Neurons of the Drosophila central brain fall into approximately 100 paired groups, termed lineages. Each lineage is derived from a single asymmetrically-dividing neuroblast. Embryonic neuroblasts produce 1,500 primary neurons (per hemisphere) that make up the larval CNS followed by a second mitotic period in the larva that generates approximately 10,000 secondary, adult-specific neurons. Clonal analyses based on previous works using lineage-specific Gal4 drivers have established that such lineages form highly invariant morphological units. All neurons of a lineage project as one or a few axon tracts (secondary axon tracts, SATs) with characteristic trajectories, thereby representing unique hallmarks. In the neuropil, SATs assemble into larger fiber bundles (fascicles) which interconnect different neuropil compartments. We have analyzed the SATs and fascicles formed by lineages during larval, pupal, and adult stages using antibodies against membrane molecules (Neurotactin/Neuroglian) and synaptic proteins (Bruchpilot/N-Cadherin). The use of these markers allows one to identify fiber bundles of the adult brain and associate them with SATs and fascicles of the larval brain. This work lays the foundation for assigning the lineage identity of GFP-labeled MARCM clones on the basis of their close association with specific SATs and neuropil fascicles, as described in the accompanying paper (Wong et al., 2013. Postembryonic lineages of the Drosophila brain: II. Identification of lineage projection patterns based on MARCM clones. Submitted.).
BACKGROUNDGWAS of schizophrenia demonstrated that variations in the non-coding regions are responsible for most of common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Thus, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease. In this study we use Cultured Neural progenitor cells derived from Olfactory Neuroepithelium (CNON) as a genetically unaltered cellular model to elucidate the neurodevelopmental aspects of schizophrenia.METHODSWe performed a gene expression study using RNA-Seq of CNON from 111 controls and 144 individuals with schizophrenia. Differentially expressed (DEX) genes were identified with DESeq2, using covariates to correct for sex, age, library batches and one surrogate variable component.RESULTS80 genes were DEX (FDR<10%), showing enrichment in cell migration, cell adhesion, developmental process, synapse assembly, cell proliferation and related gene ontology categories. Cadherin and Wnt signaling pathways were positive in overrepresentation test, and, in addition, many genes are specifically involved in Wnt5A signaling. The DEX genes were significantly, enriched in the genes overlapping SNPs with genome-wide significant association from the PGC GWAS of schizophrenia (PGC SCZ2). We also found substantial overlap with genes associated with other psychiatric disorders or brain development, enrichment in the same GO categories as genes with mutations de novo in schizophrenia, and studies of iPSC-derived neural progenitor cells.CONCLUSIONSCNON cells are a good model of the neurodevelopmental aspects of schizophrenia and can be used to elucidate the etiology of the disorder.
BackgroundRecently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known.ResultsHere, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5–10 molecules.ConclusionsBased on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3300-3) contains supplementary material, which is available to authorized users.
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