Arabidopsis phenotyping through geometric morphometrics
Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental...
| Autores principales: | , |
|---|---|
| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
| Publicado: |
Oxford University Press
2018
|
| Materias: | |
| Acceso en línea: | https://academic.oup.com/gigascience/article/7/7/giy073/5039702 http://hdl.handle.net/20.500.12123/3637 https://doi.org/10.1093/gigascience/giy073 |
| _version_ | 1855035176998928384 |
|---|---|
| author | Manacorda, Carlos Augusto Asurmendi, Sebastian |
| author_browse | Asurmendi, Sebastian Manacorda, Carlos Augusto |
| author_facet | Manacorda, Carlos Augusto Asurmendi, Sebastian |
| author_sort | Manacorda, Carlos Augusto |
| collection | INTA Digital |
| description | Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units.
Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed.
Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner. |
| format | info:ar-repo/semantics/artículo |
| id | INTA3637 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Oxford University Press |
| publisherStr | Oxford University Press |
| record_format | dspace |
| spelling | INTA36372018-10-18T18:40:10Z Arabidopsis phenotyping through geometric morphometrics Manacorda, Carlos Augusto Asurmendi, Sebastian Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica Background: Recently, great technical progress has been achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it possible to extract shape and size parameters for genetic, physiological, and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of the platform and segmentation software used are still lacking, and shape descriptions still rely on ad hoc or even contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis, and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations among groups and measure them in shape distance units. Results: Here, a particular scheme of landmark placement on Arabidopsis rosette images is proposed to study shape variation in viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown, and reproducibility issues are assessed. Conclusions: Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner. Instituto de Biotecnología Fil: Manacorda, Carlos Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina Fil: Asurmendi, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina 2018-10-18T18:36:20Z 2018-10-18T18:36:20Z 2018-07 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://academic.oup.com/gigascience/article/7/7/giy073/5039702 http://hdl.handle.net/20.500.12123/3637 2047-217X https://doi.org/10.1093/gigascience/giy073 eng info:eu-repograntAgreement/INTA/PNBIO/1131022/AR./Genómica funcional y biología de sistemas. info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Oxford University Press GigaScience 7 (7) : 1-20 (Julio 2018) |
| spellingShingle | Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica Manacorda, Carlos Augusto Asurmendi, Sebastian Arabidopsis phenotyping through geometric morphometrics |
| title | Arabidopsis phenotyping through geometric morphometrics |
| title_full | Arabidopsis phenotyping through geometric morphometrics |
| title_fullStr | Arabidopsis phenotyping through geometric morphometrics |
| title_full_unstemmed | Arabidopsis phenotyping through geometric morphometrics |
| title_short | Arabidopsis phenotyping through geometric morphometrics |
| title_sort | arabidopsis phenotyping through geometric morphometrics |
| topic | Arabidopsis Fenotipos Phenotypes Geometric Morphometrics Morfometría Geométrica |
| url | https://academic.oup.com/gigascience/article/7/7/giy073/5039702 http://hdl.handle.net/20.500.12123/3637 https://doi.org/10.1093/gigascience/giy073 |
| work_keys_str_mv | AT manacordacarlosaugusto arabidopsisphenotypingthroughgeometricmorphometrics AT asurmendisebastian arabidopsisphenotypingthroughgeometricmorphometrics |