Transcriptomic analysis of HEK293A cells with a CRISPR/Cas9-mediated TDP1 knockout.

Tyrosyl-DNA phosphodiesterase 1 (TDP1) is a human DNA repair protein. It is a member of the phospholipase D family based on structural similarity. TDP1 is a key enzyme of the repair of stalled topoisomerase 1 (TOP1)-DNA complexes. Previously, with the CRISPR/Cas9 method, we obtained HEK293A cells with a homozygous knockout of the TDP1 gene and used the TDP1 knockout cells as a cellular model for studying mechanisms of action of an anticancer therapy. In the present work, we hypothesized that the TDP1 knockout would alter the expression of DNA repair-related genes. By transcriptomic analysis, we investigated for the first time the effect of the TDP1 gene knockout on genes' expression changes in the human HEK293A cell line. We obtained original data implying a role of TDP1 in other processes besides the repair of the DNA-TOP1 complex. Differentially expressed gene analysis revealed that TDP1 may participate in cell adhesion and communication, spermatogenesis, mitochondrial function, neurodegeneration, a cytokine response, and the MAPK signaling pathway.

RNAseq profiling of blood from patients with coronary artery disease: Signature of a T cell imbalance.

Background: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD. Methods: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA). Results: The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r = 0.87), but there was only 9 % overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93 %) of DEGs were down-regulated ~1.7-fold in patients with moderate to severe CAD (>20 % stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. DEGs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells. Conclusions: These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

RNAseq analysis of treatment-dependent signaling changes during inflammation in a mouse cutaneous wound healing model.

BACKGROUND: Despite proven therapeutic effects in inflammatory conditions, the specific mechanisms of phytochemical therapies are not well understood. The transcriptome effects of Traumeel (Tr14), a multicomponent natural product, and diclofenac, a non-selective cyclooxygenase (COX) inhibitor, were compared in a mouse cutaneous wound healing model to identify both known and novel pathways for the anti-inflammatory effect of plant-derived natural products. METHODS: Skin samples from abraded mice were analyzed by single-molecule, amplification-free RNAseq transcript profiling at 7 points between 12 and 192 h after injury. Immediately after injury, the wounds were treated with either diclofenac, Tr14, or placebo control (n = 7 per group/time). RNAseq levels were compared between treatment and control at each time point using a systems biology approach. RESULTS: At early time points (12-36 h), both control and Tr14-treated wounds showed marked increase in the inducible COX2 enzyme mRNA, while diclofenac-treated wounds did not. Tr14, in contrast, modulated lipoxygenase transcripts, especially ALOX12/15, and phospholipases involved in arachidonate metabolism. Notably, Tr14 modulated a group of cell-type specific markers, including the T cell receptor, that could be explained by an overarching effect on the type of cells that were recruited into the wound tissue. CONCLUSIONS: Tr14 and diclofenac had very different effects on the COX/LOX synthetic pathway after cutaneous wounding. Tr14 allowed normal autoinduction of COX2 mRNA, but suppressed mRNA levels for key enzymes in the leukotriene synthetic pathway. Tr14 appeared to have a broad 'phytocellular' effect on the wound transcriptome by altering the balance of cell types present in the wound.

Genome-wide association and whole exome sequencing studies reveal a novel candidate locus for restless legs syndrome.

INTRODUCTION: The restless legs syndrome (RLS) is a common heritable neurologic disorder which is characterized by an irresistible desire to move and unpleasant sensations in the legs. METHODS: We aim to identify new variants associated with RLS by performing genome-wide linkage and subsequent association analysis of forty member's family with history of RLS. RESULTS: We found evidence of linkage for three loci 7q21.11 (HLOD = 3.02), 7q21.13-7q21.3 (HLOD = 3.02) and 7q22.3 (HLOD = 3.09). Fine-mapping of those regions in association study using exome sequencing identified SEMA3A (p-value = 8.5·10-4), PPP1R9A (p-value = 7.2·10-4), PUS7 (p-value = 8.7·10-4), CDHR3 (p-value = 7.2·10-4), HBP1 (p-value = 1.5·10-4) and COG5 (p-value = 1.5·10-4) genes with p-values below significance threshold. CONCLUSION: Linkage analysis with subsequent association study of exome variants identified six new genes associated with RLS mapped on 7q21 and q22.

Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis.

MOTIVATION: The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be addressed via the style transfer approach. Either technical factors or any biological details about the samples which we would like to control (gender, biological state, treatment, etc.) can be used as style components. RESULTS: The proposed style transfer solution is based on Conditional Variational Autoencoders, Y-Autoencoders and adversarial feature decomposition. To quantitatively measure the quality of the style transfer, neural network classifiers which predict the style and semantics after training on real expression were used. Comparison with several existing style-transfer based approaches shows that proposed model has the highest style prediction accuracy on all considered datasets while having comparable or the best semantics prediction accuracy. AVAILABILITY AND IMPLEMENTATION: https://github.com/NRshka/stvae-source. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Biomarker discovery in attention deficit hyperactivity disorder: RNA sequencing of whole blood in discordant twin and case-controlled cohorts.

BACKGROUND: A variety of DNA-based methods have been applied to identify genetic markers of attention deficit hyperactivity disorder (ADHD), but the connection to RNA-based gene expression has not been fully exploited. METHODS: Using well defined cohorts of discordant, monozygotic twins from the Michigan State University Twin Registry, and case-controlled ADHD cases in adolescents, the present studies utilized advanced single molecule RNA sequencing to identify expressed changes in whole blood RNA in ADHD. Multiple analytical strategies were employed to narrow differentially expressed RNA targets to a small set of potential biomarkers of ADHD. RESULTS: RNA markers common to both the discordant twin study and case-controlled subjects further narrowed the putative targets, some of which had been previously associated with ADHD at the DNA level. The potential role of several differentially expressed genes, including ABCB5, RGS2, GAK, GIT1 and 3 members of the galactose metabolism pathway (GALE, GALT, GALK1) are substantiated by prior associations to ADHD and by established mechanistic connections to molecular pathways relevant to ADHD and behavioral control. CONCLUSIONS: The convergence of DNA, RNA, and metabolic data suggests these may be promising targets for diagnostics and therapeutics in ADHD.

CellCountCV-A Web-Application for Accurate Cell Counting and Automated Batch Processing of Microscopic Images Using Fully Convolutional Neural Networks.

In vitro cellular models are promising tools for studying normal and pathological conditions. One of their important applications is the development of genetically engineered biosensor systems to investigate, in real time, the processes occurring in living cells. At present, there are fluorescence, protein-based, sensory systems for detecting various substances in living cells (for example, hydrogen peroxide, ATP, Ca2+ etc.,) or for detecting processes such as endoplasmic reticulum stress. Such systems help to study the mechanisms underlying the pathogenic processes and diseases and to screen for potential therapeutic compounds. It is also necessary to develop new tools for the processing and analysis of obtained microimages. Here, we present our web-application CellCountCV for automation of microscopic cell images analysis, which is based on fully convolutional deep neural networks. This approach can efficiently deal with non-convex overlapping objects, that are virtually inseparable with conventional image processing methods. The cell counts predicted with CellCountCV were very close to expert estimates (the average error rate was < 4%). CellCountCV was used to analyze large series of microscopic images obtained in experimental studies and it was able to demonstrate endoplasmic reticulum stress development and to catch the dose-dependent effect of tunicamycin.

Deep Sequencing Transcriptome Analysis of Murine Wound Healing: Effects of a Multicomponent, Multitarget Natural Product Therapy-Tr14.

Wound healing involves an orchestrated response that engages multiple processes, such as hemostasis, cellular migration, extracellular matrix synthesis, and in particular, inflammation. Using a murine model of cutaneous wound repair, the transcriptome was mapped from 12 h to 8 days post-injury, and in response to a multicomponent, multi-target natural product, Tr14. Using single-molecule RNA sequencing (RNA-seq), there were clear temporal changes in known transcripts related to wound healing pathways, and additional novel transcripts of both coding and non-coding genes. Tr14 treatment modulated >100 transcripts related to key wound repair pathways, such as response to wounding, wound contraction, and cytokine response. The results provide the most precise and comprehensive characterization to date of the transcriptome's response to skin damage, repair, and multicomponent natural product therapy. By understanding the wound repair process, and the effects of natural products, it should be possible to intervene more effectively in diseases involving aberrant repair.

Genome-wide profiling and differential expression of microRNA in rat pluripotent stem cells.

MicroRNAs (miRNAs) constitute a class of small noncoding RNAs that plays an important role in the post-transcriptional regulation of gene expression. Much evidence has demonstrated that miRNAs are involved in regulating the human and mouse pluripotency. Nevertheless, to our knowledge, miRNAs in the pluripotent stem cells of one of the most commonly used model organisms - the Rattus norvegicus have not been studied. In the present study, we performed deep sequencing of small RNA molecules in the embryonic fibroblasts, embryonic stem cells, and induced pluripotent stem cells of laboratory rats. Bioinformatics analysis revealed 674 known miRNAs and 394 novel miRNA candidates in all of the samples. Expression of known pluripotency-associated miRNAs, such as the miR-290-295 and miR-183-96-182 clusters as well as members of the miR-200 family, was detected in rat pluripotent stem cells. Analysis of the targets of differentially expressed known and novel miRNAs showed their involvement in the regulation of pluripotency and the reprogramming process in rats. Bioinformatics and systems biology approaches identified potential pathways that are regulated by these miRNAs. This study contributes to our understanding of miRNAs in the regulation of pluripotency and cell reprogramming in the laboratory rat.

Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.

Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlinc RNAs genes likely function in cisto activate nearby genes. This effect while most pronounced in closely spaced vlinc RNA-gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlinc RNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs.

Genome-wide analysis of A-to-I RNA editing by single-molecule sequencing in Drosophila.

The accurate and thorough genome-wide detection of adenosine-to-inosine editing, a biologically indispensable process, has proven challenging. Here, we present a discovery pipeline in adult Drosophila, with 3,581 high-confidence editing sites identified with an estimated accuracy of 87%. The target genes and specific sites highlight global biological properties and functions of RNA editing, including hitherto-unknown editing in well-characterized classes of noncoding RNAs and 645 sites that cause amino acid substitutions, usually at conserved positions. The spectrum of functions that these gene targets encompass suggests that editing participates in a diverse set of cellular processes. Editing sites in Drosophila exhibit sequence-motif preferences and tend to be concentrated within a small subset of total RNAs. Finally, editing regulates expression levels of target mRNAs and strongly correlates with alternative splicing.

VlincRNAs controlled by retroviral elements are a hallmark of pluripotency and cancer.

BACKGROUND: The function of the non-coding portion of the human genome remains one of the most important questions of our time. Its vast complexity is exemplified by the recent identification of an unusual and notable component of the transcriptome - very long intergenic non-coding RNAs, termed vlincRNAs. RESULTS: Here we identify 2,147 vlincRNAs covering 10 percent of our genome. We show they are present not only in cancerous cells, but also in primary cells and normal human tissues, and are controlled by canonical promoters. Furthermore, vlincRNA promoters frequently originate from within endogenous retroviral sequences. Strikingly, the number of vlincRNAs expressed from endogenous retroviral promoters strongly correlates with pluripotency or the degree of malignant transformation. These results suggest a previously unknown connection between the pluripotent state and cancer via retroviral repeat-driven expression of vlincRNAs. Finally, we show that vlincRNAs can be syntenically conserved in humans and mouse and their depletion using RNAi can cause apoptosis in cancerous cells. CONCLUSIONS: These intriguing observations suggest that vlincRNAs could create a framework that combines many existing short ESTs and lincRNAs into a landscape of very long transcripts functioning in the regulation of gene expression in the nucleus. Certain types of vlincRNAs participate at specific stages of normal development and, based on analysis of a limited set of cancerous and primary cell lines, they appear to be co-opted by cancer-associated transcriptional programs. This provides additional understanding of transcriptome regulation during the malignant state, and could lead to additional targets and options for its reversal.

On the importance of small changes in RNA expression.

The analysis of the differential expression of genes has been the key goal of many molecular biology methods for decades and will remain with us for decades to come. It constitutes a fundamental resource at our disposal for determining the relationship between products of transcription, biology and disease. The completed genome sequencing of many common species allowed microarrays and RNA sequencing (RNAseq) to become major tools in Systems Biology. However, we estimate that at least half of all experiments ignore transcripts that change less than some subjectively chosen threshold, typically around 2-3 fold. Here we show that a majority of the informative RNAs and differentially expressed transcripts can exhibit fold changes less than 2. We use highly quantitative single-molecule sequencing of total cellular RNA derived from a time course of inflammatory response, a process critical to a large number of diseases. Furthermore, we show that enrichment of biologically-relevant functions occurs even at very low fold changes in RNA levels. In addition, we show that most of the common statistical methods can reliably detect transcripts with low fold change when as few as 3 biological replicates are sequenced using single-molecule based RNAseq. In conclusion, given the prevalence of expression profiling in current research, the loss of data in half of all expression studies results in a significant, yet needless drain on the discovery process.

Insights from the HuR-interacting transcriptome: ncRNAs, ubiquitin pathways, and patterns of secondary structure dependent RNA interactions.

The HuR protein regulates the expression of thousands of cellular transcripts by modulating mRNA splicing, trafficking, translation, and stability. Although it serves as a model of RNA-protein interactions, many features of HuR's interactions with RNAs remain unknown. In this report, we deployed the cryogenic RNA immunoprecipitation technique to analyze HuR-interacting RNAs with the Affymetrix all-exon microarray platform. We revealed several thousand novel HuR-interacting RNAs, including hundreds of non-coding RNAs such as natural antisense transcripts from stress responsive loci. To gain insight into the mechanisms of specificity and sensitivity of HuR's interaction with its target RNAs, we searched HuR-interacting RNAs for composite patterns of primary sequence and secondary structure. We provide evidence that secondary structures of 66-75 nucleotides enhance HuR's recognition of its specific RNA targets composed of short primary sequence patterns. We validated thousands of these RNAs by analysis of overlap with recently published findings, including HuR's interaction with RNAs in the pathways of RNA splicing and stability. Finally, we observed a striking enrichment for members of ubiquitin ligase pathways among the HuR-interacting mRNAs, suggesting a new role for HuR in the regulation of protein degradation to mirror its known function in protein translation.

Intronic RNAs constitute the major fraction of the non-coding RNA in mammalian cells.

BACKGROUND: The function of RNA from the non-coding (the so called "dark matter") regions of the genome has been a subject of considerable recent debate. Perhaps the most controversy is regarding the function of RNAs found in introns of annotated transcripts, where most of the reads that map outside of exons are usually found. However, it has been reported that the levels of RNA in introns are minor relative to those of the corresponding exons, and that changes in the levels of intronic RNAs correlate tightly with that of adjacent exons. This would suggest that RNAs produced from the vast expanse of intronic space are just pieces of pre-mRNAs or excised introns en route to degradation. RESULTS: We present data that challenges the notion that intronic RNAs are mere by-standers in the cell. By performing a highly quantitative RNAseq analysis of transcriptome changes during an inflammation time course, we show that intronic RNAs have a number of features that would be expected from functional, standalone RNA species. We show that there are thousands of introns in the mouse genome that generate RNAs whose overall abundance, which changes throughout the inflammation timecourse, and other properties suggest that they function in yet unknown ways. CONCLUSIONS: So far, the focus of non-coding RNA discovery has shied away from intronic regions as those were believed to simply encode parts of pre-mRNAs. Results presented here suggest a very different situation--the sequences encoded in the introns appear to harbor a yet unexplored reservoir of novel, functional RNAs. As such, they should not be ignored in surveys of functional transcripts or other genomic studies.