Amplification-based method for microRNA detection

Shen, Yanting; Tian, Fei; Chen, Zhenzhu; Li, Rui; Ge, Qinyu; Zhang, Lu

doi:10.1016/j.bios.2015.04.057

Cited by 62 publications

(40 citation statements)

References 167 publications

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“…Although these transcripts display constant expression in single analyses, their expression levels can change under different experimental conditions and may be affected by specific types of disease (53). Therefore, the different normalizers should be first established for different sample types, and the combination of several normalizers might be more appropriate than a single universal normalizer (55). …”

Section: Relative Data Normalization To Endogenous Reference Genesmentioning

confidence: 99%

Data Normalization Strategies for MicroRNA Quantification

et al. 2015

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Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure miRNA expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains to be problematic, and can have serious impact on the actual available transcript levels and consequently, on the biological interpretation of data. In this review article we intend to discuss the reliability of use of small RNAs commonly reported in the literature as miRNAs expression normalizers and to compare different normalization strategies used, setting the base for establishing a global standard of miRNAs expression data normalization.

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Section: Relative Data Normalization To Endogenous Reference Genesmentioning

confidence: 99%

Data Normalization Strategies for MicroRNA Quantification

et al. 2015

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“…Some amplification-based strategies that employ intercalating dyes may be unable to correctly differentiate one nucleotide mismatches, particularly when located near the 5′ end (Shen et al 2015). To assess specificity among closely related microRNAs, a universal strand specific to miR-141 was tested with members of the miR-8 family, which differ by 1–6 nucleotides, including miR-200a, miR-429, miR-200a, miR-200b, and miR-200c (Fig.…”

Section: Resultsmentioning

confidence: 99%

Quantification of microRNAs directly from body fluids using a base-stacking isothermal amplification method in a point-of-care device

Williams

Stedtfeld

et al. 2017

Biomed Microdevices

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MicroRNAs have been proposed to be a class of biomarkers of disease as expression levels are significantly altered in various tissues and body fluids when compared to healthy controls. As such, the detection and quantification of microRNAs is imperative. While many methods have been established for quantification of microRNAs, they typically rely on time consuming handling such as RNA extraction, purification, or ligation. Here we describe a novel method for quantification of microRNAs using direct amplification in body fluids without upstream sample preparation. Tested with a point-of-care device (termed Gene-Z), the presence of microRNA promotes base-stacking hybridization, and subsequent amplification between two universal strands. The base-stacking approach, which was achieved in <60 min, provided a sensitivity of 1.4 fmol per reaction. Tested in various percentages of whole blood, plasma, and faeces, precision (coefficient of variation = 2.6%) was maintained and comparable to amplification in pristine samples. Overall, the developed method represents a significant step towards rapid, one-step detection of microRNAs.

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“…Different studies use different normalization strategies to report miRNA expression levels; consequently, there is no consensus on the optimal approach [56]. However, there is some evidence that the combination of several internal reference miRNA normalizers might be more appropriate than a single universal normalize [57]. We did not perform RT-qPCR for our validation because of the concern that RT-qPCR usually uses an individual miRNA as internal control, and the effects of exercise on this selected internal control is unknown.…”

Section: Discussionmentioning

confidence: 99%

Circulating MiRNAs as biomarkers of gait speed responses to aerobic exercise training in obese older adults

Zhang

Brinkley

Liu

et al. 2017

Aging

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Gait speed is a useful predictor of adverse outcomes, including incident mobility disability and mortality in older adults. While aerobic exercise training (AEX) is generally an effective therapy to improve gait speed, individual responses are highly variable. Circulating microRNAs (miRNAs) may contribute to inter-individual changes in gait speed with AEX. We examined whether plasma miRNAs are associated with gait speed changes (dGaitSp) in 33 obese older adults (age: 69.3±3.6 years, BMI: 34.0±3.1 kg/m2, 85% white, 73% women) who performed treadmill walking, 4 days/week for 5 months. Gait speed (baseline: 1.02±0.19 m/s; range of response: −0.2 to 0.35 m/s) was assessed using a 400 meter-fast-paced walk test. Using Nanostring technology, 120 out of 800 miRNAs were found to be abundantly expressed in plasma and 4 of these were significantly changed after AEX: miR-376a-5p increased, while miR-16-5p, miR-27a-3p, and miR-28-3p all decreased. In addition, baseline miR-181a-5p levels (r=-0.40, p=0.02) and percent changes in miR-92a-3p (r=-0.44, p=0.009) associated negatively with dGaitSp. Linear regression combined baseline miR-181a-5p and miR-92a-3p levels showed even stronger associations with dGaitSp (r=-0.48, p=0.005). These results suggest that circulating miR-181a-5p and miR-92a-3p may predict and/or regulate AEX-induced gait speed changes in obese older adults.

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Amplification-based method for microRNA detection

Cited by 62 publications

References 167 publications

Data Normalization Strategies for MicroRNA Quantification

Data Normalization Strategies for MicroRNA Quantification

Quantification of microRNAs directly from body fluids using a base-stacking isothermal amplification method in a point-of-care device

Circulating MiRNAs as biomarkers of gait speed responses to aerobic exercise training in obese older adults

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