PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

Integrative multi-omics module network inference with Lemon-Tree

Module network inference is an established statistical method to reconstruct co-expression modules and their upstream regulatory programs from integrated multi-omics datasets measuring the activity levels of various cellular components across different individuals, experimental conditions or time points of a dynamic process. We have developed Lemon-Tree, an open-source, platform-independent, modular, extensible software package implementing state-of-the-art ensemble methods for module network inference. We benchmarked Lemon-Tree using large-scale tumor datasets and showed that Lemon-Tree algorithms compare favorably with state-of-the-art module network inference software. We also analyzed a large dataset of somatic copy-number alterations and gene expression levels measured in glioblastoma samples from The Cancer Genome Atlas and found that Lemon-Tree correctly identifies known glioblastoma oncogenes and tumor suppressors as master regulators in the inferred module network. Novel candidate driver genes predicted by Lemon-Tree were validated using tumor pathway and survival analyses. Lemon-Tree is available from http://lemon-tree.googlecode.com under the GNU General Public License version 2.0.Comment: minor revision; 13 pages text + 4 figures + 4 tables + 4 pages supplementary methods; supplementary tables available from the author

Modular expression analysis reveals functional conservation between human Langerhans cells and mouse cross-priming dendritic cells

Characterization of functionally distinct dendritic cell (DC) subsets in mice has fueled interest in whether analogous counterparts exist in humans. Transcriptional modules of coordinately expressed genes were used for defining shared functions between the species. Comparing modules derived from four human skin DC subsets and modules derived from the Immunological Genome Project database for all mouse DC subsets revealed that human Langerhans cells (LCs) and the mouse XCR1(+)CD8α(+)CD103(+) DCs shared the class I-mediated antigen processing and cross-presentation transcriptional modules that were not seen in mouse LCs. Furthermore, human LCs were enriched in a transcriptional signature specific to the blood cross-presenting CD141/BDCA-3(+) DCs, the proposed equivalent to mouse CD8α(+) DCs. Consistent with our analysis, LCs were highly adept at inducing primary CTL responses. Thus, our study suggests that the function of LCs may not be conserved between mouse and human and supports human LCs as an especially relevant therapeutic target

A GWAS sequence variant for platelet volume marks an alternative DNM3 promoter in megakaryocytes near a MEIS1 binding site

We recently identified 68 genomic loci where common sequence variants are associated with platelet count and volume. Platelets are formed in the bone marrow by megakaryocytes, which are derived from hematopoietic stem cells by a process mainly controlled by transcription factors. The homeobox transcription factor MEIS1 is uniquely transcribed in megakaryocytes and not in the other lineage-committed blood cells. By ChIP-seq, we show that 5 of the 68 loci pinpoint a MEIS1 binding event within a group of 252 MK-overexpressed genes. In one such locus in DNM3, regulating platelet volume, the MEIS1 binding site falls within a region acting as an alternative promoter that is solely used in megakaryocytes, where allelic variation dictates different levels of a shorter transcript. The importance of dynamin activity to the latter stages of thrombopoiesis was confirmed by the observation that the inhibitor Dynasore reduced murine proplatelet for-mation in vitro

The TAL1 complex targets the FBXW7 tumor suppressor by activating miR-223 in human T cell acute lymphoblastic leukemia

The oncogenic transcription factor TAL1/SCL is aberrantly expressed in 60% of cases of human T cell acute lymphoblastic leukemia (T-ALL) and initiates T-ALL in mouse models. By performing global microRNA (miRNA) expression profiling after depletion of TAL1, together with genome-wide analysis of TAL1 occupancy by chromatin immunoprecipitation coupled to massively parallel DNA sequencing, we identified the miRNA genes directly controlled by TAL1 and its regulatory partners HEB, E2A, LMO1/2, GATA3, and RUNX1. The most dynamically regulated miRNA was miR-223, which is bound at its promoter and up-regulated by the TAL1 complex. miR-223 expression mirrors TAL1 levels during thymic development, with high expression in early thymocytes and marked down-regulation after the double-negative-2 stage of maturation. We demonstrate that aberrant miR-223 up-regulation by TAL1 is important for optimal growth of TAL1-positive T-ALL cells and that sustained expression of miR-223 partially rescues T-ALL cells after TAL1 knockdown. Overexpression of miR-223 also leads to marked down-regulation of FBXW7 protein expression, whereas knockdown of TAL1 leads to up-regulation of FBXW7 protein levels, with a marked reduction of its substrates MYC, MYB, NOTCH1, and CYCLIN E. We conclude that TAL1-mediated up-regulation of miR-223 promotes the malignant phenotype in T-ALL through repression of the FBXW7 tumor suppressor.National Cancer Institute (U.S.) (5P01CA109901)National Cancer Institute (U.S.) (5P01CA68484)National Cancer Institute (U.S.) (1K99CA157951)National Institutes of Health (U.S.). Intramural Research ProgramCenter for Cancer Research (National Cancer Institute (U.S.)

The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment.

Understanding how differentiation programs originate from the gene-expression 'landscape' of hematopoietic stem cells (HSCs) is crucial for the development of new clinical therapies. We mapped the transcriptional dynamics underlying the first steps of commitment by tracking transcriptome changes in human HSCs and eight early progenitor populations. We found that transcriptional programs were extensively shared, extended across lineage-potential boundaries and were not strictly lineage affiliated. Elements of stem, lymphoid and myeloid programs were retained in multilymphoid progenitors (MLPs), which reflected a hybrid transcriptional state. By functional single cell analysis, we found that the transcription factors Bcl-11A, Sox4 and TEAD1 (TEF1) governed transcriptional networks in MLPs, which led to B cell specification. Overall, we found that integrated transcriptome approaches can be used to identify previously unknown regulators of multipotency and show additional complexity in lymphoid commitment

A Genomewide Functional Network for the Laboratory Mouse

Establishing a functional network is invaluable to our understanding of gene function, pathways, and systems-level properties of an organism and can be a powerful resource in directing targeted experiments. In this study, we present a functional network for the laboratory mouse based on a Bayesian integration of diverse genetic and functional genomic data. The resulting network includes probabilistic functional linkages among 20,581 protein-coding genes. We show that this network can accurately predict novel functional assignments and network components and present experimental evidence for predictions related to Nanog homeobox (Nanog), a critical gene in mouse embryonic stem cell pluripotency. An analysis of the global topology of the mouse functional network reveals multiple biologically relevant systems-level features of the mouse proteome. Specifically, we identify the clustering coefficient as a critical characteristic of central modulators that affect diverse pathways as well as genes associated with different phenotype traits and diseases. In addition, a cross-species comparison of functional interactomes on a genomic scale revealed distinct functional characteristics of conserved neighborhoods as compared to subnetworks specific to higher organisms. Thus, our global functional network for the laboratory mouse provides the community with a key resource for discovering protein functions and novel pathway components as well as a tool for exploring systems-level topological and evolutionary features of cellular interactomes. To facilitate exploration of this network by the biomedical research community, we illustrate its application in function and disease gene discovery through an interactive, Web-based, publicly available interface at http://mouseNET.princeton.edu

The creatine kinase pathway is a metabolic vulnerability in EVI1-positive acute myeloid leukemia

Expression of the MECOM (also known as EVI1) proto-oncogene is deregulated by chromosomal translocations in some cases of acute myeloid leukemia (AML) and is associated with poor clinical outcome. Here, through transcriptomic and metabolomic profiling of hematopoietic cells, we reveal that EVI1 overexpression alters cellular metabolism. A screen using pooled short hairpin RNAs (shRNAs) identified the ATP-buffering, mitochondrial creatine kinase CKMT1 as necessary for survival of EVI1-expressing cells in subjects with EVI1-positive AML. EVI1 promotes CKMT1 expression by repressing the myeloid differentiation regulator RUNX1. Suppression of arginine-creatine metabolism by CKMT1-directed shRNAs or by the small molecule cyclocreatine selectively decreased the viability, promoted the cell cycle arrest and apoptosis of human EVI1-positive cell lines, and prolonged survival in both orthotopic xenograft models and mouse models of primary AML. CKMT1 inhibition altered mitochondrial respiration and ATP production, an effect that was abrogated by phosphocreatine-mediated reactivation of the arginine-creatine pathway. Targeting CKMT1 is thus a promising therapeutic strategy for this EVI1-driven AML subtype that is highly resistant to current treatment regimens. Keywords: AML; RUNX1; CKMT1; cyclocreatine; arginine metabolismNational Cancer Institute (U.S.) (NIH 1R35 CA210030-01)Stand Up To CancerBridge ProjectNational Cancer Institute (U.S.) (David H. Koch Institute for Integrative Cancer Research at MIT. Grant P30-CA14051

Highly Parallel Genome-Wide Expression Analysis of Single Mammalian Cells

We have developed a high-throughput amplification method for generating robust gene expression profiles using single cell or low RNA inputs.The method uses tagged priming and template-switching, resulting in the incorporation of universal PCR priming sites at both ends of the synthesized cDNA for global PCR amplification. Coupled with a whole-genome gene expression microarray platform, we routinely obtain expression correlation values of R(2)~0.76-0.80 between individual cells and R(2)~0.69 between 50 pg total RNA replicates. Expression profiles generated from single cells or 50 pg total RNA correlate well with that generated with higher input (1 ng total RNA) (R(2)~0.80). Also, the assay is sufficiently sensitive to detect, in a single cell, approximately 63% of the number of genes detected with 1 ng input, with approximately 97% of the genes detected in the single-cell input also detected in the higher input.In summary, our method facilitates whole-genome gene expression profiling in contexts where starting material is extremely limiting, particularly in areas such as the study of progenitor cells in early development and tumor stem cell biology

Rational drug repurposing using sscMap analysis in a HOX-TALE model of leukemia

Drug discovery and development are often hampered by lack of target identification and clinical tractability. Repurposing of approved drugs to life-threatening diseases such as leukemia is emerging as a promising alternative approach. Connectivity mapping systems link approved drugs with disease-related gene signatures. Relevant preclinical models provide essential tools for system validation and proof-of-concept studies. Herein we describe procedures aimed at generating disease-based gene signatures and applying them to established cross-referencing databases of potential candidate drugs. As a proof of principle, we present the identification of Entinostat as a candidate drug for the treatment of HOX TALE-related leukemia