Comprehensive, targeted eukaryotic metagenomics analysis of environmental DNA biodiversity using Oxford Nanopore sequencing
收藏NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/10416914
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Metagenomics has become a prominent technology for studying the functional potential of all organisms in a microbial and eukaryotic community. The study of symbiotic organisms from different classes or kingdoms, including those previously unknown, is possible with simultaneous and equally efficient metagenomic analysis of these species. A variety of targeted primer sets are used for eukaryotic metagenomic biodiversity, including those that are universal for specific families, classes, or kingdoms. The most universal for all existing cellular organisms is the presence of ribosomal RNA encoding gene sequences. For eukaryotic sequences, these are 16S and 23s rDNA, and for eukaryotic sequences of nuclear (18S and 28S) and mitochondrial (12S and 16S) ribosomal RNA. Here we present the application of the eukaryotic metagenomics approach to the simultaneous, quantitative, and unbiased identification of most eukaryotic species. To achieve this, we have developed a universal PCR assay that targets the most conservative nuclear regions of the ribosomal gene for all cellular organisms, including plants, algae, fungi, protists, insects, and animals. The amplification product contains polymorphic regions of both ribosomal genes and the intergenic spacer. The size of the PCR products varies by class, kingdom, or domain, ranging from 2 kb for fungi to 7 kb for birds. This assay is also adapted for use with the Oxford Nanopore Rapid Barcoding Library Kit, which enables metagenomic biodiversity analysis. Our approach provides a rapid, sensitive, and equally efficient way to study the composition of eDNA from mixed species in the environment. This protocol reduces the time and cost of metagenomic biodiversity analysis using Oxford Nanopore sequencing. We can efficiently analyze the biodiversity of mixed species present in environmental samples.
创建时间:
2024-02-01



