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Post by Admin on Jan 18, 2024 12:34:51 GMT
Genetic history of Cambridgeshire before and after the Black Death RUOYUN HUI, CHRISTIANA L. SCHEIB, EUGENIA D’ATANASIO Abstract 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. INTRODUCTION Evidence from ancient DNA (aDNA) continues to increase our understanding of the human past. By linking the genetic profiles to a place and time, it allows us to study population movements (1, 2), genetic relatedness (3–5), infectious diseases (6, 7), and natural selection (8, 9) as they occurred. When combined with historical and archaeological contexts, such information offers a more detailed perspective on life in past societies. aDNA studies centered around broad geographical regions and long time periods have been fundamental in establishing major migration events, population turnovers, or continuity in both prehistory and historic periods, while being less informative about everyday life experience within complex societies. Taking what we call “the whole town approach,” we have studied hundreds of skeletal remains from later medieval (c. 1000–1550 CE) Cambridgeshire (Table 1). They were excavated from burial grounds connected with different social groups: urban and rural parish churchyards, urban charitable institutions, and religious institutions. For historical context, we also included postmedieval burial grounds (c. 1550–1855 CE). Apart from Clopton and Hemingford Grey, all the sites are within a few kilometers of each other (Fig. 1A). www.science.org/doi/10.1126/sciadv.adi5903
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Post by Admin on Jan 19, 2024 15:07:37 GMT
Fig. 1. Sampling locations and genetic ancestry. (A) Sampling locations in Cambridgeshire. (B) Zoomed in map of Cambridge. (C) PC plot of 109 later medieval and postmedieval genomes with coverage >0.1× in context of ancient (Roman and Saxon period) and modern (UK Biobank) references, with PC1 and PC2 accounting for 0.165 and 0.07% of total variance explained, respectively. (D) Supervised Uniform Manifold Approximation and Projection (UMAP) cluster analysis using PiC with modern references based on 5-cM LSAI sharing among modern and 108 ancient genomes, including 80 from later medieval period, with coverage >0.2×. (E) Intensity of maximum PiC scores. (F) Transect of time of correlations between the regional PiC vectors. The “Modern” correlation for East Anglia is shown as the correlation between PiC vectors of East Anglia and Bedfordshire/Hertfordshire. Cambridge during the later medieval period was a middle-sized market town where people from all sections of society crossed paths. After they died, most townspeople were buried in one of the parish cemeteries, including All Saints by the Castle; however, other places of burial existed and increased over time. Toward the end of the 12th century, the Hospital of St John the Evangelist was founded by the townspeople as a charitable institute for the poor, the infirm and the sick. Most of the burials included in this study come from a cemetery for charitable inmates of the Hospital. The 13th century saw the founding of the university and houses of the mendicant orders, including an Augustinian Friary (from which some of our study population are drawn). Apart from the friars, some patrons of the friary were also buried in the cemetery and chapter house of the friary. The first wave of the Second Plague Pandemic (which we hereafter refer to with the commonly used term “Black Death,” although the term was not in use until the 18th century) hit Cambridge in 1349; some of its victims were found in a mass burial of unknown size on Bene’t Street (10). Two parish cemeteries outside Cambridge, Cherry Hinton and Clopton, are within the rural hinterland of the town. Table 1 and table S1 list the archaeological sites covered in this study, the dating of the burials, and the function of the medieval and postmedieval sites. The Black Death and subsequent plague outbreaks had multiple effects on medieval society in England. Its death toll in Europe, estimated at 30 to 65% (11, 12), could have posed selective pressure for better resistance to the plague. Genetic adaptations via the innate (13) and adaptive immune system (14) have been proposed. Although reference bias can pose challenges to detect allele frequency changes due to natural selection (15), a study of 206 aDNA extracts from individuals buried in London and Denmark before, during, and after the Black Death revealed enrichment of immune genes among highly differentiated single-nucleotide variants, suggesting major impact of the pandemic in shaping the disease susceptibility of surviving population (16). Besides genetic susceptibility, it is not clear to what extent social identity modified the morbid and mortal effects of the Black Death. Plague mortality appeared to be selective with respect to frailty (17, 18) caused possibly by factors such as malnutrition, impaired immunocompetence, and others affected by social conditions. For example, the Great Famine of 1315–1322 could have severely affected people of low socioeconomic position. In this sense, health inequality between social groups sets the background for understanding the potential for different experiences through the pandemic. As longer-term consequences of the mortality, it has been argued that the Black Death pandemic initiated or accelerated profound socioeconomic changes, such as increased social mobility, improved quality of life of the laboring population, and technological innovations to increase productivity (19, 20). Together with evidence from osteology, isotopes, and the rich context around the burial grounds, we aim to explore to what extent genetic data might aid the construction of a social history, both in relation to the pandemic and regarding the more stable aspects of later medieval life. RESULTS
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Post by Admin on Jan 20, 2024 23:32:12 GMT
We extracted aDNA and generated whole-genome shotgun sequence data with a mean coverage of 0.228 from a total of 250 later medieval and 25 postmedieval skeletons, retrieving for further analyses 190 genomes at coverage >0.01× (Table 1 and table S1). They form the most extensive bioarchaeological sampling within a focused temporal and geographical range to date. The examined medieval sites represent burials of individuals from different social and cause of death backgrounds, including urban cemeteries of the charitable poor from the Hospital of St. John, All Saints parish cemetery, Augustinian Friary, Bene’t Street plague burial, and rural cemeteries of Cherry Hinton and Clopton (Table 1, Fig. 1A, and the Supplementary Materials). The analyses of the medieval genomes were performed in context of postmedieval genomes from four sites in Cambridgeshire (Table 1) as well as published genomic data of the Late Iron Age/Roman (c. 100 BCE to 400 CE) and Early Saxon periods (c. 400–700 CE) from Cambridgeshire and elsewhere from England (21, 22). Average endogenous human DNA content was 13% and average contamination rate 1.06%, with 209 individuals under 5%. Average damage in the first 5 base pairs (bp) was 8.02% (table S1). A subset of 143 genomes sequenced to >0.05× coverage were imputed to study the changes in phenotypes related to health and lifestyle. The imputed genomes include 109 individuals with coverage >0.1×, which were subsequently used to resolve genetic ancestry, kinship, recent inbreeding, and heterozygosity.
Genetic ancestry The frequencies of mitochondrial DNA (mtDNA) haplogroups in England have remained relatively stable since the Neolithic (table S2). Similarly, principal components analysis (PCA) reveals that all 109 individuals with >0.1× coverage from later medieval Cambridgeshire (Fig. 1, A and B) share their autosomal ancestry with modern northern and western European populations without evidence of migration from more distant regions (Fig. 1C and fig. S1); the same conclusion is supported when projecting pseudohaploid genomes without imputation onto PC space established by modern genomes (figs. S2 to S11). In contrast to genomes from the Roman or Early Saxon periods (21, 22), most later medieval genomes cluster with those from the modern English genomes from the UK Biobank data (Fig. 1C). Individual outliers who, similarly to most Early Saxon period individuals, are placed among modern Dutch and Danish populations, include a few from Cherry Hinton and the Hospital of St John. Two of them (PSN332 from the Hospital and PSN930 from Cherry Hinton) are also outliers in terms of dental enamel 87Sr/86Sr values (PSN332 = 0.7122, PSN930 = 0.7108) (23). These values, particularly for PSN332, are higher than the estimated biosphere 87Sr/86Sr values for the East of England (24), indicating that they did not spend their childhoods in the area local to where they were buried. To study the genetic affinity changes across time at finer geographic resolution, we defined interindividual connections by identifying long [>5 centimorgan (cM)] shared allele intervals (LSAIs) with IBIS (25) and explored the modularity of individual connectedness (PiC) (26) among the historical and modern genomes. Similarly to PCA results, we find that the majority of historical genomes from Cambridgeshire cluster by their connectedness with modern UK Biobank genomes from East England (Fig. 1D and table S3) whereas a small fraction of later medieval and Roman period genomes, which display low LSAI sharing with any population (Fig. 1E), cluster with the UK Biobank donors born in France who also display low levels of LSAI sharing. The Early Saxon period genomes show higher connectedness with Scandinavian genomes, which is also reflected in individual PCA outliers from Cherry Hinton. Overall, we observe regional shifts in individual connectedness over time (Fig. 1F). We observe increasing Danish connectedness in the transition from Roman to Early Saxon period; later, during and after the later medieval period, there is an increase of LSAI sharing with both modern Dutch genomes [mirroring documentary evidence showing the Dutch as the most common late medieval immigrants locally (27, 28)] and genomes from a broader zone of England. Last, we identify a major shift in modern East England toward higher LSAI sharing with Wales and Scotland, clearly reflecting the political and economic integration of recent Britain. Our analyses of individual connectedness in the People of the British Isles (29) data suggest that all later medieval genomes from Cambridgeshire likely draw most of their genetic ancestry broadly from the same sources as present-day central/eastern England population (Fig. 2). Although we are able to distinguish certain regional differences in the modern data with our approach, such as between Cornwall and Devon or between North and South Yorkshire, we observe less resolution in a broad area between Lincolnshire and Surrey where our ancient genomes come from (Fig. 2). This means that even if some of the individuals had come from Kent or Lincolnshire, for example, we would not be able to detect such fine-scale migration patterns among regions within that area.
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Post by Admin on Jan 23, 2024 1:51:31 GMT
Fig. 2. UMAP plot of individual connectedness among modern and ancient genomes from Britain. (A) Density of maximum PiC score values per individual in one of the extracted communities. (B) UMAP coordinates of the medieval and postmedieval genomes (> 0.2× coverage) from Cambridgeshire. Archaeological site codes as shown in Fig. 1. (C) Individual connectedness among modern genomes of the “People of the British Isles” project based on PiC scores of 20 significant communities with more than 10 members extracted from the combined data with the Louvain method (unsupervised cluster analysis). (D) Map showing the color codes by counties for the modern genomes used in the UMAP plot A. (E) UMAP coordinates of the Iron Age/Roman and Saxon period genomes. Changes in genetic ancestry or selective pressure could cause phenotypic changes over time. We analyzed 214 genomes with >0.05× coverage from the Roman period to the 19th century, including previously published data (21, 22, 30), for changes in allele frequency of 113 phenotype informative single-nucleotide polymorphisms (SNPs) related to diet, health, and pigmentation (tables S4 to S6). Of 74 SNPs related to health and diet, only 2 involved in autoimmune diseases reached the adjusted significance threshold in the analysis of variance (ANOVA) statistical tests, showing differences between the medieval and postmedieval periods. One SNP, i.e., rs6822844, is an intronic variant in the KIAA1109/Tenr/IL2/IL21 block and has been identified as a risk factor in several autoimmune diseases, including celiac disease, rheumatoid arthritis and type 1 diabetes (31, 32). The other variant, i.e., the intronic rs1891467 in the TGFB2 gene, has been associated with sarcoidosis (33). We did not find significant allele frequency changes during and after the later medieval period for the 39 SNPs affecting eye, hair, and skin color included in the HIrisPlex-S set (34), which is expected considering the proximity of the later medieval and present-day English in genetic ancestry (Fig. 2).
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Post by Admin on Jan 24, 2024 18:13:03 GMT
Social landscape Kinship and relatedness Although the “kinship” bonds that tie together social groups often go beyond or replace “blood-relationships,” the types and intensity of genetic relatedness among individuals buried in the same locality can be informative of the social structure of the population. To study the probability of genetic relatedness among burials of different social backgrounds we used READ-based estimates (3) of pairwise differences in autosomes and the X chromosome in 171 later medieval genomes with >0.01× coverage. Among individual pairs with >10,000 overlapping SNPs, 21 cases of first- to third-degree relatedness were detected (Fig. 3A and table S7). All kinship pairs detected by READ that involved individuals with >0.1× coverage were confirmed in our analyses with IBIS (25) to share multiple > 7-cM LSAI segments and kinship coefficient > 0.005 (table S7). Expectedly, considering the time gaps, none of the 97 later medieval individuals showed kinship with 463,855 modern UK Biobank individuals by the same threshold. Nine of the 12 tested postmedieval individuals were found to form a total of 20 fourth- to sixth-degree relationships with modern individuals who identify themselves as British, including one born outside of the United Kingdom. Among the later medieval individuals, we detect 12 cases of more distant form of relatedness within the same archaeological site beyond those identified with READ—10 at Cherry Hinton and 2 at All Saints—while none were found at the Hospital or Friary. We found multiple cases (more than 1% of all pairs considered) in the rural Cherry Hinton and urban All Saints parish cemeteries. In contrast, we detected only one pair of relatives, a middle-aged (46 to 59 years old) friar and a female child (second degree). No kinship relations were found at the Hospital, despite the large sample size analyzed. On average, pairwise differences between individuals from the Hospital were found to be greater than those between individuals from other sites (Fig. 3B), highlighting the heterogeneity of the ancestry of individuals entering the Hospital. Fig. 3. Kinship, genetic diversity and inbreeding. (A) Normalized pairwise differences (P0) in autosomal data and X chromosome for later medieval sites with more than five burials. Each individual data point represents a pair of individuals (from a total of 171 individuals with >0.01× coverage tested), the aggregate coverage of which is reflected by the opacity of the color. Boundaries for the first- to third-degree of relatedness for autosomal data were defined as in (3). Error bars with two SEMs are shown for the pairs of first- to third-degree of relatedness only. ** and * correspond to significant differences at P < 0.01 and P < 0.05 by two-tailed t test, respectively. (B) Boxplot of normalized autosomal pairwise differences in four Cambridge medieval sites represented by the largest sample size in this study. Each rectangular data point represents a pairwise comparison of individuals sampled from the same site, normalized (with READ) by the average of all pairwise comparisons made in the pool of all later medieval individuals from Cambridge. The opacity of the rectangular color reflects the aggregate of the coverages of the two individuals. The results of significant (P < 0.01) two-tailed Wilcoxon rank sum test are shown with **. (C) The total lengths of ROH tracks longer than 4 cM in individuals grouped by site, showing highly inbred outliers.
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