Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data.

Transcription factors (TFs) are crucial epigenetic regulators, which enable cells to dynamically adjust gene expression in response to environmental signals. Computational procedures like digital genomic footprinting on chromatin accessibility assays such as ATACseq can be used to identify bound TFs in a genome-wide scale. This method utilizes short regions of low accessibility signals due to steric hindrance of DNA bound proteins, called footprints (FPs), which are combined with motif databases for TF identification. However, while over 1600 TFs have been described in the human genome, only ~ 700 of these have a known binding motif. Thus, a substantial number of FPs without overlap to a known DNA motif are normally discarded from FP analysis. In addition, the FP method is restricted to organisms with a substantial number of known TF motifs. Here we present DENIS (DE Novo motIf diScovery), a framework to generate and systematically investigate the potential of de novo TF motif discovery from FPs. DENIS includes functionality (1) to isolate FPs without binding motifs, (2) to perform de novo motif generation and (3) to characterize novel motifs. Here, we show that the framework rediscovers artificially removed TF motifs, quantifies de novo motif usage during an early embryonic development example dataset, and is able to analyze and uncover TF activity in organisms lacking canonical motifs. The latter task is exemplified by an investigation of a scATAC-seq dataset in zebrafish which covers different cell types during hematopoiesis.

Shortened CRISPR-Cas9 arrays enable multiplexed gene targeting in bacteria from a smaller DNA footprint.

CRISPR technologies comprising a Cas nuclease and a guide RNA (gRNA) can utilize multiple gRNAs to enact multi-site editing or regulation in the same cell. Nature devised a highly compact means of encoding gRNAs in the form of CRISPR arrays composed of conserved repeats separated by targeting spacers. However, the capacity to acquire new spacers keeps the arrays longer than necessary for CRISPR technologies. Here, we show that CRISPR arrays utilized by the Cas9 nuclease can be shortened without compromising and sometimes even enhancing targeting activity. Using multiplexed gene repression in E. coli, we found that each region could be systematically shortened to varying degrees before severely compromising targeting activity. Surprisingly, shortening some spacers yielded enhanced targeting activity, which was linked to folding of the transcribed array prior to processing. Overall, shortened CRISPR-Cas9 arrays can facilitate multiplexed editing and gene regulation from a smaller DNA footprint across many bacterial applications of CRISPR technologies.

Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds.

In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, FST, FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes.

Genome-wide quantification of transcription factor binding at single-DNA-molecule resolution using methyl-transferase footprinting.

Precise control of gene expression requires the coordinated action of multiple factors at cis-regulatory elements. We recently developed single-molecule footprinting to simultaneously resolve the occupancy of multiple proteins including transcription factors, RNA polymerase II and nucleosomes on single DNA molecules genome-wide. The technique combines the use of cytosine methyltransferases to footprint the genome with bisulfite sequencing to resolve transcription factor binding patterns at cis-regulatory elements. DNA footprinting is performed by incubating permeabilized nuclei with recombinant methyltransferases. Upon DNA extraction, whole-genome or targeted bisulfite libraries are prepared and loaded on Illumina sequencers. The protocol can be completed in 4-5 d in any laboratory with access to high-throughput sequencing. Analysis can be performed in 2 d using a dedicated R package and requires access to a high-performance computing system. Our method can be used to analyze how transcription factors cooperate and antagonize to regulate transcription.

The native cistrome and sequence motif families of the maize ear.

Elucidating the transcriptional regulatory networks that underlie growth and development requires robust ways to define the complete set of transcription factor (TF) binding sites. Although TF-binding sites are known to be generally located within accessible chromatin regions (ACRs), pinpointing these DNA regulatory elements globally remains challenging. Current approaches primarily identify binding sites for a single TF (e.g. ChIP-seq), or globally detect ACRs but lack the resolution to consistently define TF-binding sites (e.g. DNAse-seq, ATAC-seq). To address this challenge, we developed MNase-defined cistrome-Occupancy Analysis (MOA-seq), a high-resolution (< 30 bp), high-throughput, and genome-wide strategy to globally identify putative TF-binding sites within ACRs. We used MOA-seq on developing maize ears as a proof of concept, able to define a cistrome of 145,000 MOA footprints (MFs). While a substantial majority (76%) of the known ATAC-seq ACRs intersected with the MFs, only a minority of MFs overlapped with the ATAC peaks, indicating that the majority of MFs were novel and not detected by ATAC-seq. MFs were associated with promoters and significantly enriched for TF-binding and long-range chromatin interaction sites, including for the well-characterized FASCIATED EAR4, KNOTTED1, and TEOSINTE BRANCHED1. Importantly, the MOA-seq strategy improved the spatial resolution of TF-binding prediction and allowed us to identify 215 motif families collectively distributed over more than 100,000 non-overlapping, putatively-occupied binding sites across the genome. Our study presents a simple, efficient, and high-resolution approach to identify putative TF footprints and binding motifs genome-wide, to ultimately define a native cistrome atlas.

Resolving diverse protein-DNA footprints from exonuclease-based ChIP experiments.

MOTIVATION: High-throughput chromatin immunoprecipitation (ChIP) sequencing-based assays capture genomic regions associated with the profiled transcription factor (TF). ChIP-exo is a modified protocol, which uses lambda exonuclease to digest DNA close to the TF-DNA complex, in order to improve on the positional resolution of the TF-DNA contact. Because the digestion occurs in the 5'-3' orientation, the protocol produces directional footprints close to the complex, on both sides of the double stranded DNA. Like all ChIP-based methods, ChIP-exo reports a mixture of different regions associated with the TF: those bound directly to the TF as well as via intermediaries. However, the distribution of footprints are likely to be indicative of the complex forming at the DNA. RESULTS: We present ExoDiversity, which uses a model-based framework to learn a joint distribution over footprints and motifs, thus resolving the mixture of ChIP-exo footprints into diverse binding modes. It uses no prior motif or TF information and automatically learns the number of different modes from the data. We show its application on a wide range of TFs and organisms/cell-types. Because its goal is to explain the complete set of reported regions, it is able to identify co-factor TF motifs that appear in a small fraction of the dataset. Further, ExoDiversity discovers small nucleotide variations within and outside canonical motifs, which co-occur with variations in footprints, suggesting that the TF-DNA structural configuration at those regions is likely to be different. Finally, we show that detected modes have specific DNA shape features and conservation signals, giving insights into the structure and function of the putative TF-DNA complexes. AVAILABILITY AND IMPLEMENTATION: The code for ExoDiversity is available on https://github.com/NarlikarLab/exoDIVERSITY. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic Footprinting Analyses from DNase-seq Data to Construct Gene Regulatory Networks.

Chromatin accessibility is directly linked with transcription in eukaryotes. Accessible regions associated with regulatory proteins are highly sensitive to DNase I digestion and are termed DNase I hypersensitive sites (DHSs). DHSs can be identified by DNase I digestion, followed by high-throughput DNA sequencing (DNase-seq). The single-base-pair resolution digestion patterns from DNase-seq allows identifying transcription factor (TF) footprints of local DNA protection that predict TF-DNA binding. The identification of differential footprinting between two conditions allows mapping relevant TF regulatory interactions. Here, we provide step-by-step instructions to build gene regulatory networks from DNase-seq data. Our pipeline includes steps for DHSs calling, identification of differential TF footprints between treatment and control conditions, and construction of gene regulatory networks. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be adapted to work with DNase-seq data from any organism with a sequenced genome.

Evolving origin-of-transfer sequences on staphylococcal conjugative and mobilizable plasmids-who's mimicking whom?

In Staphylococcus aureus, most multiresistance plasmids lack conjugation or mobilization genes for horizontal transfer. However, most are mobilizable due to carriage of origin-of-transfer (oriT) sequences mimicking those of conjugative plasmids related to pWBG749. pWBG749-family plasmids have diverged to carry five distinct oriT subtypes and non-conjugative plasmids have been identified that contain mimics of each. The relaxasome accessory factor SmpO, encoded by each conjugative plasmid, determines specificity for its cognate oriT. Here we characterized the binding of SmpO proteins to each oriT. SmpO proteins predominantly formed tetramers in solution and bound 5'-GNNNNC-3' sites within each oriT. Four of the five SmpO proteins specifically bound their cognate oriT. An F7K substitution in pWBG749 SmpO switched oriT-binding specificity in vitro. In vivo, the F7K substitution reduced but did not abolish self-transfer of pWBG749. Notably, the substitution broadened the oriT subtypes that were mobilized. Thus, this substitution represents a potential evolutionary intermediate with promiscuous DNA-binding specificity that could facilitate a switch between oriT specificities. Phylogenetic analysis suggests pWBG749-family plasmids have switched oriT specificity more than once during evolution. We hypothesize the convergent evolution of oriT specificity in distinct branches of the pWBG749-family phylogeny reflects indirect selection pressure to mobilize plasmids carrying non-cognate oriT-mimics.

Rapid and inexpensive preparation of genome-wide nucleosome footprints from model and non-model organisms.

MNase-seq (micrococcal nuclease sequencing) is used to map nucleosome positions in eukaryotic genomes to study the relationship between chromatin structure and DNA-dependent processes. Current protocols require at least two days to isolate nucleosome-protected DNA fragments. We have developed a streamlined protocol for S. cerevisiae and other fungi which takes only three hours. Modified protocols were developed for wild fungi and mammalian cells. This method for rapidly producing sequencing-ready nucleosome footprints from several organisms makes MNase-seq faster and easier, with less chemical waste.

In Vivo Footprinting Analysis in Trichoderma reesei.

The in vivo footprinting method identifies protein-targeted DNA regions under different conditions such as carbon sources. Dimethyl sulfate (DMS) generates methylated purine bases at DNA sites which are not bound by proteins or transcription factors. The DNA is cleaved by HCl, and the resulting DNA fragments are 5'-end [6-FAM]-labeled by a linker-mediated PCR (LM-PCR). Fluorescent fragments are separated and analyzed on a capillary sequencer, followed by automated data analysis using the software tool ivFAST.

Using an L7Ae-Tethered, Hydroxyl Radical-Mediated Footprinting Strategy to Identify and Validate Kink-Turns in RNAs.

Kink-turns are important RNA structural modules that facilitate long-range tertiary interactions and form binding sites for members of the L7Ae family of proteins. Present in a wide variety of functional RNAs, kink-turns play key organizational roles in many RNA-based cellular processes, including translation, modification, and tRNA biogenesis. It is important to determine the contribution of kink-turns to the overall architecture of resident RNAs, as these modules dictate ribonucleoprotein (RNP) assembly and function. This chapter describes a site-directed, hydroxyl radical-mediated footprinting strategy that utilizes L7Ae-tethered chemical nucleases to experimentally validate computationally identified kink-turns in any RNA and under a wide variety of conditions. The work plan described here uses the catalytic RNase P RNA as an example to provide a blueprint for using this footprinting method to map RNA-protein interactions in other RNP complexes.

Molecular Co-occupancy Identifies Transcription Factor Binding Cooperativity In Vivo.

Gene activation requires the cooperative activity of multiple transcription factors at cis-regulatory elements (CREs). Yet, most transcription factors have short residence time, questioning the requirement of their physical co-occupancy on DNA to achieve cooperativity. Here, we present a DNA footprinting method that detects individual molecular interactions of transcription factors and nucleosomes with DNA in vivo. We apply this strategy to quantify the simultaneous binding of multiple transcription factors on single DNA molecules at mouse CREs. Analysis of the binary occupancy patterns at thousands of motif combinations reveals that high DNA co-occupancy occurs for most types of transcription factors, in the absence of direct physical interaction, at sites of competition with nucleosomes. Perturbation of pairwise interactions demonstrates the function of molecular co-occupancy in binding cooperativity. Our results reveal the interactions regulating CREs at molecular resolution and identify DNA co-occupancy as a widespread cooperativity mechanism used by transcription factors to remodel chromatin.

ATAC-seq with unique molecular identifiers improves quantification and footprinting.

ATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) provides an efficient way to analyze nucleosome-free regions and has been applied widely to identify transcription factor footprints. Both applications rely on the accurate quantification of insertion events of the hyperactive transposase Tn5. However, due to the presence of the PCR amplification, it is impossible to accurately distinguish independently generated identical Tn5 insertion events from PCR duplicates using the standard ATAC-seq technique. Removing PCR duplicates based on mapping coordinates introduces increasing bias towards highly accessible chromatin regions. To overcome this limitation, we establish a UMI-ATAC-seq technique by incorporating unique molecular identifiers (UMIs) into standard ATAC-seq procedures. UMI-ATAC-seq can rescue about 20% of reads that are mistaken as PCR duplicates in standard ATAC-seq in our study. We demonstrate that UMI-ATAC-seq could more accurately quantify chromatin accessibility and significantly improve the sensitivity of identifying transcription factor footprints. An analytic pipeline is developed to facilitate the application of UMI-ATAC-seq, and it is available at https://github.com/tzhu-bio/UMI-ATAC-seq .

Molecular Footprints of the Immune Assault on Pancreatic Beta Cells in Type 1 Diabetes.

Type 1 diabetes (T1D) is a chronic disease caused by the selective destruction of the insulin-producing pancreatic beta cells by infiltrating immune cells. We presently evaluated the transcriptomic signature observed in beta cells in early T1D and compared it with the signatures observed following in vitro exposure of human islets to inflammatory or metabolic stresses, with the aim of identifying "footprints" of the immune assault in the target beta cells. We detected similarities between the beta cell signatures induced by cytokines present at different moments of the disease, i.e., interferon-α (early disease) and interleukin-1ß plus interferon-γ (later stages) and the beta cells from T1D patients, identifying biological process and signaling pathways activated during early and late stages of the disease. Among the first responses triggered on beta cells was an enrichment in antiviral responses, pattern recognition receptors activation, protein modification and MHC class I antigen presentation. During putative later stages of insulitis the processes were dominated by T-cell recruitment and activation and attempts of beta cells to defend themselves through the activation of anti-inflammatory pathways (i.e., IL10, IL4/13) and immune check-point proteins (i.e., PDL1 and HLA-E). Finally, we mined the beta cell signature in islets from T1D patients using the Connectivity Map, a large database of chemical compounds/drugs, and identified interesting candidates to potentially revert the effects of insulitis on beta cells.

CUT&RUN detects distinct DNA footprints of RNA polymerase II near the transcription start sites.

CUT&RUN is a powerful tool to study protein-DNA interactions in vivo. DNA fragments cleaved by the targeted micrococcal nuclease identify the footprints of DNA-binding proteins on the chromatin. We performed CUT&RUN on human lung carcinoma cell line A549 maintained in a multi-well cell culture plate to profile RNA polymerase II. Long (> 270 bp) DNA fragments released by CUT&RUN corresponded to the bimodal peak around the transcription start sites, as previously seen with chromatin immunoprecipitation. However, we found that short (< 120 bp) fragments identify a well-defined peak localised at the transcription start sites. This distinct DNA footprint of short fragments, which constituted only about 5% of the total reads, suggests the transient positioning of RNA polymerase II before promoter-proximal pausing, which has not been detected in the physiological settings by standard chromatin immunoprecipitation. We showed that the positioning of the large-size-class DNA footprints around the short-fragment peak was associated with the directionality of transcription, demonstrating the biological significance of distinct CUT&RUN footprints of RNA polymerase II.

Global reference mapping of human transcription factor footprints.

Combinatorial binding of transcription factors to regulatory DNA underpins gene regulation in all organisms. Genetic variation in regulatory regions has been connected with diseases and diverse phenotypic traits1, but it remains challenging to distinguish variants that affect regulatory function2. Genomic DNase I footprinting enables the quantitative, nucleotide-resolution delineation of sites of transcription factor occupancy within native chromatin3-6. However, only a small fraction of such sites have been precisely resolved on the human genome sequence6. Here, to enable comprehensive mapping of transcription factor footprints, we produced high-density DNase I cleavage maps from 243 human cell and tissue types and states and integrated these data to delineate about 4.5 million compact genomic elements that encode transcription factor occupancy at nucleotide resolution. We map the fine-scale structure within about 1.6 million DNase I-hypersensitive sites and show that the overwhelming majority are populated by well-spaced sites of single transcription factor-DNA interaction. Cell-context-dependent cis-regulation is chiefly executed by wholesale modulation of accessibility at regulatory DNA rather than by differential transcription factor occupancy within accessible elements. We also show that the enrichment of genetic variants associated with diseases or phenotypic traits in regulatory regions1,7 is almost entirely attributable to variants within footprints, and that functional variants that affect transcription factor occupancy are nearly evenly partitioned between loss- and gain-of-function alleles. Unexpectedly, we find increased density of human genetic variation within transcription factor footprints, revealing an unappreciated driver of cis-regulatory evolution. Our results provide a framework for both global and nucleotide-precision analyses of gene regulatory mechanisms and functional genetic variation.

Expanded encyclopaedias of DNA elements in the human and mouse genomes.

The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.

The SNAIL1 promoter contains G-quadruplex structures regulating its gene expression and DNA replication.

SNAIL1 is a key regulator of epithelial-mesenchymal transition (EMT) and its expression is associated with tumor progression and poor clinical prognosis of cancer patients. Compared to the studies of SNAIL1 stability and its transcriptional regulation, very limited knowledge is available regarding effective approaches to directly target SNAIL1. In this study, we revealed the potential regulation of SNAIL1 gene expression by G-quadruplex structures in its promoter. We first revealed that the negative strand of the SNAIL1 promoter contained a multi-G-tract region with high potential of forming G-quadruplex structures. In circular dichroism studies, the oligonucleotide based on this region showed characteristic molar ellipticity at specific wavelengths of G-quadruplex structures. We also utilized native polyacrylamide gel electrophoresis, gel-shift assays, immunofluorescent staining, dimethyl sulfate footprinting and chromatin immunoprecipitation studies to verify the G-quadruplex structures formed by the oligonucleotide. In reporter assays, disruption of G-quadruplex potential increased SNAIL1 promoter-mediated transcription, suggesting that G-quadruplexes played a negative role in SNAIL1 expression. In a DNA synthesis study, we detected G-quadruplex-mediated retardation in the SNAIL1 promoter replication. Consistently, we discovered that the G-quadruplex region of the SNAIL1 promoter is highly enriched for mutations, implicating the clinical relevance of G-quadruplexes to the altered SNAIL1 expression in cancer cells.

Disome and Trisome Profiling Reveal Genome-wide Targets of Ribosome Quality Control.

The ribosome-associated protein quality control (RQC) system that resolves stalled translation events is activated when ribosomes collide and form disome, trisome, or higher-order complexes. However, it is unclear whether this system distinguishes collision complexes formed on defective mRNAs from those with functional roles on endogenous transcripts. Here, we performed disome and trisome footprint profiling in yeast and found collisions were enriched on diverse sequence motifs known to slow translation. When 60S recycling was inhibited, disomes accumulated at stop codons and could move into the 3' UTR to reinitiate translation. The ubiquitin ligase and RQC factor Hel2/ZNF598 generally recognized collisions but did not induce degradation of endogenous transcripts. However, loss of Hel2 triggered the integrated stress response, via phosphorylation of eIF2α, thus linking these pathways. Our results suggest that Hel2 has a role in sensing ribosome collisions on endogenous mRNAs, and such events may be important for cellular homeostasis.

TRACE: transcription factor footprinting using chromatin accessibility data and DNA sequence.

Transcription is tightly regulated by cis-regulatory DNA elements where transcription factors (TFs) can bind. Thus, identification of TF binding sites (TFBSs) is key to understanding gene expression and whole regulatory networks within a cell. The standard approaches used for TFBS prediction, such as position weight matrices (PWMs) and chromatin immunoprecipitation followed by sequencing (ChIP-seq), are widely used but have their drawbacks, including high false-positive rates and limited antibody availability, respectively. Several computational footprinting algorithms have been developed to detect TFBSs by investigating chromatin accessibility patterns; however, these also have limitations. We have developed a footprinting method to predict TF footprints in active chromatin elements (TRACE) to improve the prediction of TFBS footprints. TRACE incorporates DNase-seq data and PWMs within a multivariate hidden Markov model (HMM) to detect footprint-like regions with matching motifs. TRACE is an unsupervised method that accurately annotates binding sites for specific TFs automatically with no requirement for pregenerated candidate binding sites or ChIP-seq training data. Compared with published footprinting algorithms, TRACE has the best overall performance with the distinct advantage of targeting multiple motifs in a single model.