Investigating the genetic diversity, population structure and archaic admixture history in worldwide human populations using high-coverage genomes

I present the analysis on 929 high-coverage (>30x) genomes from the Human Genome Diversity Project (HGDP) panel, a collection of cell lines from 54 populations across the world. Some data processing steps were necessary for downstream analysis, including lifting over resources on a different reference genome assembly, annotating the genome, and statistical phasing. Genome-wide genetic diversity conforms with previous studies using SNP arrays and microsatellites, yet haplotype information reveals fine scale structures and recent demographic history that vary between populations. This dataset also provides a valuable opportunity to explore the diversity and distribution of archaic segments in modern human populations. I implemented a hidden Markov model to detect such segments, based on patterns of allele-sharing with sequenced archaic genomes and a sub-Saharan African control panel. I also compared several variants of the model and different training methods using simulated data. Applying the model on the HGDP dataset using two Neanderthal genomes and one Denisova genome, I detected variations in the level of archaic ancestry across continental regions, populations, and individuals within each population. I further compared Neanderthal and Denisovan segments regarding their lengths, genomic distribution, divergence to the archaic genomes, nucleotide diversity, and haplotype networks to shed light on the structure of the admixture events. Neanderthal segments from all non-African populations appear largely homogeneous after accounting for the recent demographic history of modern human populations, which is consistent with a single admixture event that happened before they diverged from each other. In contrast, a distinct separation exists between Denisovan haplotypes recovered from Oceania and those from East/South Asia, whilst the complicated structure in the latter cannot be explained by a single source of gene flow. Therefore I propose that more than one episode of admixture with different Denisova groups occurred in the ancestral population of present-day East Asian, South Asian and American populations after the separation from the ancestors of present-day Oceanians, and that a separate admixture event occurred between the ancestors of Oceanians and the Denisova population.Gates Cambridg

Evaluating genotype imputation pipeline for ultra-low coverage ancient genomes

Funder: Sapienza Università di RomaAbstract: 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

Detecting archaic introgression using an unadmixed outgroup.

Human populations outside of Africa have experienced at least two bouts of introgression from archaic humans, from Neanderthals and Denisovans. In Papuans there is prior evidence of both these introgressions. Here we present a new approach to detect segments of individual genomes of archaic origin without using an archaic reference genome. The approach is based on a hidden Markov model that identifies genomic regions with a high density of single nucleotide variants (SNVs) not seen in unadmixed populations. We show using simulations that this provides a powerful approach to identifying segments of archaic introgression with a low rate of false detection, given data from a suitable outgroup population is available, without the archaic introgression but containing a majority of the variation that arose since initial separation from the archaic lineage. Furthermore our approach is able to infer admixture proportions and the times both of admixture and of initial divergence between the human and archaic populations. We apply the model to detect archaic introgression in 89 Papuans and show how the identified segments can be assigned to likely Neanderthal or Denisovan origin. We report more Denisovan admixture than previous studies and find a shift in size distribution of fragments of Neanderthal and Denisovan origin that is compatible with a difference in admixture time. Furthermore, we identify small amounts of Denisova ancestry in South East Asians and South Asians

Genetic history of Cambridgeshire before and after the Black Death.

The extent of the devastation of the Black Death pandemic (1346-1353) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at the local scale. Here, we report 275 ancient genomes, including 109 with coverage >0.1×, from later medieval and postmedieval Cambridgeshire of individuals buried before and after the Black Death. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death

Genomic analyses of hair from Ludwig van Beethoven

Ludwig van Beethoven (1770–1827) remains among the most influential and popular classical music composers. Health problems significantly impacted his career as a composer and pianist, including progressive hearing loss, recurring gastrointestinal complaints, and liver disease. In 1802, Beethoven requested that following his death, his disease be described and made public. Medical biographers have since proposed numerous hypotheses, including many substantially heritable conditions. Here we attempt a genomic analysis of Beethoven in order to elucidate potential underlying genetic and infectious causes of his illnesses. We incorporated improvements in ancient DNA methods into existing protocols for ancient hair samples, enabling the sequencing of high-coverage genomes from small quantities of historical hair. We analyzed eight independently sourced locks of hair attributed to Beethoven, five of which originated from a single European male. We deemed these matching samples to be almost certainly authentic and sequenced Beethoven\u27s genome to 24-fold genomic coverage. Although we could not identify a genetic explanation for Beethoven\u27s hearing disorder or gastrointestinal problems, we found that Beethoven had a genetic predisposition for liver disease. Metagenomic analyses revealed furthermore that Beethoven had a hepatitis B infection during at least the months prior to his death. Together with the genetic predisposition and his broadly accepted alcohol consumption, these present plausible explanations for Beethoven\u27s severe liver disease, which culminated in his death. Unexpectedly, an analysis of Y chromosomes sequenced from five living members of the Van Beethoven patrilineage revealed the occurrence of an extra-pair paternity event in Ludwig van Beethoven\u27s patrilineal ancestry

Insights into human genetic variation and population history from 929 diverse genomes.

Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented common genetic variation private to southern Africa, central Africa, Oceania, and the Americas, but an absence of such variants fixed between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the past 10,000 years, and a contrast between single Neanderthal but multiple Denisovan source populations contributing to present-day human populations.Wellcome grants 098051 and 206194, and S.A.M. and R.D. also by Wellcome grant 207492. A.B. and P.S. were supported by the Francis Crick Institute (FC001595) which receives its core funding from Cancer Research UK, the UK Medical Research Council and the Wellcome Trust. P.S. was also supported by the European Research Council (grant no. 852558) and the Wellcome Trust (217223/Z/19/Z). R.H. was supported by a Gates Cambridge scholarship. P.H. was supported by Estonian Research Council Grant PUT1036. D.R. is an Investigator of the Howard Hughes Medical Institute

Pathways to the medieval hospital : Collective osteobiographies of poverty and charity

Medieval hospitals were founded to provide charity, but poverty and infirmity were broad and socially determined categories and little is known about the residents of these institutions and the pathways that led them there. Combining skeletal, isotopic and genetic data, the authors weave a collective biography of individuals buried at the Hospital of St John the Evangelist, Cambridge. By starting with the physical remains, rather than historical expectations, they demonstrate the varied life courses of those who were ultimately buried in the hospital's cemetery, illustrating the diverse faces of medieval poverty and institutional notions of charity. The findings highlight the value of collective osteobiography when reconstructing the social landscapes of the past

Evaluating genotype imputation pipeline for ultra-low coverage ancient genomes

Funder: Sapienza Università di RomaAbstract: 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

Genetic history of Cambridgeshire before and after the Black Death

The extent of the devastation of the Black Death pandemic (1346-53) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at local scale. Here we report 275 new ancient genomes, including 109 with coverage >0.1x, from later medieval and post-medieval Cambridgeshire of individuals buried before and after the Black Death. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death

Transform based spatio-temporal descriptors for human action recognition

Classic transformation methods have been widely and efficiently used in image processing areas, such as image de-noising, image segmentation, feature detection, and compression. Based on their compact signal and image representation ability, we apply the transform based techniques on the video recognition area to extract discriminative information from each given video sequence, and use the transformed coefficients as descriptors for representing and recognizing human actions in video sequences. We validate our proposed methods on the KTH and the Hollywood datasets, which have been extensively studied by a lot of researchers. The proposed descriptors, especially the wavelet transform based descriptor, yield promising results on action recognition. (C) 2010 Elsevier B.V. All rights reserved