Neolithic and Medieval virus genomes reveal complex evolution of Hepatitis B
Abstract
The hepatitis B virus (HBV) is one of the most widespread human pathogens known today, yet its origin and evolutionary history are still unclear and controversial. Here, we report the analysis of three ancient HBV genomes recovered from human skeletons found at three different archaeological sites in Germany. We reconstructed two Neolithic and one medieval HBV genomes by de novo assembly from shotgun DNA sequencing data. Additionally, we observed HBV-specific peptides using paleo-proteomics. Our results show that HBV circulates in the European population for at least 7000 years. The Neolithic HBV genomes show a high genomic similarity to each other. In a phylogenetic network, they do not group with any human-associated HBV genome and are most closely related to those infecting African non-human primates. These ancient virus forms appear to represent distinct lineages that have no close relatives today and possibly went extinct. Our results reveal the great potential of ancient DNA from human skeletons in order to study the long-time evolution of blood borne viruses.
Data availability
Raw sequence read files have been deposited at the European Nucleotide Archive under accession no. PRJEB24921
Article and author information
Author details
Funding
European Research Council (APGREID)
- Johannes Krause
Deutsche Forschungsgemeinschaft (Al 287-7-1)
- Kurt W Alt
Deutsche Forschungsgemeinschaft (Me 3245/1-1)
- Harald Meller
Collaborative Research Center (1266)
- Ben Krause-Kyora
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Stephen Locarnini, Doherty Institute, Australia
Ethics
Human subjects: Our human remains used are prehistoric European specimens. No consent from them can be required. No decedent groups claim responsibility or ancestry to those people.
Version history
- Received: March 14, 2018
- Accepted: May 9, 2018
- Accepted Manuscript published: May 10, 2018 (version 1)
- Version of Record published: June 19, 2018 (version 2)
Copyright
© 2018, Krause-Kyora et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 6,031
- views
-
- 906
- downloads
-
- 102
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Genetics and Genomics
LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.
-
- Evolutionary Biology
- Genetics and Genomics
Copy number variation in large gene families is well characterized for plant resistance genes, but similar studies are rare in animals. The zebrafish (Danio rerio) has hundreds of NLR immune genes, making this species ideal for studying this phenomenon. By sequencing 93 zebrafish from multiple wild and laboratory populations, we identified a total of 1513 NLRs, many more than the previously known 400. Approximately half of those are present in all wild populations, but only 4% were found in 80% or more of the individual fish. Wild fish have up to two times as many NLRs per individual and up to four times as many NLRs per population than laboratory strains. In contrast to the massive variability of gene copies, nucleotide diversity in zebrafish NLR genes is very low: around half of the copies are monomorphic and the remaining ones have very few polymorphisms, likely a signature of purifying selection.