New genes for accurate normalization of qRT-PCR results in study of iPS and iPS-derived cells

Artyuhov, Alexander; Дашинимаев, Э. Б.; Tsvetkov, Vasily O.; Bolshakov, A D; Коновалова, Е. В.; Kolbaev, Sergey N.; Vorotelyak, E. A.; Vasiliev, A. V.

doi:10.1016/j.gene.2017.05.045

Cited by 17 publications

(21 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Accurate normalization of gene expression data is required to identify differentially expressed genes. Hence, six candidate genes, ACTB , B2M , GAPDH , HPRT1 , TBP , and YWHAZ , have been selected, as they have been used as normalizers in previous studies involving stem cells and neuronal differentiation ( 25 – 28 ). Using the geNorm option in qBase, the reference target stability (M value) for these genes was calculated after omitting the least stable gene ( SI Appendix , Fig.…”

Section: Resultsmentioning

confidence: 99%

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

Hsu

Brinkhof

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Stem cells with the capability to self-renew and differentiate into multiple cell derivatives provide platforms for drug screening and promising treatment options for a wide variety of neural diseases. Nevertheless, clinical applications of stem cells have been hindered partly owing to a lack of standardized techniques to characterize cell molecular profiles noninvasively and comprehensively. Here, we demonstrate that a label-free and noninvasive single-cell Raman microspectroscopy (SCRM) platform was able to identify neural cell lineages derived from clinically relevant human induced pluripotent stem cells (hiPSCs). By analyzing the intrinsic biochemical profiles of single cells at a large scale (8,774 Raman spectra in total), iPSCs and iPSC-derived neural cells can be distinguished by their intrinsic phenotypic Raman spectra. We identified a Raman biomarker from glycogen to distinguish iPSCs from their neural derivatives, and the result was verified by the conventional glycogen detection assays. Further analysis with a machine learning classification model, utilizing t-distributed stochastic neighbor embedding (t-SNE)-enhanced ensemble stacking, clearly categorized hiPSCs in different developmental stages with 97.5% accuracy. The present study demonstrates the capability of the SCRM-based platform to monitor cell development using high content screening with a noninvasive and label-free approach. This platform as well as our identified biomarker could be extensible to other cell types and can potentially have a high impact on neural stem cell therapy.

show abstract

Section: Resultsmentioning

confidence: 99%

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

Hsu

Brinkhof

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…And then the cDNA template was used for subsequent qRT-PCR analysis, which was carried out as described previously. 12 To prepare the reaction mixes, HS-SYBR (Evrogen, Moscow, Russia) was used. The primers used were as follows: RNF38, forward 5ʹ-TTCTTATCGGTTCAATCC-3ʹ and reverse 5ʹ-A ACTCGTGGTTACAGGGT-3ʹ; LDB1, forward 5ʹ-GCTGT GCCTGTCCTGGTT-3ʹ and reverse 5ʹ-GCCCACATCCCT ATCCAG-3ʹ; GAPDH, forward 5ʹ-GCACCGTCAAGGCT GAGAAC-3ʹ and reverse 5ʹ-TGGTGAAGACGCCAGTG GA-3ʹ.…”

Section: Quantitative Real-time Polymerase Chain Reaction (Qrt-pcr)mentioning

confidence: 99%

<p>RING Finger Protein 38 Mediates LIM Domain Binding 1 Degradation and Regulates Cell Growth in Colorectal Cancer</p>

Huang

Yang

et al. 2020

OTT

View full text Add to dashboard Cite

Background and Objectives: RING finger protein 38 (RNF38) has been reported to be involved in the tumorigenesis of several tumors, but its role in colorectal cancer (CRC) is still not investigated. In the present study, we aimed to investigate the effect of RNF38 in CRC cells. Materials and Methods: The public tumor databases GEPIA and Kaplan-Meier Plotter were used to analyze RNF38 expression and patients' overall survival in CRC. The qRT-PCR was carried out to assess the mRNA levels of RNF38 and LDB1. Western blot and co-immunoprecipitation were used to detect protein expression and ubiquitination. CCK-8 assay was performed to analyze CRC cell growth and viability. Results: RNF38 was found downregulated in CRC tumor tissues and cell lines, and CRC patients with high RNF38 expression had a longer overall survival than patients with low RNF38 expression. Our further investigations showed that RNF38 interacted with LDB1, and downregulated LDB1 expression by inducing its polyubiquitination. Moreover, overexpression of RNF38 inhibited CRC cell growth but enforced LDB1 could significantly antagonize RNF38-induced cell growth inhibition in CRC cells. Additionally, RNF38/LDB1 axis was involved in the drug sensitivity of 5-FU to CRC cells. Conclusion: Our studies suggested that RNF38 was functional in CRC cells, and downregulated CRC cell growth by inducing LDB1 polyubiquitination, which indicated that RNF38 could be as a novel target for CRC therapy.

show abstract

“…The aforementioned studies have focused on ES cells with the exception of one study, conducted in differentiating iPS cells, where the team investigated the stability of commonly used housekeeping genes 13 . In this study, ACTB, C1orf43, PSMB4, GAPDH and HMBS were identified as the most stable genes out of 16 genes during iPS differentiation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the stability of 70 housekeeping genes during iPS reprogramming

Panina

Germond

Watanabe

2020

Sci Rep

View full text Add to dashboard Cite

Studies on induced pluripotent stem (iPS) cells highly rely on the investigation of their gene expression which requires normalization by housekeeping genes. Whether the housekeeping genes are stable during the iPS reprogramming, a transition of cell state known to be associated with profound changes, has been overlooked. In this study we analyzed the expression patterns of the most comprehensive list to date of housekeeping genes during iPS reprogramming of a mouse neural stem cell line N31. Our results show that housekeeping genes’ expression fluctuates significantly during the iPS reprogramming. Clustering analysis shows that ribosomal genes’ expression is rising, while the expression of cell-specific genes, such as vimentin (Vim) or elastin (Eln), is decreasing. To ensure the robustness of the obtained data, we performed a correlative analysis of the genes. Overall, all 70 genes analyzed changed the expression more than two-fold during the reprogramming. The scale of this analysis, that takes into account 70 previously known and newly suggested genes, allowed us to choose the most stable of all genes. We highlight the fact of fluctuation of housekeeping genes during iPS reprogramming, and propose that, to ensure robustness of qPCR experiments in iPS cells, housekeeping genes should be used together in combination, and with a prior testing in a specific line used in each study. We suggest that the longest splice variants of Rpl13a, Rplp1 and Rps18 can be used as a starting point for such initial testing as the most stable candidates.

show abstract

New genes for accurate normalization of qRT-PCR results in study of iPS and iPS-derived cells

Cited by 17 publications

References 17 publications

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons

<p>RING Finger Protein 38 Mediates LIM Domain Binding 1 Degradation and Regulates Cell Growth in Colorectal Cancer</p>

Analysis of the stability of 70 housekeeping genes during iPS reprogramming

Contact Info

Product

Resources

About