Transcription factors (TFs) are key players in eukaryotic gene regulation, but the DNA binding specificity of many TFs remains unknown. Here, we assay 284 mostly uncharacterized putative human TFs using selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq), revealing 74 new DNA binding motifs. To investigate whether TFs lacking detectable motifs preferably bind epigenetically modified DNA, we develop methylation-sensitive SMiLE-seq (meSMiLE-seq), a microfluidic assay that simultaneously probes binding to methylated and unmethylated DNA. Using meSMiLE-seq, we assay 114 TFs and identify DNA-binding models for 48 proteins, including known methylation-sensitive binding modes for POU5F1 and RFX5. 11 TFs prefer methylated DNA or display alternative methylation-dependent motifs (e.g. PRDM13), while 13 show aversion to methylated sequences (e.g. USF3). Finally, we identify ZHX2 as a putative Z-DNA binder. Altogether, our study significantly expands the human TF codebook, while providing a versatile platform to quantitatively assay the impact of DNA modifications on TF binding.

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

We describe an effort ("Codebook") to determine the sequence specificity of 332 putative and largely uncharacterized human transcription factors (TFs), as well as 61 control TFs. Nearly 5,000 independent experiments across multiple in vitro and in vivo assays produced motifs for just over half of the putative TFs analyzed (177, or 53%), of which most are unique to a single TF. The data highlight the extensive contribution of transposable elements to TF evolution, both in cis and trans, and identify tens of thousands of conserved, base-level binding sites in the human genome. The use of multiple assays provides an unprecedented opportunity to benchmark and analyze TF sequence specificity, function, and evolution, as further explored in accompanying manuscripts. 1,421 human TFs are now associated with a DNA binding motif. Extrapolation from the Codebook benchmarking, however, suggests that many of the currently known binding motifs for well-studied TFs may inaccurately describe the TF's true sequence preferences.

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies. Analysis of 92 human homeodomain mutants, including disease-associated variants and variants of uncertain significance, reveals variants with altered DNA binding affinity and/or specificity and specificity-determining positions.

A DNA sequence pattern, or "motif", is an essential representation of DNA-binding specificity of a transcription factor (TF). Any particular motif model has potential flaws due to shortcomings of the underlying experimental data and computational motif discovery algorithm. As a part of the Codebook/GRECO-BIT initiative, here we evaluated at large scale the cross-platform recognition performance of positional weight matrices (PWMs), which remain popular motif models in many practical applications. We applied ten different DNA motif discovery tools to generate PWMs from the "Codebook" data comprised of 4,237 experiments from five different platforms profiling the DNA-binding specificity of 394 human proteins, focusing on understudied transcription factors of different structural families. For many of the proteins, there was no prior knowledge of a genuine motif. By benchmarking-supported human curation, we constructed an approved subset of experiments comprising about 30% of all experiments and 50% of tested TFs which displayed consistent motifs across platforms and replicates. We present the Codebook Motif Explorer (https://mex.autosome.org), a detailed online catalog of DNA motifs, including the top-ranked PWMs, and the underlying source and benchmarking data. We demonstrate that in the case of high-quality experimental data, most of the popular motif discovery tools detect valid motifs and generate PWMs, which perform well both on genomic and synthetic data. Yet, for each of the algorithms, there were problematic combinations of proteins and platforms, and the basic motif properties such as nucleotide composition and information content offered little help in detecting such pitfalls. By combining multiple PMWs in decision trees, we demonstrate how our setup can be readily adapted to train and test binding specificity models more complex than PWMs. Overall, our study provides a rich motif catalog as a solid baseline for advanced models and highlights the power of the multi-platform multi-tool approach for reliable mapping of DNA binding specificities.

Supplementary Materials and Methods and Supplementary Figure Legends

The immunological basis of the clinical heterogeneity in autoimmune vasculitis remains poorly understood. In this study, we conduct single-cell transcriptome analyses on peripheral blood mononuclear cells (PBMCs) from newly-onset patients with microscopic polyangiitis (MPA). Increased proportions of activated CD14+ monocytes and CD14+ monocytes expressing interferon signature genes (ISGs) are distinctive features of MPA. Patient-specific analysis further classifies MPA into two groups. The MPA-MONO group is characterized by a high proportion of activated CD14+ monocytes, which persist before and after immunosuppressive therapy. These patients are clinically defined by increased monocyte ratio in the total PBMC count and have a high relapse rate. The MPA-IFN group is characterized by a high proportion of ISG+ CD14+ monocytes. These patients are clinically defined by high serum interferon-alpha concentrations and show good response to immunosuppressive therapy. Our findings identify the immunological phenotypes of MPA and provide clinical insights for personalized treatment and accurate prognostic prediction.

Figure S5, Related to Figure 6. A, Assessment of SRC mRNA levels in MDA-MB-231 SRC-ORF, EMPTY-ORF, or parental cell lines. Data is normalized in RPL19 levels. B, Crystal violet staining assays on day 5 post-transfection confirms the ability of c-SRC to rescue miR-34a-induced anti-tumor growth. C-D, Examples of Pearson correlation analysis indicating MDA-MB-231 cells were not similar to BT-549 and MDA-MB-436 cells, and therefore were not included in the initial K-Means clustering analysis (results shown in D). E, The fold knockdown by miR-34a as compared to the miR-Scr treatments of the indicated genes in Clusters 1-3 in both BT-549 and MDA-MB-436 cells using a 2-fold change cut-off. None of the genes in Cluster 4 were downregulated by miR-34a (data not shown). F, Schematic of the KEGG pathway (hsa04510: Focal Adhesion) with miR-34a downregulated genes highlighted in red. G-H, Represents further analysis of the miR-34a gene signature in breast cancer. G, Indicates correlation analyses of miR-34a target genes in TNBC patients from Metabric data. H, Confirmation of prognostic importance of mIR-34a gene signature using a PROGgeneV2 algorithm on the TCGA data set.

Figure S3, Related to Figure 4. A, c-SRC expression in normal (HFF and MCF-10A), luminal-A (MCF-7), LAR-TNBC (MDA-MB-453), and mesenchymal-TNBC (MDA-MB-231, BT-549, and Hs578T) cell lines. Expression was normalized to GAPDH and made relative to c-SRC expression in HFF lines. B-C, Clonogenic assays in Hs578T (B), and MDA-MB-436 (C) TNBC cells after miR-34a transfection and treatment with Dasatnib (left panels) and paclitaxel (right panel) or as a control HeLa cells after dasatinib treatment (C, right panel). D-E, Assessment of miR-34a target genes in MDA-MB-231 cells after 72 hours of dasatinib treatment (D), or miR-34a levels after 72 hours paclitaxel treatment (E). F, miR-34a promoter luciferase assays in MDA-MB-31 cells after dasatinib treatment. G-H, Spearman rank correlation analysis of SRC levels in cell lines described in Figure 1A (G), and in all breast cancer samples in the Metabric dataset (H). I, Comparable decreases in phospho-Tyr416 active c-SRC, non-phospho-Tyr527 c-SRC, and total c-SRC are observed in MDA-MB-231 cells transfected with 15nM miR-34a versus miR-Scr control, as determined by Western blot analysis. J, Schematic highlighting the miR-34a-c-SRC double-negative feedback loop present in MSL TNBC cells, which can be influenced by exogenous addition of miR-34a, or by dasatinib treatment. * Indicates p<0.05, as compared to control conditions.

Figure S1, Related to Figure 1. A, miRNA microarray data of the top 50 most variant miRNAs across 17 breast cancer cell lines representing either basal/TNBC (top left blue bar) or luminal (top right red bar) breast cancer subgroups. Amongst these miRNAs, miR-34a (red asterisk) was found to be uniquely downregulated in basal lines. B-C, qPCR validation of array data in TNBC and Luminal-A cancer cell lines as compared to normal mammary epithelial lines (CRCs were cultured using the ROCK inhibitor and condition medium from the 3T3 feeder system as previously described(20)). D, Schematic of WebGestalt 2 analysis of Affymetrix microarray data across 19 cell lines. ¬¬miR-34a is one of several miRNAs with target enrichment in the TNBC overexpressed gene set. E, Results of hypergeometric analysis of miR-34a targets using a more stringent context score cutoff of -0.27. F, SRB growth assays on additional TNBC and normal cell lines.

Figure S2, Related to Figure 2. A-F, Functional characterization of miR-34a re-introduction in additional TNBC and non-TNBC cell lines by way of Matrigel-invasion (A), soft agar growth (B), and BrdU labeling (C) experiments. For BrdU assays, we observed only a 5-10% accumulation of BrdU-positive cells 4 days post-transfection. SA-β-gal assays on MDA-MB-157 (D), and BT-20 (E, left panel) TNBC cells, as compared to MCF-7 luminal-A cells (E, right panel). F, MCF-7 cells stably transfected with either a miR-34a (miR-34a SP) or a control (Empty SP) reporter/sponge construct was assayed for SA-β-gal activity. Two independent miR-34a SP pools were generated. G, Luciferase reporter assays indicative of miR-34a activity in all TNBC, luminal, and normal cell lines used in this study. H, miRNA levels in MDA-MB-231, MDA-MB-436, and BT-549 TNBC cells or BT-474 and MCF-7 Luminal-A cells 72 hours after 10nM miR-34a or miR-Scr transfection. In TNBC cells miR-34a expressing lines harbored lower levels of miR-17/92 family members as compared to miR-Scr treated lines. * Indicates p<0.05, as compared to control conditions.

Figure S4, Related to Figure 5. A-F, Further characterization of c-SRC siRNA treatments in TNBC cell lines. A, Crystal violet staining of MDA-MB-231 and Hs578T cells post 15nM si-SRC and si-Neg transfection (Day 6 images, left panel), and quantification of staining abundance is shown on right panels). B, SRB results on Hs578T cell line. C, Analysis of a second siRNA to c-SRC in MDA-MB-231 cells. SRB assays are shown in the left panel and western blot analysis confirming c-SRC knockdown (72 hour post-transfection) is shown on the right panel. D, Crystal violet staining of HFF cells. E, SA-β-gal assays in the indicated cell lines 5 days after 15nM si-SRC transfection. F, miR-34a levels 72 hours after 15nM si-SRC transfection in Hs578T cells. G, Assessment of SRC mRNA levels in the indicated cell lines 72 hours after 15nM si-SRC transfection.

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. Wefurther demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

Expression levels of many microRNAs (miRNAs) change during aging, notably declining globally in a number of organisms and tissues across taxa. However, little is known about the mechanisms or the biological relevance for this change. We investigated the network of genes that controls miRNA transcription and processing duringC. elegansaging. We found that miRNA biogenesis genes are highly networked with transcription factors and aging-associated miRNAs. In particular, miR-71, known to influence life span and itself up-regulated during aging, repressesalg-1/Argonaute expression post-transcriptionally during aging. Increased ALG-1 abundance inmir-71loss-of-function mutants led to globally increased miRNA expression. Interestingly, these mutants demonstrated widespread mRNA expression dysregulation and diminished levels of variability both in gene expression and in overall life span. Thus, the progressive molecular decline often thought to be the result of accumulated damage over an organism's life may be partially explained by a miRNA-directed mechanism of age-associated decline.

Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA. While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding. In this review, we discuss technological developments for identifying TF binding preferences and highlight recent discoveries that elaborate how TF interactions, local DNA structure, and genomic features influence TF-DNA binding. We highlight novel approaches for characterizing functional binding site motifs that promise to inform our understanding of how TF binding controls gene expression and ultimately contributes to phenotype.

Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their impact on DNA binding activity and used universal protein-binding microarrays to assay sequence-specific DNA binding activity across 41 reference and 117 variant alleles found in individuals of diverse ancestries and families with Mendelian diseases. We found 77 variants in 28 genes that affect DNA binding affinity or specificity and identified thousands of rare alleles likely to alter the DNA binding activity of human sequence-specific TFs. Our results suggest that most individuals have unique repertoires of TF DNA binding activities, which may contribute to phenotypic variation.

Abstract Triple-negative breast cancer (TNBC) is an aggressive subtype with no clinically proven biologically targeted treatment options. The molecular heterogeneity of TNBC and lack of high frequency driver mutations other than TP53 have hindered the development of new and effective therapies that significantly improve patient outcomes. miRNAs, global regulators of survival and proliferation pathways important in tumor development and maintenance, are becoming promising therapeutic agents. We performed miRNA-profiling studies in different TNBC subtypes to identify miRNAs that significantly contribute to disease progression. We found that miR-34a was lost in TNBC, specifically within mesenchymal and mesenchymal stem cell–like subtypes, whereas expression of miR-34a targets was significantly enriched. Furthermore, restoration of miR-34a in cell lines representing these subtypes inhibited proliferation and invasion, activated senescence, and promoted sensitivity to dasatinib by targeting the proto-oncogene c-SRC. Notably, SRC depletion in TNBC cell lines phenocopied the effects of miR-34a reintroduction, whereas SRC overexpression rescued the antitumorigenic properties mediated by miR-34a. miR-34a levels also increased when cells were treated with c-SRC inhibitors, suggesting a negative feedback exists between miR-34a and c-SRC. Moreover, miR-34a administration significantly delayed tumor growth of subcutaneously and orthotopically implanted tumors in nude mice, and was accompanied by c-SRC downregulation. Finally, we found that miR-34a and SRC levels were inversely correlated in human tumor specimens. Together, our results demonstrate that miR-34a exerts potent antitumorigenic effects in vitro and in vivo and suggests that miR-34a replacement therapy, which is currently being tested in human clinical trials, represents a promising therapeutic strategy for TNBC. Cancer Res; 76(4); 927–39. ©2015 AACR.

Abstract Triple-negative breast cancer (TNBC) accounts for a disproportionate share of the total breast cancer morbidity because of its aggressive behavior and lack of effective targeted therapies to treat the disease. MicroRNAs, global regulators of survival and proliferation pathways important in tumor development and maintenance, are highly dysregulated in cancer. We identified miR-34a to be aberrantly lost in TNBC lines when compared to both a luminal cancer subtype as well as normal breast cells. Re-introduction of miR-34a in TNBC lines results in inhibition of cell proliferation and invasion, reactivation of senescence, and enhanced sensitivity to apoptosis inducing agents. Furthermore, intratumoral delivery of miR-34a into subcutaneous tumors in nude mice, as well as systemic delivery of poly(amine-co-ester) PACE-loaded miR-34a in an orthotopic setting, delayed tumor growth. In conclusion, re-introduction of miR-34a in TNBC promotes potent anti-tumorigenic phenotypes in vitro and in vivo, and could be a promising targeted therapeutic agent to treat the disease. Citation Format: Brian D. Adams, Vikram Wali, Chris Cheng, Sachi Inukai, David Rimm, Lajos Pusztai, Mark Saltzman, Frank Slack. Reintroduction of tumor-suppressor miR-34a shows therapeutic efficacy in triple-negative breast cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-300. doi:10.1158/1538-7445.AM2015-LB-300

BackgroundDietary restriction (DR) has been shown to prolong longevity across diverse taxa, yet the mechanistic relationship between DR and longevity remains unclear. MicroRNAs (miRNAs) control aging-related functions such as metabolism and lifespan through regulation of genes in insulin signaling, mitochondrial respiration, and protein homeostasis.ResultsWe have conducted a network analysis of aging-associated miRNAs connected to transcription factors PHA-4/FOXA and SKN-1/Nrf, which are both necessary for DR-induced lifespan extension in Caenorhabditis elegans. Our network analysis has revealed extensive regulatory interactions between PHA-4, SKN-1, and miRNAs and points to two aging-associated miRNAs, miR-71 and miR-228, as key nodes of this network. We show that miR-71 and miR-228 are critical for the response to DR in C. elegans. DR induces the expression of miR-71 and miR-228, and the regulation of these miRNAs depends on PHA-4 and SKN-1. In turn, we show that PHA-4 and SKN-1 are negatively regulated by miR-228, whereas miR-71 represses PHA-4.ConclusionsBased on our findings, we have discovered new links in an important pathway connecting DR to aging. By interacting with PHA-4 and SKN-1, miRNAs transduce the effect of dietary-restriction-mediated lifespan extension in C. elegans. Given the conservation of miRNAs, PHA-4, and SKN-1 across phylogeny, these interactions are likely to be conserved in more-complex species.