A promoter-level mammalian expression atlas

DNA replication initiation shapes the mutational landscape and expression of the human genome

The interplay between active biological processes and DNA repair is central to mutagenesis. Here, we show that the ubiquitous process of replication initiation is mutagenic, leaving a specific mutational footprint at thousands of early and efficient replication origins. The observed mutational pattern is consistent with two distinct mechanisms, reflecting the two-step process of origin activation, triggering the formation of DNA breaks at the center of origins and local error-prone DNA synthesis in their immediate vicinity. We demonstrate that these replication initiation-dependent mutational processes exert an influence on phenotypic diversity in humans that is disproportionate to the origins' genomic size: By increasing mutational loads at gene promoters and splice junctions, the presence of an origin significantly influences both gene expression and mRNA isoform usage. Last, we show that mutagenesis at origins not only drives the evolution of origin sequences but also contributes to sculpting regulatory domains of the human genome.

Systematic characterization of cancer transcriptome at transcript resolution

Transcribed RNAs undergo various regulation and modification to become functional transcripts. Notably, cancer transcriptome has not been fully characterized at transcript resolution. Herein, we carry out a reference-based transcript assembly across >1000 cancer cell lines. We identify 498,255 transcripts, approximately half of which are unannotated. Unannotated transcripts are closely associated with cancer-related hallmarks and show clinical significance. We build a high-confidence RNA binding protein (RBP)-transcript regulatory network, wherein most RBPs tend to regulate transcripts involved in cell proliferation. We identify numerous transcripts that are highly associated with anti-cancer drug sensitivity. Furthermore, we establish RBP-transcript-drug axes, wherein PTBP1 is experimentally validated to affect the sensitivity to decitabine by regulating KIAA1522-a6 transcript. Finally, we establish a user-friendly data portal to serve as a valuable resource for understanding cancer transcriptome diversity and its potential clinical utility at transcript level. Our study substantially extends cancer RNA repository and will facilitate anti-cancer drug discovery.

Multi-Layered Regulations on the Chromatin Architectures: Establishing the Tight and Specific Responses of Fission Yeast fbp1 Gene Transcription

Transcriptional regulation is pivotal for all living organisms and is required for adequate response to environmental fluctuations and intercellular signaling molecules. For precise regulation of transcription, cells have evolved regulatory systems on the genome architecture, including the chromosome higher-order structure (e.g., chromatin loops), location of transcription factor (TF)-binding sequences, non-coding RNA (ncRNA) transcription, chromatin configuration (e.g., nucleosome positioning and histone modifications), and the topological state of the DNA double helix. To understand how these genome-chromatin architectures and their regulators establish tight and specific responses at the transcription stage, the fission yeast fbp1 gene has been analyzed as a model system for decades. The fission yeast fbp1 gene is tightly repressed in the presence of glucose, and this gene is induced by over three orders of magnitude upon glucose starvation with a cascade of multi-layered regulations on various levels of genome and chromatin architecture. In this review article, we summarize the multi-layered transcriptional regulatory systems revealed by the analysis of the fission yeast fbp1 gene as a model system.

HIF1α-AS1 is a DNA:DNA:RNA triplex-forming lncRNA interacting with the HUSH complex

DNA:DNA:RNA triplexes that are formed through Hoogsteen base-pairing of the RNA in the major groove of the DNA duplex have been observed in vitro, but the extent to which these interactions occur in cells and how they impact cellular functions remains elusive. Using a combination of bioinformatic techniques, RNA/DNA pulldown and biophysical studies, we set out to identify functionally important DNA:DNA:RNA triplex-forming long non-coding RNAs (lncRNA) in human endothelial cells. The lncRNA HIF1α-AS1 was retrieved as a top hit. Endogenous HIF1α-AS1 reduces the expression of numerous genes, including EPH Receptor A2 and Adrenomedullin through DNA:DNA:RNA triplex formation by acting as an adapter for the repressive human silencing hub complex (HUSH). Moreover, the oxygen-sensitive HIF1α-AS1 is down-regulated in pulmonary hypertension and loss-of-function approaches not only result in gene de-repression but also enhance angiogenic capacity. As exemplified here with HIF1α-AS1, DNA:DNA:RNA triplex formation is a functionally important mechanism of trans-acting gene expression control.

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

Gene product diversity: adaptive or not?

One gene does not equal one RNA or protein. The genomic revolution has revealed numerous different RNA and protein molecules that can be produced from one gene, such as circular RNAs generated by back-splicing, proteins with residues mismatching the genomic encoding because of RNA editing, and proteins extended in the C terminus via stop codon readthrough in translation. Are these diverse products results of exquisite gene regulations or imprecise biological processes? While there are cases where the gene product diversity appears beneficial, genome-scale patterns suggest that much of this diversity arises from nonadaptive, molecular errors. This finding has important implications for studying the functions of diverse gene products and for understanding the fundamental properties and evolution of cellular life.

Regulatory variants in a novel distal enhancer regulate the expression of CYP3A4 and CYP3A5

The cytochrome P450 3As (CYP3As) are abundantly expressed in the liver and metabolize many commonly prescribed medications. Their expression is highly variable between individuals with little known genetic cause. Despite extensive investigation, cis-acting genetic elements that control the expression of the CYP3As remain uncharacterized. Using chromatin conformation capture (4C assays), we detected reciprocal interaction between a distal regulatory region (DRR) and the CYP3A4 promoter. The DRR colocalizes with a variety of enhancer marks and was found to promote transcription in reporter assays. CRISPR-mediated deletion of the DRR decreased expression of CYP3A4, CYP3A5, and CYP3A7, supporting its role as a shared enhancer regulating the expression of three CYP3A genes. Using reporter gene assays, we identified two single-nucleotide polymorphisms (rs115025140 and rs776744/rs776742) that increased DRR-driven luciferase reporter expression. In a liver cohort (n = 246), rs115025140 was associated with increased expression of CYP3A4 mRNA (1.8-fold) and protein (1.6-fold) and rs776744/rs776742 was associated with 1.39-fold increased expression of CYP3A5 mRNA. The rs115025140 is unique to the African population and in a clinical cohort of African Americans taking statins for lipid control rs115025140 carriers showed a trend toward reduced statin-mediated lipid reduction. In addition, using a published cohort of Chinese patients who underwent renal transplantation taking tacrolimus, rs776744/rs776742 carriers were associated with reduced tacrolimus concentration after adjusting for CYP3A5*3. Our results elucidate a complex regulatory network controlling expression of three CYP3A genes and identify two novel regulatory variants with potential clinical relevance for predicting CYP3A4 and CYP3A5 expression.

Multi-tissue DNA methylation microarray signature is predictive of gene function

Background Transcriptional correlation networks derived from publicly available gene expression microarrays have been previously shown to be predictive of known gene functions, but less is known about the predictive capacity of correlated DNA methylation at CpG sites. Guilt-by-association co-expression methods can adapted for use with DNA methylation when a representative methylation value is created for each gene. We examine how methylation compares to expression in predicting Gene Ontology terms using both co-methylation and traditional machine learning approaches across different types of representative methylation values per gene. Methods We perform guilt-by-association gene function prediction with a suite of models called Methylation Array Network Analysis, using a network of correlated methylation values derived from over 24,000 samples. In generating the correlation matrix, the performance of different methods of collapsing probe-level data effect on the resulting gene function predictions was compared, along with the use of different regions surrounding the gene of interest. Results Using mean comethylation of a given gene to its annotated term had an overall highest prediction macro-AUC of 0.60 using mean gene body methylation, across all Gene Ontology terms. This was increased using the logistic regression approach with the highest macro-AUC of 0.82 using mean gene body methylation, compared to the naive predictor of 0.72. Conclusion Genes correlated in their methylation state are functionally related. Genes clustered in co-methylation space were enriched for chromatin state, PRC2, immune response, and development-related terms.

The SCF/KIT axis in human mast cells: Capicua acts as potent KIT repressor and ERK predominates PI3K

BACKGROUND

The SCF/KIT axis regulates nearly all aspects of mast cell (MC) biology. A comprehensive view of SCF-triggered phosphorylation dynamics is lacking. The relationship between signaling modules and SCF-supported functions likewise remains ill-defined.

METHODS

Mast cells were isolated from human skin; upon stimulation by SCF, global phosphoproteomic changes were analyzed by LC-MS/MS and selectively validated by immunoblotting. MC survival was inspected by YoPro; BrdU incorporation served to monitor proliferation. Gene expression was quantified by RT-qPCR and cytokines by ELISA. Pharmacological inhibitors were supplemented by ERK1 and/or ERK2 knockdown. CIC translocation and degradation were studied in nuclear and cytoplasmic fractions. CIC's impact on KIT signaling and function was assessed following RNA interference.

RESULTS

≈5400 out of ≈10,500 phosphosites experienced regulation by SCF. The MEK/ERK cascade was strongly induced surpassing STAT5 > PI3K/Akt > p38 > JNK. Comparison between MEK/ERK's and PI3K's support of basic programs (apoptosis, proliferation) revealed equipotency between modules. In functional outputs (gene expression, cytokines), ERK was the most influential kinase. OSM and LIF production was identified in skin MCs. Strikingly, SCF triggered massive phosphorylation of a protein not associated with KIT previously: CIC. Phosphorylation was followed by CIC's cytoplasmic appearance and degradation, the latter sensitive to protease but not preoteasome inhibition. Both shuttling and degradation were ERK-dependent. Conversely, CIC-siRNA facilitated KIT signaling, functional outputs, and survival.

CONCLUSION

The SCF/KIT axis shows notable strength in MCs, and MEK/ERK as most prominent module. An inhibitory circuit exists between KIT and CIC. CIC stabilization in MCs may turn out as a therapeutic option to interfere with allergic and MC-driven diseases.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Building integrative functional maps of gene regulation

Every cell in the human body inherits a copy of the same genetic information. The three billion base pairs of DNA in the human genome, and the roughly 50 000 coding and non-coding genes they contain, must thus encode all the complexity of human development and cell and tissue type diversity. Differences in gene regulation, or the modulation of gene expression, enable individual cells to interpret the genome differently to carry out their specific functions. Here we discuss recent and ongoing efforts to build gene regulatory maps, which aim to characterize the regulatory roles of all sequences in a genome. Many researchers and consortia have identified such regulatory elements using functional assays and evolutionary analyses; we discuss the results, strengths and shortcomings of their approaches. We also discuss new techniques the field can leverage and emerging challenges it will face while striving to build gene regulatory maps of ever-increasing resolution and comprehensiveness.

A map of cis-regulatory modules and constituent transcription factor binding sites in 80% of the mouse genome

BACKGROUND

Mouse is probably the most important model organism to study mammal biology and human diseases. A better understanding of the mouse genome will help understand the human genome, biology and diseases. However, despite the recent progress, the characterization of the regulatory sequences in the mouse genome is still far from complete, limiting its use to understand the regulatory sequences in the human genome.

RESULTS

Here, by integrating binding peaks in ~ 9,000 transcription factor (TF) ChIP-seq datasets that cover 79.9% of the mouse mappable genome using an efficient pipeline, we were able to partition these binding peak-covered genome regions into a cis-regulatory module (CRM) candidate (CRMC) set and a non-CRMC set. The CRMCs contain 912,197 putative CRMs and 38,554,729 TF binding sites (TFBSs) islands, covering 55.5% and 24.4% of the mappable genome, respectively. The CRMCs tend to be under strong evolutionary constraints, indicating that they are likely cis-regulatory; while the non-CRMCs are largely selectively neutral, indicating that they are unlikely cis-regulatory. Based on evolutionary profiles of the genome positions, we further estimated that 63.8% and 27.4% of the mouse genome might code for CRMs and TFBSs, respectively.

CONCLUSIONS

Validation using experimental data suggests that at least most of the CRMCs are authentic. Thus, this unprecedentedly comprehensive map of CRMs and TFBSs can be a good resource to guide experimental studies of regulatory genomes in mice and humans.

Structure-based screening for functional non-coding RNAs in fission yeast identifies a factor repressing untimely initiation of sexual differentiation

Non-coding RNAs (ncRNAs) ubiquitously exist in normal and cancer cells. Despite their prevalent distribution, the functions of most long ncRNAs remain uncharacterized. The fission yeast Schizosaccharomyces pombe expresses >1800 ncRNAs annotated to date, but most unconventional ncRNAs (excluding tRNA, rRNA, snRNA and snoRNA) remain uncharacterized. To discover the functional ncRNAs, here we performed a combinatory screening of computational and biological tests. First, all S. pombe ncRNAs were screened in silico for those showing conservation in sequence as well as in secondary structure with ncRNAs in closely related species. Almost a half of the 151 selected conserved ncRNA genes were uncharacterized. Twelve ncRNA genes that did not overlap with protein-coding sequences were next chosen for biological screening that examines defects in growth or sexual differentiation, as well as sensitivities to drugs and stresses. Finally, we highlighted an ncRNA transcribed from SPNCRNA.1669, which inhibited untimely initiation of sexual differentiation. A domain that was predicted as conserved secondary structure by the computational operations was essential for the ncRNA to function. Thus, this study demonstrates that in silico selection focusing on conservation of the secondary structure over species is a powerful method to pinpoint novel functional ncRNAs.

The Comparative Anatomy of Nanopublications and FAIR Digital Objects

Beginning in 1995, early Internet pioneers proposed Digital Objects as encapsulations of data and metadata made accessible through persistent identifier resolution services (Kahn and Wilensky 2006). In recent years, this Digital Object Architecture has been extended to include the FAIR Guiding Principles (Wilkinson et al. 2016), resulting in the concept of a FAIR Digital Object (FDO), a minimal, uniform container making any digital resource machine-actionable. Intense effort is currently underway by a global community of experts to clarify definitions around an FDO Framework (FDOF) and to provide technical specifications (FAIR DO group 2020, FAIR Digital Object Forum 2020 , Bonino da Silva Santos (2021)) regarding their potential implementation.

Beginning in 2009, nanopublications were independently conceived (Groth et al. 2010) as a minimal, uniform container making individual semantic assertions and their associated provenance metadata, machine-actionable. They represent minimal units of structured data as citable entities (Mons and Velterop 2009). A nanopublication consists of an assertion, the provenance of the assertion, and the provenance of the nanopublication (publication info). Nanopublications are implemented in and aligned with Semantic Web technologies such as RDF, OWL, and SPARQL (World Wide Web Consortium (W3C) 2015) and can be permanently and uniquely identified using resolvable Trusty URIs (Groth et al. 2021). The existing Nanopublication Server Network provides vital services orchestrating nanopublications (Kuhn et al. 2021) including identifier resolution, storage, search and access. Nanopublications can be used to expose quantitative and qualitative data, as well as hypotheses, claims, negative results, and opinions that are typically unavailable as structured data or go unpublished altogether. The first practical application of nanopublications occurred in 2014, with the publication of millions of nanopublications as part of the FANTOM5 Project (The FANTOM Consortium and the RIKEN PMI and CLST (DGT) 2014, Lizio et al. 2015). Since then, millions of real-world examples spanning diverse knowledge domains are now available on the nanopublication server network.

Like nanopublication, the FDOF also posits an ultra-minimal approach to structured, self-contained, machine-readable data and metadata. An FDO consists of: the object itself (subsequently referred to here as the resource to avoid confusion with other meanings of the term “object”); the metadata describing the resource; and a globally unique and persistent identifier with predictable resolution behaviors.

These two technologies share the same vision of a data infrastructure, and act as instances of Machine-Actionable Containers (MACs) that make use of minimal uniform standards to enable FAIR operations. Here, we compare the structure and computational behaviors of the existing nanopublication infrastructure, to those in the proposed FAIR Digital Object Framework. Although developed independently there are clear parallels between the vision and the approach of nanopublication and FDOF. Each aspires to minimal standards for the encapsulation of digital information into free-standing, publishable (citable, referenceable) entities. The minimal standards involve globally unique and persistent identifiers that resolve to standardized semantically enabled metadata descriptions that include machine actionable paths to the resource itself.

At the same time, there are also differences. The scope of nanopublications is limited to the assertional data type and, as the name suggests, nanopublications should remain small in size (limited to single assertions as individual triples or small RDF graphs). In contrast FDOs are unlimited in their scope, accommodating digital resources of arbitrarily large size, type and complexity, so long as their type can be ontologically described. Furthermore, whereas nanopublications represent a moderately mature technology, the FDOF is a specification still under development. If it were possible to formally draw points of contact between the two approaches, then it would be possible to leverage the vast practical experience gained in the nanopublishing of assertions for the FDO community.

Here, inspired by recent applications of nanopublications in the FIP Wizard tool (Schultes et al. 2020), and their extension to research claims (Kuhn 2022, McNamara 2022) and data using Schultes (2022a), Schultes (2022b), we attempt a point-by-point comparison of the specifications between nanopublication and FDOs. We find a remarkable congruence between the currently proposed FDO requirements and the existing nanopublication infrastructure, including several FDO-like qualities already embodied in the nanopublication ecosystem.

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Analyses of rare predisposing variants of lung cancer in 6,004 whole genomes in Chinese

We present the largest whole-genome sequencing (WGS) study of non-small cell lung cancer (NSCLC) to date among 6,004 individuals of Chinese ancestry, coupled with 23,049 individuals genotyped by SNP array. We construct a high-quality haplotype reference panel for imputation and identify 20 common and low-frequency loci (minor allele frequency [MAF] ≥ 0.5%), including five loci that have never been reported before. For rare loss-of-function (LoF) variants (MAF < 0.5%), we identify BRCA2 and 18 other cancer predisposition genes that affect 5.29% of individuals with NSCLC, and 98.91% (181 of 183) of LoF variants have not been linked previously to NSCLC risk. Promoter variants of BRCA2 also have a substantial effect on NSCLC risk, and their prevalence is comparable with BRCA2 LoF variants. The associations are validated in an independent case-control study including 4,410 individuals and a prospective cohort study including 23,826 individuals. Our findings not only provide a high-quality reference panel for future array-based association studies but depict the whole picture of rare pathogenic variants for NSCLC.

Accurate prediction of functional states of cis-regulatory modules reveals common epigenetic rules in humans and mice

BACKGROUND

Predicting cis-regulatory modules (CRMs) in a genome and their functional states in various cell/tissue types of the organism are two related challenging computational tasks. Most current methods attempt to simultaneously achieve both using data of multiple epigenetic marks in a cell/tissue type. Though conceptually attractive, they suffer high false discovery rates and limited applications. To fill the gaps, we proposed a two-step strategy to first predict a map of CRMs in the genome, and then predict functional states of all the CRMs in various cell/tissue types of the organism. We have recently developed an algorithm for the first step that was able to more accurately and completely predict CRMs in a genome than existing methods by integrating numerous transcription factor ChIP-seq datasets in the organism. Here, we presented machine-learning methods for the second step.

RESULTS

We showed that functional states in a cell/tissue type of all the CRMs in the genome could be accurately predicted using data of only 1~4 epigenetic marks by a variety of machine-learning classifiers. Our predictions are substantially more accurate than the best achieved so far. Interestingly, a model trained on a cell/tissue type in humans can accurately predict functional states of CRMs in different cell/tissue types of humans as well as of mice, and vice versa. Therefore, epigenetic code that defines functional states of CRMs in various cell/tissue types is universal at least in humans and mice. Moreover, we found that from tens to hundreds of thousands of CRMs were active in a human and mouse cell/tissue type, and up to 99.98% of them were reutilized in different cell/tissue types, while as small as 0.02% of them were unique to a cell/tissue type that might define the cell/tissue type.

CONCLUSIONS

Our two-step approach can accurately predict functional states in any cell/tissue type of all the CRMs in the genome using data of only 1~4 epigenetic marks. Our approach is also more cost-effective than existing methods that typically use data of more epigenetic marks. Our results suggest common epigenetic rules for defining functional states of CRMs in various cell/tissue types in humans and mice.

Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

The accurate annotation of transcription start sites (TSSs) and their usage are critical for the mechanistic understanding of gene regulation in different biological contexts. To fulfill this, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner, and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these computational tools cast the problem as a binary classification task on a balanced dataset, thus resulting in drastic false positive predictions when applied on the genome scale. Here, we present DeeReCT-TSS, a deep learning-based method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types, which enables the identification of cell type-specific TSSs. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin states. The source code for DeeReCT-TSS is available at https://github.com/JoshuaChou2018/DeeReCT-TSS_release and https://ngdc.cncb.ac.cn/biocode/tools/BT007316.

Hypomethylation of miR-17-92 cluster in lupus T cells and no significant role for genetic factors in the lupus-associated DNA methylation signature

OBJECTIVES

Lupus T cells demonstrate aberrant DNA methylation patterns dominated by hypomethylation of interferon-regulated genes. The objective of this study was to identify additional lupus-associated DNA methylation changes and determine the genetic contribution to epigenetic changes characteristic of lupus.

METHODS

Genome-wide DNA methylation was assessed in naïve CD4+ T cells from 74 patients with lupus and 74 age-matched, sex-matched and race-matched healthy controls. We applied a trend deviation analysis approach, comparing methylation data in our cohort with over 16 500 samples. Methylation quantitative trait loci (meQTL) analysis was performed by integrating methylation profiles with genome-wide genotyping data.

RESULTS

In addition to the previously reported epigenetic signature in interferon-regulated genes, we observed hypomethylation in the promoter region of the miR-17-92 cluster in patients with lupus. Members of this microRNA cluster play an important role in regulating T cell proliferation and differentiation. Expression of two microRNAs in this cluster, miR-19b1 and miR-18a, showed a significant positive correlation with lupus disease activity. Among miR-18a target genes, TNFAIP3, which encodes a negative regulator of nuclear factor kappa B, was downregulated in lupus CD4+ T cells. MeQTL identified in lupus patients showed overlap with genetic risk loci for lupus, including CFB and IRF7. The lupus risk allele in IRF7 (rs1131665) was associated with significant IRF7 hypomethylation. However, <1% of differentially methylated CpG sites in patients with lupus were associated with an meQTL, suggesting minimal genetic contribution to lupus-associated epigenotypes.

CONCLUSION

The lupus defining epigenetic signature, characterised by robust hypomethylation of interferon-regulated genes, does not appear to be determined by genetic factors. Hypomethylation of the miR-17-92 cluster that plays an important role in T cell activation is a novel epigenetic locus for lupus.

Pathway-Specific Polygenic Risk Scores Identify Obstructive Sleep Apnea-Related Pathways Differentially Moderating Genetic Susceptibility to Coronary Artery Disease

BACKGROUND

Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner.

METHODS

We selected a cross-sectional sample of 471 877 participants from the UK Biobank, with 4974 ascertained to have OSA, 25 988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics), annotated to specific genes and pathways using functional genomics databases. Based on prior evidence of involvement with intermittent hypoxia and CAD, we tested pathway-specific polygenic risk scores for the HIF1 (hypoxia-inducible factor 1), VEGF (vascular endothelial growth factor), NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells) and TNF (tumor necrosis factor) signaling pathways.

RESULTS

In a multivariable-adjusted logistic generalized additive model, elevated pathway-specific polygenic risk scores for the Kyoto Encyclopedia of Genes and Genomes VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, P=6×10-4). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA.

CONCLUSIONS

We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. This invites further study of how OSA interacts with genetic risk at the molecular level and suggests eventual personalization of OSA treatment to reduce CAD risk according to individual pathway-specific genetic risk profiles.

SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells

MOTIVATION

Cell type-specific activities of cis-regulatory elements (CRE) are central to understanding gene regulation and disease predisposition. Single-cell RNA 5'end sequencing (sc-end5-seq) captures the transcription start sites (TSS) which can be used as a proxy to measure the activity of transcribed CREs (tCREs). However, a substantial fraction of TSS identified from sc-end5-seq data may not be genuine due to various artifacts, hindering the use of sc-end5-seq for de novo discovery of tCREs.

RESULTS

We developed SCAFE-Single-Cell Analysis of Five-prime Ends-a software suite that processes sc-end5-seq data to de novo identify TSS clusters based on multiple logistic regression. It annotates tCREs based on the identified TSS clusters and generates a tCRE-by-cell count matrix for downstream analyses. The software suite consists of a set of flexible tools that could either be run independently or as pre-configured workflows.

AVAILABILITY AND IMPLEMENTATION

SCAFE is implemented in Perl and R. The source code and documentation are freely available for download under the MIT License from https://github.com/chung-lab/SCAFE. Docker images are available from https://hub.docker.com/r/cchon/scafe. The submitted software version and test data are archived at https://doi.org/10.5281/zenodo.7023163 and https://doi.org/10.5281/zenodo.7024060, respectively.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Repression and 3D-restructuring resolves regulatory conflicts in evolutionarily rearranged genomes

Regulatory landscapes drive complex developmental gene expression, but it remains unclear how their integrity is maintained when incorporating novel genes and functions during evolution. Here, we investigated how a placental mammal-specific gene, Zfp42, emerged in an ancient vertebrate topologically associated domain (TAD) without adopting or disrupting the conserved expression of its gene, Fat1. In ESCs, physical TAD partitioning separates Zfp42 and Fat1 with distinct local enhancers that drive their independent expression. This separation is driven by chromatin activity and not CTCF/cohesin. In contrast, in embryonic limbs, inactive Zfp42 shares Fat1's intact TAD without responding to active Fat1 enhancers. However, neither Fat1 enhancer-incompatibility nor nuclear envelope-attachment account for Zfp42's unresponsiveness. Rather, Zfp42's promoter is rendered inert to enhancers by context-dependent DNA methylation. Thus, diverse mechanisms enabled the integration of independent Zfp42 regulation in the Fat1 locus. Critically, such regulatory complexity appears common in evolution as, genome wide, most TADs contain multiple independently expressed genes.

Deep sequencing of short capped RNAs reveals novel families of noncoding RNAs

In eukaryotes, capped RNAs include long transcripts such as messenger RNAs and long noncoding RNAs, as well as shorter transcripts such as spliceosomal RNAs, small nucleolar RNAs, and enhancer RNAs. Long capped transcripts can be profiled using cap analysis gene expression (CAGE) sequencing and other methods. Here, we describe a sequencing library preparation protocol for short capped RNAs, apply it to a differentiation time course of the human cell line THP-1, and systematically compare the landscape of short capped RNAs to that of long capped RNAs. Transcription initiation peaks associated with genes in the sense direction have a strong preference to produce either long or short capped RNAs, with one out of six peaks detected in the short capped RNA libraries only. Gene-associated short capped RNAs have highly specific 3' ends, typically overlapping splice sites. Enhancers also preferentially generate either short or long capped RNAs, with 10% of enhancers observed in the short capped RNA libraries only. Enhancers producing either short or long capped RNAs show enrichment for GWAS-associated disease SNPs. We conclude that deep sequencing of short capped RNAs reveals new families of noncoding RNAs and elucidates the diversity of transcripts generated at known and novel promoters and enhancers.

How "Neuronal" Are Human Skin Mast Cells?

Mast cells are evolutionarily old cells and the principal effectors in allergic responses and inflammation. They are seeded from the yolk sac during embryogenesis or are derived from hematopoietic progenitors and are therefore related to other leukocyte subsets, even though they form a separate clade in the hematopoietic system. Herein, we systematically bundle information from several recent high-throughput endeavors, especially those comparing MCs with other cell types, and combine such information with knowledge on the genes’ functions to reveal groups of neuronal markers specifically expressed by MCs. We focus on recent advances made regarding human tissue MCs, but also refer to studies in mice. In broad terms, genes hyper-expressed in MCs, but largely inactive in other myelocytes, can be classified into subcategories such as traffic/lysosomes (MLPH and RAB27B), the dopamine system (MAOB, DRD2, SLC6A3, and SLC18A2), Ca²⁺-related entities (CALB2), adhesion molecules (L1CAM and NTM) and, as an overall principle, the transcription factors and modulators of transcriptional activity (LMO4, PBX1, MEIS2, and EHMT2). Their function in MCs is generally unknown but may tentatively be deduced by comparison with other systems. MCs share functions with the nervous system, as they express typical neurotransmitters (histamine and serotonin) and a degranulation machinery that shares features with the neuronal apparatus at the synapse. Therefore, selective overlaps are plausible, and they further highlight the uniqueness of MCs within the myeloid system, as well as when compared with basophils. Apart from investigating their functional implications in MCs, a key question is whether their expression in the lineage is due to the specific reactivation of genes normally silenced in leukocytes or whether the genes are not switched off during mastocytic development from early progenitors.

Lyl1-deficiency promotes inflammatory responses and increases mycobacterial burden in response to Mycobacterium tuberculosis infection in mice

Lymphoblastic leukemia 1 (Lyl1) is a well-studied transcription factor known to exhibit oncogenic potential in various forms of leukemia with pivotal roles in hematopoietic stem cell biology. While its role in early hematopoiesis is well established, its function in mature innate cells is less explored. Here, we identified Lyl1 as a drastically perturbed gene in the Mycobacterium tuberculosis (Mtb) infected mouse macrophage transcriptome. We report that Lyl1 downregulation upon immune stimulation is a host-driven process regulated by NFκB and MAP kinase pathways. Interestingly, Lyl1-deficient macrophages have decreased bacterial killing potential with reduced nitric oxide (NO) levels while expressing increased levels of pro-inflammatory interleukin-1 and CXCL1. Lyl1-deficient mice show reduced survival to Mtb HN878 infection with increased bacterial burden and exacerbated inflammatory responses in chronic stages. We observed that increased susceptibility to infection was accompanied by increased neutrophil recruitment and IL-1, CXCL1, and CXCL5 levels in the lung homogenates. Collectively, these results suggest that Lyl1 controls Mtb growth, reduces neutrophilic inflammation and reveals an underappreciated role for Lyl1 in innate immune responses.

Isoform-resolved mRNA profiling of ribosome load defines interplay of HIF and mTOR dysregulation in kidney cancer

Hypoxia inducible factor (HIF) and mammalian target of rapamycin (mTOR) pathways orchestrate responses to oxygen and nutrient availability. These pathways are frequently dysregulated in cancer, but their interplay is poorly understood, in part because of difficulties in simultaneous measurement of global and mRNA-specific translation. Here, we describe a workflow for measurement of ribosome load of mRNAs resolved by their transcription start sites (TSSs). Its application to kidney cancer cells reveals extensive translational reprogramming by mTOR, strongly affecting many metabolic enzymes and pathways. By contrast, global effects of HIF on translation are limited, and we do not observe reported translational activation by HIF2A. In contrast, HIF-dependent alterations in TSS usage are associated with robust changes in translational efficiency in a subset of genes. Analyses of the interplay of HIF and mTOR reveal that specific classes of HIF1A and HIF2A transcriptional target gene manifest different sensitivity to mTOR, in a manner that supports combined use of HIF2A and mTOR inhibitors in treatment of kidney cancer.

In silico gene expression and pathway analysis of DEK in the human brain across the lifespan

DEK, a chromatin-remodelling phosphoprotein, is associated with various functions and biological pathways in the periphery, including inflammation, oncogenesis, DNA repair, and transcriptional regulation. We recently identified an association between DEK loss and central nervous system diseases, such as Alzheimer's. To understand DEK's potential role in disease, it is critical to characterize DEK in healthy human brain to distinguish between neural DEK expression and function in healthy versus diseased states like dementia. We utilized two public databases, BrainCloud and Human Brain Transcriptome, and analysed DEK mRNA expression across the lifespan in learning and memory relevant brain regions. Since DEK loss induces phenotypes associated with brain ageing (e.g., DNA damage and apoptosis), we hypothesized that neural DEK expression may be highest during foetal development and lower in elderly individuals. In agreement with this hypothesis, DEK was most prominently expressed during foetal development in all queried forebrain areas, relative to other ages. Consistent with its roles in the periphery, pathways related to DEK in the brain were associated with cellular proliferation, DNA replication and repair, apoptosis, and inflammation. We also found novel neural development-relevant pathways (e.g., synaptic transmission, neurite outgrowth, and myelination) to be enriched from genes correlated with DEK expression. These findings suggest that DEK is important for human brain development. Overall, we highlight age-related changes in neural DEK expression across the human lifespan and illuminate novel biological pathways associated with DEK that are distinct from normal brain ageing. These findings may further our understanding of how DEK impacts brain function and disease susceptibility.

Hotspots of single-strand DNA “breakome” are enriched at transcriptional start sites of genes

Single-strand breaks (SSBs) represent one of the most common types of DNA damage, yet not much is known about the genome landscapes of this type of DNA lesions in mammalian cells. Here, we found that SSBs are more likely to occur in certain positions of the human genome—SSB hotspots—in different cells of the same cell type and in different cell types. We hypothesize that the hotspots are likely to represent biologically relevant breaks. Furthermore, we found that the hotspots had a prominent tendency to be enriched in the immediate vicinity of transcriptional start sites (TSSs). We show that these hotspots are not likely to represent technical artifacts or be caused by common mechanisms previously found to cause DNA cleavage at promoters, such as apoptotic DNA fragmentation or topoisomerase type II (TOP2) activity. Therefore, such TSS-associated hotspots could potentially be generated using a novel mechanism that could involve preferential cleavage at cytosines, and their existence is consistent with recent studies suggesting a complex relationship between DNA damage and regulation of gene expression.

Temporal analysis of enhancers during mouse cerebellar development reveals dynamic and novel regulatory functions

We have identified active enhancers in the mouse cerebellum at embryonic and postnatal stages which provides a view of novel enhancers active during cerebellar development. The majority of cerebellar enhancers have dynamic activity between embryonic and postnatal development. Cerebellar enhancers were enriched for neural transcription factor binding sites with temporally specific expression. Putative gene targets displayed spatially restricted expression patterns, indicating cell-type specific expression regulation. Functional analysis of target genes indicated that enhancers regulate processes spanning several developmental epochs such as specification, differentiation and maturation. We use these analyses to discover one novel regulator and one novel marker of cerebellar development: Bhlhe22 and Pax3, respectively. We identified an enrichment of de novo mutations and variants associated with autism spectrum disorder in cerebellar enhancers. Furthermore, by comparing our data with relevant brain development ENCODE histone profiles and cerebellar single-cell datasets we have been able to generalize and expand on the presented analyses, respectively. We have made the results of our analyses available online in the Developing Mouse Cerebellum Enhancer Atlas (https://goldowitzlab.shinyapps.io/developing_mouse_cerebellum_enhancer_atlas/), where our dataset can be efficiently queried, curated and exported by the scientific community to facilitate future research efforts. Our study provides a valuable resource for studying the dynamics of gene expression regulation by enhancers in the developing cerebellum and delivers a rich dataset of novel gene-enhancer associations providing a basis for future in-depth studies in the cerebellum.

Polysome-CAGE of TCL1-driven chronic lymphocytic leukemia revealed multiple N-terminally altered epigenetic regulators and a translation stress signature

The transformation of normal to malignant cells is accompanied by substantial changes in gene expression programs through diverse mechanisms. Here, we examined the changes in the landscape of transcription start sites and alternative promoter (AP) usage and their impact on the translatome in TCL1-driven chronic lymphocytic leukemia (CLL). Our findings revealed a marked elevation of APs in CLL B cells from Eµ-Tcl1 transgenic mice, which are particularly enriched with intra-genic promoters that generate N-terminally truncated or modified proteins. Intra-genic promoter activation is mediated by (1) loss of function of 'closed chromatin' epigenetic regulators due to the generation of inactive N-terminally modified isoforms or reduced expression; (2) upregulation of transcription factors, including c-Myc, targeting the intra-genic promoters and their associated enhancers. Exogenous expression of Tcl1 in MEFs is sufficient to induce intra-genic promoters of epigenetic regulators and promote c-Myc expression. We further found a dramatic translation downregulation of transcripts bearing CNY cap-proximal trinucleotides, reminiscent of cells undergoing metabolic stress. These findings uncovered the role of Tcl1 oncogenic function in altering promoter usage and mRNA translation in leukemogenesis.

Pathogenic Roles of RNA-Binding Proteins in Sarcomas

RNA-binding proteins (RBPs) are proteins that physically and functionally bind to RNA to regulate the RNA metabolism such as alternative splicing, polyadenylation, transport, maintenance of stability, localization, and translation. There is accumulating evidence that dysregulated RBPs play an essential role in the pathogenesis of malignant tumors including a variety of types of sarcomas. On the other hand, prognosis of patients with sarcoma, especially with sarcoma in advanced stages, is very poor, and almost no effective standard treatment has been established for most of types of sarcomas so far, highlighting the urgent need for identifying novel therapeutic targets based on the deep understanding of pathogenesis. Therefore, defining the network of interactions between RBPs and disease-related RNA targets will contribute to a better understanding of sarcomagenesis and identification of a novel therapeutic target for sarcomas.

A high-resolution map of human RNA translation

Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome.

Transcriptomic diversity in human medullary thymic epithelial cells

The induction of central T cell tolerance in the thymus depends on the presentation of peripheral self-epitopes by medullary thymic epithelial cells (mTECs). This promiscuous gene expression (pGE) drives mTEC transcriptomic diversity, with non-canonical transcript initiation, alternative splicing, and expression of endogenous retroelements (EREs) representing important but incompletely understood contributors. Here we map the expression of genome-wide transcripts in immature and mature human mTECs using high-throughput 5' cap and RNA sequencing. Both mTEC populations show high splicing entropy, potentially driven by the expression of peripheral splicing factors. During mTEC maturation, rates of global transcript mis-initiation increase and EREs enriched in long terminal repeat retrotransposons are up-regulated, the latter often found in proximity to differentially expressed genes. As a resource, we provide an interactive public interface for exploring mTEC transcriptomic diversity. Our findings therefore help construct a map of transcriptomic diversity in the healthy human thymus and may ultimately facilitate the identification of those epitopes which contribute to autoimmunity and immune recognition of tumor antigens.

Temporally divergent regulatory mechanisms govern neuronal diversification and maturation in the mouse and marmoset neocortex

Mammalian neocortical neurons span one of the most diverse cell type spectra of any tissue. Cortical neurons are born during embryonic development, and their maturation extends into postnatal life. The regulatory strategies underlying progressive neuronal development and maturation remain unclear. Here we present an integrated single-cell epigenomic and transcriptional analysis of individual mouse and marmoset cortical neuron classes, spanning both early postmitotic stages of identity acquisition and later stages of neuronal plasticity and circuit integration. We found that, in both species, the regulatory strategies controlling early and late stages of pan-neuronal development diverge. Early postmitotic neurons use more widely shared and evolutionarily conserved molecular regulatory programs. In contrast, programs active during later neuronal maturation are more brain- and neuron-specific and more evolutionarily divergent. Our work uncovers a temporal shift in regulatory choices during neuronal diversification and maturation in both mice and marmosets, which likely reflects unique evolutionary constraints on distinct events of neuronal development in the neocortex.

Postmitotic differentiation of human monocytes requires cohesin-structured chromatin

Cohesin is a major structural component of mammalian genomes and is required to maintain loop structures. While acute depletion in short-term culture models suggests a limited importance of cohesin for steady-state transcriptional circuits, long-term studies are hampered by essential functions of cohesin during replication. Here, we study genome architecture in a postmitotic differentiation setting, the differentiation of human blood monocytes (MO). We profile and compare epigenetic, transcriptome and 3D conformation landscapes during MO differentiation (either into dendritic cells or macrophages) across the genome and detect numerous architectural changes, ranging from higher level compartments down to chromatin loops. Changes in loop structures correlate with cohesin-binding, as well as epigenetic and transcriptional changes during differentiation. Functional studies show that the siRNA-mediated depletion of cohesin (and to a lesser extent also CTCF) markedly disturbs loop structures and dysregulates genes and enhancers that are primarily regulated during normal MO differentiation. In addition, gene activation programs in cohesin-depleted MO-derived macrophages are disturbed. Our findings implicate an essential function of cohesin in controlling long-term, differentiation- and activation-associated gene expression programs.

How chromatin structure and gene accessibility changes during monocyte differentiation is not clearly defined. Here the authors characterize the chromatin changes during macrophage or dendritic cell maturation from monocytes and the dependence of this upon cohesin and CTCF.

Endogenous spacing enables co-processing of microRNAs and efficient combinatorial RNAi

We present Multi-miR, a microRNA-embedded shRNA system modeled after endogenous microRNA clusters that enables simultaneous expression of up to three or four short hairpin RNAs (shRNAs) from a single promoter without loss of activity, enabling robust combinatorial RNA interference (RNAi). We further developed complementary all-in-one vectors that are over one log-scale more sensitive to doxycycline-mediated activation in vitro than previous methods and resistant to shRNA inactivation in vivo. We demonstrate the utility of this system for intracranial expression of shRNAs in a glioblastoma model. Additionally, we leverage this platform to target the redundant RAF signaling node in a mouse model of KRAS-mutant cancer and show that robust combinatorial synthetic lethality efficiently abolishes tumor growth.

Precision Anti-Cancer Medicines by Oligonucleotide Therapeutics in Clinical Research Targeting Undruggable Proteins and Non-Coding RNAs

Cancer incidence and mortality continue to increase, while the conventional chemotherapeutic drugs confer limited efficacy and relevant toxic side effects. Novel strategies are urgently needed for more effective and safe therapeutics in oncology. However, a large number of proteins are considered undruggable by conventional drugs, such as the small molecules. Moreover, the mRNA itself retains oncological functions, and its targeting offers the double advantage of blocking the tumorigenic activities of the mRNA and the translation into protein. Finally, a large family of non-coding RNAs (ncRNAs) has recently emerged that are also dysregulated in cancer, but they could not be targeted by drugs directed against the proteins. In this context, this review describes how the oligonucleotide therapeutics targeting RNA or DNA sequences, are emerging as a new class of drugs, able to tackle the limitations described above. Numerous clinical trials are evaluating oligonucleotides for tumor treatment, and in the next few years some of them are expected to reach the market. We describe the oligonucleotide therapeutics targeting undruggable proteins (focusing on the most relevant, such as those originating from the MYC and RAS gene families), and for ncRNAs, in particular on those that are under clinical trial evaluation in oncology. We highlight the challenges and solutions for the clinical success of oligonucleotide therapeutics, with particular emphasis on the peculiar challenges that render it arduous to treat tumors, such as heterogeneity and the high mutation rate. In the review are presented these and other advantages offered by the oligonucleotide as an emerging class of biotherapeutics for a new era of precision anti-cancer medicine.

Compatibility rules of human enhancer and promoter sequences

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Multiomic atlas with functional stratification and developmental dynamics of zebrafish cis-regulatory elements

Zebrafish, a popular organism for studying embryonic development and for modeling human diseases, has so far lacked a systematic functional annotation program akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created a central repository to store and process zebrafish developmental functional genomic data. Our data coordination center ( https://danio-code.zfin.org ) combines a total of 1,802 sets of unpublished and re-analyzed published genomic data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements throughout development, including classes with distinct features dependent on their activity in time and space. We delineated the distinct distance topology and chromatin features between regulatory elements active during zygotic genome activation and those active during organogenesis. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predicted functional relationships between them beyond sequence similarity, thus extending the utility of zebrafish developmental genomics to mammals.

Bookend: precise transcript reconstruction with end-guided assembly

We developed Bookend, a package for transcript assembly that incorporates data from different RNA-seq techniques, with a focus on identifying and utilizing RNA 5' and 3' ends. We demonstrate that correct identification of transcript start and end sites is essential for precise full-length transcript assembly. Utilization of end-labeled reads present in full-length single-cell RNA-seq datasets dramatically improves the precision of transcript assembly in single cells. Finally, we show that hybrid assembly across short-read, long-read, and end-capture RNA-seq datasets from Arabidopsis thaliana, as well as meta-assembly of RNA-seq from single mouse embryonic stem cells, can produce reference-quality end-to-end transcript annotations.

Genes Possessing the Most Frequent DNA DSBs Are Highly Associated with Development and Cancers, and Essentially Overlap with the rDNA-Contacting Genes

Double-strand DNA breakes (DSBs) are the most deleterious and widespread examples of DNA damage. They inevitably originate from endogenous mechanisms in the course of transcription, replication, and recombination, as well as from different exogenous factors. If not properly repaired, DSBs result in cell death or diseases. Genome-wide analysis of DSBs has revealed the numerous endogenous DSBs in human chromosomes. However, until now, it has not been clear what kind of genes are preferentially subjected to breakage. We performed a genetic and epigenetic analysis of the most frequent DSBs in HEK293T cells. Here, we show that they predominantly occur in the active genes controlling differentiation, development, and morphogenesis. These genes are highly associated with cancers and other diseases. About one-third of the genes possessing frequent DSBs correspond to rDNA-contacting genes. Our data suggest that a specific set of active genes controlling morphogenesis are the main targets of DNA breakage in human cells, although there is a specific set of silent genes controlling metabolism that also are enriched in DSBs. We detected this enrichment by different activators and repressors of transcription at DSB target sites, as well breakage at promoters. We propose that both active transcription and silencing of genes give a propensity for DNA breakage. These results have implications for medicine and gene therapy.

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.

GGC repeat expansion of RILPL1 is associated with oculopharyngodistal myopathy

OBJECTIVE

Oculopharyngodistal myopathy (OPDM) is an adult-onset neuromuscular disease characterized by progressive ptosis, dysarthria, ophthalmoplegia, and distal muscle weakness. Recent studies revealed GGC repeat expansions in 5'-UTR of LRP12, GIPC1, and NOTCH2NLC are associated with OPDM. Despite these advances, around 30% of OPDM patients remain genetically undiagnosed. Herein, we aim to investigate genetic basis for undiagnosed OPDM patients in two unrelated Chinese Han families.

METHODS

Parametric linkage analysis was performed. Long-read sequencing followed by repeat-primed polymerase chain reaction (RP-PCR) and amplicon length polymerase chain reaction (AL-PCR) were used to determine the genetic cause. Targeted methylation sequencing was implemented to detect epigenetic changes. The possible pathogenesis mechanism was investigated by qPCR, immunoblotting, RNA FISH, and immunofluorescence staining of muscle biopsy samples.

RESULTS

The disease locus was mapped to 12q24.3. Subsequently, GGC repeat expansion in the promoter region of RILPL1 was identified in six OPDM patients from two families, findings consistent with a founder effect, designated as OPDM type 4 (OPDM4). Targeted methylation sequencing revealed hypermethylation at RILPL1 locus in unaffected individuals with ultralong expansion. Analysis of muscle samples showed no significant differences in RILPL1 mRNA or RILPL1 protein levels between patients and controls. Public CAGE-seq data indicated that alternative TSSs exist upstream of the RefSeq-annotated RILPL1 TSS. Strand-specific RNAseq data revealed bidirectional transcription from the RILPL1 locus. Finally, FISH/IF indicated that both sense and antisense transcripts formed RNA foci and were co-localized with hnRNPA2B1 and p62 in the intranuclear inclusions of OPDM4 patients.

INTERPRETATION

Our findings implicate abnormal GGC repeat expansions in the promoter region of RILPL1 as a novel genetic cause for OPDM, and suggest a methylation mechanism and a potential RNA toxicity mechanism are involved in OPDM4 pathogenesis. This article is protected by copyright. All rights reserved.

Systematic Analysis of Actively Transcribed Core Matrisome Genes Across Tissues and Cell Phenotypes

The extracellular matrix (ECM) is a highly dynamic, well-organized acellular network of tissue-specific biomolecules, that can be divided into structural or core ECM proteins and ECM-associated proteins. The ECM serves as a blueprint for organ development and function and, when structurally altered through mutation, altered expression, or degradation, can lead to debilitating syndromes that often affect one tissue more than another. Cross-referencing the FANTOM5 SSTAR (Semantic catalog of Samples, Transcription initiation And Regulators) and the defined catalog of core matrisome ECM (glyco)proteins, we conducted a comprehensive analysis of 511 different human samples to annotate the context-specific transcription of the individual components of the defined matrisome. Relative log expression normalized SSTAR cap analysis gene expression peak data files were downloaded from the FANTOM5 online database and filtered to exclude all cell lines and diseased tissues. Promoter-level expression values were categorized further into eight core tissue systems and three major ECM categories: proteoglycans, glycoproteins, and collagens. Hierarchical clustering and correlation analyses were conducted to identify complex relationships in promoter-driven gene expression activity. Integration of the core matrisome and curated FANTOM5 SSTAR data creates a unique tool that provides insight into the promoter-level expression of ECM-encoding genes in a tissue- and cell-specific manner. Unbiased clustering of cap analysis gene expression peak data reveals unique ECM signatures within defined tissue systems. Correlation analysis among tissue systems exposes both positive and negative correlation of ECM promoters with varying levels of significance. This tool can be used to provide new insight into the relationships between ECM components and tissues and can inform future research on the ECM in human disease and development. We invite the matrix biology community to continue to explore and discuss this dataset as part of a larger and continuing conversation about the human ECM. An interactive web tool can be found at matrixpromoterome.github.io along with additional resources that can be found at dx.doi.org/10.6084/m9.figshare.19794481 (figures) and https://figshare.com/s/e18ecbc3ae5aaf919b78 (python notebook).

In-Depth Temporal Transcriptome Profiling of an Alphaherpesvirus Using Nanopore Sequencing

In this work, a long-read sequencing (LRS) technique based on the Oxford Nanopore Technology MinION platform was used for quantifying and kinetic characterization of the poly(A) fraction of bovine alphaherpesvirus type 1 (BoHV-1) lytic transcriptome across a 12-h infection period. Amplification-based LRS techniques frequently generate artefactual transcription reads and are biased towards the production of shorter amplicons. To avoid these undesired effects, we applied direct cDNA sequencing, an amplification-free technique. Here, we show that a single promoter can produce multiple transcription start sites whose distribution patterns differ among the viral genes but are similar in the same gene at different timepoints. Our investigations revealed that the circ gene is expressed with immediate–early (IE) kinetics by utilizing a special mechanism based on the use of the promoter of another IE gene (bicp4) for the transcriptional control. Furthermore, we detected an overlap between the initiation of DNA replication and the transcription from the bicp22 gene, which suggests an interaction between the two molecular machineries. This study developed a generally applicable LRS-based method for the time-course characterization of transcriptomes of any organism.

Detection of ovarian cancer using plasma cell-free DNA methylomes

BACKGROUND

Ovarian cancer (OC) is a highly lethal gynecologic cancer, and it is hard to diagnose at an early stage. Clinically, there are no ovarian cancer-specific markers for early detection. Here, we demonstrate the use of cell-free DNA (cfDNA) methylomes to detect ovarian cancer, especially the early-stage OC.

EXPERIMENTAL DESIGN

Plasma from 74 epithelial ovarian cancer patients, 86 healthy volunteers, and 20 patients with benign pelvic masses was collected. The cfDNA methylomes of these samples were generated by cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). The differentially methylated regions (DMRs) were identified by the contrasts between tumor and non-tumor groups, and the discrimination performance was evaluated with the iterative training and testing method.

RESULTS

The DMRs identified for cfDNA methylomes can well discriminate tumor groups and non-tumor groups (ROC values from 0.86 to 0.98). The late-stage top 300 DMRs are more late-stage-specific and failed to detect early-stage OC. However, the early-stage markers have the potential to discriminate all-stage OCs from non-tumor samples.

CONCLUSIONS

This study demonstrates that cfDNA methylomes generated with cfMeDIP-seq could be used to identify OC-specific biomarkers for OC, especially early OC detection. To detect early-stage OC, the biomarkers should be directly identified from early OC plasma samples rather than mix-stage ones. Further exploration of DMRs from a k larger early-stage OC cohort is warranted.

Somatic point mutations are enriched in non-coding RNAs with possible regulatory function in breast cancer

Non-coding RNAs (ncRNAs) form a large portion of the mammalian genome. However, their biological functions are poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we analyze de novo somatic point mutations from the International Cancer Genome Consortium (ICGC) whole-genome sequencing data of 1,855 breast cancer samples. We identify 1030 candidates of ncRNAs that are significantly and explicitly mutated in breast cancer samples. By integrating data from the ENCODE regulatory features and FANTOM5 expression atlas, we show that the candidate ncRNAs significantly enrich active chromatin histone marks (1.9 times), CTCF binding sites (2.45 times), DNase accessibility (1.76 times), HMM predicted enhancers (2.26 times) and eQTL polymorphisms (1.77 times). Importantly, we show that the 1030 ncRNAs contain a much higher level (3.64 times) of breast cancer-associated genome-wide association (GWAS) single nucleotide polymorphisms (SNPs) than genome-wide expectation. Such enrichment has not been seen with GWAS SNPs from other cancers. Using breast cell line related Hi-C data, we then show that 82% of our candidate ncRNAs (1.9 times) significantly interact with the promoter of protein-coding genes, including previously known cancer-associated genes, suggesting the critical role of candidate ncRNA genes in the activation of essential regulators of development and differentiation in breast cancer. We provide an extensive web-based resource (https://www.ihealthe.unsw.edu.au/research) to communicate our results with the research community. Our list of breast cancer-specific ncRNA genes has the potential to provide a better understanding of the underlying genetic causes of breast cancer. Lastly, the tool developed in this study can be used to analyze somatic mutations in all cancers.

The SomaGene tool is developed to identify non-coding RNAs (ncRNAs) mutated in breast cancer but can be used for other cancers. Candidate ncRNAs are shown to be enriched for regulatory features and to contain specific trait loci polymorphisms.

Differential cofactor dependencies define distinct types of human enhancers

All multicellular organisms rely on differential gene transcription regulated by genomic enhancers, which function through cofactors that are recruited by transcription factors^1,2. Emerging evidence suggests that not all cofactors are required at all enhancers^3-5, yet whether these observations reflect more general principles or distinct types of enhancers remained unknown. Here we categorized human enhancers by their cofactor dependencies and show that these categories provide a framework to understand the sequence and chromatin diversity of enhancers and their roles in different gene-regulatory programmes. We quantified enhancer activities along the entire human genome using STARR-seq⁶ in HCT116 cells, following the rapid degradation of eight cofactors. This analysis identified different types of enhancers with distinct cofactor requirements, sequences and chromatin properties. Some enhancers were insensitive to the depletion of the core Mediator subunit MED14 or the bromodomain protein BRD4 and regulated distinct transcriptional programmes. In particular, canonical Mediator⁷ seemed dispensable for P53-responsive enhancers, and MED14-depleted cells induced endogenous P53 target genes. Similarly, BRD4 was not required for the transcription of genes that bear CCAAT boxes and a TATA box (including histone genes and LTR12 retrotransposons) or for the induction of heat-shock genes. This categorization of enhancers through cofactor dependencies reveals distinct enhancer types that can bypass broadly utilized cofactors, which illustrates how alternative ways to activate transcription separate gene expression programmes and provide a conceptual framework to understand enhancer function and regulatory specificity.

Meiotic cDNA libraries reveal gene truncations and mitochondrial proteins important for competitive fitness in Saccharomyces cerevisiae

Gametogenesis is an evolutionarily conserved developmental program whereby a diploid progenitor cell undergoes meiosis and cellular remodeling to differentiate into haploid gametes, the precursors for sexual reproduction. Even in the simple eukaryotic organism Saccharomyces cerevisiae, the meiotic transcriptome is very rich and complex, thereby necessitating new tools for functional studies. Here, we report the construction of 5 stage-specific, inducible complementary DNA libraries from meiotic cells that represent over 84% of the genes found in the budding yeast genome. We employed computational strategies to detect endogenous meiotic transcript isoforms as well as library-specific gene truncations. Furthermore, we developed a robust screening pipeline to test the effect of each complementary DNA on competitive fitness. Our multiday proof-of-principle time course revealed 877 complementary DNAs that were detrimental for competitive fitness when overexpressed. The list included mitochondrial proteins that cause dose-dependent disruption of cellular respiration as well as library-specific gene truncations that expose a dominant negative effect on competitive growth. Together, these high-quality complementary DNA libraries provide an important tool for systematically identifying meiotic genes, transcript isoforms, and protein domains that are important for a specific biological function.