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BACKGROUND: Tumour dormancy, a resistance mechanism employed by cancer cells, is a significant challenge in cancer treatment, contributing to minimal residual disease (MRD) and potential relapse. Despite its clinical importance, the mechanisms underlying tumour dormancy and MRD remain unclear. In this study, we employed two syngeneic murine models of myeloid leukemia and melanoma to investigate the genetic, epigenetic, transcriptomic and protein signatures associated with tumour dormancy. We used a multiomics approach to elucidate the molecular mechanisms driving MRD and identify potential therapeutic targets. RESULTS: We conducted an in-depth omics analysis encompassing whole-exome sequencing (WES), copy number variation (CNV) analysis, chromatin immunoprecipitation followed by sequencing (ChIP-seq), transcriptome and proteome investigations. WES analysis revealed a modest overlap of gene mutations between melanoma and leukemia dormancy models, with a significant number of mutated genes found exclusively in dormant cells. These exclusive genetic signatures suggest selective pressure during MRD, potentially conferring resistance to the microenvironment or therapies. CNV, histone marks and transcriptomic gene expression signatures combined with Gene Ontology (GO) enrichment analysis highlighted the potential functional roles of the mutated genes, providing insights into the pathways associated with MRD. In addition, we compared "murine MRD genes" profiles to the corresponding human disease through public datasets and highlighted common features according to disease progression. Proteomic analysis combined with multi-omics genetic investigations, revealed a dysregulated proteins signature in dormant cells with minimal genetic mechanism involvement. Pathway enrichment analysis revealed the metabolic, differentiation and cytoskeletal remodeling processes involved in MRD. Finally, we identified 11 common proteins differentially expressed in dormant cells from both pathologies. CONCLUSIONS: Our study underscores the complexity of tumour dormancy, implicating both genetic and nongenetic factors. By comparing genomic, transcriptomic, proteomic, and epigenomic datasets, our study provides a comprehensive understanding of the molecular landscape of minimal residual disease. These results provide a robust foundation for forthcoming investigations and offer potential avenues for the advancement of targeted MRD therapies in leukemia and melanoma patients, emphasizing the importance of considering both genetic and nongenetic factors in treatment strategies.

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BACKGROUND: Discovery biological motifs plays a fundamental role in understanding regulatory mechanisms. Computationally, they can be efficiently represented as kmers, making the counting of these elements a critical aspect for ensuring not only the accuracy but also the efficiency of the analytical process. This is particularly useful in scenarios involving large data volumes, such as those generated by the ChIP-seq protocol. Against this backdrop, we introduce BIOMAPP::CHIP, a tool specifically designed to optimize the discovery of biological motifs in large data volumes. RESULTS: We conducted a comprehensive set of comparative tests with state-of-the-art algorithms. Our analyses revealed that BIOMAPP::CHIP outperforms existing approaches in various metrics, excelling both in terms of performance and accuracy. The tests demonstrated a higher detection rate of significant motifs and also greater agility in the execution of the algorithm. Furthermore, the SMT component played a vital role in the system's efficiency, proving to be both agile and accurate in kmer counting, which in turn improved the overall efficacy of our tool. CONCLUSION: BIOMAPP::CHIP represent real advancements in the discovery of biological motifs, particularly in large data volume scenarios, offering a relevant alternative for the analysis of ChIP-seq data and have the potential to boost future research in the field. This software can be found at the following address: (https://github.com/jadermcg/biomapp-chip).

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BACKGROUND: Lung cancer is the leading cause of cancer death worldwide. It has been reported that genetic and epigenetic factors play a crucial role in the onset and evolution of lung cancer. Previous reports have shown that essential transcription factors in embryonic development contribute to this pathology. Runt-related transcription factor (RUNX) proteins belong to a family of master regulators of embryonic developmental programs. Specifically, RUNX2 is the master transcription factor (TF) of osteoblastic differentiation, and it can be involved in pathological conditions such as prostate, thyroid, and lung cancer by regulating apoptosis and mesenchymal-epithelial transition processes. In this paper, we identified TALAM1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) as a genetic target of the RUNX2 TF in lung cancer and then performed functional validation of the main findings. METHODS: We performed ChIP-seq analysis of tumor samples from a patient diagnosed with lung adenocarcinoma to evaluate the target genes of the RUNX2 TF. In addition, we performed shRNA-mediated knockdown of RUNX2 in this lung adenocarcinoma cell line to confirm the regulatory role of RUNX2 in TALAM1 expression. RESULTS: We observed RUNX2 overexpression in cell lines and primary cultured lung cancer cells. Interestingly, we found that lncRNA TALAM1 was a target of RUNX2 and that RUNX2 exerted a negative regulatory effect on TALAM1 transcription.

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Hexamerins, the proteins massively stored in the larval haemolymph of insects, are gradually used throughout metamorphosis as a source of raw material and energy for the development of adult tissues. Such behaviour defined hexamerins as storage proteins. Immunofluorescence experiments coupled with confocal microscopy show a hexamerin, HEX 70a, in the nucleus of the brain and fat body cells from honeybee workers, an unexpected localization for a storage protein. HEX 70a colocalizes with fibrillarin, a nucleolar-specific protein and H3 histone, thus suggesting a potential role as a chromatin-binding protein. This was investigated through chromatin immunoprecipitation and high-throughput DNA sequencing (ChIP-seq). The significant HEX 70a-DNA binding sites were mainly localized at the intergenic, promoter and intronic regions. HEX 70a targeted DNA stretches mapped to the genomic regions encompassing genes with relevant functional attributes. Several HEX 70a targeted genes were associated with H3K27ac or/and H3K27me3, known as active and repressive histone marks. Brain and fat body tissues shared a fraction of the HEX 70 targeted genes, and tissue-specific targets were also detected. The presence of overrepresented DNA motifs in the binding sites is consistent with specific HEX 70a-chromatin association. In addition, a search for HEX 70a targets in RNA-seq public libraries of fat bodies from nurses and foragers revealed differentially expressed targets displaying hex 70a-correlated developmental expression, thus supporting a regulatory activity for HEX 70a. Our results support the premise that HEX 70a is a moonlighting protein that binds chromatin and has roles in the brain and fat body cell nuclei, apart from its canonical role as a storage protein.

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Aims: To evaluate H3K9 acetylation and gene expression profiles in three brain regions of Alzheimer's disease (AD) patients and elderly controls, and to identify AD region-specific abnormalities. Methods: Brain samples of auditory cortex, hippocampus and cerebellum from AD patients and controls underwent chromatin immunoprecipitation sequencing, RNA sequencing and network analyses. Results: We found a hyperacetylation of AD cerebellum and a slight hypoacetylation of AD hippocampus. The transcriptome revealed differentially expressed genes in the hippocampus and auditory cortex. Network analysis revealed Rho GTPase-mediated mechanisms. Conclusions: These findings suggest that some crucial mechanisms, such as Rho GTPase activity and cytoskeletal organization, are differentially dysregulated in brain regions of AD patients at the epigenetic and transcriptomic levels, and might contribute toward future research on AD pathogenesis.

Alzheimer's disease (AD) is the most common form of dementia affecting the elderly population. The onset and progression of AD are influenced by environmental factors, which are able to promote epigenetic changes on the DNA and/or the DNA-associated proteins called histones. We investigated a specific epigenetic modification of histones (H3K9 acetylation) in three brain regions of AD patients and compared them with elderly controls. We found increased levels of H3K9 acetylation in the cerebellum of AD patients, as well as a slight decrease of this modification in the hippocampus of the same patients. These brain tissues from AD patients showed abnormal gene expression patterns when compared with elderly controls. These findings contribute to understanding the molecular changes that occur in AD, and provide a basis for future research or drug development for AD treatment.

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Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in Escherichia coli K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium E. coli K-12.

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Estrogen (E2) and Progesterone (Pg), via their specific receptors (ERalpha and PR), are major determinants in the development and progression of endometrial carcinomas, However, their precise mechanism of action and the role of other transcription factors involved are not entirely clear. Using Ishikawa endometrial cancer cells, we report that E2 treatment exposes a set of progestin-dependent PR binding sites which include both E2 and progestin target genes. ChIP-seq results from hormone-treated cells revealed a non-random distribution of PAX2 binding in the vicinity of these estrogen-promoted PR sites. Altered expression of hormone regulated genes in PAX2 knockdown cells suggests a role for PAX2 in fine-tuning ERalpha and PR interplay in transcriptional regulation. Analysis of long-range interactions by Hi-C coupled with ATAC-seq data showed that these regions, that we call 'progestin control regions' (PgCRs), exhibited an open chromatin state even before hormone exposure and were non-randomly associated with regulated genes. Nearly 20% of genes potentially influenced by PgCRs were found to be altered during progression of endometrial cancer. Our findings suggest that endometrial response to progestins in differentiated endometrial tumor cells results in part from binding of PR together with PAX2 to accessible chromatin regions. What maintains these regions open remains to be studied.

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BACKGROUND: Inhaled corticosteroid (ICS) response among patients with asthma is influenced by genetics, but biologically actionable insights based on associations have not been found. Various glucocorticoid response omics data sets are available to interrogate their biological effects. OBJECTIVE: We sought to identify functionally relevant ICS-response genetic associations by integrating complementary multiomics data sets. METHODS: Variants with P values less than 10-4 from a previous ICS-response genome-wide association study were reranked on the basis of integrative scores determined from (1) glucocorticoid receptor- and (2) RNA polymerase II-binding regions inferred from ChIP-Seq data for 3 airway cell types, (3) glucocorticoid response element motifs, (4) differentially expressed genes in response to glucocorticoid exposure according to 20 transcriptomic data sets, and (5) expression quantitative trait loci from GTEx. Candidate variants were tested for association with ICS response and asthma in 6 independent studies. RESULTS: Four variants had significant (q value < 0.05) multiomics integrative scores. These variants were in a locus consisting of 52 variants in high linkage disequilibrium (r2 ≥ 0.8) near glucocorticoid receptor-binding sites by the gene BIRC3. Variants were also BIRC3 expression quantitative trait loci in lung, and 2 were within/near putative glucocorticoid response element motifs. BIRC3 had increased RNA polymerase II occupancy and gene expression, with glucocorticoid exposure in 2 ChIP-Seq and 13 transcriptomic data sets. Some BIRC3 variants in the 52-variant locus were associated (P < .05) with ICS response in 3 independent studies and others with asthma in 1 study. CONCLUSIONS: BIRC3 should be prioritized for further functional studies of ICS response.

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The SALL2 transcription factor, an evolutionarily conserved gene through vertebrates, is involved in normal development and neuronal differentiation. In disease, SALL2 is associated with eye, kidney, and brain disorders, but mainly is related to cancer. Some studies support a tumor suppressor role and others an oncogenic role for SALL2, which seems to depend on the cancer type. An additional consideration is tissue-dependent expression of different SALL2 isoforms. Human and mouse SALL2 gene loci contain two promoters, each controlling the expression of a different protein isoform (E1 and E1A). Also, several improvements on the human genome assembly and gene annotation through next-generation sequencing technologies reveal correction and annotation of additional isoforms, obscuring dissection of SALL2 isoform-specific transcriptional targets and functions. We here integrated current data of normal/tumor gene expression databases along with ChIP-seq binding profiles to analyze SALL2 isoforms expression distribution and infer isoform-specific SALL2 targets. We found that the canonical SALL2 E1 isoform is one of the lowest expressed, while the E1A isoform is highly predominant across cell types. To dissect SALL2 isoform-specific targets, we analyzed publicly available ChIP-seq data from Glioblastoma tumor-propagating cells and in-house ChIP-seq datasets performed in SALL2 wild-type and E1A isoform knockout HEK293 cells. Another available ChIP-seq data in HEK293 cells (ENCODE Consortium Phase III) overexpressing a non-canonical SALL2 isoform (short_E1A) was also analyzed. Regardless of cell type, our analysis indicates that the SALL2 long E1 and E1A isoforms, but not short_E1A, are mostly contributing to transcriptional control, and reveals a highly conserved network of brain-specific transcription factors (i.e., SALL3, POU3F2, and NPAS3). Our data integration identified a conserved molecular network in which SALL2 regulates genes associated with neural function, cell differentiation, development, and cell adhesion between others. Also, we identified PODXL as a gene that is likely regulated by SALL2 across tissues. Our study encourages the validation of publicly available ChIP-seq datasets to assess a specific gene/isoform's transcriptional targets. The knowledge of SALL2 isoforms expression and function in different tissue contexts is relevant to understanding its role in disease.

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Membranous nephropathy (MN), characterized by the presence of diffuse thickening of the glomerular basement membrane and subepithelial in situ immune complex disposition, is the most common cause of idiopathic nephrotic syndrome in adults, with an incidence of 5-10 per million per year. A number of studies have confirmed the relevance of several experimental insights to the pathogenesis of human MN, but the specific biomarkers of MN have not been fully elucidated. As a result, our knowledge of the alterations in histone methylation in MN is unclear. We used chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) to analyze the variations in a methylated histone (H3K9me3) in peripheral blood mononuclear cells from 10 MN patients and 10 healthy subjects. There were 108 genes with significantly different expression in the MN patients compared with the normal controls. In MN patients, significantly increased activity was seen in 75 H3K9me3 genes, and decreased activity was seen in 33, compared with healthy subjects. Five positive genes, DiGeorge syndrome critical region gene 6 (DGCR6), sorting nexin 16 (SNX16), contactin 4 (CNTN4), baculoviral IAP repeat containing 3 (BIRC3), and baculoviral IAP repeat containing 2 (BIRC2), were selected and quantified. There were alterations of H3K9me3 in MN patients. These may be candidates to help explain pathogenesis in MN patients. Such novel findings show that H3K9me3 may be a potential biomarker or promising target for epigenetic-based MN therapies.

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Aluminum (Al) toxicity in plants is one of the primary constraints in crop production. Al³âº, the most toxic form of Al, is released into soil under acidic conditions and causes extensive damage to plants, especially in the roots. In rice, Al tolerance requires the ASR5 gene, but the molecular function of ASR5 has remained unknown. Here, we perform genome-wide analyses to identify ASR5-dependent Al-responsive genes in rice. Based on ASR5_RNAi silencing in plants, a global transcriptome analysis identified a total of 961 genes that were responsive to Al treatment in wild-type rice roots. Of these genes, 909 did not respond to Al in the ASR5_RNAi plants, indicating a central role for ASR5 in Al-responsive gene expression. Under normal conditions, without Al treatment, the ASR5_RNAi plants expressed 1.756 genes differentially compared to the wild-type plants, and 446 of these genes responded to Al treatment in the wild-type plants. Chromatin immunoprecipitation followed by deep sequencing identified 104 putative target genes that were directly regulated by ASR5 binding to their promoters, including the STAR1 gene, which encodes an ABC transporter required for Al tolerance. Motif analysis of the binding peak sequences revealed the binding motif for ASR5, which was confirmed via in vitro DNA-binding assays using the STAR1 promoter. These results demonstrate that ASR5 acts as a key transcription factor that is essential for Al-responsive gene expression and Al tolerance in rice.

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