Search

The area of the Spanish Pyrenees is particularly interesting for studying the demographic dynamics of European rural areas given its orography, the main traditional rural condition of its population and the reported higher patterns of consanguinity of the region. Previous genetic studies suggest a gradient of genetic continuity of the area in the West to East axis. However, it has been shown that micro-population substructure can be detected when considering high-quality NGS data and using spatial explicit methods. In this work, we have analyzed the genome of 30 individuals sequenced at 40× from five different valleys in the Spanish Eastern Pyrenees (SEP) separated by less than 140 km along a west to east axis. Using haplotype-based methods and spatial analyses, we have been able to detect micro-population substructure within SEP not seen in previous studies. Linkage disequilibrium and autozygosity analyses suggest that the SEP populations show diverse demographic histories. In agreement with these results, demographic modeling by means of ABC-DL identify heterogeneity in their effective population sizes despite of their close geographic proximity, and suggests that the population substructure within SEP could have appeared around 2500 years ago. Overall, these results suggest that each rural population of the Pyrenees could represent a unique entity., (© 2021. The Author(s).)

The Cycladic, the Minoan, and the Helladic (Mycenaean) cultures define the Bronze Age (BA) of Greece. Urbanism, complex social structures, craft and agricultural specialization, and the earliest forms of writing characterize this iconic period. We sequenced six Early to Middle BA whole genomes, along with 11 mitochondrial genomes, sampled from the three BA cultures of the Aegean Sea. The Early BA (EBA) genomes are homogeneous and derive most of their ancestry from Neolithic Aegeans, contrary to earlier hypotheses that the Neolithic-EBA cultural transition was due to massive population turnover. EBA Aegeans were shaped by relatively small-scale migration from East of the Aegean, as evidenced by the Caucasus-related ancestry also detected in Anatolians. In contrast, Middle BA (MBA) individuals of northern Greece differ from EBA populations in showing ∼50% Pontic-Caspian Steppe-related ancestry, dated at ca. 2,600-2,000 BCE. Such gene flow events during the MBA contributed toward shaping present-day Greek genomes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Previous studies indicated existing, albeit limited, genetic-geographic population substructure in the Dutch population based on genome-wide data and a lack of this for mitochondrial SNP based data. Despite the aforementioned studies, Y-chromosomal SNP data from the Netherlands remain scarce and do not cover the territory of the Netherlands well enough to allow a reliable investigation of genetic-geographic population substructure. Here we provide the first substantial dataset of detailed spatial Y-chromosomal haplogroup information in 2085 males collected across the Netherlands and supplemented with previously published data from northern Belgium. We found Y-chromosomal evidence for genetic-geographic population substructure, and several Y-haplogroups demonstrating significant clinal frequency distributions in different directions. By means of prediction surface maps we could visualize (complex) distribution patterns of individual Y-haplogroups in detail. These results highlight the value of a micro-geographic approach and are of great use for forensic and epidemiological investigations and our understanding of the Dutch population history. Moreover, the previously noted absence of genetic-geographic population substructure in the Netherlands based on mitochondrial DNA in contrast to our Y-chromosome results, hints at different population histories for women and men in the Netherlands.

Correct identification of different human epithelial materials such as from skin, saliva and vaginal origin is relevant in forensic casework as it provides crucial information for crime reconstruction. However, the overlap in human cell type composition between these three epithelial materials provides challenges for their differentiation and identification when using previously proposed human cell biomarkers, while their microbiota composition largely differs. By using validated 16S rRNA gene massively parallel sequencing data from the Human Microbiome Project of 1636 skin, oral and vaginal samples, 50 taxonomy-independent deep learning networks were trained to classify these three tissues. Validation testing was performed in de-novo generated high-throughput 16S rRNA gene sequencing data using the Ion Torrent ™ Personal Genome Machine from 110 test samples: 56 hand skin, 31 saliva and 23 vaginal secretion specimens. Body-site classification accuracy of these test samples was very high as indicated by AUC values of 0.99 for skin, 0.99 for oral, and 1 for vaginal secretion. Misclassifications were limited to 3 (5%) skin samples. Additional forensic validation testing was performed in mock casework samples by de-novo high-throughput sequencing of 19 freshly-prepared samples and 22 samples aged for 1 up to 7.6 years. All of the 19 fresh and 20 (91%) of the 22 aged mock casework samples were correctly tissue-type classified. Moreover, comparing the microbiome results with outcomes from previous human mRNA-based tissue identification testing in the same 16 aged mock casework samples reveals that our microbiome approach performs better in 12 (75%), similarly in 2 (12.5%), and less good in 2 (12.5%) of the samples. Our results demonstrate that this new microbiome approach allows for accurate tissue-type classification of three human epithelial materials of skin, oral and vaginal origin, which is highly relevant for future forensic investigations., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama-Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25-40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10-32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama-Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51-72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.

Determining the time a biological trace was left at a scene of crime reflects a crucial aspect of forensic investigations as - if possible - it would permit testing the sample donor's alibi directly from the trace evidence, helping to link (or not) the DNA-identified sample donor with the crime event. However, reliable and robust methodology is lacking thus far. In this study, we assessed the suitability of mRNA for the purpose of estimating blood deposition time, and its added value relative to melatonin and cortisol, two circadian hormones we previously introduced for this purpose. By analysing 21 candidate mRNA markers in blood samples from 12 individuals collected around the clock at 2h intervals for 36h under real-life, controlled conditions, we identified 11 mRNAs with statistically significant expression rhythms. We then used these 11 significantly rhythmic mRNA markers, with and without melatonin and cortisol also analysed in these samples, to establish statistical models for predicting day/night time categories. We found that although in general mRNA-based estimation of time categories was less accurate than hormone-based estimation, the use of three mRNA markers HSPA1B, MKNK2 and PER3 together with melatonin and cortisol generally enhanced the time prediction accuracy relative to the use of the two hormones alone. Our data best support a model that by using these five molecular biomarkers estimates three time categories, i.e. night/early morning, morning/noon, and afternoon/evening with prediction accuracies expressed as AUC values of 0.88, 0.88, and 0.95, respectively. For the first time, we demonstrate the value of mRNA for blood deposition timing and introduce a statistical model for estimating day/night time categories based on molecular biomarkers, which shall be further validated with additional samples in the future. Moreover, our work provides new leads for molecular approaches on time of death estimation using the significantly rhythmic mRNA markers established here., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)