Densely interconnected transcriptional circuits control cell states in human hematopoiesis.

Though many individual transcription factors are known to regulate hematopoietic differentiation, major aspects of the global architecture of hematopoiesis remain unknown. Here, we profiled gene expression in 38 distinct purified populations of human hematopoietic cells and used probabilistic models of gene expression and analysis of cis-elements in gene promoters to decipher the general organization of their regulatory circuitry. We identified modules of highly coexpressed genes, some of which are restricted to a single lineage but most of which are expressed at variable levels across multiple lineages. We found densely interconnected cis-regulatory circuits and a large number of transcription factors that are differentially expressed across hematopoietic states. These findings suggest a more complex regulatory system for hematopoiesis than previously assumed.

Inherited myeloproliferative neoplasm risk affects haematopoietic stem cells.

Myeloproliferative neoplasms (MPNs) are blood cancers that are characterized by the excessive production of mature myeloid cells and arise from the acquisition of somatic driver mutations in haematopoietic stem cells (HSCs). Epidemiological studies indicate a substantial heritable component of MPNs that is among the highest known for cancers1. However, only a limited number of genetic risk loci have been identified, and the underlying biological mechanisms that lead to the acquisition of MPNs remain unclear. Here, by conducting a large-scale genome-wide association study (3,797 cases and 1,152,977 controls), we identify 17 MPN risk loci (P < 5.0 × 10-8), 7 of which have not been previously reported. We find that there is a shared genetic architecture between MPN risk and several haematopoietic traits from distinct lineages; that there is an enrichment for MPN risk variants within accessible chromatin of HSCs; and that increased MPN risk is associated with longer telomere length in leukocytes and other clonal haematopoietic states-collectively suggesting that MPN risk is associated with the function and self-renewal of HSCs. We use gene mapping to identify modulators of HSC biology linked to MPN risk, and show through targeted variant-to-function assays that CHEK2 and GFI1B have roles in altering the function of HSCs to confer disease risk. Overall, our results reveal a previously unappreciated mechanism for inherited MPN risk through the modulation of HSC function.

Genome-wide association study on 13 167 individuals identifies regulators of blood CD34+cell levels.

Stem cell transplantation is a cornerstone in the treatment of blood malignancies. The most common method to harvest stem cells for transplantation is by leukapheresis, requiring mobilization of CD34+ hematopoietic stem and progenitor cells (HSPCs) from the bone marrow into the blood. Identifying the genetic factors that control blood CD34+ cell levels could reveal new drug targets for HSPC mobilization. Here we report the first large-scale, genome-wide association study on blood CD34+ cell levels. Across 13 167 individuals, we identify 9 significant and 2 suggestive associations, accounted for by 8 loci (PPM1H, CXCR4, ENO1-RERE, ITGA9, ARHGAP45, CEBPA, TERT, and MYC). Notably, 4 of the identified associations map to CXCR4, showing that bona fide regulators of blood CD34+ cell levels can be identified through genetic variation. Further, the most significant association maps to PPM1H, encoding a serine/threonine phosphatase never previously implicated in HSPC biology. PPM1H is expressed in HSPCs, and the allele that confers higher blood CD34+ cell levels downregulates PPM1H. Through functional fine-mapping, we find that this downregulation is caused by the variant rs772557-A, which abrogates an MYB transcription factor-binding site in PPM1H intron 1 that is active in specific HSPC subpopulations, including hematopoietic stem cells, and interacts with the promoter by chromatin looping. Furthermore, PPM1H knockdown increases the proportion of CD34+ and CD34+90+ cells in cord blood assays. Our results provide the first large-scale analysis of the genetic architecture of blood CD34+ cell levels and warrant further investigation of PPM1H as a potential inhibition target for stem cell mobilization.

The insertion/deletion polymorphism rs201494641 at ITGA9 influences blood CD34+ cell levels by altering ZNF384 binding.

Not available.

MPRAscore: robust and non-parametric analysis of massively parallel reporter assays.

MOTIVATION: Massively parallel reporter assays (MPRA) enable systematic screening of DNA sequence variants for effects on transcriptional activity. However, convenient analysis tools are still needed. RESULTS: We introduce MPRAscore, a novel tool to infer allele-specific effects on transcription from MPRA data. MPRAscore uses a weighted, variance-regularized method to calculate variant effect sizes robustly, and a permutation approach to test for significance without assuming normality or independence. AVAILABILITY AND IMPLEMENTATION: Source code (C++), precompiled binaries and data used in the paper at https://github.com/abhisheknrl/MPRAscore and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA554195. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptome-wide association study of multiple myeloma identifies candidate susceptibility genes.

BACKGROUND: While genome-wide association studies (GWAS) of multiple myeloma (MM) have identified variants at 23 regions influencing risk, the genes underlying these associations are largely unknown. To identify candidate causal genes at these regions and search for novel risk regions, we performed a multi-tissue transcriptome-wide association study (TWAS). RESULTS: GWAS data on 7319 MM cases and 234,385 controls was integrated with Genotype-Tissue Expression Project (GTEx) data assayed in 48 tissues (sample sizes, N = 80-491), including lymphocyte cell lines and whole blood, to predict gene expression. We identified 108 genes at 13 independent regions associated with MM risk, all of which were in 1 Mb of known MM GWAS risk variants. Of these, 94 genes, located in eight regions, had not previously been considered as a candidate gene for that locus. CONCLUSIONS: Our findings highlight the value of leveraging expression data from multiple tissues to identify candidate genes responsible for GWAS associations which provide insight into MM tumorigenesis. Among the genes identified, a number have plausible roles in MM biology, notably APOBEC3C, APOBEC3H, APOBEC3D, APOBEC3F, APOBEC3G, or have been previously implicated in other malignancies. The genes identified in this TWAS can be explored for follow-up and validation to further understand their role in MM biology.

Auditory brainstem response (ABR) profiling tests as diagnostic support for schizophrenia and adult attention-deficit hyperactivity disorder (ADHD).

OBJECTIVE: To evaluate the performances of two auditory brainstem response (ABR) profiling tests as potential biomarkers and diagnostic support for schizophrenia and adult attention-deficit hyperactivity disorder (ADHD), respectively, in an investigator-initiated blinded study design. METHOD: Male and female patients with schizophrenia (n=26) and adult ADHD (n=24) meeting Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (DSM IV) diagnostic criteria and healthy controls (n=58) comprised the analysis set (n=108) of the total number of study participants (n=119). Coded sets of randomized ABR recordings were analysed by an independent party blinded to clinical diagnoses before a joint code-breaking session. RESULTS: The ABR profiling test for schizophrenia identified schizophrenia patients versus controls with a sensitivity of 84.6% and a specificity of 93.1%. The ADHD test identified patients with adult ADHD versus controls with a sensitivity of 87.5% and a specificity of 91.4%. CONCLUSION: The ABR profiling tests discriminated schizophrenia and ADHD versus healthy controls with high sensitivity and specificity. The methods deserve to be further explored in larger clinical studies including a broad range of psychiatric disorders to determine their utility as potential diagnostic biomarkers.

Anti-apoptotic quinolinate phosphoribosyltransferase (QPRT) is a target gene of Wilms' tumor gene 1 (WT1) protein in leukemic cells.

Wilms' tumor gene 1 (WT1) is a zinc finger transcription factor that has been implicated as an oncogene in leukemia and several other malignancies. When investigating possible gene expression network partners of WT1 in a large acute myeloid leukemia (AML) patient cohort, one of the genes with the highest correlation to WT1 was quinolinate phosphoribosyltransferase (QPRT), a key enzyme in the de novo nicotinamide adenine dinucleotide (NAD+) synthesis pathway. To investigate the possible relationship between WT1 and QPRT, we overexpressed WT1 in hematopoietic progenitor cells and cell lines, resulting in an increase of QPRT expression. WT1 knock-down gave a corresponding decrease in QPRT gene and protein expression. Chromatin-immunoprecipitation revealed WT1 binding to a conserved site in the first intron of the QPRT gene. Upon overexpression in leukemic K562 cells, QPRT conferred partial resistance to the anti-leukemic drug imatinib, indicating possible anti-apoptotic functions, consistent with previous reports on glioma cells. Interestingly, the rescue effect of QPRT overexpression was not correlated to increased NAD + levels, suggesting NAD + independent mechanisms. We conclude that QPRT, encoding a protein with anti-apoptotic properties, is a novel and direct target gene of WT1 in leukemic cells.

Distinct global binding patterns of the Wilms tumor gene 1 (WT1) -KTS and +KTS isoforms in leukemic cells.

The zinc finger transcription factor Wilms tumor gene 1 (WT1) acts as an oncogene in acute myeloid leukemia. A naturally occurring alternative splice event between zinc fingers three and four, removing or retaining three amino acids (±KTS), is believed to change the DNA binding affinity of WT1, although there are conflicting data regarding the binding affinity and motifs of the different isoforms. Increased expression of the WT1 -KTS isoform at the expense of the WT1 +KTS isoform is associated with poor prognosis in acute myeloid leukemia. We determined the genome-wide binding pattern of WT1 -KTS and WT1 +KTS in leukemic K562 cells by chromatin immunoprecipitation and deep sequencing. We discovered that the WT1 -KTS isoform predominantly binds close to transcription start sites and to enhancers, in a similar fashion to other transcription factors, whereas WT1 +KTS binding is enriched within gene bodies. We observed a significant overlap between WT1 -KTS and WT1 +KTS target genes, despite the binding sites being distinct. Motif discovery revealed distinct binding motifs for the isoforms, some of which have been previously reported as WT1 binding sites. Additional analyses showed that both WT1 -KTS and WT1 +KTS target genes are more likely to be transcribed than non-targets, and are involved in cell proliferation, cell death, and development. Our study provides evidence that WT1 -KTS and WT1 +KTS share target genes yet still bind distinct locations, indicating isoform-specific regulation in transcription of genes related to cell proliferation and differentiation, consistent with the involvement of WT1 in acute myeloid leukemia.

Robust isolation of malignant plasma cells in multiple myeloma.

Molecular characterization of malignant plasma cells is increasingly important for diagnostic and therapeutic stratification in multiple myeloma. However, the malignant plasma cells represent a relatively small subset of bone marrow cells, and need to be enriched prior to analysis. Currently, the cell surface marker CD138 (SDC1) is used for this enrichment, but has an important limitation in that its expression decreases rapidly after sampling. Seeking alternatives to CD138, we performed a computational screen for myeloma plasma cell markers and systematically evaluated 7 candidates. Our results conclusively show that the markers CD319 (SLAMF7/CS1) and CD269 (TNFRSF17/BCMA) are considerably more robust than CD138 and enable isolation of myeloma plasma cells under more diverse conditions, including the samples that have been delayed or frozen. Our results form the basis of improved procedures for characterizing cases of multiple myeloma in clinical practice.

Karolinska Scales of Personality, cognition and psychotic symptoms in patients with schizophrenia and healthy controls.

BACKGROUND: Studies on both personality dimensions and cognition in schizophrenia are scarce. The objective of the present study was to examine personality traits and the relation to cognitive function and psychotic symptoms in a sample of patients with schizophrenia and healthy controls. METHOD: In total 23 patients with schizophrenia and 14 controls were assessed with the Karolinska Scales of Personality (KSP). A broad cognitive test programme was used, including the Wechsler Adult Intelligence Scales, the Finger-Tapping Test, the Trail Making Test, the Verbal Fluency Test, the Benton Visual Retention Test, the Wisconsin Card Sorting Test and Rey Auditory Verbal Learning Test . RESULTS: Compared with controls, the patients exhibited prominent elevations on KSP scales measuring anxiety proneness and neuroticism (P = 0.000005-0.0001), on the Detachment scale (P < 0.00009) and lower value on the Socialization scale (P < 0.0002). The patients also scored higher on the Inhibition of Aggression, Suspicion, Guilt and Irritability scales (P = 0.002-0.03) while the remaining five scales did not differ between patients and controls. KSP anxiety-related scales correlated with the Positive and Negative Symptoms Scale (PANSS) general psychopathology subscale. Cognitive test results were uniformly lower in the patient group and correlated with PANSS negative symptoms subscale. There was no association between KSP scale scores and PANSS positive or negative symptoms. CONCLUSION: The patients revealed a highly discriminative KSP test profile with elevated scores in neuroticism- and psychoticism-related scales as compared to controls. Results support previous findings utilizing other personality inventories in patients with schizophrenia. Cognitive test performance correlated inversely with negative symptoms.

The DEK oncoprotein binds to highly and ubiquitously expressed genes with a dual role in their transcriptional regulation.

BACKGROUND: The DEK gene is highly expressed in a wide range of cancer cells, and a recurrent translocation partner in acute myeloid leukemia. While DEK has been identified as one of the most abundant proteins in human chromatin, its function and binding properties are not fully understood. METHODS: We performed ChIP-seq analysis in the myeloid cell line U937 and coupled it with epigenetic and gene expression analysis to explore the genome-wide binding pattern of DEK and its role in gene regulation. RESULTS: We show that DEK preferentially binds to open chromatin, with a low degree of DNA methylation and scarce in the heterochromatin marker H3K9me(3) but rich in the euchromatin marks H3K4me(2/3), H3K27ac and H3K9ac. More specifically, DEK binding is predominantly located at the transcription start sites of highly transcribed genes and a comparative analysis with previously established transcription factor binding patterns shows a similarity with that of RNA polymerase II. Further bioinformatic analysis demonstrates that DEK mainly binds to genes that are ubiquitously expressed across tissues. The functional significance of DEK binding was demonstrated by knockdown of DEK by shRNA, resulting in both significant upregulation and downregulation of DEK-bound genes. CONCLUSIONS: We find that DEK binds to transcription start sites with a dual role in activation and repression of highly and ubiquitously expressed genes.

Clinical effect of point mutations in myelodysplastic syndromes.

BACKGROUND: Myelodysplastic syndromes are clinically heterogeneous disorders characterized by clonal hematopoiesis, impaired differentiation, peripheral-blood cytopenias, and a risk of progression to acute myeloid leukemia. Somatic mutations may influence the clinical phenotype but are not included in current prognostic scoring systems. METHODS: We used a combination of genomic approaches, including next-generation sequencing and mass spectrometry-based genotyping, to identify mutations in samples of bone marrow aspirate from 439 patients with myelodysplastic syndromes. We then examined whether the mutation status for each gene was associated with clinical variables, including specific cytopenias, the proportion of blasts, and overall survival. RESULTS: We identified somatic mutations in 18 genes, including two, ETV6 and GNAS, that have not been reported to be mutated in patients with myelodysplastic syndromes. A total of 51% of all patients had at least one point mutation, including 52% of the patients with normal cytogenetics. Mutations in RUNX1, TP53, and NRAS were most strongly associated with severe thrombocytopenia (P<0.001 for all comparisons) and an increased proportion of bone marrow blasts (P<0.006 for all comparisons). In a multivariable Cox regression model, the presence of mutations in five genes retained independent prognostic significance: TP53 (hazard ratio for death from any cause, 2.48; 95% confidence interval [CI], 1.60 to 3.84), EZH2 (hazard ratio, 2.13; 95% CI, 1.36 to 3.33), ETV6 (hazard ratio, 2.04; 95% CI, 1.08 to 3.86), RUNX1 (hazard ratio, 1.47; 95% CI, 1.01 to 2.15), and ASXL1 (hazard ratio, 1.38; 95% CI, 1.00 to 1.89). CONCLUSIONS: Somatic point mutations are common in myelodysplastic syndromes and are associated with specific clinical features. Mutations in TP53, EZH2, ETV6, RUNX1, and ASXL1 are predictors of poor overall survival in patients with myelodysplastic syndromes, independently of established risk factors. (Funded by the National Institutes of Health and others.).

Ultranet: efficient solver for the sparse inverse covariance selection problem in gene network modeling.

SUMMARY: Graphical Gaussian models (GGMs) are a promising approach to identify gene regulatory networks. Such models can be robustly inferred by solving the sparse inverse covariance selection (SICS) problem. With the high dimensionality of genomics data, fast methods capable of solving large instances of SICS are needed. We developed a novel network modeling tool, Ultranet, that solves the SICS problem with significantly improved efficiency. Ultranet combines a range of mathematical and programmatical techniques, exploits the structure of the SICS problem and enables computation of genome-scale GGMs without compromising analytic accuracy. AVAILABILITY AND IMPLEMENTATION: Ultranet is implemented in C++ and available at www.broadinstitute.org/ultranet.

AliGater: a framework for the development of bioinformatic pipelines for large-scale, high-dimensional cytometry data.

Motivation: AliGater is an open-source framework to accelerate the development of bioinformatic pipelines for the analysis of large-scale, high-dimensional flow cytometry data. AliGater provides a Python package for automatic feature extraction workflows, as well as building blocks to construct analysis pipelines. Results: We illustrate the use of AliGater in a high-resolution flow cytometry-based genome-wide association study on 46 immune cell populations in 14 288 individuals. Availability and implementation: Source code and documentation at https://github.com/LudvigEk/aligater and https://aligater.readthedocs.io.

Sequence enrichment profiles enable target-agnostic antibody generation for a broad range of antigens.

Phenotypic drug discovery (PDD) enables the target-agnostic generation of therapeutic drugs with novel mechanisms of action. However, realizing its full potential for biologics discovery requires new technologies to produce antibodies to all, a priori unknown, disease-associated biomolecules. We present a methodology that helps achieve this by integrating computational modeling, differential antibody display selection, and massive parallel sequencing. The method uses the law of mass action-based computational modeling to optimize antibody display selection and, by matching computationally modeled and experimentally selected sequence enrichment profiles, predict which antibody sequences encode specificity for disease-associated biomolecules. Applied to a phage display antibody library and cell-based antibody selection, ∼105 antibody sequences encoding specificity for tumor cell surface receptors expressed at 103-106 receptors/cell were discovered. We anticipate that this approach will be broadly applicable to molecular libraries coupling genotype to phenotype and to the screening of complex antigen populations for identification of antibodies to unknown disease-associated targets.

Functional and molecular profiling of hematopoietic stem cells during regeneration.

Hematopoietic stem cells (HSCs) enable hematopoietic stem cell transplantation (HCT) through their ability to replenish the entire blood system. Proliferation of HSCs is linked to decreased reconstitution potential, and a precise regulation of actively dividing HSCs is thus essential to ensure long-term functionality. This regulation becomes important in the transplantation setting where HSCs undergo proliferation followed by a gradual transition to quiescence and homeostasis. Although mouse HSCs have been well studied under homeostatic conditions, the mechanisms regulating HSC activation under stress remain unclear. Here, we analyzed the different phases of regeneration after transplantation. We isolated bone marrow from mice at 8 time points after transplantation and examined the reconstitution dynamics and transcriptional profiles of stem and progenitor populations. We found that regenerating HSCs initially produced rapidly expanding progenitors and displayed distinct changes in fatty acid metabolism and glycolysis. Moreover, we observed molecular changes in cell cycle, MYC and mTOR signaling in both HSCs, and progenitor subsets. We used a decay rate model to fit the temporal transcription profiles of regenerating HSCs and identified genes with progressively decreased or increased expression after transplantation. These genes overlapped to a large extent with published gene sets associated with key aspects of HSC function, demonstrating the potential of this data set as a resource for identification of novel HSC regulators. Taken together, our study provides a detailed functional and molecular characterization of HSCs at different phases of regeneration and identifies a gene set associated with the transition from proliferation to quiescence.

Genetic regulation of fetal hemoglobin across global populations.

Human genetic variation has enabled the identification of several key regulators of fetal-to-adult hemoglobin switching, including BCL11A, resulting in therapeutic advances. However, despite the progress made, limited further insights have been obtained to provide a fuller accounting of how genetic variation contributes to the global mechanisms of fetal hemoglobin (HbF) gene regulation. Here, we have conducted a multi-ancestry genome-wide association study of 28,279 individuals from several cohorts spanning 5 continents to define the architecture of human genetic variation impacting HbF. We have identified a total of 178 conditionally independent genome-wide significant or suggestive variants across 14 genomic windows. Importantly, these new data enable us to better define the mechanisms by which HbF switching occurs in vivo. We conduct targeted perturbations to define BACH2 as a new genetically-nominated regulator of hemoglobin switching. We define putative causal variants and underlying mechanisms at the well-studied BCL11A and HBS1L-MYB loci, illuminating the complex variant-driven regulation present at these loci. We additionally show how rare large-effect deletions in the HBB locus can interact with polygenic variation to influence HbF levels. Our study paves the way for the next generation of therapies to more effectively induce HbF in sickle cell disease and ß-thalassemia.

Network modeling of the transcriptional effects of copy number aberrations in glioblastoma.

DNA copy number aberrations (CNAs) are a hallmark of cancer genomes. However, little is known about how such changes affect global gene expression. We develop a modeling framework, EPoC (Endogenous Perturbation analysis of Cancer), to (1) detect disease-driving CNAs and their effect on target mRNA expression, and to (2) stratify cancer patients into long- and short-term survivors. Our method constructs causal network models of gene expression by combining genome-wide DNA- and RNA-level data. Prognostic scores are obtained from a singular value decomposition of the networks. By applying EPoC to glioblastoma data from The Cancer Genome Atlas consortium, we demonstrate that the resulting network models contain known disease-relevant hub genes, reveal interesting candidate hubs, and uncover predictors of patient survival. Targeted validations in four glioblastoma cell lines support selected predictions, and implicate the p53-interacting protein Necdin in suppressing glioblastoma cell growth. We conclude that large-scale network modeling of the effects of CNAs on gene expression may provide insights into the biology of human cancer. Free software in MATLAB and R is provided.

Functional dissection of inherited non-coding variation influencing multiple myeloma risk.

Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy.