Microarrays and the microscope: balancing throughput with resolution

Functional genomics of the brain: uncovering networks in the CNS using a systems approach

The central nervous system (CNS) is undoubtedly the most complex human organ system in terms of its diverse functions, cellular composition, and connections. Attempts to capture this diversity experimentally were the foundation on which the field of neurobiology was built. Until now though, techniques were either painstakingly slow or insufficient in capturing this heterogeneity. In addition, the combination of multiple layers of information needed for a complete picture of neuronal diversity from the epigenome to the proteome requires an even more complex compilation of data. In this era of high-throughput genomics though, the ability to isolate and profile neurons and brain tissue has increased tremendously and now requires less effort. Both microarrays and next-generation sequencing have identified neuronal transcriptomes and signaling networks involved in normal brain development, as well as in disease. However, the expertise needed to organize and prioritize the resultant data remains substantial. A combination of supervised organization and unsupervised analyses are needed to fully appreciate the underlying structure in these datasets. When utilized effectively, these analyses have yielded striking insights into a number of fundamental questions in neuroscience on topics ranging from the evolution of the human brain to neuropsychiatric and neurodegenerative disorders. Future studies will incorporate these analyses with behavioral and physiological data from patients to more efficiently move toward personalized therapeutics.

Integrative gene-tissue microarray-based approach for identification of human disease biomarkers: application to amyotrophic lateral sclerosis

Advances in genomics and proteomics permit rapid identification of disease-relevant genes and proteins. Challenges include biological differences between animal models and human diseases, high discordance between DNA and protein expression data and a lack of experimental models to study human complex diseases. To overcome some of these limitations, we developed an integrative approach using animal models, postmortem human material and a combination of high-throughput microarray methods to identify novel molecular markers of amyotrophic lateral sclerosis (ALS). We used laser capture microdissection coupled with microarrays to identify early transcriptome changes occurring in spinal cord motor neurons or surrounding glial cells. Two models of familial motor neuron disease, SOD1(G93A) and TAU(P301L), transgenic mice were used at the presymptomatic stage. Identified gene expression changes were predominantly model-specific. However, several genes were regulated in both models. The relevance of identified genes as clinical biomarkers was tested in the peripheral blood transcriptome of presymptomatic SOD1(G93A) animals using custom-designed ALS microarray. To confirm the relevance of identified genes in human sporadic ALS (SALS), selected corresponding protein products were examined by high-throughput immunoassays using tissue microarrays constructed from human postmortem spinal cord tissues. Genes that were identified by these experiments and located within a linkage region associated with familial ALS/frontotemporal dementia were sequenced in several families. This large-scale gene and protein expression study pointing to distinct molecular mechanisms of TAU- and SOD1-induced motor neuron degeneration identified several new SALS-relevant proteins (CNGA3, CRB1, OTUB2, MMP14, SLK, DDX58, RSPO2) and putative blood biomarkers, including Nefh, Prph and Mgll.

Neuroscience in the era of functional genomics and systems biology

Advances in genetics and genomics have fuelled a revolution in discovery-based, or hypothesis-generating, research that provides a powerful complement to the more directly hypothesis-driven molecular, cellular and systems neuroscience. Genetic and functional genomic studies have already yielded important insights into neuronal diversity and function, as well as disease. One of the most exciting and challenging frontiers in neuroscience involves harnessing the power of large-scale genetic, genomic and phenotypic data sets, and the development of tools for data integration and mining. Methods for network analysis and systems biology offer the promise of integrating these multiple levels of data, connecting molecular pathways to nervous system function.

Gene expression analysis of neural cells and tissues using DNA microarrays

DNA microarrays pose specific challenges to those studying the central and peripheral nervous systems. Probably the most important involve difficulty in obtaining appropriate tissue for study, as well as the problems posed by cellular heterogeneity. This unit describes advances in the available technologies and provides protocols for cDNA microarray hybridization, including the use of PCR amplicons. Protocols are also provided for the two major methods for limiting cellular heterogeneity by study of RNA from single cell populations in high-throughput microarray studies, laser capture microdissection (LCM), and automated fluorescent cell sorting (FACS-array).

Molecular profiling of striatonigral and striatopallidal medium spiny neurons past, present, and future

Defining distinct molecular properties of the two striatal medium spiny neurons (MSNs) has been a challenging task for basal ganglia (BG) neuroscientists. Identifying differential molecular components in each MSN subtype is crucial for BG researchers to understand functional properties of these two neurons. The two MSN populations are morphologically identical except in their projections through the direct verses indirect BG pathways and they are heterogeneously dispersed throughout the dorsal striatum (dStr) and nucleus accumbens (NAc). These characteristics have made it difficult for researchers to distinguish and isolate these two neuronal populations thereby hindering progress toward a more comprehensive understanding of their differential molecular properties. Researchers began to investigate molecular differences in the striatonigral and striatopallidal neurons using in situ hybridization (ISH) techniques and single cell reverse transcription-polymerase chain reaction (scRT-PCR). Currently the field is utilizing more advanced techniques for large-scale gene expression studies including fluorescence activated cell sorting (FACS) of MSNs, from which RNA is purified, from fluorescent reporter transgenic mice or use of transgenic mice in which ribosomes from each MSN are tagged and can be immunoprecipitated followed by RNA isolation, a technique termed translating ribosomal affinity purification (TRAP). Additionally, the availability of fluorescent reporter mice for each MSN subtype is allowing, scientists to perform more accurate histology studies evaluating differential protein expression and signaling changes in each cell subtype. Finally, researchers are able to evaluate the role of specific genes in vivo by utilizing cell type-specific mouse models including Cre driver lines that can be crossed with conditional overexpression or knockout systems. This is a very exciting time in the BG field because researchers are well equipped with the most progressive tools to comprehensively evaluate molecular components in the two MSNs and their consequence on BG functional output in the normal, diseased, and developing brain.

Complementary RNA amplification methods enhance microarray identification of transcripts expressed in the C. elegans nervous system

Background

DNA microarrays provide a powerful method for global analysis of gene expression. The application of this technology to specific cell types and tissues, however, is typically limited by small amounts of available mRNA, thereby necessitating amplification. Here we compare microarray results obtained with two different methods of RNA amplification to profile gene expression in the C. elegans larval nervous system.

Results

We used the mRNA-tagging strategy to isolate transcripts specifically from C. elegans larval neurons. The WT-Ovation Pico System (WT-Pico) was used to amplify 2 ng of pan-neural RNA to produce labeled cDNA for microarray analysis. These WT-Pico-derived data were compared to microarray results obtained with a labeled aRNA target generated by two rounds of In Vitro Transcription (IVT) of 25 ng of pan-neural RNA. WT-Pico results in a higher fraction of present calls than IVT, a finding consistent with the proposal that DNA-DNA hybridization results in lower mismatch signals than the RNA-DNA heteroduplexes produced by IVT amplification. Microarray data sets from these samples were compared to a reference profile of all larval cells to identify transcripts with elevated expression in neurons. These results were validated by the high proportion of known neuron-expressed genes detected in these profiles and by promoter-GFP constructs for previously uncharacterized genes in these data sets. Together, the IVT and WT-Pico methods identified 2,173 unique neuron-enriched transcripts. Only about half of these transcripts (1,044), however, are detected as enriched by both IVT and WT-Pico amplification.

Conclusion

We show that two different methods of RNA amplification, IVT and WT-Pico, produce valid microarray profiles of gene expression in the C. elegans larval nervous system with a low rate of false positives. However, our results also show that each method of RNA amplification detects a unique subset of bona fide neural-enriched transcripts and thus a wider array of authentic neural genes are identified by the combination of these data sets than by the microarray profiles obtained with either method of RNA amplification alone. With its relative ease of implementation and greater sensitivity, WT-Pico is the preferred method of amplification for cases in which sample RNA is limiting.