Imputation of ancient genomes
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB61632 | ENA |
REPOSITORIES: ENA
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Project description:Due to postmortem DNA degradation and microbial colonization, most ancient genomes have low depth of coverage, hindering genotype calling. Genotype imputation can improve genotyping accuracy for low-coverage genomes. However, it is unknown how accurate ancient DNA imputation is and whether imputation introduces bias to downstream analyses. Here we re-sequence an ancient trio (mother, father, son) and downsample and impute a total of 43 ancient genomes, including 42 high-coverage (above 10x) genomes. We assess imputation accuracy across ancestries, time, depth of coverage, and sequencing technology. We find that ancient and modern DNA imputation accuracies are comparable. When downsampled at 1x, 36 of the 42 genomes are imputed with low error rates (below 5%) while African genomes have higher error rates. We validate imputation and phasing results using the ancient trio data and an orthogonal approach based on Mendel's rules of inheritance. We further compare the downstream analysis results between imputed and high-coverage genomes, notably principal component analysis, genetic clustering, and runs of homozygosity, observing similar results starting from 0.5x coverage, except for the African genomes. These results suggest that, for most populations and depths of coverage as low as 0.5x, imputation is a reliable method that can improve ancient DNA studies.
| S-EPMC10282092 | biostudies-literature
Project description:Alignment of publicly available ancient genomes to hg38
| PRJEB64654 | ENA
Project description:Matthias Hunyadi son and grandson ancient genomes
| PRJEB47418 | ENA
Project description:Although ancient DNA data have become increasingly more important in studies about past populations, it is often not feasible or practical to obtain high coverage genomes from poorly preserved samples. While methods of accurate genotype imputation from > 1 × coverage data have recently become a routine, a large proportion of ancient samples remain unusable for downstream analyses due to their low coverage. Here, we evaluate a two-step pipeline for the imputation of common variants in ancient genomes at 0.05-1 × coverage. We use the genotype likelihood input mode in Beagle and filter for confident genotypes as the input to impute missing genotypes. This procedure, when tested on ancient genomes, outperforms a single-step imputation from genotype likelihoods, suggesting that current genotype callers do not fully account for errors in ancient sequences and additional quality controls can be beneficial. We compared the effect of various genotype likelihood calling methods, post-calling, pre-imputation and post-imputation filters, different reference panels, as well as different imputation tools. In a Neolithic Hungarian genome, we obtain ~ 90% imputation accuracy for heterozygous common variants at coverage 0.05 × and > 97% accuracy at coverage 0.5 ×. We show that imputation can mitigate, though not eliminate reference bias in ultra-low coverage ancient genomes.
| S-EPMC7596702 | biostudies-literature
Project description:Three hepatitis B genomes were recovered from ancient human bones
| PRJEB24921 | ENA
Project description:For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.
| EGAS00001003359 | EGA
Project description:Ancient nuclear genomes enable repatriation of Indigenous human remains
| PRJEB29663 | ENA
Project description:DE microRNAs between normal bone and ancient osteosarcoma
2019-06-21 | GSE118540 | GEO
Project description:Ancient human dental calculus Metagenome
| PRJNA608541 | ENA
Project description:Ancient Mycobacterium leprae genomes from mediaeval England
| PRJEB31393 | ENA