center for Integrated Breeding Research (CiBreed)Georg‐August‐University GöttingenGöttingenGermany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) GaterslebenSeelandGermany
- German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐LeipzigLeipzigGermany
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13
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Grüneberg WJ, De Boeck B, Diaz F, Eyzaguirre R, Low JW, Reif JC, Campos H. Heterosis and Responses to Selection in Orange-Fleshed Sweetpotato ( Ipomoea batatas L.) Improved Using Reciprocal Recurrent Selection. Front Plant Sci 2022; 13:793904. [PMID: 35557716 PMCID: PMC9087839 DOI: 10.3389/fpls.2022.793904] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 01/13/2022] [Indexed: 06/15/2023]
Abstract
Sweetpotato is a highly heterozygous hybrid, and populations of orange-fleshed sweetpotato (OFSP) have a considerable importance for food security and health. The objectives were to estimate heterosis increments and response to selection in three OFSP hybrid populations (H1) developed in Peru for different product profiles after one reciprocal recurrent selection cycle, namely, H1 for wide adaptation and earliness (O-WAE), H1 for no sweetness after cooking (O-NSSP), and H1 for high iron (O-HIFE). The H1 populations were evaluated at two contrasting locations together with parents, foundation (parents in H0), and two widely adapted checks. Additionally, O-WAE was tested under two environmental conditions of 90-day and a normal 120-day harvest. In each H1, the yield and selected quality traits were recorded. The data were analyzed using linear mixed models. The storage root yield traits exhibited population average heterosis increments of up to 43.5%. The quality traits examined have exhibited no heterosis increments that are worth exploiting. The storage root yield genetic gain relative to the foundation was remarkable: 118.8% for H1-O-WAE for early harvest time, 81.5% for H1-O-WAE for normal harvest time, 132.4% for H1-O-NSSP, and 97.1% for H1-O-HIFE. Population hybrid breeding is a tool to achieve large genetic gains in sweetpotato yield via more efficient population improvement and allows a rapid dissemination of globally true seed that is generated from reproducible elite crosses, thus, avoiding costly and time-consuming virus cleaning of elite clones typically transferred as vegetative plantlets. The population hybrid breeding approach is probably applicable to other clonally propagated crops, where potential for true seed production exists.
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Affiliation(s)
| | | | | | | | | | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Hugo Campos
- International Potato Center (CIP), Lima, Peru
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14
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Fu J, Hao Y, Li H, Reif JC, Chen S, Huang C, Wang G, Li X, Xu Y, Li L. Integration of genomic selection with doubled-haploid evaluation in hybrid breeding: From GS 1.0 to GS 4.0 and beyond. Mol Plant 2022; 15:577-580. [PMID: 35149251 DOI: 10.1016/j.molp.2022.02.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/27/2022] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Affiliation(s)
- Junjie Fu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yangfan Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Huihui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Shaojiang Chen
- College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Changling Huang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Guoying Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xinhai Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yunbi Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; International Maize and Wheat Improvement Center (CIMMYT), EI Batan, Texcoco 56130, Mexico
| | - Liang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
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15
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Li YF, Li YH, Su SS, Reif JC, Qi ZM, Wang XB, Wang X, Tian Y, Li DL, Sun RJ, Liu ZX, Xu ZJ, Fu GH, Ji YL, Chen QS, Liu JQ, Qiu LJ. SoySNP618K array: A high-resolution single nucleotide polymorphism platform as a valuable genomic resource for soybean genetics and breeding. J Integr Plant Biol 2022; 64:632-648. [PMID: 34914170 DOI: 10.1111/jipb.13202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 12/05/2021] [Indexed: 05/13/2023]
Abstract
Innovations in genomics have enabled the development of low-cost, high-resolution, single nucleotide polymorphism (SNP) genotyping arrays that accelerate breeding progress and support basic research in crop science. Here, we developed and validated the SoySNP618K array (618,888 SNPs) for the important crop soybean. The SNPs were selected from whole-genome resequencing data containing 2,214 diverse soybean accessions; 29.34% of the SNPs mapped to genic regions representing 86.85% of the 56,044 annotated high-confidence genes. Identity-by-state analyses of 318 soybeans revealed 17 redundant accessions, highlighting the potential of the SoySNP618K array in supporting gene bank management. The patterns of population stratification and genomic regions enriched through domestication were highly consistent with previous findings based on resequencing data, suggesting that the ascertainment bias in the SoySNP618K array was largely compensated for. Genome-wide association mapping in combination with reported quantitative trait loci enabled fine-mapping of genes known to influence flowering time, E2 and GmPRR3b, and of a new candidate gene, GmVIP5. Moreover, genomic prediction of flowering and maturity time in 502 recombinant inbred lines was highly accurate (>0.65). Thus, the SoySNP618K array is a valuable genomic tool that can be used to address many questions in applied breeding, germplasm management, and basic crop research.
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Affiliation(s)
- Yan-Fei Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Ying-Hui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Shan-Shan Su
- Beijing Compass Biotechnology Co. Ltd, Beijing, 102206, China
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, 06466, Germany
| | - Zhao-Ming Qi
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Xiao-Bo Wang
- School of Agronomy, Anhui Agricultural University, Hefei, 230036, China
| | - Xing Wang
- Xuzhou Institute of Agricultural Sciences of Xu-huai Region of Jiangsu, Xuzhou, 221131, China
| | - Yu Tian
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - De-Lin Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, China
| | - Ru-Jian Sun
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
- Hulun Buir Institution of Agricultural Sciences, Zhalantun, Inner Mongolia, 021000, China
| | - Zhang-Xiong Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Ze-Jun Xu
- Xuzhou Institute of Agricultural Sciences of Xu-huai Region of Jiangsu, Xuzhou, 221131, China
| | - Guang-Hui Fu
- Suzhou Academy of Agricultural Sciences, Suzhou, 234000, China
| | - Ya-Liang Ji
- Beijing Compass Biotechnology Co. Ltd, Beijing, 102206, China
| | - Qing-Shan Chen
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, 150030, China
| | - Ji-Qiang Liu
- Beijing Compass Biotechnology Co. Ltd, Beijing, 102206, China
| | - Li-Juan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI)/Key Laboratory of Crop Gene Resource and Germplasm Enhancement (MOA)/Key Laboratory of Soybean Biology (Beijing) (MOA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
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16
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Hinterberger V, Douchkov D, Lück S, Kale S, Mascher M, Stein N, Reif JC, Schulthess AW. Mining for New Sources of Resistance to Powdery Mildew in Genetic Resources of Winter Wheat. Front Plant Sci 2022; 13:836723. [PMID: 35300015 PMCID: PMC8922026 DOI: 10.3389/fpls.2022.836723] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/31/2022] [Indexed: 05/02/2023]
Abstract
Genetic pathogen control is an economical and sustainable alternative to the use of chemicals. In order to breed resistant varieties, information about potentially unused genetic resistance mechanisms is of high value. We phenotyped 8,316 genotypes of the winter wheat collection of the German Federal ex situ gene bank for Agricultural and Horticultural Crops, Germany, for resistance to powdery mildew (PM), Blumeria graminis f. sp. tritici, one of the most important biotrophic pathogens in wheat. To achieve this, we used a semi-automatic phenotyping facility to perform high-throughput detached leaf assays. This data set, combined with genotyping-by-sequencing (GBS) marker data, was used to perform a genome-wide association study (GWAS). Alleles of significantly associated markers were compared with SNP profiles of 171 widely grown wheat varieties in Germany to identify currently unexploited resistance conferring genes. We also used the Chinese Spring reference genome annotation and various domain prediction algorithms to perform a domain enrichment analysis and produced a list of candidate genes for further investigation. We identified 51 significantly associated regions. In most of these, the susceptible allele was fixed in the tested commonly grown wheat varieties. Eleven of these were located on chromosomes for which no resistance conferring genes have been previously reported. In addition to enrichment of leucine-rich repeats (LRR), we saw enrichment of several domain types so far not reported as relevant to PM resistance, thus, indicating potentially novel candidate genes for the disease resistance research and prebreeding in wheat.
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Affiliation(s)
| | - Dimitar Douchkov
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Stefanie Lück
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Sandip Kale
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
- Center for Integrated Breeding Research (CiBreed), Georg-August-University, Göttingen, Germany
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Albert W. Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
- *Correspondence: Albert W. Schulthess
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17
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Gonzalez MY, Zhao Y, Jiang Y, Stein N, Habekuss A, Reif JC, Schulthess AW. Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses. Theor Appl Genet 2021; 134:2181-2196. [PMID: 33768281 PMCID: PMC8263548 DOI: 10.1007/s00122-021-03815-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/10/2021] [Indexed: 05/04/2023]
Abstract
Genomic prediction with special weight of major genes is a valuable tool to populate bio-digital resource centers. Phenotypic information of crop genetic resources is a prerequisite for an informed selection that aims to broaden the genetic base of the elite breeding pools. We investigated the potential of genomic prediction based on historical screening data of plant responses against the Barley yellow mosaic viruses for populating the bio-digital resource center of barley. Our study includes dense marker data for 3838 accessions of winter barley, and historical screening data of 1751 accessions for Barley yellow mosaic virus (BaYMV) and of 1771 accessions for Barley mild mosaic virus (BaMMV). Linear mixed models were fitted by considering combinations for the effects of genotypes, years, and locations. The best linear unbiased estimations displayed a broad spectrum of plant responses against BaYMV and BaMMV. Prediction abilities, computed as correlations between predictions and observed phenotypes of accessions, were low for the marker-assisted selection approach amounting to 0.42. In contrast, prediction abilities of genomic best linear unbiased predictions were high, with values of 0.62 for BaYMV and 0.64 for BaMMV. Prediction abilities of genomic prediction were improved by up to ~ 5% using W-BLUP, in which more weight is given to markers with significant major effects found by association mapping. Our results outline the utility of historical screening data and W-BLUP model to predict the performance of the non-phenotyped individuals in genebank collections. The presented strategy can be considered as part of the different approaches used in genebank genomics to valorize genetic resources for their usage in disease resistance breeding and research.
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Affiliation(s)
- Maria Y Gonzalez
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
- Department of Crop Sciences, Center for Integrated Breeding Research (CiBreed), Georg-August-University, Göttingen, Germany
| | - Antje Habekuss
- Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
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18
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Schneider J, Berkner MO, Philipp N, Schulthess AW, Reif JC. Assessing the Suitability of Elite Lines for Hybrid Seed Production and as Testers in Wide Crosses With Wheat Genetic Resources. Front Plant Sci 2021; 12:689825. [PMID: 34194460 PMCID: PMC8236896 DOI: 10.3389/fpls.2021.689825] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/18/2021] [Indexed: 06/13/2023]
Abstract
The use of genetic resources in breeding is considered critical to ensure future selection gain, but the absence of important adaptation genes often masks the breeding value of genetic resources for grain yield. Testing genetic resources in a hybrid background has been proposed as a solution to obtain unbiased estimates of breeding values for grain yield. In our study, we evaluated the suitability of European wheat elite lines for implementing this hybrid strategy, focusing on maximizing seed yield in hybrid production and reducing masking effects due to susceptibility to lodging, yellow rust, and leaf rust of genetic resources. Over a 3-year period, 63 wheat elite female lines were crossed with eight male plant genetic resources in a multi-environment field experiment to evaluate seed yield on the female side. Then, the resulting hybrids and their parents were tested for plant height, lodging, and susceptibility to yellow rust and leaf rust in a further field experiment at multiple locations. We found that seed yield was strongly influenced by the elite wheat line choice in addition to environment and observed substantial differences among elite tester lines in their ability to reduce susceptibility to lodging, yellow rust, and leaf rust when the hybrid strategy was implemented. Consequently, breeders can significantly increase the amount of hybrid seed produced in wide crosses through appropriate tester choice and adapt genetic resources of wheat with the hybrid strategy to the modern cropping system.
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19
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Sinha P, Singh VK, Bohra A, Kumar A, Reif JC, Varshney RK. Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits. Theor Appl Genet 2021; 134:1829-1843. [PMID: 34014373 PMCID: PMC8205890 DOI: 10.1007/s00122-021-03847-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/29/2021] [Indexed: 05/03/2023]
Abstract
KEY MESSAGE Integrating genomics technologies and breeding methods to tweak core parameters of the breeder's equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers' fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder's equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder's equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits.
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Affiliation(s)
- Pallavi Sinha
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
- International Rice Research Institute (IRRI), IRRI South Asia Hub, ICRISAT, Hyderabad, India
| | - Vikas K Singh
- International Rice Research Institute (IRRI), IRRI South Asia Hub, ICRISAT, Hyderabad, India
| | - Abhishek Bohra
- ICAR- Indian Institute of Pulses Research (IIPR), Kanpur, India
| | - Arvind Kumar
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, India.
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University, Murdoch, WA, Australia.
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20
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Zhao Y, Thorwarth P, Jiang Y, Philipp N, Schulthess AW, Gils M, Boeven PHG, Longin CFH, Schacht J, Ebmeyer E, Korzun V, Mirdita V, Dörnte J, Avenhaus U, Horbach R, Cöster H, Holzapfel J, Ramgraber L, Kühnle S, Varenne P, Starke A, Schürmann F, Beier S, Scholz U, Liu F, Schmidt RH, Reif JC. Unlocking big data doubled the accuracy in predicting the grain yield in hybrid wheat. Sci Adv 2021; 7:7/24/eabf9106. [PMID: 34117061 PMCID: PMC8195483 DOI: 10.1126/sciadv.abf9106] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 04/28/2021] [Indexed: 05/07/2023]
Abstract
The potential of big data to support businesses has been demonstrated in financial services, manufacturing, and telecommunications. Here, we report on efforts to enter a new data era in plant breeding by collecting genomic and phenotypic information from 12,858 wheat genotypes representing 6575 single-cross hybrids and 6283 inbred lines that were evaluated in six experimental series for yield in field trials encompassing ~125,000 plots. Integrating data resulted in twofold higher prediction ability compared with cases in which hybrid performance was predicted across individual experimental series. Our results suggest that combining data across breeding programs is a particularly appropriate strategy to exploit the potential of big data for predictive plant breeding. This paradigm shift can contribute to increasing yield and resilience, which is needed to feed the growing world population.
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Affiliation(s)
- Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Patrick Thorwarth
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Norman Philipp
- Syngenta Seeds GmbH, Kroppenstedterstr. 4, 39398 Hadmersleben, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Mario Gils
- Nordsaat Saatzucht GmbH, , Böhnshauserstr. 1, 38895 Langenstein, Germany
| | | | - C Friedrich H Longin
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | | | - Erhard Ebmeyer
- KWS LOCHOW GmbH, Ferdinand-von-Lochow-Str. 5, 29303 Bergen, Germany
| | - Viktor Korzun
- KWS SAAT SE & Co. KGaA, Grimsehlstr. 31, 37574 Einbeck, Germany
- Federal State Budgetary Institution of Science Federal Research Center, "Kazan Scientific Center of Russian Academy of Sciences," ul. Lobachevskogo, 2/31, Kazan, 420111 Tatarstan, Russian Federation
| | - Vilson Mirdita
- BASF Agricultural Solutions Seed GmbH, OT Gatersleben, Am Schwabeplan 8, 06466 Seeland, Germany
| | - Jost Dörnte
- Deutsche Saatveredelung AG, Leutewitz 26, 01665 Käbschütztal, Germany
| | - Ulrike Avenhaus
- W. von Borries-Eckendorf GmbH & Co. KG, Hovedisserstr. 92, 33818 Leopoldshöhe, Germany
| | - Ralf Horbach
- Saatzucht Bauer GmbH & Co. KG, Hofmarkstr.1, 93083 Niederträubling, Germany
| | | | - Josef Holzapfel
- Secobra Saatzucht GmbH, Feldkirchen 3, 85368 Moosburg, Germany
| | - Ludwig Ramgraber
- Saatzucht Josef Breun GmbH & Co. KG, Amselweg 1, 91074 Herzogenaurach, Germany
| | - Simon Kühnle
- Pflanzenzucht Oberlimpurg, Oberlimpurg 2, 74523 Schwäbisch Hall, Germany
| | - Pierrick Varenne
- Limagrain Europe, Ferme de l'Etang BP3, 77390 Verneuil l'Etang, France
| | - Anne Starke
- Limagrain GmbH, Salderstr. 4, 31226 Peine-Rosenthal, Germany
| | | | - Sebastian Beier
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Fang Liu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Renate H Schmidt
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany.
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21
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Zhang J, Liu F, Reif JC, Jiang Y. On the use of GBLUP and its extension for GWAS with additive and epistatic effects. G3 (Bethesda) 2021; 11:6237487. [PMID: 33871030 PMCID: PMC8495923 DOI: 10.1093/g3journal/jkab122] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 04/04/2021] [Indexed: 11/29/2022]
Abstract
Genomic best linear unbiased prediction (GBLUP) is the most widely used model for genome-wide predictions. Interestingly, it is also possible to perform genome-wide association studies (GWAS) based on GBLUP. Although the estimated marker effects in GBLUP are shrunken and the conventional test based on such effects has low power, it was observed that a modified test statistic can be produced and the result of test was identical to a standard GWAS model. Later, a mathematical proof was given for the special case that there is no fixed covariate in GBLUP. Since then, the new approach has been called “GWAS by GBLUP”. Nevertheless, covariates such as environmental and subpopulation effects are very common in GBLUP. Thus, it is necessary to confirm the equivalence in the general case. Recently, the concept was generalized to GWAS for epistatic effects and the new approach was termed rapid epistatic mixed-model association analysis (REMMA) because it greatly improved the computational efficiency. However, the relationship between REMMA and the standard GWAS model has not been investigated. In this study, we first provided a general mathematical proof of the equivalence between “GWAS by GBLUP” and the standard GWAS model for additive effects. Then, we compared REMMA with the standard GWAS model for epistatic effects by a theoretical investigation and by empirical data analyses. We hypothesized that the similarity of the two models is influenced by the relative contribution of additive and epistatic effects to the phenotypic variance, which was verified by empirical and simulation studies.
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Affiliation(s)
- Jie Zhang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Stadt Seeland, Germany
| | - Fang Liu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Stadt Seeland, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Stadt Seeland, Germany
| | - Yong Jiang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Stadt Seeland, Germany
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22
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Muqaddasi QH, Kamal R, Mirdita V, Rodemann B, Ganal MW, Reif JC, Röder MS. Genome-Wide Association Studies and Prediction of Tan Spot ( Pyrenophora tritici-repentis) Infection in European Winter Wheat via Different Marker Platforms. Genes (Basel) 2021; 12:genes12040490. [PMID: 33801723 PMCID: PMC8103242 DOI: 10.3390/genes12040490] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/17/2021] [Accepted: 03/25/2021] [Indexed: 11/22/2022] Open
Abstract
Tan spot, caused by the fungus Pyrenophoratritici-repentis (Ptr), is a severe foliar disease of wheat (Triticumaestivum L.). Improving genetic resistance is a durable strategy to reduce Ptr-related losses. Here, we dissected Ptr-infection’s genetic basis in 372 European wheat varieties via simple sequence repeats (SSRs) plus 35k and 90k single nucleotide polymorphism (SNP) marker platforms. In our phenotypic data analyses, Ptr infection showed a significant genotypic variance and a significant negative correlation with plant height. Genome-wide association studies revealed a highly quantitative nature of Ptr infection and identified two quantitative trait loci (QTL), viz., QTs.ipk-7A and QTs.ipk-7B, which imparted 21.23 and 5.84% of the genotypic variance, respectively. Besides, the Rht-D1 gene showed a strong allelic influence on the infection scores. Due to the complex genetic nature of the Ptr infection, the potential of genome-wide prediction (GP) was assessed via three different genetic models on individual and combined marker platforms. The GP results indicated that the marker density and marker platforms do not considerably impact prediction accuracy (~40–42%) and that higher-order epistatic interactions may not be highly pervasive. Our results provide a further understanding of Ptr-infection’s genetic nature, serve as a resource for marker-assisted breeding, and highlight the potential of genome-wide selection for improved Ptr resistance.
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Affiliation(s)
- Quddoos H. Muqaddasi
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Stadt Seeland OT Gatersleben, Germany; (R.K.); (J.C.R.); (M.S.R.)
- European Wheat Breeding Center, BASF Agricultural Solutions GmbH, Am Schwabeplan 8, D-06466 Stadt Seeland OT Gatersleben, Germany;
- Correspondence:
| | - Roop Kamal
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Stadt Seeland OT Gatersleben, Germany; (R.K.); (J.C.R.); (M.S.R.)
| | - Vilson Mirdita
- European Wheat Breeding Center, BASF Agricultural Solutions GmbH, Am Schwabeplan 8, D-06466 Stadt Seeland OT Gatersleben, Germany;
| | - Bernd Rodemann
- Julius-Kühn-Institute (JKI), D-38104 Braunschweig, Germany;
| | - Martin W. Ganal
- TraitGenetics GmbH, Am Schwabeplan 1b, D-06466 Stadt Seeland OT Gatersleben, Germany;
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Stadt Seeland OT Gatersleben, Germany; (R.K.); (J.C.R.); (M.S.R.)
| | - Marion S. Röder
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, D-06466 Stadt Seeland OT Gatersleben, Germany; (R.K.); (J.C.R.); (M.S.R.)
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23
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Li D, Zhou Z, Lu X, Jiang Y, Li G, Li J, Wang H, Chen S, Li X, Würschum T, Reif JC, Xu S, Li M, Liu W. Genetic Dissection of Hybrid Performance and Heterosis for Yield-Related Traits in Maize. Front Plant Sci 2021; 12:774478. [PMID: 34917109 PMCID: PMC8670227 DOI: 10.3389/fpls.2021.774478] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/01/2021] [Indexed: 05/14/2023]
Abstract
Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.
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Affiliation(s)
- Dongdong Li
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Zhiqiang Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaohuan Lu
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Stadt Seeland, Germany
| | - Guoliang Li
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Junhui Li
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Haoying Wang
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Shaojiang Chen
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
| | - Xinhai Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tobias Würschum
- Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Stadt Seeland, Germany
| | - Shizhong Xu
- Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA, United States
- *Correspondence: Wenxin Liu,
| | - Mingshun Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Mingshun Li,
| | - Wenxin Liu
- Key Laboratory of Crop Heterosis and Utilization, The Ministry of Education/Key Laboratory of Crop Genetic Improvement, Beijing Municipality/National Maize Improvement Center/College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
- Shizhong Xu,
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24
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Liu F, Jiang Y, Zhao Y, Schulthess AW, Reif JC. Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat. J Exp Bot 2020; 71:6958-6968. [PMID: 32827041 DOI: 10.1093/jxb/eraa387] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 08/17/2020] [Indexed: 05/12/2023]
Abstract
Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs often explained only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1574 hybrids and characterized with 626 245 high-quality SNPs. In total, 2408 and 1 139 828 significant associations were detected in the mapping population by using SNP-based and FH-based GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, Lr22a and Lr34-B, while FH-based GWAS detected associations not only on these genes but also on two additional genes, Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, the use of detected associations from SNP-based and FH-based GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-based GWAS is not only more powerful for detecting associations, but also improves the accuracy of marker-assisted selection compared with the SNP-based approach.
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Affiliation(s)
- Fang Liu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Albert W Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
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Abstract
The genomic relationship matrix plays a key role in the analysis of genetic diversity, genomic prediction, and genome-wide association studies. The epistatic genomic relationship matrix is a natural generalization of the classic genomic relationship matrix in the sense that it implicitly models the epistatic effects among all markers. Calculating the exact form of the epistatic relationship matrix requires high computational load, and is hence not feasible when the number of markers is large, or when high-degree of epistasis is in consideration. Currently, many studies use the Hadamard product of the classic genomic relationship matrix as an approximation. However, the quality of the approximation is difficult to investigate in the strict mathematical sense. In this study, we derived iterative formulas for the precise form of the epistatic genomic relationship matrix for arbitrary degree of epistasis including both additive and dominance interactions. The key to our theoretical results is the observation of an interesting link between the elements in the genomic relationship matrix and symmetric polynomials, which motivated the application of the corresponding mathematical theory. Based on the iterative formulas, efficient recursive algorithms were implemented. Compared with the approximation by the Hadamard product, our algorithms provided a complete solution to the problem of calculating the exact epistatic genomic relationship matrix. As an application, we showed that our new algorithms easily relieved the computational burden in a previous study on the approximation behavior of two limit models.
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Affiliation(s)
- Yong Jiang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben 06466, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben 06466, Germany
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26
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Pogoda M, Liu F, Douchkov D, Djamei A, Reif JC, Schweizer P, Schulthess AW. Identification of novel genetic factors underlying the host-pathogen interaction between barley (Hordeum vulgare L.) and powdery mildew (Blumeria graminis f. sp. hordei). PLoS One 2020; 15:e0235565. [PMID: 32614894 PMCID: PMC7332009 DOI: 10.1371/journal.pone.0235565] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 06/18/2020] [Indexed: 12/12/2022] Open
Abstract
Powdery mildew is an important foliar disease of barley (Hordeum vulgare L.) caused by the biotrophic fungus Blumeria graminis f. sp. hordei (Bgh). The understanding of the resistance mechanism is essential for future resistance breeding. In particular, the identification of race-nonspecific resistance genes is important because of their regarded durability and broad-spectrum activity. We assessed the severity of powdery mildew infection on detached seedling leaves of 267 barley accessions using two poly-virulent isolates and performed a genome-wide association study exploiting 201 of these accessions. Two-hundred and fourteen markers, located on six barley chromosomes are associated with potential race-nonspecific Bgh resistance or susceptibility. Initial steps for the functional validation of four promising candidates were performed based on phenotype and transcription data. Specific candidate alleles were analyzed via transient gene silencing as well as transient overexpression. Microarray data of the four selected candidates indicate differential regulation of the transcription in response to Bgh infection. Based on our results, all four candidate genes seem to be involved in the responses to powdery mildew attack. In particular, the transient overexpression of specific alleles of two candidate genes, a potential arabinogalactan protein and the barley homolog of Arabidopsis thaliana’s Light-Response Bric-a-Brac/-Tramtrack/-Broad Complex/-POxvirus and Zinc finger (AtLRB1) or AtLRB2, were top candidates of novel powdery mildew susceptibility genes.
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Affiliation(s)
- Maria Pogoda
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Fang Liu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Dimitar Douchkov
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Armin Djamei
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Patrick Schweizer
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
| | - Albert W. Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany
- * E-mail:
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27
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Papoutsoglou EA, Faria D, Arend D, Arnaud E, Athanasiadis IN, Chaves I, Coppens F, Cornut G, Costa BV, Ćwiek-Kupczyńska H, Droesbeke B, Finkers R, Gruden K, Junker A, King GJ, Krajewski P, Lange M, Laporte MA, Michotey C, Oppermann M, Ostler R, Poorter H, Ramı Rez-Gonzalez R, Ramšak Ž, Reif JC, Rocca-Serra P, Sansone SA, Scholz U, Tardieu F, Uauy C, Usadel B, Visser RGF, Weise S, Kersey PJ, Miguel CM, Adam-Blondon AF, Pommier C. Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytol 2020. [PMID: 32171029 DOI: 10.15454/1yxvzv] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.
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Affiliation(s)
- Evangelia A Papoutsoglou
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Daniel Faria
- BioData.pt, Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal
- INESC-ID, 1000-029, Lisboa, Portugal
| | - Daniel Arend
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Elizabeth Arnaud
- Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397, France
| | - Ioannis N Athanasiadis
- Geo-Information Science and Remote Sensing Laboratory, Wageningen University, Droevendaalsesteeg 3, Wageningen, 6708PB, the Netherlands
| | - Inês Chaves
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- Instituto de Biologia Experimental e Tecnológica (iBET), 2780-157, Oeiras, Portugal
| | - Frederik Coppens
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, 9052, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, 9052, Belgium
| | | | - Bruno V Costa
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
| | - Hanna Ćwiek-Kupczyńska
- Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479, Poznań, Poland
| | - Bert Droesbeke
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, 9052, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, 9052, Belgium
| | - Richard Finkers
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Kristina Gruden
- Department of Biotechnology and Systems Biology, National Institute of Biology, SI1000, Ljubljana, Slovenia
| | - Astrid Junker
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Graham J King
- Southern Cross Plant Science, Southern Cross University, Lismore, NSW 2577, Australia
| | - Paweł Krajewski
- Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479, Poznań, Poland
| | - Matthias Lange
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Marie-Angélique Laporte
- Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397, France
| | - Célia Michotey
- Université Paris-Saclay, INRAE, URGI, Versailles, 78026, France
| | - Markus Oppermann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Richard Ostler
- Computational and Analytical Sciences, Rothamsted Research, Harpenden, AL5 2JQ, UK
| | - Hendrik Poorter
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
- Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia
| | | | - Živa Ramšak
- Department of Biotechnology and Systems Biology, National Institute of Biology, SI1000, Ljubljana, Slovenia
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - François Tardieu
- INRA, Laboratoire d'Ecophysiologie des Plantes sous Stress Environnementaux, UMR759, Montpellier, 34060, France
| | - Cristobal Uauy
- Department of Crop Genetics, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UH, UK
| | - Björn Usadel
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
- Institute for Biology I, BioSC, RWTH Aachen University, Worringer Weg 3, 52074, Aachen, Germany
| | - Richard G F Visser
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Stephan Weise
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | | | - Célia M Miguel
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
| | | | - Cyril Pommier
- Université Paris-Saclay, INRAE, URGI, Versailles, 78026, France
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28
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Beukert U, Liu G, Thorwarth P, Boeven PHG, Longin CFH, Zhao Y, Ganal M, Serfling A, Ordon F, Reif JC. The potential of hybrid breeding to enhance leaf rust and stripe rust resistance in wheat. Theor Appl Genet 2020; 133:2171-2181. [PMID: 32281003 PMCID: PMC7311497 DOI: 10.1007/s00122-020-03588-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 03/31/2020] [Indexed: 05/20/2023]
Abstract
KEY MESSAGE Hybrid wheat breeding is a promising strategy to improve the level of leaf rust and stripe rust resistance in wheat. Leaf rust and stripe rust belong to the most important fungal diseases in wheat production. Due to a dynamic development of new virulent races, epidemics appear in high frequency and causes significant losses in grain yield and quality. Therefore, research is needed to develop strategies to breed wheat varieties carrying highly efficient resistances. Stacking of dominant resistance genes through hybrid breeding is such an approach. Within this study, we investigated the genetic architecture of leaf rust and stripe rust resistance of 1750 wheat hybrids and their 230 parental lines using a genome-wide association study. We observed on average a lower rust susceptibility for hybrids in comparison to their parental inbred lines and some hybrids outperformed their better parent with up to 56%. Marker-trait associations were identified on chromosome 3D and 4A for leaf rust and on chromosome 2A, 2B, and 6A for stripe rust resistance by using a genome-wide association study with a Bonferroni-corrected threshold of P < 0.10. Detected loci on chromosomes 4A and 2A were located within previously reported genomic regions affecting leaf rust and stripe rust resistance, respectively. The degree of dominance was for most associations favorable in the direction of improved resistance. Thus, resistance can be increased in hybrid wheat breeding by fixing complementary leaf rust and stripe rust resistance genes with desired dominance effects in opposite parental pools.
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Affiliation(s)
- Ulrike Beukert
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI), Erwin-Baur-Straße 27, 06484, Quedlinburg, Germany
| | - Guozheng Liu
- BASF Agricultural Solutions Belgium NV, Technologiepark 101, 9052, Zwijnaarde, Ghent, Belgium
| | - Patrick Thorwarth
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstraße 21, 70593, Stuttgart, Germany
| | - Philipp H G Boeven
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstraße 21, 70593, Stuttgart, Germany
| | - C Friedrich H Longin
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstraße 21, 70593, Stuttgart, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, 06466, Stadt Seeland OT Gatersleben, Germany
| | - Martin Ganal
- TraitGenetics GmbH, Am Schwabeplan 1b, 06466, Stadt Seeland, OT Gatersleben, Germany
| | - Albrecht Serfling
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI), Erwin-Baur-Straße 27, 06484, Quedlinburg, Germany
| | - Frank Ordon
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI), Erwin-Baur-Straße 27, 06484, Quedlinburg, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstraße 3, 06466, Stadt Seeland OT Gatersleben, Germany.
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29
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Papoutsoglou EA, Faria D, Arend D, Arnaud E, Athanasiadis IN, Chaves I, Coppens F, Cornut G, Costa BV, Ćwiek‐Kupczyńska H, Droesbeke B, Finkers R, Gruden K, Junker A, King GJ, Krajewski P, Lange M, Laporte M, Michotey C, Oppermann M, Ostler R, Poorter H, Ramírez‐Gonzalez R, Ramšak Ž, Reif JC, Rocca‐Serra P, Sansone S, Scholz U, Tardieu F, Uauy C, Usadel B, Visser RGF, Weise S, Kersey PJ, Miguel CM, Adam‐Blondon A, Pommier C. Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytol 2020; 227:260-273. [PMID: 32171029 PMCID: PMC7317793 DOI: 10.1111/nph.16544] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 02/24/2020] [Indexed: 05/21/2023]
Abstract
Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.
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30
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Papoutsoglou EA, Faria D, Arend D, Arnaud E, Athanasiadis IN, Chaves I, Coppens F, Cornut G, Costa BV, Ćwiek-Kupczyńska H, Droesbeke B, Finkers R, Gruden K, Junker A, King GJ, Krajewski P, Lange M, Laporte MA, Michotey C, Oppermann M, Ostler R, Poorter H, Ramı Rez-Gonzalez R, Ramšak Ž, Reif JC, Rocca-Serra P, Sansone SA, Scholz U, Tardieu F, Uauy C, Usadel B, Visser RGF, Weise S, Kersey PJ, Miguel CM, Adam-Blondon AF, Pommier C. Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytol 2020. [PMID: 32171029 DOI: 10.15454/ah6u4a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.
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Affiliation(s)
- Evangelia A Papoutsoglou
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Daniel Faria
- BioData.pt, Instituto Gulbenkian de Ciência, 2780-156, Oeiras, Portugal
- INESC-ID, 1000-029, Lisboa, Portugal
| | - Daniel Arend
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Elizabeth Arnaud
- Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397, France
| | - Ioannis N Athanasiadis
- Geo-Information Science and Remote Sensing Laboratory, Wageningen University, Droevendaalsesteeg 3, Wageningen, 6708PB, the Netherlands
| | - Inês Chaves
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- Instituto de Biologia Experimental e Tecnológica (iBET), 2780-157, Oeiras, Portugal
| | - Frederik Coppens
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, 9052, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, 9052, Belgium
| | | | - Bruno V Costa
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
| | - Hanna Ćwiek-Kupczyńska
- Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479, Poznań, Poland
| | - Bert Droesbeke
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 71, Ghent, 9052, Belgium
- VIB Center for Plant Systems Biology, Technologiepark 71, Ghent, 9052, Belgium
| | - Richard Finkers
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Kristina Gruden
- Department of Biotechnology and Systems Biology, National Institute of Biology, SI1000, Ljubljana, Slovenia
| | - Astrid Junker
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Graham J King
- Southern Cross Plant Science, Southern Cross University, Lismore, NSW 2577, Australia
| | - Paweł Krajewski
- Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszyńska 34, 60-479, Poznań, Poland
| | - Matthias Lange
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Marie-Angélique Laporte
- Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397, France
| | - Célia Michotey
- Université Paris-Saclay, INRAE, URGI, Versailles, 78026, France
| | - Markus Oppermann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Richard Ostler
- Computational and Analytical Sciences, Rothamsted Research, Harpenden, AL5 2JQ, UK
| | - Hendrik Poorter
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
- Department of Biological Sciences, Macquarie University, North Ryde, NSW 2109, Australia
| | | | - Živa Ramšak
- Department of Biotechnology and Systems Biology, National Institute of Biology, SI1000, Ljubljana, Slovenia
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - Philippe Rocca-Serra
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, 7 Keble Road, Oxford, OX1 3QG, UK
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | - François Tardieu
- INRA, Laboratoire d'Ecophysiologie des Plantes sous Stress Environnementaux, UMR759, Montpellier, 34060, France
| | - Cristobal Uauy
- Department of Crop Genetics, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UH, UK
| | - Björn Usadel
- Plant Sciences (IBG-2), Forschungszentrum Jülich GmbH, D-52425, Jülich, Germany
- Institute for Biology I, BioSC, RWTH Aachen University, Worringer Weg 3, 52074, Aachen, Germany
| | - Richard G F Visser
- Plant Breeding, Wageningen University & Research, PO Box 386, Wageningen, 6700AJ, the Netherlands
| | - Stephan Weise
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466, Seeland, Germany
| | | | - Célia M Miguel
- Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa (ITQB NOVA) Avenida da República, 2780-157, Oeiras, Portugal
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, 1749-016, Portugal
| | | | - Cyril Pommier
- Université Paris-Saclay, INRAE, URGI, Versailles, 78026, France
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31
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Liu F, Zhao Y, Beier S, Jiang Y, Thorwarth P, H. Longin CF, Ganal M, Himmelbach A, Reif JC, Schulthess AW. Exome association analysis sheds light onto leaf rust (Puccinia triticina) resistance genes currently used in wheat breeding (Triticum aestivum L.). Plant Biotechnol J 2020; 18:1396-1408. [PMID: 31782598 PMCID: PMC7207002 DOI: 10.1111/pbi.13303] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/06/2019] [Accepted: 11/17/2019] [Indexed: 05/18/2023]
Abstract
Resistance breeding is crucial for a sustainable control of leaf rust (Puccinia triticina) in wheat (Triticum aestivum L.) while directly targeting functional variants is the Holy Grail for efficient marker-assisted selection and map-based cloning. We assessed the limits and prospects of exome association analysis for severity of leaf rust in a large hybrid wheat population of 1574 single-crosses plus their 133 parents. After imputation and quality control, exome sequencing revealed 202 875 single-nucleotide polymorphisms (SNPs) covering 19.7% of the high-confidence annotated gene space. We performed intensive data mining and found significant associations for 2171 SNPs corresponding to 50 different loci. Some of these associations mapped in the proximity of the already known resistance genes Lr21, Lr34-B, Lr1 and Lr10, while other associated genomic regions, such as those on chromosomes 1A and 3D, harboured several annotated genes putatively involved in resistance. Validation with an independent population helped to narrow down the list of putative resistance genes that should be targeted by fine-mapping. We expect that the proposed strategy of intensive data mining coupled with validation will significantly influence research in plant genetics and breeding.
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Affiliation(s)
- Fang Liu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Sebastian Beier
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Patrick Thorwarth
- State Plant Breeding InstituteUniversity of HohenheimStuttgartGermany
| | | | | | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
| | - Albert W. Schulthess
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK)Stadt SeelandGermany
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32
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Boeven PHG, Zhao Y, Thorwarth P, Liu F, Maurer HP, Gils M, Schachschneider R, Schacht J, Ebmeyer E, Kazman E, Mirdita V, Dörnte J, Kontowski S, Horbach R, Cöster H, Holzapfel J, Jacobi A, Ramgraber L, Reinbrecht C, Starck N, Varenne P, Starke A, Schürmann F, Ganal M, Polley A, Hartung J, Beier S, Scholz U, Longin CFH, Reif JC, Jiang Y, Würschum T. Negative dominance and dominance-by-dominance epistatic effects reduce grain-yield heterosis in wide crosses in wheat. Sci Adv 2020; 6:eaay4897. [PMID: 32582844 PMCID: PMC7292627 DOI: 10.1126/sciadv.aay4897] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Accepted: 04/22/2020] [Indexed: 05/21/2023]
Abstract
The genetics underlying heterosis, the difference in performance of crosses compared with midparents, is hypothesized to vary with relatedness between parents. We established a unique germplasm comprising three hybrid wheat sets differing in the degree of divergence between parents and devised a genetic distance measure giving weight to heterotic loci. Heterosis increased steadily with heterotic genetic distance for all 1903 hybrids. Midparent heterosis, however, was significantly lower in the hybrids including crosses between elite and exotic lines than in crosses among elite lines. The analysis of the genetic architecture of heterosis revealed this to be caused by a higher portion of negative dominance and dominance-by-dominance epistatic effects. Collectively, these results expand our understanding of heterosis in crops, an important pillar toward global food security.
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Affiliation(s)
- Philipp H. G. Boeven
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Patrick Thorwarth
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | - Fang Liu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Hans Peter Maurer
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | - Mario Gils
- Nordsaat Saatzucht GmbH, Böhnshauserstr. 1, 38895 Langenstein, Germany
| | | | | | - Erhard Ebmeyer
- KWS LOCHOW GmbH, Ferdinand-von-Lochow-Str. 5, 29303 Bergen, Germany
| | - Ebrahim Kazman
- Syngenta Seeds GmbH, Kroppenstedterstr. 4, 39398 Hadmersleben, Germany
| | - Vilson Mirdita
- BASF Agricultural SolutionsSeed GmbH, OT Gatersleben, Am Schwabeplan 8, 06466 Seeland
| | - Jost Dörnte
- Deutsche Saatveredelung AG, Leutewitz 26, 01665 Käbschütztal, Germany
| | - Stefan Kontowski
- W. von Borries-Eckendorf GmbH & Co. KG, Hovedisserstr. 92, 33818 Leopoldshöhe, Germany
| | - Ralf Horbach
- Saatzucht Bauer GmbH & Co. KG, Hofmarkstr.1, 93083 Niederträubling, Germany
| | | | - Josef Holzapfel
- Secobra Saatzucht GmbH, Feldkirchen 3, 85368 Moosburg, Germany
| | - Andreas Jacobi
- Strube Research GmbH & Co. KG, Hauptstr. 1, 38387 Söllingen, Germany
| | - Ludwig Ramgraber
- Saatzucht Josef Breun GmbH & Co. KG, Amselweg 1, 91074 Herzogenaurach, Germany
| | - Carsten Reinbrecht
- Saatzucht Streng-Engelen GmbH & Co. KG, Aspachhof 1, 97215 Uffenheim, Germany
| | - Norbert Starck
- Pflanzenzucht Oberlimpburg, Oberlimpurg 2, 74523 Schwäbisch Hall, Germany
| | - Pierrick Varenne
- Limagrain Europe, Ferme de l’Etang – BP3 -77390 Verneuil l’Etang, France
| | - Anne Starke
- Limagrain GmbH, Salderstr. 4, 31226 Peine-Rosenthal, Germany
| | - Friederike Schürmann
- W. von Borries-Eckendorf GmbH & Co. KG, Hovedisserstr. 92, 33818 Leopoldshöhe, Germany
| | | | | | - Jens Hartung
- Biostatistics Unit, Institute of Crop Science, Fruwirthstr. 23 University of Hohenheim, 70593 Stuttgart, Germany
| | - Sebastian Beier
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - C. Friedrich H. Longin
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
| | - Jochen C. Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Stadt Seeland, Germany
| | - Tobias Würschum
- State Plant Breeding Institute, University of Hohenheim, Fruwirthstr. 21, 70593 Stuttgart, Germany
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33
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Chu J, Zhao Y, Beier S, Schulthess AW, Stein N, Philipp N, Röder MS, Reif JC. Suitability of Single-Nucleotide Polymorphism Arrays Versus Genotyping-By-Sequencing for Genebank Genomics in Wheat. Front Plant Sci 2020; 11:42. [PMID: 32117381 PMCID: PMC7033508 DOI: 10.3389/fpls.2020.00042] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 01/13/2020] [Indexed: 05/20/2023]
Abstract
Genebank genomics promises to unlock valuable diversity for plant breeding but first, one key question is which marker system is most suitable to fingerprint entire genebank collections. Using wheat as model species, we tested for the presence of an ascertainment bias and investigated its impact on estimates of genetic diversity and prediction ability obtained using three marker platforms: simple sequence repeat (SSR), genotyping-by-sequencing (GBS), and array-based SNP markers. We used a panel of 378 winter wheat genotypes including 190 elite lines and 188 plant genetic resources (PGR), which were phenotyped in multi-environmental trials for grain yield and plant height. We observed an ascertainment bias for the array-based SNP markers, which led to an underestimation of the molecular diversity within the population of PGR. In contrast, the marker system played only a minor role for the overall picture of the population structure and precision of genome-wide predictions. Interestingly, we found that rare markers contributed substantially to the prediction ability. This combined with the expectation that valuable novel diversity is most likely rare suggests that markers with minor allele frequency deserve careful consideration in the design of a pre-breeding program.
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Affiliation(s)
- Jianting Chu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Sebastian Beier
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Albert W. Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Nils Stein
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Norman Philipp
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Marion S. Röder
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland, Germany
- Faculty of Sciences III - Agricultural and Nutritional Sciences, Earth Sciences and Computer Science, Martin-Luther-University Halle-Wittenberg, Halle/Saale, Germany
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34
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Jiang Y, Weise S, Graner A, Reif JC. Using Genome-Wide Predictions to Assess the Phenotypic Variation of a Barley ( Hordeum sp.) Gene Bank Collection for Important Agronomic Traits and Passport Information. Front Plant Sci 2020; 11:604781. [PMID: 33505414 PMCID: PMC7829250 DOI: 10.3389/fpls.2020.604781] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/14/2020] [Indexed: 05/10/2023]
Abstract
Genome-wide predictions are a powerful tool for predicting trait performance. Against this backdrop we aimed to evaluate the potential and limitations of genome-wide predictions to inform the barley collection of the Federal ex situ Genebank for Agricultural and Horticultural Crops with phenotypic data on complex traits including flowering time, plant height, thousand grain weight, as well as on growth habit and row type. We used previously published sequence data, providing information on 306,049 high-quality SNPs for 20,454 barley accessions. The prediction abilities of the two unordered categorical traits row type and growth type as well as the quantitative traits flowering time, plant height and thousand grain weight were investigated using different cross validation scenarios. Our results demonstrate that the unordered categorical traits can be predicted with high precision. In this way genome-wide prediction can be routinely deployed to extract information pertinent to the taxonomic status of gene bank accessions. In addition, the three quantitative traits were also predicted with high precision, thereby increasing the amount of information available for genotyped but not phenotyped accessions. Deeply phenotyped core collections, such as the barley 1,000 core set of the IPK Gatersleben, are a promising training population to calibrate genome-wide prediction models. Consequently, genome-wide predictions can substantially contribute to increase the attractiveness of gene bank collections and help evolve gene banks into bio-digital resource centers.
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35
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Beukert U, Thorwarth P, Zhao Y, Longin CFH, Serfling A, Ordon F, Reif JC. Comparing the Potential of Marker-Assisted Selection and Genomic Prediction for Improving Rust Resistance in Hybrid Wheat. Front Plant Sci 2020; 11:594113. [PMID: 33193553 PMCID: PMC7655876 DOI: 10.3389/fpls.2020.594113] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 10/05/2020] [Indexed: 05/20/2023]
Abstract
Improving leaf rust and stripe rust resistance is a central goal in wheat breeding. The objectives of this study were to (1) elucidate the genetic basis of leaf rust and stripe rust resistance in a hybrid wheat population, (2) compare the findings using a previously published hybrid wheat data set, and (3) contrast the prediction accuracy with those of genome-wide prediction. The hybrid wheat population included 1,744 single crosses from 236 parental lines. The genotypes were fingerprinted using a 15k SNP array and evaluated for leaf rust and stripe rust resistance in multi-location field trials. We observed a high congruency of putative quantitative trait loci (QTL) for leaf rust resistance between both populations. This was not the case for stripe rust resistance. Accordingly, prediction accuracy of the detected QTL was moderate for leaf rust but low for stripe rust resistance. Genome-wide selection increased the prediction accuracy slightly for stripe rust albeit at a low level but not for leaf rust. Thus, our findings suggest that marker-assisted selection seems to be a robust and efficient tool to improve leaf rust resistance in European wheat hybrids.
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Affiliation(s)
- Ulrike Beukert
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI) – Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
| | - Patrick Thorwarth
- State Plant Breeding Institute, University of Hohenheim, Stuttgart, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | | | - Albrecht Serfling
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI) – Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
| | - Frank Ordon
- Institute for Resistance Research and Stress Tolerance, Julius Kuehn-Institute (JKI) – Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
- *Correspondence: Jochen C. Reif,
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36
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Tian Y, Liu B, Shi X, Reif JC, Guan R, Li YH, Qiu LJ. Deep genotyping of the gene GmSNAP facilitates pyramiding resistance to cyst nematode in soybean. ACTA ACUST UNITED AC 2019. [DOI: 10.1016/j.cj.2019.04.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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37
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Philipp N, Weise S, Oppermann M, Börner A, Keilwagen J, Kilian B, Arend D, Zhao Y, Graner A, Reif JC, Schulthess AW. Historical phenotypic data from seven decades of seed regeneration in a wheat ex situ collection. Sci Data 2019; 6:137. [PMID: 31358775 PMCID: PMC6662709 DOI: 10.1038/s41597-019-0146-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 07/08/2019] [Indexed: 11/16/2022] Open
Abstract
Genebanks are valuable sources of genetic diversity, which can help to cope with future problems of global food security caused by a continuously growing population, stagnating yields and climate change. However, the scarcity of phenotypic and genotypic characterization of genebank accessions severely restricts their use in plant breeding. To warrant the seed integrity of individual accessions during periodical regeneration cycles in the field phenotypic characterizations are performed. This study provides non-orthogonal historical data of 12,754 spring and winter wheat accessions characterized for flowering time, plant height, and thousand grain weight during 70 years of seed regeneration at the German genebank. Supported by historical weather observations outliers were removed following a previously described quality assessment pipeline. In this way, ready-to-use processed phenotypic data across regeneration years were generated and further validated. We encourage international and national genebanks to increase their efforts to transform into bio-digital resource centers. A first important step could consist in unlocking their historical data treasures that allows an educated choice of accessions by scientists and breeders.
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Affiliation(s)
- Norman Philipp
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Stephan Weise
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Markus Oppermann
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Andreas Börner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Jens Keilwagen
- Institute for Biosafety in Plant Biotechnology, Julius Kühn-Institut (JKI) - Federal Research Centre for Cultivated Plants, 06484, Quedlinburg, Germany
| | - Benjamin Kilian
- Global Crop Diversity Trust, Platz der Vereinten Nationen 7, 53113, Bonn, Germany
| | - Daniel Arend
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Andreas Graner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany.
| | - Albert W Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Seeland/OT, Gatersleben, Germany
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Rembe M, Zhao Y, Jiang Y, Reif JC. Reciprocal recurrent genomic selection: an attractive tool to leverage hybrid wheat breeding. Theor Appl Genet 2019; 132:687-698. [PMID: 30488192 DOI: 10.1007/s00122-018-3244-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 11/16/2018] [Indexed: 06/09/2023]
Abstract
Using a two-part breeding strategy based on a population improvement and a product development component can leverage hybrid wheat breeding. Despite the technological advance of methods to facilitate hybrid breeding in self-pollinating crops, line breeding is still the dominating breeding strategy. This is likely due to a higher long-term selection gain in line compared to hybrid breeding. In this respect, recent studies on two-part strategies splitting the breeding program into a population improvement and a product development component could mark a trend reversal. Here, an overview of experimental and simulation-based studies exploring the possibilities to integrate genome-wide prediction into recurrent selection is given. Furthermore, possibilities to make use of recurrent selection for inter-population improvement are discussed. Current findings of simulation studies and quantitative genetic considerations suggest that long-term selection gain of hybrid breeding can be increased by implementing a two-part selection strategy based on reciprocal recurrent genomic selection. This would strengthen the competitiveness of hybrid versus line breeding facilitating to develop outstanding hybrid varieties also for self-pollinating plants such as wheat.
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Affiliation(s)
- Maximilian Rembe
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yong Jiang
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
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39
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Mérida-García R, Liu G, He S, Gonzalez-Dugo V, Dorado G, Gálvez S, Solís I, Zarco-Tejada PJ, Reif JC, Hernandez P. Genetic dissection of agronomic and quality traits based on association mapping and genomic selection approaches in durum wheat grown in Southern Spain. PLoS One 2019; 14:e0211718. [PMID: 30811415 PMCID: PMC6392243 DOI: 10.1371/journal.pone.0211718] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Accepted: 01/19/2019] [Indexed: 01/12/2023] Open
Abstract
Climatic conditions affect the growth, development and final crop production. As wheat is of paramount importance as a staple crop in the human diet, there is a growing need to study its abiotic stress adaptation through the performance of key breeding traits. New and complementary approaches, such as genome-wide association studies (GWAS) and genomic selection (GS), are used for the dissection of different agronomic traits. The present study focused on the dissection of agronomic and quality traits of interest (initial agronomic score, yield, gluten index, sedimentation index, specific weight, whole grain protein and yellow colour) assessed in a panel of 179 durum wheat lines (Triticum durum Desf.), grown under rainfed conditions in different Mediterranean environments in Southern Spain (Andalusia). The findings show a total of 37 marker-trait associations (MTAs) which affect phenotype expression for three quality traits (specific weight, gluten and sedimentation indexes). MTAs could be mapped on the A and B durum wheat subgenomes (on chromosomes 1A, 1B, 2A, 2B and 3A) through the recently available bread wheat reference assembly (IWGSC RefSeqv1). Two of the MTAs found for quality traits (gluten index and SDS) corresponded to the known Glu-B1 and Glu-A1 loci, for which candidate genes corresponding to high molecular weight glutenin subunits could be located. The GS prediction ability values obtained from the breeding materials analyzed showed promising results for traits as grain protein content, sedimentation and gluten indexes, which can be used in plant breeding programs.
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Affiliation(s)
- Rosa Mérida-García
- Instituto de Agricultura Sostenible (IAS) Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, Córdoba, Spain
| | - Guozheng Liu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland, Germany
| | - Sang He
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland, Germany
| | - Victoria Gonzalez-Dugo
- Instituto de Agricultura Sostenible (IAS) Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, Córdoba, Spain
| | - Gabriel Dorado
- Departamento de Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba, Córdoba, Spain
| | - Sergio Gálvez
- Universidad de Málaga, Andalucía Tech, ETSI Informática, Campus de Teatinos s/n, Málaga, Spain
| | - Ignacio Solís
- ETSIA (University of Seville), Ctra de Utrera km1, Seville, Spain
| | - Pablo J. Zarco-Tejada
- Instituto de Agricultura Sostenible (IAS) Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, Córdoba, Spain
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, Stadt Seeland, Germany
| | - Pilar Hernandez
- Instituto de Agricultura Sostenible (IAS) Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, Córdoba, Spain
- * E-mail:
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40
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Gonzalez MY, Weise S, Zhao Y, Philipp N, Arend D, Börner A, Oppermann M, Graner A, Reif JC, Schulthess AW. Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection. Sci Data 2018; 5:180278. [PMID: 30512010 PMCID: PMC6278694 DOI: 10.1038/sdata.2018.278] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 10/15/2018] [Indexed: 01/21/2023] Open
Abstract
The scarce knowledge on phenotypic characterization restricts the usage of genetic diversity of plant genetic resources in research and breeding. We describe original and ready-to-use processed data for approximately 60% of ~22,000 barley accessions hosted at the Federal ex situ Genebank for Agricultural and Horticultural Plant Species. The dataset gathers records for three traits with agronomic relevance: flowering time, plant height and thousand grain weight. This information was collected for seven decades for winter and spring barley during the seed regeneration routine. The curated data represent a source for research on genetics and genomics of adaptive and yield related traits in cereals due to the importance of barley as model organism. This data could be used to predict the performance of non-phenotyped individuals in other collections through genomic prediction. Moreover, the dataset empowers the utilization of phenotypic diversity of genetic resources for crop improvement.
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Affiliation(s)
- Maria Y Gonzalez
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Stephan Weise
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Norman Philipp
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Daniel Arend
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Andreas Börner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Markus Oppermann
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Andreas Graner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
| | - Albert W Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466, Gatersleben, Germany
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41
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Guo Z, Liu G, Röder MS, Reif JC, Ganal MW, Schnurbusch T. Genome-wide association analyses of plant growth traits during the stem elongation phase in wheat. Plant Biotechnol J 2018; 16:2042-2052. [PMID: 29723916 PMCID: PMC6230955 DOI: 10.1111/pbi.12937] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Revised: 02/17/2018] [Accepted: 03/31/2018] [Indexed: 05/18/2023]
Abstract
One of the primary objectives of wheat breeding was to increase grain yield. Floral abortion during the stem elongation phase (SEP) leads to a loss of more than 50% of the grain number potential. In this study, we quantified 75 plant growth-associated traits at seven stages during the SEP and mapped 15 696 single nucleotide polymorphism (SNP) markers in 210 accessions of wheat (Triticum aestivum). Our genomewide association study identified trait-associated SNPs that are shared among various stages of the SEP, as well as SNPs that are shared between plant growth traits and grain yield in the field. The genomic selection analysis shows variation among the prediction abilities of various traits and stages. Furthermore, we found that the allelic variants of Ppd-D1 (chromosome 2D) and Rht-D1 (chromosome 4D) loci affect some plant growth traits (e.g. leaf area and spike length). These results have identified a narrow time window within the SEP in which plant growth traits can be manipulated to alter grain yield. This suggests that there may be multiple ways to regulate plant growth during the SEP, to ultimately influence grain number in wheat.
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Affiliation(s)
- Zifeng Guo
- Independent HEISENBERG Research Group Plant ArchitectureLeibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
| | - Guozheng Liu
- Research Group Quantitative GeneticsDepartment of Breeding ResearchLeibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
| | - Marion S. Röder
- Research Group Gene and Genome MappingDepartment of Breeding ResearchLeibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
| | - Jochen C. Reif
- Research Group Quantitative GeneticsDepartment of Breeding ResearchLeibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
| | | | - Thorsten Schnurbusch
- Independent HEISENBERG Research Group Plant ArchitectureLeibniz Institute of Plant Genetics and Crop Plant ResearchGaterslebenGermany
- Faculty of Natural Sciences IIIInstitute of Agricultural and Nutritional SciencesMartin Luther University Halle‐WittenbergHalleGermany
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42
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Milner SG, Jost M, Taketa S, Mazón ER, Himmelbach A, Oppermann M, Weise S, Knüpffer H, Basterrechea M, König P, Schüler D, Sharma R, Pasam RK, Rutten T, Guo G, Xu D, Zhang J, Herren G, Müller T, Krattinger SG, Keller B, Jiang Y, González MY, Zhao Y, Habekuß A, Färber S, Ordon F, Lange M, Börner A, Graner A, Reif JC, Scholz U, Mascher M, Stein N. Genebank genomics highlights the diversity of a global barley collection. Nat Genet 2018; 51:319-326. [PMID: 30420647 DOI: 10.1038/s41588-018-0266-x] [Citation(s) in RCA: 192] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 09/26/2018] [Indexed: 01/22/2023]
Abstract
Genebanks hold comprehensive collections of cultivars, landraces and crop wild relatives of all major food crops, but their detailed characterization has so far been limited to sparse core sets. The analysis of genome-wide genotyping-by-sequencing data for almost all barley accessions of the German ex situ genebank provides insights into the global population structure of domesticated barley and points out redundancies and coverage gaps in one of the world's major genebanks. Our large sample size and dense marker data afford great power for genome-wide association scans. We detect known and novel loci underlying morphological traits differentiating barley genepools, find evidence for convergent selection for barbless awns in barley and rice and show that a major-effect resistance locus conferring resistance to bymovirus infection has been favored by traditional farmers. This study outlines future directions for genomics-assisted genebank management and the utilization of germplasm collections for linking natural variation to human selection during crop evolution.
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Affiliation(s)
- Sara G Milner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Matthias Jost
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.,Agriculture and Food, The Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia
| | - Shin Taketa
- Institute of Plant Science and Resources, Okayama University, Kurashiki, Japan
| | - Elena Rey Mazón
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Axel Himmelbach
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Markus Oppermann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Stephan Weise
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Helmut Knüpffer
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Martín Basterrechea
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Patrick König
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Danuta Schüler
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Rajiv Sharma
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.,University of Dundee at the James Hutton Institute, Invergowrie, UK
| | - Raj K Pasam
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany.,Department of Economic Development, Jobs, Transport and Resources, Centre for AgriBioscience, Agriculture Victoria Research, Bundoora, Victoria, Australia
| | - Twan Rutten
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Ganggang Guo
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dongdong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Gerhard Herren
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
| | - Thomas Müller
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
| | - Simon G Krattinger
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland.,Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Beat Keller
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Maria Y González
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Antje Habekuß
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Sandra Färber
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Frank Ordon
- Institute for Resistance Research and Stress Tolerance, Julius Kühn Institute (Federal Research Centre for Cultivated Plants), Quedlinburg, Germany
| | - Matthias Lange
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Andreas Börner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Andreas Graner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Uwe Scholz
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany
| | - Martin Mascher
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany. .,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
| | - Nils Stein
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, Germany. .,Center for Integrated Breeding Research, Georg-August-Universität Göttingen, Göttingen, Germany.
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43
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Guo Z, Zhao Y, Röder MS, Reif JC, Ganal MW, Chen D, Schnurbusch T. Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat. Sci Rep 2018; 8:14435. [PMID: 30258057 PMCID: PMC6158183 DOI: 10.1038/s41598-018-31977-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 08/22/2018] [Indexed: 12/11/2022] Open
Abstract
In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3-0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield.
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Affiliation(s)
- Zifeng Guo
- Independent HEISENBERG Research Group Plant Architecture, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany
| | - Yusheng Zhao
- Research Group Quantitative Genetics, Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany
| | - Marion S Röder
- Research Group Gene and Genome Mapping, Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany
| | - Jochen C Reif
- Research Group Quantitative Genetics, Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany
| | | | - Dijun Chen
- Research Group Image Analysis, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany
| | - Thorsten Schnurbusch
- Independent HEISENBERG Research Group Plant Architecture, Leibniz Institute of Plant Genetics and Crop Plant Research, 06466, Gatersleben, Germany.
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44
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González MY, Philipp N, Schulthess AW, Weise S, Zhao Y, Börner A, Oppermann M, Graner A, Reif JC. Unlocking historical phenotypic data from an ex situ collection to enhance the informed utilization of genetic resources of barley (Hordeum sp.). Theor Appl Genet 2018; 131:2009-2019. [PMID: 29959470 DOI: 10.1007/s00122-018-3129-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 06/17/2018] [Indexed: 05/11/2023]
Abstract
Key message Historical data generated during seed regeneration are valuable to populate a bio-digital resource center for barley (Hordeum sp.). Precise estimates of trait performance of genetic resources are considered as an intellectually challenging, complex, costly and time-consuming step needed to exploit the phenotypic and genetic diversity maintained in genebanks for breeding and research. Using barley (Hordeum sp.) as a model, we examine strategies to tap into historical data available from regeneration trials. This is a first step toward extending the Federal ex situ Genebank into a bio-digital resource center facilitating an informed choice of barley accessions for research and breeding. Our study is based on historical data of seven decades collected for flowering time, plant height, and thousand grain weight during the regeneration of 12,872 spring and winter barley accessions. Linear mixed models were implemented in conjunction with routines for assessment of data quality. A resampling study highlights the potential risk of biased estimates in second-order statistics when grouping accessions for regeneration according to the year of collection or geographic origin. Based on rigorous quality assessment, we obtained high heritability estimates for the traits under consideration exceeding 0.8. Thus, the best linear unbiased estimations for the three traits are a valuable source to populate a bio-digital resource center for the IPK barley collection. The proposed strategy to leverage historical data from regeneration trials is not crop specific and can be used as a blueprint for other ex situ collections.
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Affiliation(s)
- Maria Y González
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Norman Philipp
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Albert W Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Stephan Weise
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Andreas Börner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Markus Oppermann
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Andreas Graner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
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45
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Würschum T, Liu G, Boeven PHG, Longin CFH, Mirdita V, Kazman E, Zhao Y, Reif JC. Exploiting the Rht portfolio for hybrid wheat breeding. Theor Appl Genet 2018; 131:1433-1442. [PMID: 29556941 DOI: 10.1007/s00122-018-3088-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Accepted: 03/12/2018] [Indexed: 05/10/2023]
Abstract
The portfolio of available Reduced height loci (Rht-B1, Rht-D1, and Rht24) can be exploited for hybrid wheat breeding to achieve the desired heights in the female and male parents, as well as in the hybrids, without adverse effects on other traits relevant for hybrid seed production. Plant height is an important trait in wheat line breeding, but is of even greater importance in hybrid wheat breeding. Here, the height of the female and male parental lines must be controlled and adjusted relative to each other to maximize hybrid seed production. In addition, the height of the resulting hybrids must be fine-tuned to meet the specific requirements of the farmers in the target regions. Moreover, this must be achieved without adversely impacting traits relevant for hybrid seed production. In this study, we explored Reduced height (Rht) loci effective in elite wheat and exploited their utilization for hybrid wheat breeding. We performed association mapping in a panel of 1705 wheat hybrids and their 225 parental lines, which besides the Rht-B1 and Rht-D1 loci revealed Rht24 as a major QTL for plant height. Furthermore, we found that the Rht-1 loci also reduce anther extrusion and thus cross-pollination ability, whereas Rht24 appeared to have no adverse effect on this trait. Our results suggest different haplotypes of the three Rht loci to be used in the female or male pool of a hybrid breeding program, but also show that in general, plant height is a quantitative trait controlled by numerous small-effect QTL. Consequently, marker-assisted selection for the major Rht loci must be complemented by phenotypic selection to achieve the desired height in the female and male parents as well as in the wheat hybrids.
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Affiliation(s)
- Tobias Würschum
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany.
| | - Guozheng Liu
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, 06466, Stadt Seeland, Germany
- Bayer AG, European Wheat Breeding Center, Am Schwabeplan 8, 06466, Gatersleben, Germany
| | - Philipp H G Boeven
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany
| | - C Friedrich H Longin
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany
| | - Vilson Mirdita
- Bayer AG, European Wheat Breeding Center, Am Schwabeplan 8, 06466, Gatersleben, Germany
| | - Ebrahim Kazman
- Syngenta Seeds GmbH, Kroppenstedterstr. 4, 39398, Hadmersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, 06466, Stadt Seeland, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Corrensstraße 3, 06466, Stadt Seeland, Germany
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46
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Philipp N, Weise S, Oppermann M, Börner A, Graner A, Keilwagen J, Kilian B, Zhao Y, Reif JC, Schulthess AW. Leveraging the Use of Historical Data Gathered During Seed Regeneration of an ex Situ Genebank Collection of Wheat. Front Plant Sci 2018; 9:609. [PMID: 29868066 PMCID: PMC5953327 DOI: 10.3389/fpls.2018.00609] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Accepted: 04/17/2018] [Indexed: 05/20/2023]
Abstract
Genebanks are a rich source of genetic variation. Most of this variation is absent in breeding programs but may be useful for further crop plant improvement. However, the lack of phenotypic information forms a major obstacle for the educated choice of genebank accessions for research and breeding. A promising approach to fill this information gap is to exploit historical information gathered routinely during seed regeneration cycles. Still, this data is characterized by a high non-orthogonality hampering their analysis. By examining historical data records for flowering time, plant height, and thousand grain weight collected during 70 years of regeneration of 6,207 winter wheat (Triticum aestivum L.) accessions at the German Federal ex situ Genebank, we aimed to elaborate a strategy to analyze and validate non-orthogonal historical data in order to charge genebank information platforms with high quality ready-to-use phenotypic information. First, a three-step quality control assessment considering the plausibility of trait values and a standard as well as a weather parameter index based outlier detection was implemented, resulting in heritability estimates above 0.90 for all three traits. Then, the data was analyzed by estimating best linear unbiased estimations (BLUEs) applying a linear mixed-model approach. An in silico resampling study mimicking different missing data patterns revealed that accessions should be regenerated in a random fashion and not blocked by origin or acquisition date in order to minimize estimation biases in historical data sets. Validation data was obtained from multi-environmental orthogonal field trials considering a random subsample of 3,083 accessions. Correlations above 0.84 between BLUEs estimated for historical data and validation trials outperformed previous approaches and confirmed the robustness of our strategy as well as the high quality of the historical data. The results indicate that the IPK winter wheat collection reveals an extraordinary high phenotypic diversity compared to other collections. The quality checked ready-to-use phenotypic information resulting from this study is the first brick to extend traditional, conservation driven genebanks into bio-digital resource centers.
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Affiliation(s)
- Norman Philipp
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Stephan Weise
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Markus Oppermann
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Andreas Börner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Andreas Graner
- Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Jens Keilwagen
- Institute for Biosafety in Plant Biotechnology, Julius Kühn-Institut (JKI) – Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
| | | | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Jochen C. Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Albert W. Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
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47
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Schulthess AW, Zhao Y, Longin CFH, Reif JC. Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.). Theor Appl Genet 2018; 131:685-701. [PMID: 29198016 DOI: 10.1007/s00122-017-3029-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 11/24/2017] [Indexed: 05/20/2023]
Abstract
Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.
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Affiliation(s)
- Albert W Schulthess
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - Yusheng Zhao
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany
| | - C Friedrich H Longin
- State Plant Breeding Institute, University of Hohenheim, 70593, Stuttgart, Germany
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
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48
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Li YH, Reif JC, Hong HL, Li HH, Liu ZX, Ma YS, Li J, Tian Y, Li YF, Li WB, Qiu LJ. Genome-wide association mapping of QTL underlying seed oil and protein contents of a diverse panel of soybean accessions. Plant Sci 2018; 266:95-101. [PMID: 29241572 DOI: 10.1016/j.plantsci.2017.04.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Revised: 04/24/2017] [Accepted: 04/26/2017] [Indexed: 05/08/2023]
Abstract
To investigate the genetic basis of variation in oil and protein contents in soybean seeds, a diverse collection of 421 mainly Chinese soybean cultivars was genotyped using 1536 SNPs, mostly from candidate genes related to acyl-lipid metabolism and from regions harboring known QTL. Six significant associations were identified for each of seed oil and protein contents which individually explained 2.7-5.9% of the phenotypic variance. Six associations occurred in or near known QTL and the remaining are putative novel QTL. Ten significant associations influenced the oil content without decreasing protein content, and vice versa. One SNP was pleiotropic, with opposite effects on oil and protein contents. The genetic region covering Map-6076 and-6077 was shown to be involved in controlling oil content in soybean by integrating the results of association mapping with information on known QTL and tissue-specific expression data. This region was subject to strong selection during the genetic improvement of soybean. Our results not only confirm and refine the map positions of known QTL but also contribute to a further elucidation of the genetic architecture of protein and oil contents in soybean seeds by identifying new associations exhibiting pleiotropic effects on seed protein and oil contents.
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Affiliation(s)
- Ying-Hui Li
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Jochen C Reif
- Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
| | - Hui-Long Hong
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Hui-Hui Li
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Zhang-Xiong Liu
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Yan-Song Ma
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, 150086 Harbin, China.
| | - Jun Li
- College of agriculture, Guangxi University, 530004 Nanning, China
| | - Yun Tian
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Yan-Fei Li
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
| | - Wen-Bin Li
- Key Laboratory of Soybean Biology in Chinese Education Ministry, Northeast Agricultural University, 150030 Harbin, China.
| | - Li-Juan Qiu
- The National Key Facility for Crop, Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, 100081 Beijing, China.
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49
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Varshney RK, Shi C, Thudi M, Mariac C, Wallace J, Qi P, Zhang H, Zhao Y, Wang X, Rathore A, Srivastava RK, Chitikineni A, Fan G, Bajaj P, Punnuri S, Gupta SK, Wang H, Jiang Y, Couderc M, Katta MAVSK, Paudel DR, Mungra KD, Chen W, Harris-Shultz KR, Garg V, Desai N, Doddamani D, Kane NA, Conner JA, Ghatak A, Chaturvedi P, Subramaniam S, Yadav OP, Berthouly-Salazar C, Hamidou F, Wang J, Liang X, Clotault J, Upadhyaya HD, Cubry P, Rhoné B, Gueye MC, Sunkar R, Dupuy C, Sparvoli F, Cheng S, Mahala RS, Singh B, Yadav RS, Lyons E, Datta SK, Hash CT, Devos KM, Buckler E, Bennetzen JL, Paterson AH, Ozias-Akins P, Grando S, Wang J, Mohapatra T, Weckwerth W, Reif JC, Liu X, Vigouroux Y, Xu X. Pearl millet genome sequence provides a resource to improve agronomic traits in arid environments. Nat Biotechnol 2017; 35:969-976. [PMID: 28922347 PMCID: PMC6871012 DOI: 10.1038/nbt.3943] [Citation(s) in RCA: 199] [Impact Index Per Article: 28.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2017] [Accepted: 07/17/2017] [Indexed: 01/21/2023]
Abstract
Draft genome, 994 re-sequenced lines and GWAS for yield-traits provide a resource of genetics and genomics tools for pearl millet researchers and breeders. Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D2B1-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.
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Affiliation(s)
- Rajeev K Varshney
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | | | - Mahendar Thudi
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Cedric Mariac
- Institut de recherche pour le développement (IRD), Montpellier, France
| | | | - Peng Qi
- University of Georgia, Athens, Georgia, USA
| | | | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Xiyin Wang
- University of Georgia, Athens, Georgia, USA
| | - Abhishek Rathore
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Rakesh K Srivastava
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Annapurna Chitikineni
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | | | - Prasad Bajaj
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | | | - S K Gupta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Hao Wang
- Cornell University, Ithaca, New York, USA
| | - Yong Jiang
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Marie Couderc
- Institut de recherche pour le développement (IRD), Montpellier, France
| | - Mohan A V S K Katta
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Dev R Paudel
- University of Florida, Gainesville, Florida, USA
| | - K D Mungra
- Junagadh Agricultural University, Jamnagar, Gujarat, India
| | | | - Karen R Harris-Shultz
- United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Tifton, Georgia, USA
| | - Vanika Garg
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Neetin Desai
- Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria.,Amity University, Mumbai, Maharashtra, India
| | - Dadakhalandar Doddamani
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Ndjido Ardo Kane
- Institut Sénégalais de Recherches Agricoles (ISRA), Dakar, Senegal
| | | | - Arindam Ghatak
- Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria.,School of Bioinformatics and Biotechnology, D.Y. Patil University, Mumbai, Maharashtra, India
| | - Palak Chaturvedi
- Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria
| | - Sabarinath Subramaniam
- University of Arizona, Tucson, Arizona, USA.,Phoenix Bioinformatics, Redwood City, California, USA
| | - Om Parkash Yadav
- Indian Council of Agricultural Research (ICAR)-Central Arid Zone Research Institute (CAZRI), Jodhpur, Rajasthan, India
| | - Cécile Berthouly-Salazar
- Institut de recherche pour le développement (IRD), Montpellier, France.,Laboratoire Mixte International Adaptation des Plantes et Microorganismes Associés aux Stress Environnementaux, Centre de Recherche de Bel Air, Dakar, Senegal
| | - Falalou Hamidou
- ICRISAT Sahelian Center, Niamey, Niger.,Faculty of Sciences and Techniques, University Abdou Moumouni, Niamey, Niger
| | | | | | - Jérémy Clotault
- Institut de recherche pour le développement (IRD), Montpellier, France.,University of Montpellier, Montpellier, France
| | - Hari D Upadhyaya
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | - Philippe Cubry
- Institut de recherche pour le développement (IRD), Montpellier, France
| | - Bénédicte Rhoné
- Institut de recherche pour le développement (IRD), Montpellier, France.,Laboratoire de biométrie et Biologie Evolutive, Université Lyon 1, Villeurbanne, France
| | - Mame Codou Gueye
- Institut Sénégalais de Recherches Agricoles (ISRA), Dakar, Senegal
| | | | | | - Francesca Sparvoli
- CNR-Consiglio Nazionale delle Ricerche, Istituto di Biologia e Biotecnologia Agraria, Milan, Italy
| | | | - R S Mahala
- Pioneer Hi-Bred Private Limited, Hyderabad, Telangana State, India
| | - Bharat Singh
- Fort Valley State University, Fort Valley, Georgia, USA
| | - Rattan S Yadav
- Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Ceredigion, UK
| | - Eric Lyons
- University of Arizona, Tucson, Arizona, USA
| | | | | | | | - Edward Buckler
- Cornell University, Ithaca, New York, USA.,USDA-ARS, Ithaca, New York, USA
| | | | | | | | - Stefania Grando
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana State, India
| | | | | | - Wolfram Weckwerth
- Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria.,Vienna Metabolomics Center (VIME), University of Vienna, Vienna, Austria
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
| | - Xin Liu
- BGI-Shenzhen, Shenzhen, China.,BGI-Qingdao, Qingdao, China
| | - Yves Vigouroux
- Institut de recherche pour le développement (IRD), Montpellier, France.,University of Montpellier, Montpellier, France
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, China.,BGI-Qingdao, Qingdao, China.,China National GeneBank (CNGB), Shenzen, China
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Neumann K, Zhao Y, Chu J, Keilwagen J, Reif JC, Kilian B, Graner A. Genetic architecture and temporal patterns of biomass accumulation in spring barley revealed by image analysis. BMC Plant Biol 2017; 17:137. [PMID: 28797222 PMCID: PMC5554006 DOI: 10.1186/s12870-017-1085-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 07/23/2017] [Indexed: 05/02/2023]
Abstract
BACKGROUND Genetic mapping of phenotypic traits generally focuses on a single time point, but biomass accumulates continuously during plant development. Resolution of the temporal dynamics that affect biomass recently became feasible using non-destructive imaging. RESULTS With the aim to identify key genetic factors for vegetative biomass formation from the seedling stage to flowering, we explored growth over time in a diverse collection of two-rowed spring barley accessions. High heritabilities facilitated the temporal analysis of trait relationships and identification of quantitative trait loci (QTL). Biomass QTL tended to persist only a short period during early growth. More persistent QTL were detected around the booting stage. We identified seven major biomass QTL, which together explain 55% of the genetic variance at the seedling stage, and 43% at the booting stage. Three biomass QTL co-located with genes or QTL involved in phenology. The most important locus for biomass was independent from phenology and is located on chromosome 7HL at 141 cM. This locus explained ~20% of the genetic variance, was significant over a long period of time and co-located with HvDIM, a gene involved in brassinosteroid synthesis. CONCLUSIONS Biomass is a dynamic trait and is therefore orchestrated by different QTL during early and late growth stages. Marker-assisted selection for high biomass at booting stage is most effective by also including favorable alleles from seedling biomass QTL. Selection for dynamic QTL may enhance genetic gain for complex traits such as biomass or, in the future, even grain yield.
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Affiliation(s)
- Kerstin Neumann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany.
| | - Yusheng Zhao
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
| | - Jianting Chu
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
| | - Jens Keilwagen
- Julius Kühn-Institute (JKI), Federal Research Centre for Cultivated Plants, Quedlinburg, Germany
| | - Jochen C Reif
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
| | - Benjamin Kilian
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
- Global Crop Diversity Trust (GCDT), Bonn, Germany
| | - Andreas Graner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Seeland OT Gatersleben, Germany
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