Genome-wide translocation sequencing reveals mechanisms of chromosome breaks and rearrangements in B cells.

Whereas chromosomal translocations are common pathogenetic events in cancer, mechanisms that promote them are poorly understood. To elucidate translocation mechanisms in mammalian cells, we developed high-throughput, genome-wide translocation sequencing (HTGTS). We employed HTGTS to identify tens of thousands of independent translocation junctions involving fixed I-SceI meganuclease-generated DNA double-strand breaks (DSBs) within the c-myc oncogene or IgH locus of B lymphocytes induced for activation-induced cytidine deaminase (AID)-dependent IgH class switching. DSBs translocated widely across the genome but were preferentially targeted to transcribed chromosomal regions. Additionally, numerous AID-dependent and AID-independent hot spots were targeted, with the latter comprising mainly cryptic I-SceI targets. Comparison of translocation junctions with genome-wide nuclear run-ons revealed a marked association between transcription start sites and translocation targeting. The majority of translocation junctions were formed via end-joining with short microhomologies. Our findings have implications for diverse fields, including gene therapy and cancer genomics.

Total RNA sequencing reveals gene expression and microbial alterations shared by oral pre-malignant lesions and cancer.

Head and neck cancers are a complex malignancy comprising multiple anatomical sites, with cancer of the oral cavity ranking among the deadliest and the most disfiguring cancers globally. Oral cancer (OC) constitutes a subset of head and neck cancer cases, presenting primarily as tobacco- and alcohol-associated oral squamous cell carcinoma (OSCC), with a 5-year survival rate of ~ 65%, partly due to the lack of early detection and effective treatments. OSCC arises from premalignant lesions (PMLs) in the oral cavity through a multi-step series of clinical and histopathological stages, including varying degrees of epithelial dysplasia. To gain insights into the molecular mechanisms associated with the progression of PMLs to OSCC, we profiled the whole transcriptome of 66 human PMLs comprising leukoplakia with dysplasia and hyperkeratosis non-reactive (HkNR) pathologies, alongside healthy controls and OSCC. Our data revealed that PMLs were enriched in gene signatures associated with cellular plasticity, such as partial EMT (p-EMT) phenotypes, and with immune response. Integrated analyses of the host transcriptome and microbiome further highlighted a significant association between differential microbial abundance and PML pathway activity, suggesting a contribution of the oral microbiome toward PML evolution to OSCC. Collectively, this study reveals molecular processes associated with PML progression that may help early diagnosis and disease interception at an early stage.

Structure learning for gene regulatory networks.

Inference of biological network structures is often performed on high-dimensional data, yet is hindered by the limited sample size of high throughput "omics" data typically available. To overcome this challenge, often referred to as the "small n, large p problem," we exploit known organizing principles of biological networks that are sparse, modular, and likely share a large portion of their underlying architecture. We present SHINE-Structure Learning for Hierarchical Networks-a framework for defining data-driven structural constraints and incorporating a shared learning paradigm for efficiently learning multiple Markov networks from high-dimensional data at large p/n ratios not previously feasible. We evaluated SHINE on Pan-Cancer data comprising 23 tumor types, and found that learned tumor-specific networks exhibit expected graph properties of real biological networks, recapture previously validated interactions, and recapitulate findings in literature. Application of SHINE to the analysis of subtype-specific breast cancer networks identified key genes and biological processes for tumor maintenance and survival as well as potential therapeutic targets for modulating known breast cancer disease genes.

Antisense Transcripts Delimit Exonucleolytic Activity of the Mitochondrial 3' Processome to Generate Guide RNAs.

Small, noncoding RNA biogenesis typically involves cleavage of structured precursor by RNase III-like endonucleases. However, guide RNAs (gRNAs) that direct U-insertion/deletion mRNA editing in mitochondria of trypanosomes maintain 5' triphosphate characteristic of the transcription initiation and possess a U-tail indicative of 3' processing and uridylation. Here, we identified a protein complex composed of RET1 TUTase, DSS1 3'-5' exonuclease, and three additional subunits. This complex, termed mitochondrial 3' processome (MPsome), is responsible for primary uridylation of ∼800 nt gRNA precursors, their processive degradation to a mature size of 40-60 nt, and secondary U-tail addition. Both strands of the gRNA gene are transcribed into sense and antisense precursors of similar lengths. Head-to-head hybridization of these transcripts blocks symmetrical 3'-5' degradation at a fixed distance from the double-stranded region. Together, our findings suggest a model in which gRNA is derived from the 5' extremity of a primary molecule by uridylation-induced, antisense transcription-controlled 3'-5' exonucleolytic degradation.

Yap suppresses T-cell function and infiltration in the tumor microenvironment.

A major challenge for cancer immunotherapy is sustaining T-cell activation and recruitment in immunosuppressive solid tumors. Here, we report that the levels of the Hippo pathway effector Yes-associated protein (Yap) are sharply induced upon the activation of cluster of differentiation 4 (CD4)-positive and cluster of differentiation 8 (CD8)-positive T cells and that Yap functions as an immunosuppressive factor and inhibitor of effector differentiation. Loss of Yap in T cells results in enhanced T-cell activation, differentiation, and function, which translates in vivo to an improved ability for T cells to infiltrate and repress tumors. Gene expression analyses of tumor-infiltrating T cells following Yap deletion implicates Yap as a mediator of global T-cell responses in the tumor microenvironment and as a negative regulator of T-cell tumor infiltration and patient survival in diverse human cancers. Collectively, our results indicate that Yap plays critical roles in T-cell biology and suggest that Yap inhibition improves T-cell responses in cancer.

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data.

As high-throughput genomics assays become more efficient and cost effective, their utilization has become standard in large-scale biomedical projects. These studies are often explorative, in that relationships between samples are not explicitly defined a priori, but rather emerge from data-driven discovery and annotation of molecular subtypes, thereby informing hypotheses and independent evaluation. Here, we present K2Taxonomer, a novel unsupervised recursive partitioning algorithm and associated R package that utilize ensemble learning to identify robust subgroups in a 'taxonomy-like' structure. K2Taxonomer was devised to accommodate different data paradigms, and is suitable for the analysis of both bulk and single-cell transcriptomics, and other '-omics', data. For each of these data types, we demonstrate the power of K2Taxonomer to discover known relationships in both simulated and human tissue data. We conclude with a practical application on breast cancer tumor infiltrating lymphocyte (TIL) single-cell profiles, in which we identified co-expression of translational machinery genes as a dominant transcriptional program shared by T cells subtypes, associated with better prognosis in breast cancer tissue bulk expression data.

Naturally occurring hotspot cancer mutations in Gα13 promote oncogenic signaling.

Heterotrimeric G-proteins are signaling switches broadly divided into four families based on the sequence and functional similarity of their Gα subunits: Gs, Gi/o, Gq/11, and G12/13 Artificial mutations that activate Gα subunits of each of these families have long been known to induce oncogenic transformation in experimental systems. With the advent of next-generation sequencing, activating hotspot mutations in Gs, Gi/o, or Gq/11 proteins have also been identified in patient tumor samples. In contrast, patient tumor-associated G12/13 mutations characterized to date lead to inactivation rather than activation. By using bioinformatic pathway analysis and signaling assays, here we identified cancer-associated hotspot mutations in Arg-200 of Gα13 (encoded by GNA13) as potent activators of oncogenic signaling. First, we found that components of a G12/13-dependent signaling cascade that culminates in activation of the Hippo pathway effectors YAP and TAZ is frequently altered in bladder cancer. Up-regulation of this signaling cascade correlates with increased YAP/TAZ activation transcriptional signatures in this cancer type. Among the G12/13 pathway alterations were mutations in Arg-200 of Gα13, which we validated to promote YAP/TAZ-dependent (TEAD) and MRTF-A/B-dependent (SRE.L) transcriptional activity. We further showed that this mechanism relies on the same RhoGEF-RhoGTPase cascade components that are up-regulated in bladder cancers. Moreover, Gα13 Arg-200 mutants induced oncogenic transformation in vitro as determined by focus formation assays. In summary, our findings on Gα13 mutants establish that naturally occurring hotspot mutations in Gα subunits of any of the four families of heterotrimeric G-proteins are putative cancer drivers.

PPR polyadenylation factor defines mitochondrial mRNA identity and stability in trypanosomes.

In Trypanosoma brucei, most mitochondrial mRNAs undergo internal changes by RNA editing and 3' end modifications. The temporally separated and functionally distinct modifications are manifested by adenylation prior to editing, and by post-editing extension of a short A-tail into a long A/U-heteropolymer. The A-tail stabilizes partially and fully edited mRNAs, while the A/U-tail enables mRNA binding to the ribosome. Here, we identify an essential pentatricopeptide repeat-containing RNA binding protein, kinetoplast polyadenylation factor 3 (KPAF3), and demonstrate its role in protecting pre-mRNA against degradation by the processome. We show that KPAF3 recruits KPAP1 poly(A) polymerase to the 3' terminus, thus leading to pre-mRNA stabilization, or decay depending on the occurrence and extent of editing. In vitro, KPAF3 stimulates KPAP1 activity and inhibits mRNA uridylation by RET1 TUTase. Our findings indicate that KPAF3 selectively directs pre-mRNA toward adenylation rather than uridylation, which is a default post-trimming modification characteristic of ribosomal and guide RNAs. As a quality control mechanism, KPAF3 binding ensures that mRNAs entering the editing pathway are adenylated and, therefore, competent for post-editing A/U-tailing and translational activation.

hypeR: an R package for geneset enrichment workflows.

SUMMARY: Geneset enrichment is a popular method for annotating high-throughput sequencing data. Existing tools fall short in providing the flexibility to tackle the varied challenges researchers face in such analyses, particularly when analyzing many signatures across multiple experiments. We present a comprehensive R package for geneset enrichment workflows that offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting. hypeR is a one-stop solution to performing geneset enrichment for a wide audience and range of use cases. AVAILABILITY AND IMPLEMENTATION: The most recent version of the package is available at https://github.com/montilab/hypeR.

PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects.

MOTIVATION: Over the last decade, more diverse populations have been included in genome-wide association studies. If a genetic variant has a varying effect on a phenotype in different populations, genome-wide association studies applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery. RESULTS: In this paper, we propose PopCluster: an algorithm to automatically discover subsets of individuals in which the genetic effects of a variant are statistically different. PopCluster provides a simple framework to directly analyze genotype data without prior knowledge of subjects' ethnicities. PopCluster combines logistic regression modeling, principal component analysis, hierarchical clustering and a recursive bottom-up tree parsing procedure. The evaluation of PopCluster suggests that the algorithm has a stable low false positive rate (∼4%) and high true positive rate (>80%) in simulations with large differences in allele frequencies between cases and controls. Application of PopCluster to data from genetic studies of longevity discovers ethnicity-dependent heterogeneity in the association of rs3764814 (USP42) with the phenotype. AVAILABILITY AND IMPLEMENTATION: PopCluster was implemented using the R programming language, PLINK and Eigensoft software, and can be found at the following GitHub repository: https://github.com/gurinovich/PopCluster with instructions on its installation and usage. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CXCR4 upregulation is an indicator of sensitivity to B-cell receptor/PI3K blockade and a potential resistance mechanism in B-cell receptor-dependent diffuse large B-cell lymphomas.

B-cell receptor (BCR) signaling pathway components represent promising treatment targets in multiple B-cell malignancies including diffuse large B-cell lymphoma (DLBCL). In in vitro and in vivo model systems, a subset of DLBCLs depend upon BCR survival signals and respond to proximal BCR/phosphoinositide 3 kinase (PI3K) blockade. However, single-agent BCR pathway inhibitors have had more limited activity in patients with DLBCL, underscoring the need for indicators of sensitivity to BCR blockade and insights into potential resistance mechanisms. Here, we report highly significant transcriptional upregulation of C-X-C chemokine receptor 4 (CXCR4) in BCR-dependent DLBCL cell lines and primary tumors following chemical spleen tyrosine kinase (SYK) inhibition, molecular SYK depletion or chemical PI3K blockade. SYK or PI3K inhibition also selectively upregulated cell surface CXCR4 protein expression in BCR-dependent DLBCLs. CXCR4 expression was directly modulated by fork-head box O1 via the PI3K/protein kinase B/forkhead box O1 signaling axis. Following chemical SYK inhibition, all BCR-dependent DLBCLs exhibited significantly increased stromal cell-derived factor-1α (SDF-1α) induced chemotaxis, consistent with the role of CXCR4 signaling in B-cell migration. Select PI3K isoform inhibitors also augmented SDF-1α induced chemotaxis. These data define CXCR4 upregulation as an indicator of sensitivity to BCR/PI3K blockade and identify CXCR4 signaling as a potential resistance mechanism in BCR-dependent DLBCLs.

Glutamine-utilizing transaminases are a metabolic vulnerability of TAZ/YAP-activated cancer cells.

The transcriptional regulators TAZ and YAP (TAZ/YAP) have emerged as pro-tumorigenic factors that drive many oncogenic traits, including induction of cell growth, resistance to cell death, and activation of processes that promote migration and invasion. Here, we report that TAZ/YAP reprogram cellular energetics to promote the dependence of breast cancer cell growth on exogenous glutamine. Rescue experiments with glutamine-derived metabolites suggest an essential role for glutamate and α-ketoglutarate (AKG) in TAZ/YAP-driven cell growth in the absence of glutamine. Analysis of enzymes that mediate the conversion of glutamate to AKG shows that TAZ/YAP induce glutamic-oxaloacetic transaminase (GOT1) and phosphoserine aminotransferase (PSAT1) expression and that TAZ/YAP activity positively correlates with transaminase expression in breast cancer patients. Notably, we find that the transaminase inhibitor aminooxyacetate (AOA) represses cell growth in a TAZ/YAP-dependent manner, identifying transamination as a potential vulnerable metabolic requirement for TAZ/YAP-driven breast cancer.

How the AHR Became Important in Cancer: The Role of Chronically Active AHR in Cancer Aggression.

For decades, the aryl hydrocarbon receptor (AHR) was studied for its role in environmental chemical toxicity i.e., as a quirk of nature and a mediator of unintended consequences of human pollution. During that period, it was not certain that the AHR had a "normal" physiological function. However, the ongoing accumulation of data from an ever-expanding variety of studies on cancer, cancer immunity, autoimmunity, organ development, and other areas bears witness to a staggering array of AHR-controlled normal and pathological activities. The objective of this review is to discuss how the AHR has gone from a likely contributor to genotoxic environmental carcinogen-induced cancer to a master regulator of malignant cell progression and cancer aggression. Particular focus is placed on the association between AHR activity and poor cancer outcomes, feedback loops that control chronic AHR activity in cancer, and the role of chronically active AHR in driving cancer cell invasion, migration, cancer stem cell characteristics, and survival.

Inhibition of Ubc13-mediated Ubiquitination by GPS2 Regulates Multiple Stages of B Cell Development.

Non-proteolytic ubiquitin signaling mediated by Lys63 ubiquitin chains plays a critical role in multiple pathways that are key to the development and activation of immune cells. Our previous work indicates that GPS2 (G-protein Pathway Suppressor 2) is a multifunctional protein regulating TNFα signaling and lipid metabolism in the adipose tissue through modulation of Lys63 ubiquitination events. However, the full extent of GPS2-mediated regulation of ubiquitination and the underlying molecular mechanisms are unknown. Here, we report that GPS2 is required for restricting the activation of TLR and BCR signaling pathways and the AKT/FOXO1 pathway in immune cells based on direct inhibition of Ubc13 enzymatic activity. Relevance of this regulatory strategy is confirmed in vivo by B cell-targeted deletion of GPS2, resulting in developmental defects at multiple stages of B cell differentiation. Together, these findings reveal that GPS2 genomic and non-genomic functions are critical for the development and cellular homeostasis of B cells.

Diffuse large B-cell lymphoma patient-derived xenograft models capture the molecular and biological heterogeneity of the disease.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined by transcriptional classifications, specific signaling and survival pathways, and multiple low-frequency genetic alterations. Preclinical model systems that capture the genetic and functional heterogeneity of DLBCL are urgently needed. Here, we generated and characterized a panel of large B-cell lymphoma (LBCL) patient-derived xenograft (PDX) models, including 8 that reflect the immunophenotypic, transcriptional, genetic, and functional heterogeneity of primary DLBCL and 1 that is a plasmablastic lymphoma. All LBCL PDX models were subjected to whole-transcriptome sequencing to classify cell of origin and consensus clustering classification (CCC) subtypes. Mutations and chromosomal rearrangements were evaluated by whole-exome sequencing with an extended bait set. Six of the 8 DLBCL models were activated B-cell (ABC)-type tumors that exhibited ABC-associated mutations such as MYD88, CD79B, CARD11, and PIM1. The remaining 2 DLBCL models were germinal B-cell type, with characteristic alterations of GNA13, CREBBP, and EZH2, and chromosomal translocations involving IgH and either BCL2 or MYC Only 25% of the DLBCL PDX models harbored inactivating TP53 mutations, whereas 75% exhibited copy number alterations of TP53 or its upstream modifier, CDKN2A, consistent with the reported incidence and type of p53 pathway alterations in primary DLBCL. By CCC criteria, 6 of 8 DLBCL PDX models were B-cell receptor (BCR)-type tumors that exhibited selective surface immunoglobulin expression and sensitivity to entospletinib, a recently developed spleen tyrosine kinase inhibitor. In summary, we have established and characterized faithful PDX models of DLBCL and demonstrated their usefulness in functional analyses of proximal BCR pathway inhibition.

Targetable genetic features of primary testicular and primary central nervous system lymphomas.

Primary central nervous system lymphomas (PCNSLs) and primary testicular lymphomas (PTLs) are extranodal large B-cell lymphomas (LBCLs) with inferior responses to current empiric treatment regimens. To identify targetable genetic features of PCNSL and PTL, we characterized their recurrent somatic mutations, chromosomal rearrangements, copy number alterations (CNAs), and associated driver genes, and compared these comprehensive genetic signatures to those of diffuse LBCL and primary mediastinal large B-cell lymphoma (PMBL). These studies identify unique combinations of genetic alterations in discrete LBCL subtypes and subtype-selective bases for targeted therapy. PCNSLs and PTLs frequently exhibit genomic instability, and near-uniform, often biallelic, CDKN2A loss with rare TP53 mutations. PCNSLs and PTLs also use multiple genetic mechanisms to target key genes and pathways and exhibit near-uniform oncogenic Toll-like receptor signaling as a result of MYD88 mutation and/or NFKBIZ amplification, frequent concurrent B-cell receptor pathway activation, and deregulation of BCL6. Of great interest, PCNSLs and PTLs also have frequent 9p24.1/PD-L1/PD-L2 CNAs and additional translocations of these loci, structural bases of immune evasion that are shared with PMBL.

Tributyltin induces a transcriptional response without a brite adipocyte signature in adipocyte models.

Tributyltin (TBT), a peroxisome proliferator-activated receptor γ (PPARγ)/retinoid X receptor (RXR) ligand and founding member of the environmental obesogen chemical class, induces adipocyte differentiation and suppresses bone formation. A growing number of environmental PPARγ ligands are being identified. However, the potential for environmental PPARγ ligands to induce adverse metabolic effects has been questioned because PPARγ is a therapeutic target in treatment of type II diabetes. We evaluated the molecular consequences of TBT exposure during bone marrow multipotent mesenchymal stromal cell (BM-MSC) differentiation in comparison to rosiglitazone, a therapeutic PPARγ ligand, and LG100268, a synthetic RXR ligand. Mouse primary BM-MSCs (female, C57BL/6J) undergoing bone differentiation were exposed to maximally efficacious and human relevant concentrations of rosiglitazone (100 nM), LG100268 (100 nM) or TBT (80 nM) for 4 days. Gene expression was assessed using microarrays, and in silico functional annotation was performed using pathway enrichment analysis approaches. Pathways related to osteogenesis were downregulated by all three ligands, while pathways related to adipogenesis were upregulated by rosiglitazone and TBT. However, pathways related to mitochondrial biogenesis and brown-in-white (brite) adipocyte differentiation were more significantly upregulated in rosiglitazone-treated than TBT-treated cells. The lack of induction of genes involved in adipocyte energy dissipation by TBT was confirmed by an independent gene expression analysis in BM-MSCs undergoing adipocyte differentiation and by analysis of a publically available 3T3 L1 data set. Furthermore, rosiglitazone, but not TBT, induced mitochondrial biogenesis and respiration. This study is the first to show that an environmental PPARγ ligand has a limited capacity to induce health-promoting activities of PPARγ.

Towards Resolving the Pro- and Anti-Tumor Effects of the Aryl Hydrocarbon Receptor.

We have postulated that the aryl hydrocarbon receptor (AHR) drives the later, more lethal stages of some cancers when chronically activated by endogenous ligands. However, other studies have suggested that, under some circumstances, the AHR can oppose tumor aggression. Resolving this apparent contradiction is critical to the design of AHR-targeted cancer therapeutics. Molecular (siRNA, shRNA, AHR repressor, CRISPR-Cas9) and pharmacological (AHR inhibitors) approaches were used to confirm the hypothesis that AHR inhibition reduces human cancer cell invasion (irregular colony growth in 3D Matrigel cultures and Boyden chambers), migration (scratch wound assay) and metastasis (human cancer cell xenografts in zebrafish). Furthermore, these assays were used for a head-to-head comparison between AHR antagonists and agonists. AHR inhibition or knockdown/knockout consistently reduced human ER−/PR−/Her2− and inflammatory breast cancer cell invasion, migration, and metastasis. This was associated with a decrease in invasion-associated genes (e.g., Fibronectin, VCAM1, Thrombospondin, MMP1) and an increase in CDH1/E-cadherin, previously associated with decreased tumor aggression. Paradoxically, AHR agonists (2,3,7,8-tetrachlorodibenzo-p-dioxin and/or 3,3′-diindolylmethane) similarly inhibited irregular colony formation in Matrigel and blocked metastasis in vivo but accelerated migration. These data demonstrate the complexity of modulating AHR activity in cancer while suggesting that AHR inhibitors, and, under some circumstances, AHR agonists, may be useful as cancer therapeutics.

Network-based analysis of transcriptional profiles from chemical perturbations experiments.

BACKGROUND: Methods for inference and comparison of biological networks are emerging as powerful tools for the identification of groups of tightly connected genes whose activity may be altered during disease progression or due to chemical perturbations. Connectivity-based comparisons help identify aggregate changes that would be difficult to detect with differential analysis methods comparing individual genes. METHODS: In this study, we describe a pipeline for network comparison and its application to the analysis of gene expression datasets from chemical perturbation experiments, with the goal of elucidating the modes of actions of the profiled perturbations. We apply our pipeline to the analysis of the DrugMatrix and the TG-GATEs, two of the largest toxicogenomics resources available, containing gene expression measurements for model organisms exposed to hundreds of chemical compounds with varying carcinogenicity and genotoxicity. RESULTS: Starting from chemical-specific transcriptional networks inferred from these data, we show that the proposed comparative analysis of their associated networks identifies groups of chemicals with similar functions and similar carcinogenicity/genotoxicity profiles. We also show that the in-silico annotation by pathway enrichment analysis of the gene modules with a significant gain or loss of connectivity for specific groups of compounds can reveal molecular pathways significantly associated with the chemical perturbations and their likely modes of action. CONCLUSIONS: The proposed pipeline for transcriptional network inference and comparison is highly reproducible and allows grouping chemicals with similar functions and carcinogenicity/genotoxicity profiles. In the context of drug discovery or drug repositioning, the methods presented here could help assign new functions to novel or existing drugs, based on the similarity of their associated network with those built for other known compounds. Additionally, the method has broad applicability beyond the uses here described and could be used as an alternative or as a complement to standard approaches of differential gene expression analysis.

Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data.

Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log2 number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.