Three topological features of regulatory networks control life-essential and specialized subsystems

Autor(es)

Wolf, Ivan Rodrigo ^[1] ; Simoes, Rafael Plana ^{[2, 1]} ; Valente, Guilherme Targino ^{[1, 3]}

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ UNESP, Sch Agr, Dept Bioprocess & Biotechnol, BR-18610034 Botucatu, SP - Brazil

^[2] Sao Paulo State Univ Unesp, Sch Med, BR-18618687 Botucatu, SP - Brazil

^[3] Max Planck Inst, Max Planck Inst Herz & Lungenforschung, D-61231 Bad Nauheim - Germany

• Tipo de documento: Artigo Científico
• Fonte: SCIENTIFIC REPORTS; v. 11, n. 1 DEC 20 2021.
• Citações Web of Science: 0

Resumo

Gene regulatory networks (GRNs) play key roles in development, phenotype plasticity, and evolution. Although graph theory has been used to explore GRNs, associations amongst topological features, transcription factors (TFs), and systems essentiality are poorly understood. Here we sought the relationship amongst the main GRN topological features that influence the control of essential and specific subsystems. We found that the K-nn, page rank, and degree are the most relevant GRN features: the ones are conserved along the evolution and are also relevant in pluripotent cells. Interestingly, life-essential subsystems are governed mainly by TFs with intermediary K-nn and high page rank or degree, whereas specialized subsystems are mainly regulated by TFs with low K-nn. Hence, we suggest that the high probability of TFs be toured by a random signal, and the high probability of the signal propagation to target genes ensures the life-essential subsystems' robustness. Gene/genome duplication is the main evolutionary process to rise K-nn as the most relevant feature. Herein, we shed light on unexplored topological GRN features to assess how they are related to subsystems and how the duplications shaped the regulatory systems along the evolution. The classification model generated can be found here: https://github.com/ivanrwolf/NoC/. (AU)

• Processo FAPESP: 15/12093-9 - Análises integrativas aplicadas à tolerância ao etanol em linhagens de Saccharomyces cerevisiae: uma abordagem envolvendo transcriptoma, proteômica, biologia de sistemas e aprendizado de máquina
• Beneficiário: Guilherme Targino Valente
• Modalidade de apoio: Auxílio à Pesquisa - Programa BIOEN - Regular
• Processo FAPESP: 15/19211-7 - Identificação de assinaturas sistêmicas associadas à tolerância ao etanol em linhagens de Saccharomyces cerevisiae
• Beneficiário: Ivan Rodrigo Wolf
• Modalidade de apoio: Bolsas no Brasil - Doutorado