Gene Functional Networks from Time Expression Profiles: A Constructive Approach Demonstrated in Chili Pepper (Capsicum annuum L.)
06 de marzo de 2023
Les invitamos a leer el artículo: "Gene Functional Networks from Time Expression Profiles: A Constructive Approach Demonstrated in Chili Pepper (Capsicum annuum L.)" del Dr. Octavio Martínez de la Vega, Investigador de Cinvestav UGA-Langebio, junto con el doctorando Alan Flores Díaz del Posgrado Biologia Integrativa Cinvestav, y de los doctorandos Christian Escoto Sandoval y Felipe Cervantes Hernández de Biotecnología de Plantas Cinvestav, además del Dr. José Juan Ordaz Ortiz, Profesor Investigador de Cinvestav UGA-Langebio y el Dr. Neftalí Ochoa Alejo, Investigador de Cinvestav Irapuato.
Autores: Alan Flores-Díaz1, Christian Escoto-Sandoval1, Felipe Cervantes-Hernández1, José J. Ordaz-Ortiz1, Corina Hayano-Kanashiro2, Humberto Reyes-Valdés3, Ana Garcés-Claver4, Neftalí Ochoa-Alejo5 and Octavio Martínez1.
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
- Departamento de Investigaciones Científicas y Tecnológicas de la Universidad de Sonora, Hermosillo 83000, Mexico
- Department of Plant Breeding, Universidad Autónoma Agraria Antonio Narro, Saltillo 25315, Mexico
- Unidad de Hortofruticultura, Centro de Investigación y Tecnología Agroalimentaria de Aragón, Instituto Agroalimentario de Aragón-IA2 (CITA-Universidad de Zaragoza), 50059 Zaragoza, Spain
- Departamento de Ingeniería Genética, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
Felicitamos al estudiantado y profesorado que contribuyeron en esta investigación por su arduo trabajo.
Abstract: Gene co-expression networks are powerful tools to understand functional interactions between genes. However, large co-expression networks are difficult to interpret and do not guarantee that the relations found will be true for different genotypes. Statistically verified time expression profiles give information about significant changes in expressions through time, and genes with highly correlated time expression profiles, which are annotated in the same biological process, are likely to be functionally connected. A method to obtain robust networks of functionally related genes will be useful to understand the complexity of the transcriptome, leading to biologically relevant insights. We present an algorithm to construct gene functional networks for genes annotated in a given biological process or other aspects of interest. We assume that there are genome-wide time expression profiles for a set of representative genotypes of the species of interest. The method is based on the correlation of time expression profiles, bound by a set of thresholds that assure both, a given false discovery rate, and the discard of correlation outliers. The novelty of the method consists in that a gene expression relation must be repeatedly found in a given set of independent genotypes to be considered valid. This automatically discards relations particular to specific genotypes, assuring a network robustness, which can be set a priori. Additionally, we present an algorithm to find transcription factors candidates for regulating hub genes within a network. The algorithms are demonstrated with data from a large experiment studying gene expression during the development of the fruit in a diverse set of chili pepper genotypes. The algorithm is implemented and demonstrated in a new version of the publicly available R package “Salsa” (version 1.0).
Keywords: gene expression; RNA-Seq; time expression profile; fruit development.Capsicum