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...
| Autores principales: | , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Wiley
2023
|
| Acceso en línea: | https://hdl.handle.net/10568/163960 |
| _version_ | 1855514916915511296 |
|---|---|
| author | Massahiro Yassue, Rafael Galli, Giovanni James Chen, Chun-Peng Fritsche-Neto, Roberto Morota, Gota |
| author_browse | Fritsche-Neto, Roberto Galli, Giovanni James Chen, Chun-Peng Massahiro Yassue, Rafael Morota, Gota |
| author_facet | Massahiro Yassue, Rafael Galli, Giovanni James Chen, Chun-Peng Fritsche-Neto, Roberto Morota, Gota |
| author_sort | Massahiro Yassue, Rafael |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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 | Journal Article |
| id | CGSpace163960 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Wiley |
| publisherStr | Wiley |
| record_format | dspace |
| spelling | CGSpace1639602025-08-21T15:39:31Z 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 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. 2023-04 2024-12-19T12:53:14Z 2024-12-19T12:53:14Z Journal Article https://hdl.handle.net/10568/163960 en Open Access Wiley Massahiro Yassue, Rafael; Galli, Giovanni; James Chen, Chun‐Peng; Fritsche‐Neto, Roberto and Morota, Gota. 2023. 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 Direct, Volume 7, no. 4 |
| spellingShingle | 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 |
| url | https://hdl.handle.net/10568/163960 |
| work_keys_str_mv | AT massahiroyassuerafael genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation AT galligiovanni genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation AT jameschenchunpeng genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation AT fritschenetoroberto genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation AT morotagota genomewideassociationanalysisofhyperspectralreflectancedatatodissectthegeneticarchitectureofgrowthrelatedtraitsinmaizeunderplantgrowthpromotingbacteriainoculation |