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Quantitative DNA data extracted from four different soils and two subsurface rock samples

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DataCite Commons2025-12-10 更新2025-04-15 收录
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https://dataservices.gfz.de/panmetaworks/showshort.php?id=f510e733-1685-11ee-95b8-f851ad6d1e4b
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This data publication presents quantitative DNA data obtained through fluorometric detection of genomic DNA and the estimation of 16S rRNA gene copies using quantitative Polymerase Chain Reaction (qPCR). The data encompasses various soil and rock samples collected across a climate gradient. The DNA was extracted using a protocol enabling the separate analysis of intracellular DNA (iDNA) and extracellular DNA (eDNA) from the same sample. The primary objective of this study was to enhance a previously established method developed by Alawi et al. (2014) for analyzing terrestrial samples by introducing modifications to the extraction buffer. Phosphate buffers at two different concentrations (120 mM and 300 mM), EDTA (300 mM), and a high-concentration phosphate buffer in combination with EDTA (300 mM each) were tested in conjunction with a detergent mix (detailed in Medina et al., 2023; submitted). Thorough tests, including spiked DNA experiments and cell counts, were conducted on one low biomass sample to validate the extraction setups. The two most effective extraction protocols were then applied to all samples from the four designated sites and compared with the phosphate buffer described by Alawi et al. (2014), resulting in the calculation of improvement factors. The resulting dataset provides valuable quantitative DNA information and estimates of 16S rRNA gene copies across diverse soil and rock samples along a climate gradient. The modifications made to the extraction buffer demonstrated improved efficiency in extracting especially iDNA compared to the original method. These findings contribute to the refinement and optimization of DNA extraction protocols for terrestrial samples, enabling more accurate and comprehensive analyses of microbial communities in different environments.
提供机构:
GFZ Data Services
创建时间:
2023-06-30
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