Encyclopedia Of DNA Elements Research Articles

G-quadruplexes as pivotal components of cis-regulatory elements in the human genome

BackgroundCis-regulatory elements (CREs) are crucial for regulating gene expression, and G-quadruplexes (G4s), as prototypal non-canonical DNA structures, may play a role in this regulation. However, the relationship between G4s and CREs, especially with non-promoter-like functional elements, requires further systematic investigation. We aimed to investigate the associations between G4s and human cCREs (candidate CREs) inferred from the Encyclopedia of DNA Elements (ENCODE) data.ResultsWe found that G4s are prominently enriched in most types of cCREs, especially those with promoter-like signatures (PLS). The co-occurrence of CTCF signals with H3K4me3 or H3K27ac signals strengthens the association between cCREs and G4s. Genetic variants in G4s, particularly within their G-runs, exhibit higher regulatory potential and deleterious effects compared to cCREs. The G-runs within G4s near transcriptional start sites (TSSs) are more evolutionarily constrained compared to G-runs in cCREs, while those far from the TSS are relatively less conserved. The presence of G4s is often linked to a more favorable local chromatin environment for the activation and execution of regulatory function of cCREs, potentially attributable to the formation of G4 secondary structures. Finally, we discovered that G4-associated cCREs exhibit widespread activation in a variety of cancers.ConclusionsOur study suggests that G4s are integral components of human cis-regulatory elements, extending beyond their potential role in promoters. The G4 primary sequences are associated with the localization of CREs, while the G4 structures are linked to the activation of these elements. Therefore, we propose defining G4s as pivotal regulatory elements in the human genome.

Identification, Design, and Application of Noncoding Cis-Regulatory Elements.

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.

Super-enhancer-driven LncRNA PPARα-seRNA exacerbates glucolipid metabolism and diabetic cardiomyopathy via recruiting KDM4B

ObjectiveAberrant glucolipid metabolism in the heart is a characteristic factor in diabetic cardiomyopathy (DbCM). Super-enhancers-driven noncoding RNAs (seRNAs) are emerging as powerful regulators in the progression of cardiac diseases. However, the functions of seRNAs in DbCM have not been fully elucidated. MethodsSuper enhancers and their associated seRNAs were screened and identified by H3K27ac ChIP-seq data in the Encyclopedia of DNA Elements (ENCODE) dataset. A dual-luciferase reporter assay was performed to analyze the function of super-enhancers on the transcription of peroxisome proliferator-activated receptor α-related seRNA (PPARα-seRNA). A DbCM mouse model was established using db/db leptin receptor-deficient mice. Adeno-associated virus serotype 9-seRNA (AAV9-seRNA) was injected via the tail vein to evaluate the role of seRNA in DbCM. The underlying mechanism was explored through RNA pull-down, RNA and chromatin immunoprecipitation, and chromatin isolation by RNA purification. ResultsPPARα-seRNA was regulated by super-enhancers and its levels were increased in response to high glucose and palmitic acid stimulation in cardiomyocytes. Functionally, PPARα-seRNA overexpression aggravated lipid deposition, reduced glucose uptake, and repressed energy production. In contrast, PPARα-seRNA knockdown ameliorated metabolic disorder in vitro. In vivo, overexpression of PPARα-seRNA exacerbated cardiac metabolic disorder and deteriorated cardiac dysfunction, myocardial fibrosis, and hypertrophy in DbCM. Mechanistically, PPARα-seRNA bound to the histone demethylase KDM4B (Lysine-specific demethylase 4B) and decreased H3K9me3 levels in the promoter region of PPARα, ultimately enhancing its transcription. ConclusionsOur study revealed the pivotal function of a super-enhancer-driven long noncoding RNA (lncRNA), PPARα-seRNA, in the deterioration of cardiac function and the exacerbation of metabolic abnormalities in diabetic cardiomyopathy, which recruited KDM4B to the promoter region of PPARα and repression of its transcription. This suggests a promising therapeutic strategy for the treatment of DbCM.

An updated compendium and reevaluation of the evidence for nuclear transcription factor occupancy over the mitochondrial genome.

In most eukaryotes, mitochondrial organelles contain their own genome, usually circular, which is the remnant of the genome of the ancestral bacterial endosymbiont that gave rise to modern mitochondria. Mitochondrial genomes are dramatically reduced in their gene content due to the process of endosymbiotic gene transfer to the nucleus; as a result most mitochondrial proteins are encoded in the nucleus and imported into mitochondria. This includes the components of the dedicated mitochondrial transcription and replication systems and regulatory factors, which are entirely distinct from the information processing systems in the nucleus. However, since the 1990s several nuclear transcription factors have been reported to act in mitochondria, and previously we identified 8 human and 3 mouse transcription factors (TFs) with strong localized enrichment over the mitochondrial genome using ChIP-seq (Chromatin Immunoprecipitation) datasets from the second phase of the ENCODE (Encyclopedia of DNA Elements) Project Consortium. Here, we analyze the greatly expanded in the intervening decade ENCODE compendium of TF ChIP-seq datasets (a total of 6,153 ChIP experiments for 942 proteins, of which 763 are sequence-specific TFs) combined with interpretative deep learning models of TF occupancy to create a comprehensive compendium of nuclear TFs that show evidence of association with the mitochondrial genome. We find some evidence for chrM occupancy for 50 nuclear TFs and two other proteins, with bZIP TFs emerging as most likely to be playing a role in mitochondria. However, we also observe that in cases where the same TF has been assayed with multiple antibodies and ChIP protocols, evidence for its chrM occupancy is not always reproducible. In the light of these findings, we discuss the evidential criteria for establishing chrM occupancy and reevaluate the overall compendium of putative mitochondrial-acting nuclear TFs.

Ethical considerations in utilizing artificial intelligence for analyzing the NHGRI’s History of Genomics and Human Genome Project archives

Understanding “how to optimize the production of scientific knowledge” is paramount to those who support scientific research—funders as well as research institutions—to the communities served, and to researchers. Structured archives can help all involved to learn what decisions and processes help or hinder the production of new knowledge. Using artificial intelligence (AI) and large language models (LLMs), we recently created the first structured digital representation of the historic archives of the National Human Genome Research Institute (NHGRI), part of the National Institutes of Health. This work yielded a digital knowledge base of entities, topics, and documents that can be used to probe the inner workings of the Human Genome Project, a massive international public-private effort to sequence the human genome, and several of its offshoots like The Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE). The resulting knowledge base will be instrumental in understanding not only how the Human Genome Project and genomics research developed collaboratively, but also how scientific goals come to be formulated and evolve. Given the diverse and rich data used in this project, we evaluated the ethical implications of employing AI and LLMs to process and analyze this valuable archive. As the first computational investigation of the internal archives of a massive collaborative project with multiple funders and institutions, this study will inform future efforts to conduct similar investigations while also considering and minimizing ethical challenges. Our methodology and risk-mitigating measures could also inform future initiatives in developing standards for project planning, policymaking, enhancing transparency, and ensuring ethical utilization of artificial intelligence technologies and large language models in archive exploration.Author Contributions: Mohammad Hosseini: Investigation; Project Administration; Writing – original draft; Writing – review & editing. Spencer Hong: Conceptualization, Data curation, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. Thomas Stoeger: Conceptualization; Investigation; Project Administration; Supervision; Writing – original draft; Writing – review & editing. Kristi Holmes: Funding acquisition, Supervision, Writing – review & editing. Luis A. Nunes Amaral: Funding acquisition, Supervision, Writing – review & editing. Christopher Donohue: Conceptualization, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing. Kris Wetterstrand: Conceptualization, Funding acquisition, Project administration.

Application of Single-Cell Assay for Transposase-Accessible Chromatin with High Throughput Sequencing in Plant Science: Advances, Technical Challenges, and Prospects.

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.

CisDynet: An integrated platform for modeling gene-regulatory dynamics and networks.

Chromatin accessibility sequencing has been widely used for uncovering genetic regulatory mechanisms and inferring gene regulatory networks. However, effectively integrating large-scale chromatin accessibility datasets has posed a significant challenge. This is due to the lack of a comprehensive end-to-end solution, as many existing tools primarily emphasize data preprocessing and overlook downstream analyses. To bridge this gap, we have introduced cisDynet, a holistic solution that combines streamlined data preprocessing using Snakemake and R functions with advanced downstream analysis capabilities. cisDynet excels in conventional data analyses, encompassing peak statistics, peak annotation, differential analysis, motif enrichment analysis, and more. Additionally, it allows to perform sophisticated data exploration, such as tissue-specific peak identification, time course data modeling, integration of RNA-seq data to establish peak-to-gene associations, constructing regulatory networks, and conducting enrichment analysis of genome-wide association study (GWAS) variants. As a proof of concept, we applied cisDynet to reanalyze comprehensive ATAC-seq datasets across various tissues from the Encyclopedia of DNA Elements (ENCODE) project. The analysis successfully delineated tissue-specific open chromatin regions (OCRs), established connections between OCRs and target genes, and effectively linked these discoveries with 1861 GWAS variants. Furthermore, cisDynet was instrumental in dissecting the time course open chromatin data of mouse embryonic development, revealing the dynamic behavior of OCRs over developmental stages and identifying key transcription factors governing differentiation trajectories. In summary, cisDynet offers researchers a user-friendly solution that minimizes the need for extensive coding, ensures the reproducibility of results, and greatly simplifies the exploration of epigenomic data.

Characterizing intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues

Intergenic transcription in normal and cancerous tissues is pervasive but incompletely understood. To investigate this, we constructed an atlas of over 180,000 consensus RNA polymerase II (RNAPII)-bound intergenic regions from 900 RNAPII chromatin immunoprecipitation sequencing (ChIP-seq) experiments in normal and cancer samples. Through unsupervised analysis, we identified 51 RNAPII consensus clusters, many of which mapped to specific biotypes and revealed tissue-specific regulatory signatures. We developed a meta-clustering methodology to integrate our RNAPII atlas with active transcription across 28,797 RNA sequencing (RNA-seq) samples from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Encyclopedia of DNA Elements (ENCODE). This analysis revealed strong tissue- and disease-specific interconnections between RNAPII occupancy and transcriptional activity. We demonstrate that intergenic transcription at RNAPII-bound regions is a novel per-cancer and pan-cancer biomarker. This biomarker displays genomic and clinically relevant characteristics, distinguishing cancer subtypes and linking to overall survival. Our results demonstrate the effectiveness of coherent data integration to uncover intergenic transcriptional activity in normal and cancer tissues.

New oncogenic functions of LINE1 retroelement as a ceRNA for tumor suppressive microRNA miR-126 on ENPP5.

Retroelements (REs) had been considered 'Junk' until the encyclopedia of DNA elements (ENCODE) project demonstrated that most genome is functional. Although the function of retroelements has been reported in diverse cancers including human breast cancer (HBC) and subtypes, only a few studies have suggested the putative functions of REs via their random genome integration. A canine mammary tumor (CMT) has been highlighted due to the similarities in molecular and pathophysiology with HBC. This study investigated the putative roles of REs common in both HBC and CMT. The human LINE and HERV-K sequences harbor many miRNAs responsive elements (MREs) for tumor-suppressive miRNA such as let-7. We also observed that various MREs are exist in the ERV and LINE highly expressed in the transcriptome data of CMT as well as HBC sets. MREs against miR-126 were highly expressed in both HBC and CMT while the levels of miR-126 were down-regulated. Oppositely, the expression of miR-126 target genes was significantly up-regulated in the cancers. Moreover, cancer patients with an increased level of miR-126 showed better overall survival. The expression of ENPP5, a putative miR-126 target gene, was downregulated by miR-126 mimic. Importantly, overexpression of LINE fragment significantly suppressed miR-126 function on the target gene expression. We propose the functional role of REs expression in tumorigenesis as competing endogenous RNAs (ceRNA) against tumor-suppressive miRNAs. This study provided pieces of evidence that LINE expression, even partial and fragmented, have a regulatory function in ENPP5 gene expression via the competition with miR-126.

Evolutionary constraint and innovation across hundreds of placental mammals.

Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.

ATAC-seq Data Processing.

ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) has gained wide popularity as a fast, straightforward, and efficient way of generating genome-wide maps of open chromatin and guiding identification of active regulatory elements and inference of DNA protein binding locations. Given the ubiquity of this method, uniform and standardized methods for processing and assessing the quality of ATAC-seq datasets are needed. Here, we describe the data processing pipeline used by the ENCODE (Encyclopedia of DNA Elements) consortium to process ATAC-seq data into peak call sets and signal tracks and to assess the quality of these datasets.

Genetic architecture of tuberculosis susceptibility: A comprehensive research synopsis, meta-analyses, and epidemiological evidence.

To date, many studies have been conducted to investigate associations between variants and tuberculosis risk; however, the results have been inconclusive. Here, we systematically provide a summary of the understanding of the genetic architecture of tuberculosis susceptibility. We searched PubMed, Embase and Web of Science to identify genetic association studies of tuberculosis published through October 31, 2021. We conducted meta-analyses for the genetic association with tuberculosis risk. We graded levels of cumulative epidemiological evidence of significant associations with risk of tuberculosis and false-positive report probability tests. We performed functional annotations for these variants using data from the Encyclopedia of DNA Elements (ENCODE) Project and other databases. We identified 703 eligible articles comprising 298,074 cases and 879,593 controls through screening a total of 24,398 citations. Meta-analyses were conducted for 614 genetic variants in 469 genes or loci. We found 39 variants that were nominally significantly associated with tuberculosis risk. Cumulative epidemiological evidence for a significant association was graded strong for 9 variants in or near 9 genes. Among them, 5 variants were associated with tuberculosis risk in at least three main ethnicity (African, Asian and White) which together explained approximately 9.59% of the familial relative risk of tuberculosis. Data from ENCODE and other databases suggested that 8 of these 9 genetic variants with strong evidence might fall within putative functional regions. Our study summarizes the current literature on the genetic architecture of tuberculosis susceptibility and provides useful data for designing future studies to investigate the genetic association with tuberculosis risk.

Establishing a Novel Gene Signature Related to Histone Modifications for Predicting Prognosis in Lung Adenocarcinoma.

Background Epigenetic modifications have been revealed to play an important role in tumorigenesis and tumor development. This study aims to analyze the role of histone modifications and the prognostic values of histone modifications in lung adenocarcinoma (LUAD). The promoters and enhancers of protein encoding genes (PCGs) were the regions of enriched histone modifications. Methods Expression profiles and clinical information of LUAD samples were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Histone modification data of LUAD cell lines were downloaded from Encyclopedia of DNA Elements (ENCODE) database. Limma R package was used to identify differentially expressed PCGs. To identify molecular subtypes, consensus clustering was conducted based on the expression of dysregulated PCGs with abnormal histone modifications. Univariate Cox regression analysis and stepwise Akaike information criterion (stepAIC) were utilized to establish a prognostic model. Results We identified a total of 699 epigenetic dysregulated genes with 122 of them significantly correlating with LUAD prognosis. We constructed three molecular subtypes (C1, C2, and C3) based on the 122 prognostic genes. C2 had the longest overall survival while C1 had the worst prognosis. In addition, three subtypes had differential immune infiltration and the response to immune checkpoint inhibitors. Moreover, we identified a risk model containing 5 epi-PCGs that had favorable performance to predict prognosis in different datasets. Conclusions This study further supported the critical histone modifications in LUAD development. Three subtypes may provide guidance for the immunotherapy of LUAD patients. Importantly, the prognostic model had great potential to predict LUAD prognosis.

Greenscreen: A simple method to remove artifactual signals and enrich for true peaks in genomic datasets including ChIP-seq data.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is widely used to identify factor binding to genomic DNA and chromatin modifications. ChIP-seq data analysis is affected by genomic regions that generate ultra-high artifactual signals. To remove these signals from ChIP-seq data, the Encyclopedia of DNA Elements (ENCODE) project developed comprehensive sets of regions defined by low mappability and ultra-high signals called blacklists for human, mouse (Mus musculus), nematode (Caenorhabditis elegans), and fruit fly (Drosophila melanogaster). However, blacklists are not currently available for many model and nonmodel species. Here, we describe an alternative approach for removing false-positive peaks called greenscreen. Greenscreen is easy to implement, requires few input samples, and uses analysis tools frequently employed for ChIP-seq. Greenscreen removes artifactual signals as effectively as blacklists in Arabidopsis thaliana and human ChIP-seq dataset while covering less of the genome and dramatically improves ChIP-seq peak calling and downstream analyses. Greenscreen filtering reveals true factor binding overlap and occupancy changes in different genetic backgrounds or tissues. Because it is effective with as few as two inputs, greenscreen is readily adaptable for use in any species or genome build. Although developed for ChIP-seq, greenscreen also identifies artifactual signals from other genomic datasets including Cleavage Under Targets and Release Using Nuclease. We present an improved ChIP-seq pipeline incorporating greenscreen that detects more true peaks than other methods.

Cis-regulatory elements (CREs) in spinal solitary fibrous tumours (SFT)

Spinal Solitary Fibrous Tumour is a rare soft tissue neoplasm. Although a lot of genes are involved in Spinal Solitary Fibrous Tumour progression, survival and metastasis, NGFI-A binding protein 2 (NAB2) - signal transducer and activator of transcription 6 (STAT6) gene fusion is one of the most commonly occurring genetic abnormalities in all types of Solitary Fibrous Tumours (SFT). The interaction of STAT6 (Early Growth Response (EGR) transcriptional activator) and NAB2 (EGR transcriptional repressor) activates the conversion of the transcription repressor to the transcriptional activator and promotes EGR-induced promoter activity. EGR has shown to plays a role in the regulation of cell survival, proliferation and cell death. Cis-regulatory elements (CREs) are genomic sequences in non-coding regions of the genomic DNA which binds with the transcription factors, and they play an essential role in precise control of gene expression. CREs composed of enhancers, suppressors and insulators play pivotal roles in gene expression throughout life and development. They have important role in maintaining the normal homeostasis, preventing organogenesis, tumourigenesis and teratoma formation. In this study, we investigate the non-coding regions in the human genome to detect enhancers and suppressors present in different tissue samples of Spinal SFT using Encyclopedia of DNA Elements (ENCODE). The study of these enhancers and suppressors may be used to develop newer diagnostic and treatment strategies. A total of 75 genes and immunohistochemistry (IHC) markers expressed in Spinal SFT were obtained from PubMed and Google Scholar. CREs were identified using the ENCODE consortium. Protein interaction network was obtained using String v11.0 using the proteins corresponding to these 75 genes. Results obtained from ENCODE were enumerated and web-hosted for public access to design a treatment strategy. This may enable the wet lab scientist design CREs specific for Spinal SFT using the in silico results obtained.

Comprehensive epigenomic profiling of human alveolar epithelial differentiation identifies key epigenetic states and transcription factor co-regulatory networks for maintenance of distal lung identity

BackgroundDisruption of alveolar epithelial cell (AEC) differentiation is implicated in distal lung diseases such as chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and lung adenocarcinoma that impact morbidity and mortality worldwide. Elucidating underlying disease pathogenesis requires a mechanistic molecular understanding of AEC differentiation. Previous studies have focused on changes of individual transcription factors, and to date no study has comprehensively characterized the dynamic, global epigenomic alterations that facilitate this critical differentiation process in humans.ResultsWe comprehensively profiled the epigenomic states of human AECs during type 2 to type 1-like cell differentiation, including the methylome and chromatin functional domains, and integrated this with transcriptome-wide RNA expression data. Enhancer regions were drastically altered during AEC differentiation. Transcription factor binding analysis within enhancer regions revealed diverse interactive networks with enrichment for many transcription factors, including NKX2–1 and FOXA family members, as well as transcription factors with less well characterized roles in AEC differentiation, such as members of the MEF2, TEAD, and AP1 families. Additionally, associations among transcription factors changed during differentiation, implicating a complex network of heterotrimeric complex switching in driving differentiation. Integration of AEC enhancer states with the catalog of enhancer elements in the Roadmap Epigenomics Mapping Consortium and Encyclopedia of DNA Elements (ENCODE) revealed that AECs have similar epigenomic structures to other profiled epithelial cell types, including human mammary epithelial cells (HMECs), with NKX2–1 serving as a distinguishing feature of distal lung differentiation.ConclusionsEnhancer regions are hotspots of epigenomic alteration that regulate AEC differentiation. Furthermore, the differentiation process is regulated by dynamic networks of transcription factors acting in concert, rather than individually. These findings provide a roadmap for understanding the relationship between disruption of the epigenetic state during AEC differentiation and development of lung diseases that may be therapeutically amenable.

Gestational Age Dependence of the Maternal Circulating Long Non-Coding RNA Transcriptome During Normal Pregnancy Highlights Antisense and Pseudogene Transcripts.

In the post-genomic era, our understanding of the molecular regulators of physiologic and pathologic processes in pregnancy is expanding at the whole-genome level. Longitudinal changes in the known protein-coding transcriptome during normal pregnancy, which we recently reported (Gomez-Lopez et al., 2019), have improved our definition of the major operant networks, yet pregnancy-related functions of the non-coding RNA transcriptome remain poorly understood. A key finding of the ENCODE (Encyclopedia of DNA Elements) Consortium, the successor of the Human Genome Project, was that the human genome contains approximately 60,000 genes, the majority of which do not encode proteins. The total transcriptional output of non-protein-coding RNA genes, collectively referred to as the non-coding transcriptome, is comprised mainly of long non-coding RNA (lncRNA) transcripts (Derrien et al., 2012). Although the ncRNA transcriptome eclipses its protein-coding counterpart in abundance, it has until recently lacked a comprehensive, unbiased, genome-scale characterization over the timecourse of normal human pregnancy. Here, we annotated, characterized, and selectively validated the longitudinal changes in the non-coding transcriptome of maternal whole blood during normal pregnancy to term. We identified nine long non-coding RNAs (lncRNAs), including long intergenic non-coding RNAs (lincRNAs) as well as lncRNAs antisense to or otherwise in the immediate vicinity of protein-coding genes, that were differentially expressed with advancing gestation in normal pregnancy: AL355711, BC039551 (expressed mainly in the placenta), JHDM1D-AS1, A2M-AS1, MANEA-AS1, NR_034004, LINC00649, LINC00861, and LINC01094. By cross-referencing our dataset against major public pseudogene catalogs, we also identified six transcribed pseudogenes that were differentially expressed over time during normal pregnancy in maternal blood: UBBP4, FOXO3B, two Makorin (MKRN) pseudogenes (MKRN9P and LOC441455), PSME2P2, and YBX3P1. We also identified three non-coding RNAs belonging to other classes that were modulated during gestation: the microRNA MIR4439, the small nucleolar RNA (snoRNA) SNORD41, and the small Cajal-body specific ncRNA SCARNA2. The expression profiles of most hits were broadly suggestive of functions in pregnancy. These time-dependent changes of the non-coding transcriptome during normal pregnancy, which may confer specific regulatory impacts on their protein-coding gene targets, will facilitate a deeper molecular understanding of pregnancy and lncRNA-mediated molecular pathways at the maternal-fetal interface and of how these pathways impact maternal and fetal health.

Decoding the Equine Genome: Lessons from ENCODE.

The horse reference genome assemblies, EquCab2.0 and EquCab3.0, have enabled great advancements in the equine genomics field, from tools to novel discoveries. However, significant gaps of knowledge regarding genome function remain, hindering the study of complex traits in horses. In an effort to address these gaps and with inspiration from the Encyclopedia of DNA Elements (ENCODE) project, the equine Functional Annotation of Animal Genome (FAANG) initiative was proposed to bridge the gap between genome and gene expression, providing further insights into functional regulation within the horse genome. Three years after launching the initiative, the equine FAANG group has generated data from more than 400 experiments using over 50 tissues, targeting a variety of regulatory features of the equine genome. In this review, we examine how valuable lessons learned from the ENCODE project informed our decisions in the equine FAANG project. We report the current state of the equine FAANG project and discuss how FAANG can serve as a template for future expansion of functional annotation in the equine genome and be used as a reference for studies of complex traits in horse. A well-annotated reference functional atlas will also help advance equine genetics in the pan-genome and precision medicine era.

Differential enrichment of H3K9me3 at annotated satellite DNA repeats in human cell lines and during fetal development in mouse

BackgroundTrimethylation of histone H3 on lysine 9 (H3K9me3) at satellite DNA sequences has been primarily studied at (peri)centromeric regions, where its level shows differences associated with various processes such as development and malignant transformation. However, the dynamics of H3K9me3 at distal satellite DNA repeats has not been thoroughly investigated.ResultsWe exploit the sets of publicly available data derived from chromatin immunoprecipitation combined with massively parallel DNA sequencing (ChIP-Seq), produced by the The Encyclopedia of DNA Elements (ENCODE) project, to analyze H3K9me3 at assembled satellite DNA repeats in genomes of human cell lines and during mouse fetal development. We show that annotated satellite elements are generally enriched for H3K9me3, but its level in cancer cell lines is on average lower than in normal cell lines. We find 407 satellite DNA instances with differential H3K9me3 enrichment between cancer and normal cells including a large 115-kb cluster of GSATII elements on chromosome 12. Differentially enriched regions are not limited to satellite DNA instances, but instead encompass a wider region of flanking sequences. We found no correlation between the levels of H3K9me3 and noncoding RNA at corresponding satellite DNA loci. The analysis of data derived from multiple tissues identified 864 instances of satellite DNA sequences in the mouse reference genome that are differentially enriched between fetal developmental stages.ConclusionsOur study reveals significant differences in H3K9me3 level at a subset of satellite repeats between biological states and as such contributes to understanding of the role of satellite DNA repeats in epigenetic regulation during development and carcinogenesis.

A Functional Polymorphism in Accessible Chromatin Region Confers Risk of Non-Small Cell Lung Cancer in Chinese Population.

BackgroundThe disease-associated non-coding variants identified by genome-wide association studies (GWASs) were enriched in open chromatin regions (OCRs) and implicated in gene regulation. Genetic variants in OCRs thus may exert regulatory functions and contribute to non-small cell lung cancer (NSCLC) susceptibility.ObjectiveTo fine map potential functional variants in GWAS loci that contribute to NSCLC predisposition using chromatin accessibility and histone modification data and explore their functions by population study and biochemical experimental analyses.MethodsWe mapped the chromatin accessible regions of lung tissues using data of assay for transposase-accessible chromatin using sequencing (ATAC-seq) in The Cancer Genome Atlas (TCGA) and prioritized potential regulatory variants within lung cancer GWAS loci by aligning with histone signatures using data of chromatin immunoprecipitation assays followed by sequencing (ChIP-seq) in the Encyclopedia of DNA Elements (ENCODE). A two-stage case–control study with 1,830 cases and 2,001 controls was conducted to explore the associations between candidate variants and NSCLC risk in Chinese population. Bioinformatic annotations and biochemical experiments were performed to further reveal the potential functions of significant variants.ResultsSixteen potential functional single-nucleotide polymorphisms (SNPs) were selected as candidates from bioinformatics analyses. Three variants out of the 16 candidate SNPs survived after genotyping in stage 1 case–control study, and only the results of SNP rs13064999 were successfully validated in the analyses of stage 2 case–control study. In combined analyses, rs13064999 was significantly associated with NSCLC risk [additive model; odds ratio (OR) = 1.17; 95%CI, 1.07–1.29; p = 0.001]. Functional annotations indicated its potential enhancer bioactivity, and dual-luciferase reporter assays revealed a significant increase in luciferase activity for the reconstructed plasmid with rs13064999 A allele, when compared to the one with wild-type G allele (pA549 < 0.001, pSK-MES-1 = 0.004). Further electrophoretic mobility shift assays (EMSA) and super-shift assays confirmed a stronger affinity of HP1γ for the binding motif containing SNP rs13064999 A allele.ConclusionThese findings suggested that the functional variant rs13064999, identified by the integration of ATAC-seq and ChIP-seq data, contributes to the susceptibility of NSCLC by affecting HP1γ binding, while the exact biological mechanism awaits further exploration.