Cargando…

Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions

Drought significantly influences maize morphology and yield potential. The elucidation of the genetic mechanisms of yield components and morphological traits, and tightly linked molecular markers under drought stress are thus of great importance in marker assisted selection (MAS) breeding. Here, we...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhao, Xiaoqiang, Zhang, Jinwen, Fang, Peng, Peng, Yunling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society of Breeding 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977450/
https://www.ncbi.nlm.nih.gov/pubmed/31988626
http://dx.doi.org/10.1270/jsbbs.18021
_version_ 1783490513192615936
author Zhao, Xiaoqiang
Zhang, Jinwen
Fang, Peng
Peng, Yunling
author_facet Zhao, Xiaoqiang
Zhang, Jinwen
Fang, Peng
Peng, Yunling
author_sort Zhao, Xiaoqiang
collection PubMed
description Drought significantly influences maize morphology and yield potential. The elucidation of the genetic mechanisms of yield components and morphological traits, and tightly linked molecular markers under drought stress are thus of great importance in marker assisted selection (MAS) breeding. Here, we identified 32 QTLs for grain weight per ear, kernel ratio, and ear height-to-plant height ratio across two F(2:3) populations under both drought and non-drought conditions by single-environment mapping with composite interval mapping (CIM), of which 21 QTLs were mapped under water-stressed conditions. We identified 29 QTLs by joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 14 QTLs involved in QTL-by-environment interactions, and 11 epistatic interactions. Further analysis simultaneously identified 20 stable QTLs (sQTLs) by CIM and MCIM could be useful for genetic improvement of these traits via QTL pyramiding. Remarkably, bin 1.07-1.10/6.05/8.03/8.06 exhibited four pleiotropic sQTLs that were consistent with phenotypic correlations among traits, supporting the pleiotropy of QTLs and playing important roles in conferring growth and yield advantages under contrasting watering conditions. These findings provide information on the genetic mechanisms responsible for yield components and morphological traits that are affected by different watering conditions. Furthermore, these alleles provide useful targets for MAS.
format Online
Article
Text
id pubmed-6977450
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Japanese Society of Breeding
record_format MEDLINE/PubMed
spelling pubmed-69774502020-01-27 Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions Zhao, Xiaoqiang Zhang, Jinwen Fang, Peng Peng, Yunling Breed Sci Research Paper Drought significantly influences maize morphology and yield potential. The elucidation of the genetic mechanisms of yield components and morphological traits, and tightly linked molecular markers under drought stress are thus of great importance in marker assisted selection (MAS) breeding. Here, we identified 32 QTLs for grain weight per ear, kernel ratio, and ear height-to-plant height ratio across two F(2:3) populations under both drought and non-drought conditions by single-environment mapping with composite interval mapping (CIM), of which 21 QTLs were mapped under water-stressed conditions. We identified 29 QTLs by joint analysis of all environments with mixed-linear-model-based composite interval mapping (MCIM), 14 QTLs involved in QTL-by-environment interactions, and 11 epistatic interactions. Further analysis simultaneously identified 20 stable QTLs (sQTLs) by CIM and MCIM could be useful for genetic improvement of these traits via QTL pyramiding. Remarkably, bin 1.07-1.10/6.05/8.03/8.06 exhibited four pleiotropic sQTLs that were consistent with phenotypic correlations among traits, supporting the pleiotropy of QTLs and playing important roles in conferring growth and yield advantages under contrasting watering conditions. These findings provide information on the genetic mechanisms responsible for yield components and morphological traits that are affected by different watering conditions. Furthermore, these alleles provide useful targets for MAS. Japanese Society of Breeding 2019-12 2019-10-31 /pmc/articles/PMC6977450/ /pubmed/31988626 http://dx.doi.org/10.1270/jsbbs.18021 Text en Copyright © 2019 by JAPANESE SOCIETY OF BREEDING http://creativecommons.org/licenses/by-nc-nd/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Zhao, Xiaoqiang
Zhang, Jinwen
Fang, Peng
Peng, Yunling
Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title_full Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title_fullStr Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title_full_unstemmed Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title_short Comparative QTL analysis for yield components and morphological traits in maize (Zea mays L.) under water-stressed and well-watered conditions
title_sort comparative qtl analysis for yield components and morphological traits in maize (zea mays l.) under water-stressed and well-watered conditions
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6977450/
https://www.ncbi.nlm.nih.gov/pubmed/31988626
http://dx.doi.org/10.1270/jsbbs.18021
work_keys_str_mv AT zhaoxiaoqiang comparativeqtlanalysisforyieldcomponentsandmorphologicaltraitsinmaizezeamayslunderwaterstressedandwellwateredconditions
AT zhangjinwen comparativeqtlanalysisforyieldcomponentsandmorphologicaltraitsinmaizezeamayslunderwaterstressedandwellwateredconditions
AT fangpeng comparativeqtlanalysisforyieldcomponentsandmorphologicaltraitsinmaizezeamayslunderwaterstressedandwellwateredconditions
AT pengyunling comparativeqtlanalysisforyieldcomponentsandmorphologicaltraitsinmaizezeamayslunderwaterstressedandwellwateredconditions