Cargando…

Improvement of Rice Biomass Yield through QTL-Based Selection

Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based...

Descripción completa

Detalles Bibliográficos
Autores principales: Matsubara, Kazuki, Yamamoto, Eiji, Kobayashi, Nobuya, Ishii, Takuro, Tanaka, Junichi, Tsunematsu, Hiroshi, Yoshinaga, Satoshi, Matsumura, Osamu, Yonemaru, Jun-ichi, Mizobuchi, Ritsuko, Yamamoto, Toshio, Kato, Hiroshi, Yano, Masahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795639/
https://www.ncbi.nlm.nih.gov/pubmed/26986071
http://dx.doi.org/10.1371/journal.pone.0151830
_version_ 1782421635153788928
author Matsubara, Kazuki
Yamamoto, Eiji
Kobayashi, Nobuya
Ishii, Takuro
Tanaka, Junichi
Tsunematsu, Hiroshi
Yoshinaga, Satoshi
Matsumura, Osamu
Yonemaru, Jun-ichi
Mizobuchi, Ritsuko
Yamamoto, Toshio
Kato, Hiroshi
Yano, Masahiro
author_facet Matsubara, Kazuki
Yamamoto, Eiji
Kobayashi, Nobuya
Ishii, Takuro
Tanaka, Junichi
Tsunematsu, Hiroshi
Yoshinaga, Satoshi
Matsumura, Osamu
Yonemaru, Jun-ichi
Mizobuchi, Ritsuko
Yamamoto, Toshio
Kato, Hiroshi
Yano, Masahiro
author_sort Matsubara, Kazuki
collection PubMed
description Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F(2) plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F(6) lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield.
format Online
Article
Text
id pubmed-4795639
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-47956392016-03-23 Improvement of Rice Biomass Yield through QTL-Based Selection Matsubara, Kazuki Yamamoto, Eiji Kobayashi, Nobuya Ishii, Takuro Tanaka, Junichi Tsunematsu, Hiroshi Yoshinaga, Satoshi Matsumura, Osamu Yonemaru, Jun-ichi Mizobuchi, Ritsuko Yamamoto, Toshio Kato, Hiroshi Yano, Masahiro PLoS One Research Article Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F(2) plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F(6) lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield. Public Library of Science 2016-03-17 /pmc/articles/PMC4795639/ /pubmed/26986071 http://dx.doi.org/10.1371/journal.pone.0151830 Text en © 2016 Matsubara 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
Matsubara, Kazuki
Yamamoto, Eiji
Kobayashi, Nobuya
Ishii, Takuro
Tanaka, Junichi
Tsunematsu, Hiroshi
Yoshinaga, Satoshi
Matsumura, Osamu
Yonemaru, Jun-ichi
Mizobuchi, Ritsuko
Yamamoto, Toshio
Kato, Hiroshi
Yano, Masahiro
Improvement of Rice Biomass Yield through QTL-Based Selection
title Improvement of Rice Biomass Yield through QTL-Based Selection
title_full Improvement of Rice Biomass Yield through QTL-Based Selection
title_fullStr Improvement of Rice Biomass Yield through QTL-Based Selection
title_full_unstemmed Improvement of Rice Biomass Yield through QTL-Based Selection
title_short Improvement of Rice Biomass Yield through QTL-Based Selection
title_sort improvement of rice biomass yield through qtl-based selection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795639/
https://www.ncbi.nlm.nih.gov/pubmed/26986071
http://dx.doi.org/10.1371/journal.pone.0151830
work_keys_str_mv AT matsubarakazuki improvementofricebiomassyieldthroughqtlbasedselection
AT yamamotoeiji improvementofricebiomassyieldthroughqtlbasedselection
AT kobayashinobuya improvementofricebiomassyieldthroughqtlbasedselection
AT ishiitakuro improvementofricebiomassyieldthroughqtlbasedselection
AT tanakajunichi improvementofricebiomassyieldthroughqtlbasedselection
AT tsunematsuhiroshi improvementofricebiomassyieldthroughqtlbasedselection
AT yoshinagasatoshi improvementofricebiomassyieldthroughqtlbasedselection
AT matsumuraosamu improvementofricebiomassyieldthroughqtlbasedselection
AT yonemarujunichi improvementofricebiomassyieldthroughqtlbasedselection
AT mizobuchiritsuko improvementofricebiomassyieldthroughqtlbasedselection
AT yamamototoshio improvementofricebiomassyieldthroughqtlbasedselection
AT katohiroshi improvementofricebiomassyieldthroughqtlbasedselection
AT yanomasahiro improvementofricebiomassyieldthroughqtlbasedselection