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SnpAD: an ancient DNA genotype caller.

ABSTRACT: Motivation:The study of ancient genomes can elucidate the evolutionary past. However, analyses are complicated by base-modifications in ancient DNA molecules that result in errors in DNA sequences. These errors are particularly common near the ends of sequences and pose a challenge for genotype calling. Results:I describe an iterative method that estimates genotype frequencies and errors along sequences to allow for accurate genotype calling from ancient sequences. The implementation of this method, called snpAD, performs well on high-coverage ancient data, as shown by simulations and by subsampling the data of a high-coverage Neandertal genome. Although estimates for low-coverage genomes are less accurate, I am able to derive approximate estimates of heterozygosity from several low-coverage Neandertals. These estimates show that low heterozygosity, compared to modern humans, was common among Neandertals. Availability and implementation:The C++ code of snpAD is freely available at http://bioinf.eva.mpg.de/snpAD/. Supplementary information:Supplementary data are available at Bioinformatics online.

SUBMITTER: Prufer K

PROVIDER: S-EPMC6289138 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

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snpAD: an ancient DNA genotype caller.

Prüfer Kay K

Bioinformatics (Oxford, England) 20181201 24

<h4>Motivation</h4>The study of ancient genomes can elucidate the evolutionary past. However, analyses are complicated by base-modifications in ancient DNA molecules that result in errors in DNA sequences. These errors are particularly common near the ends of sequences and pose a challenge for genotype calling.<h4>Results</h4>I describe an iterative method that estimates genotype frequencies and errors along sequences to allow for accurate genotype calling from ancient sequences. The implementat ...[more]

PMID: 29931305

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Project description:Abstract Objectives Ancient DNA provides an opportunity to separate the genetic and environmental bases of complex traits by allowing direct estimation of genetic values in ancient individuals. Here, we test whether genetic scores for height in ancient individuals are predictive of their actual height, as inferred from skeletal remains. We estimate the contributions of genetic and environmental variables to observed phenotypic variation as a first step towards quantifying individual sources of morphological variation. Materials and methods We collected stature estimates and femur lengths from West Eurasian skeletal remains with published genome‐wide ancient DNA data (n = 182, dating from 33,000–850 BP). We also recorded genetic sex, genetic ancestry, date and paleoclimate data for each individual, and δ13C and δ15N stable isotope values where available (n = 69). We tested different methods of calculating polygenic scores, using summary statistics from four different genome wide association studies (GWAS) for height, and three methods for imputing missing genotypes. Results A polygenic score for height predicts 6.3% of the variance in femur length in our data (n = 132, SD = 0.0069%, p = 0.001), controlling for sex, ancestry, and date. This is consistent with the predictive power of height PRS in present‐day populations and the low coverage of ancient samples. Comparatively, sex explains about 17% of the variance in femur length in our sample. Environmental effects also likely play a role in variation, independent of genetics, though with considerable uncertainty (longitude: R2 = 0.033, SD = 0.008, p = 0.011). Genotype imputation did not improve polygenic prediction, and results varied based on the GWAS summary statistics we used. Discussion Polygenic scores explain a small but significant proportion of the variance in height in ancient individuals, though not enough to make useful predictions of individual phenotypes. However, environmental variables also contribute to phenotypic outcomes and understanding their interaction with direct genetic predictions will provide a framework with which to model how plasticity and genetic changes ultimately combine to drive adaptation and evolution.

Dataset Information

SnpAD: an ancient DNA genotype caller.

Publications

snpAD: an ancient DNA genotype caller.

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