Evaluation of sense-strand mRNA amplification by comparative quantitative PCR

BACKGROUND: RNA amplification is required for incorporating laser-capture microdissection techniques into microarray assays. However, standard oligonucleotide microarrays contain sense-strand probes, so traditional T7 amplification schemes producing anti-sense RNA are not appropriate for hybridization when combined with conventional reverse transcription labeling methods. We wished to assess the accuracy of a new sense-strand RNA amplification method by comparing ratios between two samples using quantitative real-time PCR (qPCR), mimicking a two-color microarray assay. RESULTS: We performed our validation using qPCR. Three samples of rat brain RNA and three samples of rat liver RNA were amplified using several kits (Ambion messageAmp, NuGen Ovation, and several versions of Genisphere SenseAmp). Results were assessed by comparing the liver/brain ratio for 192 mRNAs before and after amplification. In general, all kits produced strong correlations with unamplified RNAs. The SenseAmp kit produced the highest correlation, and was also able to amplify a partially degraded sample accurately. CONCLUSION: We have validated an optimized sense-strand RNA amplification method for use in comparative studies such as two-color microarrays

Single-Cell RNA-Seq of Mouse Dopaminergic Neurons Informs Candidate Gene Selection for Sporadic Parkinson Disease.

Genetic variation modulating risk of sporadic Parkinson disease (PD) has been primarily explored through genome-wide association studies (GWASs). However, like many other common genetic diseases, the impacted genes remain largely unknown. Here, we used single-cell RNA-seq to characterize dopaminergic (DA) neuron populations in the mouse brain at embryonic and early postnatal time points. These data facilitated unbiased identification of DA neuron subpopulations through their unique transcriptional profiles, including a postnatal neuroblast population and substantia nigra (SN) DA neurons. We use these population-specific data to develop a scoring system to prioritize candidate genes in all 49 GWAS intervals implicated in PD risk, including genes with known PD associations and many with extensive supporting literature. As proof of principle, we confirm that the nigrostriatal pathway is compromised in Cplx1-null mice. Ultimately, this systematic approach establishes biologically pertinent candidates and testable hypotheses for sporadic PD, informing a new era of PD genetic research

Universal prediction of cell-cycle position using transfer learning.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. Results: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays. Conclusions: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data. Keywords: Cell cycle; Single-cell RNA-sequencing; Transfer learning.Chan Zuckerberg Initiative DAF Silicon Valley Community Foundation United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) Appeared in source as:National Institute of General Medical Sciences of the National Institutes of Health National Science Foundation (NSF) National Institute of Agin Maryland Stem Cell Research Foundation Kavli Neurodiscovery Institute Johns Hopkins Provost Award Program BRAIN Initiative United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Neurological Disorders & Stroke (NINDS) Appeared in source as:National Institute of Neurological Disorder

Spatiotemporal expression and transcriptional perturbations by long noncoding RNAs in the mouse brain

Long noncoding RNAs (lncRNAs) have been implicated in numerous cellular processes including brain development. However, the in vivo expression dynamics and molecular pathways regulated by these loci are not well understood. Here, we leveraged a cohort of 13 lncRNA-null mutant mouse models to investigate the spatiotemporal expression of lncRNAs in the developing and adult brain and the transcriptome alterations resulting from the loss of these lncRNA loci. We show that several lncRNAs are differentially expressed both in time and space, with some presenting highly restricted expression in only selected brain regions. We further demonstrate altered regulation of genes for a large variety of cellular pathways and processes upon deletion of the lncRNA loci. Finally, we found that 4 of the 13 lncRNAs significantly affect the expression of several neighboring protein-coding genes in a cis-like manner. By providing insight into the endogenous expression patterns and the transcriptional perturbations caused by deletion of the lncRNA locus in the developing and postnatal mammalian brain, these data provide a resource to facilitate future examination of the specific functional relevance of these genes in neural development, brain function, and disease.National Science Foundation (U.S.) (Postdoctoral Research Fellowship in Biology DBI-0905973

DNMT1-interacting RNAs block gene specific DNA methylation

Summary DNA methylation was described almost a century ago. However, the rules governing its establishment and maintenance remain elusive. Here, we present data demonstrating that active transcription regulates levels of genomic methylation. We identified a novel RNA arising from the CEBPA gene locus critical in regulating the local DNA methylation profile. This RNA binds to DNMT1 and prevents CEBPA gene locus methylation. Deep sequencing of transcripts associated with DNMT1 combined with genome-scale methylation and expression profiling extended the generality of this finding to numerous gene loci. Collectively, these results delineate the nature of DNMT1-RNA interactions and suggest strategies for gene selective demethylation of therapeutic targets in disease

Ago2 Immunoprecipitation Identifies Predicted MicroRNAs in Human Embryonic Stem Cells and Neural Precursors

MicroRNAs are required for maintenance of pluripotency as well as differentiation, but since more microRNAs have been computationally predicted in genome than have been found, there are likely to be undiscovered microRNAs expressed early in stem cell differentiation.SOLiD ultra-deep sequencing identified >10(7) unique small RNAs from human embryonic stem cells (hESC) and neural-restricted precursors that were fit to a model of microRNA biogenesis to computationally predict 818 new microRNA genes. These predicted genomic loci are associated with chromatin patterns of modified histones that are predictive of regulated gene expression. 146 of the predicted microRNAs were enriched in Ago2-containing complexes along with 609 known microRNAs, demonstrating association with a functional RISC complex. This Ago2 IP-selected subset was consistently expressed in four independent hESC lines and exhibited complex patterns of regulation over development similar to previously-known microRNAs, including pluripotency-specific expression in both hESC and iPS cells. More than 30% of the Ago2 IP-enriched predicted microRNAs are new members of existing families since they share seed sequences with known microRNAs.Extending the classic definition of microRNAs, this large number of new microRNA genes, the majority of which are less conserved than their canonical counterparts, likely represent evolutionarily recent regulators of early differentiation. The enrichment in Ago2 containing complexes, the presence of chromatin marks indicative of regulated gene expression, and differential expression over development all support the identification of 146 new microRNAs active during early hESC differentiation

Gene co-regulation by Fezf2 selects neurotransmitter identity and connectivity of corticospinal neurons

The neocortex contains an unparalleled diversity of neuronal subtypes, each defined by distinct traits that are developmentally acquired under the control of subtype-specific and pan-neuronal genes. The regulatory logic that orchestrates the expression of these unique combinations of genes is unknown for any class of cortical neuron. Here, we report that Fezf2 is a selector gene able to regulate the expression of gene sets that collectively define mouse corticospinal motor neurons (CSMN). We find that Fezf2 directly induces the glutamatergic identity of CSMN via activation of Vglut1 (Slc17a7) and inhibits a GABAergic fate by repressing transcription of Gad1. In addition, we identify the axon guidance receptor EphB1 as a target of Fezf2 necessary to execute the ipsilateral extension of the corticospinal tract. Our data indicate that co-regulated expression of neuron subtype–specific and pan-neuronal gene batteries by a single transcription factor is one component of the regulatory logic responsible for the establishment of CSMN identity

Topological organization of multichromosomal regions by the long intergenic noncoding RNA Firre

RNA, including long noncoding RNA (lncRNA), is known to be an abundant and important structural component of the nuclear matrix. However, the molecular identities, functional roles and localization dynamics of lncRNAs that influence nuclear architecture remain poorly understood. Here, we describe one lncRNA, Firre, that interacts with the nuclear-matrix factor hnRNPU through a 156-bp repeating sequence and localizes across an ~5-Mb domain on the X chromosome. We further observed Firre localization across five distinct trans-chromosomal loci, which reside in spatial proximity to the Firre genomic locus on the X chromosome. Both genetic deletion of the Firre locus and knockdown of hnRNPU resulted in loss of colocalization of these trans-chromosomal interacting loci. Thus, our data suggest a model in which lncRNAs such as Firre can interface with and modulate nuclear architecture across chromosomes

methods-CuffFeatureSet.R methods-CuffGene.R methods-CuffFeature.R tools.R

Cufflinks high-throughput sequencing data. Version 2.3.