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Heterotrimeric (αβγ) G protein signaling pathways are critical environmental sensing systems found in eukaryotic cells. Exchange of GDP for GTP on the Gα subunit leads to its activation. In contrast, GTP hydrolysis on the Gα is accelerated by Regulator of G protein Signaling (RGS) proteins, resulting in a return to the GDP-bound, inactive state. Here, we analyzed growth, development and extracellular cellulase production in strains with knockout mutations in the seven identified RGS genes (rgs-1 to rgs-7) in the filamentous fungus, Neurospora crassa. We compared phenotypes to those of strains with either knockout mutations or expressing predicted constitutively activated, GTPase-deficient alleles for each of the three Gα subunit genes (gna-1Q204L, gna-2Q205L or gna-3Q208L). Our data revealed that six RGS mutants have taller aerial hyphae than wild type and all seven mutants exhibit reduced asexual sporulation, phenotypes shared with strains expressing the gna-1Q204L or gna-3Q208L allele. In contrast, Δrgs-1 and Δrgs-3 were the only RGS mutants with a slower growth rate phenotype, a defect in common with gna-1Q204L strains. With respect to female sexual development, Δrgs-1 possessed defects most similar to gna-3Q208L strains, while those of Δrgs-2 mutants resembled strains expressing the gna-1Q204L allele. Finally, we observed that four of the seven RGS mutants had significantly different extracellular cellulase levels relative to wild type. Of interest, the Δrgs-2 mutant had no detectable activity, similar to the gna-3Q208L strain. In contrast, the Δrgs-1 and Δrgs-4 mutants and gna-1Q204L and gna-2Q205L strains exhibited significantly higher cellulase activity than wild type. With the exception of sexual development, our results demonstrate the greatest number of genetic interactions between rgs-1 and gna-1 and rgs-2 and gna-3 in N. crassa. [ABSTRACT FROM AUTHOR]

Background: With 9730 protein-coding genes and a nearly complete gene knockout strain collection, Neurospora crassa is a major model organism for filamentous fungi. Despite this abundance of information, the phenotypes of these gene knockout mutants have not been categorized to determine whether there are broad correlations between phenotype and any genetic features. Results: Here, we analyze data for 10 different growth or developmental phenotypes that have been obtained for 1168 N. crassa knockout mutants. Of these mutants, 265 (23%) are in the normal range, while 903 (77%) possess at least one mutant phenotype. With the exception of unclassified functions, the distribution of functional categories for genes in the mutant dataset mirrors that of the N. crassa genome. In contrast, most genes do not possess a yeast ortholog, suggesting that our analysis will reveal functions that are not conserved in Saccharomyces cerevisiae. To leverage the phenotypic data to identify pathways, we used weighted Partitioning Around Medoids (PAM) approach with 40 clusters. We found that genes encoding metabolic, transmembrane and protein phosphorylation-related genes are concentrated in subsets of clusters. Results from K-Means clustering of transcriptomic datasets showed that most phenotypic clusters contain multiple expression profiles, suggesting that co-expression is not generally observed for genes with shared phenotypes. Analysis of yeast orthologs of genes that co-clustered in MAPK signaling cascades revealed potential networks of interacting proteins in N. crassa. Conclusions: Our results demonstrate that clustering analysis of phenotypes is a promising tool for generating new hypotheses regarding involvement of genes in cellular pathways in N. crassa. Furthermore, information about gene clusters identified in N. crassa should be applicable to other filamentous fungi, including saprobes and pathogens. [ABSTRACT FROM AUTHOR]