Optimal design of synthetic circular RNAs.

Circular RNAs are an unusual class of single-stranded RNAs whose ends are covalently linked via back-splicing. Due to their versatility, the need to express circular RNAs in vivo and in vitro has increased. Efforts have been made to efficiently and precisely synthesize circular RNAs. However, a review on the optimization of the processes of circular RNA design, synthesis, and delivery is lacking. Our review highlights the multifaceted aspects considered when producing optimal circular RNAs and summarizes the available options for each step of exogenous circular RNA design and synthesis, including circularization strategies. Additionally, this review describes several potential applications of circular RNAs.

Comparative interactome analysis of α-arrestin families in human and Drosophila.

The α-arrestins form a large family of evolutionally conserved modulators that control diverse signaling pathways, including both G-protein-coupled receptor (GPCR)-mediated and non-GPCR-mediated pathways, across eukaryotes. However, unlike ß-arrestins, only a few α-arrestin targets and functions have been characterized. Here, using affinity purification and mass spectrometry, we constructed interactomes for 6 human and 12 Drosophila α-arrestins. The resulting high-confidence interactomes comprised 307 and 467 prey proteins in human and Drosophila, respectively. A comparative analysis of these interactomes predicted not only conserved binding partners, such as motor proteins, proteases, ubiquitin ligases, RNA splicing factors, and GTPase-activating proteins, but also those specific to mammals, such as histone modifiers and the subunits of V-type ATPase. Given the manifestation of the interaction between the human α-arrestin, TXNIP, and the histone-modifying enzymes, including HDAC2, we undertook a global analysis of transcription signals and chromatin structures that were affected by TXNIP knockdown. We found that TXNIP activated targets by blocking HDAC2 recruitment to targets, a result that was validated by chromatin immunoprecipitation assays. Additionally, the interactome for an uncharacterized human α-arrestin ARRDC5 uncovered multiple components in the V-type ATPase, which plays a key role in bone resorption by osteoclasts. Our study presents conserved and species-specific protein-protein interaction maps for α-arrestins, which provide a valuable resource for interrogating their cellular functions for both basic and clinical research.

Clustering malignant cell states using universally variable genes.

Single-cell RNA sequencing (scRNA-seq) has revealed important insights into the heterogeneity of malignant cells. However, sample-specific genomic alterations often confound such analysis, resulting in patient-specific clusters that are difficult to interpret. Here, we present a novel approach to address the issue. By normalizing gene expression variances to identify universally variable genes (UVGs), we were able to reduce the formation of sample-specific clusters and identify underlying molecular hallmarks in malignant cells. In contrast to highly variable genes vulnerable to a specific sample bias, UVGs led to better detection of clusters corresponding to distinct malignant cell states. Our results demonstrate the utility of this approach for analyzing scRNA-seq data and suggest avenues for further exploration of malignant cell heterogeneity.

Molecular traces of Drosophila hemocytes reveal transcriptomic conservation with vertebrate myeloid cells.

Drosophila hemocytes serve as the primary defense system against harmful threats, allowing the animals to thrive. Hemocytes are often compared to vertebrate innate immune system cells due to the observed functional similarities between the two. However, the similarities have primarily been established based on a limited number of genes and their functional homologies. Thus, a systematic analysis using transcriptomic data could offer novel insights into Drosophila hemocyte function and provide new perspectives on the evolution of the immune system. Here, we performed cross-species comparative analyses using single-cell RNA sequencing data from Drosophila and vertebrate immune cells. We found several conserved markers for the cluster of differentiation (CD) genes in Drosophila hemocytes and validated the role of CG8501 (CD59) in phagocytosis by plasmatocytes, which function much like macrophages in vertebrates. By comparing whole transcriptome profiles in both supervised and unsupervised analyses, we showed that Drosophila hemocytes are largely homologous to vertebrate myeloid cells, especially plasmatocytes to monocytes/macrophages and prohemocyte 1 (PH1) to hematopoietic stem cells. Furthermore, a small subset of prohemocytes with hematopoietic potential displayed homology with hematopoietic progenitor populations in vertebrates. Overall, our results provide a deeper understanding of molecular conservation in the Drosophila immune system.

Toward the functional interpretation of somatic structural variations: bulk- and single-cell approaches.

Structural variants (SVs) are genomic rearrangements that can take many different forms such as copy number alterations, inversions and translocations. During cell development and aging, somatic SVs accumulate in the genome with potentially neutral, deleterious or pathological effects. Generation of somatic SVs is a key mutational process in cancer development and progression. Despite their importance, the detection of somatic SVs is challenging, making them less studied than somatic single-nucleotide variants. In this review, we summarize recent advances in whole-genome sequencing (WGS)-based approaches for detecting somatic SVs at the tissue and single-cell levels and discuss their advantages and limitations. First, we describe the state-of-the-art computational algorithms for somatic SV calling using bulk WGS data and compare the performance of somatic SV detectors in the presence or absence of a matched-normal control. We then discuss the unique features of cutting-edge single-cell-based techniques for analyzing somatic SVs. The advantages and disadvantages of bulk and single-cell approaches are highlighted, along with a discussion of their sensitivity to copy-neutral SVs, usefulness for functional inferences and experimental and computational costs. Finally, computational approaches for linking somatic SVs to their functional readouts, such as those obtained from single-cell transcriptome and epigenome analyses, are illustrated, with a discussion of the promise of these approaches in health and diseases.

Comparison of Proportional Mortality Between Korean Atomic Bomb Survivors and the General Population During 1992-2019.

BACKGROUND: Atomic bombs dropped on Hiroshima and Nagasaki in Japan in August 1945 were estimated to have killed approximately 70,000 Koreans. In Japan, studies on the health status and mortality of atomic bomb survivors compared with the non-exposed population have been conducted. However, there have been no studies related to the mortality of Korean atomic bomb survivors. Therefore, we aimed to study the cause of death of atomic bomb survivors compared to that of the general population. METHODS: Of 2,299 atomic bomb survivors registered with the Korean Red Cross, 2,176 were included in the study. In the general population, the number of deaths by age group was calculated from 1992 to 2019, and 6,377,781 individuals were assessed. Causes of death were categorized according to the Korean Standard Classification of Diseases. To compare the proportional mortality between the two groups, the P value for the ratio test was confirmed, and the Cochran-Armitage trend test and χ² test were performed to determine the cause of death according to the distance from the hypocenter. RESULTS: Diseases of the circulatory system were the most common cause of death (25.4%), followed by neoplasms (25.1%) and diseases of the respiratory system (10.6%) in atomic bomb survivors who died between 1992 and 2019. The proportional mortality associated with respiratory diseases, nervous system diseases, and other diseases among atomic bomb survivors was higher than that of the general population. Of the dead people between 1992 and 2019, the age at death of survivors who were exposed at a close distance was younger than those who were exposed at a greater distance. CONCLUSION: Overall, proportional mortality of respiratory diseases and nervous system diseases was high in atomic bomb survivors, compared with the general population. Further studies on the health status of Korean atomic bomb survivors are needed.

Cohort Study Protocol: A Cohort of Korean Atomic Bomb Survivors and Their Offspring.

In 1945, atomic bombs were dropped on Hiroshima and Nagasaki. Approximately 70 000 Koreans are estimated to have been exposed to radiation from atomic bombs at that time. After Korea's Liberation Day, approximately 23 000 of these people returned to Korea. To investigate the long-term health and hereditary effects of atomic bomb exposure on the offspring, cohort studies have been conducted on atomic bomb survivors in Japan. This study is an ongoing cohort study to determine the health status of Korean atomic bomb survivors and investigate whether any health effects were inherited by their offspring. Atomic bomb survivors are defined by the Special Act On the Support for Korean Atomic Bomb Victims, and their offspring are identified by participating atomic bomb survivors. As of 2024, we plan to recruit 1500 atomic bomb survivors and their offspring, including 200 trios with more than 300 people. Questionnaires regarding socio-demographic factors, health behaviors, past medical history, laboratory tests, and pedigree information comprise the data collected to minimize survival bias. For the 200 trios, whole-genome analysis is planned to identify de novo mutations in atomic bomb survivors and to compare the prevalence of de novo mutations with trios in the general population. Active follow-up based on telephone surveys and passive follow-up with linkage to the Korean Red Cross, National Health Insurance Service, death registry, and Korea Central Cancer Registry data are ongoing. By combining pedigree information with the findings of trio-based whole-genome analysis, the results will elucidate the hereditary health effects of atomic bomb exposure.

Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets.

Variant callers typically produce massive numbers of false positives for structural variations, such as cancer-relevant copy-number alterations and fusion genes resulting from genome rearrangements. Here we describe an ultrafast and accurate detector of somatic structural variations that reduces read-mapping costs by filtering out reads matched to pan-genome k-mer sets. The detector, which we named ETCHING (for efficient detection of chromosomal rearrangements and fusion genes), reduces the number of false positives by leveraging machine-learning classifiers trained with six breakend-related features (clipped-read count, split-reads count, supporting paired-end read count, average mapping quality, depth difference and total length of clipped bases). When benchmarked against six callers on reference cell-free DNA, validated biomarkers of structural variants, matched tumour and normal whole genomes, and tumour-only targeted sequencing datasets, ETCHING was 11-fold faster than the second-fastest structural-variant caller at comparable performance and memory use. The speed and accuracy of ETCHING may aid large-scale genome projects and facilitate practical implementations in precision medicine.

hnRNPC induces isoform shifts in miR-21-5p leading to cancer development.

MicroRNA (miRNA) processing is a critical step in mature miRNA production. Its dysregulation leads to an increase in miRNA isoforms with heterogenous 5'-ends (isomiRs), which can recognize distinct target sites because of their shifted seed sequence. Although some miRNA genes display productive expression of their 5'-isomiRs in cancers, how their production is controlled and how 5'-isomiRs affect tumor progression have yet to be explored. In this study, based on integrative analyses of high-throughput sequencing data produced by our group and publicly available data, we demonstrate that primary miR-21 (pri-miR-21) is processed into the cancer-specific isomiR isomiR-21-5p | ±1, which suppresses growth hormone receptor (GHR) in liver cancer. Treatment with antagomirs against isomiR-21-5p | ±1 inhibited the in vitro tumorigenesis of liver cancer cells and allowed the recovery of GHR, whereas the introduction of isomiR-21-5p | ±1 mimics attenuated these effects. These effects were validated in a mouse model of spontaneous liver cancer. Heterogeneous nuclear ribonucleoprotein C and U2 small nuclear RNA auxiliary factor 2 were predicted to bind upstream of pre-miR-21 via a poly-(U) motif and influence Drosha processing to induce the production of isomiR-21-5p | ±1. Our findings suggest an oncogenic function for the non-canonical isomiR-21-5p | ±1 in liver cancer, and its production was shown to be regulated by hnRNPC.

Tumor immune microenvironment lncRNAs.

Long non-coding ribonucleic acids (RNAs) (lncRNAs) are key players in tumorigenesis and immune responses. The nature of their cell type-specific gene expression and other functional evidence support the idea that lncRNAs have distinct cellular functions in the tumor immune microenvironment (TIME). To date, the majority of lncRNA studies have heavily relied on bulk RNA-sequencing data in which various cell types contribute to an averaged signal, limiting the discovery of cell type-specific lncRNA functions. Single-cell RNA-sequencing (scRNA-seq) is a potential solution for tackling this limitation despite the lack of annotations for low abundance yet cell type-specific lncRNAs. Hence, updated annotations and further understanding of the cellular expression of lncRNAs will be necessary for characterizing cell type-specific functions of lncRNA genes in the TIME. In this review, we discuss lncRNAs that are specifically expressed in tumor and immune cells, summarize the regulatory functions of the lncRNAs at the cell type level and highlight how a scRNA-seq approach can help to study the cell type-specific functions of TIME lncRNAs.

The regulatory impact of RNA-binding proteins on microRNA targeting.

Argonaute is the primary mediator of metazoan miRNA targeting (MT). Among the currently identified >1,500 human RNA-binding proteins (RBPs), there are only a handful of RBPs known to enhance MT and several others reported to suppress MT, leaving the global impact of RBPs on MT elusive. In this study, we have systematically analyzed transcriptome-wide binding sites for 150 human RBPs and evaluated the quantitative effect of individual RBPs on MT efficacy. In contrast to previous studies, we show that most RBPs significantly affect MT and that all of those MT-regulating RBPs function as MT enhancers rather than suppressors, by making the local secondary structure of the target site accessible to Argonaute. Our findings illuminate the unappreciated regulatory impact of human RBPs on MT, and as these RBPs may play key roles in the gene regulatory network governed by metazoan miRNAs, MT should be understood in the context of co-regulating RBPs.

Preoperative immune landscape predisposes adverse outcomes in hepatocellular carcinoma patients with liver transplantation.

Immune class in hepatocellular carcinoma (HCC) has been shown to possess immunogenic power; however, how preestablished immune landscapes in premalignant and early HCC stages impact the clinical outcomes of HCC patients remains unexplored. We sequenced bulk transcriptomes for 62 malignant tumor samples from a Korean HCC cohort in which 38 patients underwent total hepatectomy, as well as for 15 normal and 47 adjacent nontumor samples. Using in silico deconvolution of expression mixtures, 22 immune cell fractions for each sample were inferred, and validated with immune cell counting by immunohistochemistry. Cell type-specific immune signatures dynamically shifted from premalignant stages to the late HCC stage. Total hepatectomy patients displayed elevated immune infiltration and prolonged disease-free survival compared to the partial hepatectomy patients. However, patients who exhibited an infiltration of regulatory T cells (Tregs) during the pretransplantation period displayed a high risk of tumor relapse with suppressed immune responses, and pretreatment was a potential driver of Treg infiltration in the total hepatectomy group. Treg infiltration appeared to be independent of molecular classifications based on transcriptomic data. Our study provides not only comprehensive immune signatures in adjacent nontumor lesions and early malignant HCC stages but also clinical guidance for HCC patients who will undergo liver transplantation.

An Inflammatory Loop Between Spleen-Derived Myeloid Cells and CD4+ T Cells Leads to Accumulation of Long-Lived Plasma Cells That Exacerbates Lupus Autoimmunity.

Splenic long-lived plasma cells are abnormally numerous and deleterious in systemic autoimmune diseases, yet how they accumulate remains poorly understood. We demonstrate here that a pathological role of spleen-derived CD11b+Gr-1+ myeloid cells (SDMCs) underpins the accumulation of splenic long-lived plasma cells in a lupus-prone model named sanroque. We found that SDMCs were progressively accumulated in sanroque mice from the early clinical phase. Transcriptome profiles revealed that SDMCs have a predominant shift toward an inflammatory phenotype relative to the bone marrow-derived counterparts and are distinct from neutrophils and monocytes. SDMCs were expanded in situ via splenic extramedullary myelopoiesis under the proinflammatory cytokine milieu during lupus progression. SDMCs promoted the development of IFN-γ-secreting Th1 and follicular helper T cells, thereby licensing CD4+ T cells to be pathologic activators of SDMCs and plasma cells. SDMCs also directly promoted the survival of plasma cells by providing B-cell activating factor of the TNF family. The frequency of SDMCs correlated with that of splenic long-lived plasma cells. Selective depletion of CD11b+Gr-1+ cells reduced autoantibody production in sanroque mice. Thus, our findings suggest that SDMCs expanded in situ establish a positive feedback loop with CD4+ T cells, leading to accumulation of long-lived plasma cells which exacerbates lupus autoimmunity.

Author Correction: Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Single-cell transcriptome maps of myeloid blood cell lineages in Drosophila.

The Drosophila lymph gland, the larval hematopoietic organ comprised of prohemocytes and mature hemocytes, has been a valuable model for understanding mechanisms underlying hematopoiesis and immunity. Three types of mature hemocytes have been characterized in the lymph gland: plasmatocytes, lamellocytes, and crystal cells, which are analogous to vertebrate myeloid cells, yet molecular underpinnings of the lymph gland hemocytes have been less investigated. Here, we use single-cell RNA sequencing to comprehensively analyze heterogeneity of developing hemocytes in the lymph gland, and discover previously undescribed hemocyte types including adipohemocytes, stem-like prohemocytes, and intermediate prohemocytes. Additionally, we identify the developmental trajectory of hemocytes during normal development as well as the emergence of the lamellocyte lineage following active cellular immunity caused by wasp infestation. Finally, we establish similarities and differences between embryonically derived- and larval lymph gland hemocytes. Altogether, our study provides detailed insights into the hemocyte development and cellular immune responses at single-cell resolution.

A single-cell survey of Drosophila blood.

Drosophila blood cells, called hemocytes, are classified into plasmatocytes, crystal cells, and lamellocytes based on the expression of a few marker genes and cell morphologies, which are inadequate to classify the complete hemocyte repertoire. Here, we used single-cell RNA sequencing (scRNA-seq) to map hemocytes across different inflammatory conditions in larvae. We resolved plasmatocytes into different states based on the expression of genes involved in cell cycle, antimicrobial response, and metabolism together with the identification of intermediate states. Further, we discovered rare subsets within crystal cells and lamellocytes that express fibroblast growth factor (FGF) ligand branchless and receptor breathless, respectively. We demonstrate that these FGF components are required for mediating effective immune responses against parasitoid wasp eggs, highlighting a novel role for FGF signaling in inter-hemocyte crosstalk. Our scRNA-seq analysis reveals the diversity of hemocytes and provides a rich resource of gene expression profiles for a systems-level understanding of their functions.

CGD: Comprehensive guide designer for CRISPR-Cas systems.

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas systems, including dead Cas9 (dCas9), Cas9, and Cas12a, have revolutionized genome engineering in mammalian somatic cells. Although computational tools that assess the target sites of CRISPR-Cas systems are inevitably important for designing efficient guide RNAs (gRNAs), they exhibit generalization issues in selecting features and do not provide optimal results in a comprehensive manner. Here, we introduce a Comprehensive Guide Designer (CGD) for four different CRISPR systems, which utilizes the machine learning algorithm, Elastic Net Logistic Regression (ENLOR), to autonomously generalize the models. CGD contains specific models trained with public datasets generated by CRISPRi, CRISPRa, CRISPR-Cas9, and CRISPR-Cas12a (designated as CGDi, CGDa, CGD9, and CGD12a, respectively) in an unbiased manner. The trained CGD models were benchmarked to other regression-based machine learning models, such as ElasticNet Linear Regression (ENLR), Random Forest and Boruta (RFB), and Extreme Gradient Boosting (Xgboost) with inbuilt feature selection. Evaluation with independent test datasets showed that CGD models outperformed the pre-existing methods in predicting the efficacy of gRNAs. All CGD source codes and datasets are available at GitHub (https://github.com/vipinmenon1989/CGD), and the CGD webserver can be accessed at http://big.hanyang.ac.kr:2195/CGD.

Mass Cytometry and Single-Cell RNA-seq Profiling of the Heterogeneity in Human Peripheral Blood Mononuclear Cells Interacting with Silver Nanoparticles.

Understanding the interactions between nanoparticles (NPs) and human immune cells is necessary for justifying their utilization in consumer products and biomedical applications. However, conventional assays may be insufficient in describing the complexity and heterogeneity of cell-NP interactions. Herein, mass cytometry and single-cell RNA-sequencing (scRNA-seq) are complementarily used to investigate the heterogeneous interactions between silver nanoparticles (AgNPs) and primary immune cells. Mass cytometry reveals the heterogeneous biodistribution of the positively charged polyethylenimine-coated AgNPs in various cell types and finds that monocytes and B cells have higher association with the AgNPs than other populations. scRNA-seq data of these two cell types demonstrate that each type has distinct responses to AgNP treatment: NRF2-mediated oxidative stress is confined to B cells, whereas monocytes show Fcγ-mediated phagocytosis. Besides the between-population heterogeneity, analysis of single-cell dose-response relationships further reveals within-population diversity for the B cells and naïve CD4+ T cells. Distinct subsets having different levels of cellular responses with respect to their cellular AgNP doses are found. This study demonstrates that the complementary use of mass cytometry and scRNA-seq is helpful for gaining in-depth knowledge on the heterogeneous interactions between immune cells and NPs and can be incorporated into future toxicity assessments of nanomaterials.

Assessment of Inflammation in Pulmonary Artery Hypertension by 68Ga-Mannosylated Human Serum Albumin.

Rationale: Diagnosis and monitoring of patients with pulmonary artery hypertension (PAH) is currently difficult.Objectives: We aimed to develop a noninvasive imaging modality for PAH that tracks the infiltration of macrophages into the pulmonary vasculature, using a positron emission tomography (PET) agent, 68Ga-2-(p-isothiocyanatobenzyl)-1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) mannosylated human serum albumin (MSA), that targets the mannose receptor (MR).Methods: We induced PAH in rats by monocrotaline injection. Tissue analysis, echocardiography, and 68Ga-NOTA-MSA PET were performed weekly in rats after monocrotaline injection and in those treated with either sildenafil or macitentan. The translational potential of 68Ga-NOTA-MSA PET was explored in patients with PAH.Measurements and Main Results: Gene sets related to macrophages were significantly enriched on whole transcriptome sequencing of the lung tissue in PAH rats. Serial PET images of PAH rats demonstrated increasing uptake of 68Ga-NOTA-MSA in the lung by time that corresponded with the MR-positive macrophage recruitment observed in immunohistochemistry. In sildenafil- or macitentan-treated PAH rats, the infiltration of MR-positive macrophages by histology and the uptake of 68Ga-NOTA-MSA on PET was significantly lower than that of the PAH-only group. The pulmonary uptake of 68Ga-NOTA-MSA was significantly higher in patients with PAH than normal subjects (P = 0.009) or than those with pulmonary hypertension by left heart disease (P = 0.019) (n = 5 per group).Conclusions:68Ga-NOTA-MSA PET can help diagnose PAH and monitor the inflammatory status by imaging the degree of macrophage infiltration into the lung. These observations suggest that 68Ga-NOTA-MSA PET has the potential to be used as a novel noninvasive diagnostic and monitoring tool of PAH.

Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse.

The Jeju horse, indigenous to the Jeju Island in Korea may have originated from Mongolian horses. Adaptations to the local harsh environment have conferred Jeju horse with unique traits such as small-sized body, stocky head, and shorter limbs. These characteristics have not been studied previously at the genomic level. Therefore, we sequenced and compared the genome of 41 horses belonging to 6 breeds. We identified numerous breed-specific non-synonymous SNPs and loss-of-function mutants. Demographic and admixture analyses showed that, though Jeju horse is genetically the closest to the Mongolian breeds, its genetic ancestry is independent of that of the Mongolian breeds. Genome wide selection signature analysis revealed that genes such as LCORL, MSTN, HMGA2, ZFAT, LASP1, PDK4, and ACTN2, were positively selected in the Jeju horse. RNAseq analysis showed that several of these genes were also differentially expressed in Jeju horse compared to Thoroughbred horse. Comparative muscle fiber analysis showed that, the type I muscle fibre content was substantially higher in Jeju horse compared to Thoroughbred horse. Our results provide insights about the selection of complex phenotypic traits in the small-sized Jeju horse and the novel SNPs identified will aid in designing high-density SNP chip for studying other native horse breeds.