Analysis of one million base pairs of Neanderthal DNA

Computational challenges in the analysis of ancient DNA

“…With the enormous throughput of next generation sequencers, it has become tractable to simply shotgun sequence DNA as it is recovered from fossil bones [9-13]. Despite the fact that most of the recovered DNA is from microbes that colonized the bone after death [4,14], the sheer volume of sequence generated means that the few percent that are typically from the species of interest still constitute a sequence dataset large enough for genome-scale analysis.…”

“…Furthermore, because ancient DNA molecules are often fragmented to very short pieces [15], ancient DNA sequencing is not limited in practice by the short read length of current sequencers. The mean ancient DNA fragment length has varied between 60 and 150 bp in most recent large-scale sequencing studies [9-11,13,16-18], but can vary greatly from sample to sample.…”

“…The several recent analyses of ancient DNA shotgun data have largely deployed ad hoc methods to deal with these issues [9-11,13,17]. While necessity has required the use of fast local alignment programs such as BLAST [23], Mega BLAST [24] or BLASTZ [25] when handling such large datasets, the exact classification and filtering regimes have not been standardized or even comprehensively examined.…”

“…In the most straight-forward classification scheme, reads that match a specific target genome with sufficient similarity are classified as endogenous (that is, from the target species) [11,13]. A simple extension of this method considers whether better alignments to other sequence databases exist, and use these to exclude potential microbial or other contaminants [9,10,17]. Divergence can then be calculated in a pairwise manner from the average similarity of all alignments for the sequences deemed to be endogenous [11,13,17].…”

“…Alternatively, in cases where an additional outgroup genome is available, such as the chimpanzee genome for the human/Neandertal comparison, a parsimony approach can be used to assign sequence differences to lineages. From such alignments a more reliable divergence estimate can be derived (later discussed in more detail) [9,10]. …”