scholarly journals mir-16-5p as a Suitable Reference Gene for Normalization of Quantitative Real Time PCR in Acute Lymphoblastic Leukemia

2019 ◽  
Vol 51 (2) ◽  
Author(s):  
Samiah Shahid ◽  
Jawaria Shaheen ◽  
Wajeehah Shahid ◽  
M. Waheed Akhtar ◽  
Saima Sadaf
2018 ◽  
Vol 19 (8) ◽  
pp. 2258 ◽  
Author(s):  
Yuning Hu ◽  
Hongtuo Fu ◽  
Hui Qiao ◽  
Shengming Sun ◽  
Wenyi Zhang ◽  
...  

Quantitative real-time PCR (qPCR) is widely used in molecular biology, although the accuracy of the quantitative results is determined by the stability of the reference genes used. Recent studies have investigated suitable reference genes for some crustaceans under various conditions, but studies in Macrobrachium nipponense are currently lacking. In this study, we selected the following seven genes from among 35 commonly used housekeeping genes as candidate qPCR reference genes for temporal and spatial expression: EIF (eukaryotic translation initiation factor 5A), 18S (18S ribosomal RNA), EF-1α (elongation factor-1α), GAPDH (glyceraldehyde-3-phosphate dehydrogenase), TUB (α-tubulin), β-act (β-actin), and RPL18 (Ribosomal protein L18). The stability of each reference gene was evaluated by GeNorm, NormFinder, BestKeeper, and comparative ∆C t methods, and was comprehensively ranked using RefFinder. RPL18 was shown to be the most suitable reference gene for adult M. nipponense tissues, while EIF was the most stable in different ovarian and embryo stages and in white spot syndrome virus infection, and β-act was the most stable reference gene under hypoxia stress. The reliability of the rankings was confirmed by RNA interference experiments. To the best of our knowledge, this represents the first systematic analysis of reference genes for qPCR experiments in M. nipponense, and the results will provide invaluable information for future research in closely related crustaceans.


PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6253 ◽  
Author(s):  
Jun-Yi Li ◽  
Wan-Zhu Chen ◽  
Si-Hua Yang ◽  
Chun-Ling Xu ◽  
Xin Huang ◽  
...  

Six candidate reference genes were chosen from the transcriptome database of Radopholus similis using the bioinformatics method, including four conventional reference genes (actin, Eukaryotic translation initiation factor 5A (eIF5A), Tubulin alpha (a-tubulin), ubiquitin (UBI)) and two new candidate reference genes (Ribosomal protein S21 (Rps21) and Serine/threonine protein phosphatase PP1-β catalytic subunit (β-PP1)). In addition, a traditional reference gene 18S ribosomal RNA (18S rRNA) obtained from NCBI databases was also added to the analysis. Real-time PCR was used to detect the expression of seven candidate reference genes in six populations of R. similis and four developmental stages (female, male, larva and egg) of a population. The stability of the expression of candidate genes was evaluated by three software programs, BestKeeper, geNorm and NormFinder. The results showed that eIF5A is the most suitable reference gene for gene functional research of different populations, while both Rps21 and eIF5A are the most suitable reference genes for different developmental stages of a population. Therefore, eIF5A is the best reference gene for studying R. similis. However, one defect of this study is that only seven candidate reference genes were analyzed; ideally, more genes should be tested.


2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Xian Chen ◽  
Pedro Laborda ◽  
Yan Dong ◽  
Fengquan Liu

Abstract Exogenous melatonin (MT) was found to be an interesting tool for enhancing the resistance of rice to Xanthomonasoryzaepv. oryzae (Xoo)-caused bacterial blight (BB). However, the accurate comparison of the expression levels across samples was a challenging task. In this work, the stability of 10 common used housekeeping genes under Xoo-infection and MT supplementation in rice was analyzed using quantitative real-time PCR (qRT-PCR), and algorithms geNorm, NormFinder and BestKeeper. Our results indicated that most reference genes remained stable in Xoo-infected rice plants, while a number of reference genes were affected by MT supplementation. Among all studied genes, the transcript levels of 18S(18S ribosomal RNA) and UBC (Ubiquitin-conjugating enzyme E2) remained unaltered by Xoo infection, while UBC and UBQ5(Ubiquitin 5) were the most stable genes when examining simultaneous Xoo-infection and MT supplementation, demonstrating that UBC is a suitable reference gene for qRT-PCR data normalization in rice under Xoo-infection and MT supplementation.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Meng Wang ◽  
Tingting Ren ◽  
Prince Marowa ◽  
Haina Du ◽  
Zongchang Xu

AbstractQuantitative real-time polymerase chain reaction (qPCR) using a stable reference gene is widely used for gene expression research. Suaeda glauca L. is a succulent halophyte and medicinal plant that is extensively used for phytoremediation and extraction of medicinal compounds. It thrives under high-salt conditions, which promote the accumulation of high-value secondary metabolites. However, a suitable reference gene has not been identified for gene expression standardization in S. glauca under saline conditions. Here, 10 candidate reference genes, ACT7, ACT11, CCD1, TUA5, UPL1, PP2A, DREB1D, V-H+-ATPase, MPK6, and PHT4;5, were selected from S. glauca transcriptome data. Five statistical algorithms (ΔCq, geNorm, NormFinder, BestKeeper, and RefFinder) were applied to determine the expression stabilities of these genes in 72 samples at different salt concentrations in different tissues. PP2A and TUA5 were the most stable reference genes in different tissues and salt treatments, whereas DREB1D was the least stable. The two reference genes were sufficient to normalize gene expression across all sample sets. The suitability of identified reference genes was validated with MYB and AP2 in germinating seeds of S. glauca exposed to different NaCl concentrations. Our study provides a foundational framework for standardizing qPCR analyses, enabling accurate gene expression profiling in S. glauca.


PLoS ONE ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. e0226668 ◽  
Author(s):  
Xu Su ◽  
Liuyang Lu ◽  
Yashe Li ◽  
Congai Zhen ◽  
Guilei Hu ◽  
...  

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