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Tyler and his team retrieving sediment cores in the Yukon (2017). Photo Credit: Tyler Murchie

A new approach to sedimentary ancient DNA analysis

Researchers at the Ancient DNA Centre outline new methods for the extraction and enrichment of ancient DNA from permafrost cores greatly increasing the amount of breadth of material recovered.

Sep 01, 2020

Optimizing extraction and targeted capture of ancient environmental DNA for reconstructing past environments using the PalaeoChip Arctic-1.0 bait-set

Authors: Tyler J. Murchie, Melanie Kuch, Ana T. Duggan, Marissa L. Ledger, Kévin Roche, Jennifer Klunk, Emil Karpinski, Dirk Hackenberger, Tara Sadoway, Ross MacPhee, Duane Froese, & Hendrik Poinar

Quaternary Research, September 2020. DOI: https://doi.org/10.1017/qua.2020.59

Abstract

Sedimentary ancient DNA (sedaDNA) has been established as a viable biomolecular proxy for tracking taxon presence through time in a local environment, even in the total absence of surviving tissues. SedaDNA is thought to survive through mineral binding, facilitating long-term biomolecular preservation, but also challenging DNA isolation. Two common limitations in sedaDNA extraction are the carryover of other substances that inhibit enzymatic reactions, and the loss of authentic sedaDNA when attempting to reduce inhibitor co-elution. Here, we present a sedaDNA extraction procedure paired with targeted enrichment intended to maximize DNA recovery. Our procedure exhibits a 7.7–19.3x increase in on-target plant and animal sedaDNA compared to a commercial soil extraction kit, and a 1.2–59.9x increase compared to a metabarcoding approach. To illustrate the effectiveness of our cold spin extraction and PalaeoChip capture enrichment approach, we present results for the diachronic presence of plants and animals from Yukon permafrost samples dating to the Pleistocene-Holocene transition, and discuss new potential evidence for the late survival (~9700 years ago) of mammoth (Mammuthus sp.) and horse (Equus sp.) in the Klondike region of Yukon, Canada. This enrichment approach translates to a more taxonomically diverse dataset and improved on-target sequencing.

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