The Drosophila HP1 homolog Rhino is required for transposon silencing and piRNA production by dual-strand clusters.

Piwi-interacting RNAs (piRNAs) silence transposons and maintain genome integrity during germline development. In Drosophila, transposon-rich heterochromatic clusters encode piRNAs either on both genomic strands (dual-strand clusters) or predominantly one genomic strand (uni-strand clusters). Primary piRNAs derived from these clusters are proposed to drive a ping-pong amplification cycle catalyzed by proteins that localize to the perinuclear nuage. We show that the HP1 homolog Rhino is required for nuage organization, transposon silencing, and ping-pong amplification of piRNAs. rhi mutations virtually eliminate piRNAs from the dual-strand clusters and block production of putative precursor RNAs from both strands of the major 42AB dual-strand cluster, but not of transcripts or piRNAs from the uni-strand clusters. Furthermore, Rhino protein associates with the 42AB dual-strand cluster,but does not bind to uni-strand cluster 2 or flamenco. Rhino thus appears to promote transcription of dual-strand clusters, leading to production of piRNAs that drive the ping-pong amplification cycle.

Collapse of germline piRNAs in the absence of Argonaute3 reveals somatic piRNAs in flies.

Piwi-interacting RNAs (piRNAs) silence transposons in animal germ cells. piRNAs are thought to derive from long transcripts spanning transposon-rich genomic loci and to direct an autoamplification loop in which an antisense piRNA, bound to Aubergine or Piwi protein, triggers production of a sense piRNA bound to the PIWI protein Argonaute3 (Ago3). In turn, the new piRNA is envisioned to produce a second antisense piRNA. Here, we describe strong loss-of-function mutations in ago3, allowing a direct genetic test of this model. We find that Ago3 acts to amplify piRNA pools and to enforce on them an antisense bias, increasing the number of piRNAs that can act to silence transposons. We also detect a second, Ago3-independent piRNA pathway centered on Piwi. Transposons targeted by this second pathway often reside in the flamenco locus, which is expressed in somatic ovarian follicle cells, suggesting a role for piRNAs beyond the germline.

3'Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling.

BACKGROUND: The advent of Next Generation Sequencing has allowed transcriptomes to be profiled with unprecedented accuracy, but the high costs of full-length mRNA sequencing have posed a limit on the accessibility and scalability of the technology. To address this, we developed 3'Pool-seq: a simple, cost-effective, and scalable RNA-seq method that focuses sequencing to the 3'-end of mRNA. We drew from aspects of SMART-seq, Drop-seq, and TruSeq to implement an easy workflow, and optimized parameters such as input RNA concentrations, tagmentation conditions, and read depth specifically for bulk-RNA. RESULTS: Thorough optimization resulted in a protocol that takes less than 12 h to perform, does not require custom sequencing primers or instrumentation, and cuts over 90% of the costs associated with TruSeq, while still achieving accurate gene expression quantification (Pearson's correlation coefficient with ERCC theoretical concentration r = 0.96) and differential gene detection (ROC analysis of 3'Pool-seq compared to TruSeq AUC = 0.921). The 3'Pool-seq dual indexing scheme was further adapted for a 96-well plate format, and ERCC spike-ins were used to correct for potential row or column pooling effects. Transcriptional profiling of troglitazone and pioglitazone treatments at multiple doses and time points in HepG2 cells was then used to show how 3'Pool-seq could distinguish the two molecules based on their molecular signatures. CONCLUSIONS: 3'Pool-seq can accurately detect gene expression at a level that is on par with TruSeq, at one tenth of the total cost. Furthermore, its unprecedented TruSeq/Nextera hybrid indexing scheme and streamlined workflow can be applied in several different formats, including 96-well plates, which allows users to thoroughly evaluate biological systems under several conditions and timepoints. Care must be taken regarding experimental design and plate layout such that potential pooling effects can be accounted for and corrected. Lastly, further studies using multiple sets of ERCC spike-ins may be used to simulate differential gene expression in a system with known ground-state values.

Transcriptomic RNAseq drug screen in cerebrocortical cultures: toward novel neurogenetic disease therapies.

Rare monogenic diseases affect millions worldwide; although over 4500 rare disease genotypes are known, disease-modifying drugs are available for only 5% of them. The sheer number of these conditions combined with their rarity precludes traditional costly drug discovery programs. An economically viable alternative is to repurpose established drugs for rare diseases. Many genetic diseases result from increased or decreased protein activity and identification of clinically approved drugs which moderate this pathogenic dosage holds therapeutic potential. To identify such agents for neurogenetic diseases, we have generated genome-wide transcriptome profiles of mouse primary cerebrocortical cultures grown in the presence of 218 blood-brain barrier (BBB) penetrant clinic-tested drugs. RNAseq and differential expression analyses were used to generate transcriptomic profiles; therapeutically relevant drug-gene interactions related to rare neurogenetic diseases identified in this fashion were further analyzed by quantitative reverse transcriptase-polymerase chain reaction, western blot and immunofluorescence. We have created a transcriptome-wide searchable database for easy access to the gene expression data resulting from the cerebrocortical drug screen (Neuron Screen) and have mined this data to identify a novel link between thyroid hormone and expression of the peripheral neuropathy associated gene Pmp22. Our results demonstrate the utility of cerebrocortical cultures for transcriptomic drug screening, and the database we have created will foster further discovery of novel links between over 200 clinic-tested BBB penetrant drugs and genes related to diverse neurologic conditions.

Inhibition of 2-AG hydrolysis differentially regulates blood brain barrier permeability after injury.

BACKGROUND: Acute neurological insults caused by infection, systemic inflammation, ischemia, or traumatic injury are often associated with breakdown of the blood-brain barrier (BBB) followed by infiltration of peripheral immune cells, cytotoxic proteins, and water. BBB breakdown and extravasation of these peripheral components into the brain parenchyma result in inflammation, oxidative stress, edema, excitotoxicity, and neurodegeneration. These downstream consequences of BBB dysfunction can drive pathophysiological processes and play a substantial role in the morbidity and mortality of acute and chronic neurological insults, and contribute to long-term sequelae. Preserving or rescuing BBB integrity and homeostasis therefore represents a translational research area of high therapeutic potential. METHODS: Induction of general and localized BBB disruption in mice was carried out using systemic administration of LPS and focal photothrombotic ischemic insult, respectively, in the presence and absence of the monoacylglycerol lipase (MAGL) inhibitor, CPD-4645. The effects of CPD-4645 treatment were assessed by gene expression analysis performed on neurovascular-enriched brain fractions, cytokine and inflammatory mediator measurement, and functional assessment of BBB permeability. The mechanism of action of CPD-4645 was studied pharmacologically using inverse agonists/antagonists of the cannabinoid receptors CB1 and CB2. RESULTS: Here, we demonstrate that the neurovasculature exhibits a unique transcriptional signature following inflammatory insults, and pharmacological inhibition of MAGL using a newly characterized inhibitor rescues the transcriptional profile of brain vasculature and restores its functional homeostasis. This pronounced effect of MAGL inhibition on blood-brain barrier permeability is evident following both systemic inflammatory and localized ischemic insults. Mechanistically, the protective effects of the MAGL inhibitor are partially mediated by cannabinoid receptor signaling in the ischemic brain insult. CONCLUSIONS: Our results support considering MAGL inhibitors as potential therapeutics for BBB dysfunction and cerebral edema associated with inflammatory brain insults.

Genetics of CD33 in Alzheimer's disease and acute myeloid leukemia.

The CD33 single-nucleotide polymorphism (SNP) rs3865444 has been associated with the risk of Alzheimer's disease (AD). Rs3865444 is in linkage disequilibrium with rs12459419 which has been associated with efficacy of an acute myeloid leukemia (AML) chemotherapeutic agent based on a CD33 antibody. We seek to evaluate the extent to which CD33 genetics in AD and AML can inform one another and advance human disease therapy. We have previously shown that these SNPs are associated with skipping of CD33 exon 2 in brain mRNA. Here, we report that these CD33 SNPs are associated with exon 2 skipping in leukocytes from AML patients and with a novel CD33 splice variant that retains CD33 intron 1. Each copy of the minor rs12459419T allele decreases prototypic full-length CD33 expression by ∼ 25% and decreases the AD odds ratio by ∼ 0.10. These results suggest that CD33 antagonists may be useful in reducing AD risk. CD33 inhibitors may include humanized CD33 antibodies such as lintuzumab which was safe but ineffective in AML clinical trials. Here, we report that lintuzumab downregulates cell-surface CD33 by 80% in phorbol-ester differentiated U937 cells, at concentrations as low as 10 ng/ml. Overall, we propose a model wherein a modest effect on RNA splicing is sufficient to mediate the CD33 association with AD risk and suggest the potential for an anti-CD33 antibody as an AD-relevant pharmacologic agent.

QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization.

BACKGROUND: RNA sequencing (RNA-seq), a next-generation sequencing technique for transcriptome profiling, is being increasingly used, in part driven by the decreasing cost of sequencing. Nevertheless, the analysis of the massive amounts of data generated by large-scale RNA-seq remains a challenge. Multiple algorithms pertinent to basic analyses have been developed, and there is an increasing need to automate the use of these tools so as to obtain results in an efficient and user friendly manner. Increased automation and improved visualization of the results will help make the results and findings of the analyses readily available to experimental scientists. RESULTS: By combing the best open source tools developed for RNA-seq data analyses and the most advanced web 2.0 technologies, we have implemented QuickRNASeq, a pipeline for large-scale RNA-seq data analyses and visualization. The QuickRNASeq workflow consists of three main steps. In Step #1, each individual sample is processed, including mapping RNA-seq reads to a reference genome, counting the numbers of mapped reads, quality control of the aligned reads, and SNP (single nucleotide polymorphism) calling. Step #1 is computationally intensive, and can be processed in parallel. In Step #2, the results from individual samples are merged, and an integrated and interactive project report is generated. All analyses results in the report are accessible via a single HTML entry webpage. Step #3 is the data interpretation and presentation step. The rich visualization features implemented here allow end users to interactively explore the results of RNA-seq data analyses, and to gain more insights into RNA-seq datasets. In addition, we used a real world dataset to demonstrate the simplicity and efficiency of QuickRNASeq in RNA-seq data analyses and interactive visualizations. The seamless integration of automated capabilites with interactive visualizations in QuickRNASeq is not available in other published RNA-seq pipelines. CONCLUSION: The high degree of automation and interactivity in QuickRNASeq leads to a substantial reduction in the time and effort required prior to further downstream analyses and interpretation of the analyses findings. QuickRNASeq advances primary RNA-seq data analyses to the next level of automation, and is mature for public release and adoption.

Comparison of stranded and non-stranded RNA-seq transcriptome profiling and investigation of gene overlap.

BACKGROUND: While RNA-sequencing (RNA-seq) is becoming a powerful technology in transcriptome profiling, one significant shortcoming of the first-generation RNA-seq protocol is that it does not retain the strand specificity of origin for each transcript. Without strand information it is difficult and sometimes impossible to accurately quantify gene expression levels for genes with overlapping genomic loci that are transcribed from opposite strands. It has recently become possible to retain the strand information by modifying the RNA-seq protocol, known as strand-specific or stranded RNA-seq. Here, we evaluated the advantages of stranded RNA-seq in transcriptome profiling of whole blood RNA samples compared with non-stranded RNA-seq, and investigated the influence of gene overlaps on gene expression profiling results based on practical RNA-seq datasets and also from a theoretical perspective. RESULTS: Our results demonstrated a substantial impact of stranded RNA-seq on transcriptome profiling and gene expression measurements. As many as 1751 genes in Gencode Release 19 were identified to be differentially expressed when comparing stranded and non-stranded RNA-seq whole blood samples. Antisense and pseudogenes were significantly enriched in differential expression analyses. Because stranded RNA-seq retains strand information of a read, we can resolve read ambiguity in overlapping genes transcribed from opposite strands, which provides a more accurate quantification of gene expression levels compared with traditional non-stranded RNA-seq. In the human genome, it is not uncommon to find genomic loci where both strands encode distinct genes. Among the over 57,800 annotated genes in Gencode release 19, there are an estimated 19 % (about 11,000) of overlapping genes transcribed from the opposite strands. Based on our whole blood mRNA-seq datasets, the fraction of overlapping nucleotide bases on the same and opposite strands were estimated at 2.94 % and 3.1 %, respectively. The corresponding theoretical estimations are 3 % and 3.6 %, well in agreement with our own findings. CONCLUSIONS: Stranded RNA-seq provides a more accurate estimate of transcript expression compared with non-stranded RNA-seq, and is therefore the recommended RNA-seq approach for future mRNA-seq studies.

Temporal regulation of nuclear factor one occupancy by calcineurin/NFAT governs a voltage-sensitive developmental switch in late maturing neurons.

Dendrite and synapse development are critical for establishing appropriate neuronal circuits, and disrupted timing of these events can alter neural connectivity. Using microarrays, we have identified a nuclear factor I (NFI)-regulated temporal switch program linked to dendrite formation in developing mouse cerebellar granule neurons (CGNs). NFI function was required for upregulation of many synapse-related genes as well as downregulation of genes expressed in immature CGNs. Chromatin immunoprecipitation analysis revealed that a central feature of this program was temporally regulated NFI occupancy of late-expressed gene promoters. Developing CGNs undergo a hyperpolarizing shift in membrane potential, and depolarization inhibits their dendritic and synaptic maturation via activation of calcineurin (CaN) (Okazawa et al., 2009). Maintaining immature CGNs in a depolarized state blocked NFI temporal occupancy of late-expressed genes and the NFI switch program via activation of the CaN/nuclear factor of activated T-cells, cytoplasmic (NFATc) pathway and promotion of late-gene occupancy by NFATc4, and these mechanisms inhibited dendritogenesis. Conversely, inhibition of the CaN/NFATc pathway in CGNs maturing under physiological nondepolarizing conditions upregulated the NFI switch program, NFI temporal occupancy, and dendrite formation. NFATc4 occupied the promoters of late-expressed NFI program genes in immature mouse cerebellum, and its binding was temporally downregulated with development. Further, NFI temporal binding and switch gene expression were upregulated in the developing cerebellum of Nfatc4 (-/-) mice. These findings define a novel NFI switch and temporal occupancy program that forms a critical link between membrane potential/CaN and dendritic maturation in CGNs. CaN inhibits the program and NFI occupancy in immature CGNs by promoting NFATc4 binding to late-expressed genes. As maturing CGNs become more hyperpolarized, NFATc4 binding declines leading to onset of NFI temporal binding and the NFI switch program.

Phosphoproteomic evaluation of pharmacological inhibition of leucine-rich repeat kinase 2 reveals significant off-target effects of LRRK-2-IN-1.

Genetic mutations in leucine-rich repeat kinase 2 (LRRK2) have been linked to autosomal dominant Parkinson's disease. The most prevalent mutation, G2019S, results in enhanced LRRK2 kinase activity that potentially contributes to the etiology of Parkinson's disease. Consequently, disease progression is potentially mediated by poorly characterized phosphorylation-dependent LRRK2 substrate pathways. To address this gap in knowledge, we transduced SH-SY5Y neuroblastoma cells with LRRK2 G2019S via adenovirus, then determined quantitative changes in the phosphoproteome upon LRRK2 kinase inhibition (LRRK2-IN-1 treatment) using stable isotope labeling of amino acids in culture combined with phosphopeptide enrichment and LC-MS/MS analysis. We identified 776 phosphorylation sites that were increased or decreased at least 50% in response to LRRK2-IN-1 treatment, including sites on proteins previously known to associate with LRRK2. Bioinformatic analysis of those phosphoproteins suggested a potential role for LRRK2 kinase activity in regulating pro-inflammatory responses and neurite morphology, among other pathways. In follow-up experiments, LRRK2-IN-1 inhibited lipopolysaccharide-induced tumor necrosis factor alpha (TNFα) and C-X-C motif chemokine 10 (CXCL10) levels in astrocytes and also enhanced multiple neurite characteristics in primary neuronal cultures. However, LRRK2-IN-1 had almost identical effects in primary glial and neuronal cultures from LRRK2 knockout mice. These data suggest LRRK2-IN-1 may inhibit pathways of perceived LRRK2 pathophysiological function independently of LRRK2 highlighting the need to use multiple pharmacological tools and genetic approaches in studies determining LRRK2 function.

HIF1α is required for survival maintenance of chronic myeloid leukemia stem cells.

Hypoxia-inducible factor-1α (HIF1α), a master transcriptional regulator of the cellular and systemic hypoxia response, is essential for the maintenance of self-renewal capacity of normal HSCs. It is still unknown whether HIF1α has a role in survival regulation of leukemia stem cells (LSCs) in chronic myeloid leukemia (CML). Using a mouse model of CML, here we report that HIF1α plays a crucial role in survival maintenance of LSCs. Deletion of HIF1α impairs the propagation of CML through impairing cell-cycle progression and inducing apoptosis of LSCs. Deletion of HIF1α results in elevated expression of p16(Ink4a) and p19(Arf) in LSCs, and knockdown of p16(Ink4a) and p19(Arf) rescues the defective colony-forming ability of HIF1α(-/-) LSCs. Compared with normal HSCs, LSCs appear to be more dependent on the HIF1α pathway. Together, these results demonstrate that HIF1α represents a critical pathway in LSCs and inhibition of the HIF1α pathway provides a therapeutic strategy for eradicating LSCs in CML.

HELM: a hierarchical notation language for complex biomolecule structure representation.

When biological macromolecules are used as therapeutic agents, it is often necessary to introduce non-natural chemical modifications to improve their pharmaceutical properties. The final products are complex structures where entities such as proteins, peptides, oligonucleotides, and small molecule drugs may be covalently linked to each other, or may include chemically modified biological moieties. An accurate in silico representation of these complex structures is essential, as it forms the basis for their electronic registration, storage, analysis, and visualization. The size of these molecules (henceforth referred to as "biomolecules") often makes them too unwieldy and impractical to represent at the atomic level, while the presence of non-natural chemical modifications makes it impossible to represent them by sequence alone. Here we describe the Hierarchical Editing Language for Macromolecules ("HELM") and demonstrate its utility in the representation of structures such as antisense oligonucleotides, short interference RNAs, peptides, proteins, and antibody drug conjugates.

Roadmap for the use of base editors to decipher drug mechanism of action.

CRISPR base editors are powerful tools for large-scale mutagenesis studies. This kind of approach can elucidate the mechanism of action of compounds, a key process in drug discovery. Here, we explore the utility of base editors in an early drug discovery context focusing on G-protein coupled receptors. A pooled mutagenesis screening framework was set up based on a modified version of the CRISPR-X base editor system. We determine optimized experimental conditions for mutagenesis where sgRNAs are delivered by cell transfection or viral infection over extended time periods (>14 days), resulting in high mutagenesis produced in a short region located at -4/+8 nucleotides with respect to the sgRNA match. The ß2 Adrenergic Receptor (B2AR) was targeted in this way employing a 6xCRE-mCherry reporter system to monitor its response to isoproterenol. The results of our screening indicate that residue 184 of B2AR is crucial for its activation. Based on our experience, we outline the crucial points to consider when designing and performing CRISPR-based pooled mutagenesis screening, including the typical technical hurdles encountered when studying compound pharmacology.

PFRED: A computational platform for siRNA and antisense oligonucleotides design.

PFRED a software application for the design, analysis, and visualization of antisense oligonucleotides and siRNA is described. The software provides an intuitive user-interface for scientists to design a library of siRNA or antisense oligonucleotides that target a specific gene of interest. Moreover, the tool facilitates the incorporation of various design criteria that have been shown to be important for stability and potency. PFRED has been made available as an open-source project so the code can be easily modified to address the future needs of the oligonucleotide research community. A compiled version is available for downloading at https://github.com/pfred/pfred-gui/releases/tag/v1.0 as a java Jar file. The source code and the links for downloading the precompiled version can be found at https://github.com/pfred.

Arrayed CRISPR reveals genetic regulators of tau aggregation, autophagy and mitochondria in Alzheimer's disease model.

Alzheimer's disease (AD) is a common neurodegenerative disease with poor prognosis. New options for drug discovery targets are needed. We developed an imaging based arrayed CRISPR method to interrogate the human genome for modulation of in vitro correlates of AD features, and used this to assess 1525 human genes related to tau aggregation, autophagy and mitochondria. This work revealed (I) a network of tau aggregation modulators including the NF-κB pathway and inflammatory signaling, (II) a correlation between mitochondrial morphology, respiratory function and transcriptomics, (III) machine learning predicted novel roles of genes and pathways in autophagic processes and (IV) individual gene function inferences and interactions among biological processes via multi-feature clustering. These studies provide a platform to interrogate underexplored aspects of AD biology and offer several specific hypotheses for future drug discovery efforts.

Identification and characterization of cell type-specific and ubiquitous chromatin regulatory structures in the human genome.

The identification of regulatory elements from different cell types is necessary for understanding the mechanisms controlling cell type-specific and housekeeping gene expression. Mapping DNaseI hypersensitive (HS) sites is an accurate method for identifying the location of functional regulatory elements. We used a high throughput method called DNase-chip to identify 3,904 DNaseI HS sites from six cell types across 1% of the human genome. A significant number (22%) of DNaseI HS sites from each cell type are ubiquitously present among all cell types studied. Surprisingly, nearly all of these ubiquitous DNaseI HS sites correspond to either promoters or insulator elements: 86% of them are located near annotated transcription start sites and 10% are bound by CTCF, a protein with known enhancer-blocking insulator activity. We also identified a large number of DNaseI HS sites that are cell type specific (only present in one cell type); these regions are enriched for enhancer elements and correlate with cell type-specific gene expression as well as cell type-specific histone modifications. Finally, we found that approximately 8% of the genome overlaps a DNaseI HS site in at least one the six cell lines studied, indicating that a significant percentage of the genome is potentially functional.

GluN2D-mediated excitatory drive onto medial prefrontal cortical PV+ fast-spiking inhibitory interneurons.

Deficits in fast-spiking inhibitory interneurons (FSINs) within the dorsolateral prefrontal cortex (dlPFC) are hypothesized to underlie cognitive impairment associated with schizophrenia. Though representing a minority of interneurons, this key cell type coordinates broad neural network gamma-frequency oscillations, associated with cognition and cognitive flexibility. Here we report expression of GluN2D mRNA selectively in parvalbumin positive cells of human postmortem dlPFC tissue, but not pyramidal neurons, with little to no GluN2C expression in either cell type. In acute murine mPFC slices the GluN2C/D selective positive allosteric modulator (PAM), CIQ(+), increased the intrinsic excitability as well as enhanced NMDAR-mediated EPSCs onto FSINs. This increase in intrinsic excitability with GluN2C/D PAM was also observed in the Dlx 5/6+/- FSIN developmental deficit model with reported FSIN hypoexcitability. Together these data speak to selective modulation of FSINs by a GluN2D PAM, providing a potential mechanism to counter the FSIN-deficit seen in schizophrenia.

Activated microglia cause metabolic disruptions in developmental cortical interneurons that persist in interneurons from individuals with schizophrenia.

The mechanisms by which prenatal immune activation increase the risk for neuropsychiatric disorders are unclear. Here, we generated developmental cortical interneurons (cINs)-which are known to be affected in schizophrenia (SCZ) when matured-from induced pluripotent stem cells (iPSCs) derived from healthy controls (HCs) and individuals with SCZ and co-cultured them with or without activated microglia. Co-culture with activated microglia disturbed metabolic pathways, as indicated by unbiased transcriptome analyses, and impaired mitochondrial function, arborization, synapse formation and synaptic GABA release. Deficits in mitochondrial function and arborization were reversed by alpha lipoic acid and acetyl-L-carnitine treatments, which boost mitochondrial function. Notably, activated-microglia-conditioned medium altered metabolism in cINs and iPSCs from HCs but not in iPSCs from individuals with SCZ or in glutamatergic neurons. After removal of activated-microglia-conditioned medium, SCZ cINs but not HC cINs showed prolonged metabolic deficits, which suggests that there is an interaction between SCZ genetic backgrounds and environmental risk factors.

Cell type-specific genetic regulation of gene expression across human tissues.

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.

Enhanced HTS hit selection via a local hit rate analysis.

The postprocessing of high-throughput screening (HTS) results is complicated by the occurrence of false positives (inactive compounds misidentified as active by the primary screen) and false negatives (active compounds misidentified as inactive by the primary screen). An activity cutoff is frequently used to select "active" compounds from HTS data; however, this approach is insensitive to both false positives and false negatives. An alternative method that can minimize the occurrence of these artifacts will increase the efficiency of hit selection and therefore lead discovery. In this work, rather than merely using the activity of a given compound, we look at the presence and absence of activity among all compounds in its "chemical space neighborhood" to give a degree of confidence in its activity. We demonstrate that this local hit rate (LHR) analysis method outperforms hit selection based on ranking by primary screen activity values across ten diverse high throughput screens, spanning both cell-based and biochemical assay formats of varying biology and robustness. On average, the local hit rate analysis method was approximately 2.3-fold and approximately 1.3-fold more effective in identifying active compounds and active chemical series, respectively, than selection based on primary activity alone. Moreover, when applied to finding false negatives, this method was 2.3-fold better than ranking by primary activity alone. In most cases, novel hit series were identified that would have otherwise been missed. Additional uses of and observations regarding this HTS analysis approach are also discussed.