Genomic Decoding of Neuronal Depolarization by Stimulus-Specific NPAS4 Heterodimers.

Cells regulate gene expression in response to salient external stimuli. In neurons, depolarization leads to the expression of inducible transcription factors (ITFs) that direct subsequent gene regulation. Depolarization encodes both a neuron's action potential (AP) output and synaptic inputs, via excitatory postsynaptic potentials (EPSPs). However, it is unclear if distinct types of electrical activity can be transformed by an ITF into distinct modes of genomic regulation. Here, we show that APs and EPSPs in mouse hippocampal neurons trigger two spatially segregated and molecularly distinct induction mechanisms that lead to the expression of the ITF NPAS4. These two pathways culminate in the formation of stimulus-specific NPAS4 heterodimers that exhibit distinct DNA binding patterns. Thus, NPAS4 differentially communicates increases in a neuron's spiking output and synaptic inputs to the nucleus, enabling gene regulation to be tailored to the type of depolarizing activity along the somato-dendritic axis of a neuron.

MEIRLOP: improving score-based motif enrichment by incorporating sequence bias covariates.

BACKGROUND: Motif enrichment analysis (MEA) identifies over-represented transcription factor binding (TF) motifs in the DNA sequence of regulatory regions, enabling researchers to infer which transcription factors can regulate transcriptional response to a stimulus, or identify sequence features found near a target protein in a ChIP-seq experiment. Score-based MEA determines motifs enriched in regions exhibiting extreme differences in regulatory activity, but existing methods do not control for biases in GC content or dinucleotide composition. This lack of control for sequence bias, such as those often found in CpG islands, can obscure the enrichment of biologically relevant motifs. RESULTS: We developed Motif Enrichment In Ranked Lists of Peaks (MEIRLOP), a novel MEA method that determines enrichment of TF binding motifs in a list of scored regulatory regions, while controlling for sequence bias. In this study, we compare MEIRLOP against other MEA methods in identifying binding motifs found enriched in differentially active regulatory regions after interferon-beta stimulus, finding that using logistic regression and covariates improves the ability to call enrichment of ISGF3 binding motifs from differential acetylation ChIP-seq data compared to other methods. Our method achieves similar or better performance compared to other methods when quantifying the enrichment of TF binding motifs from ENCODE TF ChIP-seq datasets. We also demonstrate how MEIRLOP is broadly applicable to the analysis of numerous types of NGS assays and experimental designs. CONCLUSIONS: Our results demonstrate the importance of controlling for sequence bias when accurately identifying enriched DNA sequence motifs using score-based MEA. MEIRLOP is available for download from https://github.com/npdeloss/meirlop under the MIT license.

MEPP: more transparent motif enrichment by profiling positional correlations.

Score-based motif enrichment analysis (MEA) is typically applied to regulatory DNA to infer transcription factors (TFs) that may modulate transcription and chromatin state in different conditions. Most MEA methods determine motif enrichment independent of motif position within a sequence, even when those sequences harbor anchor points that motifs and their bound TFs may functionally interact with in a distance-dependent fashion, such as other TF binding motifs, transcription start sites (TSS), sequencing assay cleavage sites, or other biologically meaningful features. We developed motif enrichment positional profiling (MEPP), a novel MEA method that outputs a positional enrichment profile of a given TF's binding motif relative to key anchor points (e.g. transcription start sites, or other motifs) within the analyzed sequences while accounting for lower-order nucleotide bias. Using transcription initiation and TF binding as test cases, we demonstrate MEPP's utility in determining the sequence positions where motif presence correlates with measures of biological activity, inferring positional dependencies of binding site function. We demonstrate how MEPP can be applied to interpretation and hypothesis generation from experiments that quantify transcription initiation, chromatin structure, or TF binding measurements. MEPP is available for download from https://github.com/npdeloss/mepp.

Tracking of Normal and Malignant Progenitor Cell Cycle Transit in a Defined Niche.

While implicated in therapeutic resistance, malignant progenitor cell cycle kinetics have been difficult to quantify in real-time. We developed an efficient lentiviral bicistronic fluorescent, ubiquitination-based cell cycle indicator reporter (Fucci2BL) to image live single progenitors on a defined niche coupled with cell cycle gene expression analysis. We have identified key differences in cell cycle regulatory gene expression and transit times between normal and chronic myeloid leukemia progenitors that may inform cancer stem cell eradication strategies.

RNA Splicing Modulation Selectively Impairs Leukemia Stem Cell Maintenance in Secondary Human AML.

Age-related human hematopoietic stem cell (HSC) exhaustion and myeloid-lineage skewing promote oncogenic transformation of hematopoietic progenitor cells into therapy-resistant leukemia stem cells (LSCs) in secondary acute myeloid leukemia (AML). While acquisition of clonal DNA mutations has been linked to increased rates of secondary AML for individuals older than 60 years, the contribution of RNA processing alterations to human hematopoietic stem and progenitor aging and LSC generation remains unclear. Comprehensive RNA sequencing and splice-isoform-specific PCR uncovered characteristic RNA splice isoform expression patterns that distinguished normal young and aged human stem and progenitor cells (HSPCs) from malignant myelodysplastic syndrome (MDS) and AML progenitors. In splicing reporter assays and pre-clinical patient-derived AML models, treatment with a pharmacologic splicing modulator, 17S-FD-895, reversed pro-survival splice isoform switching and significantly impaired LSC maintenance. Therapeutic splicing modulation, together with monitoring splice isoform biomarkers of healthy HSPC aging versus LSC generation, may be employed safely and effectively to prevent relapse, the leading cause of leukemia-related mortality.

ADAR1 Activation Drives Leukemia Stem Cell Self-Renewal by Impairing Let-7 Biogenesis.

Post-transcriptional adenosine-to-inosine RNA editing mediated by adenosine deaminase acting on RNA1 (ADAR1) promotes cancer progression and therapeutic resistance. However, ADAR1 editase-dependent mechanisms governing leukemia stem cell (LSC) generation have not been elucidated. In blast crisis chronic myeloid leukemia (BC CML), we show that increased JAK2 signaling and BCR-ABL1 amplification activate ADAR1. In a humanized BC CML mouse model, combined JAK2 and BCR-ABL1 inhibition prevents LSC self-renewal commensurate with ADAR1 downregulation. Lentiviral ADAR1 wild-type, but not an editing-defective ADAR1(E912A) mutant, induces self-renewal gene expression and impairs biogenesis of stem cell regulatory let-7 microRNAs. Combined RNA sequencing, qRT-PCR, CLIP-ADAR1, and pri-let-7 mutagenesis data suggest that ADAR1 promotes LSC generation via let-7 pri-microRNA editing and LIN28B upregulation. A small-molecule tool compound antagonizes ADAR1's effect on LSC self-renewal in stromal co-cultures and restores let-7 biogenesis. Thus, ADAR1 activation represents a unique therapeutic vulnerability in LSCs with active JAK2 signaling.