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Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model

Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a q...

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Autores principales: Ganopoulou, Maria, Michailidis, Michail, Angelis, Lefteris, Ganopoulos, Ioannis, Molassiotis, Athanassios, Xanthopoulou, Aliki, Moysiadis, Theodoros
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750600/
https://www.ncbi.nlm.nih.gov/pubmed/35011654
http://dx.doi.org/10.3390/cells11010092
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author Ganopoulou, Maria
Michailidis, Michail
Angelis, Lefteris
Ganopoulos, Ioannis
Molassiotis, Athanassios
Xanthopoulou, Aliki
Moysiadis, Theodoros
author_facet Ganopoulou, Maria
Michailidis, Michail
Angelis, Lefteris
Ganopoulos, Ioannis
Molassiotis, Athanassios
Xanthopoulou, Aliki
Moysiadis, Theodoros
author_sort Ganopoulou, Maria
collection PubMed
description Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. ‘Tragana Edessis’ tissues represented by 29,247 genes and 7584 proteins. The aim of the current study was to perform a targeted analysis at the gene/protein level to assess the structure of their relation, and the biological implications. Weighted correlation network analysis and causal modeling were employed to, respectively, cluster the gene/protein pairs, and reveal their cause–effect relations, aiming to assess the associated biological functions. To the best of our knowledge, this is the first time that causal modeling has been employed within the proteogenomics concept in plants. The analysis revealed the complex nature of causal relations among genes/proteins that are important for traits of interest in perennial fruit trees, particularly regarding the fruit softening and ripening process in sweet cherry. Causal discovery could be used to highlight persistent relations at the gene/protein level, stimulating biological interpretation and facilitating further study of the proteogenomic atlas in plants.
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spelling pubmed-87506002022-01-12 Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model Ganopoulou, Maria Michailidis, Michail Angelis, Lefteris Ganopoulos, Ioannis Molassiotis, Athanassios Xanthopoulou, Aliki Moysiadis, Theodoros Cells Article Genome-wide transcriptome analysis is a method that produces important data on plant biology at a systemic level. The lack of understanding of the relationships between proteins and genes in plants necessitates a further thorough analysis at the proteogenomic level. Recently, our group generated a quantitative proteogenomic atlas of 15 sweet cherry (Prunus avium L.) cv. ‘Tragana Edessis’ tissues represented by 29,247 genes and 7584 proteins. The aim of the current study was to perform a targeted analysis at the gene/protein level to assess the structure of their relation, and the biological implications. Weighted correlation network analysis and causal modeling were employed to, respectively, cluster the gene/protein pairs, and reveal their cause–effect relations, aiming to assess the associated biological functions. To the best of our knowledge, this is the first time that causal modeling has been employed within the proteogenomics concept in plants. The analysis revealed the complex nature of causal relations among genes/proteins that are important for traits of interest in perennial fruit trees, particularly regarding the fruit softening and ripening process in sweet cherry. Causal discovery could be used to highlight persistent relations at the gene/protein level, stimulating biological interpretation and facilitating further study of the proteogenomic atlas in plants. MDPI 2021-12-29 /pmc/articles/PMC8750600/ /pubmed/35011654 http://dx.doi.org/10.3390/cells11010092 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ganopoulou, Maria
Michailidis, Michail
Angelis, Lefteris
Ganopoulos, Ioannis
Molassiotis, Athanassios
Xanthopoulou, Aliki
Moysiadis, Theodoros
Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title_full Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title_fullStr Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title_full_unstemmed Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title_short Could Causal Discovery in Proteogenomics Assist in Understanding Gene–Protein Relations? A Perennial Fruit Tree Case Study Using Sweet Cherry as a Model
title_sort could causal discovery in proteogenomics assist in understanding gene–protein relations? a perennial fruit tree case study using sweet cherry as a model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750600/
https://www.ncbi.nlm.nih.gov/pubmed/35011654
http://dx.doi.org/10.3390/cells11010092
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