Lack of nAChR Activity Depresses Cochlear Maturation and Up-Regulates GABA System Components: Temporal Profiling of Gene Expression in α9 Null Mice

It has previously been shown that deletion of chrna9, the gene encoding the alpha9 nicotinic acetylcholine receptor (nAChR) subunit, results in abnormal synaptic terminal structure. Additionally, all nAChR-mediated cochlear activity is lost, as characterized by a failure of the descending efferent system to suppress cochlear responses to sound. In an effort to characterize the molecular mechanisms underlying the structural and functional consequences following loss of alpha9 subunit expression, we performed whole-transcriptome gene expression analyses on cochleae of wild type and alpha9 knockout (alpha9(-/-)) mice during postnatal days spanning critical periods of synapse formation and maturation.Data revealed that loss of alpha9 receptor subunit expression leads to an up-regulation of genes involved in synaptic transmission and ion channel activity. Unexpectedly, loss of alpha9 receptor subunit expression also resulted in an increased expression of genes encoding GABA receptor subunits and the GABA synthetic enzyme, glutamic acid decarboxylase. These data suggest the existence of a previously unrecognized association between the nicotinic cholinergic and GABAergic systems in the cochlea. Computational analyses have highlighted differential expression of several gene sets upon loss of nicotinic cholinergic activity in the cochlea. Time-series analysis of whole transcriptome patterns, represented as self-organizing maps, revealed a disparate pattern of gene expression between alpha9(-/-) and wild type cochleae at the onset of hearing (P13), with knockout samples resembling immature postnatal ages.We have taken a systems biology approach to provide insight into molecular programs influenced by the loss of nicotinic receptor-based cholinergic activity in the cochlea and to identify candidate genes that may be involved in nicotinic cholinergic synapse formation, stabilization or function within the inner ear. Additionally, our data indicate a change in the GABAergic system upon loss of alpha9 nicotinic receptor subunit within the cochlea

Synthetic lethal analysis of Caenorhabditis elegans posterior embryonic patterning genes identifies conserved genetic interactions

Phenotypic robustness is evidenced when single-gene mutations do not result in an obvious phenotype. It has been suggested that such phenotypic stability results from 'buffering' activities of homologous genes as well as non-homologous genes acting in parallel pathways. One approach to characterizing mechanisms of phenotypic robustness is to identify genetic interactions, specifically, double mutants where buffering is compromised. To identify interactions among genes implicated in posterior patterning of the Caenorhabditis elegans embryo, we measured synthetic lethality following RNA interference of 22 genes in 15 mutant strains. A pair of homologous T-box transcription factors (tbx-8 and tbx-9) is found to interact in both C. elegans and C. briggsae, indicating that their compensatory function is conserved. Furthermore, a muscle module is defined by transitive interactions between the MyoD homolog hlh-1, another basic helix-loop-helix transcription factor, hnd-1, and the MADS-box transcription factor unc-120. Genetic interactions within a homologous set of genes involved in vertebrate myogenesis indicate broad conservation of the muscle module and suggest that other genetic modules identified in C. elegans will be conserved

The homeodomain protein PAL-1 specifies a lineage-specific regulatory network in the C. elegans embryo

Maternal and zygotic activities of the homeodomain protein PAL-1 specify the identity and maintain the development of the multipotent C blastomere lineage in the C. elegans embryo. To identify PAL-1 regulatory target genes, we used microarrays to compare transcript abundance in wild-type embryos with mutant embryos lacking a C blastomere and to mutant embryos with extra C blastomeres. pal-1-dependent C-lineage expression was verified for select candidate target genes by reporter gene analysis, though many of the target genes are expressed in additional lineages as well. The set of validated target genes includes 12 transcription factors, an uncharacterized wingless ligand and five uncharacterized genes. Phenotypic analysis demonstrates that the identified PAL-1 target genes affect specification, differentiation and morphogenesis of C-lineage cells. In particular, we show that cell fate-specific genes (or tissue identity genes) and a posterior HOX gene are activated in lineage-specific fashion. Transcription of targets is initiated in four temporal phases, which together with their spatial expression patterns leads to a model of the regulatory network specified by PAL-1

Evaluation of Normalization Procedures for Oligonucleotide Array Data Based On Spiked cRNA Controls

Background: Affymetrix oligonucleotide arrays simultaneously measure the abundances of thousands of mRNAs in biological samples. Comparability of array results is necessary for the creation of large-scale gene expression databases. The standard strategy for normalizing oligonucleotide array readouts has practical drawbacks. We describe alternative normalization procedures for oligonucleotide arrays based on a common pool of known biotin-labeled cRNAs spiked into each hybridization. Results: We first explore the conditions for validity of the 'constant mean assumption', the key assumption underlying current normalization methods. We introduce 'frequency normalization', a 'spike-in'-based normalization method which estimates array sensitivity, reduces background noise and allows comparison between array designs. This approach does not rely on the constant mean assumption and so can be effective in conditions where standard procedures fail. We also define 'scaled frequency', a hybrid normalization method relying on both spiked transcripts and the constant mean assumption while maintaining all other advantages of frequency normalization. We compare these two procedures to a standard global normalization method using experimental data. We also use simulated data to estimate accuracy and investigate the effects of noise. We find that scaled frequency is as reproducible and accurate as global normalization while offering several practical advantages. Conclusions: Scaled frequency quantitation is a convenient, reproducible technique that performs as well as global normalization on serial experiments with the same array design, while offering several additional features. Specifically, the scaled-frequency method enables the comparison of expression measurements across different array designs, yields estimates of absolute message abundance in cRNA and determines the sensitivity of individual arrays.Molecular and Cellular Biolog

Synthetic Lethal Analysis of Caenorhabditis elegans Posterior Embryonic Patterning Genes Identifies Conserved Genetic Interactions

Phenotypic robustness is evidenced when single-gene mutations do not result in an obvious phenotype. It has been suggested that such phenotypic stability results from 'buffering' activities of homologous genes as well as non-homologous genes acting in parallel pathways. One approach to characterizing mechanisms of phenotypic robustness is to identify genetic interactions, specifically, double mutants where buffering is compromised. To identify interactions among genes implicated in posterior patterning of the Caenorhabditis elegans embryo, we measured synthetic lethality following RNA interference of 22 genes in 15 mutant strains. A pair of homologous T-box transcription factors (tbx-8 and tbx-9) is found to interact in both C. elegans and C. briggsae, indicating that their compensatory function is conserved. Furthermore, a muscle module is defined by transitive interactions between the MyoD homolog hlh-1, another basic helix-loop-helix transcription factor, hnd-1, and the MADS-box transcription factor unc-120. Genetic interactions within a homologous set of genes involved in vertebrate myogenesis indicate broad conservation of the muscle module and suggest that other genetic modules identified in C. elegans will be conserved.Molecular and Cellular Biolog

Pairing of Competitive and Topologically Distinct Regulatory Modules Enhances Patterned Gene Expression

Biological networks are inherently modular, yet little is known about how modules are assembled to enable coordinated and complex functions. We used RNAi and time series, whole-genome microarray analyses to systematically perturb and characterize components of a Caenorhabditis elegans lineage-specific transcriptional regulatory network. These data are supported by selected reporter gene analyses and comprehensive yeast one-hybrid and promoter sequence analyses. Based on these results, we define and characterize two modules composed of muscle- and epidermal-specifying transcription factors that function together within a single cell lineage to robustly specify multiple cell types. The expression of these two modules, although positively regulated by a common factor, is reliably segregated among daughter cells. Our analyses indicate that these modules repress each other, and we propose that this cross-inhibition coupled with their relative time of induction function to enhance the initial asymmetry in their expression patterns, thus leading to the observed invariant gene expression patterns and cell lineage. The coupling of asynchronous and topologically distinct modules may be a general principle of module assembly that functions to potentiate genetic switches.Molecular and Cellular Biolog

Assessment of network module identification across complex diseases

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the 'Disease Module Identification DREAM Challenge', an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology