The Orthology Clause in the Next Generation Sequencing Era: Novel Reference Genes Identified by RNA-seq in Humans Improve Normalization of Neonatal Equine Ovary RT-qPCR Data

Scarlet, D.; Ertl, Reinhard; Aurich, Christine; Steinborn, Ralf

doi:10.1371/journal.pone.0142122

Cited by 22 publications

(17 citation statements)

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“…Controls without RT‐enzyme were included to monitor for PCR amplification of residual DNA. RT‐qPCR primer were designed using the PrimerQuest assay design tool (http: //eu.idtdna.com/PrimerQuest/Home/Index; Integrated DNA Technologies, Coralville, IA, USA) or taken from the literature . Assay details are provided in Table .…”

Section: Methodsmentioning

confidence: 99%

“…All samples were analysed in duplicate on the AriaMx Realtime PCR System (Agilent Technologies Inc.) using the temperatures: initial denaturation at 95°C for 3 min, followed by 40 cycles of 95°C for 3 s and 60°C for 20 s, and a melting curve analysis over a temperature range of 65°C to 95°C. Four candidate reference genes (RGs) GAPDH, REEP5, SNRPD3 and VCP were included for normalization . The expression stability of all RGs was assessed using the BestKeeper analysis tool, identifying VCP as the most stable gene [SD (±Cq) VCP: 0.44, REEP5: 0.55, GAPDH: 0.57, SNRPD3: 0.66].…”

Section: Methodsmentioning

confidence: 99%

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Cytokine‐induced interleukin‐1 receptor antagonist protein expression in genetically engineered equine mesenchymal stem cells for osteoarthritis treatment

Gabner

Ertl

Velde

et al. 2018

The Journal of Gene Medicine

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BackgroundA combination of tissue engineering methods employing mesenchymal stem cells (MSCs) together with gene transfer takes advantage of innovative strategies and highlights a new approach for targeting osteoarthritis (OA) and other cartilage defects. Furthermore, the development of systems allowing tunable transgene expression as regulated by natural disease‐induced substances is highly desirable.MethodsBone marrow‐derived equine MSCs were transduced with a lentiviral vector expressing interleukin‐1 receptor antagonist (IL‐1Ra) gene under the control of an inducible nuclear factor‐kappa B‐responsive promoter and IL‐1Ra production upon pro‐inflammatory cytokine stimulation [tumor necrosis factor (TNF)α, interleukin (IL)‐1β] was analysed. To assess the biological activity of the IL‐1Ra protein that was produced and the therapeutic effect of IL‐1Ra‐expressing MSCs (MSC/IL‐1Ra), cytokine‐based two‐ and three‐dimensional in vitro models of osteoarthritis using equine chondrocytes were established and quantitative real‐time polymerase chain reaction (PCR) analysis was used to measure the gene expression of aggrecan, collagen IIA1, interleukin‐1β, interleukin‐6, interleukin‐8, matrix metalloproteinase‐1 and matrix metalloproteinase‐13.ResultsA dose‐dependent increase in IL‐1Ra expression was found in MSC/IL‐1Ra cells upon TNFα administration, whereas stimulation using IL‐1β did not lead to IL‐1Ra production above the basal level observed in nonstimulated cells as a result of the existing feedback loop. Repeated cycles of induction allowed on/off modulation of transgene expression. In vitro analyses revealed that IL‐1Ra protein present in the conditioned medium from MSC/IL‐1Ra cells blocks OA onset in cytokine‐treated equine chondrocytes and co‐cultivation of MSC/IL‐1Ra cells with osteoarthritic spheroids alleviates the severity of the osteoarthritic changes.ConclusionsThus, pro‐inflammatory cytokine induced IL‐1Ra protein expression from genetically modified MSCs might represent a promising strategy for osteoarthritis treatment.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Cytokine‐induced interleukin‐1 receptor antagonist protein expression in genetically engineered equine mesenchymal stem cells for osteoarthritis treatment

Gabner

Ertl

Velde

et al. 2018

The Journal of Gene Medicine

Self Cite

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“…The RNA-seq technology is highly automated for global gene expression profiling and may generate a low percentage of data that do not exactly reflect the expression status. Real time qPCR on the other hand, is more accurate but limited to quantification of one gene at a time 67 . In the case of discrepancy between results of RNA-seq and qPCR, we regard that the RNA-seq result may be inaccurate.…”

Section: Discussionmentioning

confidence: 99%

Analysis of mRNA abundance for histone variants, histone- and DNA-modifiers in bovine in vivo and in vitro oocytes and embryos

Duan

Zhu

Dai

et al. 2019

Sci Rep

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Transcript abundance of histone variants, modifiers of histone and DNA in bovine in vivo oocytes and embryos were measured as mean transcripts per million (TPM). Six of 14 annotated histone variants, 8 of 52 histone methyl-transferases, 5 of 29 histone de-methylases, 5 of 20 acetyl-transferases, 5 of 19 de-acetylases, 1 of 4 DNA methyl-transferases and 0 of 3 DNA de-methylases were abundant (TPM >50) in at least one stage studied. Overall, oocytes and embryos contained more varieties of mRNAs for histone modification than for DNA. Three expression patterns were identified for histone modifiers: (1) transcription before embryonic genome activation (EGA) and down-regulated thereafter such as PRMT1; (2) low in oocytes but transiently increased for EGA such as EZH2; (3) high in oocytes but decreased by EGA such as SETD3. These expression patterns were altered by in vitro culture. Additionally, the presence of mRNAs for the TET enzymes throughout pre-implantation development suggests persistent de-methylation. Together, although DNA methylation changes are well-recognized, the first and second orders of significance in epigenetic changes by in vivo embryos may be histone variant replacements and modifications of histones.

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“…Gene-specific amplification was demonstrated by a single peak using the Bio-Rad dissociation melt curve. Samples were normalized based on HPRT1, GAPDH, and GPI (housekeeping genes [ 32 – 34 ]) expression, which were run in parallel reactions to the genes of interest. Additional file 2 : Fig.…”

Section: Methodsmentioning

confidence: 99%

Classification models using circulating neutrophil transcripts can detect unruptured intracranial aneurysm

et al. 2020

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Background Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods. Methods Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n = 94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n = 40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction. Results Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC) = 0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance. Conclusions We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

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The Orthology Clause in the Next Generation Sequencing Era: Novel Reference Genes Identified by RNA-seq in Humans Improve Normalization of Neonatal Equine Ovary RT-qPCR Data

Cited by 22 publications

References 50 publications

Cytokine‐induced interleukin‐1 receptor antagonist protein expression in genetically engineered equine mesenchymal stem cells for osteoarthritis treatment

Cytokine‐induced interleukin‐1 receptor antagonist protein expression in genetically engineered equine mesenchymal stem cells for osteoarthritis treatment

Analysis of mRNA abundance for histone variants, histone- and DNA-modifiers in bovine in vivo and in vitro oocytes and embryos

Classification models using circulating neutrophil transcripts can detect unruptured intracranial aneurysm

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