ArticleEcology and evolution2020
Using in silico predicted ancestral genomes to improve the efficiency of paleogenome reconstruction.
Article in Ecology and evolution, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Probing the genomic limits of de-extinction in the Christmas Island rat.Current biology : CB · 2022Article
- A Chromosome-Scale Hybrid Genome Assembly of the Extinct Tasmanian Tiger (Thylacinus cynocephalus).Genome biology and evolution · 2022Article
- Using in silico predicted ancestral genomes to improve the efficiency of paleogenome reconstruction.Ecology and evolution · 2020Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
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