Ancient DNA requires specialized considerations for primer design
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Peer-reviewed literature demonstrates that ancient DNA studies require specialized PCR primer combinations—specifically targeting short amplicons—to account for degradation and amplification biases.
Fungi are crucial organisms in most ecosystems as they exert ecological key functions and are closely associated with land plants. Fungal community changes may, therefore, help reveal biodiversity changes in past ecosystems. Lake sediments contain the DNA of organisms in the catchment area, which allows reconstructing past biodiversity by using metabarcoding of ancient sedimentary DNA. We re- evaluated various commonly used metabarcoding primers, and we developed a novel PCR primer combination for fungal metabarcoding to produce a short amplicon, thus accounting for amplification bias due to the degradation of ancient DNA. In silico PCRs showed higher diversity using this new primer combination, compared with previously established fungal metabarcoding primers. We analyzed data from sediment cores from four artic and one boreal lake in Siberia. These cores had been stored for 2– 22 years after coring; we, therefore, examined the degradation effects of ancient DNA and storage time- related bias affecting fungal communities. Amplicon lengths showed considerable variation within and between the major divisions of fungi, for example, amplicons of Basidiomycota were significantly longer than those of Mucoromycota; however, we observed no significant effect of sample age on amplicon length and GC content, suggesting the robustness of our results. We also found no indication of post- coring fungal growth during storage regarding the proportions of common mold taxa, which would otherwise distort conclusions on past fungal communities. Terrestrial soil fungi, including mycorrhizal fungi and saprotrophs
Fungi are crucial organisms in most ecosystems as they exert ecological key functions and are closely associated with land plants. Fungal community changes may therefore help reveal biodiversity changes in past ecosystems. Lake sediments contain DNA of organisms in the catchment area, which allows reconstructing past biodiversity by using metabarcoding of ancient sedimentary DNA. We developed a novel PCR primer combination for fungal metabarcoding targeting a short amplicon to account for length bias of amplification due to ancient DNA degradation. In-silico PCRs showed higher diversity using this primer combination than using previously established fungal metabarcoding primers. We analyzed existing data from sediment cores from four artic and one boreal lake in Siberia. These cores had been stored for 2–22 years and examined degradation effects of ancient DNA and storage time-related bias in fungal communities. Amplicon size differed between fungal divisions, however, we observed no significant effect of sample age on amplicon length and GC content, suggesting robust results. We also found no indication of post-coring fungal growth during storage distorting ancient fungal communities. Terrestrial soil fungi, including mycorrhizal fungi and saprotrophs, were predominant in all lakes, which supports the use of lake sedimentary ancient DNA for reconstructing terrestrial communities.
Ancient DNA (aDNA) recovered from archaeobotanical remains can provide key insights into many prominent archaeological research questions, including processes of domestication, past subsistence strategies, and human interactions with the environment. However, it is often difficult to isolate aDNA from ancient plant materials, and furthermore, such DNA extracts frequently contain inhibitory substances that preclude successful PCR amplification. In the age of high-throughput sequencing, this problem is even more significant because each additional endogenous aDNA molecule improves analytical res
ABSTRACT Like modern metagenomics, ancient metagenomics is a highly data-rich discipline, with the added challenge that the DNA of interest is degraded and, depending on the sample type, in low abundance. This requires the application of specialized measures during molecular experiments and computational analyses. Furthermore, researchers often work with finite sample sizes, which impedes optimal experimental design and control of confounding factors, and with ethically sensitive samples necessi
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