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miR-26a/30d/152是用于皮肤伤口年龄估计中miRNA定量的可靠内参基因。

miR-26a/30d/152 are reliable reference genes for miRNA quantification in skin wound age estimation.

作者信息

Suo Longlong, Cheng Jian, Yuan Haomiao, Jiang Zhenfei, Tash Dilichati, Wang Linlin, Cheng Hao, Zhang Zhongduo, Zhang Fuyuan, Zhang Miao, Cao Zhipeng, Zhao Rui, Guan Dawei

机构信息

Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.

Department of Road Traffic Accident Investigation, Academy of Forensic Science, Shanghai, China.

出版信息

Forensic Sci Res. 2023 Oct 15;8(3):230-240. doi: 10.1093/fsr/owad037. eCollection 2023 Sep.

DOI:10.1093/fsr/owad037
PMID:38221964
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10785593/
Abstract

UNLABELLED

MicroRNAs (miRNAs) are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression. They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation. However, no reports have described any miRNAs as suitable reference genes (RGs) for miRNA quantification in wounded skin or samples with post-mortem changes. Here, we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation. Overall, nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals (PTIs) were preselected by next-generation sequencing as candidate RGs. These nine miRNAs and the commonly used reference genes (comRGs: U6, GAPDH, ACTB, 18S, 5S, LC-Ogdh) were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTIs during skin wound healing in mice. The stabilities of these genes were evaluated using four independent algorithms: GeNorm, NormFinder, BestKeeper, and comparative Delta Ct. Stability was further evaluated in mice with different post-mortem intervals (PMIs). Overall, mmu-miR-26a-5p, mmu-miR-30d-5p, and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMIs. These three miRNA RGs were additionally validated and compared with the comRGs in human samples. After assessing using one, two, or three miRNAs in combination for stability at different PTIs, PMIs, or in human samples, the set of miR-26a/30d/152 was approved as the best normalizer. In conclusion, our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation.

KEY POINTS

The small size of miRNAs makes them less susceptible to post-mortem autolysis or putrefaction, leading to their potential use in wound age estimation.Studying miRNAs as biological indicators of skin wound age estimation requires the selection and validation of stable reference genes because commonly used reference genes, such as U6, ACTB, GAPDH, 5S, 18S, and LC-Ogdh, are not stable.miR-26a/30d/152 are stable and reliable as reference genes and their use in combination is a recommended normalization strategy for miRNA quantitative analysis in wounded skin.

摘要

未标注

微小RNA(miRNA)是一类小的非编码RNA,作为基因表达的负调控因子发挥其生物学功能。它们以动态表达模式参与皮肤伤口愈合过程,因此有可能作为皮肤伤口年龄估计的生物标志物。然而,尚无报告描述任何miRNA可作为受伤皮肤或有死后变化样本中miRNA定量的合适内参基因(RG)。在此,我们旨在鉴定特定的miRNA作为RG用于miRNA定量,以支持皮肤伤口年龄估计的进一步研究。总体而言,通过下一代测序预先选择了在小鼠皮肤创伤后特定时间间隔(PTI)稳定表达的9种miRNA作为候选RG。在小鼠皮肤伤口愈合的不同PTI期间,使用定量实时逆转录聚合酶链反应对这9种miRNA和常用内参基因(comRG:U6、GAPDH、ACTB、18S、5S、LC-Ogdh)进行定量检测。使用四种独立算法(GeNorm、NormFinder、BestKeeper和比较ΔCt)评估这些基因的稳定性。在具有不同死后间隔(PMI)的小鼠中进一步评估稳定性。总体而言,mmu-miR-26a-5p、mmu-miR-30d-5p和mmu-miR-152-3p在不同PTI和PMI时均被鉴定为最稳定的基因。这三种miRNA RG在人类样本中进行了额外验证并与comRG进行比较。在评估不同PTI、PMI或人类样本中使用一种、两种或三种miRNA组合的稳定性后,miR-26a/30d/`152组合被批准为最佳标准化物。总之,我们的数据表明,建议将miR-26a/30d/152组合作为皮肤伤口年龄估计中miRNA qRT-PCR定量的标准化策略。

关键点

miRNA的小尺寸使其较不易受到死后自溶或腐败的影响,从而使其有可能用于伤口年龄估计。将miRNA作为皮肤伤口年龄估计的生物学指标进行研究需要选择和验证稳定的内参基因,因为常用的内参基因,如U6、ACTB、GAPDH、5S、18S和LC-Ogdh并不稳定。miR-26a/30d/152作为内参基因稳定可靠,将它们组合使用是受伤皮肤中miRNA定量分析推荐的标准化策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/d0aae06012aa/owad037f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/675cdce662d0/owad037f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/15728f66071e/owad037f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/8a1ffbbc540c/owad037f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/04f42bcc102f/owad037f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/d0aae06012aa/owad037f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/675cdce662d0/owad037f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/15728f66071e/owad037f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/8a1ffbbc540c/owad037f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/04f42bcc102f/owad037f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/120a/10785593/d0aae06012aa/owad037f5.jpg

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