RESUMEN
Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53.
Asunto(s)
Mapeo Cromosómico , Código de Barras del ADN Taxonómico , Daño del ADN , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/genética , Reparación del ADN , Epistasis Genética , Eliminación de Gen , Sitios Genéticos , Secuenciación de Nucleótidos de Alto Rendimiento , Metilmetanosulfonato , Modelos Teóricos , Regiones Promotoras Genéticas , Reproducibilidad de los ResultadosRESUMEN
Genetic suppression occurs when the phenotypic defects caused by a mutation in a particular gene are rescued by a mutation in a second gene. To explore the principles of genetic suppression, we examined both literature-curated and unbiased experimental data, involving systematic genetic mapping and whole-genome sequencing, to generate a large-scale suppression network among yeast genes. Most suppression pairs identified novel relationships among functionally related genes, providing new insights into the functional wiring diagram of the cell. In addition to suppressor mutations, we identified frequent secondary mutations,in a subset of genes, that likely cause a delay in the onset of stationary phase, which appears to promote their enrichment within a propagating population. These findings allow us to formulate and quantify general mechanisms of genetic suppression.
Asunto(s)
Redes Reguladoras de Genes , Genes Fúngicos , Genes Supresores , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/genética , Supresión Genética , Fenómenos Fisiológicos Celulares/genética , Mapeo CromosómicoRESUMEN
We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.
Asunto(s)
Prueba de Complementación Genética/métodos , Enfermedades Genéticas Congénitas , Saccharomyces cerevisiae , Transcripción Genética , Enfermedades Genéticas Congénitas/genética , Enfermedades Genéticas Congénitas/metabolismo , Humanos , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismoRESUMEN
Glucose homeostasis is regulated primarily by the opposing actions of insulin and glucagon, hormones that are secreted by pancreatic islets from beta-cells and alpha-cells, respectively. Insulin secretion is increased in response to elevated blood glucose to maintain normoglycemia by stimulating glucose transport in muscle and adipocytes and reducing glucose production by inhibiting gluconeogenesis in the liver. Whereas glucagon secretion is suppressed by hyperglycemia, it is stimulated during hypoglycemia, promoting hepatic glucose production and ultimately raising blood glucose levels. Diabetic hyperglycemia occurs as the result of insufficient insulin secretion from the beta-cells and/or lack of insulin action due to peripheral insulin resistance. Remarkably, excessive secretion of glucagon from the alpha-cells is also a major contributor to the development of diabetic hyperglycemia. Insulin is a physiological suppressor of glucagon secretion; however, at the cellular and molecular levels, how intraislet insulin exerts its suppressive effect on the alpha-cells is not very clear. Although the inhibitory effect of insulin on glucagon gene expression is an important means to regulate glucagon secretion, recent studies suggest that the underlying mechanisms of the intraislet insulin on suppression of glucagon secretion involve the modulation of K(ATP) channel activity and the activation of the GABA-GABA(A) receptor system. Nevertheless, regulation of glucagon secretion is multifactorial and yet to be fully understood.