RESUMEN
Gene loci are found in nuclear subcompartments that are related to their expression status. For instance, silent genes are often localized to heterochromatin and the nuclear periphery, whereas active genes tend to be found in the nuclear center. Evidence also suggests that chromosomes may be specifically positioned within the nucleus; however, the nature of this organization and how it is achieved are not yet fully understood. To examine whether gene regulation is related to a discernible pattern of genomic organization, we analyzed the linear arrangement of co-regulated genes along chromosomes and determined the organization of chromosomes during the differentiation of a hematopoietic progenitor to erythroid and neutrophil cell types. Our analysis reveals that there is a significant tendency for co-regulated genes to be proximal, which is related to the association of homologous chromosomes and the spatial juxtaposition of lineage-specific gene domains. We suggest that proximity in the form of chromosomal gene distribution and homolog association may be the basis for organizing the genome for coordinate gene regulation during cellular differentiation.
Asunto(s)
Posicionamiento de Cromosoma/genética , Regulación del Desarrollo de la Expresión Génica , Genoma , Hematopoyesis/genética , Células Madre Hematopoyéticas/fisiología , Animales , Diferenciación Celular , Núcleo Celular/genética , Células Cultivadas , Células Eritroides/citología , Células Madre Hematopoyéticas/citología , Ratones , Neutrófilos/citología , Neutrófilos/fisiología , Análisis de Secuencia por Matrices de OligonucleótidosRESUMEN
CL-Quant is a new solution platform for broad, high-content, live-cell image analysis. Powered by novel machine learning technologies and teach-by-example interfaces, CL-Quant provides a platform for the rapid development and application of scalable, high-performance, and fully automated analytics for a broad range of live-cell microscopy imaging applications, including label-free phase contrast imaging. The authors used CL-Quant to teach off-the-shelf universal analytics, called standard recipes, for cell proliferation, wound healing, cell counting, and cell motility assays using phase contrast movies collected on the BioStation CT and BioStation IM platforms. Similar to application modules, standard recipes are intended to work robustly across a wide range of imaging conditions without requiring customization by the end user. The authors validated the performance of the standard recipes by comparing their performance with truth created manually, or by custom analytics optimized for each individual movie (and therefore yielding the best possible result for the image), and validated by independent review. The validation data show that the standard recipes' performance is comparable with the validated truth with low variation. The data validate that the CL-Quant standard recipes can provide robust results without customization for live-cell assays in broad cell types and laboratory settings.