Autor según el artículo: Suriyalaksh, Manusnan; Raimondi, Celia; Mains, Abraham; Segonds-Pichon, Anne; Mukhtar, Shahzabe; Murdoch, Sharlene; Aldunate, Rebeca; Krueger, Felix; Guimera, Roger; Andrews, Simon; Sales-Pardo, Marta; Casanueva, Olivia
Departamento: Enginyeria Química
Autor/es de la URV: Guimera Manrique, Roger / Sales Pardo, Marta
Palabras clave: Life-span Genomics Genetics Bioinformatics metabolism longevity insulin/igf-1 identification expression evolution drosophila daf-16 bow-ties
Resumen: We design a “wisdom-of-the-crowds” GRN inference pipeline and couple it to complex network analysis to understand the organizational principles governing gene regulation in long-lived glp-1/Notch Caenorhabditis elegans. The GRN has three layers (input, core, and output) and is topologically equivalent to bow-tie/hourglass structures prevalent among metabolic networks. To assess the functional importance of structural layers, we screened 80% of regulators and discovered 50 new aging genes, 86% with human orthologues. Genes essential for longevity—including ones involved in insulin-like signaling (ILS)—are at the core, indicating that GRN's structure is predictive of functionality. We used in vivo reporters and a novel functional network covering 5,497 genetic interactions to make mechanistic predictions. We used genetic epistasis to test some of these predictions, uncovering a novel transcriptional regulator, sup-37, that works alongside DAF-16/FOXO. We present a framework with predictive power that can accelerate discovery in C. elegans and potentially humans.
Áreas temáticas: Multidisciplinary sciences Multidisciplinary
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: roger.guimera@urv.cat marta.sales@urv.cat
Identificador del autor: 0000-0002-3597-4310 0000-0002-8140-6525
Fecha de alta del registro: 2024-10-19
Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Iscience. 25 (1): 103663-
Referencia de l'ítem segons les normes APA: Suriyalaksh, Manusnan; Raimondi, Celia; Mains, Abraham; Segonds-Pichon, Anne; Mukhtar, Shahzabe; Murdoch, Sharlene; Aldunate, Rebeca; Krueger, Felix; (2022). Gene regulatory network inference in long-lived C. elegans reveals modular properties that are predictive of novel aging genes. Iscience, 25(1), 103663-. DOI: 10.1016/j.isci.2021.103663
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2022
Tipo de publicación: Journal Publications