Search

Abstract We investigate alternative strategies against reference bias and postmortem damage in low coverage paleogenomes. Compared to alignment to the linear reference genome, we show that masking known polymorphic sites and graph alignment effectively remove reference bias, but only starting from raw read files. We next study approaches to overcome postmortem damage: trimming, rescaling, and our newly developed algorithm, bamRefine (github.com/etkayapar/bamRefine and zenodo.org/records/14234666), masking reads only at positions possibly affected by PMD. We propose graph alignment coupled with bamRefine as a simple strategy to minimize data loss and bias, and urge the community to publish FASTQ files.

Abstract The Neolithic transition introduced major diet and lifestyle changes to human populations across continents. Beyond well‐documented bioarcheological and genetic effects, whether these changes also had molecular‐level epigenetic repercussions in past human populations has been an open question. In fact, methylation signatures can be inferred from UDG‐treated ancient DNA through postmortem damage patterns, but with low signal‐to‐noise ratios; it is thus unclear whether published paleogenomes would provide the necessary resolution to discover systematic effects of lifestyle and diet shifts. To address this we compiled UDG‐treated shotgun genomes of 13 pre‐Neolithic hunter‐gatherers (HGs) and 21 Neolithic farmers (NFs) individuals from West and North Eurasia, published by six different laboratories and with coverage c.1×–58× (median = 9×). We used epiPALEOMIX and a Monte Carlo normalization scheme to estimate methylation levels per genome. Our paleomethylome dataset showed expected genome‐wide methylation patterns such as CpG island hypomethylation. However, analyzing the data using various approaches did not yield any systematic signals for subsistence type, genetic sex, or tissue effects. Comparing the HG‐NF methylation differences in our dataset with methylation differences between hunter‐gatherers versus farmers in modern‐day Central Africa also did not yield consistent results. Meanwhile, paleomethylome profiles did cluster strongly by their laboratories of origin. Using larger data volumes, minimizing technical noise and/or using alternative protocols may be necessary for capturing subtle environment‐related biological signals from paleomethylomes.

Abstract This study re-examines the linguistic phylogeny of the South Caucasian linguistic family (aka the Kartvelian linguistic family) and attempts to identify its Urheimat. We apply Bayesian phylogenetics to infer a dated phylogeny of the South Caucasian languages. We infer the Urheimat and the reasons for the split of the Kartvelian languages by taking into consideration (1) the past distribution ranges of wildlife elements whose names can be traced back to proto-Kartvelian roots, (2) the distribution ranges of past cultures and (3) the genetic variations of past and extant human populations. Our best-fit Bayesian phylogenetic model is in agreement with the widely accepted topology suggested by previous studies. However, in contrast to these studies, our model suggests earlier mean split dates, according to which the divergence between Svan and Karto-Zan occurred in the early Copper Age, while Georgian and Zan diverged in the early Iron Age. The split of Zan into Megrelian and Laz is widely attributed to the spread of Georgian and/or Georgian speakers in the seventh-eighth centuries CE. Our analyses place the Kartvelian Urheimat in an area that largely intersects the Colchis glacial refugium in the South Caucasus. The divergence of Kartvelian languages is strongly associated with differences in the rate of technological expansions in relation to landscape heterogeneity, as well as the emergence of state-run communities. Neolithic societies could not colonize dense forests, whereas Copper Age societies made limited progress in this regard, but not to the same degree of success achieved by Bronze and Iron Age societies. The paper also discusses the importance of glacial refugia in laying the foundation for linguistic families and where Indo-European languages might have originated.

A major challenge in zooarchaeology is to morphologically distinguish closely related species’ remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species’ reference genomes will only apply when reference nuclear genomes of comparable quality are available, and may still fail when coverages are low. Here, we propose an alternative method, MTaxi, that uses highly accessible mitochondrial DNA (mtDNA) to distinguish between pairs of closely related species from ancient DNA sequences. MTaxi utilises mtDNA transversion-type substitutions between pairs of candidate species, assigns reads to either species, and performs a binomial test to determine the sample taxon. We tested MTaxi on sheep/goat and horse/donkey data, between which zooarchaeological classification can be challenging in ways that epitomise our case. The method performed efficiently on simulated ancient genomes down to 0.3x mitochondrial coverage for both sheep/goat and horse/donkey, with no false positives. Trials on n=18 ancient sheep/goat samples and n=10 horse/donkey samples of known species identity also yielded 100% accuracy. Overall, MTaxi provides a straightforward approach to classify closely related species that are difficult to distinguish through zooarchaeological methods using low coverage aDNA data, especially when similar quality reference genomes are unavailable. MTaxi is freely available at https://github.com/goztag/MTaxi.

Yurtman, Özer, Yüncü et al. provide an ancient DNA data set to demonstrate the impact of human activity on the demographic history of domestic sheep. The authors demonstrate that there may have been multiple domestication events with notable changes to the gene pool of European and Anatolian sheep since the Neolithic.

To date, ancient genome analyses have been largely confined to the study of single nucleotide polymorphisms (SNPs). Copy number variants (CNVs) are a major contributor of disease and of evolutionary adaptation, but identifying CNVs in ancient shotgun-sequenced genomes is hampered by typical low genome coverage (1 kbps with F-scores >0.75 at ≥1×, and distinguish between heterozygous and homozygous states. We used CONGA to genotype 10,002 outgroup-ascertained deletions across a heterogenous set of 71 ancient human genomes spanning the last 50,000 years, produced using variable experimental protocols. A fraction of these (21/71) display divergent deletion profiles unrelated to their population origin, but attributable to technical factors such as coverage and read length. The majority of the sample (50/71), despite originating from nine different laboratories and having coverages ranging from 0.44×-26× (median 4×) and average read lengths 52-121 bps (median 69), exhibit coherent deletion frequencies. Across these 50 genomes, inter-individual genetic diversity measured using SNPs and CONGA-genotyped deletions are highly correlated. CONGA-genotyped deletions also display purifying selection signatures, as expected. CONGA thus paves the way for systematic CNV analyses in ancient genomes, despite the technical challenges posed by low and variable genome coverage.