Stephen A. Fisher

Transcriptome in vivo analysis (TIVA) of spatially defined single cells in live tissue

Transcriptome profiling of single cells resident in their natural microenvironment depends upon RNA capture methods that are both noninvasive and spatially precise. We engineered a transcriptome in vivo analysis (TIVA) tag, which upon photoactivation enables mRNA capture from single cells in live tissue. Using the TIVA tag in combination with RNA sequencing (RNA-seq), we analyzed transcriptome variance among single neurons in culture and in mouse and human tissue in vivo. Our data showed that the tissue microenvironment shapes the transcriptomic landscape of individual cells. The TIVA methodology is, to our knowledge, the first noninvasive approach for capturing mRNA from live single cells in their natural microenvironment.

Cytoplasmic Intron Sequence-Retaining Transcripts Can Be Dendritically Targeted via ID Element Retrotransposons

RNA precursors give rise to mRNA after splicing of intronic sequences traditionally thought to occur in the nucleus. Here, we show that intron sequences are retained in a number of dendritically-targeted mRNAs, by using microarray and Illumina sequencing of isolated dendritic mRNA as well as in situ hybridization. Many of the retained introns contain ID elements, a class of SINE retrotransposon. A portion of these SINEs confers dendritic targeting to exogenous and endogenous transcripts showing the necessity of ID-mediated mechanisms for the targeting of different transcripts to dendrites. ID elements are capable of selectively altering the distribution of endogenous proteins, providing a link between intronic SINEs and protein function. As such, the ID element represents a common dendritic targeting element found across multiple RNAs. Retention of intronic sequence is a more general phenomenon than previously thought and plays a functional role in the biology of the neuron, partly mediated by co-opted repetitive sequences.

Deep sequencing reveals cell-type-specific patterns of single-cell transcriptome variation

BackgroundDifferentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype. This brings into question the relationship between transcriptome states and cell phenotypes. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question.ResultsWe present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We develop methods to filter genes for reliable quantification and to calibrate biological variation. All cell types include genes with high variability in expression, in a tissue-specific manner. We also find evidence that single-cell variability of neuronal genes in mice is correlated with that in rats consistent with the hypothesis that levels of variation may be conserved.ConclusionsSingle-cell RNA-sequencing data provide a unique view of transcriptome function; however, careful analysis is required in order to use single-cell RNA-sequencing measurements for this purpose. Technical variation must be considered in single-cell RNA-sequencing studies of expression variation. For a subset of genes, biological variability within each cell type appears to be regulated in order to perform dynamic functions, rather than solely molecular noise.

Serotonergic neuron regulation informed by in vivo single-cell transcriptomics

Despite the recognized importance of the dorsal raphe (DR) serotonergic (5‐HT) nuclei in the pathophysiology of depression and anxiety, the molecular components/putative drug targets expressed by these neurons are poorly characterized. Utilizing the promoter of an ETS domain transcription factor that is a stable marker of 5‐HT neurons (Pet‐1) to drive 5‐HT neuronal expression of YFP, we identified 5‐HT neurons in live acute slices. We isolated RNA from single 5‐HT neurons in the ventromedial and lateral wings of the DR and performed single‐cell RNA‐Seq analysis identifying >500 G‐protein coupled receptors (GPCRs) including receptors for classical transmitters, lipid signals, and peptides as well as dozens of orphan‐GPCRs. Using these data to inform our selection of receptors to assess, we found that oxytocin and lysophosphatidic acid 1 receptors are translated and active in costimulating, with the α1‐adrenergic receptor, the firing of DR 5‐HT neurons, while the effects of histamine are inhibitory and exerted at H3 histamine receptors. The inhibitory histamine response provides evidence for tonic in vivo histamine inhibition of 5‐HT neurons. This study illustrates that unbiased single‐cell transcriptomics coupled with functional analyses provides novel insights into how neurons and neuronal systems are regulated.—Spaethling, J. M., Piel, D., Dueck, H., Buckley, P. T., Morris, J. F., Fisher, S. A., Lee, J., Sul, J.‐Y., Kim, J., Bartfai, T., Beck, S. G., Eberwine, J. H. Serotonergic neuron regulation informed by in vivo single‐cell transcriptomics. FASEB J. 28, 771–780 (2014). www.fasebj.org

Assessing characteristics of RNA amplification methods for single cell RNA sequencing

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.

Single-cell transcriptomics and functional target validation of brown adipocytes show their complex roles in metabolic homeostasis

Brown adipocytes (BAs) are specialized for adaptive thermogenesis and, upon sympathetic stimulation, activate mitochondrial uncoupling protein (UCP)‐1 and oxidize fatty acids to generate heat. The capacity for brown adipose tissue (BAT) to protect against obesity and metabolic disease is recognized, yet information about which signals activate BA, besides β3‐adrenergic receptor stimulation, is limited. Using single‐cell transcriptomics, we confirmed the presence of mRNAs encoding traditional BAT markers (i.e., UCP1, expressed in 100% of BAs Adrb3, expressed in <50% of BAs) in mouse and have shown single‐cell variability (>1000‐fold) in their expression at both the mRNA and protein levels. We further identified mRNAs encoding novel markers, orphan GPCRs, and many receptors that bind the classic neurotransmitters, neuropeptides, chemokines, cytokines, and hormones. The transcriptome variability between BAs suggests a much larger range of responsiveness of BAT than previously recognized and that not all BAs function identically. We examined the in vivo functional expression of 12 selected receptors by micro‐injecting agonists into live mouse BAT and analyzing the metabolic response. In this manner, we expanded the number of known receptors on BAs at least 25‐fold, while showing that the expression of classic BA markers is more complex and variable than previously thought.—Spaethling, J. M., Sanchez‐Alavez, M., Lee, J., Xia, F. C., Dueck, H., Wang, W., Fisher, S. A., Sul, J.‐Y., Seale, P., Kim, J., Bartfai, T., Eberwine, J. Single‐cell transcriptomics and functional target validation of brown adipocytes show their complex roles in metabolic homeostasis. FASEB J. 30, 81‐92 (2016). www.fasebj.org

Lifestyle Modification in Blood Pressure Study II (LIMBS): study protocol of a randomized controlled trial assessing the efficacy of a 24 week structured yoga program versus lifestyle modification on blood pressure reduction.

Hypertension is a major public health issue affecting 68 million adults in the United States. Lifestyle modifications including complementary therapies such as the movement based mind body practice of yoga have become increasingly popular in the United States and have been considered as a potential alternative to medication in blood pressure reduction. We completed a pilot study in 2009 which showed meaningful decreases in 24-hour ambulatory blood pressure readings after a 12 week period of yoga participation. Based on data from our pilot study we are now completing The Lifestyle Modification and Blood Pressure Study (LIMBS II) which is a phase 2 randomized controlled trial designed to determine the effects of yoga therapy and enhanced lifestyle modification on lowering blood pressure in pre-hypertensive and stage 1 hypertensive subjects. Using 24-hour ambulatory blood pressure monitoring, LIMBS II aims to compare the effects on blood pressure reduction in subjects randomized for 24 weeks to one of the three following groups: yoga therapy versus blood pressure education program (sodium restriction and walking program) versus a combination program that involves components of both groups. LIMBS II will also examine the impact that changes in blood pressure have on cerebral blood flow. If successful, the LIMBS study will determine if yoga therapy combined with enhanced lifestyle modification will result in clinically meaningful decreases in blood pressure and thus can be implemented as an alternative to drug therapy for patients with prehypertension and stage 1 hypertension.

Coordination of olfactory receptor choice with guidance receptor expression and function in olfactory sensory neurons

Olfactory sensory neurons choose to express a single odorant receptor (OR) from a large gene repertoire and extend axons to reproducible, OR-specific locations within the olfactory bulb. This developmental process produces a topographically organized map of odorant experience in the brain. The axon guidance mechanisms that generate this pattern of connectivity, as well as those that coordinate OR choice and axonal guidance receptor expression, are incompletely understood. We applied the powerful approach of single-cell RNA-seq on newly born olfactory sensory neurons (OSNs) in young zebrafish larvae to address these issues. Expression profiles were generated for 56 individual Olfactory Marker Protein (OMP) positive sensory neurons by single-cell (SC) RNA-seq. We show that just as in mouse OSNs, mature zebrafish OSNs typically express a single predominant OR transcript. Our previous work suggests that OSN targeting is related to the OR clade from which a sensory neuron chooses to express its odorant receptor. We categorized each of the mature cells based on the clade of their predominantly expressed OR. Transcripts expressed at higher levels in each of three clade-related categories were identified using Penalized Linear Discriminant Analysis (PLDA). A genome-wide approach was used to identify membrane-associated proteins that are most likely to have guidance-related activity. We found that OSNs that choose to express an OR from a particular clade also express specific subsets of potential axon guidance genes and transcription factors. We validated our identification of candidate axon guidance genes for one clade of OSNs using bulk RNA-seq from a subset of transgene-labeled neurons that project to a single protoglomerulus. The differential expression patterns of selected candidate guidance genes were confirmed using fluorescent in situ hybridization. Most importantly, we observed axonal mistargeting in knockouts of three candidate axonal guidance genes identified in this analysis: nrp1a, nrp1b, and robo2. In each case, targeting errors were detected in the subset of axons that normally express these transcripts at high levels, and not in the axons that express them at low levels. Our findings demonstrate that specific, functional, axonal guidance related genes are expressed in subsets of OSNs that that can be categorized by their patterns of OR expression.

KimLabIDV: Application for Interactive RNA- Seq Data Analysis and Visualization

Summary: We developed the KimLabIDV package (IDV) to facilitate fast and interactive RNA-Seq data analysis and visualization. IDV supports routine analysis including differential expression analysis, correlation analysis, dimension reduction, clustering and classification. With the graphical user interface IDV provides, users can easily obtain statistical test results and publication-quality graphs with their data. IDV further supports program state saving and report generation, so that all analysis can be saved, shared and reproduced. Availability and implementation: IDV is implemented in R and is distributed as an R package. It is developed based on the Shiny framework, multiple R packages and a collection of scripts written by members of Junhyong Kims Lab at University of Pennsylvania. IDV supports any system that has R and a modern web browser installed. It can be downloaded from Kim Lab Software Repository (http://kim.bio.upenn.edu/software).Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages is difficult. Here we present PIVOT, an R-based application with a uniform user interface and graphical data management that allows non-programmers to conveniently access various bioinformatics tools and interactively explore transcriptomics data. PIVOT supports many popular open source packages for transcriptome analysis and provides an extensive set of tools for statistical data manipulations. A graph-based visual interface is used to represent the links between derived datasets, allowing easy tracking of data versions. PIVOT further supports automatic report generation, publication-quality plots, and program/data state saving, such that all analysis can be saved, shared and reproduced.

Discovering Similar Workflows via Provenance Clustering: A Case Study

Several workflow management systems and scripting languages have adopted provenance tracking, yet many researchers choose to manually capture or instrument their processing scripts to write provenance information to files. The Next Generation Sequencing (NGS) project we are associated with is tracking provenance in such manner. The NGS project is a collaboration between multiple groups at different sites, where each group is collecting and processing samples using an agreed-upon workflow. The workflow contains many stages with varying degrees of complexity. Over time workflow stages are modified, but data samples are only comparable when processed with identical versions of the workflow. However, for various reasons (including the distributed nature of the collaboration) it is not always clear which samples have been processed with which version of the workflow. In this paper, we introduce new techniques for clustering provenance datasets and attempt to discover the ones that are likely to be generated by same workflow. Based on the clustering result, users can identify similar provenance and would be able to categorize them into different clusters for debugging and zoom-in/zoom-out viewing.