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Identifying yield-related genes in maize based on ear trait plasticity
BACKGROUND: Phenotypic plasticity is defined as the phenotypic variation of a trait when an organism is exposed to different environments, and it is closely related to genotype. Exploring the genetic basis behind the phenotypic plasticity of ear traits in maize is critical to achieve climate-stable...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127483/ https://www.ncbi.nlm.nih.gov/pubmed/37098597 http://dx.doi.org/10.1186/s13059-023-02937-6 |
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author | Liu, Minguo Zhang, Shuaisong Li, Wei Zhao, Xiaoming Wang, Xi-Qing |
author_facet | Liu, Minguo Zhang, Shuaisong Li, Wei Zhao, Xiaoming Wang, Xi-Qing |
author_sort | Liu, Minguo |
collection | PubMed |
description | BACKGROUND: Phenotypic plasticity is defined as the phenotypic variation of a trait when an organism is exposed to different environments, and it is closely related to genotype. Exploring the genetic basis behind the phenotypic plasticity of ear traits in maize is critical to achieve climate-stable yields, particularly given the unpredictable effects of climate change. Performing genetic field studies in maize requires development of a fast, reliable, and automated system for phenotyping large numbers of samples. RESULTS: Here, we develop MAIZTRO as an automated maize ear phenotyping platform for high-throughput measurements in the field. Using this platform, we analyze 15 common ear phenotypes and their phenotypic plasticity variation in 3819 transgenic maize inbred lines targeting 717 genes, along with the wild type lines of the same genetic background, in multiple field environments in two consecutive years. Kernel number is chosen as the primary target phenotype because it is a key trait for improving the grain yield and ensuring yield stability. We analyze the phenotypic plasticity of the transgenic lines in different environments and identify 34 candidate genes that may regulate the phenotypic plasticity of kernel number. CONCLUSIONS: Our results suggest that as an integrated and efficient phenotyping platform for measuring maize ear traits, MAIZTRO can help to explore new traits that are important for improving and stabilizing the yield. This study indicates that genes and alleles related with ear trait plasticity can be identified using transgenic maize inbred populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02937-6. |
format | Online Article Text |
id | pubmed-10127483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101274832023-04-26 Identifying yield-related genes in maize based on ear trait plasticity Liu, Minguo Zhang, Shuaisong Li, Wei Zhao, Xiaoming Wang, Xi-Qing Genome Biol Research BACKGROUND: Phenotypic plasticity is defined as the phenotypic variation of a trait when an organism is exposed to different environments, and it is closely related to genotype. Exploring the genetic basis behind the phenotypic plasticity of ear traits in maize is critical to achieve climate-stable yields, particularly given the unpredictable effects of climate change. Performing genetic field studies in maize requires development of a fast, reliable, and automated system for phenotyping large numbers of samples. RESULTS: Here, we develop MAIZTRO as an automated maize ear phenotyping platform for high-throughput measurements in the field. Using this platform, we analyze 15 common ear phenotypes and their phenotypic plasticity variation in 3819 transgenic maize inbred lines targeting 717 genes, along with the wild type lines of the same genetic background, in multiple field environments in two consecutive years. Kernel number is chosen as the primary target phenotype because it is a key trait for improving the grain yield and ensuring yield stability. We analyze the phenotypic plasticity of the transgenic lines in different environments and identify 34 candidate genes that may regulate the phenotypic plasticity of kernel number. CONCLUSIONS: Our results suggest that as an integrated and efficient phenotyping platform for measuring maize ear traits, MAIZTRO can help to explore new traits that are important for improving and stabilizing the yield. This study indicates that genes and alleles related with ear trait plasticity can be identified using transgenic maize inbred populations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-02937-6. BioMed Central 2023-04-25 /pmc/articles/PMC10127483/ /pubmed/37098597 http://dx.doi.org/10.1186/s13059-023-02937-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liu, Minguo Zhang, Shuaisong Li, Wei Zhao, Xiaoming Wang, Xi-Qing Identifying yield-related genes in maize based on ear trait plasticity |
title | Identifying yield-related genes in maize based on ear trait plasticity |
title_full | Identifying yield-related genes in maize based on ear trait plasticity |
title_fullStr | Identifying yield-related genes in maize based on ear trait plasticity |
title_full_unstemmed | Identifying yield-related genes in maize based on ear trait plasticity |
title_short | Identifying yield-related genes in maize based on ear trait plasticity |
title_sort | identifying yield-related genes in maize based on ear trait plasticity |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10127483/ https://www.ncbi.nlm.nih.gov/pubmed/37098597 http://dx.doi.org/10.1186/s13059-023-02937-6 |
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