Widespread and Functional RNA Circularization in Localized Prostate Cancer.

The cancer transcriptome is remarkably complex, including low-abundance transcripts, many not polyadenylated. To fully characterize the transcriptome of localized prostate cancer, we performed ultra-deep total RNA-seq on 144 tumors with rich clinical annotation. This revealed a linear transcriptomic subtype associated with the aggressive intraductal carcinoma sub-histology and a fusion profile that differentiates localized from metastatic disease. Analysis of back-splicing events showed widespread RNA circularization, with the average tumor expressing 7,232 circular RNAs (circRNAs). The degree of circRNA production was correlated to disease progression in multiple patient cohorts. Loss-of-function screening identified 11.3% of highly abundant circRNAs as essential for cell proliferation; for ∼90% of these, their parental linear transcripts were not essential. Individual circRNAs can have distinct functions, with circCSNK1G3 promoting cell growth by interacting with miR-181. These data advocate for adoption of ultra-deep RNA-seq without poly-A selection to interrogate both linear and circular transcriptomes.

The Evolutionary Landscape of Localized Prostate Cancers Drives Clinical Aggression.

The majority of newly diagnosed prostate cancers are slow growing, with a long natural life history. Yet a subset can metastasize with lethal consequences. We reconstructed the phylogenies of 293 localized prostate tumors linked to clinical outcome data. Multiple subclones were detected in 59% of patients, and specific subclonal architectures associate with adverse clinicopathological features. Early tumor development is characterized by point mutations and deletions followed by later subclonal amplifications and changes in trinucleotide mutational signatures. Specific genes are selectively mutated prior to or following subclonal diversification, including MTOR, NKX3-1, and RB1. Patients with low-risk monoclonal tumors rarely relapse after primary therapy (7%), while those with high-risk polyclonal tumors frequently do (61%). The presence of multiple subclones in an index biopsy may be necessary, but not sufficient, for relapse of localized prostate cancer, suggesting that evolution-aware biomarkers should be studied in prospective studies of low-risk tumors suitable for active surveillance.

Childhood cerebellar tumours mirror conserved fetal transcriptional programs.

Study of the origin and development of cerebellar tumours has been hampered by the complexity and heterogeneity of cerebellar cells that change over the course of development. Here we use single-cell transcriptomics to study more than 60,000 cells from the developing mouse cerebellum and show that different molecular subgroups of childhood cerebellar tumours mirror the transcription of cells from distinct, temporally restricted cerebellar lineages. The Sonic Hedgehog medulloblastoma subgroup transcriptionally mirrors the granule cell hierarchy as expected, while group 3 medulloblastoma resembles Nestin+ stem cells, group 4 medulloblastoma resembles unipolar brush cells, and PFA/PFB ependymoma and cerebellar pilocytic astrocytoma resemble the prenatal gliogenic progenitor cells. Furthermore, single-cell transcriptomics of human childhood cerebellar tumours demonstrates that many bulk tumours contain a mixed population of cells with divergent differentiation. Our data highlight cerebellar tumours as a disorder of early brain development and provide a proximate explanation for the peak incidence of cerebellar tumours in early childhood.

Prediction of acute myeloid leukaemia risk in healthy individuals.

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure1. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)4-8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.

Tracing the origins of relapse in acute myeloid leukaemia to stem cells.

In acute myeloid leukaemia, long-term survival is poor as most patients relapse despite achieving remission. Historically, the failure of therapy has been thought to be due to mutations that produce drug resistance, possibly arising as a consequence of the mutagenic properties of chemotherapy drugs. However, other lines of evidence have pointed to the pre-existence of drug-resistant cells. For example, deep sequencing of paired diagnosis and relapse acute myeloid leukaemia samples has provided direct evidence that relapse in some cases is generated from minor genetic subclones present at diagnosis that survive chemotherapy, suggesting that resistant cells are generated by evolutionary processes before treatment and are selected by therapy. Nevertheless, the mechanisms of therapy failure and capacity for leukaemic regeneration remain obscure, as sequence analysis alone does not provide insight into the cell types that are fated to drive relapse. Although leukaemia stem cells have been linked to relapse owing to their dormancy and self-renewal properties, and leukaemia stem cell gene expression signatures are highly predictive of therapy failure, experimental studies have been primarily correlative and a role for leukaemia stem cells in acute myeloid leukaemia relapse has not been directly proved. Here, through combined genetic and functional analysis of purified subpopulations and xenografts from paired diagnosis/relapse samples, we identify therapy-resistant cells already present at diagnosis and two major patterns of relapse. In some cases, relapse originated from rare leukaemia stem cells with a haematopoietic stem/progenitor cell phenotype, while in other instances relapse developed from larger subclones of immunophenotypically committed leukaemia cells that retained strong stemness transcriptional signatures. The identification of distinct patterns of relapse should lead to improved methods for disease management and monitoring in acute myeloid leukaemia. Moreover, the shared functional and transcriptional stemness properties that underlie both cellular origins of relapse emphasize the importance of developing new therapeutic approaches that target stemness to prevent relapse.

Genomic hallmarks of localized, non-indolent prostate cancer.

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns.

Pancreatic cancer, a highly aggressive tumour type with uniformly poor prognosis, exemplifies the classically held view of stepwise cancer development. The current model of tumorigenesis, based on analyses of precursor lesions, termed pancreatic intraepithelial neoplasm (PanINs) lesions, makes two predictions: first, that pancreatic cancer develops through a particular sequence of genetic alterations (KRAS, followed by CDKN2A, then TP53 and SMAD4); and second, that the evolutionary trajectory of pancreatic cancer progression is gradual because each alteration is acquired independently. A shortcoming of this model is that clonally expanded precursor lesions do not always belong to the tumour lineage, indicating that the evolutionary trajectory of the tumour lineage and precursor lesions can be divergent. This prevailing model of tumorigenesis has contributed to the clinical notion that pancreatic cancer evolves slowly and presents at a late stage. However, the propensity for this disease to rapidly metastasize and the inability to improve patient outcomes, despite efforts aimed at early detection, suggest that pancreatic cancer progression is not gradual. Here, using newly developed informatics tools, we tracked changes in DNA copy number and their associated rearrangements in tumour-enriched genomes and found that pancreatic cancer tumorigenesis is neither gradual nor follows the accepted mutation order. Two-thirds of tumours harbour complex rearrangement patterns associated with mitotic errors, consistent with punctuated equilibrium as the principal evolutionary trajectory. In a subset of cases, the consequence of such errors is the simultaneous, rather than sequential, knockout of canonical preneoplastic genetic drivers that are likely to set-off invasive cancer growth. These findings challenge the current progression model of pancreatic cancer and provide insights into the mutational processes that give rise to these aggressive tumours.

CHIP-MYTH: a novel interactive proteomics method for the assessment of agonist-dependent interactions of the human ß2-adrenergic receptor.

G-protein coupled receptors (GPCRs) are involved in a variety of disease processes and comprise major drug targets. However, the complexity of integral membrane proteins such as GPCRs makes the identification of their interacting partners and subsequent drug development challenging. A comprehensive understanding of GPCR protein interaction networks is needed to design effective therapeutic strategies to inhibit these drug targets. Here, we developed a novel split-ubiquitin membrane yeast two-hybrid (MYTH) technology called CHIP-MYTH, which allows the unbiased characterization of interaction partners of full-length GPCRs in a drug-dependent manner. This was achieved by coupling DNA microarray technology to the MYTH approach, which allows a quantitative evaluation of interacting partners of a given integral membrane protein in the presence or absence of drug. As a proof of principle, we applied the CHIP-MYTH approach to the human ß2-adrenergic receptor (ß2AR), a target of interest in the treatment of asthma, chronic obstructive pulmonary disease (COPD), neurological disease, cardiovascular disease, and obesity. A CHIP-MYTH screen was performed in the presence or absence of salmeterol, a long-acting ß2AR-agonist. Our results suggest that ß2AR activation with salmeterol can induce the dissociation of heterotrimeric G-proteins, Gαßγ, into Gα and Gßγ subunits, which in turn activates downstream signaling cascades. Using CHIP-MYTH, we confirmed previously known and identified novel ß2AR interactors involved in GPCR-mediated signaling cascades. Several of these interactions were confirmed in mammalian cells using LUminescence-based Mammalian IntERactome (LUMIER) and co-immunoprecipitation assays. In summary, the CHIP-MYTH approach is ideal for conducting comprehensive protein-protein interactions (PPI) screenings of full-length GPCRs in the presence or absence of drugs, thus providing a valuable tool to further our understanding of GPCR-mediated signaling.

Multiple means to the same end: the genetic basis of acquired stress resistance in yeast.

In nature, stressful environments often occur in combination or close succession, and thus the ability to prepare for impending stress likely provides a significant fitness advantage. Organisms exposed to a mild dose of stress can become tolerant to what would otherwise be a lethal dose of subsequent stress; however, the mechanism of this acquired stress tolerance is poorly understood. To explore this, we exposed the yeast gene-deletion libraries, which interrogate all essential and non-essential genes, to successive stress treatments and identified genes necessary for acquiring subsequent stress resistance. Cells were exposed to one of three different mild stress pretreatments (salt, DTT, or heat shock) and then challenged with a severe dose of hydrogen peroxide (H(2)O(2)). Surprisingly, there was little overlap in the genes required for acquisition of H(2)O(2) tolerance after different mild-stress pretreatments, revealing distinct mechanisms of surviving H(2)O(2) in each case. Integrative network analysis of these results with respect to protein-protein interactions, synthetic-genetic interactions, and functional annotations identified many processes not previously linked to H(2)O(2) tolerance. We tested and present several models that explain the lack of overlap in genes required for H(2)O(2) tolerance after each of the three pretreatments. Together, this work shows that acquired tolerance to the same severe stress occurs by different mechanisms depending on prior cellular experiences, underscoring the context-dependent nature of stress tolerance.

Oncogenic ETS fusions promote DNA damage and proinflammatory responses via pericentromeric RNAs in extracellular vesicles.

Aberrant expression of the E26 transformation-specific (ETS) transcription factors characterizes numerous human malignancies. Many of these proteins, including EWS:FLI1 and EWS:ERG fusions in Ewing sarcoma (EwS) and TMPRSS2:ERG in prostate cancer (PCa), drive oncogenic programs via binding to GGAA repeats. We report here that both EWS:FLI1 and ERG bind and transcriptionally activate GGAA-rich pericentromeric heterochromatin. The respective pathogen-like HSAT2 and HSAT3 RNAs, together with LINE, SINE, ERV, and other repeat transcripts, are expressed in EwS and PCa tumors, secreted in extracellular vesicles (EVs), and are highly elevated in plasma of patients with EwS with metastatic disease. High human satellite 2 and 3 (HSAT2,3) levels in EWS:FLI1- or ERG-expressing cells and tumors were associated with induction of G2/M checkpoint, mitotic spindle, and DNA damage programs. These programs were also activated in EwS EV-treated fibroblasts, coincident with accumulation of HSAT2,3 RNAs, proinflammatory responses, mitotic defects, and senescence. Mechanistically, HSAT2,3-enriched cancer EVs induced cGAS-TBK1 innate immune signaling and formation of cytosolic granules positive for double-strand RNAs, RNA-DNA, and cGAS. Hence, aberrantly expressed ETS proteins derepress pericentromeric heterochromatin, yielding pathogenic RNAs that transmit genotoxic stress and inflammation to local and distant sites. Monitoring HSAT2,3 plasma levels and preventing their dissemination may thus improve therapeutic strategies and blood-based diagnostics.

Early Cancer Detection in Li-Fraumeni Syndrome with Cell-Free DNA.

People with Li-Fraumeni syndrome (LFS) harbor a germline pathogenic variant in the TP53 tumor suppressor gene, face a near 100% lifetime risk of cancer, and routinely undergo intensive surveillance protocols. Liquid biopsy has become an attractive tool for a range of clinical applications, including early cancer detection. Here, we provide a proof-of-principle for a multimodal liquid biopsy assay that integrates a targeted gene panel, shallow whole-genome, and cell-free methylated DNA immunoprecipitation sequencing for the early detection of cancer in a longitudinal cohort of 89 LFS patients. Multimodal analysis increased our detection rate in patients with an active cancer diagnosis over uni-modal analysis and was able to detect cancer-associated signal(s) in carriers prior to diagnosis with conventional screening (positive predictive value = 67.6%, negative predictive value = 96.5%). Although adoption of liquid biopsy into current surveillance will require further clinical validation, this study provides a framework for individuals with LFS. SIGNIFICANCE: By utilizing an integrated cell-free DNA approach, liquid biopsy shows earlier detection of cancer in patients with LFS compared with current clinical surveillance methods such as imaging. Liquid biopsy provides improved accessibility and sensitivity, complementing current clinical surveillance methods to provide better care for these patients. See related commentary by Latham et al., p. 23. This article is featured in Selected Articles from This Issue, p. 5.

A polygenic two-hit hypothesis for prostate cancer.

Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

Identification of yeast genes that confer resistance to chitosan oligosaccharide (COS) using chemogenomics.

BACKGROUND: Chitosan oligosaccharide (COS), a deacetylated derivative of chitin, is an abundant, and renewable natural polymer. COS has higher antimicrobial properties than chitosan and is presumed to act by disrupting/permeabilizing the cell membranes of bacteria, yeast and fungi. COS is relatively non-toxic to mammals. By identifying the molecular and genetic targets of COS, we hope to gain a better understanding of the antifungal mode of action of COS. RESULTS: Three different chemogenomic fitness assays, haploinsufficiency (HIP), homozygous deletion (HOP), and multicopy suppression (MSP) profiling were combined with a transcriptomic analysis to gain insight in to the mode of action and mechanisms of resistance to chitosan oligosaccharides. The fitness assays identified 39 yeast deletion strains sensitive to COS and 21 suppressors of COS sensitivity. The genes identified are involved in processes such as RNA biology (transcription, translation and regulatory mechanisms), membrane functions (e.g. signalling, transport and targeting), membrane structural components, cell division, and proteasome processes. The transcriptomes of control wild type and 5 suppressor strains overexpressing ARL1, BCK2, ERG24, MSG5, or RBA50, were analyzed in the presence and absence of COS. Some of the up-regulated transcripts in the suppressor overexpressing strains exposed to COS included genes involved in transcription, cell cycle, stress response and the Ras signal transduction pathway. Down-regulated transcripts included those encoding protein folding components and respiratory chain proteins. The COS-induced transcriptional response is distinct from previously described environmental stress responses (i.e. thermal, salt, osmotic and oxidative stress) and pre-treatment with these well characterized environmental stressors provided little or any resistance to COS. CONCLUSIONS: Overexpression of the ARL1 gene, a member of the Ras superfamily that regulates membrane trafficking, provides protection against COS-induced cell membrane permeability and damage. We found that the ARL1 COS-resistant over-expression strain was as sensitive to Amphotericin B, Fluconazole and Terbinafine as the wild type cells and that when COS and Fluconazole are used in combination they act in a synergistic fashion. The gene targets of COS identified in this study indicate that COS's mechanism of action is different from other commonly studied fungicides that target membranes, suggesting that COS may be an effective fungicide for drug-resistant fungal pathogens.

Quantitative phenotyping via deep barcode sequencing.

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or "Bar-seq," outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that approximately 20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene-environment interactions on a genome-wide scale.

Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples.

Next-generation sequencing has proven an extremely effective technology for molecular counting applications where the number of sequence reads provides a digital readout for RNA-seq, ChIP-seq, Tn-seq and other applications. The extremely large number of sequence reads that can be obtained per run permits the analysis of increasingly complex samples. For lower complexity samples, however, a point of diminishing returns is reached when the number of counts per sequence results in oversampling with no increase in data quality. A solution to making next-generation sequencing as efficient and affordable as possible involves assaying multiple samples in a single run. Here, we report the successful 96-plexing of complex pools of DNA barcoded yeast mutants and show that such 'Bar-seq' assessment of these samples is comparable with data provided by barcode microarrays, the current benchmark for this application. The cost reduction and increased throughput permitted by highly multiplexed sequencing will greatly expand the scope of chemogenomics assays and, equally importantly, the approach is suitable for other sequence counting applications that could benefit from massive parallelization.

Molecular and Pathology Features of Colorectal Tumors and Patient Outcomes Are Associated with Fusobacterium nucleatum and Its Subspecies animalis.

BACKGROUND: Fusobacterium nucleatum (F. nucleatum) activates oncogenic signaling pathways and induces inflammation to promote colorectal carcinogenesis. METHODS: We characterized F. nucleatum and its subspecies in colorectal tumors and examined associations with tumor characteristics and colorectal cancer-specific survival. We conducted deep sequencing of nusA, nusG, and bacterial 16s rRNA genes in tumors from 1,994 patients with colorectal cancer and assessed associations between F. nucleatum presence and clinical characteristics, colorectal cancer-specific mortality, and somatic mutations. RESULTS: F. nucleatum, which was present in 10.3% of tumors, was detected in a higher proportion of right-sided and advanced-stage tumors, particularly subspecies animalis. Presence of F. nucleatum was associated with higher colorectal cancer-specific mortality (HR, 1.97; P = 0.0004). This association was restricted to nonhypermutated, microsatellite-stable tumors (HR, 2.13; P = 0.0002) and those who received chemotherapy [HR, 1.92; confidence interval (CI), 1.07-3.45; P = 0.029). Only F. nucleatum subspecies animalis, the main subspecies detected (65.8%), was associated with colorectal cancer-specific mortality (HR, 2.16; P = 0.0016), subspecies vincentii and nucleatum were not (HR, 1.07; P = 0.86). Additional adjustment for tumor stage suggests that the effect of F. nucleatum on mortality is partly driven by a stage shift. Presence of F. nucleatum was associated with microsatellite instable tumors, tumors with POLE exonuclease domain mutations, and ERBB3 mutations, and suggestively associated with TP53 mutations. CONCLUSIONS: F. nucleatum, and particularly subspecies animalis, was associated with a higher colorectal cancer-specific mortality and specific somatic mutated genes. IMPACT: Our findings identify the F. nucleatum subspecies animalis as negatively impacting colorectal cancer mortality, which may occur through a stage shift and its effect on chemoresistance.

A comprehensive platform for highly multiplexed mammalian functional genetic screens.

BACKGROUND: Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens. RESULTS: Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens. CONCLUSION: Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.

Yeast Barcoders: a chemogenomic application of a universal donor-strain collection carrying bar-code identifiers.

The ability to perform complex bioassays in parallel enables experiments that are otherwise impossible because of throughput and cost constraints. For example, highly parallel chemical-genetic screens using pooled collections of thousands of defined Saccharomyces cerevisiae gene deletion strains are feasible because each strain is bar-coded with unique DNA sequences. It is, however, time-consuming and expensive to individually bar-code individual strains. To provide a simple and general method of barcoding yeast collections, we built a set of donor strains, called Barcoders, with unique bar codes that can be systematically transferred to any S. cerevisiae collection. We applied this technology by generating a collection of bar-coded 'decreased abundance by mRNA perturbation' (DAmP) loss-of-function strains comprising 87.1% of all essential yeast genes. These experiments validate both the Barcoders and the DAmP strain collection as useful tools for genome-wide chemical-genetic assays.

Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast.

To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac) interfered with establishment of cell polarity, cyproheptadine (Periactin) targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil) interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril) had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol) and pimozide (Orap). Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes.