Updated guidelines for gene nomenclature in wheat.
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Date
2023
Authors
Boden, S.A.
McIntosh, R.A.
Uauy, C.
Krattinger, S.G.
Dubcovsky, J.
Rogers, W.J.
Xia, X.C.
Badaeva, E.D.
Bentley, A.R.
Brown-Guedira, G.
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Journal article
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Theoretical and Applied Genetics: international journal of plant breeding research, 2023; 136(4):1-16
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S. A. Boden, R. A. McIntosh, C. Uauy, S. G. Krattinger, J. Dubcovsky, W. J. Rogers, X. C. Xia, E. D. Badaeva, A. R. Bentley, G. Brown, Guedira, M. Caccamo, L. Cattivelli, P. Chhuneja, J. Cockram, B. Contreras, Moreira, S. Dreisigacker, D. Edwards, F. G. González, C. Guzmán, T. M. Ikeda, I. Karsai, S. Nasuda, C. Pozniak, R. Prins, T. Z. Sen, P. Silva, H. Simkova, Y. Zhang, the Wheat Initiative
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Abstract
Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.
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© The Author(s) 2023. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.