Annotation of nuclear lncRNAs based on chromatin interactions.

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

ROR2 expression predicts human induced pluripotent stem cell differentiation into neural stem/progenitor cells and GABAergic neurons.

Despite the development of various in vitro differentiation protocols for the efficient derivation of specific cell types, human induced pluripotent stem cell (hiPSC) lines have varing ability to differentiate into specific lineages. Therefore, surrogate markers for accurately predicting the differentiation propensity of hiPSC lines may facilitate cell-based therapeutic product development and manufacture. We attempted to identify marker genes that could predict the differentiation propensity of hiPSCs into neural stem/progenitor cells (NS/PCs). Using Spearman's rank correlation coefficients, we investigated genes in the undifferentiated state, the expression levels of which were significantly correlated with the neuronal differentiation propensity of several hiPSC lines. Among genes significantly correlated with NS/PC differentiation (P < 0.01), we identified ROR2 as a novel predictive marker. ROR2 expression in hiPSCs was negatively correlated with NS/PC differentiation tendency, regardless of the differentiation method, whereas its knockdown enhanced differentiation. ROR2 regulates NS/PC differentiation, suggesting that ROR2 is functionally essential for NS/PC differentiation. Selecting cell lines with relatively low ROR2 expression facilitated identification of hiPSCs that can differentiate into NS/PCs. Cells with ROR2 knockdown showed increased efficiency of differentiation into forebrain GABAergic neurons compared to controls. These findings suggest that ROR2 is a surrogate marker for selecting hiPSC lines appropriate for NS/PC and GABAergic neuronal differentiations.

OVCH1 Antisense RNA 1 is differentially expressed between non-frail and frail old adults.

While some old adults stay healthy and non-frail up to late in life, others experience multimorbidity and frailty often accompanied by a pro-inflammatory state. The underlying molecular mechanisms for those differences are still obscure. Here, we used gene expression analysis to understand the molecular underpinning between non-frail and frail individuals in old age. Twenty-four adults (50% non-frail and 50% frail) from InCHIANTI study were included. Total RNA extracted from whole blood was analyzed by Cap Analysis of Gene Expression (CAGE). CAGE identified transcription start site (TSS) and active enhancer regions. We identified a set of differentially expressed (DE) TSS and enhancer between non-frail and frail and male and female participants. Several DE TSSs were annotated as lncRNA (XIST and TTTY14) and antisense RNAs (ZFX-AS1 and OVCH1 Antisense RNA 1). The promoter region chr6:366,786,54-366,787,97;+ was DE and overlapping the longevity CDKN1A gene. GWAS-LD enrichment analysis identifies overlapping LD-blocks with the DE regions with reported traits in GWAS catalog (isovolumetric relaxation time and urinary tract infection frequency). Furthermore, we used weighted gene co-expression network analysis (WGCNA) to identify changes of gene expression associated with clinical traits and identify key gene modules. We performed functional enrichment analysis of the gene modules with significant trait/module correlation. One gene module is showing a very distinct pattern in hub genes. Glycogen Phosphorylase L (PYGL) was the top ranked hub gene between non-frail and frail. We predicted transcription factor binding sites (TFBS) and motif activity. TF involved in age-related pathways (e.g., FOXO3 and MYC) shows different expression patterns between non-frail and frail participants. Expanding the study of OVCH1 Antisense RNA 1 and PYGL may help understand the mechanisms leading to loss of homeostasis that ultimately causes frailty.

Single-Cell RNA-Seq Reveals LRRC75A-Expressing Cell Population Involved in VEGF Secretion of Multipotent Mesenchymal Stromal/Stem Cells Under Ischemia.

Human multipotent mesenchymal stromal/stem cells (MSCs) have been utilized in cell therapy for various diseases and their clinical applications are expected to increase in the future. However, the variation in MSC-based product quality due to the MSC heterogeneity has resulted in significant constraints in the clinical utility of MSCs. Therefore, we hypothesized that it might be important to identify and ensure/enrich suitable cell subpopulations for therapies using MSC-based products. In this study, we aimed to identify functional cell subpopulations to predict the efficacy of angiogenic therapy using bone marrow-derived MSCs (BM-MSCs). To assess its angiogenic potency, we observed various levels of vascular endothelial growth factor (VEGF) secretion among 11 donor-derived BM-MSC lines under in vitro ischemic culture conditions. Next, by clarifying the heterogeneity of BM-MSCs using single-cell RNA-sequencing analysis, we identified a functional cell subpopulation that contributed to the overall VEGF production in BM-MSC lines under ischemic conditions. We also found that leucine-rich repeat-containing 75A (LRRC75A) was more highly expressed in this cell subpopulation than in the others. Importantly, knockdown of LRRC75A using small interfering RNA resulted in significant inhibition of VEGF secretion in ischemic BM-MSCs, indicating that LRRC75A regulates VEGF secretion under ischemic conditions. Therefore, LRRC75A may be a useful biomarker to identify cell subpopulations that contribute to the angiogenic effects of BM-MSCs. Our work provides evidence that a strategy based on single-cell transcriptome profiles is effective for identifying functional cell subpopulations in heterogeneous MSC-based products.

Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC.

SkewC is a single-cell RNA sequencing (scRNA-seq) data quality evaluation tool. The approach is based on determining gene body coverage, and its skewness, as a quality metric for each individual cell. SkewC distinguishes between two types of single cells: typical cells with prototypical gene body coverage profiles and skewed cells with skewed gene body coverage profiles. SkewC can be used on any scRNA-seq data as it is independent from the underlying technology used to generate the data. For complete details on the use and execution of this protocol, please refer to Abugessaisa et al. (2022).1.

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.

Systematic Functional Annotation Workflow for Insects.

Next-generation sequencing has revolutionized entomological study, rendering it possible to analyze the genomes and transcriptomes of non-model insects. However, use of this technology is often limited to obtaining the nucleotide sequences of target or related genes, with many of the acquired sequences remaining unused because other available sequences are not sufficiently annotated. To address this issue, we have developed a functional annotation workflow for transcriptome-sequenced insects to determine transcript descriptions, which represents a significant improvement over the previous method (functional annotation pipeline for insects). The developed workflow attempts to annotate not only the protein sequences obtained from transcriptome analysis but also the ncRNA sequences obtained simultaneously. In addition, the workflow integrates the expression-level information obtained from transcriptome sequencing for application as functional annotation information. Using the workflow, functional annotation was performed on the sequences obtained from transcriptome sequencing of the stick insect (Entoria okinawaensis) and silkworm (Bombyx mori), yielding richer functional annotation information than that obtained in our previous study. The improved workflow allows the more comprehensive exploitation of transcriptome data and is applicable to other insects because the workflow has been openly developed on GitHub.

SkewC: Identifying cells with skewed gene body coverage in single-cell RNA sequencing data.

The analysis and interpretation of single-cell RNA sequencing (scRNA-seq) experiments are compromised by the presence of poor-quality cells. For meaningful analyses, such poor-quality cells should be excluded as they introduce noise in the data. We introduce SkewC, a quality-assessment tool, to identify skewed cells in scRNA-seq experiments. The tool's methodology is based on the assessment of gene coverage for each cell, and its skewness as a quality measure; the gene body coverage is a unique characteristic for each protocol, and different protocols yield highly different coverage profiles. This tool is designed to avoid misclustering or false clusters by identifying, isolating, and removing cells with skewed gene body coverage profiles. SkewC is capable of processing any type of scRNA-seq dataset, regardless of the protocol. We envision SkewC as a distinctive QC method to be incorporated into scRNA-seq QC processing to preclude the possibility of scRNA-seq data misinterpretation.

Prediction of transcription factors associated with DNA demethylation during human cellular development.

DNA methylation of CpG dinucleotides is an important epigenetic modification involved in the regulation of mammalian gene expression, with each type of cell developing a specific methylation profile during its differentiation. Recently, it has been shown that a small subgroup of transcription factors (TFs) might promote DNA demethylation at their binding sites. We developed a bioinformatics pipeline to predict from genome-wide DNA methylation data TFs that promote DNA demethylation at their binding site. We applied the pipeline to International Human Epigenome Consortium methylome data and selected 393 candidate transcription factor binding motifs and associated 383 TFs that are likely associated with DNA demethylation. Validation of a subset of the candidate TFs using an in vitro assay suggested that 28 of 49 TFs from various TF families had DNA-demethylation-promoting activity; TF families, such as bHLH and ETS, contained both TFs with and without the activity. The identified TFs showed large demethylated/methylated CpG ratios and their demethylated CpGs showed significant bias toward hypermethylation in original cells. Furthermore, the identified TFs promoted demethylation of distinct sets of CpGs, with slight overlap of the targeted CpGs among TF family members, which was consistent with the results of a gene ontology (GO) term analysis of the identified TFs. Gene expression analysis of the identified TFs revealed that multiple TFs from various families are specifically expressed in human cells and tissues. Together, our results suggest that a large number of TFs from various TF families are associated with cell-type-specific DNA demethylation during human cellular development.

Inducing human retinal pigment epithelium-like cells from somatic tissue.

Regenerative medicine relies on basic research outcomes that are only practical when cost effective. The human eyeball requires the retinal pigment epithelium (RPE) to interface the neural retina and the choroid at large. Millions of people suffer from age-related macular degeneration (AMD), a blinding multifactor genetic disease among RPE degradation pathologies. Recently, autologous pluripotent stem-cell-derived RPE cells were prohibitively expensive due to time; therefore, we developed a faster reprogramming system. We stably induced RPE-like cells (iRPE) from human fibroblasts (Fibs) by conditional overexpression of both broad plasticity and lineage-specific transcription factors (TFs). iRPE cells displayed critical RPE benchmarks and significant in vivo integration in transplanted retinas. Herein, we detail the iRPE system with comprehensive single-cell RNA sequencing (scRNA-seq) profiling to interpret and characterize its best cells. We anticipate that our system may enable robust retinal cell induction for basic research and affordable autologous human RPE tissue for regenerative cell therapy.

IκBα is required for full transcriptional induction of some NFκB-regulated genes in response to TNF in MCF-7 cells.

Inflammatory stimuli triggers the degradation of three inhibitory κB (IκB) proteins, allowing for nuclear translocation of nuclear factor-κB (NFκB) for transcriptional induction of its target genes. Of these three, IκBα is a well-known negative feedback regulator that limits the duration of NFκB activity. We sought to determine whether IκBα's role in enabling or limiting NFκB activation is important for tumor necrosis factor (TNF)-induced gene expression in human breast cancer cells (MCF-7). Contrary to our expectations, many more TNF-response genes showed reduced induction than enhanced induction in IκBα knockdown cells. Mathematical modeling was used to investigate the underlying mechanism. We found that the reduced activation of some NFκB target genes in IκBα-deficient cells could be explained by the incoherent feedforward loop (IFFL) model. In addition, for a subset of genes, prolonged NFκB activity due to loss of negative feedback control did not prolong their transient activation; this implied a multi-state transcription cycle control of gene induction. Genes encoding key inflammation-related transcription factors, such as JUNB and KLF10, were found to be best represented by a model that contained both the IFFL and the transcription cycle motif. Our analysis sheds light on the regulatory strategies that safeguard inflammatory gene expression from overproduction and repositions the function of IκBα not only as a negative feedback regulator of NFκB but also as an enabler of NFκB-regulated stimulus-responsive inflammatory gene expression. This study indicates the complex involvement of IκBα in the inflammatory response to TNF that is induced by radiation therapy in breast cancer.

The choice of negative control antisense oligonucleotides dramatically impacts downstream analysis depending on the cellular background.

BACKGROUND: The lymphatic and the blood vasculature are closely related systems that collaborate to ensure the organism's physiological function. Despite their common developmental origin, they present distinct functional fates in adulthood that rely on robust lineage-specific regulatory programs. The recent technological boost in sequencing approaches unveiled long noncoding RNAs (lncRNAs) as prominent regulatory players of various gene expression levels in a cell-type-specific manner. RESULTS: To investigate the potential roles of lncRNAs in vascular biology, we performed antisense oligonucleotide (ASO) knockdowns of lncRNA candidates specifically expressed either in human lymphatic or blood vascular endothelial cells (LECs or BECs) followed by Cap Analysis of Gene Expression (CAGE-Seq). Here, we describe the quality control steps adopted in our analysis pipeline before determining the knockdown effects of three ASOs per lncRNA target on the LEC or BEC transcriptomes. In this regard, we especially observed that the choice of negative control ASOs can dramatically impact the conclusions drawn from the analysis depending on the cellular background. CONCLUSION: In conclusion, the comparison of negative control ASO effects on the targeted cell type transcriptomes highlights the essential need to select a proper control set of multiple negative control ASO based on the investigated cell types.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism.

Automatic identification of small molecules that promote cell conversion and reprogramming.

Controlling cell fate has great potential for regenerative medicine, drug discovery, and basic research. Although transcription factors are able to promote cell reprogramming and transdifferentiation, methods based on their upregulation often show low efficiency. Small molecules that can facilitate conversion between cell types can ameliorate this problem working through safe, rapid, and reversible mechanisms. Here, we present DECCODE, an unbiased computational method for identification of such molecules based on transcriptional data. DECCODE matches a large collection of drug-induced profiles for drug treatments against a large dataset of primary cell transcriptional profiles to identify drugs that either alone or in combination enhance cell reprogramming and cell conversion. Extensive validation in the context of human induced pluripotent stem cells shows that DECCODE is able to prioritize drugs and drug combinations enhancing cell reprogramming. We also provide predictions for cell conversion with single drugs and drug combinations for 145 different cell types.

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/.

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.

The Number of Transcription Factors at an Enhancer Determines Switch-like Gene Expression.

NF-κB is a transcription factor that activates super enhancers (SEs) and typical enhancers (TEs) and triggers threshold and graded gene expression, respectively. However, the mechanisms by which NF-κB selectively participates in these enhancers remain unclear. Here we show using mouse primary B lymphocytes that SE activity simultaneously associates with chromatin opening and enriched NF-κB binding, resulting in a higher fold change and threshold expression upon B cell receptor (BCR) activation. The higher fold change results from longer DNA, whereas the threshold response is explained by synergy in DNA-NF-κB binding and is supported by the coexistence of PU.1 and NF-κB in a SE before cell stimulation. This model indicates that the pre-existing NF-κB functions as a seed and triggers its processive binding upon BCR activation. Our mathematical modeling of the single-cell transcriptome reveals an additional role for SEs in divergent clonal responses in B cells.