Optimisation of DNA extraction from the crustacean Daphnia

甲壳类水蚤 DNA 提取的优化

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作者:Camila Gonçalves Athanasio, James K Chipman, Mark R Viant, Leda Mirbahai

Abstract

Daphnia are key model organisms for mechanistic studies of phenotypic plasticity, adaptation and microevolution, which have led to an increasing demand for genomics resources. A key step in any genomics analysis, such as high-throughput sequencing, is the availability of sufficient and high quality DNA. Although commercial kits exist to extract genomic DNA from several species, preparation of high quality DNA from Daphnia spp. and other chitinous species can be challenging. Here, we optimise methods for tissue homogenisation, DNA extraction and quantification customised for different downstream analyses (e.g., LC-MS/MS, Hiseq, mate pair sequencing or Nanopore). We demonstrate that if Daphnia magna are homogenised as whole animals (including the carapace), absorbance-based DNA quantification methods significantly over-estimate the amount of DNA, resulting in using insufficient starting material for experiments, such as preparation of sequencing libraries. This is attributed to the high refractive index of chitin in Daphnia's carapace at 260 nm. Therefore, unless the carapace is removed by overnight proteinase digestion, the extracted DNA should be quantified with fluorescence-based methods. However, overnight proteinase digestion will result in partial fragmentation of DNA therefore the prepared DNA is not suitable for downstream methods that require high molecular weight DNA, such as PacBio, mate pair sequencing and Nanopore. In conclusion, we found that the MasterPure DNA purification kit, coupled with grinding of frozen tissue, is the best method for extraction of high molecular weight DNA as long as the extracted DNA is quantified with fluorescence-based methods. This method generated high yield and high molecular weight DNA (3.10 ± 0.63 ng/µg dry mass, fragments >60 kb), free of organic contaminants (phenol, chloroform) and is suitable for large number of downstream analyses.

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