Determination and inference of eukaryotic transcription factor sequence specificity.

Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only ∼1% of eukaryotic TFs. Broadly sampling DNA-binding domain (DBD) types from multiple eukaryotic clades, we determined DNA sequence preferences for >1,000 TFs encompassing 54 different DBD classes from 131 diverse eukaryotes. We find that closely related DBDs almost always have very similar DNA sequence preferences, enabling inference of motifs for ∼34% of the ∼170,000 known or predicted eukaryotic TFs. Sequences matching both measured and inferred motifs are enriched in chromatin immunoprecipitation sequencing (ChIP-seq) peaks and upstream of transcription start sites in diverse eukaryotic lineages. SNPs defining expression quantitative trait loci in Arabidopsis promoters are also enriched for predicted TF binding sites. Importantly, our motif "library" can be used to identify specific TFs whose binding may be altered by human disease risk alleles. These data present a powerful resource for mapping transcriptional networks across eukaryotes.

Nuclear TARBP2 Drives Oncogenic Dysregulation of RNA Splicing and Decay.

Post-transcriptional regulation of RNA stability is a key step in gene expression control. We describe a regulatory program, mediated by the RNA binding protein TARBP2, that controls RNA stability in the nucleus. TARBP2 binding to pre-mRNAs results in increased intron retention, subsequently leading to targeted degradation of TARBP2-bound transcripts. This is mediated by TARBP2 recruitment of the m6A RNA methylation machinery to its target transcripts, where deposition of m6A marks influences the recruitment of splicing regulators, inhibiting efficient splicing. Interactions between TARBP2 and the nucleoprotein TPR then promote degradation of these TARBP2-bound transcripts by the nuclear exosome. Additionally, analysis of clinical gene expression datasets revealed a functional role for TARBP2 in lung cancer. Using xenograft mouse models, we find that TARBP2 affects tumor growth in the lung and that this is dependent on TARBP2-mediated destabilization of ABCA3 and FOXN3. Finally, we establish ZNF143 as an upstream regulator of TARBP2 expression.

PHF6-mediated transcriptional control of NSC via Ephrin receptors is impaired in the intellectual disability syndrome BFLS.

The plant homeodomain zinc-finger protein, PHF6, is a transcriptional regulator, and PHF6 germline mutations cause the X-linked intellectual disability (XLID) Börjeson-Forssman-Lehmann syndrome (BFLS). The mechanisms by which PHF6 regulates transcription and how its mutations cause BFLS remain poorly characterized. Here, we show genome-wide binding of PHF6 in the developing cortex in the vicinity of genes involved in central nervous system development and neurogenesis. Characterization of BFLS mice harbouring PHF6 patient mutations reveals an increase in embryonic neural stem cell (eNSC) self-renewal and a reduction of neural progenitors. We identify a panel of Ephrin receptors (EphRs) as direct transcriptional targets of PHF6. Mechanistically, we show that PHF6 regulation of EphR is impaired in BFLS mice and in conditional Phf6 knock-out mice. Knockdown of EphR-A phenocopies the PHF6 loss-of-function defects in altering eNSCs, and its forced expression rescues defects of BFLS mice-derived eNSCs. Our data indicate that PHF6 directly promotes Ephrin receptor expression to control eNSC behaviour in the developing brain, and that this pathway is impaired in BFLS.

Pyruvate Kinase M (PKM) binds ribosomes in a poly-ADP ribosylation dependent manner to induce translational stalling.

In light of the numerous studies identifying post-transcriptional regulators on the surface of the endoplasmic reticulum (ER), we asked whether there are factors that regulate compartment specific mRNA translation in human cells. Using a proteomic survey of spatially regulated polysome interacting proteins, we identified the glycolytic enzyme Pyruvate Kinase M (PKM) as a cytosolic (i.e. ER-excluded) polysome interactor and investigated how it influences mRNA translation. We discovered that the PKM-polysome interaction is directly regulated by ADP levels-providing a link between carbohydrate metabolism and mRNA translation. By performing enhanced crosslinking immunoprecipitation-sequencing (eCLIP-seq), we found that PKM crosslinks to mRNA sequences that are immediately downstream of regions that encode lysine- and glutamate-enriched tracts. Using ribosome footprint protection sequencing, we found that PKM binding to ribosomes causes translational stalling near lysine and glutamate encoding sequences. Lastly, we observed that PKM recruitment to polysomes is dependent on poly-ADP ribosylation activity (PARylation)-and may depend on co-translational PARylation of lysine and glutamate residues of nascent polypeptide chains. Overall, our study uncovers a novel role for PKM in post-transcriptional gene regulation, linking cellular metabolism and mRNA translation.

Myf6/MRF4 is a myogenic niche regulator required for the maintenance of the muscle stem cell pool.

The function and maintenance of muscle stem cells (MuSCs) are tightly regulated by signals originating from their niche environment. Skeletal myofibers are a principle component of the MuSC niche and are in direct contact with the muscle stem cells. Here, we show that Myf6 establishes a ligand/receptor interaction between muscle stem cells and their associated muscle fibers. Our data show that Myf6 transcriptionally regulates a broad spectrum of myokines and muscle-secreted proteins in skeletal myofibers, including EGF. EGFR signaling blocks p38 MAP kinase-induced differentiation of muscle stem cells. Homozygous deletion of Myf6 causes a significant reduction in the ability of muscle to produce EGF, leading to a deregulation in EGFR signaling. Consequently, although Myf6-knockout mice are born with a normal muscle stem cell compartment, they undergo a progressive reduction in their stem cell pool during postnatal life due to spontaneous exit from quiescence. Taken together, our data uncover a novel role for Myf6 in promoting the expression of key myokines, such as EGF, in the muscle fiber which prevents muscle stem cell exhaustion by blocking their premature differentiation.

High-resolution genome-wide expression analysis of single myofibers using SMART-Seq.

Skeletal muscle is a heterogeneous tissue. Individual myofibers that make up muscle tissue exhibit variation in their metabolic and contractile properties. Although biochemical and histological assays are available to study myofiber heterogeneity, efficient methods to analyze the whole transcriptome of individual myofibers are lacking. Here, we report on a single-myofiber RNA-sequencing (smfRNA-Seq) approach to analyze the whole transcriptome of individual myofibers by combining single-fiber isolation with Switching Mechanism at 5' end of RNA Template (SMART) technology. Using smfRNA-Seq, we first determined the genes that are expressed in the whole muscle, including in nonmyogenic cells. We also analyzed the differences in the transcriptome of myofibers from young and old mice to validate the effectiveness of this new method. Our results suggest that aging leads to significant changes in the expression of metabolic genes, such as Nos1, and structural genes, such as Myl1, in myofibers. We conclude that smfRNA-Seq is a powerful tool to study developmental, disease-related, and age-related changes in the gene expression profile of skeletal muscle.

Multiparameter functional diversity of human C2H2 zinc finger proteins.

C2H2 zinc finger proteins represent the largest and most enigmatic class of human transcription factors. Their C2H2-ZF arrays are highly variable, indicating that most will have unique DNA binding motifs. However, most of the binding motifs have not been directly determined. In addition, little is known about whether or how these proteins regulate transcription. Most of the ∼700 human C2H2-ZF proteins also contain at least one KRAB, SCAN, BTB, or SET domain, suggesting that they may have common interacting partners and/or effector functions. Here, we report a multifaceted functional analysis of 131 human C2H2-ZF proteins, encompassing DNA binding sites, interacting proteins, and transcriptional response to genetic perturbation. We confirm the expected diversity in DNA binding motifs and genomic binding sites, and provide motif models for 78 previously uncharacterized C2H2-ZF proteins, most of which are unique. Surprisingly, the diversity in protein-protein interactions is nearly as high as diversity in DNA binding motifs: Most C2H2-ZF proteins interact with a unique spectrum of co-activators and co-repressors. Thus, multiparameter diversification likely underlies the evolutionary success of this large class of human proteins.

A compendium of RNA-binding motifs for decoding gene regulation.

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.

Systematic discovery of structural elements governing stability of mammalian messenger RNAs.

Decoding post-transcriptional regulatory programs in RNA is a critical step towards the larger goal of developing predictive dynamical models of cellular behaviour. Despite recent efforts, the vast landscape of RNA regulatory elements remains largely uncharacterized. A long-standing obstacle is the contribution of local RNA secondary structure to the definition of interaction partners in a variety of regulatory contexts, including--but not limited to--transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (for example, human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. Here we present a computational framework based on context-free grammars and mutual information that systematically explores the immense space of small structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behaviour. By applying this framework to genome-wide human mRNA stability data, we reveal eight highly significant elements with substantial structural information, for the strongest of which we show a major role in global mRNA regulation. Through biochemistry, mass spectrometry and in vivo binding studies, we identified human HNRPA2B1 (heterogeneous nuclear ribonucleoprotein A2/B1, also known as HNRNPA2B1) as the key regulator that binds this element and stabilizes a large number of its target genes. We created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach could also be used to reveal the structural elements that modulate other aspects of RNA behaviour.

Expression of DRD2 Is Increased in Human Pancreatic Ductal Adenocarcinoma and Inhibitors Slow Tumor Growth in Mice.

BACKGROUND & AIMS: Incidence of and mortality from pancreatic ductal adenocarcinoma (PDAC), the most common form of pancreatic cancer, are almost equivalent, so better treatments are needed. We studied gene expression profiles of PDACs and the functions of genes with altered expression to identify new therapeutic targets. METHODS: We performed microarray analysis to analyze gene expression profiles of 195 PDAC and 41 non-tumor pancreatic tissue samples. We undertook an extensive analysis of the PDAC transcriptome by superimposing interaction networks of proteins encoded by aberrantly expressed genes over signaling pathways associated with PDAC development to identify factors that might alter regulation of these pathways during tumor progression. We performed tissue microarray analysis to verify changes in expression of candidate protein using an independent set of 152 samples (40 nontumor pancreatic tissues, 63 PDAC sections, and 49 chronic pancreatitis samples). We validated the functional relevance of the candidate molecule using RNA interference or pharmacologic inhibitors in pancreatic cancer cell lines and analyses of xenograft tumors in mice. RESULTS: In an analysis of 38,276 human genes and loci, we identified 1676 genes that were significantly up-regulated and 1166 genes that were significantly down-regulated in PDAC compared with nontumor pancreatic tissues. One gene that was up-regulated and associated with multiple signaling pathways that are dysregulated in PDAC was G protein subunit αi2, which has not been previously associated with PDAC. G protein subunit αi2 mediates the effects of dopamine receptor D2 (DRD2) on cyclic adenosine monophosphate signaling; PDAC tissues had a slight but significant increase in DRD2 messenger RNA. Levels of DRD2 protein were substantially increased in PDACs, compared with non-tumor tissues, in tissue microarray analyses. RNA interference knockdown of DRD2 or inhibition with pharmacologic antagonists (pimozide and haloperidol) reduced proliferation of pancreatic cancer cells, induced endoplasmic reticulum stress and apoptosis, and reduced cell migration. RNA interference knockdown of DRD2 in pancreatic tumor cells reduced growth of xenograft tumors in mice, and administration of the DRD2 inhibitor haloperidol to mice with orthotopic xenograft tumors reduced final tumor size and metastasis. CONCLUSIONS: In gene expression profile analysis of PDAC samples, we found the DRD2 signaling pathway to be activated. Inhibition of DRD2 in pancreatic cancer cells reduced proliferation and migration, and slowed growth of xenograft tumors in mice. DRD2 antagonists routinely used for management of schizophrenia might be tested in patients with pancreatic cancer.

Motif comparison based on similarity of binding affinity profiles.

Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs. AVAILABILITY AND IMPLEMENTATION: MoSBAT is available as a webserver at mosbat.ccbr.utoronto.ca, and for download at github.com/csglab/MoSBAT. CONTACT: t.hughes@utoronto.ca or hamed.najafabadi@mcgill.caSupplementary information: Supplementary data are available at Bioinformatics online.

A structural approach reveals how neighbouring C2H2 zinc fingers influence DNA binding specificity.

Development of an accurate protein-DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C2H2 zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C2H2-ZF-DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C2H2-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering.

Identification of C2H2-ZF binding preferences from ChIP-seq data using RCADE.

UNLABELLED: Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys2His2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data. RCADE combines predictions from a DNA recognition code of C2H2-ZFs with ChIP-seq data to identify models that represent the genuine DNA binding preferences of C2H2-ZF proteins. We show that RCADE is able to identify generalizable binding models even from peaks that are exclusively located within the repeat regions of the genome, where state-of-the-art motif finding approaches largely fail. AVAILABILITY AND IMPLEMENTATION: RCADE is available as a webserver and also for download at http://rcade.ccbr.utoronto.ca/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: t.hughes@utoronto.ca.

Global identification of conserved post-transcriptional regulatory programs in trypanosomatids.

While regulatory programs are extensively studied at the level of transcription, elements that are involved in regulation of post-transcriptional processes are largely unknown, and methods for systematic identification of these elements are in early stages. Here, using a novel computational framework, we have integrated sequence information with several functional genomics data sets to characterize conserved regulatory programs of trypanosomatids, a group of eukaryotes that almost entirely rely on post-transcriptional processes for regulation of mRNA abundance. This analysis revealed a complex network of linear and structural RNA elements that potentially govern mRNA abundance across different life stages and environmental conditions. Furthermore, we show that the conserved regulatory network that we have identified is responsive to chemical perturbation of several biological functions in trypanosomatids. We have further characterized one of the most abundant regulatory RNA elements that we discovered, an AU-rich element (ARE) that can be found in 3' untranslated region of many trypanosomatid genes. Using bioinformatics approaches as well as in vitro and in vivo experiments, we have identified three ELAV-like homologs, including the developmentally critical protein TbRBP6, which regulate abundance of a large number of trypanosomatid ARE-containing transcripts. Together, these studies lay out a roadmap for characterization of mechanisms that modulate development and metabolic pathways in trypanosomatids.

Transcriptional reprogramming of skeletal muscle stem cells by the niche environment.

Adult stem cells are indispensable for tissue regeneration, but their function declines with age. The niche environment in which the stem cells reside plays a critical role in their function. However, quantification of the niche effect on stem cell function is lacking. Using muscle stem cells (MuSC) as a model, we show that aging leads to a significant transcriptomic shift in their subpopulations accompanied by locus-specific gain and loss of chromatin accessibility and DNA methylation. By combining in vivo MuSC transplantation and computational methods, we show that the expression of approximately half of all age-altered genes in MuSCs from aged male mice can be restored by exposure to a young niche environment. While there is a correlation between gene reversibility and epigenetic alterations, restoration of gene expression occurs primarily at the level of transcription. The stem cell niche environment therefore represents an important therapeutic target to enhance tissue regeneration in aging.

Analysis of mRNA Dynamics Using RNA Sequencing Data.

The RNA abundance of each gene is determined by its rates of transcription and RNA decay. Biochemical experiments that measure these rates, including transcription inhibition and metabolic labelling, are challenging to perform and are largely limited to in vitro settings. Most transcriptomic studies have focused on analyzing changes in RNA abundances without attributing those changes to transcriptional or posttranscriptional regulation. Estimating differential transcription and decay rates of RNA molecules would enable the identification of regulatory factors, such as transcription factors, RNA binding proteins, and microRNAs, that govern large-scale shifts in RNA expression. Here, we describe a protocol for estimating differential stability of RNA molecules between conditions using standard RNA-sequencing data, without the need for transcription inhibition or metabolic labeling. We apply this protocol to in vivo RNA-seq data from individuals with Alzheimer's disease and demonstrate how estimates of differential stability can be leveraged to infer the regulatory factors underlying them.

Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding.

BACKGROUND: While methylation of CpG dinucleotides is traditionally considered antagonistic to the DNA-binding activity of most transcription factors (TFs), recent in vitro studies have revealed a more complex picture, suggesting that over a third of TFs may preferentially bind to methylated sequences. Expanding these in vitro observations to in vivo TF binding preferences is challenging since the effect of methylation of individual CpG sites cannot be easily isolated from the confounding effects of DNA accessibility and regional DNA methylation. Thus, in vivo methylation preferences of most TFs remain uncharacterized. RESULTS: We introduce joint accessibility-methylation-sequence (JAMS) models, which connect the strength of the binding signal observed in ChIP-seq to the DNA accessibility of the binding site, regional methylation level, DNA sequence, and base-resolution cytosine methylation. We show that JAMS models quantitatively explain TF occupancy, recapitulate cell type-specific TF binding, and have high positive predictive value for identification of TFs affected by intra-motif methylation. Analysis of 2209 ChIP-seq experiments results in high-confidence JAMS models for 260 TFs, revealing a negative association between in vivo TF occupancy and intra-motif methylation for 45% of studied TFs, as well as 16 TFs that are predicted to bind to methylated sites, including 11 novel methyl-binding TFs mostly from the multi-zinc finger family. CONCLUSIONS: Our study substantially expands the repertoire of in vivo methyl-binding TFs, but also suggests that most TFs that prefer methylated CpGs in vitro present themselves as methylation agnostic in vivo, potentially due to the balancing effect of competition with other methyl-binding proteins.

Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs.

Measuring mRNA decay in tumours is a prohibitive challenge, limiting our ability to map the post-transcriptional programs of cancer. Here, using a statistical framework to decouple transcriptional and post-transcriptional effects in RNA-seq data, we uncover the mRNA stability changes that accompany tumour development and progression. Analysis of 7760 samples across 18 cancer types suggests that mRNA stability changes are ~30% as frequent as transcriptional events, highlighting their widespread role in shaping the tumour transcriptome. Dysregulation of programs associated with >80 RNA-binding proteins (RBPs) and microRNAs (miRNAs) drive these changes, including multi-cancer inactivation of RBFOX and miR-29 families. Phenotypic activation or inhibition of RBFOX1 highlights its role in calcium signaling dysregulation, while modulation of miR-29 shows its impact on extracellular matrix organization and stemness genes. Overall, our study underlines the integral role of mRNA stability in shaping the cancer transcriptome, and provides a resource for systematic interrogation of cancer-associated stability pathways.

An integrated model of acinar to ductal metaplasia-related N7-methyladenosine regulators predicts prognosis and immunotherapy in pancreatic carcinoma based on digital spatial profiling.

Acinar-to-ductal metaplasia (ADM) is a recently recognized, yet less well-studied, precursor lesion of pancreatic ductal adenocarcinoma (PDAC) developed in the setting of chronic pancreatitis. Through digital spatial mRNA profiling, we compared ADM and adjacent PDAC tissues from patient samples to unveil the bridging genes during the malignant transformation of pancreatitis. By comparing the bridging genes with the 7-methylguanosine (m7G)-seq dataset, we screened 19 m7G methylation genes for a subsequent large sample analysis. We constructed the "m7G score" model based on the RNA-seq data for pancreatic cancer in The Cancer Genome Atlas (TCGA) database and The Gene Expression Omnibus (GEO) database. Tumors with a high m7G score were characterized by increased immune cell infiltration, increased genomic instability, higher response rate to combined immune checkpoint inhibitors (ICIs), and overall poor survival. These findings indicate that the m7G score is associated with tumor invasiveness, immune cell infiltration, ICI treatment response, and overall patients' survival. We also identified FN1 and ITGB1 as core genes in the m7Gscore model, which affect immune cell infiltration and genomic instability not only in pancreatic cancer but also in pan-cancer. FN1 and ITGB1 can inhibit immune T cell activition by upregulation of macrophages and neutrophils, thereby leading to immune escape of pancreatic cancer cells and reducing the response rate of ICI treatment.

Spatially mapping the immune landscape of melanoma using imaging mass cytometry.

Melanoma is an immunogenic cancer with a high response rate to immune checkpoint inhibitors (ICIs). It harbors a high mutation burden compared with other cancers and, as a result, has abundant tumor-infiltrating lymphocytes (TILs) within its microenvironment. However, understanding the complex interplay between the stroma, tumor cells, and distinct TIL subsets remains a substantial challenge in immune oncology. To properly study this interplay, quantifying spatial relationships of multiple cell types within the tumor microenvironment is crucial. To address this, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously quantify the expression of 35 protein markers, characterizing the microenvironment of 5 benign nevi and 67 melanomas. We profiled more than 220,000 individual cells to identify melanoma, lymphocyte subsets, macrophage/monocyte, and stromal cell populations, allowing for in-depth spatial quantification of the melanoma microenvironment. We found that within pretreatment melanomas, the abundance of proliferating antigen-experienced cytotoxic T cells (CD8+CD45RO+Ki67+) and the proximity of antigen-experienced cytotoxic T cells to melanoma cells were associated with positive response to ICIs. Our study highlights the potential of multiplexed single-cell technology to quantify spatial cell-cell interactions within the tumor microenvironment to understand immune therapy responses.