Factor Binding Site Research Articles

DOP135 Patient-specific regulatory network rewiring in Inflammatory Bowel Disease: How genetic polymorphisms divert incoming signals and contribute to disease pathogenesis

Abstract Background Inflammatory bowel disease (IBD), comprising ulcerative colitis (UC) and Crohn’s disease (CD), arises due to complex interactions between multiple environmental factors and genetic risk loci in the form of single nucleotide polymorphisms (SNPs)1. Many IBD-associated SNPs are located within non-coding genomic regions containing transcription factor (TF) binding sites, where they may cause regulatory shifts by altering TF binding affinity. TFs may lose or gain binding sites, causing a rewiring of the incoming signals acting on the genome2. Characterising these incoming signals could unveil critical insights into the upstream signalling mechanisms driving IBD which via non-coding genetic risk-loci impact downstream cellular processes. The identification of such incoming signals has been elusive with most studies to date evaluating the downstream impact of IBD-associated SNPs3. Methods We developed a novel systems genomics pipeline that individually analysed genotype data from 2636 IBD patients to infer the rewiring of incoming signals affecting gene regulatory networks. Our in silico approach predicted changes to the repertoire of TFs binding to genomic loci due to IBD-associated non-coding SNPs in each patient compared to the healthy state, where these SNPs may be absent. By functionally annotating the TFs in the disease and healthy states using the Gene Ontology database, we inferred the rewiring of upstream signalling pathways (Figure 1). Aggregating these patient-specific findings across the entire cohort allowed us to capture overarching shifts in the incoming signals in IBD that are likely to arise in the context of non-coding SNPs. Results This analysis revealed that 144 and 138 signals were gained or lost in UC patients and CD patients, respectively, compared to the healthy state. Among these, 95 signals were shared between UC and CD, indicating a significant overlap in the upstream signalling mechanisms underpinning both types of IBD. Notably, both diseases showed a net loss of incoming signals, emphasising a major rewiring and decrease of regulation by upstream signalling pathways. These signals belonged to broader categories representing immune response, cell stress response, epithelial barrier function, wound healing, and response to viral/bacterial infection (Figure 2). Conclusion This study highlights that IBD-associated SNPs contribute to disease pathogenesis not only through their downstream effects, but by rewiring the incoming signals which regulate gene expression. Our findings underscore the importance of investigating signalling processes upstream of genetic polymorphisms to gain a more comprehensive understanding of IBD pathogenesis.

ATF6 enables pathogen infection in ticks by inducing stomatin and altering cholesterol dynamics.

How tick-borne pathogens interact with their hosts has been primarily studied in vertebrates where disease is observed. Comparatively less is known about pathogen interactions within the tick. Here, we report that Ixodes scapularis ticks infected with either Anaplasma phagocytophilum (causative agent of anaplasmosis) or Borrelia burgdorferi (causative agent of Lyme disease) show activation of the ATF6 branch of the unfolded protein response (UPR). Disabling ATF6 functionally restricts pathogen survival in ticks. When stimulated, ATF6 functions as a transcription factor, but is the least understood out of the three UPR pathways. To interrogate the Ixodes ATF6 transcriptional network, we developed a custom R script to query tick promoter sequences. This revealed stomatin as a potential gene target, which has roles in lipid homeostasis and vesical transport. Ixodes stomatin was experimentally validated as a bona fide ATF6-regulated gene through luciferase reporter assays, pharmacological activators, and RNAi transcriptional repression. Silencing stomatin decreased A. phagocytophilum colonization in Ixodes and disrupted cholesterol dynamics in tick cells. Furthermore, blocking stomatin restricted cholesterol availability to the bacterium, thereby inhibiting growth and survival. Taken together, we have identified the Ixodes ATF6 pathway as a novel contributor to vector competence through Stomatin-regulated cholesterol homeostasis. Moreover, our custom, web-based transcription factor binding site search tool "ArthroQuest" revealed that the ATF6-regulated nature of stomatin is unique to blood-feeding arthropods. Collectively, these findings highlight the importance of studying fundamental processes in non-model organisms.

ERβ-regulated circATP2B1/miR-204-3p/TWIST1 positive feedback loop facilitates epithelial to mesenchymal transition in clear cell renal cell carcinoma.

Our previous studies have shown that estrogen receptor beta (ERβ) can promote the progression of clear cell renal cell carcinoma (ccRCC) by downregulating the expression of circATP2B1 and miR-204-3p. Here, we found that ERβ might promote the epithelial-mesenchymal transition(EMT) of ccRCC by modulating the circATP2B1/miR-204-3p/TWIST1(Twist family basic helix-loop-helix transcription factor 1) signaling pathway. We utilized bioinformatics analysis to determine the clinical significance of TWIST1 in ccRCC. The expression of TWIST1 in ccRCC tissues and cells was examined using immunohistochemistry, real-time quantitative polymerase chain reaction and western blotting assay. Chromatin Immunoprecipitation assay were conducted to validate the relationship between ERβ and TWIST1. Luciferase reporter gene assays were employed to validate the binding targets of TWIST1 and miR-204-3p. The role of TWIST1 in ccRCC was studied through in vitro and in vivo experiments. Transwell assays and wound healing assays were used to assess the impact of TWIST1 on the invasive and migratory abilities of ccRCC cells. Mechanism analysis revealed that miR-204-3p can inhibit TWIST1 by targeting its 3' untranslated region. Additionally, TWIST1 can promote ERβ transcription by directly binding to transcription factor binding site in the ERβ promoter region, forming a positive feedback loop. These in vitro data were further validated in an in vivo mouse model. Importantly, analysis of data from the TCGA-KIRC database further confirmed the above in vitro/in vivo findings. Together, our results suggest that ERβ/circATP2B1/miR-204-3p/TWIST1 can promote EMT by forming a positive feedback loop, thus promoting the progression of ccRCC. Targeting this newly identified signaling pathway may more effectively control the progression of ccRCC.

Machine and Deep Learning Methods for Predicting 3D Genome Organization.

Three-dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, topologically associating domains (TADs), and A/B compartments, play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers and transcription factor binding site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, and TAD boundaries) and analyze their pros and cons. We also point out obstacles to the computational prediction of 3D interactions and suggest future research directions.

Analyses of the MYBL1 Gene in Triple Negative Breast Cancer: Evidence of Regulation of the VCPIP1 Gene and Identification of a Specific Exon Overexpressed in Tumor Cell Lines.

Previous data show that the knockdown of the MYBL1 gene in the MDA-MB-231 cell line leads to the downregulation of VCPIP1 gene expression. In addition, MYBL1 and VCPIP1 genes are co-expressed and dysregulated in some of the same triple negative breast cancer patient samples. We propose that the co-expression of the two genes is attributed to the MYBL1 transcription factor regulation of the VCPIP1 gene. We identify the MYBL1 transcription factor binding site upstream of the VCPIP1 start site and show that the MYBL1 protein can bind to the sequence identified in the VCPIP1 promoter region. Combined with the results from the knockdown study, these data support the ability of MYBL1 to regulate the VCPIP1 gene. The VCPIP1 gene functions as a deubiquitinating enzyme involved in DNA repair, protein positioning, and the assembly of the Golgi apparatus during mitotic signaling. The transcriptional regulation of VCPIP1 by the MYBL1 gene could implicate MYBL1 in these processes, which might contribute to tumor processes in TNBC. Although both genes are involved in cell cycle regulatory mechanisms, converging signaling mechanisms have not been identified. In a separate study, we performed sequence alignment of the MYBL1 transcript variants and identified an exon unique to the canonical variant. Probes that specifically target the unique MYBL1 exon show that the exon is overexpressed in tumor cell lines compared to non-tumor breast cells. We are classifying this unique MYBL1 exon as a tumor-associated exon.

Genetic Insights into Facial Variation and Craniofacial Development: Unraveling the Interplay of Genes, Expression Patterns, and Evolutionary Significance.

The development of genome technology has opened new possibilities for comparative primate genomics. Non-human primates share approximately 98% genome similarity and provides vital information into the genetic similarities and variances among species utilized as disease models. DNA study links unique genetic variations to common facial attributes such as nose and eyes. This is because of higher adaptation and improved cognitive skills over these sensual areas. Non-protein coding sequences represent approximately 85% of the human DNA under evolutionary restrictions, and the primary part of this is the cis regulatory regions. In this study, a total of 103 tissue specific human enhancers were finalized with help of VISTA Enhancer Browser that showed distinctive expression in the facial tissues and their orthologs were collected. A total of 43 out of 190 transcription factors from TRANSFAC were seen as binding in both Human and Non-Human primate enhancers. It was observed that factor binding sites of 7 of the 43 transcription factors were exclusively gained in the human eye and nose enhancers (Oct, Pax, Sox, MyoD, Foxd3, cRel and Gata). Furthermore, we performed molecular docking through PyMol; DNA & Protein (pdb) structures were modelled by SCFBio & SWISSMODEL respectively to observe interactions of the transcription factors, either by placing the contact surface of the protein exclusively to identify the DNA, to enable a representation to gain information about identification and genetic expression.

Stratified Medicine Paediatrics: Cell free DNA and serial tumour sequencing identifies subtype specific cancer evolution and epigenetic states.

We profiled a large heterogenous cohort of matched diagnostic-relapse tumour tissue and paired plasma-derived cell free DNA (cfDNA) from patients with relapsed and progressive solid tumours of childhood. Tissue and cfDNA sequencing results were concordant, with a wider spectrum of mutant alleles and higher degree of intra-tumour heterogeneity captured by the latter, if sufficient circulating tumour-derived DNA (ctDNA) was present. Serial tumour sequencing identified putative drivers of relapse, with alterations in epigenetic drivers being a common feature. In keeping with epigenetic alterations being a common driver of many childhood cancers, fragmentomics analysis of cfDNA identified tumour-specific epigenetic states and transcription factor binding sites accessible in chromatin. This study leverages a large and well-annotated genomic dataset of aggressive childhood malignancies, identifies genomic and epigenetic drivers of childhood cancer relapse, and highlights the power and practicality of cfDNA analysis to capture both intra-tumoural heterogeneity and the epigenetic state of cancer cells.

ScEccDNAdb: an integrated single-cell eccDNA resource for human and mouse.

Extrachromosomal circular DNA (eccDNA), an extrachromosomal circular structured DNA, is extensively found in eukaryotes. Investigating eccDNA at the single-cell level is crucial for understanding cellular heterogeneity, evolution, development, and specific cellular functions. However, high-throughput identification methods for single-cell eccDNA are complex, and the lack of mature, widely applicable technologies has resulted in limited resources. To address this gap, we built scEccDNAdb, a database based on single-cell whole-genome sequencing data. It contains 3 195 464 single-cell eccDNA entries from human and mouse samples, with annotations including oncogenes, typical enhancers, super-enhancers, CCCTC-binding factor-binding sites, single nucleotide polymorphisms, chromatin accessibility, expression quantitative trait loci, transcription factor binding sites, motifs, and structural variants. Additionally, it provides nine online analysis and visualization tools, which enable the creation of publication-quality figures through user-uploaded files. Overall, scEccDNAdb is a comprehensive database for analyzing single-cell eccDNA data across diverse cell types, tissues, and species. Database URL: https://lcbb.swjtu.edu.cn/scEccDNAdb/.

Structural basis of H3K36 trimethylation by SETD2 during chromatin transcription.

During transcription, RNA polymerase II traverses through chromatin, and post-translational modifications including histone methylations mark regions of active transcription. Histone protein H3 lysine 36 trimethylation (H3K36me3), which is established by the histone methyltransferase SETD2, suppresses cryptic transcription, regulates splicing, and serves as a binding site for transcription elongation factors. The mechanism by which the transcription machinery coordinates the deposition of H3K36me3 is not well understood. Here we provide cryo-electron microscopy structures of mammalian RNA polymerase II-DSIF-SPT6-PAF1c-TFIIS-IWS1-SETD2-nucleosome elongation complexes, revealing that the transcription machinery regulates H3K36me3 deposition by SETD2 on downstream and upstream nucleosomes. SPT6 binds the exposed H2A-H2B dimer during transcription and the SPT6 death-like domain mediates an interaction with SETD2 bound to a nucleosome upstream of RNA polymerase II.

Evolution of a SHOOTMERISTEMLESS transcription factor binding site promotes fruit shape determination

In animals and plants, organ shape is primarily determined during primordium development by carefully coordinated growth and cell division1, 2–3. Rare examples of post-primordial change in morphology (reshaping) exist that offer tractable systems for the study of mechanisms required for organ shape determination and diversification. One such example is morphogenesis in Capsella fruits whose heart-shaped appearance emerges by reshaping of the ovate spheroid gynoecium upon fertilization4. Here we use whole-organ live-cell imaging and single-cell RNA sequencing (scRNA-seq) analysis to show that Capsella fruit shape determination is based on dynamic changes in cell growth and cell division coupled with local maintenance of meristematic identity. At the molecular level, we reveal an auxin-induced mechanism that is required for morphological alteration and ultimately determined by a single cis-regulatory element. This element resides in the promoter of the Capsella rubella SHOOTMERISTEMLESS5 (CrSTM) gene. The CrSTM meristem identity factor positively regulates its own expression through binding to this element, thereby providing a feed-forward loop at the position and time of protrusion emergence to form the heart. Independent evolution of the STM-binding element in STM promoters across Brassicaceae species correlates with those undergoing a gynoecium-to-fruit shape change. Accordingly, genetic and phenotypic studies show that the STM-binding element is required to facilitate the shape transition and suggest a conserved molecular mechanism for organ morphogenesis.

The evaluation of transcription factor binding site prediction tools in human and Arabidopsis genomes

BackgroundThe precise prediction of transcription factor binding sites (TFBSs) is pivotal for unraveling the gene regulatory networks underlying biological processes. While numerous tools have emerged for in silico TFBS prediction in recent years, the evolving landscape of computational biology necessitates thorough assessments of tool performance to ensure accuracy and reliability. Only a limited number of studies have been conducted to evaluate the performance of TFBS prediction tools comprehensively. Thus, the present study focused on assessing twelve widely used TFBS prediction tools and four de novo motif discovery tools using a benchmark dataset comprising real, generic, Markov, and negative sequences. TFBSs of Arabidopsis thaliana and Homo sapiens genomes downloaded from the JASPAR database were implanted in these sequences and the performance of tools was evaluated using several statistical parameters at different overlap percentages between the lengths of known and predicted binding sites.ResultsOverall, the Multiple Cluster Alignment and Search Tool (MCAST) emerged as the best TFBS prediction tool, followed by Find Individual Motif Occurrences (FIMO) and MOtif Occurrence Detection Suite (MOODS). In addition, MotEvo and Dinucleotide Weight Tensor Toolbox (DWT-toolbox) demonstrated the highest sensitivity in identifying TFBSs at 90% and 80% overlap. Further, MCAST and DWT-toolbox managed to demonstrate the highest sensitivity across all three data types real, generic, and Markov. Among the de novo motif discovery tools, the Multiple Em for Motif Elicitation (MEME) emerged as the best performer. An analysis of the promoter regions of genes involved in the anthocyanin biosynthesis pathway in plants and the pentose phosphate pathway in humans, using the three best-performing tools, revealed considerable variation among the top 20 motifs identified by these tools.ConclusionThe findings of this study lay a robust groundwork for selecting optimal TFBS prediction tools for future research. Given the variability observed in tool performance, employing multiple tools for identifying TFBSs in a set of sequences is highly recommended. In addition, further studies are recommended to develop an integrated toolbox that incorporates TFBS prediction or motif discovery tools, aiming to streamline result precision and accuracy.

TFinder: A Python Web Tool for Predicting Transcription Factor Binding Sites.

Transcription is a key cell process that consists of synthesizing several copies of RNA from a gene DNA sequence. This process is highly regulated and closely linked to the ability of transcription factors to bind specifically to DNA. TFinder is an easy-to-use Python web portal allowing the identification of Individual Motifs (IM) such as Transcription Factor Binding Sites (TFBS). Using the NCBI API, TFinder extracts either promoter or gene terminal regulatory regions, through a simple query of NCBI gene name or ID. It enables simultaneous analysis across five different species for an unlimited number of genes. TFinder searches for Individual Motifs in different formats, including IUPAC codes and JASPAR entries. Moreover, TFinder also allows de novo generations of a Position Weight Matrix (PWM) and the use of already established PWM. Finally, the data are provided in a tabular and a graph format showing the relevance and the P-value of the Individual Motifs found as well as their location relative to the Transcription Start Site (TSS) or the terminal region of the gene. The results are then sent by email to users facilitating the subsequent data analysis and sharing. TFinder is written in Python and freely available on GitHub under the MIT license: https://github.com/Jumitti/TFinder. It can be accessed as a web application implemented in Streamlit at https://tfinder-ipmc.streamlit.app. Resources are available on Streamlit "Resources" tab. TFINDER strength is that it relies on an all-in-one intuitive tool allowing users inexperienced with bioinformatics tools to retrieve gene regulatory regions sequences in multiple species and to search for individual motifs in a huge number of genes.

BCDB: A Dual-Branch Network Based on Transformer for Predicting Transcription Factor Binding Sites.

Transcription factor binding sites (TFBSs) are critical in regulating gene expression. Precisely locating TFBSs can reveal the mechanisms of action of different transcription factors in gene transcription. Various deep learning methods have been proposed to predict TFBS; however, these models often need help demonstrating ideal performance under limited data conditions. Furthermore, these models typically have complex structures, which makes their decision-making processes difficult to transparentize. Addressing these issues, we have developed a framework named BCDB. This framework integrates multi-scale DNA information and employs a dual-branch output strategy. Integrating DNABERT, convolutional neural networks(CNN), and multi-head attention mechanisms enhances the feature extraction capabilities, significantly improving the accuracy of predictions. This innovative method aims to balance the extraction of global and local information, enhancing predictive performance while utilizing attention mechanisms to provide an intuitive way to explain the model's predictions, thus strengthening the overall interpretability of the model. Prediction results on 165 ChIP-seq datasets show that BCDB significantly outperforms other existing deep learning methods in terms of performance. Additionally, since the BCDB model utilizes transfer learning methods, it can transfer knowledge learned from many unlabeled data to specific cell line prediction tasks, allowing our model to achieve cross-cell line TFBS prediction. The source code for BCDB is available on https://github.com/ZhangLab312/BCDB.

Cell-state dependent regulation of PPARγ signaling by the transcription factor ZBTB9 in adipocytes

Peroxisome proliferator-activated receptor-γ (PPARγ) is a nuclear hormone receptor that is a master regulator of adipocyte differentiation and function. ZBTB9 is a widely expressed but poorly studied transcription factor that was predicted to interact with PPARγ based on large-scale protein-protein interaction experiments. In addition, genome-wide association studies (GWAS) revealed associations between ZBTB9 and BMI, T2D risk, and HbA1c levels. Here we show that Zbtb9 deficiency in mature adipocytes decreased PPARγ activity and protein level, and thus acts as a positive regulator of PPARγ signaling. In contrast, Zbtb9 deficiency in 3T3-L1 and human preadipocytes increased PPARγ levels and enhanced adipogenesis. Transcriptomic and transcription factor binding site analyses of Zbtb9 deficient preadipocytes revealed that the E2F pathway, controlled by the E2F family of transcription factors that are classically associated with cell cycle regulation, was among the most upregulated pathways. E2F1 positively regulates adipogenesis by promoting Pparg expression, independent of its cell cycle role, via direct binding to the Pparg promoter early during adipogenesis. RB phosphorylation (pRB), which regulates E2F activity, was also upregulated in Zbtb9 deficient preadipocytes. Critically, an E2F1 inhibitor blocked the effects of Zbtb9 deficiency on adipogenesis. Collectively, these results demonstrate that Zbtb9 inhibits adipogenesis as a negative regulator of Pparg expression via pRB-E2F signaling. Our findings reveal cell-state dependent roles of ZBTB9 in adipocytes, identifying a new molecule that regulates adipocyte biology as both a positive and negative regulator of PPARγ signaling depending on the cellular context, and thus may be important in the pathogenesis of obesity and T2D.

Integrative transcriptome and metabolome analyses reveal the mechanism of melatonin in delaying postharvest senescence in cowpeas

Rapid postharvest senescence and quality deterioration severely limit logistics of cowpeas. Melatonin (MEL) is a pivotal bioactive molecule that can modulate multiple physiological attributes in plants. In this study, physiological, transcriptomic and metabolomic analyses were conducted to explore the effects of exogenous MEL on cowpea senescence and its underlying mechanisms. Physiological results showed that 100 μM MEL treatment maintained sensory quality (greeness, firmness and soluble solids content), reduced weight loss as well as inhibited the degradation of chlorophyll (Chl) and protopectin. Preservation of color and firmness in cowpeas was greatly attributed to inhibition of expression of genes related to Chl and cell wall metabolism, which was based on a transcriptomic analysis. Integrated transcriptomic and metabolomic analyses revealed that MEL promoted transcription of genes associated with amino acid and carbohydrate metabolism, resulting in the accumulation of amino acid and sugar metabolites. Additionally, by integrating transcription factor-binding site analysis with cis-acting element analysis, we constructed a regulatory network of transcription factors underlying MEL-mediated antisenescence. The present study found a series of potential candidate genes and metabolites involved in regulating senescence process and provided an insight into improving postharvest quality of cowpeas.

LncRNA MEG3, GAS5, and HOTTIP Polymorphisms Association with Risk of Polycystic Ovary Syndrome: A Case-Control Study and Computational Analyses.

As a multifactorial and endocrine disease, polycystic ovary syndrome (PCOS) affects approximately 5-20% of women worldwide. Recently, long noncoding RNAs (lncRNAs) have emerged as potent predictors of a particular phenotype in PCOS. Our preliminary study examines the link between polymorphisms in lncRNAs MEG3, HOTTIP, and GAS5 and the risk of PCOS. The present study included 200 women with PCOS and 200 healthy women. The studied variations were genotyped by applying the PCR-RFLP and the tetra-ARMS-PCR reaction) techniques. The effect of variation in lncRNA on miRNA:lncRNA interactions, lncRNA-RNA interaction network, and the impact of the variations on the splicing site were predicted using different computational databases. The codominant heterozygous (TC vs. TT) model, the dominant (TC + CC vs. TT) model, the overdominant (TT + CC vs. TC) model, the C allele of rs2023843, and the C allele of rs55829688 had a protective role against PCOS. The A allele of rs4081134 and G allele of rs7158663 of the MEG3 conferred an increased risk of PCOS by 1.37 and 1.44 folds, respectively. The interaction analysis revealed that TC/GG/AA/TC and TC/GG/GA/TC strongly decreased the risk of PCOS by 94 and 92%, respectively. Interestingly, MEG3 and HOTTIP variants can create or disrupt binding sites for several splicing factors. In our population, MEG3 rs4081134 and rs7158663, GAS5 rs55829688, and HOTTIP rs2023843 polymorphisms were associated with PCOS risk. Replication studies on larger sample sizes must be conducted to confirm these findings and investigate other potential causative factors involved in the pathophysiology of PCOS.

Identification of CAP genes in finger lime (Citrus australasica) and their role in plant responses to abiotic and biotic stress

The study focuses on the in silico analysis of cysteine-rich secretory proteins and PR1-like (CAP) genes in finger lime (Citrus australasica), a citrus species known for its tolerance to Huanglongbing (HLB). We identified several PR1-like genes, all belonging to the CRISP family within the CAP superfamily. Of them, CaCAP2 transcript levels increased by over 300-fold in the finger lime compared to ‘Valencia' sweet orange upon infection with ‘Candidatus Liberibacter asiaticus' (CaLas). Localization studies using an EGFP fusion showed that the CAP2 protein is predominantly located in the nucleus, extracellular and plasma membrane. The study also examined CAP2 transcript levels in response to cold, drought stress, and salicylic acid application. Despite environmental stress causing apparent damage, CAP genes seem to play a significant role in managing both biotic and abiotic stresses. Analysis of CAP2 gene promoters from finger lime and sweet orange revealed 95.33% sequence identity, with variations in transcription factor-binding sites and cis-acting elements such as Stress Response Element (STRE: AGGGG), which might influence the differential expression of CAP2 between the two species. Additionally, expressing the finger lime-derived CaCAP2 gene in transgenic Nicotiana tabacum induced a strong defense response against Pseudomonas syringae pv. Tabaci., underscoring the CAP gene's crucial role in plant defense mechanisms against bacterial pathogens.

KAS-ATAC reveals the genome-wide single-stranded accessible chromatin landscape of the human genome.

Gene regulation in most eukaryotes involves two fundamental physical processes -- alterations in the packaging of the genome by nucleosomes, with active cis-regulatory elements (CREs) generally characterized by an open-chromatin configuration, and the activation of transcription. Mapping these physical properties and biochemical activities genome-wide -- through profiling chromatin accessibility and active transcription -- are key tools used to understand the logic and mechanisms of transcription and its regulation. However, the relationship between these two states has until now not been accessible to simultaneous measurement. To address this, we developed KAS-ATAC, a combination of the KAS-seq (Kethoxal-Assisted SsDNA sequencing and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) methods for mapping single-stranded DNA (and thus active transcription) and chromatin accessibility, respectively, enabling the genome-wide identification of DNA fragments that are simultaneously accessible and contain ssDNA. We use KAS-ATAC to evaluate levels of active transcription over different classes of regulatory elements in the human genome, to estimate the absolute levels of transcribed accessible DNA over CREs, to map the nucleosomal configurations associated with RNA polymerase activities, and to assess transcription factor association with transcribed DNA through transcription factor binding site (TFBS) footprinting. We observe lower levels of transcription over distal enhancers compared to promoters and distinct nucleosomal configurations around transcription initiation sites associated with active transcription. Most TFs associate equally with transcribed and nontranscribed DNA but a few factors specifically do not exhibit footprints over ssDNA-containing fragments. We anticipate KAS-ATAC to continue to derive useful insights into chromatin organization and transcriptional regulation in other contexts in the future.

Abstract PR011: Advance prostate cancer detection through epigenomic profiling of cell-free DNA

Abstract Introduction: Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease which can be classified into clinically relevant subtypes based on the expression of genes, such as the androgen receptor (AR) and neuroendocrine markers. Neuroendocrine prostate cancer (NEPC), characterized by gain of stem-like and neuroendocrine features and lack of AR expression is a clinically aggressive variant. Due to the lack of adequate biomarkers, NEPC is usually detected at a very advanced stage. There is mounting evidence that molecular subtype changes seen in NEPC are enforced by widespread epigenetic alterations, in particular DNA methylation changes. In this study, we aim to devise a novel DNA methylation-based assay for molecular subtyping and disease monitoring from cell-free DNA (cfDNA). Methods: We analyzed genome wide methylation patterns in 56 prostate cancer patient-derived xenograft (PDX) and 128 mCRPC tumors using array- and sequencing-based assays. We integrated DNA methylation at promoters, gene bodies and transcription factor binding site (TFBS) to determine the landscape of methylation alterations at key lineage specific genes. Using whole genome methylation derived from tissue with matched expression data we developed a deep learning framework to predict gene expression directly from tissue or cfDNA. Using key marker genes, the model was used to discern tumor molecular phenotypes from tissue and cfDNA in three independent cohorts of mCRPC patients using whole genome bisulfite sequencing and low-pass Enzymatic Methyl-Seq (EM-seq). Results: We observed a tight association between promoter, gene body and TFBS methylation with gene expression. Inferring gene expression from methylation for lineage specific markers such as AR, KLK3, ASCL1, INSM1, SRRM4 and DLL3 we classified molecular subtypes from both tissue and cfDNA. Additionally, for AR and ASCL1, we identified core sets of TFBSs whose differential methylation allowed for accurate assay-independent molecular subtype quantification. Applying the optimized quantitative model to mCRPC patients who underwent comprehensive tissue sampling by rapid autopsy we observed accurate subtype classification from both tissue samples and cfDNA for all cases. A similar analytical performance was observed in additional clinical mCRPC cohorts with cfDNA. Conclusion: Whole-genome methylation analysis of cfDNA allows for the prediction of gene expression patterns in tumor tissues, enabling non-invasive tumor subclassification and assessment of therapeutic targets. Citation Format: Mohamed Adil, Brian Hanratty, Pallabi Mustafi, Chitvan Mittal, Helen Richards, Ilsa Coleman, Radhika Patel, Anna-Lisa Doebley, Robert Patton, Eden Cruikshank, Patricia Galipeau, Ruth Dumpit, Martine Roudier, Jin-Yih Low, Navonil Sarkar, Robert Montgomery, Eva Corey, Colm Morrissey, Peter Nelson, Gavin Ha, Michael Haffner. Advance prostate cancer detection through epigenomic profiling of cell-free DNA [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR011.

Single cell variant to enhancer to gene map for coronary artery disease.

Although genome wide association studies (GWAS) in large populations have identified hundreds of variants associated with common diseases such as coronary artery disease (CAD), most disease-associated variants lie within non-coding regions of the genome, rendering it difficult to determine the downstream causal gene and cell type. Here, we performed paired single nucleus gene expression and chromatin accessibility profiling from 44 human coronary arteries. To link disease variants to molecular traits, we developed a meta-map of 88 samples and discovered 11,182 single-cell chromatin accessibility quantitative trait loci (caQTLs). Heritability enrichment analysis and disease variant mapping demonstrated that smooth muscle cells (SMCs) harbor the greatest genetic risk for CAD. To capture the continuum of SMC cell states in disease, we used dynamic single cell caQTL modeling for the first time in tissue to uncover QTLs whose effects are modified by cell state and expand our insight into genetic regulation of heterogenous cell populations. Notably, we identified a variant in the COL4A1/COL4A2 CAD GWAS locus which becomes a caQTL as SMCs de-differentiate by changing a transcription factor binding site for EGR1/2. To unbiasedly prioritize functional candidate genes, we built a genome-wide single cell variant to enhancer to gene (scV2E2G) map for human CAD to link disease variants to causal genes in cell types. Using this approach, we found several hundred genes predicted to be linked to disease variants in different cell types. Next, we performed genome-wide Hi-C in 16 human coronary arteries to build tissue specific maps of chromatin conformation and link disease variants to integrated chromatin hubs and distal target genes. Using this approach, we show that rs4887091 within the ADAMTS7 CAD GWAS locus modulates function of a super chromatin interactome through a change in a CTCF binding site. Finally, we used CRISPR interference to validate a distal gene, AMOTL2, liked to a CAD GWAS locus. Collectively we provide a disease-agnostic framework to translate human genetic findings to identify pathologic cell states and genes driving disease, producing a comprehensive scV2E2G map with genetic and tissue level convergence for future mechanistic and therapeutic studies.