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Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response
Many studies showed that few degrees above tomato optimum growth temperature threshold can lead to serious loss in production. Therefore, the development of innovative strategies to obtain tomato cultivars with improved yield under high temperature conditions is a main goal both for basic genetic st...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484564/ https://www.ncbi.nlm.nih.gov/pubmed/34593775 http://dx.doi.org/10.1038/s41438-021-00647-3 |
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author | Cappetta, Elisa Andolfo, Giuseppe Guadagno, Anna Di Matteo, Antonio Barone, Amalia Frusciante, Luigi Ercolano, Maria Raffaella |
author_facet | Cappetta, Elisa Andolfo, Giuseppe Guadagno, Anna Di Matteo, Antonio Barone, Amalia Frusciante, Luigi Ercolano, Maria Raffaella |
author_sort | Cappetta, Elisa |
collection | PubMed |
description | Many studies showed that few degrees above tomato optimum growth temperature threshold can lead to serious loss in production. Therefore, the development of innovative strategies to obtain tomato cultivars with improved yield under high temperature conditions is a main goal both for basic genetic studies and breeding activities. In this paper, a F4 segregating population was phenotypically evaluated for quantitative and qualitative traits under heat stress conditions. Moreover, a genotyping by sequencing (GBS) approach has been employed for building up genomic selection (GS) models both for yield and soluble solid content (SCC). Several parameters, including training population size, composition and marker quality were tested to predict genotype performance under heat stress conditions. A good prediction accuracy for the two analyzed traits (0.729 for yield production and 0.715 for SCC) was obtained. The predicted models improved the genetic gain of selection in the next breeding cycles, suggesting that GS approach is a promising strategy to accelerate breeding for heat tolerance in tomato. Finally, the annotation of SNPs located in gene body regions combined with QTL analysis allowed the identification of five candidates putatively involved in high temperatures response, and the building up of a GS model based on calibrated panel of SNP markers. |
format | Online Article Text |
id | pubmed-8484564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84845642021-10-12 Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response Cappetta, Elisa Andolfo, Giuseppe Guadagno, Anna Di Matteo, Antonio Barone, Amalia Frusciante, Luigi Ercolano, Maria Raffaella Hortic Res Article Many studies showed that few degrees above tomato optimum growth temperature threshold can lead to serious loss in production. Therefore, the development of innovative strategies to obtain tomato cultivars with improved yield under high temperature conditions is a main goal both for basic genetic studies and breeding activities. In this paper, a F4 segregating population was phenotypically evaluated for quantitative and qualitative traits under heat stress conditions. Moreover, a genotyping by sequencing (GBS) approach has been employed for building up genomic selection (GS) models both for yield and soluble solid content (SCC). Several parameters, including training population size, composition and marker quality were tested to predict genotype performance under heat stress conditions. A good prediction accuracy for the two analyzed traits (0.729 for yield production and 0.715 for SCC) was obtained. The predicted models improved the genetic gain of selection in the next breeding cycles, suggesting that GS approach is a promising strategy to accelerate breeding for heat tolerance in tomato. Finally, the annotation of SNPs located in gene body regions combined with QTL analysis allowed the identification of five candidates putatively involved in high temperatures response, and the building up of a GS model based on calibrated panel of SNP markers. Nature Publishing Group UK 2021-10-01 /pmc/articles/PMC8484564/ /pubmed/34593775 http://dx.doi.org/10.1038/s41438-021-00647-3 Text en © The Author(s) 2021 https://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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cappetta, Elisa Andolfo, Giuseppe Guadagno, Anna Di Matteo, Antonio Barone, Amalia Frusciante, Luigi Ercolano, Maria Raffaella Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title | Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title_full | Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title_fullStr | Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title_full_unstemmed | Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title_short | Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
title_sort | tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484564/ https://www.ncbi.nlm.nih.gov/pubmed/34593775 http://dx.doi.org/10.1038/s41438-021-00647-3 |
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