High-coverage Genome Sequencing Research Articles

Investigation of RNA-binding protein NOVA1 in silico: Comparison of the modern human V197 with the archaic I197 variant present in Neanderthals

By comparing the high-coverage archaic genome sequences to those of modern humans, specific genetic differences have been identified. For example, a human-specific substitution has been found in neuro-oncological ventral antigen 1 (NOVA1) – an RNA-binding protein that regulates the alternative splicing of neuronal pre-mRNA. The amino acid substitution results in an isoleucine-to-valine change at position 197 in NOVA1 (archaic: I197, modern human: V197). Previous studies have utilised gene editing technology to compare the archaic and modern human forms of NOVA1 in cortical organoids, however, the structural and molecular details require further investigation. Using an in silico approach, the modern human (WT) and archaic (V197I) structures of NOVA1 were generated. Moreover, the structure of NOVA1 containing a glycine-to-valine substitution at position 68 (G68V), which occurs at the RNA-binding interface, was examined for comparison. Protein-RNA docking was subsequently performed to model the interaction of NOVA1 variants with RNA and the complexes were evaluated further using classical molecular dynamics (MD) simulations. Based on the MM-PBSA analysis, the binding free energies were similar between the WT (−956.8 ± 32.6 kcal/mol), V197I (−975.4 ± 65.6 kcal/mol), and G68V (−946.7 ± 34.3 kcal/mol) complexes. The findings highlight the binding and stability of protein-RNA complexes with only modest structural changes observed in the archaic and G68V variants compared to the WT NOVA1 protein. Further clarification is required to enhance our understanding of the impact of NOVA1 mutations on alternative splicing and disease development. In particular, delineating the effect of multiple mutations in the NOVA1 gene is of importance.

Genome resequencing and genome-wide polymorphisms in mosquito vectors Aedes aegypti and Aedes albopictus from south India

Aedes aegypti and Aedes albopictus mosquitoes spread major vector-borne viral diseases in tropical and sub-tropical regions of the globe. In this study, we sequenced the genome of Indian Ae. aegypti and Ae. albopictus and mapped to their reference genomes. Comparative genomics were performed between our strain and the reference strains. A total of 14,416,484 single nucleotide polymorphisms (SNPs) and 156,487 insertions and deletions (InDels) were found in Ae. aegypti, and 28,940,433 SNPs and 188,987 InDels in Ae. albopictus. Particular emphasis was given to gene families involved in mosquito digestion, development, and innate immunity, which could be putative candidates for vector control. Serine protease cascades and their inhibitors called serpins, play a central role in these processes. We extracted high-impact variants in genes associated with serine proteases and serpins. This study reports for the first time a high coverage genome sequence data of an Indian Ae. albopictus mosquito. The results from this study will provide insights into Indian Aedes specific polymorphisms and the evolution of immune related genes in mosquitoes, which can serve as a resource for future comparative genomics and those pursuing the development of targeted biopesticides for effective mosquito control strategies.

Genomic analysis of a novel Neanderthal from Mezmaiskaya Cave provides insights into the genetic relationships of Middle Palaeolithic populations

The Mezmaiskaya cave is located on the North Caucasus near the border that divides Europe and Asia. Previously, fossil remains for two Neanderthals were reported from Mezmaiskaya Cave. A tooth from the third archaic hominin specimen (Mezmaiskaya 3) was retrieved from layer 3 in Mezmaiskaya Cave. We performed genome sequencing of Mezmaiskaya 3. Analysis of partial nuclear genome sequence revealed that it belongs to a Homo sapiens neanderthalensis female. Based on a high-coverage mitochondrial genome sequence, we demonstrated that the relationships of Mezmaiskaya 3 to Mezmaiskaya 1 and Stajnia S5000 individuals were closer than those to other Neanderthals. Our data demonstrate the close genetic connections between the early Middle Palaeolithic Neanderthals that were replaced by genetically distant later group in the same geographic areas. Based on mitochondrial DNA (mtDNA) data, we suggest that Mezmaiskaya 3 was the latest Neanderthal individual from the early Neanderthal’s branches. We proposed a hierarchical nomenclature for the mtDNA haplogroups of Neanderthals. In addition, we retrieved ancestral mtDNA mutations in presumably functional sites fixed in the Neanderthal clades, and also provided the first data showing mtDNA heteroplasmy in Neanderthal specimen.

Genetic predisposition to cancer across people of different ancestries in Qatar: a population-based, cohort study.

Disparities in the genetic risk of cancer among various ancestry groups and populations remain poorly defined. This challenge is even more acute for Middle Eastern populations, where the paucity of genomic data could affect the clinical potential of cancer genetic risk profiling. We used data from the phase 1 cohort of the Qatar Genome Programme to investigate genetic variation in cancer-susceptibility genes in the Qatari population. The Qatar Genome Programme generated high-coverage genome sequencing on DNA samples collected from 6142 native Qataris, stratified into six distinct ancestry groups: general Arab, Persian, Arabian Peninsula, Admixture Arab, African, and South Asian. In this population-based, cohort study, we evaluated the performance of polygenic risk scores for the most common cancers in Qatar (breast, prostate, and colorectal cancers). Polygenic risk scores were trained in The Cancer Genome Atlas (TCGA) dataset, and their distributions were subsequently applied to the six different genetic ancestry groups of the Qatari population. Rare deleterious variants within 1218 cancer susceptibility genes were analysed, and their clinical pathogenicity was assessed by ClinVar and the CharGer computational tools. The cohort included in this study was recruited by the Qatar Biobank between Dec 11, 2012, and June 9, 2016. The initial dataset comprised 6218 cohort participants, and whole genome sequencing quality control filtering led to a final dataset of 6142 samples. Polygenic risk score analyses of the most common cancers in Qatar showed significant differences between the six ancestry groups (p<0·0001). Qataris with Arabian Peninsula ancestry showed the lowest polygenic risk score mean for colorectal cancer (-0·41), and those of African ancestry showed the highest average for prostate cancer (0·85). Cancer-gene rare variant analysis identified 76 Qataris (1·2% of 6142 individuals in the Qatar Genome Programme cohort) carrying ClinVar pathogenic or likely pathogenic variants in clinically actionable cancer genes. Variant analysis using CharGer identified 195 individuals carriers (3·17% of the cohort). Breast cancer pathogenic variants were over-represented in Qataris of Persian origin (22 [56·4%] of 39 BRCA1/BRCA2 variant carriers) and completely absent in those of Arabian Peninsula origin. We observed a high degree of heterogeneity for cancer predisposition genes and polygenic risk scores across ancestries in this population from Qatar. Stratification systems could be considered for the implementation of national cancer preventive medicine programmes. Qatar Foundation.

Emergence of Novel SARS-CoV-2 variants in India: second wave

Globally South-East Asia reported 40% of SARS-CoV-2 infected cases in the fourth week of April 2021. It continued to show an increase with India accounting for 50% of cases worldwide and 30% of global deaths. Genomic surveillance should continue at a rapid pace because of the continuously evolving nature of the virus. The time period of sample collection from the Global Initiative on Sharing All Influenza Data database was concurrent with the surge in new cases seen in the Indian subcontinent. 7,415 sequences were downloaded from Global Initiative on Sharing All Influenza Data between January and April 2021; out of which 4,411 were high coverage genome sequences and were considered for analysis. Phylogenetic analysis were carried out using Nextstrain. 21A or B.1.617 or delta was the most prevalent lineage in India accounting for 67.7% of the genomes. Next important clades were 20A, 20B and 20I accounting for 23.6%, 11.8% and 12.1% respectively collected between January 2021 and April 2021. The remaining sequences were assigned to clade 20H, 20J, 20D, 20C, 20G,20E,19A and 19B.The spike mutation frequencies of L452R, E484Q and P681R in Indian state of Maharashtra were 62.4%, 66.5% and 61.5% respectively. Two unique N-terminal domain deletion of spike protein were found at position 67 and 68. The phylogenomics of the delta variant or 21A emerged in neighboring Asian countries of Thailand, Bangladesh, Indonesia and Japan. We analyzed the SARS-CoV-2 genomes from India for mutation characterization of the spike glycoprotein and the nucleocapsid protein.

Negative linkage disequilibrium between amino acid changing variants reveals interference among deleterious mutations in the human genome.

Evolutionary forces like Hill-Robertson interference and negative epistasis can lead to deleterious mutations being found on distinct haplotypes. However, the extent to which these forces depend on the selection and dominance coefficients of deleterious mutations and shape genome-wide patterns of linkage disequilibrium (LD) in natural populations with complex demographic histories has not been tested. In this study, we first used forward-in-time simulations to predict how negative selection impacts LD. Under models where deleterious mutations have additive effects on fitness, deleterious variants less than 10 kb apart tend to be carried on different haplotypes relative to pairs of synonymous SNPs. In contrast, for recessive mutations, there is no consistent ordering of how selection coefficients affect LD decay, due to the complex interplay of different evolutionary effects. We then examined empirical data of modern humans from the 1000 Genomes Project. LD between derived alleles at nonsynonymous SNPs is lower compared to pairs of derived synonymous variants, suggesting that nonsynonymous derived alleles tend to occur on different haplotypes more than synonymous variants. This result holds when controlling for potential confounding factors by matching SNPs for frequency in the sample (allele count), physical distance, magnitude of background selection, and genetic distance between pairs of variants. Lastly, we introduce a new statistic HR(j) which allows us to detect interference using unphased genotypes. Application of this approach to high-coverage human genome sequences confirms our finding that nonsynonymous derived alleles tend to be located on different haplotypes more often than are synonymous derived alleles. Our findings suggest that interference may play a pervasive role in shaping patterns of LD between deleterious variants in the human genome, and consequently influences genome-wide patterns of LD.

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.

Differences in local population history at the finest level: the case of the Estonian population

Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10–15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.

Phenome-Genome Profiling of Single Bacterial Cell by Raman-Activated Gravity-Driven Encapsulation and Sequencing.

The small size and low DNA amount of bacterial cells have hindered establishing phenome-genome links in a precisely indexed, one-cell-per-reaction manner. Here, Raman-Activated Gravity-driven single-cell Encapsulation and Sequencing (RAGE-Seq) is presented, where individual cells are phenotypically screened via single-cell Raman spectra (SCRS) in an aquatic, vitality-preserving environment, then the cell with targeted SCRS is precisely packaged in a picoliter microdroplet and readily exported in a precisely indexed, "one-cell-one-tube" manner. Such integration of microdroplet encapsulation to Raman-activated sorting ensures high-coverage one-cell genome sequencing or cultivation that is directly linked to metabolic phenotype. For clinical Escherichia coli isolates, genome assemblies derived from precisely one cell via RAGE-Seq consistently reach >95% coverage. Moreover, directly from a urine sample of urogenital tract infection, metabolic-activity-based antimicrobial susceptibility phenotypes and genome sequence of 99.5% coverage are obtained simultaneously from precisely one cell. This single-cell global mutation map corroborates resistance phenotype and genotype, and unveils epidemiological features with high specificity and sensitivity. The ability to profile and correlate bacterial metabolic phenome and high-quality genome sequences at one-cell resolution suggests broad application of RAGE-Seq.

A structural variation reference for medical and population genetics

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25–29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Neandertal DNA in Africans

Sophisticated analyses of current human populations compared to a high-coverage Neandertal genome sequence indicate that, contrary to the previous consensus, African genomes carry a small but significant amount of Neandertal-specific DNA. This indicates back-migration into Africa of modern humans (carrying some Neandertal sequences) and underlines the complexity of ancient human migrations.

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.

Selective sweeps on novel and introgressed variation shape mimicry loci in a butterfly adaptive radiation.

Natural selection leaves distinct signatures in the genome that can reveal the targets and history of adaptive evolution. By analysing high-coverage genome sequence data from 4 major colour pattern loci sampled from nearly 600 individuals in 53 populations, we show pervasive selection on wing patterns in the Heliconius adaptive radiation. The strongest signatures correspond to loci with the greatest phenotypic effects, consistent with visual selection by predators, and are found in colour patterns with geographically restricted distributions. These recent sweeps are similar between co-mimics and indicate colour pattern turn-over events despite strong stabilising selection. Using simulations, we compare sweep signatures expected under classic hard sweeps with those resulting from adaptive introgression, an important aspect of mimicry evolution in Heliconius butterflies. Simulated recipient populations show a distinct ‘volcano’ pattern with peaks of increased genetic diversity around the selected target, characteristic of sweeps of introgressed variation and consistent with diversity patterns found in some populations. Our genomic data reveal a surprisingly dynamic history of colour pattern selection and co-evolution in this adaptive radiation.

Reconstructing Denisovan Anatomy Using DNA Methylation Maps.

Denisovans are an extinct group of humans whose morphology remains unknown. Here, we present a method for reconstructing skeletal morphology using DNA methylation patterns. Our method is based on linking unidirectional methylation changes to loss-of-function phenotypes. We tested performance by reconstructing Neanderthal and chimpanzee skeletal morphologies and obtained >85% precision in identifying divergent traits. We then applied this method to the Denisovan and offer a putative morphological profile. We suggest that Denisovans likely shared with Neanderthals traits such as an elongated face and a wide pelvis. We also identify Denisovan-derived changes, such as an increased dental arch and lateral cranial expansion. Our predictions match the only morphologically informative Denisovan bone to date, as well as the Xuchang skull, which was suggested by some to be a Denisovan. We conclude that DNA methylation can be used to reconstruct anatomical features, including some that do not survive in the fossil record.

Conservation genomic analysis reveals ancient introgression and declining levels of genetic diversity in Madagascar\u2019s hibernating dwarf lemurs

Madagascar’s biodiversity is notoriously threatened by deforestation and climate change. Many of these organisms are rare, cryptic, and severely threatened, making population-level sampling unrealistic. Such is the case with Madagascar’s dwarf lemurs (genus Cheirogaleus), the only obligate hibernating primate. We here apply comparative genomic approaches to generate the first genome-wide estimates of genetic diversity within dwarf lemurs. We generate a reference genome for the fat-tailed dwarf lemur, Cheirogaleus medius, and use this resource to facilitate analyses of high-coverage (~30×) genome sequences for wild-caught individuals representing species: C. sp. cf. medius, C. major, C. crossleyi, and C. sibreei. This study represents the largest contribution to date of novel genomic resources for Madagascar’s lemurs. We find concordant phylogenetic relationships among the four lineages of Cheirogaleus across most of the genome, and yet detect a number of discordant genomic regions consistent with ancient admixture. We hypothesized that these regions could have resulted from adaptive introgression related to hibernation, indeed finding that genes associated with hibernation are present, though most significantly, that gene ontology categories relating to transcription are over-represented. We estimate levels of heterozygosity and find particularly low levels in an individual sampled from an isolated population of C. medius that we refer to as C. sp. cf. medius. Results are consistent with a recent decline in effective population size, which is evident across species. Our study highlights the power of comparative genomic analysis for identifying species and populations of conservation concern, as well as for illuminating possible mechanisms of adaptive phenotypic evolution.

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called Linear Allele-Specific Selection InferencE (LASSIE), for estimating the fitness effects of all observed and potential single-nucleotide variants, based on polymorphism data and predictive genomic features. We applied LASSIE to 51 high-coverage genome sequences annotated with 33 genomic features and constructed a map of allele-specific selection coefficients across all protein-coding sequences in the human genome. This map is generally consistent with previous inferences of the bulk distribution of fitness effects but reveals pervasive weak negative selection against synonymous mutations. In addition, the estimated selection coefficients are highly predictive of inherited pathogenic variants and cancer driver mutations, outperforming state-of-the-art variant prioritization methods. By contrasting our estimated model with ultrahigh coverage ExAC exome-sequencing data, we identified 1118 genes under unusually strong negative selection, which tend to be exclusively expressed in the central nervous system or associated with autism spectrum disorder, as well as 773 genes under unusually weak selection, which tend to be associated with metabolism. This combination of classical population genetic theory with modern machine-learning and large-scale genomic data is a powerful paradigm for the study of both human evolution and disease.

Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing.

SummaryTumour evolution results in progressive cancer phenotypes such as metastatic spread and treatment resistance. To better treat cancers, we must characterize tumour evolution and the genetic events that confer progressive phenotypes. This is facilitated by high coverage genome or exome sequencing. However, the best approach by which, or indeed whether, these data can be used to accurately model and interpret underlying evolutionary dynamics is yet to be confirmed. Establishing this requires sequencing data from appropriately heterogeneous tumours in which the exact trajectory and combination of events occurring throughout its evolution are known. We therefore developed HeteroGenesis: a tool to generate realistically evolved tumour genomes, which can be sequenced using weighted-Wessim (w-Wessim), an in silico exome sequencing tool that we have adapted from previous methods. HeteroGenesis simulates more complex and realistic heterogeneous tumour genomes than existing methods, can model different evolutionary dynamics, and enables the creation of multi-region and longitudinal data.Availability and implementationHeteroGenesis and w-Wessim are freely available under the GNU General Public Licence from https://github.com/GeorgetteTanner, implemented in Python and supported on linux and MS Windows.Supplementary information Supplementary data are available at Bioinformatics online.

Comparative genomics of 84 Pectobacterium genomes reveals the variations related to a pathogenic lifestyle

BackgroundPectobacterium spp. are necrotrophic bacterial plant pathogens of the family Pectobacteriaceae, responsible for a wide spectrum of diseases of important crops and ornamental plants including soft rot, blackleg, and stem wilt. P. carotovorum is a genetically heterogeneous species consisting of three valid subspecies, P. carotovorum subsp. brasiliense (Pcb), P. carotovorum subsp. carotovorum (Pcc), and P. carotovorum subsp. odoriferum (Pco).ResultsThirty-two P. carotovorum strains had their whole genomes sequenced, including the first complete genome of Pco and another circular genome of Pcb, as well as the high-coverage genome sequences for 30 additional strains covering Pcc, Pcb, and Pco. In combination with 52 other publicly available genome sequences, the comparative genomics study of P. carotovorum and other four closely related species P. polaris, P. parmentieri, P. atrosepticum, and Candidatus P. maceratum was conducted focusing on CRISPR-Cas defense systems and pathogenicity determinants. Our analysis identified two CRISPR-Cas types (I-F and I-E) in Pectobacterium, as well as another I-C type in Dickeya that is not found in Pectobacterium. The core pathogenicity factors (e.g., plant cell wall-degrading enzymes) were highly conserved, whereas some factors (e.g., flagellin, siderophores, polysaccharides, protein secretion systems, and regulatory factors) were varied among these species and/or subspecies. Notably, a novel type of T6SS as well as the sorbitol metabolizing srl operon was identified to be specific to Pco in Pectobacterium.ConclusionsThis study not only advances the available knowledge about the genetic differentiation of individual subspecies of P. carotovorum, but also delineates the general genetic features of P. carotovorum by comparison with its four closely related species, thereby substantially enriching the extent of information now available for functional genomic investigations about Pectobacterium.

The complete genome sequence of the African buffalo (Syncerus caffer).

BackgroundThe African buffalo (Syncerus caffer) is an important role player in the savannah ecosystem. It has become a species of relevance because of its role as a wildlife maintenance host for an array of infectious and zoonotic diseases some of which include corridor disease, foot-and-mouth disease and bovine tuberculosis. To date, no complete genome sequence for S. caffer had been available for study and the genomes of other species such as the domestic cow (Bos taurus) had been used as a proxy for any genetics analysis conducted on this species. Here, the high coverage genome sequence of the African buffalo (S. caffer) is presented.ResultsA total of 19,765 genes were predicted and 19,296 genes could be successfully annotated to S. caffer while 469 genes remained unannotated. Moreover, in order to extend a detailed annotation of S. caffer, gene clusters were constructed using twelve additional mammalian genomes. The S. caffer genome contains 10,988 gene clusters, of which 62 are shared exclusively between B. taurus and S. caffer.ConclusionsThis study provides a unique genomic perspective for the S. caffer, allowing for the identification of novel variants that may play a role in the natural history and physiological adaptations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3364-0) contains supplementary material, which is available to authorized users.

A High-Coverage Yersinia pestis Genome from a Sixth-Century Justinianic Plague Victim.

The Justinianic Plague, which started in the sixth century and lasted to the mid eighth century, is thought to be the first of three historically documented plague pandemics causing massive casualties. Historical accounts and molecular data suggest the bacterium Yersinia pestis as its etiological agent. Here we present a new high-coverage (17.9-fold) Y. pestis genome obtained from a sixth-century skeleton recovered from a southern German burial site close to Munich. The reconstructed genome enabled the detection of 30 unique substitutions as well as structural differences that have not been previously described. We report indels affecting a lacl family transcription regulator gene as well as nonsynonymous substitutions in the nrdE, fadJ, and pcp genes, that have been suggested as plague virulence determinants or have been shown to be upregulated in different models of plague infection. In addition, we identify 19 false positive substitutions in a previously published lower-coverage Y. pestis genome from another archaeological site of the same time period and geographical region that is otherwise genetically identical to the high-coverage genome sequence reported here, suggesting low-genetic diversity of the plague during the sixth century in rural southern Germany.