SwissRegulon, a database of genome-wide annotations of regulatory sites: recent updates

Recent advances in designing synthetic plant regulatory modules

Introducing novel functions in plants through synthetic multigene circuits requires strict transcriptional regulation. Currently, the use of natural regulatory modules in synthetic circuits is hindered by our limited knowledge of complex plant regulatory mechanisms, the paucity of characterized promoters, and the possibility of crosstalk with endogenous circuits. Synthetic regulatory modules can overcome these limitations. This article introduces an integrative de novo approach for designing plant synthetic promoters by utilizing the available online tools and databases. The recent achievements in designing and validating synthetic plant promoters, enhancers, transcription factors, and the challenges of establishing synthetic circuits in plants are also discussed.

Integrative multiomics reveals common endotypes across PSEN1, PSEN2, and APP mutations in familial Alzheimer's disease

BACKGROUND

PSEN1, PSEN2, and APP mutations cause Alzheimer's disease (AD) with an early age at onset (AAO) and progressive cognitive decline. PSEN1 mutations are more common and generally have an earlier AAO; however, certain PSEN1 mutations cause a later AAO, similar to those observed in PSEN2 and APP.

METHODS

We examined whether common disease endotypes exist across these mutations with a later AAO (~ 55 years) using hiPSC-derived neurons from familial Alzheimer's disease (FAD) patients harboring mutations in PSEN1A79V, PSEN2N141I, and APPV717I and mechanistically characterized by integrating RNA-seq and ATAC-seq.

RESULTS

We identified common disease endotypes, such as dedifferentiation, dysregulation of synaptic signaling, repression of mitochondrial function and metabolism, and inflammation. We ascertained the master transcriptional regulators associated with these endotypes, including REST, ASCL1, and ZIC family members (activation), and NRF1 (repression).

CONCLUSIONS

FAD mutations share common regulatory changes within endotypes with varying severity, resulting in reversion to a less-differentiated state. The regulatory mechanisms described offer potential targets for therapeutic interventions.

Systematic functional characterization of non-coding regulatory SNPs associated with central obesity

Central obesity is associated with higher risk of developing a wide range of diseases independent of overall obesity. Genome-wide association studies (GWASs) have identified more than 300 susceptibility loci associated with central obesity. However, the functional understanding of these loci is limited by the fact that most loci are in non-coding regions. To address this issue, our study first prioritized 2,034 single-nucleotide polymorphisms (SNPs) based on fine-mapping and epigenomic annotation analysis. Subsequently, we employed self-transcribing active regulatory region sequencing (STARR-seq) to systematically evaluate the enhancer activity of these prioritized SNPs. The resulting data analysis identified 141 SNPs with allelic enhancer activity. Further analysis of allelic transcription factor (TF) binding prioritized 20 key TFs mediating the central-obesity-relevant genetic regulatory network. Finally, as an example, we illustrate the molecular mechanisms of how rs8079062 acts as an allele-specific enhancer to regulate the expression of its targeted RNF157. We also evaluated the role of RNF157 in the adipogenic differentiation process. In conclusion, our results provide an important resource for understanding the genetic regulatory mechanisms underlying central obesity.

Identification of an ArgR-controlled promoter within the outermost region of the IS10R mobile element

The transposon Tn10 is a prevalent composite element often detected in enteric bacteria, including those obtained from clinical samples. The Tn10 is flanked by two IS10 elements that work together in mediating transposition. IS10-right (IS10R) promotes transposition, while IS10-left lacks a functional transposase and cannot transpose independently. IS10R contains a weak promoter crucial for transposase transcription (pIN), along with two outward-oriented promoters, pOUT and OUTIIp, which may influence the expression of adjacent genes flanking the transposition site. Here, we report the identification of a novel outward-facing promoter, pOUT70, and a functional translation initiation region (TIR) within the last 70 nucleotides of IS10R. Furthermore, we show that pOUT70 is negatively regulated by ArgR and positively controlled by IHF, and we demonstrate that pOUT70 enables growth phase-dependent expression of a truncated yet constitutively active version of the histidine kinase BarA. These findings underscore the significance of IS elements in enhancing downstream gene expression, and highlights the role of outward-facing promoters in derepressing virulence factors or acquiring antibiotic resistance.

IMPORTANCE

Mobile genetic elements are small DNA fragments that can relocate within the genome, causing either gene inactivation or enhanced gene expression. Our research identified a new functional promoter and mRNA translation region within the IS10R element, which is part of the widely distributed Tn10 transposon. We found that the global regulators ArgR and IHF control the activity of this promoter. Additionally, insertion of this mini-Tn10 derivative into the barA gene resulted in the expression of a truncated but constitutive active form of the BarA sensor kinase. Overall, our work sheds light on how mobile genetic elements could impact the physiology and virulence of opportunistic pathogenic bacteria.

An integrated machine-learning model to predict nucleosome architecture

We demonstrate that nucleosomes placed in the gene body can be accurately located from signal decay theory assuming two emitters located at the beginning and at the end of genes. These generated wave signals can be in phase (leading to well defined nucleosome arrays) or in antiphase (leading to fuzzy nucleosome architectures). We found that the first (+1) and the last (-last) nucleosomes are contiguous to regions signaled by transcription factor binding sites and unusual DNA physical properties that hinder nucleosome wrapping. Based on these analyses, we developed a method that combines Machine Learning and signal transmission theory able to predict the basal locations of the nucleosomes with an accuracy similar to that of experimental MNase-seq based methods.

Single Cell Profiling in the Sox10 Dom/+ Hirschsprung Mouse Implicates Hoxa6 in Enteric Neuron Lineage Allocation

Background & Aims

Enteric nervous system (ENS) development requires migration, proliferation, and appropriate neuronal diversification from progenitors to enable normal gastrointestinal (GI) motility. Sox10 deficit causes aganglionosis, modeling Hirschsprung disease, and disrupts ratios of postnatal enteric neurons in proximal ganglionated bowel. How Sox10 deficiency alters ratios of enteric neuron subtypes is unclear. Sox10's prominent expression in enteric neural crest-derived progenitors (ENCP) and lack of this gene in enteric neurons led us to examine Sox10 Dom effects ENS progenitors and early differentiating enteric neurons.

Methods

ENS progenitors, developing neurons, and enteric glia were isolated from Sox10 +/+ and Sox10 Dom/+ littermates for single-cell RNA sequencing (scRNA-seq). scRNA-seq data was processed to identify cell type-specific markers, differentially expressed genes, cell fate trajectories, and gene regulatory network activity between genotypes. Hybridization chain reaction (HCR) validated expression changes detected in scRNA-seq.

Results

scRNA-seq profiles revealed three neuronal lineages emerging from cycling progenitors via two transition pathways accompanied by elevated activity of Hox gene regulatory networks (GRN) as progenitors transition to neuronal fates. Sox10 Dom/+ scRNA-seq profiles exhibited a novel progenitor cluster, decreased abundance of cells in transitional states, and shifts in cell distributions between two neuronal trajectories. Hoxa6 was differentially expressed in the neuronal lineages impacted in Sox10 Dom/+ mutants and HCR identified altered Hoxa6 expression in early developing neurons of Sox10 Dom/+ ENS.

Conclusions

Sox10 Dom/+ mutation shifts enteric neuron types by altering neuronal trajectories during early ENS lineage segregation. Multiple neurogenic transcription factors are reduced in Sox10 Dom/+ scRNA-seq profiles including multiple Hox genes. This is the first report that implicates Hox genes in lineage diversification of enteric neurons.

Multiscale regulation of nutrient stress responses in Escherichia coli from chromatin structure to small regulatory RNAs

Recent research has indicated the presence of heterochromatin-like regions of extended protein occupancy and transcriptional silencing of bacterial genomes. We utilized an integrative approach to track chromatin structure and transcription in E. coli K-12 across a wide range of nutrient conditions. In the process, we identified multiple loci which act similarly to facultative heterochromatin in eukaryotes, normally silenced but permitting expression of genes under specific conditions. We also found a strong enrichment of small regulatory RNAs (sRNAs) among the set of differentially expressed transcripts during nutrient stress. Using a newly developed bioinformatic pipeline, the transcription factors regulating sRNA expression were bioinformatically predicted, with experimental follow-up revealing novel relationships for 36 sRNA-transcription factors candidates. Direct regulation of sRNA expression was confirmed by mutational analysis for five sRNAs of metabolic interest: IsrB, CsrB and CsrC, GcvB, and GadY. Our integrative analysis thus reveals additional layers of complexity in the nutrient stress response in E. coli and provides a framework for revealing similar poorly understood regulatory logic in other organisms.

PGR-KITLG signaling drives a tumor-mast cell regulatory feedback to modulate apoptosis of breast cancer cells

The immune microenvironment constructed by tumor-infiltrating immune cells and the molecular phenotype defined by hormone receptors (HRs) have been implicated as decisive factors in the regulation of breast cancer (BC) progression. Here, we found that the infiltration of mast cells (MCs) informed impaired prognoses in HR(+) BC but predicted improved prognoses in HR(-) BC. However, molecular features of MCs in different BC remain unclear. We next discovered that HR(-) BC cells were prone to apoptosis under the stimulation of MCs, whereas HR(+) BC cells exerted anti-apoptotic effects. Mechanistically, in HR(+) BC, the KIT ligand (KITLG), a major mast cell growth factor in recruiting and activating MCs, could be transcriptionally upregulated by the progesterone receptor (PGR), and elevate the production of MC-derived granulin (GRN). GRN attenuates TNFα-induced apoptosis in BC cells by competitively binding to TNFR1. Furthermore, disruption of PGR-KITLG signaling by knocking down PGR or using the specific KITLG-cKIT inhibitor iSCK03 potently enhanced the sensitivity of HR(+) BC cells to MC-induced apoptosis and exerted anti-tumor activity. Collectively, these results demonstrate that PGR-KITLG signaling in BC cells preferentially induces GRN expression in MCs to exert anti-apoptotic effects, with potential value in developing precision medicine approaches for diagnosis and treatment.

Prediction and Analysis of Transcription Factor Binding Sites: Practical Examples and Case Studies Using R Programming

Transcription factors (TFs) bind to specific regions of DNA known as transcription factor binding sites (TFBSs) and modulate gene expression by interacting with the transcriptional machinery. TFBSs are typically located upstream of target genes, within a few thousand base pairs of the transcription start site. The binding of TFs to TFBSs influences the recruitment of the transcriptional machinery, thereby regulating gene transcription in a precise and specific manner. This chapter provides practical examples and case studies demonstrating the extraction of upstream gene regions from the genome, identification of TFBSs using PWMEnrich R/Bioconductor package, interpretation of results, and preparation of publication-ready figures and tables. The EOMES promoter is used as a case study for single DNA sequence analysis, revealing potential regulation by the LHX9-FOXP1 complex during embryonic development. Additionally, an example is presented on how to investigate TFBSs in the upstream regions of a group of genes, using a case study of differentially expressed genes in response to human parainfluenza virus type 1 (HPIV1) infection and interferon-beta. Key regulators identified in this context include the STAT1:STAT2 heterodimer and interferon regulatory factor family proteins. The presented protocol is designed to be accessible to individuals with basic computer literacy. Understanding the interactions between TFs and TFBSs provides insights into the complex transcriptional regulatory networks that govern gene expression, with broad implications for several fields such as developmental biology, immunology, and disease research.

Computational Inference of Gene Regulatory Network Using Genome-wide ChIP-X Data

Gene regulatory network is the architecture of transcription factors (TFs) and their gene targets, which help in controlling their expression as required by a phenotype during various environmental perturbations. Inferring the regulatory network from the high-throughput data needs an algorithmic approach involving statistical analysis. There are several interaction databases such as JASPAR and SwissRegulon that provide information for TFs-targets pair interaction, which are estimated based on experimental and prediction procedures. These repositories are majorly used for predicting the complex structure of GRNs either with or without gene expression data. Here we described and discussed the step-wise procedures to extract the interaction data for a desired set of target-TFs from the JASPAR database, and used that information to infer the network by using the igraph library. Further, we also mentioned the important parameters for analyzing the different properties of the network. The described procedure will be helpful in discerning the GRN based on the set of TF-gene pairs.

High-throughput PRIME-editing screens identify functional DNA variants in the human genome

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and single-base resolution manner remains challenging. Here, we develop a pooled prime-editing screen method, PRIME, that can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated single-base resolution analysis. Next, we applied PRIME to functionally characterize 1,304 genome-wide association study (GWAS)-identified non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate that PRIME is capable of characterizing genetic variants at single-base resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

Neuronal transcription of autism gene PTCHD1 is regulated by a conserved downstream enhancer sequence

Patched domain-containing 1 (PTCHD1) is a well-established susceptibility gene for autism spectrum disorder (ASD) and intellectual disability (ID). Previous studies have suggested that alterations in the dosage of PTCHD1 may contribute to the etiology of both ASD and ID. However, there has not yet been a thorough investigation regarding mechanisms that regulate PTCHD1 expression. We sought to characterize the Ptchd1 promoter in a mouse neuronal model, as well as to identify and validate cis regulatory elements. We defined specific regions of the Ptchd1 promoter essential for robust expression in P19-induced neurons. Evolutionarily-conserved putative transcription factor binding sites within these regions were subsequently identified. Using a pairwise comparison of chromatin accessibility between mouse forebrain and liver tissues, a candidate regulatory region, ~ 9.1 kbp downstream of the Ptchd1 stop codon was defined. This region harbours two ENCODE-predicted enhancer cis-regulatory elements. Further, using DNase footprint analysis, a putative YY1-binding motif was also identified. Genomic deletion of the entire 8 kbp downstream open chromatin region attenuated Ptchd1 transcription by over 60% in our neuronal model, corroborating its predicted regulatory function. This study provides mechanistic insights related to the expression of PTCHD1, and provides important context to interpret genetic and genomic variation at this locus which may influence neurodevelopment.

Ancestry-related differences in chromatin accessibility and gene expression of APOE ε4 are associated with Alzheimer's disease risk

INTRODUCTION

European local ancestry (ELA) surrounding apolipoprotein E (APOE) ε4 confers higher risk for Alzheimer's disease (AD) compared to African local ancestry (ALA). We demonstrated significantly higher APOE ε4  expression in ELA versus ALA in AD brains from APOE ε4/ε4 carriers. Chromatin accessibility differences could contribute to these expression changes.

METHODS

We performed single nuclei assays for transposase accessible chromatin sequencing from the frontal cortex of six ALA and six ELA AD brains, homozygous for local ancestry and APOE ε4.

RESULTS

Our results showed an increased chromatin accessibility at the APOE ε4  promoter area in ELA versus ALA astrocytes. This increased accessibility in ELA astrocytes extended genome wide. Genes with increased accessibility in ELA in astrocytes were enriched for synapsis, cholesterol processing, and astrocyte reactivity.

DISCUSSION

Our results suggest that increased chromatin accessibility of APOE ε4  in ELA astrocytes contributes to the observed elevated APOE ε4  expression, corresponding to the increased AD risk in ELA versus ALA APOE ε4/ε4 carriers.

Spatial distribution and functional relevance of FGFR1 and FGFR2 expression for glioblastoma tumor invasion

Glioblastoma is the most lethal brain cancer in adults. These incurable tumors are characterized by profound heterogeneity, therapy resistance, and diffuse infiltration. These traits have been linked to cancer stem cells, which are important for glioblastoma tumor progression and recurrence. The fibroblast growth factor receptor 1 (FGFR1) signaling pathway is a known regulator of therapy resistance and cancer stemness in glioblastoma. FGFR1 expression shows intertumoral heterogeneity and higher FGFR1 expression is associated with a significantly poorer survival in glioblastoma patients. The role of FGFR1 in tumor invasion has been studied in many cancers, but whether and how FGFR1 mediates glioblastoma invasion remains to be determined. Here, we investigated the distribution and functional relevance of FGFR1 and FGFR2 in human glioblastoma xenograft models. We found FGFR1, but not FGFR2, expressed in invasive glioblastoma cells. Loss of FGFR1, but not FGFR2, significantly reduced cell migration in vitro and tumor invasion in human glioblastoma xenografts. Comparative analysis of RNA-sequencing data of FGFR1 and FGFR2 knockdown glioblastoma cells revealed a FGFR1-specific gene regulatory network associated with tumor invasion. Our study reveals new gene candidates linked to FGFR1-mediated glioblastoma invasion.

High throughput PRIME editing screens identify functional DNA variants in the human genome

Despite tremendous progress in detecting DNA variants associated with human disease, interpreting their functional impact in a high-throughput and base-pair resolution manner remains challenging. Here, we develop a novel pooled prime editing screen method, PRIME, which can be applied to characterize thousands of coding and non-coding variants in a single experiment with high reproducibility. To showcase its applications, we first identified essential nucleotides for a 716 bp MYC enhancer via PRIME-mediated saturation mutagenesis. Next, we applied PRIME to functionally characterize 1,304 non-coding variants associated with breast cancer and 3,699 variants from ClinVar. We discovered that 103 non-coding variants and 156 variants of uncertain significance are functional via affecting cell fitness. Collectively, we demonstrate PRIME capable of characterizing genetic variants at base-pair resolution and scale, advancing accurate genome annotation for disease risk prediction, diagnosis, and therapeutic target identification.

Gene-by-environment interactions are pervasive among natural genetic variants

Gene-by-environment (GxE) interactions, in which a genetic variant's phenotypic effect is condition specific, are fundamental for understanding fitness landscapes and evolution but have been difficult to identify at the single-nucleotide level. Although many condition-specific quantitative trait loci (QTLs) have been mapped, these typically contain numerous inconsequential variants in linkage, precluding understanding of the causal GxE variants. Here, we introduce BARcoded Cas9 retron precise parallel editing via homology (CRISPEY-BAR), a high-throughput precision genome editing strategy, and use it to map GxE interactions of naturally occurring genetic polymorphisms impacting yeast growth. We identified hundreds of GxE variants within condition-specific QTLs, revealing unexpected genetic complexity. Moreover, we found that 93.7% of non-neutral natural variants within ergosterol biosynthesis pathway genes showed GxE interactions, including many impacting antifungal drug resistance through diverse molecular mechanisms. In sum, our results suggest an extremely complex, context-dependent fitness landscape characterized by pervasive GxE interactions while also demonstrating massively parallel genome editing as an effective means for investigating this complexity.

Application of single-cell RNA sequencing on human testicular samples: a comprehensive review

So far there has been no comprehensive review using systematic literature search strategies to show the application of single-cell RNA sequencing (scRNA-seq) in the human testis of the whole life cycle (from embryos to aging males). Here, we summarized the application of scRNA-seq analyses on various human testicular biological samples. A systematic search was conducted in PubMed and Gene Expression Omnibus (GEO), focusing on English researches published after 2009. Articles related to GEO data-series were also retrieved in PubMed or BioRxiv. 81 full-length studies were finally included in the review. ScRNA-seq has been widely used on different human testicular samples with various library strategies, and new cell subtypes such as State 0 spermatogonial stem cells (SSC) and stage_a/b/c Sertoli cells (SC) were identified. For the development of normal testes, scRNA-seq-based evidence showed dynamic transcriptional changes of both germ cells and somatic cells from embryos to adults. And dysregulated metabolic signaling or hedgehog signaling were revealed by scRNA-seq in aged SC or Leydig cells (LC), respectively. For infertile males, scRNA-seq studies revealed profound changes of testes, such as the increased proportion of immature SC/LC of Klinefelter syndrome, the somatic immaturity and altered germline autophagy of patients with non-obstructive azoospermia, and the repressed differentiation of SSC in trans-females receiving testosterone inhibition therapy. Besides, the re-analyzing of public scRNA-seq data made further discoveries such as the potential vulnerability of testicular SARS-CoV-2 infection, and both evolutionary conservatism and divergence among species. ScRNA-seq analyses would unveil mechanisms of testes' development and changes so as to help developing novel treatments for male infertility.

Enhancer variants on chromosome 2p14 regulating SPRED2 and ACTR2 act as a signal amplifier to protect against rheumatoid arthritis

Genome-wide association studies (GWASs) have repeatedly reported multiple non-coding single-nucleotide polymorphisms (SNPs) at 2p14 associated with rheumatoid arthritis (RA), but their functional roles in the pathological mechanisms of RA remain to be explored. In this study, we integrated a series of bioinformatics and functional experiments and identified three intronic RA SNPs (rs1876518, rs268131, and rs2576923) within active enhancers that can regulate the expression of SPRED2 directly. At the same time, SPRED2 and ACTR2 influence each other as a positive feedback signal amplifier to strengthen the protective role in RA by inhibiting the migration and invasion of rheumatoid fibroblast-like synoviocytes (FLSs). In particular, the transcription factor CEBPB preferentially binds to the rs1876518-T allele to increase the expression of SPRED2 in FLSs. Our findings decipher the molecular mechanisms behind the GWAS signals at 2p14 for RA and emphasize SPRED2 as a potential candidate gene for RA, providing a potential target and direction for precise treatment of RA.

Antisense-oligonucleotide-mediated perturbation of long non-coding RNA reveals functional features in stem cells and across cell types

Within the scope of the FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem cells (iPSCs) and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition. From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell-type enrichment analysis identifies lncRNAs associated with pluripotency, while the knockdown of LINC02595, CATG00000090305.1, and RP11-148B6.2 modulates colony formation of iPSCs. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit a consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights that molecular phenotyping is more comprehensive in revealing affected pathways.

CTCF: an R/bioconductor data package of human and mouse CTCF binding sites

Summary

CTCF (CCCTC-binding factor) is an 11-zinc-finger DNA binding protein which regulates much of the eukaryotic genome's 3D structure and function. The diversity of CTCF binding motifs has led to a fragmented landscape of CTCF binding data. We collected position weight matrices of CTCF binding motifs and defined strand-oriented CTCF binding sites in the human and mouse genomes, including the recent Telomere to Telomere and mm39 assemblies. We included selected experimentally determined and predicted CTCF binding sites, such as CTCF-bound cis-regulatory elements from SCREEN ENCODE. We recommend filtering strategies for CTCF binding motifs and demonstrate that liftOver is a viable alternative to convert CTCF coordinates between assemblies. Our comprehensive data resource and usage recommendations can serve to harmonize and strengthen the reproducibility of genomic studies utilizing CTCF binding data.

Availability and implementation

https://bioconductor.org/packages/CTCF. Companion website: https://dozmorovlab.github.io/CTCF/; Code to reproduce the analyses: https://github.com/dozmorovlab/CTCF.dev.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

MSALigMap-A Tool for Mapping Active-Site Amino Acids in PDB Structures onto Known and Novel Unannotated Homologous Sequences with Similar Function

MSALigMap (Multiple Sequence Alignment Ligand Mapping) is a tool for mapping active-site amino-acid residues that bind selected ligands on to target protein sequences of interest. Users can also provide novel sequences (unavailable in public databases) for analysis. MSALigMap is written in Python. There are several tools and servers available for comparing and mapping active-site amino-acid residues among protein structures. However, there has not previously been a tool for mapping ligand binding amino-acid residues onto protein sequences of interest. Using MSALigMap, users can compare multiple protein sequences, such as those from different organisms or clinical strains, with sequences of proteins with crystal structures in PDB that are bound with the ligand/drug and DNA of interest. This allows users to easily map the binding residues and to predict the consequences of different mutations observed in the binding site. The MSALigMap server can be accessed at https://albiorix.bioenv.gu.se/MSALigMap/HomePage.py.

A 5′ UTR Mutation Contributes to Down-Regulation of Bbs7 in the Berlin Fat Mouse

The Bardet–Biedl Syndrome 7 (Bbs7) gene was identified as the most likely candidate gene causing juvenile obesity in the Berlin Fat Mouse Inbred (BFMI) line. Bbs7 expression is significantly lower in the brain, adipose tissue, and liver of BFMI mice compared to lean C57BL/6NCrl (B6N) mice. A DNA sequence comparison between BFMI and B6N revealed 16 sequence variants in the Bbs7 promoter region. Here, we tested if these mutations contribute to the observed differential expression of Bbs7. In a cell-based dual-luciferase assay, we compared the effects of the BFMI and the B6N haplotypes of different regions of the Bbs7 promotor on the reporter gene expression. A single-nucleotide polymorphism (SNP) was identified causing a significant reduction in the reporter gene expression. This SNP (rs29947545) is located in the 5′ UTR of Bbs7 at Chr3:36.613.350. The SNP is not unique to BFMI mice but also occurs in several other mouse strains, where the BFMI allele is not associated with lower Bbs7 transcript amounts. Thus, we suggest a compensatory mutation in the other mouse strains that keeps Bbs7 expression at the normal level. This compensatory mechanism is missing in BFMI mice and the cell lines tested.

Genome interpretation using in silico predictors of variant impact

Estimating the effects of variants found in disease driver genes opens the door to personalized therapeutic opportunities. Clinical associations and laboratory experiments can only characterize a tiny fraction of all the available variants, leaving the majority as variants of unknown significance (VUS). In silico methods bridge this gap by providing instant estimates on a large scale, most often based on the numerous genetic differences between species. Despite concerns that these methods may lack reliability in individual subjects, their numerous practical applications over cohorts suggest they are already helpful and have a role to play in genome interpretation when used at the proper scale and context. In this review, we aim to gain insights into the training and validation of these variant effect predicting methods and illustrate representative types of experimental and clinical applications. Objective performance assessments using various datasets that are not yet published indicate the strengths and limitations of each method. These show that cautious use of in silico variant impact predictors is essential for addressing genome interpretation challenges.

Promoter hypermethylation of GALR1 acts as an early epigenetic susceptibility event in colorectal carcinogenesis

Epigenetics play an essential role in colorectal neoplasia process. There is a need to determine the appropriateness of epigenetic biomarkers for early detection as well as expand our understanding of the carcinogenic process. Therefore, the aim of the study was to assess how DNA methylation pattern of GALR1 gene evolves in a sample set representing colorectal neoplastic progression. The study was designed into three phases. Firstly, Methylation status of GALR1 was assessed with genome-wide DNA methylation beadchip and pyrosequencing assays in colorectal lesions and paired normal tissues. Then, linear mixed-effects modeling analyses were applied to describe the trend of DNA methylation during the progression of colorectal neoplasia. In the third phase, quantitative RT-PCR was used to examine GALR1 expression in patients with precursor lesion and colorectal cancer. We found that significant hypermethylation of GALR1 promoter was a widely existent modification in CRCs (P < 0.001). When further examined methylation pattern of GALR1 during neoplastic progression of CRC, we found that DNA methylation level of GALR1 showed a significant stepwise increase from normal to hyperplastic polyps, to adenomas and to carcinoma samples (P < 0.001). Besides, loss of mRNA expression is a common accompaniment to adenomas and carcinomas. Public omics data analyses showed an inverse correlation between gene expression and DNA methylation (P < 0.001). Our findings indicate that epigenetic alteration of GALR1 promoter is gradually accumulated during the colorectal neoplastic progression. It can potentially be a promising biomarker used for screening and surveillance of colorectal cancer.

Comparative genomic analysis of the human genome and six bat genomes using unsupervised machine learning: Mb-level CpG and TFBS islands

BACKGROUND

Emerging infectious disease-causing RNA viruses, such as the SARS-CoV-2 and Ebola viruses, are thought to rely on bats as natural reservoir hosts. Since these zoonotic viruses pose a great threat to humans, it is important to characterize the bat genome from multiple perspectives. Unsupervised machine learning methods for extracting novel information from big sequence data without prior knowledge or particular models are highly desirable for obtaining unexpected insights. We previously established a batch-learning self-organizing map (BLSOM) of the oligonucleotide composition that reveals novel genome characteristics from big sequence data.

RESULTS

In this study, using the oligonucleotide BLSOM, we conducted a comparative genomic study of humans and six bat species. BLSOM is an explainable-type machine learning algorithm that reveals the diagnostic oligonucleotides contributing to sequence clustering (self-organization). When unsupervised machine learning reveals unexpected and/or characteristic features, these features can be studied in more detail via the much simpler and more direct standard distribution map method. Based on this combined strategy, we identified the Mb-level enrichment of CG dinucleotide (Mb-level CpG islands) around the termini of bat long-scaffold sequences. In addition, a class of CG-containing oligonucleotides were enriched in the centromeric and pericentromeric regions of human chromosomes. Oligonucleotides longer than tetranucleotides often represent binding motifs for a wide variety of proteins (e.g., transcription factor binding sequences (TFBSs)). By analyzing the penta- and hexanucleotide composition, we observed the evident enrichment of a wide range of hexanucleotide TFBSs in centromeric and pericentromeric heterochromatin regions on all human chromosomes.

CONCLUSION

Function of transcription factors (TFs) beyond their known regulation of gene expression (e.g., TF-mediated looping interactions between two different genomic regions) has received wide attention. The Mb-level TFBS and CpG islands are thought to be involved in the large-scale nuclear organization, such as centromere and telomere clustering. TFBSs, which are enriched in centromeric and pericentromeric heterochromatin regions, are thought to play an important role in the formation of nuclear 3D structures. Our machine learning-based analysis will help us to understand the differential features of nuclear 3D structures in the human and bat genomes.

FABIAN-variant: predicting the effects of DNA variants on transcription factor binding

While great advances in predicting the effects of coding variants have been made, the assessment of non-coding variants remains challenging. This is especially problematic for variants within promoter regions which can lead to over-expression of a gene or reduce or even abolish its expression. The binding of transcription factors to the DNA can be predicted using position weight matrices (PWMs). More recently, transcription factor flexible models (TFFMs) have been introduced and shown to be more accurate than PWMs. TFFMs are based on hidden Markov models and can account for complex positional dependencies. Our new web-based application FABIAN-variant uses 1224 TFFMs and 3790 PWMs to predict whether and to which degree DNA variants affect the binding of 1387 different human transcription factors. For each variant and transcription factor, the software combines the results of different models for a final prediction of the resulting binding-affinity change. The software is written in C++ for speed but variants can be entered through a web interface. Alternatively, a VCF file can be uploaded to assess variants identified by high-throughput sequencing. The search can be restricted to variants in the vicinity of candidate genes. FABIAN-variant is available freely at https://www.genecascade.org/fabian/.

Transcription factor specificity limits the number of DNA-binding motifs

We study the limits imposed by transcription factor specificity on the maximum number of binding motifs that can coexist in a gene regulatory network, using the SwissRegulon Fantom5 collection of 684 human transcription factor binding sites as a model. We describe transcription factor specificity using regular expressions and find that most human transcription factor binding site motifs are separated in sequence space by one to three motif-discriminating positions. We apply theorems based on the pigeonhole principle to calculate the maximum number of transcription factors that can coexist given this degree of specificity, which is in the order of ten thousand and would fully utilize the space of DNA subsequences. Taking into account an expanded DNA alphabet with modified bases can further raise this limit by several orders of magnitude, at a lower level of sequence space usage. Our results may guide the design of transcription factors at both the molecular and system scale.

proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms

The transcriptional regulatory network in prokaryotes controls global gene expression mostly through transcription factors (TFs), which are DNA-binding proteins. Chromatin immunoprecipitation (ChIP) with DNA sequencing methods can identify TF binding sites across the genome, providing a bottom-up, mechanistic understanding of how gene expression is regulated. ChIP provides indispensable evidence toward the goal of acquiring a comprehensive understanding of cellular adaptation and regulation, including condition-specificity. ChIP-derived data's importance and labor-intensiveness motivate its broad dissemination and reuse, which is currently an unmet need in the prokaryotic domain. To fill this gap, we present proChIPdb (prochipdb.org), an information-rich, interactive web database. This website collects public ChIP-seq/-exo data across several prokaryotes and presents them in dashboards that include curated binding sites, nucleotide-resolution genome viewers, and summary plots such as motif enrichment sequence logos. Users can search for TFs of interest or their target genes, download all data, dashboards, and visuals, and follow external links to understand regulons through biological databases and the literature. This initial release of proChIPdb covers diverse organisms, including most major TFs of Escherichia coli, and can be expanded to support regulon discovery across the prokaryotic domain.

Enhancer RNA Expression in Response to Glucocorticoid Treatment in Murine Macrophages

Glucocorticoids are potent anti-inflammatory drugs; however, their molecular mode of action remains complex and elusive. They bind to the glucocorticoid receptor (GR), a nuclear receptor that controls gene expression in almost all tissues in a cell type-specific manner. While GR's transcriptional targets mediate beneficial reactions in immune cells, they also harbor the potential of adverse metabolic effects in other cell types such as hepatocytes. Here, we have profiled nascent transcription upon glucocorticoid stimulation in LPS-activated primary murine macrophages using 4sU-seq. We compared our results to publicly available nascent transcriptomics data from murine liver and bioinformatically identified non-coding RNAs transcribed from intergenic GR binding sites in a tissue-specific fashion. These tissue-specific enhancer RNAs (eRNAs) correlate with target gene expression, reflecting cell type-specific glucocorticoid responses. We further associate GR-mediated eRNA expression with changes in H3K27 acetylation and BRD4 recruitment in inflammatory macrophages upon glucocorticoid treatment. In summary, we propose a common mechanism by which GR-bound enhancers regulate target gene expression by changes in histone acetylation, BRD4 recruitment and eRNA expression. We argue that local eRNAs are potential therapeutic targets downstream of GR signaling which may modulate glucocorticoid response in a cell type-specific way.

Interrogating cell type-specific cooperation of transcriptional regulators in 3D chromatin

Context-specific activities of transcription regulators (TRs) in the nucleus modulate spatiotemporal gene expression precisely. Using the largest ChIP-seq data and chromatin loops in the human K562 cell line, we initially interrogated TR cooperation in 3D chromatin via a graphical model and revealed many known and novel TRs manipulating context-specific pathways. To explore TR cooperation across broad tissue/cell types, we systematically leveraged large-scale open chromatin profiles, computational footprinting, and high-resolution chromatin interactions to investigate tissue/cell type-specific TR cooperation. We first delineated a landscape of TR cooperation across 40 human tissue/cell types. Network modularity analyses uncovered the commonality and specificity of TR cooperation in different conditions. We also demonstrated that TR cooperation information can better interpret the disease-causal variants identified by genome-wide association studies and recapitulate cell states during neural development. Our study characterizes shared and unique patterns of TR cooperation associated with the cell type specificity of gene regulation in 3D chromatin.

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Computational inference of transcriptional regulator (TR) cooperation in 3D chromatin

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A landscape of 3D TR cooperation across 40 human tissue/cell types

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TR cooperation can better interpret the disease-causal variants identified by GWAS

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Cooperation of certain TRs shapes context-specific gene regulation in cell development

Genetic variants in histone modification regions are associated with the prognosis of lung adenocarcinoma

We investigated the association between genetic variants in the histone modification regions and the prognosis of lung adenocarcinoma after curative surgery. Potentially functional SNPs were selected using integrated analysis of ChIP-seq and RNA-seq. The SNPs were analyzed in a discovery set (n = 166) and a validation set (n = 238). The associations of the SNPs with overall survival (OS) and disease-free survival (DFS) were analyzed. A total of 279 SNPs were selected for genotyping. Among these, CAPN1 rs17583C>T was significantly associated with better OS and DFS (P = 0.001 and P = 0.007, respectively), and LINC00959 rs4751162A>G was significantly associated with worse DFS (P = 0.008). Luciferase assays showed a significantly lower promoter activity of CAPN1 in the rs17583 T allele than C allele (P = 0.008), and consistently the CT + TT genotypes had significantly lower CAPN1 expression than CC genotype (P = 0.01) in clinical samples. The rs4751162 G allele had higher promoter activity of GLRX3 than A allele (P = 0.05). The motif analyses and ChIP-qPCR confirmed that the variants are located in the active promoter/enhancer regions where transcription factor binding occurs. This study showed that genetic variants in the histone modification regions could predict the prognosis of lung adenocarcinoma after surgery.

Transcription factors Krüppel-like factor 4 and paired box 5 regulate the expression of the Grainyhead-like genes

Genes from the Grainyhead-like (GRHL) family code for transcription factors necessary for the development and maintenance of various epithelia. These genes are also very important in the development of many types of cancer. However, little is known about the regulation of expression of GRHL genes. Previously, there were no systematic analyses of the promoters of GRHL genes or transcription factors that bind to these promoters. Here we report that the Krüppel-like factor 4 (KLF4) and the paired box 5 factor (PAX5) bind to the regulatory regions of the GRHL genes and regulate their expression. Ectopic expression of KLF4 or PAX5 alters the expression of GRHL genes. In KLF4-overexpressing HEK293 cells, the expression of GRHL1 and GRHL3 genes was upregulated by 32% and 60%, respectively, whereas the mRNA level of GRHL2 gene was lowered by 28% when compared to the respective controls. The levels of GRHL1 and GRHL3 expression were decreased by 30% or 33% in PAX5-overexpressing HEK293 cells. The presence of minor frequency allele of single nucleotide polymorphism rs115898376 in the promoter of the GRHL1 gene affected the binding of KLF4 to this site. The evidence presented here suggests an important role of KLF4 and PAX5 in the regulation of expression of GRHL1-3 genes.

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.

Scaffold attachment factor B1 regulates androgen degradation pathways in prostate cancer

The nuclear matrix protein Scaffold Attachment Factor B1 (SAFB1, SAFB) can act in prostate cancer (PCa) as an androgen receptor (AR) co-repressor that functions through epigenetic silencing of AR targets, such as prostate specific antigen (PSA, KLK3). Genomic profiling of SAFB1-silenced PCa cells indicated that SAFB1 may play a role in modulating intracrine androgen levels through the regulation of UDP-glucuronosyltransferase (UGT) genes, which inactivate steroid hormones. Gene silencing of SAFB1 resulted in increased levels of free dihydrotesterosterone (DHT), and increased resistance to the AR inhibitor enzalutamide. SAFB1 silencing suppressed expression of the UDP-glucuronosyltransferase family 2 member B15 gene (UGT2B15) and the closely related UGT2B17 gene, which encode proteins that irreversibly inactivate testosterone (T) and DHT. Analysis of human data indicated that genomic loss at the SAFB locus, or down-regulation of expression of the SAFB gene, is associated with aggressive PCa. These findings identify SAFB1 as an important regulator of androgen catabolism in PCa and suggest that loss or inactivation of this protein may promote AR activity by retention of active androgen in tumor cells.

An Intronic Risk SNP rs12454712 for Central Obesity Acts As an Allele-Specific Enhancer To Regulate BCL2 Expression

Genome-wide association studies (GWAS) have reproducibly associated the single nucleotide polymorphism (SNP) rs12454712 with waist-to-hip ratio adjusted for BMI (WHRadjBMI), but the functional role underlying this intronic variant is unknown. Integrative genomic and epigenomic analyses supported rs12454712 as a functional independent variant. We further demonstrated that rs12454712 acted as an allele-specific enhancer regulating expression of its located gene BCL2 by using dual-luciferase reporter assays and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9. Specifically, the rs12454712-C allele can bind transcription factor ZNF329, which efficiently elevates the enhancer activity and increases BCL2 expression. Knocking down Bcl2 in 3T3-L1 cells led to the downregulation of adipogenic differentiation marker genes and increased cell apoptosis. A significant negative correlation between BCL2 expression in subcutaneous adipose tissues and obesity was observed. Our findings illustrate the molecular mechanisms behind the intronic SNP rs12454712 for central obesity, which would be a potential and promising target for developing appropriate therapies.

Uncovering Transcriptional Regulators and Targets of sRNAs Using an Integrative Data-Mining Approach: H-NS-Regulated RseX as a Case Study

Bacterial small RNAs (sRNAs) play a vital role in pathogenesis by enabling rapid, efficient networks of gene attenuation during infection. In recent decades, there has been a surge in the number of proposed and biochemically-confirmed sRNAs in both Gram-positive and Gram-negative pathogens. However, limited homology, network complexity, and condition specificity of sRNA has stunted complete characterization of the activity and regulation of these RNA regulators. To streamline the discovery of the expression of sRNAs, and their post-transcriptional activities, we propose an integrative in vivo data-mining approach that couples DNA protein occupancy, RNA-seq, and RNA accessibility data with motif identification and target prediction algorithms. We benchmark the approach against a subset of well-characterized E. coli sRNAs for which a degree of in vivo transcriptional regulation and post-transcriptional activity has been previously reported, finding support for known regulation in a large proportion of this sRNA set. We showcase the abilities of our method to expand understanding of sRNA RseX, a known envelope stress-linked sRNA for which a cellular role has been elusive due to a lack of native expression detection. Using the presented approach, we identify a small set of putative RseX regulators and targets for experimental investigation. These findings have allowed us to confirm native RseX expression under conditions that eliminate H-NS repression as well as uncover a post-transcriptional role of RseX in fimbrial regulation. Beyond RseX, we uncover 163 putative regulatory DNA-binding protein sites, corresponding to regulation of 62 sRNAs, that could lead to new understanding of sRNA transcription regulation. For 32 sRNAs, we also propose a subset of top targets filtered by engagement of regions that exhibit binding site accessibility behavior in vivo. We broadly anticipate that the proposed approach will be useful for sRNA-reliant network characterization in bacteria. Such investigations under pathogenesis-relevant environmental conditions will enable us to deduce complex rapid-regulation schemes that support infection.

The RNA Atlas expands the catalog of human non-coding RNAs

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

Dynamic landscape of protein occupancy across the Escherichia coli chromosome

Free-living bacteria adapt to environmental change by reprogramming gene expression through precise interactions of hundreds of DNA-binding proteins. A predictive understanding of bacterial physiology requires us to globally monitor all such protein-DNA interactions across a range of environmental and genetic perturbations. Here, we show that such global observations are possible using an optimized version of in vivo protein occupancy display technology (in vivo protein occupancy display-high resolution, IPOD-HR) and present a pilot application to Escherichia coli. We observe that the E. coli protein-DNA interactome organizes into 2 distinct prototypic features: (1) highly dynamic condition-dependent transcription factor (TF) occupancy; and (2) robust kilobase scale occupancy by nucleoid factors, forming silencing domains analogous to eukaryotic heterochromatin. We show that occupancy dynamics across a range of conditions can rapidly reveal the global transcriptional regulatory organization of a bacterium. Beyond discovery of previously hidden regulatory logic, we show that these observations can be utilized to computationally determine sequence specificity models for the majority of active TFs. Our study demonstrates that global observations of protein occupancy combined with statistical inference can rapidly and systematically reveal the transcriptional regulatory and structural features of a bacterial genome. This capacity is particularly crucial for non-model bacteria that are not amenable to routine genetic manipulation.

Long Noncoding RNA OIP5-AS1 Promotes Cell Apoptosis and Cataract Formation by Blocking POLG Expression Under Oxidative Stress

Purpose

Cataract, a clouding of the intraocular lens, is the leading cause of blindness. The lens-expressed long noncoding RNA OIP5-AS1 was upregulated in lens epithelial cells from patients with cataracts, suggesting its pathogenic role in cataracts. We investigated the regulatory role of OIP5-AS1 in the development of cataracts as well as potential RNA binding proteins, downstream target genes, and upstream transcription factors.

Methods

Clinical capsules and ex vivo and in vitro cataract models were used to test OIP5-AS1 expression. Cell apoptosis was detected using Western blots, JC-1 staining, and flow cytometry. Ribonucleoprotein immunoprecipitation-qPCR was performed to confirm the interaction of OIP5-AS1 and POLG. Chromatin immunoprecipitation-qPCR was used to determine the binding of TFAP2A and the OIP5-AS1 promoter region.

Results

OIP5-AS1 was upregulated in cataract lenses and B3 cells under oxidative stress. OIP5-AS1 knockdown protected B3 cells from H₂O₂-induced apoptosis and alleviated lens opacity in the ex vivo cataract model. HuR functioned as a scaffold carrying OIP5-AS1 and POLG mRNA and mediated the decay of POLG mRNA. POLG was downregulated in the cataract lens and oxidative-stressed B3 cells, and POLG depletion decreased the mtDNA copy number and MMP, increased reactive oxygen species production, and sensitized B3 cells to oxidative stress-induced apoptosis. POLG overexpression reversed these effects. TFAP2A bound the OIP5-AS1 promoter and contributed to OIP5-AS1 expression.

Conclusions

We demonstrated that OIP5-AS1, activated by TFAP2A, contributed to cataract formation by inhibiting POLG expression mediated by HuR, thus leading to increased apoptosis of lens epithelial cells and aggravated lens opacity, suggesting that OIP5-AS1 is a potential target for cataract treatment.

Comparative genomics of Glandirana rugosa using unsupervised AI reveals a high CG frequency

Genome sequencing of a unique frog (Glandirana rugosa) having XY/ZW systems within the species and comparative genomics with other six frogs were performed using a batch-learning self-organizing map, which is unsupervised AI for oligonucleotide compositions, to clarify its genome characteristics.

The Japanese wrinkled frog (Glandirana rugosa) is unique in having both XX-XY and ZZ-ZW types of sex chromosomes within the species. The genome sequencing and comparative genomics with other frogs should be important to understand mechanisms of turnover of sex chromosomes within one species or during a short period. In this study, we analyzed the newly sequenced genome of G. rugosa using a batch-learning self-organizing map which is unsupervised artificial intelligence for oligonucleotide compositions. To clarify genome characteristics of G. rugosa, we compared its short oligonucleotide compositions in all 1-Mb genomic fragments with those of other six frog species (Pyxicephalus adspersus, Rhinella marina, Spea multiplicata, Leptobrachium leishanense, Xenopus laevis, and Xenopus tropicalis). In G. rugosa, we found an Mb-level large size of repeat sequences having a high identity with the W chromosome of the African bullfrog (P. adspersus). Our study concluded that G. rugosa has unique genome characteristics with a high CG frequency, and its genome is assumed to heterochromatinize a large size of genome via methylataion of CG.

Regulation of the conserved 3'-5' exoribonuclease EXOSC10/Rrp6 during cell division, development and cancer

The conserved 3'-5' exoribonuclease EXOSC10/Rrp6 processes and degrades RNA, regulates gene expression and participates in DNA double-strand break repair and control of telomere maintenance via degradation of the telomerase RNA component. EXOSC10/Rrp6 is part of the multimeric nuclear RNA exosome and interacts with numerous proteins. Previous clinical, genetic, biochemical and genomic studies revealed the protein's essential functions in cell division and differentiation, its RNA substrates and its relevance to autoimmune disorders and oncology. However, little is known about the regulatory mechanisms that control the transcription, translation and stability of EXOSC10/Rrp6 during cell growth, development and disease and how these mechanisms evolved from yeast to human. Herein, we provide an overview of the RNA- and protein expression profiles of EXOSC10/Rrp6 during cell division, development and nutritional stress, and we summarize interaction networks and post-translational modifications across species. Additionally, we discuss how known and predicted protein interactions and post-translational modifications influence the stability of EXOSC10/Rrp6. Finally, we explore the idea that different EXOSC10/Rrp6 alleles, which potentially alter cellular protein levels or affect protein function, might influence human development and disease progression. In this review we interpret information from the literature together with genomic data from knowledgebases to inspire future work on the regulation of this essential protein's stability in normal and malignant cells.

High-pressure processing-induced transcriptome response during recovery of Listeria monocytogenes

Background

High-pressure processing (HPP) is a commonly used technique in the food industry to inactivate pathogens, including L. monocytogenes. It has been shown that L. monocytogenes is able to recover from HPP injuries and can start to grow again during long-term cold storage. To date, the gene expression profiling of L. monocytogenes during HPP damage recovery at cooling temperature has not been studied. In order identify key genes that play a role in recovery of the damage caused by HPP treatment, we performed RNA-sequencing (RNA-seq) for two L. monocytogenes strains (barotolerant RO15 and barosensitive ScottA) at nine selected time points (up to 48 h) after treatment with two pressure levels (200 and 400 MPa).

Results

The results showed that a general stress response was activated by SigB after HPP treatment. In addition, the phosphotransferase system (PTS; mostly fructose-, mannose-, galactitol-, cellobiose-, and ascorbate-specific PTS systems), protein folding, and cobalamin biosynthesis were the most upregulated genes during HPP damage recovery. We observed that cell-division-related genes (divIC, dicIVA, ftsE, and ftsX) were downregulated. By contrast, peptidoglycan-synthesis genes (murG, murC, and pbp2A) were upregulated. This indicates that cell-wall repair occurs as a part of HPP damage recovery. We also observed that prophage genes, including anti-CRISPR genes, were induced by HPP. Interestingly, a large amount of RNA-seq data (up to 85%) was mapped to Rli47, which is a non-coding RNA that is upregulated after HPP. Thus, we predicted that Rli47 plays a role in HPP damage recovery in L. monocytogenes. Moreover, gene-deletion experiments showed that amongst peptidoglycan biosynthesis genes, pbp2A mutants are more sensitive to HPP.

Conclusions

We identified several genes and mechanisms that may play a role in recovery from HPP damage of L. monocytogenes. Our study contributes to new information on pathogen inactivation by HPP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07407-6.

LETR1 is a lymphatic endothelial-specific lncRNA governing cell proliferation and migration through KLF4 and SEMA3C

Recent studies have revealed the importance of long noncoding RNAs (lncRNAs) as tissue-specific regulators of gene expression. There is ample evidence that distinct types of vasculature undergo tight transcriptional control to preserve their structure, identity, and functions. We determine a comprehensive map of lineage-specific lncRNAs in human dermal lymphatic and blood vascular endothelial cells (LECs and BECs), combining RNA-Seq and CAGE-Seq. Subsequent antisense oligonucleotide-knockdown transcriptomic profiling of two LEC- and two BEC-specific lncRNAs identifies LETR1 as a critical gatekeeper of the global LEC transcriptome. Deep RNA-DNA, RNA-protein interaction studies, and phenotype rescue analyses reveal that LETR1 is a nuclear trans-acting lncRNA modulating, via key epigenetic factors, the expression of essential target genes, including KLF4 and SEMA3C, governing the growth and migratory ability of LECs. Together, our study provides several lines of evidence supporting the intriguing concept that every cell type expresses precise lncRNA signatures to control lineage-specific regulatory programs.

The glucocorticoid receptor recruits the COMPASS complex to regulate inflammatory transcription at macrophage enhancers

Glucocorticoids (GCs) are effective anti-inflammatory drugs; yet, their mechanisms of action are poorly understood. GCs bind to the glucocorticoid receptor (GR), a ligand-gated transcription factor controlling gene expression in numerous cell types. Here, we characterize GR’s protein interactome and find the SETD1A (SET domain containing 1A)/COMPASS (complex of proteins associated with Set1) histone H3 lysine 4 (H3K4) methyltransferase complex highly enriched in activated mouse macrophages. We show that SETD1A/COMPASS is recruited by GR to specific cis-regulatory elements, coinciding with H3K4 methylation dynamics at subsets of sites, upon treatment with lipopolysaccharide (LPS) and GCs. By chromatin immunoprecipitation sequencing (ChIP-seq) and RNA-seq, we identify subsets of GR target loci that display SETD1A occupancy, H3K4 mono-, di-, or tri-methylation patterns, and transcriptional changes. However, our data on methylation status and COMPASS recruitment suggest that SETD1A has additional transcriptional functions. Setd1a loss-of-function studies reveal that SETD1A/COMPASS is required for GR-controlled transcription of subsets of macrophage target genes. We demonstrate that the SETD1A/COMPASS complex cooperates with GR to mediate anti-inflammatory effects.

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GR’s transcriptional complex in macrophages includes COMPASS proteins

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GR ligand changes SETD1A chromatin occupancy in activated macrophages

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Subsets of GR target sites show COMPASS binding and H3K4 methylation dynamics

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SETD1A is required for some of GR’s anti-inflammatory actions

FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs

The Functional ANnoTation Of the Mammalian genome (FANTOM) Consortium has continued to provide extensive resources in the pursuit of understanding the transcriptome, and transcriptional regulation, of mammalian genomes for the last 20 years. To share these resources with the research community, the FANTOM web-interfaces and databases are being regularly updated, enhanced and expanded with new data types. In recent years, the FANTOM Consortium's efforts have been mainly focused on creating new non-coding RNA datasets and resources. The existing FANTOM5 human and mouse miRNA atlas was supplemented with rat, dog, and chicken datasets. The sixth (latest) edition of the FANTOM project was launched to assess the function of human long non-coding RNAs (lncRNAs). From its creation until 2020, FANTOM6 has contributed to the research community a large dataset generated from the knock-down of 285 lncRNAs in human dermal fibroblasts; this is followed with extensive expression profiling and cellular phenotyping. Other updates to the FANTOM resource includes the reprocessing of the miRNA and promoter atlases of human, mouse and chicken with the latest reference genome assemblies. To facilitate the use and accessibility of all above resources we further enhanced FANTOM data viewers and web interfaces. The updated FANTOM web resource is publicly available at https://fantom.gsc.riken.jp/.

Dedifferentiation and neuronal repression define familial Alzheimer's disease

Identifying the systems-level mechanisms that lead to Alzheimer's disease, an unmet need, is an essential step toward the development of therapeutics. In this work, we report that the key disease-causative mechanisms, including dedifferentiation and repression of neuronal identity, are triggered by changes in chromatin topology. Here, we generated human induced pluripotent stem cell (hiPSC)-derived neurons from donor patients with early-onset familial Alzheimer's disease (EOFAD) and used a multiomics approach to mechanistically characterize the modulation of disease-associated gene regulatory programs. We demonstrate that EOFAD neurons dedifferentiate to a precursor-like state with signatures of ectoderm and nonectoderm lineages. RNA-seq, ATAC-seq, and ChIP-seq analysis reveals that transcriptional alterations in the cellular state are orchestrated by changes in histone methylation and chromatin topology. Furthermore, we demonstrate that these mechanisms are observed in EOFAD-patient brains, validating our hiPSC-derived neuron models. The mechanistic endotypes of Alzheimer's disease uncovered here offer key insights for therapeutic interventions.

Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress

Mitochondrial dysfunction was highlighted as a crucial vulnerability factor for the development of depression. However, systemic studies assessing stress-induced changes in mitochondria-associated genes in brain regions relevant to depression symptomatology remain scarce. Here, we performed a genome-wide transcriptomic study to examine mitochondrial gene expression in the prefrontal cortex (PFC) and nucleus accumbens (NAc) of mice exposed to multimodal chronic restraint stress. We identified mitochondria-associated gene pathways as most prominently affected in the PFC and with lesser significance in the NAc. A more detailed mitochondrial gene expression analysis revealed that in particular mitochondrial DNA-encoded subunits of the oxidative phosphorylation complexes were altered in the PFC. The comparison of our data with a reanalyzed transcriptome data set of chronic variable stress mice and major depression disorder subjects showed that the changes in mitochondrial DNA-encoded genes are a feature generalizing to other chronic stress-protocols as well and might have translational relevance. Finally, we provide evidence for changes in mitochondrial outputs in the PFC following chronic stress that are indicative of mitochondrial dysfunction. Collectively, our work reinforces the idea that changes in mitochondrial gene expression are key players in the prefrontal adaptations observed in individuals with high behavioral susceptibility and resilience to chronic stress.

Multiomics dissection of molecular regulatory mechanisms underlying autoimmune-associated noncoding SNPs

More than 90% of autoimmune-associated variants are located in noncoding regions, leading to challenges in deciphering the underlying causal roles of functional variants and genes and biological mechanisms. Therefore, to reduce the gap between traditional genetic findings and mechanistic understanding of disease etiologies and clinical drug development, it is important to translate systematically the regulatory mechanisms underlying noncoding variants. Here, we prioritized functional noncoding SNPs with regulatory gene targets associated with 19 autoimmune diseases by incorporating hundreds of immune cell-specific multiomics data. The prioritized SNPs are associated with transcription factor (TF) binding, histone modification, or chromatin accessibility, indicating their allele-specific regulatory roles. Their target genes are significantly enriched in immunologically related pathways and other known immunologically related functions. We found that 90.1% of target genes are regulated by distal SNPs involving several TFs (e.g., the DNA-binding protein CCCTC-binding factor [CTCF]), suggesting the importance of long-range chromatin interaction in autoimmune diseases. Moreover, we predicted potential drug targets for autoimmune diseases, including 2 genes (NFKB1 and SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. Taken together, these findings may provide useful information for future experimental follow-up and drug applications on autoimmune diseases.

Comparative transcriptomics of primary cells in vertebrates

Gene expression profiles in homologous tissues have been observed to be different between species, which may be due to differences between species in the gene expression program in each cell type, but may also reflect differences in cell type composition of each tissue in different species. Here, we compare expression profiles in matching primary cells in human, mouse, rat, dog, and chicken using Cap Analysis Gene Expression (CAGE) and short RNA (sRNA) sequencing data from FANTOM5. While we find that expression profiles of orthologous genes in different species are highly correlated across cell types, in each cell type many genes were differentially expressed between species. Expression of genes with products involved in transcription, RNA processing, and transcriptional regulation was more likely to be conserved, while expression of genes encoding proteins involved in intercellular communication was more likely to have diverged during evolution. Conservation of expression correlated positively with the evolutionary age of genes, suggesting that divergence in expression levels of genes critical for cell function was restricted during evolution. Motif activity analysis showed that both promoters and enhancers are activated by the same transcription factors in different species. An analysis of expression levels of mature miRNAs and of primary miRNAs identified by CAGE revealed that evolutionary old miRNAs are more likely to have conserved expression patterns than young miRNAs. We conclude that key aspects of the regulatory network are conserved, while differential expression of genes involved in cell-to-cell communication may contribute greatly to phenotypic differences between species.