Using in silico predicted ancestral genomes to improve the efficiency of paleogenome reconstruction
Paleogenomics is the nascent discipline concerned with sequencing and analysis of genome‐scale information from historic, ancient, and even extinct samples. While once inconceivable due to the challenges of DNA damage, contamination, and the technical limitations of PCR‐based Sanger sequencing, foll...
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Veröffentlicht in: | Ecology and evolution 2020-12, Vol.10 (23), p.12700-12709 |
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Sprache: | eng |
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Zusammenfassung: | Paleogenomics is the nascent discipline concerned with sequencing and analysis of genome‐scale information from historic, ancient, and even extinct samples. While once inconceivable due to the challenges of DNA damage, contamination, and the technical limitations of PCR‐based Sanger sequencing, following the dawn of the second‐generation sequencing revolution, it has rapidly become a reality. However, a significant challenge facing ancient DNA studies on extinct species is the lack of closely related reference genomes against which to map the sequencing reads from ancient samples. Although bioinformatic efforts to improve the assemblies have focused mainly in mapping algorithms, in this article we explore the potential of an alternative approach, namely using reconstructed ancestral genome as reference for mapping DNA sequences of ancient samples. Specifically, we present a preliminary proof of concept for a general framework and demonstrate how under certain evolutionary divergence thresholds, considerable mapping improvements can be easily obtained.
A significant challenge facing ancient DNA studies on extinct species is the lack of closely related reference genomes against which to map the sequencing reads from the ancient samples. Although bioinformatic efforts to improve the assemblies have focused mainly in mapping algorithms, in this article we explore the potential of an alternative approach, namely using reconstructed ancestral genome as reference for mapping DNA sequences of ancient samples. |
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ISSN: | 2045-7758 2045-7758 |
DOI: | 10.1002/ece3.6925 |