Performance and automation of ancient DNA capture with RNA hyRAD probes

Autor: Stéphanie Schiavinato, Tomasz Suchan, Alexander J.E. Pryor, Keiko Kitagawa, Alexander Bessudnov, Naveed Khan, Marek Nowak, Alan K. Outram, Silvia Valenzuela-Lamas, Johannes Krause, Mariya A. Kusliy, Laure Tonasso-Calvière, Alexander A. Bessudnov, Sylwia Pospuła, Marcel Keller, Alexey A. Tishkin, Lorelei Chauvey, John Southon, Alexander S. Graphodatsky, Krzysztof Tunia, Jarosław Wilczyński, Ludovic Orlando, Magdalena Moskal-del-Hoyo
Přispěvatelé: Centre d'anthropologie et de génomique de Toulouse (CAGT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Toulouse III Paul Sabatier, Centre National de la Recherche Scientifique (France), European Research Council, Russian Foundation for Basic Research
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Suchan, Tomasz; Kusliy, Mariya A.; Khan, Naveed; Chauvey, Loreleï; Tonasso-Calvière, Laure; Schiavinato, Stéphanie; Southon, John; Keller, Marcel; Kitagawa, Keiko; Krause, Johannes; Bessudnov, Alexander N.; Bessudnov, Alexander A.; Graphodatsky, Alexander S.; Valenzuela-Lamas, Silvia; Wilczyński, Jarosław; Pospuła, Sylwia; Tunia, Krzysztof; Nowak, Marek; Moskal-delHoyo, Magdalena; Tishkin, Alexey A.; ... (2022). Performance and automation of ancient DNA capture with RNA hyRAD probes. Molecular ecology resources, 22(3), pp. 891-907. Wiley 10.1111/1755-0998.13518
Molecular Ecology Resources
Molecular Ecology Resources, Wiley/Blackwell, 2021, ⟨10.1111/1755-0998.13518⟩
ISSN: 1755-098X
1755-0998
DOI: 10.1111/1755-0998.13518
Popis: DNA hybridization-capture techniques allow researchers to focus their sequencing efforts on preselected genomic regions. This feature is especially useful when analys- ing ancient DNA (aDNA) extracts, which are often dominated by exogenous environ- mental sources. Here, we assessed, for the first time, the performance of hyRAD as an inexpensive and design-free alternative to commercial capture protocols to obtain authentic aDNA data from osseous remains. HyRAD relies on double enzymatic re- striction of fresh DNA extracts to produce RNA probes that cover only a fraction ofthe genome and can serve as baits for capturing homologous fragments from aDNA li- braries. We found that this approach could retrieve sequence data from horse remains coming from a range of preservation environments, including beyond radiocarbon range, yielding up to 146.5-fold on-target enrichment for aDNA extracts showing ex- tremely low endogenous content (20%¿30%), while the fraction of endogenous reads mapping on- and off-target was relatively insensi- tive to the original endogenous DNA content. Procedures based on two instead of a single round of capture increased on-target coverage up to 3.6-fold. Additionally, we used methylation-sensitive restriction enzymes to produce probes targeting hypo- methylated regions, which improved data quality by reducing post-mortem DNA dam- age and mapping within multicopy regions. Finally, we developed a fully automated hyRAD protocol utilizing inexpensive robotic platforms to facilitate capture process- ing. Overall, our work establishes hyRAD as a cost-effective strategy to recover a set of shared orthologous variants across multiple ancient samples.
This project received funding from: the University Paul Sabatier IDEX Chaire d’Excellence (OURASI); the CNRS Programme de Recherche Conjoint (PRC); the CNRS International Research Project (IRP AMADEUS); the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 797449; the Russian Foundation for Basic Research, project No. 19-59-15001 “Horses and their importance in the life of the ancient population of Altai and adjacent territories: interdisciplinary research and reconstruction”; and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement 681605).
Databáze: OpenAIRE
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