Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

Circular RNAs in peripheral blood mononuclear cells are more stable than linear RNAs upon sample processing delay.

Circular RNAs (circRNAs) are a novel class of RNAs with closed loop structure. Blood circRNAs are widely acknowledged to be more stable than linear mRNAs, which show promising prospect to be liquid biopsy biomarkers for clinical applications. However, accumulating studies have demonstrated that sample processing delays have profound effects on blood transcriptome expression profiles, wherein knowledge remains elusive about the impacts of prolonged sample processing on blood expression profiles of circRNAs. We collected whole blood samples from three donors and isolated peripheral blood mononuclear cells (PBMCs) at six different incubation time points. We measured total RNA expression profiles using RNA sequencing (RNA-seq) and investigated the differentially expressed circRNAs, mRNAs and lncRNAs upon blood processing delay. Meanwhile, we explored the underlying inducement of aberrant expression of circRNAs against their corresponding mRNA transcripts. Finally, we utilized rMATS-turbo and CIRI-AS, respectively, to screen out differential alternative splicing (AS) events in linear mRNAs and circRNAs. Sample incubation at 4°C lasting to 48 hours (h) led to minimal effects to circRNAs' expression. However, it induced extensive alterations for mRNAs and lncRNAs when the incubation time was beyond 12 h. Additionally, only 2 h processing delays may result in profound impacts on AS events of linear mRNAs, while less impact on the equivalence of circRNAs. Our results suggested that PBMC circRNAs are stable upon sample processing delay, which are more suitable to be liquid biopsy biomarkers.

AQUARIUM: accurate quantification of circular isoforms using model-based strategy.

SUMMARY: Currently, most computational methods estimate the expression of circular RNAs (circRNAs) using the number of sequencing reads that support back-splicing junctions (BSJ) in RNA-seq data, which may introduce biased estimation of circRNA expression due to the uneven distribution of sequencing reads. To overcome this, we previously developed a model-based strategy for circRNA quantification, enabling consideration of sequencing reads from the entire transcript. Yet, the lack of exact transcript structure of circRNAs may limit its accuracy. Here, we proposed a substantially improved circRNA quantification tool, AQUARIUM, by introducing the full-length RNA structure of circular isoforms. We assessed its performance in circRNA quantification using both biological and simulated rRNA-depleted RNA-seq datasets, and demonstrated its superior performance at both BSJ and isoform level. AVAILABILITY AND IMPLEMENTATION: AQUARIUM is freely available at https://github.com/wanjun-group-seu/AQUARIUM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Peripheral blood non-canonical small non-coding RNAs as novel biomarkers in lung cancer.

One unmet challenge in lung cancer diagnosis is to accurately differentiate lung cancer from other lung diseases with similar clinical symptoms and radiological features, such as pulmonary tuberculosis (TB). To identify reliable biomarkers for lung cancer screening, we leverage the recently discovered non-canonical small non-coding RNAs (i.e., tRNA-derived small RNAs [tsRNAs], rRNA-derived small RNAs [rsRNAs], and YRNA-derived small RNAs [ysRNAs]) in human peripheral blood mononuclear cells and develop a molecular signature composed of distinct ts/rs/ysRNAs (TRY-RNA). Our TRY-RNA signature precisely discriminates between control, lung cancer, and pulmonary TB subjects in both the discovery and validation cohorts and outperforms microRNA-based biomarkers, which bears the diagnostic potential for lung cancer screening.

Rat BodyMap transcriptomes reveal unique circular RNA features across tissue types and developmental stages.

Circular RNAs (circRNAs) are a novel class of regulatory RNAs. Here, we present a comprehensive investigation of circRNA expression profiles across 11 tissues and four developmental stages in rats, along with cross-species analyses in humans and mice. Although the expression of circRNAs is positively correlated with that of cognate mRNAs, highly expressed genes tend to splice a larger fraction of circular transcripts. Moreover, circRNAs exhibit higher tissue specificity than cognate mRNAs. Intriguingly, while we observed a monotonic increase of circRNA abundance with age in the rat brain, we further discovered a dynamic, age-dependent pattern of circRNA expression in the testes that is characterized by a dramatic increase with advancing stages of sexual maturity and a decrease with aging. The age-sensitive testicular circRNAs are highly associated with spermatogenesis, independent of cognate mRNA expression. The tissue/age implications of circRNAs suggest that they present unique physiological functions rather than simply occurring as occasional by-products of gene transcription.

Technical progress in circulating tumor DNA analysis using next generation sequencing.

Circulating tumor DNA (ctDNA) is tumor-derived, fragmented DNA that circulates freely in body fluids, predominantly in the peripheral blood. Recently, ctDNA analysis has been suggested as a complement to tissue biopsy in the detection and treatment of cancer. Genetic and epigenetic information specific to tumor cells, including single nucleotide variations, copy number variations, and modified methylation patterns, can be detected in ctDNA. Importantly, mutations in heterogenous tumors that could impart therapeutic resistance could be identified in ctDNA, which would aid in cancer diagnosis, prognosis, and real-time monitoring, and inform treatment with targeted therapies. However, ctDNA is still not a routinely used method for this purpose, because its detection techniques lack adequate sensitivity for reliable use in scientific studies and clinical trials. This review provides an up-to-date summary of ctDNA mutation detection methods based on next generation sequencing, highlighting their advantages and limitations, and focusing in particular on several optimized library preparation methods for improved sensitivity and specificity of ctDNA detection.

Quantifying circular RNA expression from RNA-seq data using model-based framework.

MOTIVATION: Circular RNAs (circRNAs) are a class of non-coding RNAs that are widely expressed in various cell lines and tissues of many organisms. Although the exact function of many circRNAs is largely unknown, the cell type-and tissue-specific circRNA expression has implicated their crucial functions in many biological processes. Hence, the quantification of circRNA expression from high-throughput RNA-seq data is becoming important to ascertain. Although many model-based methods have been developed to quantify linear RNA expression from RNA-seq data, these methods are not applicable to circRNA quantification. RESULTS: Here, we proposed a novel strategy that transforms circular transcripts to pseudo-linear transcripts and estimates the expression values of both circular and linear transcripts using an existing model-based algorithm, Sailfish. The new strategy can accurately estimate transcript expression of both linear and circular transcripts from RNA-seq data. Several factors, such as gene length, amount of expression and the ratio of circular to linear transcripts, had impacts on quantification performance of circular transcripts. In comparison to count-based tools, the new computational framework had superior performance in estimating the amount of circRNA expression from both simulated and real ribosomal RNA-depleted (rRNA-depleted) RNA-seq datasets. On the other hand, the consideration of circular transcripts in expression quantification from rRNA-depleted RNA-seq data showed substantial increased accuracy of linear transcript expression. Our proposed strategy was implemented in a program named Sailfish-cir. AVAILABILITY AND IMPLEMENTATION: Sailfish-cir is freely available at https://github.com/zerodel/Sailfish-cir . CONTACT: tongz@medicine.nevada.edu or wanjun.gu@gmail.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The role of RNA structure at 5' untranslated region in microRNA-mediated gene regulation.

Recent studies have suggested that the secondary structure of the 5' untranslated region (5' UTR) of messenger RNA (mRNA) is important for microRNA (miRNA)-mediated gene regulation in humans. mRNAs that are targeted by miRNA tend to have a higher degree of local secondary structure in their 5' UTR; however, the general role of the 5' UTR in miRNA-mediated gene regulation remains unknown. We systematically surveyed the secondary structure of 5' UTRs in both plant and animal species and found a universal trend of increased mRNA stability near the 5' cap in mRNAs that are regulated by miRNA in animals, but not in plants. Intra-genome comparison showed that gene expression level, GC content of the 5' UTR, number of miRNA target sites, and 5' UTR length may influence mRNA structure near the 5' cap. Our results suggest that the 5' UTR secondary structure performs multiple functions in regulating post-transcriptional processes. Although the local structure immediately upstream of the start codon is involved in translation initiation, RNA structure near the 5' cap site, rather than the structure of the full-length 5' UTR sequences, plays an important role in miRNA-mediated gene regulation.

The sequence and de novo assembly of the giant panda genome.

Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes.

The Burmese python genome reveals the molecular basis for extreme adaptation in snakes.

Snakes possess many extreme morphological and physiological adaptations. Identification of the molecular basis of these traits can provide novel understanding for vertebrate biology and medicine. Here, we study snake biology using the genome sequence of the Burmese python (Python molurus bivittatus), a model of extreme physiological and metabolic adaptation. We compare the python and king cobra genomes along with genomic samples from other snakes and perform transcriptome analysis to gain insights into the extreme phenotypes of the python. We discovered rapid and massive transcriptional responses in multiple organ systems that occur on feeding and coordinate major changes in organ size and function. Intriguingly, the homologs of these genes in humans are associated with metabolism, development, and pathology. We also found that many snake metabolic genes have undergone positive selection, which together with the rapid evolution of mitochondrial proteins, provides evidence for extensive adaptive redesign of snake metabolic pathways. Additional evidence for molecular adaptation and gene family expansions and contractions is associated with major physiological and phenotypic adaptations in snakes; genes involved are related to cell cycle, development, lungs, eyes, heart, intestine, and skeletal structure, including GRB2-associated binding protein 1, SSH, WNT16, and bone morphogenetic protein 7. Finally, changes in repetitive DNA content, guanine-cytosine isochore structure, and nucleotide substitution rates indicate major shifts in the structure and evolution of snake genomes compared with other amniotes. Phenotypic and physiological novelty in snakes seems to be driven by system-wide coordination of protein adaptation, gene expression, and changes in the structure of the genome.

Altered splenic miRNA expression profile in H1N1 swine influenza.

Previous studies have demonstrated the key regulatory roles played by microRNAs (miRNAs) in influenza virus-host interactions. To gain more insight into the contribution of miRNAs to the host immune response, spleen tissues from mice infected with A/Swine/GD/2/12 (H1N1) virus were harvested 5 days postinfection, and miRNA deep sequencing was performed. The results showed that 50 miRNAs were modulated. Interestingly, pathway analysis of miRNAs and targets showed that upregulated miR-124-3p interacts with innate immune-related pathways such as the Toll-like receptor pathway, RIG-I-like receptor signaling pathway, NOD-like receptor signaling pathway and JAK-STAT signaling pathway, and this might play a major role in the anti-inflammatory response. Further understanding of the roles played by these miRNAs in influenza virus infection will provide new insights into host-pathogen interactions.

The impact of RNA structure on coding sequence evolution in both bacteria and eukaryotes.

BACKGROUND: Many studies have found functional RNA secondary structures are selectively conserved among species. But, the effect of RNA structure selection on coding sequence evolution remains unknown. To address this problem, we systematically investigated the relationship between nucleotide conservation level and its structural sensitivity in four model organisms, Escherichia coli, yeast, fly, and mouse. RESULTS: We define structurally sensitive sites as those with putative local structure-disruptive mutations. Using both the Mantel-Haenszel procedure and association test, we found structurally sensitive nucleotide sites evolved more slowly than non-sensitive sites in all four organisms. Furthermore, we observed that this association is more obvious in highly expressed genes and region near the start codon. CONCLUSION: We conclude that structurally sensitive sites in mRNA sequences normally have less nucleotide divergence in all species we analyzed. This study extends our understanding of the impact of RNA structure on coding sequence evolution, and is helpful to the development of a codon model with RNA structure information.

Repetitive elements may comprise over two-thirds of the human genome.

Transposable elements (TEs) are conventionally identified in eukaryotic genomes by alignment to consensus element sequences. Using this approach, about half of the human genome has been previously identified as TEs and low-complexity repeats. We recently developed a highly sensitive alternative de novo strategy, P-clouds, that instead searches for clusters of high-abundance oligonucleotides that are related in sequence space (oligo "clouds"). We show here that P-clouds predicts >840 Mbp of additional repetitive sequences in the human genome, thus suggesting that 66%-69% of the human genome is repetitive or repeat-derived. To investigate this remarkable difference, we conducted detailed analyses of the ability of both P-clouds and a commonly used conventional approach, RepeatMasker (RM), to detect different sized fragments of the highly abundant human Alu and MIR SINEs. RM can have surprisingly low sensitivity for even moderately long fragments, in contrast to P-clouds, which has good sensitivity down to small fragment sizes (∼25 bp). Although short fragments have a high intrinsic probability of being false positives, we performed a probabilistic annotation that reflects this fact. We further developed "element-specific" P-clouds (ESPs) to identify novel Alu and MIR SINE elements, and using it we identified ∼100 Mb of previously unannotated human elements. ESP estimates of new MIR sequences are in good agreement with RM-based predictions of the amount that RM missed. These results highlight the need for combined, probabilistic genome annotation approaches and suggest that the human genome consists of substantially more repetitive sequence than previously believed.

Acute Lung Injury and the NLRP3 Inflammasome.

Acute lung injury (ALI) manifests through harm to the capillary endothelium and alveolar epithelial cells, arising from a multitude of factors, leading to scattered interstitial alterations, pulmonary edema, and subsequent acute hypoxic respiratory insufficiency. Acute lung injury (ALI), along with its more serious counterpart, acute respiratory distress syndrome (ARDS), carry a fatality rate that hovers around 30-40%. Its principal pathological characteristic lies in the unchecked inflammatory reaction. Currently, the main strategies for treating ALI are alleviation of inflammation and prevention of respiratory failure. Concerning the etiology of ALI, NLRP3 Inflammasome is essential to the body's innate immune response. The composition of this inflammasome complex includes NLRP3, the pyroptosis mediator ASC, and pro-caspase-1. Recent research has reported that the inflammatory response centered on NLRP3 inflammasomes plays a key part in inflammation in ALI, and may hence be a prospective candidate for therapeutic intervention. In the review, we present an overview of the ailment characteristics of acute lung injury along with the constitution and operation of the NLRP3 inflammasome within this framework. We also explore therapeutic strategies targeting the NLRP3 inflammasome to combat acute lung injury.

Development of multiplexed orthogonal base editor (MOBE) systems.

Base editors (BEs) enable efficient, programmable installation of point mutations while avoiding the use of double-strand breaks. Simultaneous application of two or more different BEs, such as an adenine BE (which converts A·T base pairs to G·C) and a cytosine BE (which converts C·G base pairs to T·A), is not feasible because guide RNA crosstalk results in non-orthogonal editing, with all BEs modifying all target loci. Here we engineer both adenine BEs and cytosine BEs that can be orthogonally multiplexed by using RNA aptamer-coat protein systems to recruit the DNA-modifying enzymes directly to the guide RNAs. We generate four multiplexed orthogonal BE systems that enable rates of precise co-occurring edits of up to 7.1% in the same DNA strand without enrichment or selection strategies. The addition of a fluorescent enrichment strategy increases co-occurring edit rates up to 24.8% in human cells. These systems are compatible with expanded protospacer adjacent motif and high-fidelity Cas9 variants, function well in multiple cell types, have equivalent or reduced off-target propensities compared with their parental systems and can model disease-relevant point mutation combinations.

Transcriptomic Analysis of the Rat Dorsal Root Ganglion After Fracture.

In fractures, pain signals are transmitted from the dorsal root ganglion (DRG) to the brain, and the DRG generates efferent signals to the injured bone to participate in the injury response. However, little is known about how this process occurs. We analyzed DRG transcriptome at 3, 7, 14, and 28 days after fracture. We identified the key pathways through KEGG and GO enrichment analysis. We then used IPA analysis to obtain upstream regulators and disease pathways. Finally, we compared the sequencing results with those of nerve injury to identify the unique transcriptome changes in DRG after fracture. We found that the first 14 days after fracture were the main repair response period, the 3rd day was the peak of repair activity, the 14th day was dominated by the stimulus response, and on the 28th day, the repair response had reached a plateau. ECM-receptor interaction, protein digestion and absorption, and the PI3K-Akt signaling pathway were most significantly enriched, which may be involved in repair regeneration, injury response, and pain transmission. Compared with the nerve injury model, DRG after fracture produced specific alterations related to bone repair, and the bone density function was the most widely activated bone-related function. Our results obtained some important genes and pathways in DRG after fracture, and we also summarized the main features of transcriptome function at each time point through functional annotation clustering of GO pathway, which gave us a deeper understanding of the role played by DRG in fracture.

Predicting the complexity and mortality of polytrauma patients with machine learning models.

We aim to develop machine learning (ML) models for predicting the complexity and mortality of polytrauma patients using clinical features, including physician diagnoses and physiological data. We conducted a retrospective analysis of a cohort comprising 756 polytrauma patients admitted to the intensive care unit (ICU) at Pizhou People's Hospital Trauma Center, Jiangsu, China between 2020 and 2022. Clinical parameters encompassed demographics, vital signs, laboratory values, clinical scores and physician diagnoses. The two primary outcomes considered were mortality and complexity. We developed ML models to predict polytrauma mortality or complexity using four ML algorithms, including Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN) and eXtreme Gradient Boosting (XGBoost). We assessed the models' performance and compared the optimal ML model against three existing trauma evaluation scores, including Injury Severity Score (ISS), Trauma Index (TI) and Glasgow Coma Scale (GCS). In addition, we identified several important clinical predictors that made contributions to the prognostic models. The XGBoost-based polytrauma mortality prediction model demonstrated a predictive ability with an accuracy of 90% and an F-score of 88%, outperforming SVM, RF and ANN models. In comparison to conventional scoring systems, the XGBoost model had substantial improvements in predicting the mortality of polytrauma patients. External validation yielded strong stability and generalization with an accuracy of up to 91% and an AUC of 82%. To predict polytrauma complexity, the XGBoost model maintained its performance over other models and scoring systems with good calibration and discrimination abilities. Feature importance analysis highlighted several clinical predictors of polytrauma complexity and mortality, such as Intracranial hematoma (ICH). Leveraging ML algorithms in polytrauma care can enhance the prognostic estimation of polytrauma patients. This approach may have potential value in the management of polytrauma patients.

Genomic Selection Signals in Andean Highlanders Reveal Adaptive Placental Metabolic Phenotypes That Are Disrupted in Preeclampsia.

BACKGROUND: The chronic hypoxia of high-altitude residence poses challenges for tissue oxygen supply and metabolism. Exposure to high altitude during pregnancy increases the incidence of hypertensive disorders of pregnancy and fetal growth restriction and alters placental metabolism. High-altitude ancestry protects against altitude-associated fetal growth restriction, indicating hypoxia tolerance that is genetic in nature. Yet, not all babies are protected and placental pathologies associated with fetal growth restriction occur in some Andean highlanders. METHODS: We examined placental metabolic function in 79 Andeans (18-45 years; 39 preeclamptic and 40 normotensive) living in La Paz, Bolivia (3600-4100 m) delivered by unlabored Cesarean section. Using a selection-nominated approach, we examined links between putatively adaptive genetic variation and phenotypes related to oxygen delivery or placental metabolism. RESULTS: Mitochondrial oxidative capacity was associated with fetal oxygen delivery in normotensive but not preeclamptic placenta and was also suppressed in term preeclamptic pregnancy. Maternal haplotypes in or within 200 kb of selection-nominated genes were associated with lower placental mitochondrial respiratory capacity (PTPRD [protein tyrosine phosphatase receptor-δ]), lower maternal plasma erythropoietin (CPT2 [carnitine palmitoyl transferase 2], proopiomelanocortin, and DNMT3 [DNA methyltransferase 3]), and lower VEGF (vascular endothelial growth factor) in umbilical venous plasma (TBX5 [T-box transcription factor 5]). A fetal haplotype within 200 kb of CPT2 was associated with increased placental mitochondrial complex II capacity, placental nitrotyrosine, and GLUT4 (glucose transporter type 4) protein expression. CONCLUSIONS: Our findings reveal novel associations between putatively adaptive gene regions and phenotypes linked to oxygen delivery and placental metabolic function in highland Andeans, suggesting that such effects may be of genetic origin. Our findings also demonstrate maladaptive metabolic mechanisms in the context of preeclampsia, including dysregulation of placental oxygen consumption.

Functional EPAS1/HIF2A missense variant is associated with hematocrit in Andean highlanders.

Hypoxia-inducible factor pathway genes are linked to adaptation in both human and nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated with relatively lower hemoglobin concentration in Tibetans. We provide evidence for an association between an adaptive EPAS1 variant (rs570553380) and the same phenotype of relatively low hematocrit in Andean highlanders. This Andean-specific missense variant is present at a modest frequency in Andeans and absent in other human populations and vertebrate species except the coelacanth. CRISPR-base-edited human cells with this variant exhibit shifts in hypoxia-regulated gene expression, while metabolomic analyses reveal both genotype and phenotype associations and validation in a lowland population. Although this genocopy of relatively lower hematocrit in Andean highlanders parallels well-replicated findings in Tibetans, it likely involves distinct pathway responses based on a protein-coding versus noncoding variants, respectively. These findings illuminate how unique variants at EPAS1 contribute to the same phenotype in Tibetans and a subset of Andean highlanders despite distinct evolutionary trajectories.

Expression profiling of ion channel genes predicts clinical outcome in breast cancer.

BACKGROUND: Ion channels play a critical role in a wide variety of biological processes, including the development of human cancer. However, the overall impact of ion channels on tumorigenicity in breast cancer remains controversial. METHODS: We conduct microarray meta-analysis on 280 ion channel genes. We identify candidate ion channels that are implicated in breast cancer based on gene expression profiling. We test the relationship between the expression of ion channel genes and p53 mutation status, ER status, and histological tumor grade in the discovery cohort. A molecular signature consisting of ion channel genes (IC30) is identified by Spearman's rank correlation test conducted between tumor grade and gene expression. A risk scoring system is developed based on IC30. We test the prognostic power of IC30 in the discovery and seven validation cohorts by both Cox proportional hazard regression and log-rank test. RESULTS: 22, 24, and 30 ion channel genes are found to be differentially expressed with a change in p53 mutation status, ER status, and tumor histological grade in the discovery cohort. We assign the 30 tumor grade associated ion channel genes as the IC30 gene signature. We find that IC30 risk score predicts clinical outcome (P < 0.05) in the discovery cohort and 6 out of 7 validation cohorts. Multivariate and univariate tests conducted in two validation cohorts indicate that IC30 is a robust prognostic biomarker, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node status, tumor size, tumor grade, estrogen and progesterone receptor status, and p53 mutation status. CONCLUSIONS: We identified a molecular gene signature IC30, which represents a promising diagnostic and prognostic biomarker in breast cancer. Our results indicate that information regarding the expression of ion channels in tumor pathology could provide new targets for therapy in human cancers.