The future of ancient DNA: Technical advances and conceptual shifts: Prospects & Overviews

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Abstract

Technological innovations such as next generation sequencing and DNA hybridisation enrichment have resulted in multi-fold increases in both the quantity of ancient DNA sequence data and the time depth for DNA retrieval. To date, over 30 ancient genomes have been sequenced, moving from 0.7× coverage (mammoth) in 2008 to more than 50× coverage (Neanderthal) in 2014. Studies of rapid evolutionary changes, such as the evolution and spread of pathogens and the genetic responses of hosts, or the genetics of domestication and climatic adaptation, are developing swiftly and the importance of palaeogenomics for investigating evolutionary processes during the last million years is likely to increase considerably. However, these new datasets require new methods of data processing and analysis, as well as conceptual changes in interpreting the results. In this review we highlight important areas of future technical and conceptual progress and discuss research topics in the rapidly growing field of palaeogenomics.

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Derrick E Wood, Steven L Salzberg (2014)

Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of k-mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at http://ccb.jhu.edu/software/kraken/.

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Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

Christoph Hahn, Lutz Bachmann, Bastien Chevreux (2013)

We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.