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Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection
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 Agricul...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278694/ https://www.ncbi.nlm.nih.gov/pubmed/30512010 http://dx.doi.org/10.1038/sdata.2018.278 |
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author | Gonzalez, Maria Y. Weise, Stephan Zhao, Yusheng Philipp, Norman Arend, Daniel Börner, Andreas Oppermann, Markus Graner, Andreas Reif, Jochen C. Schulthess, Albert W. |
author_facet | Gonzalez, Maria Y. Weise, Stephan Zhao, Yusheng Philipp, Norman Arend, Daniel Börner, Andreas Oppermann, Markus Graner, Andreas Reif, Jochen C. Schulthess, Albert W. |
author_sort | Gonzalez, Maria Y. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6278694 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62786942018-12-05 Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection Gonzalez, Maria Y. Weise, Stephan Zhao, Yusheng Philipp, Norman Arend, Daniel Börner, Andreas Oppermann, Markus Graner, Andreas Reif, Jochen C. Schulthess, Albert W. Sci Data Data Descriptor 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. Nature Publishing Group 2018-12-04 /pmc/articles/PMC6278694/ /pubmed/30512010 http://dx.doi.org/10.1038/sdata.2018.278 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Gonzalez, Maria Y. Weise, Stephan Zhao, Yusheng Philipp, Norman Arend, Daniel Börner, Andreas Oppermann, Markus Graner, Andreas Reif, Jochen C. Schulthess, Albert W. Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title | Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title_full | Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title_fullStr | Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title_full_unstemmed | Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title_short | Unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
title_sort | unbalanced historical phenotypic data from seed regeneration of a barley ex situ collection |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6278694/ https://www.ncbi.nlm.nih.gov/pubmed/30512010 http://dx.doi.org/10.1038/sdata.2018.278 |
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