Cargando…

Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation

Plant growth‐promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth‐related traits may shed light on the underlying genetics as such data can help assess biochemical and physiologic...

Descripción completa

Detalles Bibliográficos
Autores principales: Massahiro Yassue, Rafael, Galli, Giovanni, James Chen, Chun‐Peng, Fritsche‐Neto, Roberto, Morota, Gota
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123960/
https://www.ncbi.nlm.nih.gov/pubmed/37102161
http://dx.doi.org/10.1002/pld3.492
_version_ 1785029753295601664
author Massahiro Yassue, Rafael
Galli, Giovanni
James Chen, Chun‐Peng
Fritsche‐Neto, Roberto
Morota, Gota
author_facet Massahiro Yassue, Rafael
Galli, Giovanni
James Chen, Chun‐Peng
Fritsche‐Neto, Roberto
Morota, Gota
author_sort Massahiro Yassue, Rafael
collection PubMed
description Plant growth‐promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth‐related traits may shed light on the underlying genetics as such data can help assess biochemical and physiological traits. This study aimed to integrate hyperspectral reflectance data with genome‐wide association analyses to examine maize growth‐related traits under PGPB inoculation. A total of 360 inbred maize lines with 13,826 single nucleotide polymorphisms (SNPs) were evaluated with and without PGPB inoculation; 150 hyperspectral wavelength reflectances at 386–1021 nm and 131 hyperspectral indices were used in the analysis. Plant height, stalk diameter, and shoot dry mass were measured manually. Overall, hyperspectral signatures produced similar or higher genomic heritability estimates than those of manually measured phenotypes, and they were genetically correlated with manually measured phenotypes. Furthermore, several hyperspectral reflectance values and spectral indices were identified by genome‐wide association analysis as potential markers for growth‐related traits under PGPB inoculation. Eight SNPs were detected, which were commonly associated with manually measured and hyperspectral phenotypes. Different genomic regions were found for plant growth and hyperspectral phenotypes between with and without PGPB inoculation. Moreover, the hyperspectral phenotypes were associated with genes previously reported as candidates for nitrogen uptake efficiency, tolerance to abiotic stressors, and kernel size. In addition, a Shiny web application was developed to explore multiphenotype genome‐wide association results interactively. Taken together, our results demonstrate the usefulness of hyperspectral‐based phenotyping for studying maize growth‐related traits in response to PGPB inoculation.
format Online
Article
Text
id pubmed-10123960
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-101239602023-04-25 Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation Massahiro Yassue, Rafael Galli, Giovanni James Chen, Chun‐Peng Fritsche‐Neto, Roberto Morota, Gota Plant Direct Original Research Plant growth‐promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth‐related traits may shed light on the underlying genetics as such data can help assess biochemical and physiological traits. This study aimed to integrate hyperspectral reflectance data with genome‐wide association analyses to examine maize growth‐related traits under PGPB inoculation. A total of 360 inbred maize lines with 13,826 single nucleotide polymorphisms (SNPs) were evaluated with and without PGPB inoculation; 150 hyperspectral wavelength reflectances at 386–1021 nm and 131 hyperspectral indices were used in the analysis. Plant height, stalk diameter, and shoot dry mass were measured manually. Overall, hyperspectral signatures produced similar or higher genomic heritability estimates than those of manually measured phenotypes, and they were genetically correlated with manually measured phenotypes. Furthermore, several hyperspectral reflectance values and spectral indices were identified by genome‐wide association analysis as potential markers for growth‐related traits under PGPB inoculation. Eight SNPs were detected, which were commonly associated with manually measured and hyperspectral phenotypes. Different genomic regions were found for plant growth and hyperspectral phenotypes between with and without PGPB inoculation. Moreover, the hyperspectral phenotypes were associated with genes previously reported as candidates for nitrogen uptake efficiency, tolerance to abiotic stressors, and kernel size. In addition, a Shiny web application was developed to explore multiphenotype genome‐wide association results interactively. Taken together, our results demonstrate the usefulness of hyperspectral‐based phenotyping for studying maize growth‐related traits in response to PGPB inoculation. John Wiley and Sons Inc. 2023-04-24 /pmc/articles/PMC10123960/ /pubmed/37102161 http://dx.doi.org/10.1002/pld3.492 Text en © 2023 The Authors. Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Massahiro Yassue, Rafael
Galli, Giovanni
James Chen, Chun‐Peng
Fritsche‐Neto, Roberto
Morota, Gota
Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title_full Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title_fullStr Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title_full_unstemmed Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title_short Genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
title_sort genome‐wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth‐related traits in maize under plant growth‐promoting bacteria inoculation
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123960/
https://www.ncbi.nlm.nih.gov/pubmed/37102161
http://dx.doi.org/10.1002/pld3.492
work_keys_str_mv AT massahiroyassuerafael genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation
AT galligiovanni genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation
AT jameschenchunpeng genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation
AT fritschenetoroberto genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation
AT morotagota genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation