Control of Huntington's Disease-Associated Phenotypes by the Striatum-Enriched Transcription Factor Foxp2.

Alteration of corticostriatal glutamatergic function is an early pathophysiological change associated with Huntington's disease (HD). The factors that regulate the maintenance of corticostriatal glutamatergic synapses post-developmentally are not well understood. Recently, the striatum-enriched transcription factor Foxp2 was implicated in the development of these synapses. Here, we show that, in mice, overexpression of Foxp2 in the adult striatum of two models of HD leads to rescue of HD-associated behaviors, while knockdown of Foxp2 in wild-type mice leads to development of HD-associated behaviors. We note that Foxp2 encodes the longest polyglutamine repeat protein in the human reference genome, and we show that it can be sequestered into aggregates with polyglutamine-expanded mutant Huntingtin protein (mHTT). Foxp2 overexpression in HD model mice leads to altered expression of several genes associated with synaptic function, genes that present additional targets for normalization of corticostriatal dysfunction in HD.

Molecular adaptations of striatal spiny projection neurons during levodopa-induced dyskinesia.

Levodopa treatment is the major pharmacotherapy for Parkinson's disease. However, almost all patients receiving levodopa eventually develop debilitating involuntary movements (dyskinesia). Although it is known that striatal spiny projection neurons (SPNs) are involved in the genesis of this movement disorder, the molecular basis of dyskinesia is not understood. In this study, we identify distinct cell-type-specific gene-expression changes that occur in subclasses of SPNs upon induction of a parkinsonian lesion followed by chronic levodopa treatment. We identify several hundred genes, the expression of which is correlated with levodopa dose, many of which are under the control of activator protein-1 and ERK signaling. Despite homeostatic adaptations involving several signaling modulators, activator protein-1-dependent gene expression remains highly dysregulated in direct pathway SPNs upon chronic levodopa treatment. We also discuss which molecular pathways are most likely to dampen abnormal dopaminoceptive signaling in spiny projection neurons, hence providing potential targets for antidyskinetic treatments in Parkinson's disease.

Sequencing chromosomal abnormalities reveals neurodevelopmental loci that confer risk across diagnostic boundaries.

Balanced chromosomal abnormalities (BCAs) represent a relatively untapped reservoir of single-gene disruptions in neurodevelopmental disorders (NDDs). We sequenced BCAs in patients with autism or related NDDs, revealing disruption of 33 loci in four general categories: (1) genes previously associated with abnormal neurodevelopment (e.g., AUTS2, FOXP1, and CDKL5), (2) single-gene contributors to microdeletion syndromes (MBD5, SATB2, EHMT1, and SNURF-SNRPN), (3) novel risk loci (e.g., CHD8, KIRREL3, and ZNF507), and (4) genes associated with later-onset psychiatric disorders (e.g., TCF4, ZNF804A, PDE10A, GRIN2B, and ANK3). We also discovered among neurodevelopmental cases a profoundly increased burden of copy-number variants from these 33 loci and a significant enrichment of polygenic risk alleles from genome-wide association studies of autism and schizophrenia. Our findings suggest a polygenic risk model of autism and reveal that some neurodevelopmental genes are sensitive to perturbation by multiple mutational mechanisms, leading to variable phenotypic outcomes that manifest at different life stages.

Complex reorganization and predominant non-homologous repair following chromosomal breakage in karyotypically balanced germline rearrangements and transgenic integration.

We defined the genetic landscape of balanced chromosomal rearrangements at nucleotide resolution by sequencing 141 breakpoints from cytogenetically interpreted translocations and inversions. We confirm that the recently described phenomenon of 'chromothripsis' (massive chromosomal shattering and reorganization) is not unique to cancer cells but also occurs in the germline, where it can resolve to a relatively balanced state with frequent inversions. We detected a high incidence of complex rearrangements (19.2%) and substantially less reliance on microhomology (31%) than previously observed in benign copy-number variants (CNVs). We compared these results to experimentally generated DNA breakage-repair by sequencing seven transgenic animals, revealing extensive rearrangement of the transgene and host genome with similar complexity to human germline alterations. Inversion was the most common rearrangement, suggesting that a combined mechanism involving template switching and non-homologous repair mediates the formation of balanced complex rearrangements that are viable, stably replicated and transmitted unaltered to subsequent generations.

Next-generation sequencing strategies enable routine detection of balanced chromosome rearrangements for clinical diagnostics and genetic research.

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice.

Knocking out multigene redundancies via cycles of sexual assortment and fluorescence selection.

Phenotypes that might otherwise reveal a gene's function can be obscured by genes with overlapping function. This phenomenon is best known within gene families, in which an important shared function may only be revealed by mutating all family members. Here we describe the 'green monster' technology that enables precise deletion of many genes. In this method, a population of deletion strains with each deletion marked by an inducible green fluorescent protein reporter gene, is subjected to repeated rounds of mating, meiosis and flow-cytometric enrichment. This results in the aggregation of multiple deletion loci in single cells. The green monster strategy is potentially applicable to assembling other engineered alterations in any species with sex or alternative means of allelic assortment. To test the technology, we generated a single broadly drug-sensitive strain of Saccharomyces cerevisiae bearing precise deletions of all 16 ATP-binding cassette transporters within clades associated with multidrug resistance.

Synergistic drug combinations tend to improve therapeutically relevant selectivity.

Drug combinations are a promising strategy to overcome the compensatory mechanisms and unwanted off-target effects that limit the utility of many potential drugs. However, enthusiasm for this approach is tempered by concerns that the therapeutic synergy of a combination will be accompanied by synergistic side effects. Using large scale simulations of bacterial metabolism and 94,110 multi-dose experiments relevant to diverse diseases, we provide evidence that synergistic drug combinations are generally more specific to particular cellular contexts than are single agent activities. We highlight six combinations whose selective synergy depends on multitarget drug activity. For one anti-inflammatory example, we show how such selectivity is achieved through differential expression of the drugs' targets in cell types associated with therapeutic, but not toxic, effects and validate its therapeutic relevance in a rat model of asthma. The context specificity of synergistic combinations creates many opportunities for therapeutically relevant selectivity and enables improved control of complex biological systems.

Chemical combination effects predict connectivity in biological systems.

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured.

Large-scale mapping of human protein-protein interactions by mass spectrometry.

Mapping protein-protein interactions is an invaluable tool for understanding protein function. Here, we report the first large-scale study of protein-protein interactions in human cells using a mass spectrometry-based approach. The study maps protein interactions for 338 bait proteins that were selected based on known or suspected disease and functional associations. Large-scale immunoprecipitation of Flag-tagged versions of these proteins followed by LC-ESI-MS/MS analysis resulted in the identification of 24,540 potential protein interactions. False positives and redundant hits were filtered out using empirical criteria and a calculated interaction confidence score, producing a data set of 6463 interactions between 2235 distinct proteins. This data set was further cross-validated using previously published and predicted human protein interactions. In-depth mining of the data set shows that it represents a valuable source of novel protein-protein interactions with relevance to human diseases. In addition, via our preliminary analysis, we report many novel protein interactions and pathway associations.

Functional genomics and proteomics: charting a multidimensional map of the yeast cell.

The challenge of large-scale functional genomics projects is to build a comprehensive map of the cell including genome sequence and gene expression data, information on protein localization, structure, function and expression, post-translational modifications, molecular and genetic interactions and phenotypic descriptions. Some of this broad set of functional genomics data has been already assembled for the budding yeast. Even though molecular cartography of the yeast cell is still far from comprehensive, functional genomics has begun to forge connections between disparate cellular events and to foster numerous hypotheses. Here we review several different genomics and proteomics technologies and describe bioinformatics methods for exploring these data to make new discoveries.

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry.

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.