PT  - JOURNAL ARTICLE
AU  - Giada Ferrari
AU  - Lane M. Atmore
AU  - Sissel Jentoft
AU  - Kjetill S. Jakobsen
AU  - Daniel Makowiecki
AU  - James H. Barrett
AU  - Bastiaan Star
TI  - An accurate assignment test for extremely low-coverage whole-genome sequence data
AID  - 10.1101/2021.06.04.447098
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.06.04.447098
4099  - http://biorxiv.org/content/early/2021/06/07/2021.06.04.447098.short
4100  - http://biorxiv.org/content/early/2021/06/07/2021.06.04.447098.full
AB  - Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. In ancient DNA research, such characters can provide further information on population continuity, evolution, climate change, species migration, or trade, depending on archaeological context. Yet, assignment tests often rely on moderate- to high-coverage sequence data, which can be difficult to obtain for many ancient specimens and in ecological studies, which often use sequencing techniques such as ddRAD to bypass the need for costly whole-genome sequencing. We have developed a novel approach that efficiently assigns biologically relevant information (such as population identity or structural variants) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic Single Nucleotide Polymorphisms (SNPs) associated with a biological characteristic. Low coverage alignment files from ancient specimens are subsequently compared to these databases to ascertain allelic state yielding a joint probability for each association. To assess the efficacy of this approach, we assigned inversion haplotypes and population identity in several species including Heliconius butterflies, Atlantic herring, and Atlantic cod. We used both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage (e.g. 0.0001x fold) based on genome-wide SNPs. This approach will therefore increase the number of ancient samples in ecological and bioarchaeological research for which relevant biological information can be obtained.Competing Interest StatementThe authors have declared no competing interest.