Machu Picchu originally functioned as a palace within the estate of the Inca emperor Pachacuti between ~1420 and 1532 CE. Before this study, little was known about the people who lived and died there, where they came from or how they were related to the inhabitants of the Inca capital of Cusco. We generated genome-wide data for 34 individuals buried at Machu Picchu who are believed to have been retainers or attendants assigned to serve the Inca royal family, as well as 34 individuals from Cusco for comparative purposes. When the ancient DNA results are contextualized using historical and archaeological data, we conclude that the retainer population at Machu Picchu was highly heterogeneous with individuals exhibiting genetic ancestries associated with groups from throughout the Inca Empire and Amazonia. The results suggest a diverse retainer community at Machu Picchu in which people of different genetic backgrounds lived, reproduced, and were interred together.

In‐solution hybridisation enrichment of genetic variation is a valuable methodology in human paleogenomics. It allows enrichment of endogenous DNA by targeting genetic markers that are comparable between sequencing libraries. Many studies have used the 1240k reagent—which enriches 1,237,207 genome‐wide SNPs—since 2015, though access was restricted. In 2021, Twist Biosciences and Daicel Arbor Biosciences independently released commercial kits that enabled all researchers to perform enrichments for the same 1240 k SNPs. We used the Daicel Arbor Biosciences Prime Plus kit to enrich 132 ancient samples from three continents. We identified a systematic assay bias that increases genetic similarity between enriched samples and that cannot be explained by batch effects. We present the impact of the bias on population genetics inferences (e.g. Principal Components Analysis, ƒ‐statistics) and genetic relatedness (READ). We compare the Prime Plus bias to that previously reported of the legacy 1240k enrichment assay. In ƒ‐statistics, we find that all Prime‐Plus‐generated data exhibit artefactual excess shared drift, such that within‐continent relationships cannot be correctly determined. The bias is more subtle in READ, though interpretation of the results can still be misleading in specific contexts. We expect the bias may affect analyses we have not yet tested. Our observations support previously reported concerns for the integration of different data types in paleogenomics. We also caution that technological solutions to generate 1240k data necessitate a thorough validation process before their adoption in the paleogenomic community.

In-solution hybridization enrichment of genetic markers is a method of choice in paleogenomic studies, where the DNA of interest is generally heavily fragmented and contaminated with environmental DNA, and where the retrieval of genetic data comparable between individuals is challenging. Here, we benchmark the commercial “Twist Ancient DNA” reagent from Twist Biosciences using sequencing libraries from ancient human samples of diverse demographic origin with low to high endogenous DNA content (0.1–44%). For each library, we tested one and two rounds of enrichment and assessed performance compared to deep shotgun sequencing. We find that the “Twist Ancient DNA” assay provides robust enrichment of approximately 1.2M target SNPs without introducing allelic bias that may interfere with downstream population genetics analyses. Additionally, we show that pooling up to 4 sequencing libraries and performing two rounds of enrichment is both reliable and cost-effective for libraries with less than 27% endogenous DNA content. Above 38% endogenous content, a maximum of one round of enrichment is recommended for cost-effectiveness and to preserve library complexity. In conclusion, we provide researchers in the field of human paleogenomics with a comprehensive understanding of the strengths and limitations of different sequencing and enrichment strategies, and our results offer practical guidance for optimizing experimental protocols.

The rulers of the Inka empire conquered approximately 2 million km² of the South American Andes in just under 100 years from 1438–1533 CE. Inside the empire, the elite conducted a systematic resettlement of the many Indigenous peoples in the Andes that had been rapidly colonised. The nature of this resettlement phenomenon is recorded within the Spanish colonial ethnohistorical record. Here we have broadly characterised the resettlement policy, despite the often incomplete and conflicting details in the descriptions. We then review research from multiple disciplines that investigate the empirical reality of the Inka resettlement policy, including stable isotope analysis, intentional cranial deformation morphology, ceramic artefact chemical analyses and genetics. Further, we discuss the benefits and limitations of each discipline for investigating the resettlement policy and emphasise their collective value in an interdisciplinary characterisation of the resettlement policy.

Contamination with exogenous DNA presents a significant challenge in ancient DNA (aDNA) studies of single organisms. Failure to address contamination from microbes, reagents, and present-day sources can impact the interpretation of results. Although field and laboratory protocols exist to limit contamination, there is still a need to accurately distinguish between endogenous and exogenous data computationally. Here, we propose a workflow to reduce exogenous contamination based on a metagenomic classifier. Unlike previous methods that relied exclusively on DNA sequencing reads mapping specificity to a single reference genome to remove contaminating reads, our approach uses Kraken2-based filtering before mapping to the reference genome. Using both simulated and empirical shotgun aDNA data, we show that this workflow presents a simple and efficient method that can be used in a wide range of computational environments—including personal machines. We propose strategies to build specific databases used to profile sequencing data that take into consideration available computational resources and prior knowledge about the target taxa and likely contaminants. Our workflow significantly reduces the overall computational resources required during the mapping process and reduces the total runtime by up to ~94%. The most significant impacts are observed in low endogenous samples. Importantly, contaminants that would map to the reference are filtered out using our strategy, reducing false positive alignments. We also show that our method results in a negligible loss of endogenous data with no measurable impact on downstream population genetics analyses.

In-solution hybridisation enrichment of genetic markers is a method of choice in paleogenomic studies, where the DNA of interest is generally heavily fragmented and contaminated with environmental DNA, and where the retrieval of genetic data comparable between individuals is challenging. Here, we benchmarked the commercial “Twist Ancient DNA” reagent from Twist Biosciences using sequencing libraries from ancestrally diverse ancient human samples with low to high endogenous DNA content (0.1–44%). For each library, we tested one and two rounds of enrichment, and assessed performance compared to deep shotgun sequencing. We find that the “Twist Ancient DNA” assay provides robust enrichment of ∼1.2M target SNPs without introducing allelic bias that may interfere with downstream population genetics analyses. Additionally, we show that pooling up to 4 sequencing libraries and performing two rounds of enrichment is both reliable and cost-effective for libraries with less than 27% endogenous DNA content. Above 38% endogenous content, a maximum of one round of enrichment is recommended for cost-effectiveness and to preserve library complexity. In conclusion, we provide researchers in the field of human paleogenomics with a comprehensive understanding of the strengths and limitations of different sequencing and enrichment strategies, and our results offer practical guidance for optimising experimental protocols.