Paired-end RNA-seq Research Articles

GEDI: An R Package for Integration of Transcriptomic Data from Multiple Platforms for Bioinformatics Applications.

Transcriptomic data is often expensive and difficult to generate in large cohorts relative to genomic data; therefore, it is often important to integrate multiple transcriptomic datasets from both microarray- and next generation sequencing (NGS)-based transcriptomic data across similar experiments or clinical trials to improve analytical power and discovery of novel transcripts and genes. However, transcriptomic data integration presents a few challenges including reannotation and batch effect removal. We developed the Gene Expression Data Integration (GEDI) R package to enable transcriptomic data integration by combining existing R packages. With just four functions, the GEDI R package makes constructing a transcriptomic data integration pipeline straightforward. Together, the functions overcome the complications in transcriptomic data integration by automatically reannotating the data and removing the batch effect. The removal of the batch effect is verified with principal component analysis and the data integration is verified using a logistic regression model with forward stepwise feature selection. To demonstrate the functionalities of the GEDI package, we integrated five bovine endometrial transcriptomic datasets from the NCBI Gene Expression Omnibus. These transcriptomic datasets were from multiple high-throughput platforms, namely, array-based Affymetrix and Agilent platforms, and NGS-based Illumina paired-end RNA-seq platform. Furthermore, we compared the GEDI package to existing tools and found that GEDI is the only tool that provides a full transcriptomic data integration pipeline including verification of both batch effect removal and data integration for downstream genomic and bioinformatics applications. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: ReadGE, a function to import gene expression datasets Basic Protocol 2: GEDI, a function to reannotate and merge gene expression datasets Basic Protocol 3: BatchCorrection, a function to remove batch effects from gene expression data Basic Protocol 4: VerifyGEDI, a function to confirm successful integration of gene expression data.

PSIV-23 Transcriptomic analysis revealed the mechanisms of resilience and susceptibility to nonalcoholic steatohepatitis in dairy goats under high-concentrate diet

Abstract Liver health is vital for growth and health of ruminants, which can directly affect their performance. High-concentrate diet (HCD) feeding, a common practice to meet the energy requirements for animal production and growth, has been known to induce liver damage, including nonalcoholic fatty liver (NAFL) and nonalcoholic steatohepatitis (NASH) in ruminants. To date, the regulatory mechanisms of liver metabolic dysfunctions in ruminants induced by HCD are not well defined. To elucidate molecular regulatory mechanisms underlying liver dysfunction in ruminants, we compared liver transcriptome and single-cell transcriptome of dairy goats that had varied responses to the HCD, aiming to underpin the key mechanisms behind resilience and susceptibility to NASH in ruminants. After feeding 30 dairy goats with low-concentrate diet (LCD, n = 15, defined as Con) or high-concentrate diet (HCD, n = 15) for 6 wk, 10 of them developed NASH (defined as NASH), while the other 5 did not showed any NASH symptom (defined as NASH-tolerance, NASH-T) under HCD. Liver tissues were collected to extract RNA. The paired-end RNA-seq library was sequenced with a NovaSeq6000 sequencer (Illumina). Real-time quantitative PCR was conducted to verify the significantly different genes among groups. Liver single-cell transcriptome was performed using 10×Genomics Chromium system. Liver transcriptome analysis revealed that the expression level of genes involved in the interleukin (IL)-17 signaling pathway, including IL-17A (P = 0.035; 0.001), Act1 (P = 0.036; 0.002), FOSB (P = 0.041; 0.048) and IL-1β (P = 0.022; 0.002) in the NASH group were significantly greater than those in the Con and NASH-T groups. Hepatic single-cell RNA sequencing identified seven cell types in the liver, including hepatocytes, macrophages, T cells, endothelial cell, natural killer (NK) cell, hepatic stellate cells (HSCs), B cells. In T cell subset, significantly decreased T helper 17 (TH17) cells and increased regulatory T (Treg) cells were detected in the NASH group compared with Con and NASH-T groups. In TH17 cell, the expression levels of IL-17A (P = 0.004; 0.009) and IL-23R (P = 0.007; 0.01; the surface antibodies of TH17 cells) in NASH group were significantly greater than those in the Con and NASH-T groups. The expression levels of Foxp3 (P < 0.001; 0.013), IL-2R (P < 0.001; 0.001), CTLA-4 (P = 0.005; 0.017) and CD127 (P = 0.004; 0.009; the surface antibodies of Treg cells) in NASH group were significantly less than those in the Con and NASH-T groups. Our results revealed the role of liver immune cells in maintaining tolerance to NASH in dairy goats under HCD, which provides new understanding in pathogenesis of NASH under HCD. Further studies are needed to identify major factors that drive the changes of ratio of TH17/Treg cell.

PSVII-1 Widespread allele-specific expression across tissues and cells of the chicken genome

Abstract Chickens are a valuable livestock species, providing an affordable and nutritious food source worldwide through eggs and meat. Additionally, chickens are extensively used in scientific research as model organisms in virology, immunology, epigenetics, development, and conservation biology. Considering this, there are increasing efforts to deepen our understanding of their genome complexity, such as efforts by the Functional Annotation of Animal Genomes (FAANG) Consortium. Toward this goal, we are working to contribute to the annotation of the chicken transcriptome. Allele-specific expression (ASE) is an imbalance of allelic gene expression often driven by genetic and epigenetic changes in cis-regulatory regions. We, therefore, aimed to determine allelic imbalances in gene expression across 20 tissues and cells to shed light on mechanisms regulating gene expression. Using replicate paired-end (PE) RNA-seq samples, we identified around 7 million variants across 20 tissues and cells (e.g., reproductive tissues, intestine tissues, muscle, and immune tissues and cells). We applied quality control measures and filtered out monoallelic and homozygous variants. After that, we calculated read counts per allele to determine allelic expression. We found 365,894 significant ASE SNPs and 11,530 ASE genes in at least one tissue or cell type (FDR ≤ 0.05). We discovered that ASE SNPs are widely distributed throughout the chicken genome, and ASE SNPs and ASE genes showed a varied distribution across tissues and cells. Primary macrophage exhibited the most abundant, while the pectoralis major (breast muscle) had the lowest ASE genes and ASE SNPs, ranging from 7,592 to 32,505 ASE SNPs and 773 to 2,387 ASE genes. Our findings reveal several important pathways affected by allelic imbalance of expression. These pathways included fatty acid biosynthesis and regulation, cell proliferation and differentiation, cell metabolism, adipocytokine signaling, proteolysis and autophagy, and focal adhesion. In summary, our study provides insight into relevant biological processes critical to chickens and can contribute to improving genome annotation, helping to expand the transcriptomic reference source.

Accurate assembly of circular RNAs with TERRACE.

Circular RNA (circRNA) is a class of RNA molecules that forms a closed loop with their 5' and 3' ends covalently bonded. CircRNAs are known to be more stable than linear RNAs, have distinct properties and functions, and are promising biomarkers. Existing methods for assembling circRNAs heavily rely on the annotated transcriptomes, hence exhibiting unsatisfactory accuracy without a high-quality transcriptome. We present TERRACE, a new algorithm for full-length assembly of circRNAs from paired-end total RNA-seq data. TERRACE uses the splice graph as the underlying data structure that organizes the splicing and coverage information. We transform the problem of assembling circRNAs into finding paths that "bridge" the three fragments in the splice graph induced by back-spliced reads. We adopt a definition for optimal bridging paths and a dynamic programming algorithm to calculate such optimal paths. TERRACE features an efficient algorithm to detect back-spliced reads missed by RNA-seq aligners, contributing to its much-improved sensitivity. It also incorporates a new machine-learning approach trained to assign a confidence score to each assembled circRNA, which is shown to be superior to using abundance for scoring. On both simulations and biological data sets, TERRACE consistently outperforms existing methods by a large margin in sensitivity while achieving better or comparable precision. In particular, when the annotations are not provided, TERRACE assembles 123%-413% more correct circRNAs than state-of-the-art methods. TERRACE presents a significant advance in assembling full-length circRNAs from RNA-seq data, and we expect it to be widely used in future research on circRNAs.

Development of novel MUC1-C targeting antibody-drug conjugate for pancreatic cancer treatment.

e15025 Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of cancers, which is usually diagnosed in advanced stages and presents an abysmal 5-year survival rate of 3-10%. With late detection of metastasized/advanced disease, curative surgery is not an option for most patients. Accordingly, there is an urgent unmet need for development of therapeutics targeting the pancreatic cancer cells. MUC1 is one such cell surface antigen that is aberrantly overexpressed in most solid tumors including pancreatic cancer. In this study we report preclinical efficacy of pharmacological inhibition of MUC1 signaling by GO-203 and targeted delivery of toxin conjugated to novel MUC1-C antibodies (7B8 and 3D1) binding to the extra cellular domain (ECD) to the PDAC xenografts. Methods: Subjects from TCGA-PAAD were stratified into high (75th percentile) and low (25th percentile) MUC1-expressing cohorts. Differential expression was performed using DESeq2, followed by GSEA, and signaling network analysis using partial correlation networks, ARACNE, and BC3NET. Anti-MUC1 antibody-drug conjugates (ADCs) were generated by coupling monomethyl auristatin E (3D1-MMAE, 7B8-MMAE) via V-C-PAB linker and characterized for anti-tumor activity against pancreatic cancer cells including MIA PaCa-1, CAPAN2 and HAPF-II. Paired-end RNA-seq (50bp) was aligned and quantified to the Human Ensembl GRC38 reference using STAR aligner. Subcutaneous xenografts were obtained in nude mice by injecting 5X106 HPAF-II tumor cells. Results: Differential expression, pathway, and network analyses revealed consistent dysregulation of cancer survival-related processes, and P53-related pathways in the cohort with increased MUC1 expression. The ADCs (DAR of ~3.5) exhibited efficient internalization in cancer cells and associated apoptotic cell death (Kds = 2 - 5nM). Pharmacological inhibition of MUC1 signaling by GO-203 demonstrated reduction in canonical pathways including P53 and EMT. Treatment with 3D1-MMAE compared to both vehicle and GO-203 showed dysregulation of cellular metabolism pathways (cholesterol homeostasis, glycolysis) and exhibited several strong indicators of cellular stress including activation of unfolded protein response processes and mTorc1 signaling. Excellent tumor-suppressive effects of ADCs were observed in HPAF-II xenografts in nude mice. The 7.5 mg/kg (i.v., q7dx3), treatment showed complete tumor regression from 14th day (end of treatment) till the date of termination (Day 50). Doses up to 40 mg/kg were well tolerated by the mice and this anti-tumor efficacy was observed without any appreciable loss in body weight or adverse effects on tissues. Conclusions: Targeted delivery of MMAE toxin to the pancreatic cancer cells presents an exciting opportunity for a novel therapeutic intervention for the treatment of pancreatic cancer patients with MUC1 over expression in tumors.

Abstract 7611: Circulating blood RNAseq detects activation of immune system and predicts response to immunotherapy in bladder cancer

Abstract Background: Anti-PD(L)1 immunotherapies have revolutionized oncology by getting durable tumor responses in advanced cancers. Nevertheless, currently approved biomarkers (PD-L1, MSI, TMB) have suboptimal positive/negative predictive values for tumor responses and survival. Aims & Methods: We sought to assess the value of gene expression on circulating blood to predict responses to immunotherapy. We performed total paired-end RNAseq at 20-million reads and analyzed differential gene expressions according to cancer outcomes on baseline frozen whole blood from a cohort of 186 patients prospectively enrolled in the IOPREDI study, a French ancillary cohort of the international multi-center STRONG Phase III trial testing the anti-PD-L1 durvalumab in advanced bladder cancers (NCT03084471). Results: One hundred and sixty four out of the 186 baseline samples generated valuable blood transcriptome data. Thanks to mathematical corrections, all samples were normalized, and the analysis was possible without introducing any bias despite the sample origin from 16 enrolling sites. We first observed that patients with a complete or partial response or a stable disease overexpressed 19 genes, 5 of which are markers of immune cell activation: CXCL8, EOMES, GBP5, GZMA, and GZMH. Conversely, patients with a progressive disease overexpressed 11 genes including CD177, a marker of neutrophil cells, recently associated to immunotherapy resistance. Next, patients with a PFS > 3 months showed an overexpression of 25 genes associated with immune cells activation such as CD8A, CXCL8, EOMES, FASLG, GZM genes, whereas patients with a shorter PFS highly expressed genes of immune cell inhibition: CD177, CD300LG, CD99, and CST7. Finally, patients with an OS > 7 months had also a higher expression of the same previous genes completed with 6 other genes, still indicators of immunity activation (CD3D, CD3E, CD3G, GZMM, IL2RB, and PTGDS). Conclusion: Total RNAseq from RNA directly extracted from whole blood can detect baseline activation of T-cells in patients who will subsequently benefit from anti-PD-L1 immunotherapy. This work shows that RNAseq can detect an immune activation state in circulating blood without specific cell selection. This technique could be used in clinical trials to select for patients prone to benefit from cancer immunotherapies. Citation Format: Corentin Richard, Sandy Chevrier, Aurélien Marabelle, Romain Boidot. Circulating blood RNAseq detects activation of immune system and predicts response to immunotherapy in bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7611.

Novel Isoforms Identified By Isoseq Analysis Drive Expression Differences in Key Genes That Delineate the Subtypes of Waldenstrom's Macroglobulinemia

Background: Alternative isoforms can alter regulatory motifs, binding partners, localization, and function of gene or even inhibit its function. While isoform regulation in humans is generally well described, there are still many tissue specific isoforms that remain to be fully documented. Moreover, mutations and broad dysregulation of transcriptional and RNA processing machinery is common in cancer resulting in additional novel isoforms. Analysis of 249 MYD88 mutated patients from our multi-omic data set of 253 treatment-naive patients with Waldenstrom's Macroglobulinemia (WM) identified three subtypes of WM: B-cell like (BCL), Plasma cell like (PCL), and an intermediate clone enriched for early/smoldering WM from which the other two evolved. (Hunter et al, ASH 2022) The BCL and PCL subtypes have distinct clinical as well as mutational and transcriptional characteristics. To investigate isoform usage, including novel disease related isoforms, we utilized PacBio single molecule real-time (SMRT) sequencing which can produce reads up to 10Kb allowing for end-to-end single transcript sequences for most genes. Methods: PacBio Isoseq analysis was performed on RNA isolated from CD19+ bone marrow (BM) samples from 11 WM patients; CD19+CD27+ memory B-cells (MB) from two healthy donors; and CD138+ plasma cell (PC) from two healthy donors. SMRT analysis data was aligned and processed using minimap2 with Cupcake. Observed isoforms were filtered, categorized, and annotated using Squanti. High confidence novel isoforms were then added into hg38 Gencode annotation which was used to realign our existing high depth Illumina 150bp paired end RNASeq data set of 249 untreated MYD88 mutated WM patients using STAR and Salmon. DTU analysis and functional annotation was performed using the isoformSwitchAnalyzeR package from Bioconductor in R. Results: The 11 patients in PacBio novel isoform discovery cohort had a median age of 63 (range 48-78 years) at time of sample acquisition; serum IgM of 2,150 (598-5,830 mg/dL); and BM involvement of 75% (range 20-95%). Six (55%) were female; 4 (36%) had a familial history of WM; 4 (36%) had a familial history of other B-cell malignancies; and 3 (27%) were sporadic. MYD88 and CXCR4 mutations were present in 10/11 (91%) and 6/11 (55%) patients, respectively. In the MYD88 mutated RNASeq cohort, 102/249 (41%) were female, the median age at biopsy was 66 (range: 31-95 years), BM involvement was 50% (5-95%), and the median serum IgM was 3,162 (104-10,321 mg/dL). PacBio analysis added 194,997 novel isoforms to the gencode annotation which ranged in function from minor alterations in untranslated regions (UTRs) to the introduction of novel coding sequences. Of the 3,134 genes differentially expressed between BCL and PCL, 1,175 (37.5%) and 1,149 (36.6%) had greater that 50% of their expression assigned to novel isoforms for BCL and PCL, respectively (p=NS), which highlights the impact of the improved annotation. The top result from the DTU analysis was DUSP22, a negative regulator of MAPK and ERK1/2 signaling ( Figure 1). DUSP22 was overexpressed in early/smoldering WM and PCL, with overexpression driven by a novel internal start with a partial intron inclusion. These novel isoforms express only half of DUSP22's functional domain but also contain novel 5' signal peptide sequences targeting the transcript to the endoplasmic reticulum for translation. Another top result was FCRLB, an FC receptor that can promote survival in B-lymphocytes. In HD and BCL, the minimal expression corresponded to a canonical non-coding isoform, while in PCL and early/smoldering WM most of the expression resulted from novel coding isoforms that contained the core protein coding regions of the gene. Other genes with significant DTU included HDAC4, HDAC9, and ARID5B all of which are critical modulators of chromatin accessibility. Functional validation of novel isoforms and DTU analysis of additional genomic, and clinical factors is ongoing. Conclusions: Novel transcripts identified by PacBio IsoSeq analysis drive expression of key genes including the important MAPK/ERK regulator DUSP22, and FC receptor FCRLB that promotes survival of B-lymphocytes. Other genes of interest included modulators of chromatic accessibility. Our findings demonstrate important new insights into isoform usage associated with WM subtype in WM and provide novel insights into the underlying biology of the disease.

On de novo Bridging Paired-end RNA-seq Data.

The high-throughput short-reads RNA-seq protocols often produce paired-end reads, with the middle portion of the fragments being unsequenced. We explore if the full-length fragments can be computationally reconstructed from the sequenced two ends in the absence of the reference genome-a problem here we refer to as de novo bridging. Solving this problem provides longer, more informative RNA-seq reads, and benefits downstream RNA-seq analysis such as transcript assembly, expression quantification, and splicing differential analysis. However, de novo bridging is a challenging and complicated task owing to alternative splicing, transcript noises, and sequencing errors. It remains unclear if the data provides sufficient information for accurate bridging, let alone efficient algorithms that determine the true bridges. Methods have been proposed to bridge paired-end reads in the presence of reference genome (called reference-based bridging), but the algorithms are far away from scaling for de novo bridging as the underlying compacted de Bruijn graph (cdBG) used in the latter task often contains millions of vertices and edges. We designed a new truncated Dijkstra's algorithm for this problem, and proposed a novel algorithm that reuses the shortest path tree to avoid running the truncated Dijkstra's algorithm from scratch for all vertices for further speeding up. These innovative techniques result in scalable algorithms that can bridge all paired-end reads in a cdBG with millions of vertices. Our experiments showed that paired-end RNA-seq reads can be accurately bridged to a large extent. The resulting tool is freely available at https://github.com/Shao-Group/rnabridge-denovo.

ChimeraTE: a pipeline to detect chimeric transcripts derived from genes and transposable elements.

Transposable elements (TEs) produce structural variants and are considered an important source of genetic diversity. Notably, TE-gene fusion transcripts, i.e. chimeric transcripts, have been associated with adaptation in several species. However, the identification of these chimeras remains hindered due to the lack of detection tools at a transcriptome-wide scale, and to the reliance on a reference genome, even though different individuals/cells/strains have different TE insertions. Therefore, we developed ChimeraTE, a pipeline that uses paired-end RNA-seq reads to identify chimeric transcripts through two different modes. Mode 1 is the reference-guided approach that employs canonical genome alignment, and Mode 2 identifies chimeras derived from fixed or insertionally polymorphic TEs without any reference genome. We have validated both modes using RNA-seq data from four Drosophila melanogaster wild-type strains. We found ∼1.12% of all genes generating chimeric transcripts, most of them from TE-exonized sequences. Approximately ∼23% of all detected chimeras were absent from the reference genome, indicating that TEs belonging to chimeric transcripts may be recent, polymorphic insertions. ChimeraTE is the first pipeline able to automatically uncover chimeric transcripts without a reference genome, consisting of two running Modes that can be used as a tool to investigate the contribution of TEs to transcriptome plasticity.

Sample paired-end RNA-seq data from four human macophage samples (chromsome 21 only)

Sample paired-end RNA-seq data from four human macophage samples (chromsome 21 only)

Network-Based Assessment of Minimal Change Disease Identifies Glomerular Response to IL-7 and IL-12 Pathways Activation as Innovative Treatment Target.

Background: Minimal change disease (MCD), a major cause of nephrotic syndrome, is usually treated by corticosteroid administration. MCD unresponsiveness to therapy and recurrences are nonetheless frequently observed, particularly in adults. To explore MCD-related pathogenetic mechanisms and to identify novel drug targets ultimately contributing to novel therapeutic avenues with a certain specificity for MCD, we compared glomerular transcriptomes from MCD with membranous nephropathy (MN) patients and healthy controls. Methods: Renal biopsies from adult patients with MCD (n = 14) or MN (n = 12), and non-diseased controls (n = 8) were selected from the Norwegian Kidney Biopsy Registry. RNA for 75 base-pair paired-end RNASeq were obtained from laser capture micro-dissected (LCM) glomeruli from FFPE sections. Transcriptional landscapes were computed by combining pathway-centered analyses and network science methodologies that integrate multiple bioinformatics resources. Results: Compared to normal glomeruli, cells from MCD displayed an inflammatory signature apparently governed by the IL1 and IL7 systems. While enrichment of IL1 production and secretion was a shared feature of MCD and MN compared to normal tissue, responses involving IL7 pathway activation were unique to MCD. Indeed, IL7R expressed by glomeruli was the most upregulated gene of the interleukin family in MCD versus normal controls. IL7 pathway activation was paralleled by significant enrichment in adaptive immune system processes and transcriptional regulation and depletion in pathways related to energy metabolism and transcription. Downregulation of these organ function-related themes again occurred predominately in MCD and was significantly less pronounced in MN. Immunofluorescence and immunohistochemistry, respectively, confirmed the expression of phosphorylated IL-7 receptor alpha (IL7RA, CD127) and IL12 receptor beta 1 (IL12RB1) proteins. Conclusions: Gene expression profiling of archival FFPE-biopsies identifies MCD-specific signatures with IL7RA and IL12RB1 as novel targets for MCD treatment.

A Kmer-based paired-end read de novo assembler and genotyper for canine MHC class I genotyping

The major histocompatibility complex class I (MHC-I) genes are highly polymorphic. MHC-I genotyping is required for determining the peptide epitopes available to an individual's T-cell repertoire. Current genotyping software tools do not work for the dog, due to very limited known canine alleles. To address this, we developed a Kmer-based paired-end read (KPR) de novo assembler and genotyper, which assemble paired-end RNA-seq reads from MHC-I regions into contigs, and then genotype each contig and estimate its expression level. KPR tools outperform other popular software examined in typing new alleles. We used KPR tools to successfully genotype152 dogs from a published dataset. The study discovers 33 putative new alleles, finds dominant alleles in 4 dog breeds, and builds allele diversity and expression landscapes among the 152 dogs. Our software meets a significant need in biomedical research.

Immune infiltration could predict the efficacy of short-term radiotherapy in patients with cervical cancer.

Radiotherapyis the main treatment forcervical cancer. It is usually applied alone or in combination with surgery and/or chemotherapy. To explore the association between immune microenvironment of cervical cancer and radiotherapy response, we collected 20 paired cervical cancer tumor samples before and after radiotherapy and partial clinical information. With paired-end RNA-seq, we quantified the immune infiltration and tumor purity of these samples, and obtained 6350 differentially expressed genes before and after radiotherapy. With the help of R language, the function enrichment analysis and 22 immune cells infiltration analysis were carried out. Moreover, we built a random forest model based on the immune microenvironment to predict the short-term efficacy of radiotherapy. We found that the effect of radiotherapy on the immune microenvironment of stage III and IV cervical cancer patients was weaker than that of stage I and II cervical cancer patients. Radiotherapy can significantly reduce the tumor purity and increase immune infiltration. The proportions of the immune infiltrating cells are predictive of the radiotherapy efficacy. In addition, the local mucositis caused by radiotherapy can improve the curative effect of radiotherapy.

The Landscape of Small Nucleolar RNA Expression in Multiple Myeloma

Background Small nucleolar RNAs (snoRNAs) are non-coding RNAs involved in the maturation of ribosome RNAs and various other biological processes. Emerging evidence demonstrates that snoRNAs play an essential role in tumor initiation and progression. However, their role in multiple myeloma (MM) pathogenesis remains poorly characterized. To date, the profiling of small RNAs in MM has mainly focused on microRNAs and approaches are confined to PCR- or array-based techniques. Here, we used next generation sequencing (NGS) to explore the snoRNA expression patterns of MM patients and to identify the association between snoRNAs and mRNAs, molecular subgroups of MM and clinical parameters. Methods Purified CD138+ cells from 71 newly diagnosed MMs and 4 refractory/relapsed MMs were included. Three CD19+ B cell samples from healthy donors were used as control. Total RNA was isolated with the AllPrep DNA/RNA kit (Qiagen, Germany). The mRNA and snoRNA NGS libraries were prepared using the Illumina TruSeq stranded mRNA and the NEBNext multiplex small RNA library kit, respectively. Sequencing of mRNA and snoRNA was performed on an Illumina NextSeq and NovaSeq 6000 PE 100 S1 platform, respectively. Paired-end RNA-seq reads were mapped to the hg19 reference genome using STAR. Gene expressions were quantified using featureCounts. Differentially expressed mRNAs and snoRNAs were identified using DESeq2. The Kaplan-Meier method was used for survival analyses. Progression-free survival (PFS) time was measured from enrollment to relapse or death from any cause, whichever occurred first. Results Using NGS, we observed expression of 625 full-length snoRNAs. Compared to normal B cells high levels of snoRNA expression were detected in MM plasma cells. Looking for associations between snoRNA expression and molecular subgroups of MM, we found an upregulation of 50 snoRNAs in patients with a hyperdiploid karyotype. The pattern of upregulation supported a regulatory mechanism in this molecular subgroup that goes beyond a pure copy-number effect. Even in patients with multiple trisomies the overwhelming majority (82%) of upregulated snoRNAs were located on chromosome 15, including the SNORD115 family on 15q11. In patients with gain of 1q21, all snoRNAs located on 1q25 were upregulated and the highest expression level of those snoRNAs appeared in patients with amp1q, indicating a copy-number effect. SNORD78, which was recently shown to impact outcome in prostate cancer and lung cancer, was significantly overexpressed in gain1q patients and defined a subgroup with inferior PFS (p =0.019) and overall survival (p = 0.011). SCARNA22, which was upregulated in patients with a t(4;14), was another snoRNA with a negative impact on PFS (31.06 months vs unreached, p = 0.007). To further characterize MM with upregulation of prognostically relevant snoRNAs, we analyzed bulk RNAseq of CD138-enriched MM cells and performed a pathway enrichment analysis. Comparing SNORD78 high expression group with the low group, we found 537 upregulated genes, e.g.SH2D2A, and CDK1, and 229 downregulated genes. Differentially expressed genes were enriched for cell cycle and chromosome segregation. For SCARNA22, we found 963 up- and 219 down-regulated genes. These showed enrichment for cell adhesion (upregulated in SCARNA22high) and protein targeting to the membrane or the endoplasmic reticulum (downregulated in SCARNA22high). Conclusion In this study we provide first insights into the expression patterns of snoRNAs in MM by deep sequencing. We identified snoRNAs dysregulated in MM subgroups, with two of them being associated with poor outcome. This study also shows that expression of particular snoRNAs is associated with specific chromosome gains, which is a common element in MM. Disclosures No relevant conflicts of interest to declare.

Gene Transcription in End Stage Ankle Osteoarthritis Differs Markedly From Knee Arthritis and Non- Arthritic Ankles

Category: Ankle Arthritis; Arthroscopy; Basic Sciences/Biologics; Trauma Introduction/Purpose: Post-traumatic Osteoarthritis (OA) of the ankle is a debilitating condition that impacts millions of people. However, little is known about the genetic and epigenetic risk factors for progression to OA following injury. In order to better understand these factors, a thorough knowledge of the molecular signature in ankle OA relative to non-arthritic ankles is critical. The objective of this study was to perform RNA-sequencing of ankle joint synovial samples from OA and non-OA ankles to better characterize the synovial transcriptome. We compared synovial gene expression patterns in patients with end-stage OA with ankle synovium from non-OA ankles to investigate the unique biological pathways altered in ankle OA. Methods: Patients undergoing total ankle arthroplasty or ankle arthrodesis for end stage OA and patients undergoing ankle arthroscopic surgery for non-arthritic conditions (negative control), were consented for participation. Patients with immune disorders or inflammatory arthropathies were excluded. Patient demographics and medical history were collected. Synovial samples were harvested during surgery and RNA was isolated. Bulk 150 bp, paired-end RNA seq was performed using the Illumina NovaSeq6000 platform. Differential expression was determined using the edgeR (v3.16.5) package for R, after adjustment using a scaling normalization factor and P-values were corrected using the Benjamini Hochberg method. Similarities between samples were determined using Spearman Correlation and degree of similarity was visualized considering the first three Principal Components. Gene Ontology terms were identified to classify gene properties. Results: A total of 8 synovial samples from total ankle OA and 24 synovial samples from ankle non-OA were available for analysis. We found 808 genes uniquely expressed in OA synovium and another 786 different genes expressed in synovium from the control group. GO enrichment term analysis revealed an upregulation in endomembrane system organization, ubiquitin system/proteasomal degradation, and membrane transport processes including cytoskeletal, endosomal, and vacuolar in ankle OA samples compared to controls (Figure 1). These signatures differ from those previously identified in knee OA. Reactome analysis revealed pathways to those previously identified in OA of other joints, including TGF-beta signaling modulation. However, several signatures unique to ankle OA included extracellular matrix organization, integrin signaling, and AKT signaling modulation, among others. In addition, unlike in knee OA, reactome analyses of ankle OA synovium did not present with an inflammatory component associated with M1 macrophage infiltration. Conclusion: Ankle synovium in patients with end-stage ankle OA exhibit a transcriptomic signature distinct from ankle synovium collected from non-OA patients. More intriguing, we find that the ankle OA synovial transcriptome signature is distinct from previously published datasets studying synovium from patients with OA in other joints, particularly the knee. GO term and Reactome analyses identified signatures in bulk membrane transport, proteasome, matrix organization, integrin signaling, and AKT signaling, which are different from phenotypes previously reported in the knee. We conclude that development of effective disease modifying treatments for OA require attention to joint-specific biology and disease progression.

Gene expression profiles of ischemic stroke clots retrieved by mechanical thrombectomy are associated with disease etiology

BackgroundDetermining stroke etiology is crucial for secondary prevention, but intensive workups fail to classify ~30% of strokes that are cryptogenic.ObjectiveTo examine the hypothesis that the transcriptomic profiles of clots retrieved...

First Report of Citrus Virus A in Texas Associated with Oak Leaf Patterns in Citrus sinensis.

In 2018, Navarro et al. (2018a, b) identified two new negative sense coguviruses in citrus, citrus concave gum-associated virus (CCGaV) and citrus virus A (CiVA). Since then, the members of the genus Coguvirus have been also detected in other plant species (Xin et al. 2017; Wright et al. 2018; Svanella-Duma et al. 2019). In 2016, leaf flecking with oak leaf patterns were observed in five plants among embryo-rescued navel orange (NO) (Citrus sinensis (L.) Osbeck) trees grafted on C22 (C. sunki x Poncirus trifoliata) rootstock, maintained in a shade house. Madam Vinous (MV) sweet orange trees graft-inoculated with blind buds from the symptomatic NO plants developed the same symptoms in the new growth. These symptoms were similar to those on the citrus concave gum (CG) source tree of the California isolate CG301, one of the standard citrus disease isolates used as a positive control for biological indexing (Roistacher et al. 2000). None of the trees with oak leaf symptoms tested positive with reverse transcription (RT)-PCR for a panel of viruses and viroids commonly infecting citrus (Table S1) . In this study, CG301 leaf RNA-Seq data was used as a platform to identify any viral agent(s) associated with the oak leaf symptoms observed in the symptomatic NO trees (Fig. S1). Of ~162.8 million paired-end CG301 RNA-Seq reads (150 bp), de novo assembly of ~9.6 million reads, not mapped to C. sinensis genome (v.1.1), yielded 5,375 contigs. BLASTn using NCBI virus database (txid 10239) identified two contigs, #49 (6,715 nt) and #20 (2,764 nt), which exhibited ~96% sequence identity, respectively, to RNA1 and 2 of CiVA isolate W4 (MG764565; MG764566) and 71-73% identity to that of CCGaV isolate CGW2 (KX960112; KX960111). 5'-Nuclease assay developed based on contig #20 detected coguviral sequences in the five symptomatic NO and graft-inoculated MV trees as well as in CG301 but not in 44 asymptomatic field trees located near the shade house where the symptomatic NO trees had been kept. A full genomic sequence of the coguviruses present in CG301 and a symptomatic NO tree was reconstructed by RT-PCR. Both CG301 and NO isolate have a 6689 nt long negative sense RNA1 (MT922052; MK689372) encoding RNA-dependent RNA polymerase (RdRp) and a 2739 nt long ambisense RNA2 (MT922053; MK689373) encoding movement protein (MP) and nucleocapsid protein (NP). The isolate CG301 and NO share ~96% nucleotide sequence identity. The genome of both CG301 and NO isolate share 95.4-97.8 % sequence identity to that of CiVA isolate W4 and 70-72.9 % sequence identity to CCGaV isolate CGW2. BLASTp showed that RdRp of CG301 and NO isolate have 96.3-97.7 % sequence identity to CiVA W4 RdRp and ~77 % to CCGaV CGW2 RdRp. These data indicated the presence of CiVA in the symptomatic NO trees and in the concave gum source tree CG301. Recent reports of CiVA in South Africa and Greece indicated a potential wider distribution of CiVA in various citrus growing regions that may be associated with two graft-transmissible citrus diseases, citrus concave gum and impietratura disease (Roistacher et al. 2000; Velázquez et al. 2019; Beris et al. 2021; Bester et al. 2021). Although the source of CiVA in the symptomatic NO trees and the degree of CiVA prevalence in Texas had not been determined yet, a possible involvement of vector(s) or other means of spread (e.g. seed transmission) cannot be ruled out (Timmer et al. 2017). The current study demonstrated the need for further studies to determine the level of threat of coguviruses for citrus production in Texas.

The adult horn fly transcriptome and its complement of transcripts encoding cytochrome P450s, glutathione S-transferases, and esterases

The horn fly, Haematobia irritans, is a blood-feeding parasitic fly with a global distribution that includes Europe, Africa, Asia, and the Americas. The fly has a major detrimental economic impact upon cattle production, with losses estimated at over $800 million annually in the United States and $2.5 billion in Brazil alone. Insecticide resistance in specific horn fly populations has been a problem for many years and there are several mechanisms whereby resistance develops. Little is known about the complement of metabolic enzymes encoded by the horn fly's genome that might provide the fly with detoxification or sequestration pathways to survive insecticide treatments. The cytochrome P450, glutathione S-transferase, and esterase enzyme families contain members that are capable of sequestering and/or detoxifying xenobiotic molecules such as insecticides. We sought to develop a comprehensive dataset of metabolic enzyme-encoding transcript sequences from the adult horn fly, as this is the life stage whose actions directly impose the economic costs to cattle producers. We used an Illumina paired-end read RNA-Seq approach to determine the adult horn fly transcriptomes from laboratory and field populations of horn flies with varying levels of pesticide resistance, including untreated and pyrethroid-treated newly eclosed adult flies. We followed with bioinformatic analyses to discern sequences putatively encoding cytochrome P450, esterase, and GST enzymes. We utilized read-mapping of RNA-Seq data and quantitative real-time polymerase chain reaction (qRT-PCR) to examine gene expression levels of specific P450 transcripts in several fly populations with varying degrees of pesticide resistance.

Accurate assembly of multi-end RNA-seq data with Scallop2.

Modern RNA-sequencing protocols can produce multi-end data, where multiple reads originating from the same transcript are attached to the same barcode. The long-range information in the multi-end reads is beneficial in phasing complicated spliced isoforms, but assembly algorithms that leverage such information are lacking. Here we introduce Scallop2, a reference-based assembler optimized for multi-end RNA-seq data. The algorithmic core of Scallop2 consists of three steps: (1) using an algorithm to "bridge" multi-end reads into single-end phasing paths in the context of a splice graph, (2) employing a method to refine erroneous splice graphs by utilizing multi-end reads that fail to bridge, and (3) piping the refined splice graph and the bridged phasing paths into an algorithm that integrates multiple phase-preserving decompositions. Tested on 561 cells in two Smart-seq3 datasets and on 10 Illumina paired-end RNA-seq samples, Scallop2 substantially improves the assembly accuracy compared to two popular assemblers StringTie2 and Scallop.

Gene Co-Expression Network Analysis Identifies Vitamin D-Associated Gene Modules in Adult Normal Rectal Epithelium Following Supplementation.

Colorectal cancer (CRC) is a common, multifactorial disease. While observational studies have identified an association between lower vitamin D and higher CRC risk, supplementation trials have been inconclusive and the mechanisms by which vitamin D may modulate CRC risk are not well understood. We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify modules present after vitamin D supplementation (when plasma vitamin D level was sufficient) which were absent before supplementation, and then to identify influential genes in those modules. The transcriptome from normal rectal mucosa biopsies of 49 individuals free from CRC were assessed before and after 12 weeks of 3200IU/day vitamin D (Fultium-D3) supplementation using paired-end total RNAseq. While the effects on expression patterns following vitamin D supplementation were subtle, WGCNA identified highly correlated genes forming gene modules. Four of the 17 modules identified in the post-vitamin D network were not preserved in the pre-vitamin D network, shedding new light on the biochemical impact of supplementation. These modules were enriched for GO terms related to the immune system, hormone metabolism, cell growth and RNA metabolism. Across the four treatment-associated modules, 51 hub genes were identified, with enrichment of 40 different transcription factor motifs in promoter regions of those genes, including VDR:RXR. Six of the hub genes were nominally differentially expressed in studies of vitamin D effects on adult normal mucosa organoids: LCN2, HLA-C, AIF1L, PTPRU, PDE4B and IFI6. By taking a gene-correlation network approach, we have described vitamin D induced changes to gene modules in normal human rectal epithelium in vivo, the target tissue from which CRC develops.