Genomic Analyses of Arabidopsis Flower Development: sORFs, miRNAs, and transcription factor-coding genes
The focus of this proposal is to characterize the functions of novel components of the flower development gene regulatory network in Arabidopsis, using various genomic approaches. The proposed work will target: (1) novel coding sm...
The focus of this proposal is to characterize the functions of novel components of the flower development gene regulatory network in Arabidopsis, using various genomic approaches. The proposed work will target: (1) novel coding small open reading frames (sORFs) detected in intergenic regions; (2) novel or uncharacterized microRNAs and protein-coding genes potentially implicated in flower development (by previous genome-wide expression analyses); and (3) selected transcription factors known to participate in the process. Extensive genetic analyses of flower development in Arabidopsis and Antirrhinum have led to the identification of key regulatory genes of the process. Most of these regulators code for transcription factors, and microarray analyses have revealed the existence of a complex transcriptional network underlying the floral development process. Yet, many components of this network likely still remain to be identified (belonging to classes of genes that have been more untractable by classic genetic and molecular biology methods, such as sORFs and miRNAs); and many protein coding genes that likely participate in the process remain functionally uncharacterized. In addition, targets of the known regulators are still largely ill-defined. The objectives of the project are: (1) to conduct expression profiling experiments aimed at identifying novel sORFs that may participate in flower development, and at understanding their roles; (2) to begin to elucidate the functions of novel, uncharaterized components of the regulatory network (sORFs, miRNAs, and protein-coding genes) through various reverse-genetic approaches; and (3) to use novel genomic methods, in particular the recently developed ChIP-Seq approach, to identify target genes of known regulators. While these objectives are diverse in the nature of their molecular targets and in the experimental methods used, their combination is required for a deeper understanding of developmental regulatory networks.ver más
04-09-2024:
Subvenciones casos de Uso IA Industrial
Se abre la línea de ayuda pública: Subvenciones dirigidas al desarrollo de casos de uso de inteligencia artificial aplicada a la industria, Comunidad de Madrid para el organismo:
Seleccionando "Aceptar todas las cookies" acepta el uso de cookies para ayudarnos a brindarle una mejor experiencia de usuario y para analizar el uso del sitio web. Al hacer clic en "Ajustar tus preferencias" puede elegir qué cookies permitir. Solo las cookies esenciales son necesarias para el correcto funcionamiento de nuestro sitio web y no se pueden rechazar.
Cookie settings
Nuestro sitio web almacena cuatro tipos de cookies. En cualquier momento puede elegir qué cookies acepta y cuáles rechaza. Puede obtener más información sobre qué son las cookies y qué tipos de cookies almacenamos en nuestra Política de cookies.
Son necesarias por razones técnicas. Sin ellas, este sitio web podría no funcionar correctamente.
Son necesarias para una funcionalidad específica en el sitio web. Sin ellos, algunas características pueden estar deshabilitadas.
Nos permite analizar el uso del sitio web y mejorar la experiencia del visitante.
Nos permite personalizar su experiencia y enviarle contenido y ofertas relevantes, en este sitio web y en otros sitios web.