Deep Transcriptome Research Articles

Identification and Characterization of Four Novel Viruses in Balclutha incisa.

Balclutha incisa (Cicadellidae: Deltocephalinae), a leafhopper prevalent in tropical and temperate regions, is notably abundant in grasses and rice. The virome of B. incisa was investigated using deep transcriptome sequencing, leading to the first identification of four viruses belonging to the families Aliusviridae, Iflaviridae, and Totiviridae in B. incisa. These viruses have been provisionally named B. incisa ollusvirus 1 (BiOV1), B. incisa ollusvirus 2 (BiOV2), B. incisa iflavirus 1 (BiIV1), and B. incisa totivirus 1 (BiTV1). The complete genome sequences of these viruses were obtained through rapid amplification of cDNA ends (RACE). BiOV1 has a linear genome of 15,125 nucleotides (nt), while BiOV2 possesses a circular genome of 14,853 nt. The BiIV1 genome, excluding the poly(A) tail, is 10,903 nt in length and encodes a single open reading frame (ORF) for a polyprotein consisting of 3194 amino acids (aa). The BiTV1 genome is 4357 nt long and contains two overlapping ORFs, with the viral RNA-dependent RNA polymerase (RdRp) translated via a -1 ribosomal frameshift. Phylogenetic and sequence identity analyses suggest that all these viruses are novel members of their respective families. This study significantly expands our understanding of the virome associated with B. incisa by reporting and characterizing these novel viruses.

Discovery and Genomic Analysis of Three Novel Viruses in the Order Mononegavirales in Leafhoppers.

Leafhoppers are economically important pests and may serve as vectors for pathogenic viruses that cause substantial crop damage. In this study, using deep transcriptome sequencing, we identified three novel viruses within the order Mononegavirales, including two viruses belonging to the family Rhabdoviridae and one to the family Lispiviridae. The complete genome sequences were obtained via the rapid amplification of cDNA ends and tentatively named Recilia dorsalis rhabdovirus 1 (RdRV1, 14,251 nucleotides, nt), Nephotettix virescens rhabdovirus 1 (NvRV1, 13,726 nt), and Nephotettix virescens lispivirus 1 (NvLV1, 14,055 nt). The results of a phylogenetic analysis and sequence identity comparison suggest that RdRV1 and NvRV1 represent novel species within the family Rhabdoviridae, while NvLV1 is a new virus belonging to the family Lispiviridae. As negative-sense single-strand RNA viruses, RdRV1 and NvRV1 contain the conserved transcription termination signal and intergenic trinucleotides in the non-transcribed region. Intergenomic sequence and transcriptome profile analyses suggested that all these genes were co-transcriptionally expressed in these viral genomes, facilitated by specific intergenic trinucleotides and putative transcription initiation sequences.

MASS cohort: Multicenter, longitudinal, and prospective study of the role of microbiome in severe pneumonia and host susceptibility.

The MASS cohort comprises 2000 ICU patients with severe pneumonia, covering community-acquired pneumonia, hospital-acquired pneumonia, and ventilator-associated pneumonia, sourced from 19 hospitals across 10 cities in three provinces. A wide array of samples including bronchoalveolar lavage fluid, sputum, feces, and whole blood are longitudinally collected throughout patients' ICU stays. The cohort study seeks to uncover the dynamics of lung and gut microbiomes and their associations with severe pneumonia and host susceptibility, integrating deep metagenomics and transcriptomics with detailed clinical data.

Variability in Chromosome 1 of Select Moroccan Pyrenophora teres f. teres Isolates Overcomes a Highly Effective Barley Chromosome 6H Source of Resistance.

Barley net form net blotch (NFNB) is a destructive foliar disease caused by Pyrenophora teres f. teres. Barley line CIho5791, which harbors the broadly effective chromosome 6H resistance gene Rpt5, displays dominant resistance to P. teres f. teres. To genetically characterize P. teres f. teres avirulence/virulence on the barley line CIho5791, we generated a P. teres f. teres mapping population using a cross between the Moroccan CIho5791-virulent isolate MorSM40-3 and the avirulent reference isolate 0-1. Full genome sequences were generated for 103 progenies. Saturated chromosome-level genetic maps were generated, and quantitative trait locus (QTL) mapping identified two major QTL associated with P. teres f. teres avirulence/virulence on CIho5791. The most significant QTL mapped to chromosome (Ch) 1, where the virulent allele was contributed by MorSM40-3. A second QTL mapped to Ch8; however, this virulent allele was contributed by the avirulent parent 0-1. The Ch1 and Ch8 loci accounted for 27 and 15% of the disease variation, respectively, and the avirulent allele at the Ch1 locus was epistatic over the virulent allele at the Ch8 locus. As a validation, we used a natural P. teres f. teres population in a genome-wide association study that identified the same Ch1 and Ch8 loci. We then generated a new reference quality genome assembly of parental isolate MorSM40-3 with annotation supported by deep transcriptome sequencing of infection time points. The annotation identified candidate genes predicted to encode small, secreted proteins, one or more of which are likely responsible for overcoming the CIho5791 resistance. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications.

Gastric cancer (GC) ranks as the third most prevalent malignancy and a leading cause of cancer-related mortality worldwide. However, the majority of patients with GC are diagnosed at an advanced stage, highlighting the urgent need for effective perioperative and postoperative chemotherapy to prevent relapse and metastasis. The current treatment strategies have limited overall efficacy because of intrinsic or acquired drug resistance. Recent evidence suggests that dysregulated long non-coding RNAs (lncRNAs) play a significant role in mediating drug resistance in GC. Therefore, there is an imperative to explore novel molecular mechanisms underlying drug resistance in order to overcome this challenging issue. With advancements in deep transcriptome sequencing technology, lncRNAs-once considered transcriptional noise-have garnered widespread attention as potential regulators of carcinogenesis, including tumor cell proliferation, metastasis, and sensitivity to chemo- or radiotherapy through multiple regulatory mechanisms. In light of these findings, we aim to review the mechanisms by which lncRNAs contribute to drug therapy resistance in GC with the goal of providing new insights and breakthroughs toward overcoming this formidable obstacle.

Identification of DLEU2 as biomarker based on lncRNA-Mediated ceRNA network in rupture of intracranial aneurysm.

Intracranial aneurysms (IA) is a potentially devastating clinical problem that may cause lethal subarachnoid hemorrhage upon rupture, but the molecular mechanisms remain further elucidated. Our goal in this work was to build the lncRNA-mediated ceRNA network in IS and explore the associated pathways and functions. The deep transcriptome sequencing dataset profile of rupture of IA and normal tissues (SRP150595) was obtained from NCBI database. To determine which genes were differently expressed, weighted gene co-expression network analysis and other integrated bioinformatics techniques were used (DEGs). The action mechanism and associated pathways of DEGs in IA were investigated using GO annotations and KEGG analysis. The Starbase database was used to build the ceRNA network. Vascular smooth muscle cells (VSMC) were used for the transwell assay and CCK-8. A total of 248 common differentially expressed-protein coding RNA and 76 DE-lncRNAs were obtained. Functional enrichment analysis indicated that the DEGs of IA are involved in pathways of inflammation and immune response. A lncRNAs-mediated ceRNA network including lncRNAs BASP1-AS1, DLEU2, LINC02035, LINC02363, MMP25-AS1, AC008771.1 was constructed. The biological behavior of VSMC was suppressed when DLEU2 was knocked down. In conclusion, a lncRNAs-mediated ceRNA network was constructed in IA based on the integrated bioinformatics analyses, in which DLEU2 was identified to be a novel and potential biomarker of IA.

Population-level transposable element expression dynamics influence trait evolution in a fungal crop pathogen.

The rapid adaptive evolution of microbes is driven by strong selection pressure acting on genetic variation. How adaptive genetic variation is generated within species and how such variation influences phenotypic trait expression is often not well understood though. We focused on the recent activity of transposable elements (TEs) using deep population genomics and transcriptomics analyses of a fungal plant pathogen with a highly active content of TEs in the genome. Zymoseptoria tritici causes one of the most damaging diseases on wheat, with recent adaptation to the host and environment being facilitated by TE-associated mutations. We obtained genomic and RNA-sequencing data from 146 isolates collected from a single wheat field. We established a genome-wide map of TE insertion polymorphisms in the population by analyzing recent TE insertions among individuals. We quantified the locus-specific transcription of individual TE copies and found considerable population variation at individual TE loci in the population. About 20% of all TE copies show transcription in the genome suggesting that genomic defenses such as repressive epigenetic marks and repeat-induced polymorphisms are at least partially ineffective at preventing the proliferation of TEs in the genome. A quarter of recent TE insertions are associated with expression variation of neighboring genes providing broad potential to influence trait expression. We indeed found that TE insertions are likely responsible for variation in virulence on the host and potentially diverse components of secondary metabolite production. Our large-scale transcriptomics study emphasizes how TE-derived polymorphisms segregate even in individual microbial populations and can broadly underpin trait variation in pathogens.IMPORTANCEPathogens can rapidly adapt to new hosts, antimicrobials, or changes in the environment. Adaptation arises often from mutations in the genome; however, how such variation is generated remains poorly understood. We investigated the most dynamic regions of the genome of Zymoseptoria tritici, a major fungal pathogen of wheat. We focused on the transcription of transposable elements. A large proportion of the transposable elements not only show signatures of potential activity but are also variable within a single population of the pathogen. We find that this variation in activity is likely influencing many important traits of the pathogen. Hence, our work provides insights into how a microbial species can adapt over the shortest time periods based on the activity of transposable elements.

Deep learning-based multimodal spatial transcriptomics analysis for cancer.

The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized cancer research, offering unprecedented insights into tumor biology. This book chapter explores the integration of DL with ST to advance cancer diagnostics, treatment planning, and precision medicine. DL, a subset of artificial intelligence, employs neural networks to model complex patterns in vast datasets, significantly enhancing diagnostic and treatment applications. In oncology, convolutional neural networksexcel in image classification, segmentation, and tumor volume analysis, essential for identifying tumors and optimizing radiotherapy. The chapter also delves into multimodal data analysis, which integrates genomic, proteomic, imaging, and clinical data to offer a holistic understanding of cancer biology. Leveraging diverse data sources, researchers can uncover intricate details of tumor heterogeneity, microenvironment interactions, and treatment responses. Examples include integrating MRI data with genomic profiles for accurate glioma grading and combining proteomic and clinical data to uncover drug resistance mechanisms. DL's integration with multimodal data enables comprehensive and actionable insights for cancer diagnosis and treatment. The synergy between DL models and multimodal data analysis enhances diagnostic accuracy, personalized treatment planning, and prognostic modeling. Notable applications include ST, which maps gene expression patterns within tissue contexts, providing critical insights into tumor heterogeneity and potential therapeutic targets. In summary, the integration of DL and multimodal ST represents a paradigm shift towards more precise and personalized oncology. This chapter elucidates the methodologies and applications of these advanced technologies, highlighting their transformative potential in cancer research and clinical practice.

Inter-generational nuclear crosstalk links the control of gene expression to programmed genome rearrangement during the Paramecium sexual cycle.

Multinucleate cells are found in many eukaryotes, but how multiple nuclei coordinate their functions is still poorly understood. In the cytoplasm of the ciliate Paramecium tetraurelia, two micronuclei (MIC) serving sexual reproduction coexist with a somatic macronucleus (MAC) dedicated to gene expression. During sexual processes, the MAC is progressively destroyed while still ensuring transcription, and new MACs develop from copies of the zygotic MIC. Several gene clusters are successively induced and switched off before vegetative growth resumes. Concomitantly, programmed genome rearrangement (PGR) removes transposons and their relics from the new MACs. Development of the new MACs is controlled by the old MAC, since the latter expresses genes involved in PGR, including the PGM gene encoding the essential PiggyMac endonuclease that cleaves the ends of eliminated sequences. Using RNA deep sequencing and transcriptome analysis, we show that impairing PGR upregulates key known PGR genes, together with ∼600 other genes possibly also involved in PGR. Among these genes, 42% are no longer induced when no new MACs are formed, including 180 genes that are co-expressed with PGM under all tested conditions. We propose that bi-directional crosstalk between the two coexisting generations of MACs links gene expression to the progression of MAC development.

Deep transcriptome profiling reveals limited conservation of A-to-I RNA editing in Xenopus

BackgroundXenopus has served as a valuable model system for biomedical research over the past decades. Notably, ADAR was first detected in frog oocytes and embryos as an activity that unwinds RNA duplexes. However, the scope of A-to-I RNA editing by the ADAR enzymes in Xenopus remains underexplored.ResultsHere, we identify millions of editing events in Xenopus with high accuracy and systematically map the editome across developmental stages, adult organs, and species. We report diverse spatiotemporal patterns of editing with deamination activity highest in early embryogenesis before zygotic genome activation and in the ovary. Strikingly, editing events are poorly conserved across different Xenopus species. Even sites that are detected in both X. laevis and X. tropicalis show largely divergent editing levels or developmental profiles. In protein-coding regions, only a small subset of sites that are found mostly in the brain are well conserved between frogs and mammals.ConclusionsCollectively, our work provides fresh insights into ADAR activity in vertebrates and suggest that species-specific editing may play a role in each animal’s unique physiology or environmental adaptation.

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.

Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.

Genome sequence and salinity adaptation of the desert shrub Nitraria sibirica (Nitrariaceae, Sapindales)

The genetic bases of halophytes for salinity tolerance are crucial for genetically breeding salt-tolerant crops. All natural Nitrariaceae species that exclusively occur in arid environments are highly tolerant to salt stress, but the underlying genomic bases to this adaptation remain unknown. Here we present a high-quality, chromosome-level genome sequence of Nitraria sibirica, with an assembled size of 456.66Mb and 23,365 annotated genes. Phylogenomic analyses confirmed N. sibirica as the sister to all other sampled representatives from other families in Sapindales, and no lineage-specific whole-genome duplication was found except the gamma triplication event. Still, we found that the genes involved in K + retention, energy supply, and Fe absorption expanded greatly in N. sibirica. Deep transcriptome analyses showed that leaf photosynthesis and cuticular wax formation in roots were enhanced under salt treatments. Furthermore, many transcription factors involved in salt tolerance changed their expressions significantly and displayed tissue- and concentration-dependent signaling in response to salt stress. Additionally, we found vacuolar Na + compartmentalization is an ongoing process under salt treatment, while Na + exclusion tends to function at high salt concentrations. These genomic and transcriptomic changes conferred salt tolerance in N. sibirica and pave the way for future breeding of salt-tolerant crops.

Abstract 6612: Data-driven hallmarks of cancer as a new paradigm for precision medicine: multi-omics and functional profiling in acute myeloid leukemia

Abstract The cancer hallmark concept defines biological properties that play a key role in cancer development and progression. The hallmarks reflect generic properties across all cancer types, and are not directly quantifiable nor applicable in cancer diagnostics. Here, we applied a data-driven approach to identify quantifiable hallmarks to be used as a basis for precision cancer medicine (PCM) in Acute Myeloid Leukemia (AML). We applied deep exome, transcriptome, DNA methylation and proteome profiling as well as ex-vivo functional testing of 525 drugs to 118 AML patient samples. Unsupervised multi-omic dimensionality reduction defined 11 independent axes of biological variability that we interpreted to reflect data-driven hallmarks (DDHM) of AML. Each DDHM integrates and ranks different data types and features, pinpointing those molecular features that were most informative for each hallmark. We calculated values for the 11 DDHM for each patient, constructing a DDHM-based precision medicine approach for AML diagnosis and therapy assignment. Most DDHMs were driven by other data types than genomics. For several DDHMs, different cytogenetic and mutational drivers converge on the same hallmarks and specific drug vulnerabilities. We also see how DDHM predictors of poor prognosis and high-risk AML are distinct from those that dictate specific drug response vulnerabilities. DDHM 2 reflected the cell differentiation path leading towards resistance to BH3 mimetics, ACK-inhibitors, and anthracyclines, and sensitivity to MEK inhibitors and TLR8 agonists. DDHM 2 derived a strong impact from protein expression of GATA2, MLLT11, DNMT3B and from RNA expression of WT1 and SOX4 as well as from multiple markers of different monocytic subtypes. DDHM 5 depicted cell cycle regulation and the Megakaryocytic-erythrocyte progenitor cell state that was enriched in AML patients with antecedent hematological disease. Interestingly, DDHM5 was linked to the sensitivity to purine analogs and vinca alkaloids. Moreover, DDHMs 1 and 8 captured clinical risk groups, prognosis, and responsiveness to hypomethylating agents. These DDHMs also revealed the phenotypic and functional biology that distinguished patients with high versus low FLT3-ITD mutant allele frequency. Validation of the DDHMs is realized through profiling and analysis of prospective AML samples, AML cell lines and previously published datasets. In summary, we present a data-driven approach for defining hallmarks in AML. The application of the DDHMs in AML provides a new paradigm for PCM and an opportunity for combinatorial therapeutic targeting. Each patient is characterized by a combination of independent and potentially druggable hallmarks, as opposed to traditional stratification in PCM, where each patient is assigned to one specific subgroup defined by genetic or other biomarkers. Citation Format: Tom Erkers, Nona Struyf, Tojo James, Francesco Marabita, Mattias Vesterlund, Nghia Vu, Cornelia Arnroth, Albin Österroos, Anna Bohlin, Sofia Bengtzén, Matthias Stahl, Rozbeh Jafari, Lukas Orre, Yudi Pawitan, Brinton Seashore-Ludlow, Janne Lehtiö, Sören Lehmann, Päivi Östling, Olli Kallioniemi. Data-driven hallmarks of cancer as a new paradigm for precision medicine: multi-omics and functional profiling in acute myeloid leukemia. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6612.

Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH

Nonalcoholic steatohepatitis (NASH) is the most common chronic liver disease globally and a leading cause for liver transplantation in the US. Its pathogenesis remains imprecisely defined. We combined two high-resolution modalities to tissue samples from NASH clinical trials, machine learning (ML)-based quantification of histological features and transcriptomics, to identify genes that are associated with disease progression and clinical events. A histopathology-driven 5-gene expression signature predicted disease progression and clinical events in patients with NASH with F3 (pre-cirrhotic) and F4 (cirrhotic) fibrosis. Notably, the Notch signaling pathway and genes implicated in liver-related diseases were enriched in this expression signature. In a validation cohort where pharmacologic intervention improved disease histology, multiple Notch signaling components were suppressed.

Genetic and immune microenvironment characterization of HER2-positive gastric cancer: Their association with response to trastuzumab-based treatment.

We aimed to determine the molecular and immune microenvironment characteristics of HER2-positive gastric cancer (GC) related to the patient's response to first-line trastuzumab-based treatment. Eighty-three cases of HER2-positive advanced gastric adenocarcinoma patients treated with trastuzumab were enrolled. Targeted deep sequencing and transcriptome analysis were performed on selected 21 cases (exploration cohort) along with two post-treatment samples. The results were compared between patients progressed before 6 months (Group 2) and others (Group 1), and were validated by FISH and immunohistochemistry in total cohort. Tumor-infiltrating immune cells were evaluated using RNA sequencing data and multiplex immunohistochemistry. Progression-free survival (PFS) analysis was performed. Group 1 showed frequent amplification of G1/S cell cycle checkpoint-related genes and upregulated KEGG pathways related to cell proliferation. In contrast, Group 2 had more frequent EGFR, HER3, and MET amplification and higher RNA expression in immune-related KEGG pathways than Group 1. In total cohort, significant predictors of better PFS were cell cycle-related including CCNE1 amplification, Cyclin A and PLK1 overexpression, and decreased Cyclin D3 and HER3 expression (p< 0.05), or immune-related including high density of CD3- CD57+ NK cells and PD-L1 combined positive score ≥5 (p< 0.05). The best prognostic predictors were a combination of Cyclin A, Cyclin E, p21, and HER3 (p< 0.001). HER2-positive GC with favorable response to trastuzumab were characterized by cell cycle-related gene alterations and increased CD3- CD57+ NK cell infiltration. These findings would be helpful to the fine modulation of therapeutic strategies for patients with HER2-positive GC.

Upregulation of Sarcolemmal Hemichannels and Inflammatory Transcripts with Neuromuscular Junction Instability during Lower Limb Unloading in Humans.

Human skeletal muscle atrophy and a disproportionate force loss occur within a few days of unloading in space and on Earth, but the underlying mechanisms are not fully understood. Disruption of neuromuscular junction homeostasis has been proposed as one of the possible causes. Here, we investigated the potential mechanisms involved in this neuromuscular disruption induced by a 10-day unilateral lower limb suspension (ULLS) in humans. Specifically, we investigated hemichannels' upregulation, neuromuscular junction and axonal damage, neurotrophins' receptor downregulation and inflammatory transcriptional signatures. Biomarkers were evaluated at local and systemic levels. At the sarcolemmal level, changes were found to be associated with an increased expression of connexin 43 and pannexin-1. Upregulation of the inflammatory transcripts revealed by deep transcriptomics was found after 10 days of ULLS. The destabilisation of the neuromuscular junction was not accompanied by changes in the secretion of the brain-derived neurotrophic factor and neurotrophin-4, while their receptor, BDNF/NT growth factors receptor (TrkB), decreased. Furthermore, at 5 days of ULLS, there was already a significant upregulation of the serum neurofilament light chain concentration, an established clinical biomarker of axonal injury. At 10 days of ULLS, other biomarkers of early denervation processes appeared. Hence, short periods of muscle unloading induce sarcolemmal hemichannels upregulation, inflammatory transcripts upregulation, neuromuscular junction instability and axonal damage.

ADAR RNA editing on antisense RNAs results in apparent U-to-C base changes on overlapping sense transcripts.

Despite hundreds of RNA modifications described to date, only RNA editing results in a change in the nucleotide sequence of RNA molecules compared to the genome. In mammals, two kinds of RNA editing have been described so far, adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. Recent improvements in RNA sequencing technologies have led to the discovery of a continuously growing number of editing sites. These methods are powerful but not error-free, making routine validation of newly-described editing sites necessary. During one of these validations on DDX58 mRNA, along with A-to-I RNA editing sites, we encountered putative U-to-C editing. These U-to-C edits were present in several cell lines and appeared regulated in response to specific environmental stimuli. The same findings were also observed for the human long intergenic non-coding RNA p21 (hLincRNA-p21). A more in-depth analysis revealed that putative U-to-C edits result from A-to-I editing on overlapping antisense RNAs that are transcribed from the same loci. Such editing events, occurring on overlapping genes transcribed in opposite directions, have recently been demonstrated to be immunogenic and have been linked with autoimmune and immune-related diseases. Our findings, also confirmed by deep transcriptome data, demonstrate that such loci can be recognized simply through the presence of A-to-I and U-to-C mismatches within the same locus, reflective A-to-I editing both in the sense-oriented transcript and in the cis-natural antisense transcript (cis-NAT), implying that such clusters could be a mark of functionally relevant ADAR1 editing events.

Three-dimensional mapping of hepatic lymphatic vessels and transcriptome profiling of lymphatic endothelial cells in healthy and diseased livers.

Rationale: Hepatic lymphatics are essential for liver homeostasis and immune function. However, the 3D structure and spatial distribution of hepatic lymphatic vessels (LVs) need to be confirmed. Moreover, the molecular information of hepatic lymphatic endothelial cells (LyECs) needs to be further studied. The bottleneck is the lack of specific markers or labeling methods for hepatic lymphatic endothelial cells (LyECs) Methods: Here, we proposed a method for the spatiotemporal sequential injection of antibodies (STSI-Ab) to selectively label hepatic LyECs in vivo. In addition, we also developed an efficient hepatic LyEC sorting method and performed deep transcriptome sequencing on hepatic LyECs. Results: The STSI-Ab method achieved selective labeling of the mouse hepatic lymphatic network. Three-dimensional fluorescence imaging results of the STSI-Ab mouse liver lobe clearly showed that hepatic LVs entangled with the portal vein but were not present in the central vein. The imaging data inspired a novel hepatic lobule structure model with an added set of LVs in the portal area. Furthermore, deep transcriptome sequencing of isolated hepatic LyECs and Masson's trichrome staining results suggested that hepatic LyECs might be an important source of collagen fibers deposited in the portal area during the process of liver fibrosis and bile duct ligation (BDL). Conclusions: We proposed an STSI-Ab method for selectively labeling hepatic LVs, distinguishing the hepatic LVs from other vessels, and mapping their 3D structure. This study opens an avenue for understanding hepatic lymphatic structure and it will be very beneficial to the study of hepatic LyEC functions.

Spatiotemporal evolution of the clear cell renal cell carcinoma microenvironment links intra-tumoral heterogeneity to immune escape

BackgroundIntratumoral heterogeneity (ITH) is a hallmark of clear cell renal cell carcinoma (ccRCC) that reflects the trajectory of evolution and influences clinical prognosis. Here, we seek to elucidate how ITH and tumor evolution during immune checkpoint inhibitor (ICI) treatment can lead to therapy resistance.MethodsHere, we completed a single-arm pilot study to examine the safety and feasibility of neoadjuvant nivolumab in patients with localized RCC. Primary endpoints were safety and feasibility of neoadjuvant nivolumab. Then, we spatiotemporally profiled the genomic and immunophenotypic characteristics of 29 ccRCC patients, including pre- and post-therapy samples from 17 ICI-treated patients. Deep multi-regional whole-exome and transcriptome sequencing were performed on 29 patients at different time points before and after ICI therapy. T cell repertoire was also monitored from tissue and peripheral blood collected from a subset of patients to study T cell clonal expansion during ICI therapy.ResultsAngiogenesis, lymphocytic infiltration, and myeloid infiltration varied significantly across regions of the same patient, potentially confounding their utility as biomarkers of ICI response. Elevated ITH associated with a constellation of both genomic features (HLA LOH, CDKN2A/B loss) and microenvironmental features, including elevated myeloid expression, reduced peripheral T cell receptor (TCR) diversity, and putative neoantigen depletion. Hypothesizing that ITH may itself play a role in shaping ICI response, we derived a transcriptomic signature associated with neoantigen depletion that strongly associated with response to ICI and targeted therapy treatment in several independent clinical trial cohorts.ConclusionsThese results argue that genetic and immune heterogeneity jointly co-evolve and influence response to ICI in ccRCC. Our findings have implications for future biomarker development for ICI response across ccRCC and other solid tumors and highlight important features of tumor evolution under ICI treatment.Trial registrationThe study was registered on ClinicalTrial.gov (NCT02595918) on November 4, 2015.