Genome-wide expression analysis of genetic networks in Neurospora crassa

Abstract

Abstract:The products of five structural genes and two regulatory genes of the qa gene cluster of Neurospora crassa control the metabolism of quinic acid (QA) as a carbon source. A detailed genetic network model of this metabolic process has been reported. This investigation is designed to expand the current model of the QA reaction network. The ensemble method of network identification was used to model RNA profiling data on the qa gene cluster. Through microarray and cluster analysis, genome-wide identification of RNA transcripts associated with quinic acid metabolism in N. crassa is described and suggests a connection to other metabolic circuits. More than 100 genes whose products include carbon metabolism, protein degradation and modification, amino acid metabolism and ribosome synthesis appear to be connected to quinic acid metabolism. The core of the qa gene cluster network is validated with respect to RNA profiling data obtained from microarrays.Keywords: genetic networks; quinic acid; qa gene cluster; genome; microarray Background:Advances in systems biology and the relative ease of manipulating eukaryotic microorganisms such as fungi have made it possible to elucidate a complex trait such as how a cell metabolizes a carbon source. The genetics of the metabolism of the carbon compound quinic acid in Neurospora crassa is one of the early paradigms for eukaryotic gene regulation with the support of over four decades of genetics and biochemistry. [2] The network involves 54 reactions and 38 macromolecules and small molecules and is based on a kinetics framework [3] and experimental data generated over a span of more than three decades. [4] In the diagram, circles, boxes and arrows depict, reactions, molecular species, and the flow of reactants and products for the reaction proceeding "forward". Reactions without outgoing arrows (lollipops), indicate decay reactions. Reactants include the seven genes of the qa gene cluster (qa-x, qa-2, qa-3, qa-4, qa-y, qa-1S, qa-1F) [1] with superscripts "0" or "1" indicating the presence or absence, respectively, of a bound transcriptional activator, encoded by the qa-1F gene. These genes are transcribed into RNA molecules (superscript r), which in turn are translated into protein products (in capital letters). Four out of seven proteins have been demonstrated by experimental means to participate in a known biochemical pathway at the bottom of the diagram. There are at least two cellular states for quinic acid, extracellular (depicted as QA

Systems Biology of the Clock in Neurospora crassa

“…Dial-down was achieved by shifting liquid cultures from 0.3% quinic acid to 2% galactose. Strain 74A-OR23-1A was used in shift experiments from sucrose (1.5%) to quinic acid (.3%) as a control to identify QA inducible genes [27]. Strain 93-4 ( frq − ) qa:frq + transformed with pDE3dBH qa:frq + was kindly provided by Deborah Bell-Pedersen (Biology Department, Texas A & M University) to test for auto-feedback loops in wc-1 and wc-2 .…”

Systems Biology of the qa Gene Cluster in Neurospora crassa

“…There are now only 300 genes in Figure 2 responding to the shift in experiment 1-QA response when compared to the control experiment. Many of the same functional categories are seen, such as amino acid metabolism and carbohydrate metabolism in Figure 2 as in Figure 2 of [5], but the number of identified responders is dramatically less. It is clear that the use of the control experiment has a significant effect on filtering for QA-responsive genes.…”

“…Previously we used a simple unpaired t-test to compare mRNA levels of cells grown on glucose to those grown on QA (Figure 2, [5]). A total of 895 genes with QA upstream response elements (QAREs) were identified as candidates for QA-responsive genes.…”

A Tool Set for the Genome-Wide Analysis ofNeurospora crassaby RT-PCR

“…To identify genes with near-constant expression in Neurospora, we examined the global gene expression profiles in Neurospora informed by previous RNA-Seq and microarray experiments/studies ( Hurley et al 2014 ; Wu et al 2014 ; Logan et al 2007 ). Using our analysis ( Materials and Methods ) we assigned a prediction interval ranking score (PIRS) to each gene.…”

“…Recently, extensive analyses of mRNA output via deep sequencing of mRNA levels as well as microarray analyses in Neurospora have thoroughly described circadian gene expression, as well as the organism’s response to light and to addition of quinic acid ( Hurley et al 2014 ; Logan et al 2007 ; Wu et al 2014 ; Sancar et al 2015 ). By probing these data sets, we have identified genes that can potentially serve as stably expressed reference genes when tracking changes in mRNA levels under various experimental conditions.…”