Applications of single-cell RNA sequencing in drug discovery and development.

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Lamin B2 Levels Regulate Polyploidization of Cardiomyocyte Nuclei and Myocardial Regeneration.

Heart regeneration requires cardiomyocyte proliferation. It is thought that formation of polyploid nuclei establishes a barrier for cardiomyocyte proliferation, but the mechanisms are largely unknown. Here, we show that the nuclear lamina filament Lamin B2 (Lmnb2), whose expression decreases in mice after birth, is essential for nuclear envelope breakdown prior to progression to metaphase and subsequent division. Inactivating Lmnb2 decreased metaphase progression, which led to formation of polyploid cardiomyocyte nuclei in neonatal mice, which, in turn, decreased myocardial regeneration. Increasing Lmnb2 expression promoted cardiomyocyte M-phase progression and cytokinesis and improved indicators of myocardial regeneration in neonatal mice. Inactivating LMNB2 in human iPS cell-derived cardiomyocytes reduced karyokinesis and increased formation of polyploid nuclei. In primary cardiomyocytes from human infants with heart disease, modifying LMNB2 expression correspondingly altered metaphase progression and ploidy of daughter nuclei. In conclusion, Lmnb2 expression is essential for karyokinesis in mammalian cardiomyocytes and heart regeneration.

Control of cytokinesis by ß-adrenergic receptors indicates an approach for regulating cardiomyocyte endowment.

One million patients with congenital heart disease (CHD) live in the United States. They have a lifelong risk of developing heart failure. Current concepts do not sufficiently address mechanisms of heart failure development specifically for these patients. Here, analysis of heart tissue from an infant with tetralogy of Fallot with pulmonary stenosis (ToF/PS) labeled with isotope-tagged thymidine demonstrated that cardiomyocyte cytokinesis failure is increased in this common form of CHD. We used single-cell transcriptional profiling to discover that the underlying mechanism of cytokinesis failure is repression of the cytokinesis gene ECT2, downstream of ß-adrenergic receptors (ß-ARs). Inactivation of the ß-AR genes and administration of the ß-blocker propranolol increased cardiomyocyte division in neonatal mice, which increased the number of cardiomyocytes (endowment) and conferred benefit after myocardial infarction in adults. Propranolol enabled the division of ToF/PS cardiomyocytes in vitro. These results suggest that ß-blockers could be evaluated for increasing cardiomyocyte division in patients with ToF/PS and other types of CHD.

PIVOT: platform for interactive analysis and visualization of transcriptomics data.

BACKGROUND: Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermore, exploratory data analyses often generate multiple derived datasets such as data subsets or data transformations, which can be difficult to track. RESULTS: Here we present PIVOT, an R-based platform that wraps open source transcriptome analysis packages with a uniform user interface and graphical data management that allows non-programmers to interactively explore transcriptomics data. PIVOT supports more than 40 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. CONCLUSIONS: PIVOT will allow researchers with broad background to easily access sophisticated transcriptome analysis tools and interactively explore transcriptome datasets.

Uncovering novel repositioning opportunities using the Open Targets platform.

The recently developed Open Targets platform consolidates a wide range of comprehensive evidence associating known and potential drug targets with human diseases. We have harnessed the integrated data from this platform for novel drug repositioning opportunities. Our computational workflow systematically mines data from various evidence categories and presents potential repositioning opportunities for drugs that are marketed or being investigated in ongoing human clinical trials, based on evidence strength on target-disease pairing. We classified these novel target-disease opportunities in several ways: (i) number of independent counts of evidence; (ii) broad therapy area of origin; and (iii) repositioning within or across therapy areas. Finally, we elaborate on one example that was identified by this approach.

Primary Cell Culture of Live Neurosurgically Resected Aged Adult Human Brain Cells and Single Cell Transcriptomics.

Investigation of human CNS disease and drug effects has been hampered by the lack of a system that enables single-cell analysis of live adult patient brain cells. We developed a culturing system, based on a papain-aided procedure, for resected adult human brain tissue removed during neurosurgery. We performed single-cell transcriptomics on over 300 cells, permitting identification of oligodendrocytes, microglia, neurons, endothelial cells, and astrocytes after 3 weeks in culture. Using deep sequencing, we detected over 12,000 expressed genes, including hundreds of cell-type-enriched mRNAs, lncRNAs and pri-miRNAs. We describe cell-type- and patient-specific transcriptional hierarchies. Single-cell transcriptomics on cultured live adult patient derived cells is a prime example of the promise of personalized precision medicine. Because these cells derive from subjects ranging in age into their sixties, this system permits human aging studies previously possible only in rodent systems.

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

BACKGROUND: Differentiation 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. RESULTS: We 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. CONCLUSIONS: Single-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.

The exonuclease Nibbler regulates age-associated traits and modulates piRNA length in Drosophila.

Nibbler (Nbr) is a 3'-to-5' exonuclease that trims the 3'end of microRNAs (miRNAs) to generate different length patterns of miRNAs in Drosophila. Despite its effect on miRNAs, we lack knowledge of its biological significance and whether Nbr affects other classes of small RNAs such as piRNAs and endo-siRNAs. Here, we characterized the in vivo function of nbr by defining the Nbr protein expression pattern and loss-of-function effects. Nbr protein is enriched in the ovary and head. Analysis of nbr null animals reveals adult-stage defects that progress with age, including held-up wings, decreased locomotion, and brain vacuoles, indicative of accelerated age-associated processes upon nbr loss. Importantly, these effects depend on catalytic residues in the Nbr exonuclease domain, indicating that the catalytic activity is responsible for these effects. Given the impact of nbr on miRNAs, we also analyzed the effect of nbr on piRNA and endo-siRNA lengths by deep-sequence analysis of libraries from ovaries. As with miRNAs, nbr mutation led to longer length piRNAs - an effect that was dependent on the catalytic residues of the exonuclease domain. These analyses indicate a role of nbr on age-associated processes and to modulate length of multiple classes of small RNAs including miRNAs and piRNAs in Drosophila.

Divergence of RNA localization between rat and mouse neurons reveals the potential for rapid brain evolution.

BACKGROUND: Neurons display a highly polarized architecture. Their ability to modify their features under intracellular and extracellular stimuli, known as synaptic plasticity, is a key component of the neurochemical basis of learning and memory. A key feature of synaptic plasticity involves the delivery of mRNAs to distinct sub-cellular domains where they are locally translated. Regulatory coordination of these spatio-temporal events is critical for synaptogenesis and synaptic plasticity as defects in these processes can lead to neurological diseases. In this work, using microdissected dendrites from primary cultures of hippocampal neurons of two mouse strains (C57BL/6 and Balb/c) and one rat strain (Sprague-Dawley), we investigate via microarrays, subcellular localization of mRNAs in dendrites of neurons to assay the evolutionary differences in subcellular dendritic transcripts localization. RESULTS: Our microarray analysis highlighted significantly greater evolutionary diversification of RNA localization in the dendritic transcriptomes (81% gene identity difference among the top 5% highly expressed genes) compared to the transcriptomes of 11 different central nervous system (CNS) and non-CNS tissues (average of 44% gene identity difference among the top 5% highly expressed genes). Differentially localized genes include many genes involved in CNS function. CONCLUSIONS: Species differences in sub-cellular localization may reflect non-functional neutral drift. However, the functional categories of mRNA showing differential localization suggest that at least part of the divergence may reflect activity-dependent functional differences of neurons, mediated by species-specific RNA subcellular localization mechanisms.

Cytoplasmic intron retention, function, splicing, and the sentinel RNA hypothesis.

Cytoplasmic splicing represents a newly emerging level of transcriptional regulation adding to the molecular diversity of mammalian cells. As examples of this noncanonical form of transcript processing are discovered, the evidence of its importance to normal cellular function grows. Work from a number of groups using a variety of cell types is steadily identifying a large number of transcripts (and soon to be even larger as genome-wide analyses of retained introns across a number of cellular phenotypes are currently underway) that undergo some level of regulated endogenous extranuclear splicing as part of their normal biosynthetic pathway. Here, we review the existing data covering cytoplasmic retained intron sequences and suggest that such sequences may be a component of 'sentinel RNA' that serves to generate transcript variants within the cytoplasm as well as a source for RNA-based secondary messages.

Subcellular RNA sequencing reveals broad presence of cytoplasmic intron-sequence retaining transcripts in mouse and rat neurons.

Recent findings have revealed the complexity of the transcriptional landscape in mammalian cells. One recently described class of novel transcripts are the Cytoplasmic Intron-sequence Retaining Transcripts (CIRTs), hypothesized to confer post-transcriptional regulatory function. For instance, the neuronal CIRT KCNMA1i16 contributes to the firing properties of hippocampal neurons. Intronic sub-sequence retention within IL1-ß mRNA in anucleate platelets has been implicated in activity-dependent splicing and translation. In a recent study, we showed CIRTs harbor functional SINE ID elements which are hypothesized to mediate dendritic localization in neurons. Based on these studies and others, we hypothesized that CIRTs may be present in a broad set of transcripts and comprise novel signals for post-transcriptional regulation. We carried out a transcriptome-wide survey of CIRTs by sequencing micro-dissected subcellular RNA fractions. We sequenced two batches of 150-300 individually dissected dendrites from primary cultures of hippocampal neurons in rat and three batches from mouse hippocampal neurons. After statistical processing to minimize artifacts, we found a broad prevalence of CIRTs in the neurons in both species (44-60% of the expressed transcripts). The sequence patterns, including stereotypical length, biased inclusion of specific introns, and intron-intron junctions, suggested CIRT-specific nuclear processing. Our analysis also suggested that these cytoplasmic intron-sequence retaining transcripts may serve as a primary transcript for ncRNAs. Our results show that retaining intronic sequences is not isolated to a few loci but may be a genome-wide phenomenon for embedding functional signals within certain mRNA. The results hypothesize a novel source of cis-sequences for post-transcriptional regulation. Our results hypothesize two potentially novel splicing pathways: one, within the nucleus for CIRT biogenesis; and another, within the cytoplasm for removing CIRT sequences before translation. We also speculate that release of CIRT sequences prior to translation may form RNA-based signals within the cell potentially comprising a novel class of signaling pathways.

A method for discovering common patterns from two RNA secondary structures and its application to structural repeat detection.

We propose an ab initio method, named DiscoverR, for finding common patterns from two RNA secondary structures. The method works by representing RNA secondary structures as ordered labeled trees and performs tree pattern discovery using an efficient dynamic programming algorithm. DiscoverR is able to identify and extract the largest common substructures from two RNA molecules having different sizes without prior knowledge of the locations and topologies of these substructures. We also extend DiscoverR to find repeated regions in an RNA secondary structure, and apply this extended method to detect structural repeats in the 3'-untranslated region of a protein kinase gene. We describe the biological significance of a repeated hairpin found by our method, demonstrating the usefulness of the method. DiscoverR is implemented in Java; a jar file including the source code of the program is available for download at http://bioinformatics.njit.edu/DiscoverR.

Functional divergence of gene duplicates - a domain-centric view.

BACKGROUND: Gene duplicates have been shown to evolve at different rates. Here we further investigate the mechanism and functional underpinning of this phenomenon by assessing asymmetric evolution specifically within functional domains of gene duplicates. RESULTS: Based on duplicate genes in five teleost fishes resulting from a whole genome duplication event, we first show that a Fisher Exact test based approach to detect asymmetry is more sensitive than the previously used Likelihood Ratio test. Using our Fisher Exact test, we found that the evolutionary rate asymmetry in the overall protein is largely explained by the asymmetric evolution within specific protein domains. Moreover, among cases of asymmetrically evolving domains, for the gene copy containing a fast evolving domain, the non-synonymous substitutions often cluster within the fast evolving domain. We found that rare substitutions were preferred within asymmetrically evolving domains suggestive of functional divergence. While overall ~32 % of the domains tested were found to be evolving asymmetrically, certain protein domains such as the Tyrosine and Ser/Thr Kinase domains had a much greater prevalence of asymmetric evolution. Finally, based on the spatial expression of Zebra fish duplicate proteins during development, we found that protein pairs containing asymmetrically evolving domains had a greater divergence in gene expression as compared to the duplicate proteins that did not exhibit asymmetric evolution. CONCLUSIONS: Taken together, our results suggest that the previously observed asymmetry in the overall duplicate protein evolution is largely due to divergence of specific domains of the protein, and coincides with divergence in spatial expression domains.

Epigenomic and RNA structural correlates of polyadenylation.

Polyadenylation (poly(A)) of mRNA plays a critical role in regulating gene expression. Identifying the sequence, structural, and epigenomic determinants of poly(A) site usage is an important long term goal. Several cis elements that mediate poly(A) regulation have been identified. Highly used poly(A) sites are also known to have a greater nucleosome occupancy in the immediate downstream. However, a detailed exploration of additional epigenomic and mRNA structural correlates of poly(A) site usage has not been reported. Importantly, functional interaction between sequence, structure, and the epigenome in determining the poly(A) site usage is not known. We show that highly used poly(A) sites are positively associated with an mRNA structure that is energetically more favorable and one that better exposes a critical polyadenylation cis element. In exploring potential interplay between RNA and chromatin structure, we found that a stronger nucleosome occupancy downstream of poly(A) site strongly correlated with (1) a more favorable mRNA structure, and (2) a greater accumulation of RNA Polymerase II (PolII) at the poly(A) site. Further analysis suggested a causal relationship pointing from PolII accumulation to a stable RNA structure. Additionally, we found that distinct patterns of histone modifications characterize poly(A) sites and these epigenetic patterns alone can distinguish true poly(A) sites with ~76% accuracy and also discriminate between high and low usage poly(A) sites with ~74% accuracy. Our results suggest a causative link between chromatin structure and mRNA structure whereby a compacted chromatin downstream of the poly(A) site slows down the elongating transcript, thus facilitating the folding of nascent mRNA in a favorable structure at poly(A) site during transcription. Additionally we report hitherto unknown epigenomic correlates for poly(A) site usage.

Detecting conserved secondary structures in RNA molecules using constrained structural alignment.

Constrained sequence alignment has been studied extensively in the past. Different forms of constraints have been investigated, where a constraint can be a subsequence, a regular expression, or a probability matrix of symbols and positions. However, constrained structural alignment has been investigated to a much lesser extent. In this paper, we present an efficient method for constrained structural alignment and apply the method to detecting conserved secondary structures, or structural motifs, in a set of RNA molecules. The proposed method combines both sequence and structural information of RNAs to find an optimal local alignment between two RNA secondary structures, one of which is a query and the other is a subject structure in the given set. The method allows a biologist to annotate conserved regions, or constraints, in the query RNA structure and incorporates these regions into the alignment process to obtain biologically more meaningful alignment scores. A statistical measure is developed to assess the significance of the scores. Experimental results based on detecting internal ribosome entry sites in the RNA molecules of hepatitis C virus and Trypanosoma brucei demonstrate the effectiveness of the proposed method and its superiority over existing techniques.

Mining small RNA structure elements in untranslated regions of human and mouse mRNAs using structure-based alignment.

BACKGROUND: UnTranslated Regions (UTRs) of mRNAs contain regulatory elements for various aspects of mRNA metabolism, such as mRNA localization, translation, and mRNA stability. Several RNA stem-loop structures in UTRs have been experimentally identified, including the histone 3' UTR stem-loop structure (HSL3) and iron response element (IRE). These stem-loop structures are conserved among mammalian orthologs, and exist in a group of genes encoding proteins involved in the same biological pathways. It is not known to what extent RNA structures like these exist in all mammalian UTRs. RESULTS: In this paper we took a systematic approach, named GLEAN-UTR, to identify small stem-loop RNA structure elements in UTRs that are conserved between human and mouse orthologs and exist in multiple genes with common Gene Ontology terms. This approach resulted in 90 distinct RNA structure groups containing 748 structures, with HSL3 and IRE among the top hits based on conservation of structure. CONCLUSION: Our result indicates that there may exist many conserved stem-loop structures in mammalian UTRs that are involved in coordinate post-transcriptional regulation of biological pathways.

RADAR: a web server for RNA data analysis and research.

RADAR is a web server that provides a multitude of functionality for RNA data analysis and research. It can align structure-annotated RNA sequences so that both sequence and structure information are taken into consideration during the alignment process. This server is capable of performing pairwise structure alignment, multiple structure alignment, database search and clustering. In addition, RADAR provides two salient features: (i) constrained alignment of RNA secondary structures, and (ii) prediction of the consensus structure for a set of RNA sequences. RADAR will be able to assist scientists in performing many important RNA mining operations, including the understanding of the functionality of RNA sequences, the detection of RNA structural motifs and the clustering of RNA molecules, among others. The web server together with a software package for download is freely accessible at http://datalab.njit.edu/biodata/rna/RSmatch/server.htm and http://www.ccrnp.ncifcrf.gov/~bshapiro/