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Comparison of two mechanical disaggregation methods of fresh lung tissues for extraction of high-quality RNA

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DataCite Commons2024-10-22 更新2024-08-26 收录
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https://tandf.figshare.com/articles/dataset/Comparison_of_two_mechanical_disaggregation_methods_of_fresh_lung_tissues_for_extraction_of_high-quality_RNA/25027628
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Gene expression studies are widely used in medical, biological, and pharmaceutical research. Obtaining high-quality RNA from tissues is a prerequisite for high-quality data that should accurately represent gene expression levels in-vivo. The main source of technical bias, which could affect the results from transcriptomic studies, is variation in RNA quality. In this regard, tissue preparation is critical: different disruption techniques can affect RNA quality, influencing further applications. Mechanical disaggregation is a common, inexpensive, and simple method to obtain a high cell yield, demonstrated to efficiently disrupt the extracellular matrix and release single cells. However, its efficacy is operator-dependent, leading to poorly reproducible results. A fast, reproducible, and standardized technique could undoubtedly overcome this problem, avoiding wasting time and resources. In this study, our goal was to evaluate the impact of two mechanical tissue disruption techniques on the purity and quality of RNA extracted from fresh lung biopsies. The samples were processed in parallel using manual mechanical disaggregation or an automated mechanical device. The results showed that samples processed with the automated device had a higher integrity compared to those processed manually with a median Fragmentation Index of 0.86 and 0.71 respectively. This difference is statistically significant (<i>p</i> = 0.0084). Overall, our results indicated that the use of automatic mechanical disaggregation could undoubtedly help to overcome the technical biases related to fresh tissues processing.
提供机构:
Taylor & Francis
创建时间:
2024-01-19
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