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.

A scalable SCENIC workflow for single-cell gene regulatory network analysis.

This protocol explains how to perform a fast SCENIC analysis alongside standard best practices steps on single-cell RNA-sequencing data using software containers and Nextflow pipelines. SCENIC reconstructs regulons (i.e., transcription factors and their target genes) assesses the activity of these discovered regulons in individual cells and uses these cellular activity patterns to find meaningful clusters of cells. Here we present an improved version of SCENIC with several advances. SCENIC has been refactored and reimplemented in Python (pySCENIC), resulting in a tenfold increase in speed, and has been packaged into containers for ease of use. It is now also possible to use epigenomic track databases, as well as motifs, to refine regulons. In this protocol, we explain the different steps of SCENIC: the workflow starts from the count matrix depicting the gene abundances for all cells and consists of three stages. First, coexpression modules are inferred using a regression per-target approach (GRNBoost2). Next, the indirect targets are pruned from these modules using cis-regulatory motif discovery (cisTarget). Lastly, the activity of these regulons is quantified via an enrichment score for the regulon's target genes (AUCell). Nonlinear projection methods can be used to display visual groupings of cells based on the cellular activity patterns of these regulons. The results can be exported as a loom file and visualized in the SCope web application. This protocol is illustrated on two use cases: a peripheral blood mononuclear cell data set and a panel of single-cell RNA-sequencing cancer experiments. For a data set of 10,000 genes and 50,000 cells, the pipeline runs in <2 h.

iRegulon: from a gene list to a gene regulatory network using large motif and track collections.

Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org.

Male-specific fruitless isoforms target neurodevelopmental genes to specify a sexually dimorphic nervous system.

BACKGROUND: In Drosophila, male courtship behavior is regulated in large part by the gene fruitless (fru). fru encodes a set of putative transcription factors that promote male sexual behavior by controlling the development of sexually dimorphic neuronal circuitry. Little is known about how Fru proteins function at the level of transcriptional regulation or the role that isoform diversity plays in the formation of a male-specific nervous system. RESULTS: To characterize the roles of sex-specific Fru isoforms in specifying male behavior, we generated novel isoform-specific mutants and used a genomic approach to identify direct Fru isoform targets during development. We demonstrate that all Fru isoforms directly target genes involved in the development of the nervous system, with individual isoforms exhibiting unique binding specificities. We observe that fru behavioral phenotypes are specified by either a single isoform or a combination of isoforms. Finally, we illustrate the utility of these data for the identification of novel sexually dimorphic genomic enhancers and novel downstream regulators of male sexual behavior. CONCLUSIONS: These findings suggest that Fru isoform diversity facilitates both redundancy and specificity in gene expression, and that the regulation of neuronal developmental genes may be the most ancient and conserved role of fru in the specification of a male-specific nervous system.

Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions.

The identification of transcription factor binding sites, enhancers, and transcriptional target genes often relies on the integration of gene expression profiling and computational cis-regulatory sequence analysis. Methods for the prediction of cis-regulatory elements can take advantage of comparative genomics to increase signal-to-noise levels. However, gene expression data are usually derived from only one species. Here we investigate tissue-specific cross-species gene expression profiling by high-throughput sequencing, combined with cross-species motif discovery. First, we compared different methods for expression level quantification and cross-species integration using Tag-seq data. Using the optimal pipeline, we derived a set of genes with conserved expression during retinal determination across Drosophila melanogaster, Drosophila yakuba, and Drosophila virilis. These genes are enriched for binding sites of eye-related transcription factors including the zinc-finger Glass, a master regulator of photoreceptor differentiation. Validation of predicted Glass targets using RNA-seq in homozygous glass mutants confirms that the majority of our predictions are expressed downstream from Glass. Finally, we tested nine candidate enhancers by in vivo reporter assays and found eight of them to drive GFP in the eye disc, of which seven colocalize with the Glass protein, namely, scrt, chp, dpr10, CG6329, retn, Lim3, and dmrt99B. In conclusion, we show for the first time the combined use of cross-species expression profiling with cross-species motif discovery as a method to define a core developmental program, and we augment the candidate Glass targetome from a single known target gene, lozenge, to at least 62 conserved transcriptional targets.

Adult interfollicular tumour-initiating cells are reprogrammed into an embryonic hair follicle progenitor-like fate during basal cell carcinoma initiation.

Basal cell carcinoma, the most frequent human skin cancer, arises from activating hedgehog (HH) pathway mutations; however, little is known about the temporal changes that occur in tumour-initiating cells from the first oncogenic hit to the development of invasive cancer. Using an inducible mouse model enabling the expression of a constitutively active Smoothened mutant (SmoM2) in the adult epidermis, we carried out transcriptional profiling of SmoM2-expressing cells at different times during cancer initiation. We found that tumour-initiating cells are massively reprogrammed into a fate resembling that of embryonic hair follicle progenitors (EHFPs). Wnt/ ß-catenin signalling was very rapidly activated following SmoM2 expression in adult epidermis and coincided with the expression of EHFP markers. Deletion of ß-catenin in adult SmoM2-expressing cells prevents EHFP reprogramming and tumour initiation. Finally, human basal cell carcinomas also express genes of the Wnt signalling and EHFP signatures.

i-cisTarget: an integrative genomics method for the prediction of regulatory features and cis-regulatory modules.

The field of regulatory genomics today is characterized by the generation of high-throughput data sets that capture genome-wide transcription factor (TF) binding, histone modifications, or DNAseI hypersensitive regions across many cell types and conditions. In this context, a critical question is how to make optimal use of these publicly available datasets when studying transcriptional regulation. Here, we address this question in Drosophila melanogaster for which a large number of high-throughput regulatory datasets are available. We developed i-cisTarget (where the 'i' stands for integrative), for the first time enabling the discovery of different types of enriched 'regulatory features' in a set of co-regulated sequences in one analysis, being either TF motifs or 'in vivo' chromatin features, or combinations thereof. We have validated our approach on 15 co-expressed gene sets, 21 ChIP data sets, 628 curated gene sets and multiple individual case studies, and show that meaningful regulatory features can be confidently discovered; that bona fide enhancers can be identified, both by in vivo events and by TF motifs; and that combinations of in vivo events and TF motifs further increase the performance of enhancer prediction.

Comparison of bandwidths in the inferior colliculus and the auditory nerve. I. Measurement using a spectrally manipulated stimulus.

A defining feature of auditory systems across animal divisions is the ability to sort different frequency components of a sound into separate neural frequency channels. Narrowband filtering in the auditory periphery is of obvious advantage for the representation of sound spectrum and manifests itself pervasively in human psychophysical studies as the critical band. Peripheral filtering also alters coding of the temporal waveform, so that temporal responses in the auditory periphery reflect both the stimulus waveform and peripheral filtering. Temporal coding is essential for the measurement of the time delay between waveforms at the two ears-a critical component of sound localization. A number of human psychophysical studies have shown a wider effective critical bandwidth with binaural stimuli than with monaural stimuli, although other studies found no difference. Here we directly compare binaural and monaural bandwidths (BWs) in the anesthetized cat. We measure monaural BW in the auditory nerve (AN) and binaural BW in the inferior colliculus (IC) using spectrally manipulated broadband noise and response metrics that reflect spike timing. The stimulus was a pair of noise tokens that were interaurally in phase for all frequencies below a certain flip frequency (f(flip)) and that had an interaural phase difference of pi above f(flip). The response was measured as a function of f(flip) and, using a separate stimulus protocol, as a function of interaural correlation. We find that both AN and IC filter BW depend on characteristic frequency, but that there is no difference in mean BW between the AN and IC.

Binaural and cochlear disparities.

Binaural auditory neurons exhibit "best delays" (BDs): They are maximally activated at certain acoustic delays between sounds at the two ears and thereby signal spatial sound location. BDs arise from delays internal to the auditory system, but their source is controversial. According to the classic Jeffress model, they reflect pure time delays generated by differences in axonal length between the inputs from the two ears to binaural neurons. However, a relationship has been reported between BDs and the frequency to which binaural neurons are most sensitive (the characteristic frequency), and this relationship is not predicted by the Jeffress model. An alternative hypothesis proposes that binaural neurons derive their input from slightly different places along the two cochleas, which induces BDs by virtue of the slowness of the cochlear traveling wave. To test this hypothesis, we performed a coincidence analysis on spiketrains of pairs of auditory nerve fibers originating from different cochlear locations. In effect, this analysis mimics the processing of phase-locked inputs from each ear by binaural neurons. We find that auditory nerve fibers that innervate different cochlear sites show a maximum number of coincidences when they are delayed relative to each other, and that the optimum delays decrease with characteristic frequency as in binaural neurons. These findings suggest that cochlear disparities make an important contribution to the internal delays observed in binaural neurons.

Auditory midbrain and nerve responses to sinusoidal variations in interaural correlation.

The human sensitivity to interaural temporal differences in the acoustic waveforms to the two ears shows remarkable acuity but is also very sluggish. Fast changes in binaural parameters are not detectable, and this inability contrasts sharply with the excellent temporal resolution of the monaural auditory system. We studied the response of binaural neurons in the inferior colliculus of the cat to sinusoidal changes in the interaural correlation of broadband noise. Responses to the same waveforms were also obtained from auditory nerve fibers and further analyzed with a coincidence analysis. Overall, the auditory nerve and inferior colliculus showed a similar ability to code changes in interaural correlation. This ability extended to modulation frequencies an order of magnitude higher than the highest frequencies detected binaurally in humans. We conclude that binaural sluggishness is not caused by a lack of temporal encoding of fast binaural changes at the level of the midbrain. We hypothesize that there is no neural substrate at the level of the midbrain or higher to read out this temporal code and that this constitutes a low-pass "sluggishness" filter.

Temporal damping in response to broadband noise. I. Inferior colliculus.

Many cells in the inferior colliculus (IC) are sensitive to interaural time differences (ITDs), in the form of an oscillatory dependency of average firing rate on ITD. We studied the degree of damping in such binaural responses, recording from neurons in the inferior colliculus of pentobarbital-anesthetized cats to binaural broadband noise and tones. Noise-delay functions and composite curves were characterized by computing the difference between responses to correlated and anticorrelated stimuli. We use a new metric, based on the envelope of this difference, to quantify damping. There is a clear relationship between damping and characteristic frequency (CF), but even neurons of the same CF can differ in their damping. For individual cells, damping can be stronger to tones or to noise; at the population level the two are positively correlated and are scarcely affected by SPL. The frequencies that dominate ITD sensitivity are near the CF in response to noise, but are often below CF in response to tones. These findings qualify conclusions from earlier reports but overall they support the conclusion that, at a population level, basic aspects of binaural responses to wideband noise are consistent with summed responses to pure tones.