Sarah Widener, Joyce N. Njuguna, Lindsay V. Clark, Kossonou G. Anzoua, Larisa Bagmet, Pavel Chebukin, Maria S. Dwiyanti, Elena Dzyubenko, Nicolay Dzyubenko, Bimal Kumar Ghimire, Xiaoli Jin, Uffe Jørgensen, Jens Bonderup Kjeldsen, Hironori Nagano, Junhua Peng, Karen Koefoed Petersen, Andrey Sabitov, Eun Soo Seong, Toshihiko Yamada, Ji Hye Yoo, Chang Yeon Yu, Hua Zhao, Diego Jarquin, Erik Sacks, Alexander E. Lipka
{"title":"马齿苋基因型与环境模型的预测能力","authors":"Sarah Widener, Joyce N. Njuguna, Lindsay V. Clark, Kossonou G. Anzoua, Larisa Bagmet, Pavel Chebukin, Maria S. Dwiyanti, Elena Dzyubenko, Nicolay Dzyubenko, Bimal Kumar Ghimire, Xiaoli Jin, Uffe Jørgensen, Jens Bonderup Kjeldsen, Hironori Nagano, Junhua Peng, Karen Koefoed Petersen, Andrey Sabitov, Eun Soo Seong, Toshihiko Yamada, Ji Hye Yoo, Chang Yeon Yu, Hua Zhao, Diego Jarquin, Erik Sacks, Alexander E. Lipka","doi":"10.1111/gcbb.13113","DOIUrl":null,"url":null,"abstract":"<p><i>Miscanthus</i> is a genus of perennial grasses native to East Asia that shows promise as a biofuel energy source. Breeding efforts for increasing biofuel capability in this genus have focused on two species, namely <i>M. sinensis</i> (Msi) and <i>M. sacchariflorus</i> (Msa). For these efforts to succeed, it is critical that both Msi and Msa, as well as their interspecific crosses, can be grown at a wide range of latitudes. Therefore, the purpose of this study was to investigate how well existing data from Msi and Msa trials grown at locations throughout the northern hemisphere can train state-of-the-art genomic selection (GS) models to predict genomic estimated breeding values (GEBVs) of dry yield for untested Msi and Msa accessions in untested environments. We found that accounting for genotype by environment interaction in the GS model did not notably improve predictive ability. Additionally, we observed that locations at lower latitudes showed higher predictive ability relative to locations at higher latitudes. These results suggest that it is crucial to increase the number of trial locations at higher latitude locations to investigate the source of this correlation. This will make it possible to train GS models using data from environments that are similar to growing conditions at the locations targeted by Msi and Msa breeders. Such an increase of trial locations in target environments could pave the way toward advancing breeding efforts for overwintering ability in Msi and Msa, and ultimately support the potential of <i>Miscanthus</i> as a biofuel crop.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"16 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.13113","citationCount":"0","resultStr":"{\"title\":\"Genotype by environment model predictive ability in Miscanthus\",\"authors\":\"Sarah Widener, Joyce N. Njuguna, Lindsay V. Clark, Kossonou G. Anzoua, Larisa Bagmet, Pavel Chebukin, Maria S. Dwiyanti, Elena Dzyubenko, Nicolay Dzyubenko, Bimal Kumar Ghimire, Xiaoli Jin, Uffe Jørgensen, Jens Bonderup Kjeldsen, Hironori Nagano, Junhua Peng, Karen Koefoed Petersen, Andrey Sabitov, Eun Soo Seong, Toshihiko Yamada, Ji Hye Yoo, Chang Yeon Yu, Hua Zhao, Diego Jarquin, Erik Sacks, Alexander E. Lipka\",\"doi\":\"10.1111/gcbb.13113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><i>Miscanthus</i> is a genus of perennial grasses native to East Asia that shows promise as a biofuel energy source. Breeding efforts for increasing biofuel capability in this genus have focused on two species, namely <i>M. sinensis</i> (Msi) and <i>M. sacchariflorus</i> (Msa). For these efforts to succeed, it is critical that both Msi and Msa, as well as their interspecific crosses, can be grown at a wide range of latitudes. Therefore, the purpose of this study was to investigate how well existing data from Msi and Msa trials grown at locations throughout the northern hemisphere can train state-of-the-art genomic selection (GS) models to predict genomic estimated breeding values (GEBVs) of dry yield for untested Msi and Msa accessions in untested environments. We found that accounting for genotype by environment interaction in the GS model did not notably improve predictive ability. Additionally, we observed that locations at lower latitudes showed higher predictive ability relative to locations at higher latitudes. These results suggest that it is crucial to increase the number of trial locations at higher latitude locations to investigate the source of this correlation. This will make it possible to train GS models using data from environments that are similar to growing conditions at the locations targeted by Msi and Msa breeders. 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Genotype by environment model predictive ability in Miscanthus
Miscanthus is a genus of perennial grasses native to East Asia that shows promise as a biofuel energy source. Breeding efforts for increasing biofuel capability in this genus have focused on two species, namely M. sinensis (Msi) and M. sacchariflorus (Msa). For these efforts to succeed, it is critical that both Msi and Msa, as well as their interspecific crosses, can be grown at a wide range of latitudes. Therefore, the purpose of this study was to investigate how well existing data from Msi and Msa trials grown at locations throughout the northern hemisphere can train state-of-the-art genomic selection (GS) models to predict genomic estimated breeding values (GEBVs) of dry yield for untested Msi and Msa accessions in untested environments. We found that accounting for genotype by environment interaction in the GS model did not notably improve predictive ability. Additionally, we observed that locations at lower latitudes showed higher predictive ability relative to locations at higher latitudes. These results suggest that it is crucial to increase the number of trial locations at higher latitude locations to investigate the source of this correlation. This will make it possible to train GS models using data from environments that are similar to growing conditions at the locations targeted by Msi and Msa breeders. Such an increase of trial locations in target environments could pave the way toward advancing breeding efforts for overwintering ability in Msi and Msa, and ultimately support the potential of Miscanthus as a biofuel crop.
期刊介绍:
GCB Bioenergy is an international journal publishing original research papers, review articles and commentaries that promote understanding of the interface between biological and environmental sciences and the production of fuels directly from plants, algae and waste. The scope of the journal extends to areas outside of biology to policy forum, socioeconomic analyses, technoeconomic analyses and systems analysis. Papers do not need a global change component for consideration for publication, it is viewed as implicit that most bioenergy will be beneficial in avoiding at least a part of the fossil fuel energy that would otherwise be used.
Key areas covered by the journal:
Bioenergy feedstock and bio-oil production: energy crops and algae their management,, genomics, genetic improvements, planting, harvesting, storage, transportation, integrated logistics, production modeling, composition and its modification, pests, diseases and weeds of feedstocks. Manuscripts concerning alternative energy based on biological mimicry are also encouraged (e.g. artificial photosynthesis).
Biological Residues/Co-products: from agricultural production, forestry and plantations (stover, sugar, bio-plastics, etc.), algae processing industries, and municipal sources (MSW).
Bioenergy and the Environment: ecosystem services, carbon mitigation, land use change, life cycle assessment, energy and greenhouse gas balances, water use, water quality, assessment of sustainability, and biodiversity issues.
Bioenergy Socioeconomics: examining the economic viability or social acceptability of crops, crops systems and their processing, including genetically modified organisms [GMOs], health impacts of bioenergy systems.
Bioenergy Policy: legislative developments affecting biofuels and bioenergy.
Bioenergy Systems Analysis: examining biological developments in a whole systems context.