Origins and Proliferative States of Human Oligodendrocyte Precursor Cells.

Human cerebral cortex size and complexity has increased greatly during evolution. While increased progenitor diversity and enhanced proliferative potential play important roles in human neurogenesis and gray matter expansion, the mechanisms of human oligodendrogenesis and white matter expansion remain largely unknown. Here, we identify EGFR-expressing "Pre-OPCs" that originate from outer radial glial cells (oRGs) and undergo mitotic somal translocation (MST) during division. oRG-derived Pre-OPCs provide an additional source of human cortical oligodendrocyte precursor cells (OPCs) and define a lineage trajectory. We further show that human OPCs undergo consecutive symmetric divisions to exponentially increase the progenitor pool size. Additionally, we find that the OPC-enriched gene, PCDH15, mediates daughter cell repulsion and facilitates proliferation. These findings indicate properties of OPC derivation, proliferation, and dispersion important for human white matter expansion and myelination

Single-cell genomics identifies cell type-specific molecular changes in autism.

Despite the clinical and genetic heterogeneity of autism, bulk gene expression studies show that changes in the neocortex of autism patients converge on common genes and pathways. However, direct assessment of specific cell types in the brain affected by autism has not been feasible until recently. We used single-nucleus RNA sequencing of cortical tissue from patients with autism to identify autism-associated transcriptomic changes in specific cell types. We found that synaptic signaling of upper-layer excitatory neurons and the molecular state of microglia are preferentially affected in autism. Moreover, our results show that dysregulation of specific groups of genes in cortico-cortical projection neurons correlates with clinical severity of autism. These findings suggest that molecular changes in upper-layer cortical circuits are linked to behavioral manifestations of autism

Immature excitatory neurons develop during adolescence in the human amygdala

The human amygdala grows during childhood, and its abnormal development is linked to mood disorders. The primate amygdala contains a large population of immature neurons in the paralaminar nuclei (PL), suggesting protracted development and possibly neurogenesis. Here we studied human PL development from embryonic stages to adulthood. The PL develops next to the caudal ganglionic eminence, which generates inhibitory interneurons, yet most PL neurons express excitatory markers. In children, most PL cells are immature (DCX+PSA-NCAM+), and during adolescence many transition into mature (TBR1+VGLUT2+) neurons. Immature PL neurons persist into old age, yet local progenitor proliferation sharply decreases in infants. Using single nuclei RNA sequencing, we identify the transcriptional profile of immature excitatory neurons in the human amygdala between 4–15 years. We conclude that the human PL contains excitatory neurons that remain immature for decades, a possible substrate for persistent plasticity at the interface of the hippocampus and amygdala

Neuronal vulnerability and multilineage diversity in multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disease with a relapsing-remitting disease course at early stages, distinct lesion characteristics in cortical grey versus subcortical white matter and neurodegeneration at chronic stages. Here we used single-nucleus RNA sequencing to assess changes in expression in multiple cell lineages in MS lesions and validated the results using multiplex in situ hybridization. We found selective vulnerability and loss of excitatory CUX2-expressing projection neurons in upper-cortical layers underlying meningeal inflammation; such MS neuron populations exhibited upregulation of stress pathway genes and long non-coding RNAs. Signatures of stressed oligodendrocytes, reactive astrocytes and activated microglia mapped most strongly to the rim of MS plaques. Notably, single-nucleus RNA sequencing identified phagocytosing microglia and/or macrophages by their ingestion and perinuclear import of myelin transcripts, confirmed by functional mouse and human culture assays. Our findings indicate lineage- and region-specific transcriptomic changes associated with selective cortical neuron damage and glial activation contributing to progression of MS lesions.Includes NIHR, ERC and Wellcome Trust

Analysis of Region-Specific Transcriptomic Changes in the Autistic Brain

Autism is a highly prevalent neurodevelopmental disorder that affects 1 in every 68 children in the US. Autism comprises a spectrum of highly heterogeneous disorders defined by characteristic deficits of communication and by presence of repetitive and stereotyped behavior. At the same time the disease is highly heritable and genetically heterogeneous, with hundreds of genetic variants that have been associated with it. Previous systems biology studies have provided first insights into convergence of various disease-associated genetic variants onto specific pathways, developmental windows and cell types in the brain. Additionally, transcriptomic and epigenetic studies have identified genes and pathways affected by common molecular pathology in autism. However, previous studies lacked special resolution, have not investigated commonalities and differences in transcriptomic and epigenetic changes across specific brain regions in autism, have not linked epigenetic changes to transcriptional regulation in the disease and have not looked at other levels of transcriptional control rather than gene expression, such as alternative splicing and expression of long noncoding RNAs. In my dissertation I attempt to fill in these gaps by performing analysis of antisense RNA expression in the autistic brain and by performing RNA sequencing and DNA methylation analysis of 6 different cortical regions of autism patients and controls. I demonstrate that many autism-associated genomic loci express antisense noncoding RNAs, with some of them upregulated in the cortex of autism patients. I have also developed an automated user-friendly tool to perform RNA sequencing data analysis and applied it to a large cohort of RNA-seq samples to identify differentially expressed protein-coding genes and long noncoding RNAs, with many genes and pathways recurring in multiple regions and patient cohorts. Finally, I identify convergence of transcriptomic changes of the frontal cortical regions in autism on common genes and pathways and a divergent effect of the pathology on gene expression and alternative splicing in the prefrontal and frontoinsular cortices in autism. The results of the study prompt to investigate dysfuntion of the insular cortex in autism and provide high-confidence autism gene candidates for further functional studies

Expression of non-protein-coding antisense RNAs in genomic regions related to autism spectrum disorders

BACKGROUND: Autism spectrum disorders (ASD) manifest with neurodevelopmental phenotypes including communicative, social and behavioral impairments that affect as many as 1 in 88 children. The majority of autism cases have no known genetic cause, suggesting complex genetics of the disorder, but a few genes of large effect have been identified. METHODS: In order to identify novel ASD genetic correlates, we investigated non-protein coding RNAs (ncRNAs) which are abundantly transcribed from the human genome, enriched in the brain, and have been implicated in neurodevelopmental disorders. Using an algorithm that we developed, we examined a publicly available transcriptomics database, AceView, to identify the natural antisense transcripts (NATs) that overlap with known autism-related genes. We validated the presence and differential expression of NATs in different brain regions of ASD and control brains using qRT-PCR. Additionally, we investigated the subcellular localization of these transcripts in a neuronal cell line using RNA-sequencing (RNA-seq). RESULTS: We found noncoding antisense RNA transcripts at approximately 40% of loci previously implicated in ASD. We confirmed the expression of 10 antisense RNAs in different postmortem human brain tissues. The expression of five antisense transcripts was found to be region-specific, suggesting a role for these ncRNAs in the development and function of specific brain regions. Some antisense RNAs overlapping suspected ASD genes exhibited concordant expression relative to their sense protein-coding genes, while other sense-antisense pairs demonstrate a discordant relationship. Interestingly, the antisense RNA corresponding to the SYNGAP1 locus (SYNGAP1-AS) was found to be differentially expressed in brain regions of patients with ASD compared to control individuals. RNA-seq analysis of subcellular compartments from SH-SY5Y human neuroblastoma cells demonstrated that antisense RNAs to ASD candidate genes are predominantly expressed in the nucleoplasmic or chromatin compartments, implying their involvement in nuclear-associated processes. CONCLUSIONS: Our data suggests that NATs are abundantly expressed from ASD-related loci and provide evidence for their roles in target gene regulation, neurodevelopment and autism pathogenesis. This class of RNA should therefore be considered in functional studies aimed at understanding genetic risk factors for ASD

De-repressing LncRNA-Targeted Genes to Upregulate Gene Expression: Focus on Small Molecule Therapeutics

Non-protein coding RNAs (ncRNAs) make up the overwhelming majority of transcripts in the genome and have recently gained attention for their complex regulatory role in cells, including the regulation of protein-coding genes. Furthermore, ncRNAs play an important role in normal development and their expression levels are dysregulated in several diseases. Recently, several long noncoding RNAs (lncRNAs) have been shown to alter the epigenetic status of genomic loci and suppress the expression of target genes. This review will present examples of such a mechanism and focus on the potential to target lncRNAs for achieving therapeutic gene upregulation by de-repressing genes that are epigenetically silenced in various diseases. Finally, the potential to target lncRNAs, through their interactions with epigenetic enzymes, using various tools, such as small molecules, viral vectors and antisense oligonucleotides, will be discussed. We suggest that small molecule modulators of a novel class of drug targets, lncRNA-protein interactions, have great potential to treat some cancers, cardiovascular disease, and neurological disorders

CANEapp: a user-friendly application for automated next generation transcriptomic data analysis

Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers. To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app . We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups