Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses

Decoding the molecular concerto: Toxicotranscriptomic evaluation of microplastic and nanoplastic impacts on aquatic organisms

The pervasive and steadily increasing presence of microplastics/nanoplastics (MPs/NPs) in aquatic environments has raised significant concerns regarding their potential adverse effects on aquatic organisms and their integration into trophic dynamics. This emerging issue has garnered the attention of (eco)toxicologists, promoting the utilization of toxicotranscriptomics to unravel the responses of aquatic organisms not only to MPs/NPs but also to a wide spectrum of environmental pollutants. This review aims to systematically explore the broad repertoire of predicted molecular responses by aquatic organisms, providing valuable intuitions into complex interactions between plastic pollutants and aquatic biota. By synthesizing the latest literature, present analysis sheds light on transcriptomic signatures like gene expression, interconnected pathways and overall molecular mechanisms influenced by various plasticizers. Harmful effects of these contaminants on key genes/protein transcripts associated with crucial pathways lead to abnormal immune response, metabolic response, neural response, apoptosis and DNA damage, growth, development, reproductive abnormalities, detoxification, and oxidative stress in aquatic organisms. However, unique challenge lies in enhancing the fingerprint of MPs/NPs, presenting complicated enigma that requires decoding their specific impact at molecular levels. The exploration endeavors, not only to consolidate existing knowledge, but also to identify critical gaps in understanding, push forward the frontiers of knowledge about transcriptomic signatures of plastic contaminants. Moreover, this appraisal emphasizes the imperative to monitor and mitigate the contamination of commercially important aquatic species by MPs/NPs, highlighting the pivotal role that regulatory frameworks must play in protecting all aquatic ecosystems. This commitment aligns with the broader goal of ensuring the sustainability of aquatic resources and the resilience of ecosystems facing the growing threat of plastic pollutants.

Transforming Big Data into AI-ready data for nutrition and obesity research

OBJECTIVE

Big Data are increasingly used in obesity and nutrition research to gain new insights and derive personalized guidance; however, this data in raw form are often not usable. Substantial preprocessing, which requires machine learning (ML), human judgment, and specialized software, is required to transform Big Data into artificial intelligence (AI)- and ML-ready data. These preprocessing steps are the most complex part of the entire modeling pipeline. Understanding the complexity of these steps by the end user is critical for reducing misunderstanding, faulty interpretation, and erroneous downstream conclusions.

METHODS

We reviewed three popular obesity/nutrition Big Data sources: microbiome, metabolomics, and accelerometry. The preprocessing pipelines, specialized software, challenges, and how decisions impact final AI- and ML-ready products were detailed.

RESULTS

Opportunities for advances to improve quality control, speed of preprocessing, and intelligent end user consumption were presented.

CONCLUSIONS

Big Data have the exciting potential for identifying new modifiable factors that impact obesity research. However, to ensure accurate interpretation of conclusions arising from Big Data, the choices involved in preparing AI- and ML-ready data need to be transparent to investigators and clinicians relying on the conclusions.

CRISPR Activation Reverses Haploinsufficiency and Functional Deficits Caused by TTN Truncation Variants

BACKGROUND

TTN truncation variants (TTNtvs) are the most common genetic lesion identified in individuals with dilated cardiomyopathy, a disease with high morbidity and mortality rates. TTNtvs reduce normal TTN (titin) protein levels, produce truncated proteins, and impair sarcomere content and function. Therapeutics targeting TTNtvs have been elusive because of the immense size of TTN, the rarity of specific TTNtvs, and incomplete knowledge of TTNtv pathogenicity.

METHODS

We adapted CRISPR activation using dCas9-VPR to functionally interrogate TTNtv pathogenicity and develop a therapeutic in human cardiomyocytes and 3-dimensional cardiac microtissues engineered from induced pluripotent stem cell models harboring a dilated cardiomyopathy-associated TTNtv. We performed guide RNA screening with custom TTN reporter assays, agarose gel electrophoresis to quantify TTN protein levels and isoforms, and RNA sequencing to identify molecular consequences of TTN activation. Cardiomyocyte epigenetic assays were also used to nominate DNA regulatory elements to enable cardiomyocyte-specific TTN activation.

RESULTS

CRISPR activation of TTN using single guide RNAs targeting either the TTN promoter or regulatory elements in spatial proximity to the TTN promoter through 3-dimensional chromatin interactions rescued TTN protein deficits disturbed by TTNtvs. Increasing TTN protein levels normalized sarcomere content and contractile function despite increasing truncated TTN protein. In addition to TTN transcripts, CRISPR activation also increased levels of myofibril assembly-related and sarcomere-related transcripts.

CONCLUSIONS

TTN CRISPR activation rescued TTNtv-related functional deficits despite increasing truncated TTN levels, which provides evidence to support haploinsufficiency as a relevant genetic mechanism underlying heterozygous TTNtvs. CRISPR activation could be developed as a therapeutic to treat a large proportion of TTNtvs.

Toxin-based screening of C-terminal tags in Escherichia coli reveals the exceptional potency of ssrA-like degrons

All bacteria possess ATP-dependent proteases that destroy cytosolic proteins. These enzymes help cells mitigate proteotoxic stress, adapt to changing nutrient availability, regulate virulence phenotypes, and transition to pathogenic lifestyles. Moreover, ATP-dependent proteases have emerged as promising antibacterial and antivirulence targets in a variety of pathogens. The physiological roles of these proteases are largely defined by the complement of proteins that they degrade. Substrates are typically recognized in a highly selective manner, often via short unstructured sequences termed degrons. While a few degrons have been identified and rigorously characterized, we lack a systematic understanding of how proteases select valid degrons from the vast complexity of protein sequence space. Here, we describe a novel high-throughput screening approach in Escherichia coli that couples proteolysis of a protein toxin to cell survival. We used this method to screen a combinatorial library of C-terminal pentapeptide sequences for functionality as proteolytic degrons in wild type E. coli, and in strains lacking components of the ClpXP and ClpAP proteases. By examining the competitive enrichment of sequences over time, we found that about one percent of pentapeptide tags lead to toxin proteolysis. Interestingly, the most enriched degrons were ClpXP-dependent and highly similar to the ssrA tag, one of the most extensively characterized degrons in bacteria. Among ssrA-like sequences, we observed that specific upstream residues correlate with successful recognition. The lack of diversity among strongly enriched sequences suggests that ssrA-like tags comprise a uniquely potent class of short C-terminal degron in E. coli. Efficient proteolysis of substrates lacking such degrons likely requires adaptors or multivalent interactions. These findings broaden our understanding of the constraints that shape the bacterial proteolytic landscape. Our screening approach may be broadly applicable to probing aspects of proteolytic substrate selection in other bacterial systems.

3C methods in cancer research: recent advances and future prospects

In recent years, Hi-C technology has revolutionized cancer research by elucidating the mystery of three-dimensional chromatin organization and its role in gene regulation. This paper explored the impact of Hi-C advancements on cancer research by delving into high-resolution techniques, such as chromatin loops, structural variants, haplotype phasing, and extrachromosomal DNA (ecDNA). Distant regulatory elements interact with their target genes through chromatin loops. Structural variants contribute to the development and progression of cancer. Haplotype phasing is crucial for understanding allele-specific genomic rearrangements and somatic clonal evolution in cancer. The role of ecDNA in driving oncogene amplification and drug resistance in cancer cells has also been revealed. These innovations offer a deeper understanding of cancer biology and the potential for personalized therapies. Despite these advancements, challenges, such as the accurate mapping of repetitive sequences and precise identification of structural variants, persist. Integrating Hi-C with multiomics data is key to overcoming these challenges and comprehensively understanding complex cancer genomes. Thus, Hi-C is a powerful tool for guiding precision medicine in cancer research and treatment.

De novo sequencing, assembly, and characterization of Asparagus racemosus transcriptome and analysis of expression profile of genes involved in the flavonoid biosynthesis pathway

Asparagus racemosus is known for its diverse content of secondary metabolites, i.e., saponins, alkaloids, and a wide range of flavonoids. Flavonoids, including phenols and polyphenols, have a significant role in plant physiology and are synthesized in several tissues. Despite the diverse role of flavonoids, genetic information is limited for flavonoid biosynthesis pathways in A. racemosus. The current study explores full-scale functional genomics information of A. racemosus by de novo transcriptome sequencing using Illumina paired-end sequencing technology to elucidate the genes involved in flavonoid biosynthesis pathways. The de novo assembly of high-quality paired-end reads resulted in ∼2.3 million high-quality reads with a pooled transcript of 45,647 comprising ∼76 Mb transcriptome with a mean length (bp) of 1,674 and N50 of 1,868bp. Furthermore, the coding sequence (CDS) prediction analysis from 45,647 pooled transcripts resulted in 45,444 CDS with a total length and mean length of 76,398,686 and 1,674, respectively. The Gene Ontology (GO) analysis resulted in a high number of CDSs assigned to 25,342 GO terms, which grouped the predicted CDS into three main domains, i.e., Biological Process (19,550), Molecular Function (19,873), and Cellular Component (14,577). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was used to categorize 6,353 CDS into 25 distinct biological pathway categories, in which the majority of mapped CDS were shown to be related to translation (645), followed by signal transduction (532), carbohydrate metabolism (524), folding, sorting, and degradation (522). Among these, only ∼64 and 14 CDSs were found to be involved in the phenylpropanoid and flavonoid biosynthesis pathways, respectively. Quantitative Real-time PCR was used to check the expression profile of fourteen potential flavonoid biosynthesis pathway genes. The qRT-PCR analysis result matches the transcriptome sequence data validating the Illumina sequence results. Moreover, a large number of genes associated with the flavonoids biosynthesis pathway were found to be upregulated under the induction of methyl jasmonate. The present-day study on transcriptome sequence data of A. racemosus can be utilized for characterizing genes involved in flavonoid biosynthesis pathways and for functional genomics analysis in A. racemosus using the reverse genetics approach (CRISPR/Cas9 technology).

Recent advances in chromosome capture techniques unraveling 3D genome architecture in germ cells, health, and disease

In eukaryotes, the genome does not emerge in a specific shape but rather as a hierarchial bundle within the nucleus. This multifaceted genome organization consists of multiresolution cellular structures, such as chromosome territories, compartments, and topologically associating domains, which are frequently defined by architecture, design proteins including CTCF and cohesin, and chromatin loops. This review briefly discusses the advances in understanding the basic rules of control, chromatin folding, and functional areas in early embryogenesis. With the use of chromosome capture techniques, the latest advancements in technologies for visualizing chromatin interactions come close to revealing 3D genome formation frameworks with incredible detail throughout all genomic levels, including at single-cell resolution. The possibility of detecting variations in chromatin architecture might open up new opportunities for disease diagnosis and prevention, infertility treatments, therapeutic approaches, desired exploration, and many other application scenarios.

3D genome organization and epigenetic regulation in autoimmune diseases

Three-dimensional (3D) genomics is an emerging field of research that investigates the relationship between gene regulatory function and the spatial structure of chromatin. Chromatin folding can be studied using chromosome conformation capture (3C) technology and 3C-based derivative sequencing technologies, including chromosome conformation capture-on-chip (4C), chromosome conformation capture carbon copy (5C), and high-throughput chromosome conformation capture (Hi-C), which allow scientists to capture 3D conformations from a single site to the entire genome. A comprehensive analysis of the relationships between various regulatory components and gene function also requires the integration of multi-omics data such as genomics, transcriptomics, and epigenomics. 3D genome folding is involved in immune cell differentiation, activation, and dysfunction and participates in a wide range of diseases, including autoimmune diseases. We describe hierarchical 3D chromatin organization in this review and conclude with characteristics of C-techniques and multi-omics applications of the 3D genome. In addition, we describe the relationship between 3D genome structure and the differentiation and maturation of immune cells and address how changes in chromosome folding contribute to autoimmune diseases.

Prediction of CTCF loop anchor based on machine learning

Introduction: Various activities in biological cells are affected by three-dimensional genome structure. The insulators play an important role in the organization of higher-order structure. CTCF is a representative of mammalian insulators, which can produce barriers to prevent the continuous extrusion of chromatin loop. As a multifunctional protein, CTCF has tens of thousands of binding sites in the genome, but only a portion of them can be used as anchors of chromatin loops. It is still unclear how cells select the anchor in the process of chromatin looping.

Methods: In this paper, a comparative analysis is performed to investigate the sequence preference and binding strength of anchor and non-anchor CTCF binding sites. Furthermore, a machine learning model based on the CTCF binding intensity and DNA sequence is proposed to predict which CTCF sites can form chromatin loop anchors.

Results: The accuracy of the machine learning model that we constructed for predicting the anchor of the chromatin loop mediated by CTCF reached 0.8646. And we find that the formation of loop anchor is mainly influenced by the CTCF binding strength and binding pattern (which can be interpreted as the binding of different zinc fingers).

Discussion: In conclusion, our results suggest that The CTCF core motif and it’s flanking sequence may be responsible for the binding specificity. This work contributes to understanding the mechanism of loop anchor selection and provides a reference for the prediction of CTCF-mediated chromatin loops.

Navigating bottlenecks and trade-offs in genomic data analysis

Genome sequencing and analysis allow researchers to decode the functional information hidden in DNA sequences as well as to study cell to cell variation within a cell population. Traditionally, the primary bottleneck in genomic analysis pipelines has been the sequencing itself, which has been much more expensive than the computational analyses that follow. However, an important consequence of the continued drive to expand the throughput of sequencing platforms at lower cost is that often the analytical pipelines are struggling to keep up with the sheer amount of raw data produced. Computational cost and efficiency have thus become of ever increasing importance. Recent methodological advances, such as data sketching, accelerators and domain-specific libraries/languages, promise to address these modern computational challenges. However, despite being more efficient, these innovations come with a new set of trade-offs, both expected, such as accuracy versus memory and expense versus time, and more subtle, including the human expertise needed to use non-standard programming interfaces and set up complex infrastructure. In this Review, we discuss how to navigate these new methodological advances and their trade-offs.

Phase Separation: Direct and Indirect Driving Force for High-Order Chromatin Organization

The multi-level spatial chromatin organization in the nucleus is closely related to chromatin activity. The mechanism of chromatin organization and remodeling attract much attention. Phase separation describes the biomolecular condensation which is the basis for membraneless compartments in cells. Recent research shows that phase separation is a key aspect to drive high-order chromatin structure and remodeling. In addition, chromatin functional compartmentalization in the nucleus which is formed by phase separation also plays an important role in overall chromatin structure. In this review, we summarized the latest work about the role of phase separation in spatial chromatin organization, focusing on direct and indirect effects of phase separation on 3D chromatin organization and its impact on transcription regulation.

Gene Expression Profiles in Cancers and Their Therapeutic Implications

ABSTRACT

The vast amount of gene expression profiling data of bulk tumors and cell lines available in the public domain represents a tremendous resource. For any major cancer type, expression data can identify molecular subtypes, predict patient outcome, identify markers of therapeutic response, determine the functional consequences of somatic mutation, and elucidate the biology of metastatic and advanced cancers. This review provides a broad overview of gene expression profiling in cancer (which may include transcriptome and proteome levels) and the types of findings made using these data. This review also provides specific examples of accessing public cancer gene expression data sets and generating unique views of the data and the resulting genes of interest. These examples involve pan-cancer molecular subtyping, metabolism-associated expression correlates of patient survival involving multiple cancer types, and gene expression correlates of chemotherapy response in breast tumors.

Dynamics of Viral and Host 3D Genome Structure upon Infection

Eukaryotic chromatin is highly organized in the 3D nuclear space and dynamically regulated in response to environmental stimuli. This genomic organization is arranged in a hierarchical fashion to support various cellular functions, including transcriptional regulation of gene expression. Like other host cellular mechanisms, viral pathogens utilize and modulate host chromatin architecture and its regulatory machinery to control features of their life cycle, such as lytic versus latent status. Combined with previous research focusing on individual loci, recent global genomic studies employing conformational assays coupled with high-throughput sequencing technology have informed models for host and, in some cases, viral 3D chromosomal structure re-organization during infection and the contribution of these alterations to virus-mediated diseases. Here, we review recent discoveries and progress in host and viral chromatin structural dynamics during infection, focusing on a subset of DNA (human herpesviruses and HPV) as well as RNA (HIV, influenza virus and SARS-CoV-2) viruses. An understanding of how host and viral genomic structure affect gene expression in both contexts and ultimately viral pathogenesis can facilitate the development of novel therapeutic strategies.

DLoopCaller: A deep learning approach for predicting genome-wide chromatin loops by integrating accessible chromatin landscapes

In recent years, major advances have been made in various chromosome conformation capture technologies to further satisfy the needs of researchers for high-quality, high-resolution contact interactions. Discriminating the loops from genome-wide contact interactions is crucial for dissecting three-dimensional(3D) genome structure and function. Here, we present a deep learning method to predict genome-wide chromatin loops, called DLoopCaller, by combining accessible chromatin landscapes and raw Hi-C contact maps. Some available orthogonal data ChIA-PET/HiChIP and Capture Hi-C were used to generate positive samples with a wider contact matrix which provides the possibility to find more potential genome-wide chromatin loops. The experimental results demonstrate that DLoopCaller effectively improves the accuracy of predicting genome-wide chromatin loops compared to the state-of-the-art method Peakachu. Moreover, compared to two of most popular loop callers, such as HiCCUPS and Fit-Hi-C, DLoopCaller identifies some unique interactions. We conclude that a combination of chromatin landscapes on the one-dimensional genome contributes to understanding the 3D genome organization, and the identified chromatin loops reveal cell-type specificity and transcription factor motif co-enrichment across different cell lines and species.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

OUP accepted manuscript

Super enhancers (SEs) are broad enhancer domains usually containing multiple constituent enhancers that hold elevated activities in gene regulation. Disruption in one or more constituent enhancers causes aberrant SE activities that lead to gene dysregulation in diseases. To quantify SE aberrations, differential analysis is performed to compare SE activities between cell conditions. The state-of-art strategy in estimating differential SEs relies on overall activities and neglect the changes in length and structure of SEs. Here, we propose a novel computational method to identify differential SEs by weighting the combinatorial effects of constituent-enhancer activities and locations (i.e. internal dynamics). In addition to overall activity changes, our method identified four novel classes of differential SEs with distinct enhancer structural alterations. We demonstrate that these structure alterations hold distinct regulatory impact, such as regulating different number of genes and modulating gene expression with different strengths, highlighting the differentiated regulatory roles of these unexplored SE features. When compared to the existing method, our method showed improved identification of differential SEs that were linked to better discernment of cell-type-specific SE activity and functional interpretation.

Comprehensive Insights Into Forensic Features and Genetic Background of Chinese Northwest Hui Group Using Six Distinct Categories of 231 Molecular Markers

The Hui minority is predominantly composed of Chinese-speaking Islamic adherents distributed throughout China, of which the individuals are mainly concentrated in Northwest China. In the present study, we employed the length and sequence polymorphisms-based typing system of 231 molecular markers, i.e., amelogenin, 22 phenotypic-informative single nucleotide polymorphisms (PISNPs), 94 identity-informative single nucleotide polymorphisms (IISNPs), 24 Y-chromosomal short tandem repeats (Y-STRs), 56 ancestry-informative single nucleotide polymorphisms (AISNPs), 7 X-chromosomal short tandem repeats (X-STRs), and 27 autosomal short tandem repeats (A-STRs), into 90 unrelated male individuals from the Chinese Northwest Hui group to comprehensively explore its forensic characteristics and genetic background. Total of 451 length-based and 652 sequence-based distinct alleles were identified from 58 short tandem repeats (STRs) in 90 unrelated Northwest Hui individuals, denoting that the sequence-based genetic markers could pronouncedly provide more genetic information than length-based markers. The forensic characteristics and efficiencies of STRs and IISNPs were estimated, both of which externalized high polymorphisms in the Northwest Hui group and could be further utilized in forensic investigations. No significant departure from the Hardy-Weinberg equilibrium (HWE) expectation was observed after the Bonferroni correction. Additionally, four group sets of reference population data were exploited to dissect the genetic background of the Northwest Hui group separately from different perspectives, which contained 26 populations for 93 IISNPs, 58 populations for 17 Y-STRs, 26 populations for 55 AISNPs (raw data), and 109 populations for 55 AISNPs (allele frequencies). As a result, the analyses based on the Y-STRs indicated that the Northwest Hui group primarily exhibited intimate genetic relationships with reference Hui groups from Chinese different regions except for the Sichuan Hui group and secondarily displayed close genetic relationships with populations from Central and West Asia, as well as several Chinese groups. However, the AISNP analyses demonstrated that the Northwest Hui group shared more intimate relationships with current East Asian populations apart from reference Hui group, harboring the large proportion of ancestral component contributed by East Asia.

Understanding 3D genome organization by multidisciplinary methods

Understanding how chromatin is folded in the nucleus is fundamental to understanding its function. Although 3D genome organization has been historically difficult to study owing to a lack of relevant methodologies, major technological breakthroughs in genome-wide mapping of chromatin contacts and advances in imaging technologies in the twenty-first century considerably improved our understanding of chromosome conformation and nuclear architecture. In this Review, we discuss methods of 3D genome organization analysis, including sequencing-based techniques, such as Hi-C and its derivatives, Micro-C, DamID and others; microscopy-based techniques, such as super-resolution imaging coupled with fluorescence in situ hybridization (FISH), multiplex FISH, in situ genome sequencing and live microscopy methods; and computational and modelling approaches. We describe the most commonly used techniques and their contribution to our current knowledge of nuclear architecture and, finally, we provide a perspective on up-and-coming methods that open possibilities for future major discoveries.

Systematic refinement of gene annotations by parsing mRNA 3' end sequencing datasets

Alternative cleavage and polyadenylation generates mRNA 3' isoforms in a cell type-specific manner. Due to finite available RNA sequencing data of organisms with vast cell type complexity, currently available gene annotation resources are incomplete, which poses significant challenges to the comprehensive interpretation and quantification of transcriptomes. In this chapter, we introduce 3'GAmES, a stand-alone computational pipeline for the identification and quantification of novel mRNA 3'end isoforms from 3'mRNA sequencing data. 3'GAmES expands available repositories and improves comprehensive gene-tag counting by cost-effective 3' mRNA sequencing, faithfully mirroring whole-transcriptome RNAseq measurements. By employing R and bash shell scripts (assembled in a Singularity container) 3'GAmES systematically augments cell type-specific 3' ends of RNA polymerase II transcripts and increases the sensitivity of quantitative gene expression profiling by 3' mRNA sequencing. Public access: https://github.com/AmeresLab/3-GAmES.git.

MicroRNAs: Potential Targets for Developing Stress-Tolerant Crops

Crop yield is challenged every year worldwide by changing climatic conditions. The forecasted climatic scenario urgently demands stress-tolerant crop varieties to feed the ever-increasing global population. Molecular breeding and genetic engineering approaches have been frequently exploited for developing crops with desired agronomic traits. Recently, microRNAs (miRNAs) have emerged as powerful molecules, which potentially serve as expression markers during stress conditions. The miRNAs are small non-coding endogenous RNAs, usually 20-24 nucleotides long, which mediate post-transcriptional gene silencing and fine-tune the regulation of many abiotic- and biotic-stress responsive genes in plants. The miRNAs usually function by specifically pairing with the target mRNAs, inducing their cleavage or repressing their translation. This review focuses on the exploration of the functional role of miRNAs in regulating plant responses to abiotic and biotic stresses. Moreover, a methodology is also discussed to mine stress-responsive miRNAs from the enormous amount of transcriptome data available in the public domain generated using next-generation sequencing (NGS). Considering the functional role of miRNAs in mediating stress responses, these molecules may be explored as novel targets for engineering stress-tolerant crop varieties.

Loop competition and extrusion model predicts CTCF interaction specificity

Three-dimensional chromatin looping interactions play an important role in constraining enhancer–promoter interactions and mediating transcriptional gene regulation. CTCF is thought to play a critical role in the formation of these loops, but the specificity of which CTCF binding events form loops and which do not is difficult to predict. Loops often have convergent CTCF binding site motif orientation, but this constraint alone is only weakly predictive of genome-wide interaction data. Here we present an easily interpretable and simple mathematical model of CTCF mediated loop formation which is consistent with Cohesin extrusion and can predict ChIA-PET CTCF looping interaction measurements with high accuracy. Competition between overlapping loops is a critical determinant of loop specificity. We show that this model is consistent with observed chromatin interaction frequency changes induced by CTCF binding site deletion, inversion, and mutation, and is also consistent with observed constraints on validated enhancer–promoter interactions.

Boundaries of topologically associated domains in genomes are marked by CTCF and cohesin binding. Here the authors predict CTCF interaction specificity by building a simple mathematical model with features including loop competition and extrusion.

VARAdb: a comprehensive variation annotation database for human

With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-coding variants. Here, we developed a comprehensive variation annotation database for human (VARAdb, http://www.licpathway.net/VARAdb/), which specifically considers non-coding variants. VARAdb provides annotation information for 577,283,813 variations and novel variants, prioritizes variations based on scores using nine annotation categories, and supports pathway downstream analysis. Importantly, VARAdb integrates a large amount of genetic and epigenomic data into five annotation sections, which include ‘Variation information’, ‘Regulatory information’, ‘Related genes’, ‘Chromatin accessibility’ and ‘Chromatin interaction’. The detailed annotation information consists of motif changes, risk SNPs, LD SNPs, eQTLs, clinical variant-drug-gene pairs, sequence conservation, somatic mutations, enhancers, super enhancers, promoters, transcription factors, chromatin states, histone modifications, chromatin accessibility regions and chromatin interactions. This database is a user-friendly interface to query, browse and visualize variations and related annotation information. VARAdb is a useful resource for selecting potential functional variations and interpreting their effects on human diseases and biological processes.

Using Open Chromatin Enrichment and Network Hi-C (OCEAN-C) to Identify Open Chromatin Interactions

The open chromatin enrichment and network Hi-C (OCEAN-C) was developed not only for identifying large-scale chromatin structures, including topologically associated domains (TADs) and A/B compartments, but also for globally mapping hubs of open chromatin interactions (HOCIs) and their interaction networks independent of antibody and bait-sequences.

Alternative Polyadenylation: a new frontier in post transcriptional regulation

Polyadenylation of pre-messenger RNA (pre-mRNA) specific sites and termination of their downstream transcriptions are signaled by unique sequence motif structures such as AAUAAA and its auxiliary elements. Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism that processes RNA products depending on its 3'-untranslated region (3'-UTR) specific sequence signal. APA processing can generate several mRNA isoforms from a single gene, which may have different biological functions on their target gene. As a result, cellular genomic stability, proliferation capability, and transformation feasibility could all be affected. Furthermore, APA modulation regulates disease initiation and progression. APA status could potentially act as a biomarker for disease diagnosis, severity stratification, and prognosis forecast. While the advance of modern throughout technologies, such as next generation-sequencing (NGS) and single-cell sequencing techniques, have enriched our knowledge about APA, much of APA biological process is unknown and pending for further investigation. Herein, we review the current knowledge on APA and how its regulatory complex factors (CFI/IIm, CPSF, CSTF, and RBPs) work together to determine RNA splicing location, cell cycle velocity, microRNA processing, and oncogenesis regulation. We also discuss various APA experiment strategies and the future direction of APA research.

High-Quality Draft Genome Sequence Resources of Eight Xylella fastidiosa Strains Isolated from Citrus, Coffee, Plum, and Hibiscus in South America

Xylella fastidiosa subsp. pauca, once confined to South America and infecting mainly citrus and coffee plants, has been found to be associated with other hosts and in other geographic regions. We present high-quality draft genome sequences of X. fastidiosa subsp. pauca strains J1a12, B111, U24D, and XRB isolated from citrus plants in Brazil, strain Fb7 isolated from a citrus plant in Argentina and strains 3124, Pr8x, and Hib4 isolated, respectively, from coffee, plum, and hibiscus plants in Brazil. Sequencing was performed using Roche 454-GS FLX, MiSeq-Illumina or Pacific Biosciences platforms. These high-quality genome assemblies will be useful for further studies about the genomic diversity, evolution, and biology of X. fastidiosa.

Functional impacts of non-coding RNA processing on enhancer activity and target gene expression

Tight regulation of gene expression is orchestrated by enhancers. Through recent research advancements, it is becoming clear that enhancers are not solely distal regulatory elements harboring transcription factor binding sites and decorated with specific histone marks, but they rather display signatures of active transcription, showing distinct degrees of transcription unit organization. Thereby, a substantial fraction of enhancers give rise to different species of non-coding RNA transcripts with an unprecedented range of potential functions. In this review, we bring together data from recent studies indicating that non-coding RNA transcription from active enhancers, as well as enhancer-produced long non-coding RNA transcripts, may modulate or define the functional regulatory potential of the cognate enhancer. In addition, we summarize supporting evidence that RNA processing of the enhancer-associated long non-coding RNA transcripts may constitute an additional layer of regulation of enhancer activity, which contributes to the control and final outcome of enhancer-targeted gene expression.

Free energy-based model of CTCF-mediated chromatin looping in the human genome

In recent years, high-throughput techniques have revealed considerable structural organization of the human genome with diverse regions of the chromatin interacting with each other in the form of loops. Some of these loops are quite complex and may encompass regions comprised of many interacting chain segments around a central locus. Popular techniques for extracting this information are chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture (Hi-C). Here, we introduce a physics-based method to predict the three-dimensional structure of chromatin from population-averaged ChIA-PET data. The approach uses experimentally-validated data from human B-lymphoblastoid cells to generate 2D meta-structures of chromatin using a dynamic programming algorithm that explores the chromatin free energy landscape. By generating both optimal and suboptimal meta-structures we can calculate both the free energy and additionally the relative thermodynamic probability. A 3D structure prediction program with applied restraints then can be used to generate the tertiary structures. The main advantage of this approach for population-averaged experimental data is that it provides a way to distinguish between the principal and the spurious contacts. This study also finds that euchromatin appear to have rather precisely regulated 2D meta-structures compared to heterochromatin. The program source-code is available at https://github.com/plewczynski/looper.

HiCoP, a simple and robust method for detecting interactions of regulatory regions

Background

Chromatin physical interactions provide essential information for understanding the regulation of cis-elements like enhancers, promoters, and insulators in cell development and differentiation. The Hi-C assay is a technique detecting chromatin structures of the whole genome, but not sensitive to interactions of regulatory elements. Several methods, like HiChIP, DNase-C, and OCEAN-C, have been developed for enriching interactions of regulatory regions, but all of them have some shortcomings. New simple, efficient, and robust methods are still in need for detecting interactions of regulatory regions.

Results

We developed a new, simple, and robust assay called CoP (Column Purified chromatin) for profiling of open chromatin regions by directly purifying fragmentized crosslinked chromatin with a DNA purification column. The accessible chromatin regions, including active enhancers, promoters, and insulators, were significantly enriched in CoP chromatin. The CoP-seq assay can efficiently detect open chromatin regions, especially active promoters, with a high signal-to-noise ratio. We integrated the CoP-seq and Hi-C technique (HiCoP) to detect interactions of accessible chromatin regions, which represent active cis-regulatory elements in cells. We observed that the HiCoP captured the peaks in the promoters-associated enhancer regions. HiCoP detected more promoter–enhancer (P–E), promoter–promoter (P–P), and enhancer–enhancer (E–E) interactions within 20 kb–5 Mb than Hi-C. Most of the loops identified by HiCoP are associated with the expressed genes.

Conclusion

CoP assay can efficiently enrich open chromatin regions. When CoP assay was integrated with Hi-C assay, it provides a simple, robust, alternative technique for profiling accessible chromatin regions and chromatin conformation simultaneously.

MACPET: model-based analysis for ChIA-PET

We present model-based analysis for ChIA-PET (MACPET), which analyzes paired-end read sequences provided by ChIA-PET for finding binding sites of a protein of interest. MACPET uses information from both tags of each PET and searches for binding sites in a two-dimensional space, while taking into account different noise levels in different genomic regions. MACPET shows favorable results compared with MACS in terms of motif occurrence and spatial resolution. Furthermore, significant binding sites discovered by MACPET are involved in a higher number of significant three-dimensional interactions than those discovered by MACS. MACPET is freely available on Bioconductor. ChIA-PET; MACPET; Model-based clustering; Paired-end tags; Peak-calling algorithm.

OncoBase: a platform for decoding regulatory somatic mutations in human cancers

Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.

Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning

The developmental potential of cells, termed pluripotency, is highly dynamic and progresses through a continuum of naive, formative and primed states. Pluripotency progression of mouse embryonic stem cells (ESCs) from naive to formative and primed state is governed by transcription factors (TFs) and their target genes. Genomic techniques have uncovered a multitude of TF binding sites in ESCs, yet a major challenge lies in identifying target genes from functional binding sites and reconstructing dynamic transcriptional networks underlying pluripotency progression. Here, we integrated time-resolved ‘trans-omic’ datasets together with TF binding profiles and chromatin conformation data to identify target genes of a panel of TFs. Our analyses revealed that naive TF target genes are more likely to be TFs themselves than those of formative TFs, suggesting denser hierarchies among naive TFs. We also discovered that formative TF target genes are marked by permissive epigenomic signatures in the naive state, indicating that they are poised for expression prior to the initiation of pluripotency transition to the formative state. Finally, our reconstructed transcriptional networks pinpointed the precise timing from naive to formative pluripotency progression and enabled the spatiotemporal mapping of differentiating ESCs to their in vivo counterparts in developing embryos.

Enhancer Dysfunction in 3D Genome and Disease

Spatiotemporal patterns of gene expression depend on enhancer elements and other factors during individual development and disease progression. The rapid progress of high-throughput techniques has led to well-defined enhancer chromatin properties. Various genome-wide methods have revealed a large number of enhancers and the discovery of three-dimensional (3D) genome architecture showing the distant interacting mechanisms of enhancers that loop to target gene promoters. Whole genome sequencing projects directed at cancer have led to the discovery of substantial enhancer dysfunction in misregulating gene expression and in tumor initiation and progression. Results from genome-wide association studies (GWAS) combined with functional genomics analyses have elucidated the functional impacts of many cancer risk-associated variants that are enriched within the enhancer regions of chromatin. Risk variants dysregulate the expression of enhancer variant-associated genes via 3D genomic interactions. Moreover, these enhancer variants often alter the chromatin binding affinity for cancer-relevant transcription factors, which in turn leads to aberrant expression of the genes associated with cancer susceptibility. In this review, we investigate the extent to which these genetic regulatory circuits affect cancer predisposition and how the recent development of genome-editing methods have enabled the determination of the impacts of genomic variation and alteration on cancer phenotype, which will eventually lead to better management plans and treatment responses to human cancer in the clinic.

A novel high-density grapevine (Vitis vinifera L.) integrated linkage map using GBS in a half-diallel population

A half-diallel population involving five elite grapevine cultivars was generated and genotyped by GBS, and highly-informative segregation data was used to construct a high-density genetic map for Vitis vinifera L. Grapevine is one of the most relevant fruit crops in the world. Deeper genetic knowledge could assist modern grapevine breeding programs to develop new wine grape varieties able to face climate change effects. To assist in the rapid identification of markers for crop yield components, grape quality traits and adaptation potential, we generated a large Vitis vinifera L. population (N = 624) by crossing five red wine cultivars in a half-diallel scheme, which was subsequently sequenced by an efficient GBS procedure. A high number of fully informative genetic variants was detected using a novel mapping approach capable of reconstructing local haplotypes from adjacent biallelic SNPs, which were subsequently used to construct the densest consensus genetic map available for the cultivated grapevine to date. This 1378.3-cM map integrates 10 bi-parental consensus maps and orders 4437 markers in 3353 unique positions on 19 chromosomes. Markers are well distributed all along the grapevine reference genome, covering up to 98.8% of its genomic sequence. Additionally, a good agreement was observed between genetic and physical orders, adding confidence in the quality of this map. Collectively, our results pave the way for future genetic studies (such as fine QTL mapping) aimed to understand the complex relationship between genotypic and phenotypic variation in the cultivated grapevine. In addition, the method used (which efficiently delivers a high number of fully informative markers) could be of interest to other outbred organisms, notably perennial fruit crops.

Long Noncoding RNA Discovery in Cardiovascular Disease: Decoding Form to Function

Despite significant improvements during the past 3 decades, cardiovascular disease remains a leading worldwide health epidemic. The recent identification of a fascinating group of mediators known as long noncoding RNAs (lncRNAs) has provided a wealth of new biology to explore for cardiovascular risk mitigation. lncRNAs are expressed in a highly context-specific fashion, and multiple lines of evidence implicated them in diverse biological processes. Indeed, abnormalities of lncRNAs have been directly linked with human ailments, including cardiovascular biology and disease. Of particular interest to the cardiovascular research community, dysregulation in lncRNA regulatory circuits have been associated with cardiac pathological hypertrophy, vascular disease, cell fate programming and development, atherosclerosis, dyslipidemia, and metabolic syndrome. Although techniques in interrogating noncoding RNAs are rapidly evolving, a major challenge in studying lncRNAs remains navigating through multiple technical constraints. In this review, we provide a road map for lncRNA discovery and interrogation in biological systems relevant to cardiovascular disease and highlight approaches to decipher their modes of action.

p63 cooperates with CTCF to modulate chromatin architecture in skin keratinocytes

The transcription factor p63 regulates epidermal genes and the enhancer landscape in skin keratinocytes. Its molecular function in controlling the chromatin structure is, however, not yet completely understood. Here, we integrated multi-omics profiles, including the transcriptome, transcription factor DNA-binding and chromatin accessibility, in skin keratinocytes isolated from EEC syndrome patients carrying p63 mutations, to examine the role of p63 in shaping the chromatin architecture. We found decreased chromatin accessibility in p63- and CTCF-bound open chromatin regions that potentially contributed to gene deregulation in mutant keratinocytes. Cooperation of p63 and CTCF seemed to assist chromatin interactions between p63-bound enhancers and gene promoters in skin keratinocytes. Our study suggests an intriguing model where cell type-specific transcription factors such as p63 cooperate with the genome organizer CTCF in the three-dimensional chromatin space to regulate the transcription program important for the proper cell identity.

ytiB and ythA Genes Reduce the Uranium Removal Capacity of Bacillus atrophaeus

Two Bacillus atrophaeus strains, the first being a highly stress-resistant ATCC 9372 strain and the Ua strain identified from a chromium mine by our lab, differ in their abilities to tolerate and remove Uranium (VI) from contaminated water. An increase in U(VI) concentration in growth media led to a decrease in the tolerance and bio-remedial capacity of both strains. However, under high concentrations of U(VI) in the growth media, the ATCC 9372 strain demonstrated a higher tolerance and a higher removal capacity than the Ua strain. Two approaches, transcriptome sequencing and transgenic technology, were used to elucidate the relationship between particular genes within these two strains and their U(VI) removal capacity. Sequencing confirmed the expression of two genes unique to the Ua strain, previously designated ytiB and ythA. They encode putative proteins that show the highest levels of identity to carbonic anhydrase and cytochrome bd terminal oxidase I, respectively. Using the pBE-S DNA vector, ytiB and ythA were transformed into the ATCC 9372 strain of Bacillus atrophaeus. Under a U(VI) concentration of 120 mg/L, the removal rates of the transgenic ATCC 9372-ytiB and ATCC 9372-ythA strains decreased by 7.55% and 7.43%, respectively, compared to the removal rate of the control strain transformed with empty plasmid. The results suggest that both ythA and ytiB genes have a negative influence on the uranium removing capacity of Bacillus atrophaeus. This finding will help to elucidate the molecular mechanisms of uranium removal by bacteria.

Chromatin-Associated RNA Sequencing (ChAR-seq)

RNA is a fundamental component of chromatin. Noncoding RNAs (ncRNAs) can associate with chromatin to influence gene expression and chromatin state; many also act at long distances from their transcriptional origin. Yet we know almost nothing about the functions or sites of action for most ncRNAs. Current methods to identify sites of RNA interaction with the genome are limited to the study of a single RNA at a time. Here we describe a protocol for ChAR-seq, a strategy to identify all chromatin-associated RNAs and map their DNA contacts genome-wide. In ChAR-seq, proximity ligation of RNA and DNA to a linker molecule is used to construct a chimeric RNA-DNA molecule that is converted to DNA for sequencing. In a single assay, ChAR-seq can discover de novo chromatin interactions of distinct RNAs, including nascent transcripts, splicing RNAs, and long noncoding RNAs (lncRNAs). Resulting "maps" of genome-bound RNAs should provide new insights into RNA biology. © 2019 by John Wiley & Sons, Inc.

RNA-Seq provides new insights on the relative mRNA abundance of antioxidant components during mouse liver development

Mammals have developed a variety of antioxidant systems to protect them from the oxygen environment and toxic stimuli. Little is known about the mRNA abundance of antioxidant components during postnatal development of the liver. Therefore, the purpose of this study was to compare the mRNA abundance of antioxidant components during liver development. Livers from male C57BL/6J mice were collected at 12 ages from prenatal to adulthood. The transcriptome was determined by RNA-Seq with transcript abundance estimated by Cufflinks. RNA-Seq provided a complete, more accurate, and unbiased quantification of the transcriptome. Among 33 known antioxidant components examined, three ontogeny patterns of liver antioxidant components were observed: (1) Prenatal-enriched, in which the mRNAs decreased from fetal livers to adulthood, such as metallothionein and heme oxygenase-1; (2) adolescent-rich and relatively stable expression, such as peroxiredoxins; and (3) adult-rich, in which the mRNA increased with age, such as catalase and superoxide dismutase. Alternative splicing of several antioxidant genes, such as Keap1, Glrx2, Gpx3, and Txnrd1, were also detected by RNA-Seq. In summary, RNA-Seq revealed the relative abundance of hepatic antioxidant enzymes, which are important in protecting against the deleterious effects of oxidative stress.

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

DNA size in confined environments

For short DNA molecules in crowded environments, we evaluate macroscopic parameters such as the average end-to-end distance and the twist conformation by tuning the strength of the site specific confinement driven by the crowders.

A Next-Generation Sequencing-Based Platform for Quantitative Detection of Hepatitis B Virus Pre-S Mutants in Plasma of Hepatocellular Carcinoma Patients

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Early diagnosis and treatment of HCC remain a key goal for improving patient survival. Chronic hepatitis B virus (HBV) infection is a major risk factor for HCC development. Pre-S mutants harboring deletions in HBV large surface antigen have been well demonstrated as HBV oncoproteins that dysregulate multiple signaling pathways in hepatocytes, leading to HCC formation. The presence of pre-S mutants in plasma represents important predictive and prognostic markers for HCC in patients with chronic HBV infection. However, the method to detect pre-S mutants remains to be optimized. In this study, we developed a platform, based on the next-generation sequencing (NGS) technology, for detection of pre-S mutants in plasma of HBV-related HCC patients. Compared to the current TA cloning-based analysis, the NGS-based analysis could detect pre-S deletion quantitatively, and the detection rate was significantly more sensitive in 49 plasma analyzed (McNemar's paired proportion test, P value < 0.0001; simple kappa coefficient, κ = 0.29 (95% CI, 0.12 to 0.46)). Our data suggest that the NGS-based platform may hold a promise for improving the clinical application of pre-S mutants in serving as predictive and prognostic markers for HBV-related HCC.

OCEAN-C: mapping hubs of open chromatin interactions across the genome reveals gene regulatory networks

We develop a method called open chromatin enrichment and network Hi-C (OCEAN-C) for antibody-independent mapping of global open chromatin interactions. By integrating FAIRE-seq and Hi-C, OCEAN-C detects open chromatin interactions enriched by active cis-regulatory elements. We identify more than 10,000 hubs of open chromatin interactions (HOCIs) in human cells, which are mainly active promoters and enhancers bound by many DNA-binding proteins and form interaction networks crucial for gene transcription. In addition to identifying large-scale topological structures, including topologically associated domains and A/B compartments, OCEAN-C can detect HOCI-mediated chromatin interactions that are strongly associated with gene expression, super-enhancers, and broad H3K4me3 domains.

Involvement of an ABI-like protein and a Ca2+-ATPase in drought tolerance as revealed by transcript profiling of a sweetpotato somatic hybrid and its parents Ipomoea batatas (L.) Lam. and I. triloba L

Previously, we obtained the sweetpotato somatic hybrid KT1 from a cross between sweetpotato (Ipomoea batatas (L.) Lam.) cv. Kokei No. 14 and its drought-tolerant wild relative I. triloba L. KT1 not only inherited the thick storage root characteristic of Kokei No. 14 but also the drought-tolerance trait of I. triloba L. The aim of this study was to explore the molecular mechanism of the drought tolerance of KT1. Four-week-old in vitro-grown plants of KT1, Kokei No. 14, and I. triloba L. were subjected to a simulated drought stress treatment (30% PEG6000) for 0, 6, 12 and 24 h. Total RNA was extracted from samples at each time point, and then used for transcriptome sequencing. The gene transcript profiles of KT1 and its parents were compared to identify differentially expressed genes, and drought-related modules were screened by a weighted gene co-expression network analysis. The functions of ABI-like protein and Ca2+-ATPase, two proteins screened from the cyan and light yellow modules, were analyzed in terms of their potential roles in drought tolerance in KT1 and its parents. These analyses of the drought responses of KT1 and its somatic donors at the transcriptional level provide new annotations for the molecular mechanism of drought tolerance in the somatic hybrid KT1 and its parents.

Luminal lncRNAs Regulation by ERα-Controlled Enhancers in a Ligand-Independent Manner in Breast Cancer Cells

Estrogen receptor-α (ERα) is a ligand-inducible protein which mediates estrogenic hormones signaling and defines the luminal BC phenotype. Recently, we demonstrated that even in absence of ligands ERα (apoERα) binds chromatin sites where it regulates transcription of several protein-coding and lncRNA genes. Noteworthy, apoERα-regulated lncRNAs marginally overlap estrogen-induced transcripts, thus representing a new signature of luminal BC genes. By the analysis of H3K27ac enrichment in hormone-deprived MCF-7 cells, we defined a set of Super Enhancers (SEs) occupied by apoERα, including one mapped in proximity of the DSCAM-AS1 lncRNA gene. This represents a paradigm of apoERα activity since its expression is largely unaffected by estrogenic treatment, despite the fact that E2 increases ERα binding on DSCAM-AS1 promoter. We validated the enrichment of apoERα, p300, GATA3, FoxM1 and CTCF at both DSCAM-AS1 TSS and at its associated SE by ChIP-qPCR. Furthermore, by analyzing MCF-7 ChIA-PET data and by 3C assays, we confirmed long range chromatin interaction between the SE and the DSCAM-AS1 TSS. Interestingly, CTCF and p300 binding showed an enrichment in hormone-depleted medium and in the presence of ERα, elucidating the dynamics of the estrogen-independent regulation of DSCAM-AS1 expression. The analysis of this lncRNA provides a paradigm of transcriptional regulation of a luminal specific apoERα regulated lncRNA.

Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies

The identification of therapeutic targets is a critical step in the research and developement of new drugs, with several drug discovery programmes failing because of a weak linkage between target and disease. Genome-wide association studies and large-scale gene expression experiments are providing insights into the biology of several common and complex diseases, but the complexity of transcriptional regulation mechanisms often limit our understanding of how genetic variation can influence changes in gene expression. Several initiatives in the field of regulatory genomics are aiming to close this gap by systematically identifying and cataloguing regulatory elements such as promoters and enhacers across different tissues and cell types. In this Bioconductor workflow, we will explore how different types of regulatory genomic data can be used for the functional interpretation of disease-associated variants and for the prioritisation of gene lists from gene expression experiments.

Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies

The identification of therapeutic targets is a critical step in the research and developement of new drugs, with several drug discovery programmes failing because of a weak linkage between target and disease.

Genome-wide association studies and large-scale gene expression experiments are providing insights into the biology of several common diseases, but the complexity of transcriptional regulation mechanisms often limits our understanding of how genetic variation can influence changes in gene expression. Several initiatives in the field of regulatory genomics are aiming to close this gap by systematically identifying and cataloguing regulatory elements such as promoters and enhacers across different tissues and cell types.

In this Bioconductor workflow, we will explore how different types of regulatory genomic data can be used for the functional interpretation of disease-associated variants and for the prioritisation of gene lists from gene expression experiments.