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Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding

In the breeding of citrus (Citrus spp.), suitable fruit quality is essential for consumer acceptance of new cultivars. To identify parental combinations producing F(1) progeny with fruit-quality traits exceeding certain selection criteria, we developed a simple and practical method for predicting mu...

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Autores principales: Imai, Atsushi, Kuniga, Takeshi, Yoshioka, Terutaka, Nonaka, Keisuke, Mitani, Nobuhito, Fukamachi, Hiroshi, Hiehata, Naofumi, Yamamoto, Masashi, Hayashi, Takeshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095598/
https://www.ncbi.nlm.nih.gov/pubmed/30114283
http://dx.doi.org/10.1371/journal.pone.0202341
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author Imai, Atsushi
Kuniga, Takeshi
Yoshioka, Terutaka
Nonaka, Keisuke
Mitani, Nobuhito
Fukamachi, Hiroshi
Hiehata, Naofumi
Yamamoto, Masashi
Hayashi, Takeshi
author_facet Imai, Atsushi
Kuniga, Takeshi
Yoshioka, Terutaka
Nonaka, Keisuke
Mitani, Nobuhito
Fukamachi, Hiroshi
Hiehata, Naofumi
Yamamoto, Masashi
Hayashi, Takeshi
author_sort Imai, Atsushi
collection PubMed
description In the breeding of citrus (Citrus spp.), suitable fruit quality is essential for consumer acceptance of new cultivars. To identify parental combinations producing F(1) progeny with fruit-quality traits exceeding certain selection criteria, we developed a simple and practical method for predicting multiple-trait segregation in an F(1) progeny population. This method uses breeding values of parental genotypes and an additive genetic (co)variance matrix calculated by the best linear unbiased prediction method to construct a model for trait segregation in F(1) progeny. To confirm the validity of our proposed method, we calculated the breeding values and additive genetic (co)variances based on phenotypic records on nine fruit-quality traits in 2122 genotypes, and constructed a trait segregation model. Subsequently, we applied the trait segregation model to all pairs of the 2122 genotypes (i.e., 2,252,503 combinations), and predicted the most promising combinations and evaluated their probabilities of producing superior genotypes exceeding the nine fruit-quality traits of satsuma mandarin (Citrus unshiu Marcow.) or ‘Shiranuhi’ (‘Kiyomi’ × ‘Nakano No. 3’ ponkan), two popular citrus cultivars in Japan. We consider these results to be useful not only for selecting good parental combinations for fruit quality or other important traits but also for determining the scale of breeding programs required to achieve specific breeding goals.
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spelling pubmed-60955982018-08-30 Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding Imai, Atsushi Kuniga, Takeshi Yoshioka, Terutaka Nonaka, Keisuke Mitani, Nobuhito Fukamachi, Hiroshi Hiehata, Naofumi Yamamoto, Masashi Hayashi, Takeshi PLoS One Research Article In the breeding of citrus (Citrus spp.), suitable fruit quality is essential for consumer acceptance of new cultivars. To identify parental combinations producing F(1) progeny with fruit-quality traits exceeding certain selection criteria, we developed a simple and practical method for predicting multiple-trait segregation in an F(1) progeny population. This method uses breeding values of parental genotypes and an additive genetic (co)variance matrix calculated by the best linear unbiased prediction method to construct a model for trait segregation in F(1) progeny. To confirm the validity of our proposed method, we calculated the breeding values and additive genetic (co)variances based on phenotypic records on nine fruit-quality traits in 2122 genotypes, and constructed a trait segregation model. Subsequently, we applied the trait segregation model to all pairs of the 2122 genotypes (i.e., 2,252,503 combinations), and predicted the most promising combinations and evaluated their probabilities of producing superior genotypes exceeding the nine fruit-quality traits of satsuma mandarin (Citrus unshiu Marcow.) or ‘Shiranuhi’ (‘Kiyomi’ × ‘Nakano No. 3’ ponkan), two popular citrus cultivars in Japan. We consider these results to be useful not only for selecting good parental combinations for fruit quality or other important traits but also for determining the scale of breeding programs required to achieve specific breeding goals. Public Library of Science 2018-08-16 /pmc/articles/PMC6095598/ /pubmed/30114283 http://dx.doi.org/10.1371/journal.pone.0202341 Text en © 2018 Imai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Imai, Atsushi
Kuniga, Takeshi
Yoshioka, Terutaka
Nonaka, Keisuke
Mitani, Nobuhito
Fukamachi, Hiroshi
Hiehata, Naofumi
Yamamoto, Masashi
Hayashi, Takeshi
Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title_full Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title_fullStr Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title_full_unstemmed Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title_short Predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
title_sort predicting segregation of multiple fruit-quality traits by using accumulated phenotypic records in citrus breeding
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095598/
https://www.ncbi.nlm.nih.gov/pubmed/30114283
http://dx.doi.org/10.1371/journal.pone.0202341
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