Biology subjects

Renaud, G.

Publications and source records attributed to Renaud, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Ancient Reconstructed Proteins: A Framework for Resurrecting Protein Structures from Million-Year-Old Metagenomes

DNA sequences derived from ancient samples provide insights into human history, paleoenvironments, and evolutionary biology. Advances in laboratory techniques and computational tools have established ancient DNA research as a distinct field. However, current analyses focus mainly on the DNA level, while the protein space remains under-explored. Recent progress in the de novo assembly of ancient metagenomes and the availability of protein structure prediction tools, such as AlphaFold 2, enable the reconstruction of protein structures from these degraded sequences. Here, we present a computational framework to assemble contigs, evaluate their authenticity as ancient sequences, predict open reading frames, and fold ancient protein structures directly from highly damaged metagenomic data. Applying this pipeline to two-million-year-old datasets from the Kap Kobenhavn Formation, we successfully rescued ancient proteins involved in methane metabolism. By generating structural models with AlphaFold 2 and comparing them to modern predicted reference structures, we demonstrate that these ancient proteins can be reconstructed and aligned with high confidence. We showcase this by analyzing an archaeal V/A-type ATP synthase protein recovered from the 2M-year-old Greenlandic data. Ultimately, our work proves that ancient proteins can be reliably recovered from highly degraded palaeogenomic material, establishing a new computational avenue for evolutionary and biochemical research.

evolutionary biology↗

bioRxiv2025

CHARON: Estimating the drift time and the number of individuals in environmental DNA with diploid individuals

Environmental DNA (eDNA) offers a promising avenue for reconstructing the genetic diversity and demographic history of ancient populations. However, the analysis of eDNA from humans or forensic DNA, presents significant challenges, including low coverage, DNA degradation, and the uncertainty of the number of individuals contributing to a sample. This study introduces CHARON, a novel statistical method for jointly estimating the number of individuals and drift times between a human eDNA or forensic sample and a given population with known allele frequencies. We validate our method through simulations and synthetic empirical data and show that we can reliably estimate the number of individuals up to 8 at a coverage between 2X and 4X. Our method can also pinpoint the most likely population of origin for eDNA or forensic samples. This work provides a tool for the application of human eDNA in evolutionary and forensic studies and an implementation is available here: https://github.com/Jan-van-Waaij/Charon

evolutionary biology↗

bioRxiv2025

AdDeam: A Fast and Scalable Tool for Estimating and Clustering Reference-Level Damage Profiles

MotivationDNA damage patterns, such as increased frequencies of C[->]T and G[->]A substitutions at fragment ends, are widely used in ancient DNA studies to assess authenticity and detect contamination. In metagenomic studies, fragments can be mapped against multiple references or de novo assembled contigs to identify those likely to be ancient. Generating and comparing damage profiles, however, can be both tedious and time-consuming. Although tools exist for estimating damage in single reference genomes and metagenomic datasets, none efficiently cluster damage patterns. ResultsTo address this methodological gap, we developed AdDeam, a tool that combines rapid damage estimation with clustering for streamlined analyses and easy identification of potential contaminants or outliers. Our tool takes aligned aDNA fragments from various samples or contigs as input, computes damage patterns, clusters them and outputs representative damage profiles per cluster, a probability of each sample of pertaining to a cluster as well as a PCA of the damage patterns for each sample for fast visualisation. We evaluated AdDeam on both simulated and empirical datasets. AdDeam effectively distinguishes different damage levels, such as UDG-treated samples, sample-specific damages from specimens of different time periods, and can also distinguish between contigs containing modern or ancient fragments, providing a clear framework for aDNA authentication and facilitating large-scale analyses. Availability and ImplementationAdDeam is publicly available at https://github.com/LouisPwr/AdDeam and can also be installed via Bioconda. It is implemented in Python and C++. All analysis scripts and datasets are available at https://github.com/LouisPwr/AdDeamAnalysis and on Zenodo under: 10.5281/zenodo.15052427.

bioinformatics↗

bioRxiv2024

Ancient genomics support deep divergence between Eastern and Western Mediterranean Indo-European languages

The Indo-European languages are among the most widely spoken in the world, yet their early diversification remains contentious1-5. It is widely accepted that the spread of this language family across Europe from the 5th millennium BP correlates with the expansion and diversification of steppe-related genetic ancestry from the onset of the Bronze Age6,7. However, multiple steppe-derived populations co-existed in Europe during this period, and it remains unclear how these populations diverged and which provided the demographic channels for the ancestral forms of the Italic, Celtic, Greek, and Armenian languages8,9. To investigate the ancestral histories of Indo-European-speaking groups in Southern Europe, we sequenced genomes from 314 ancient individuals from the Mediterranean and surrounding regions, spanning from 5,200 BP to 2,100 BP, and co-analysed these with published genome data. We additionally conducted strontium isotope analyses on 224 of these individuals. We find a deep east-west divide of steppe ancestry in Southern Europe during the Bronze Age. Specifically, we show that the arrival of steppe ancestry in Spain, France, and Italy was mediated by Bell Beaker (BB) populations of Western Europe, likely contributing to the emergence of the Italic and Celtic languages. In contrast, Armenian and Greek populations acquired steppe ancestry directly from Yamnaya groups of Eastern Europe. These results are consistent with the linguistic Italo-Celtic10,11 and Graeco-Armenian1,12,13 hypotheses accounting for the origins of most Mediterranean Indo-European languages of Classical Antiquity. Our findings thus align with specific linguistic divergence models for the Indo-European language family while contradicting others. This underlines the power of ancient DNA in uncovering prehistoric diversifications of human populations and language communities.

genetics↗

bioRxiv2024

Number of ancestors and length of identity-by-descent tracks over time

The divergence between genetic ancestors (those who have contributed to an individuals DNA) and genealogical ancestors (individuals recognized as ancestors in a societal context) evolves significantly over time. This study focuses on small, insular populations, where the number of genetic ancestors can swiftly encompass the entirety of genealogical ancestors. Additionally, in these populations, runs of homozygosity (ROHs) frequently occur due to random chance. This study used a forward-in-time simulation based on the Wright-Fisher model to analyze genealogical and genetic relatedness, haplotype block lengths, and runs of homozygosity (ROH) across generations. In small, insular populations, the number of genetic ancestors rapidly encompassed the total number of potential ancestors, and ROHs occurred frequently due to genetic drift. Our results showed that while genealogical ancestors followed an initial exponential growth phase before stabilizing, genetic ancestors grew more slowly. This was especially the case when the initial population size was large. These findings highlight the high frequency of ROHs in smaller populations, providing insights into the genetic structure of historically isolated groups.

genomics↗

bioRxiv2024

SAFARI: Pangenome Alignment of Ancient DNA Using Purine/Pyrimidine Encodings

Aligning DNA sequences retrieved from fossils or other paleontological artifacts, referred to as ancient DNA, is particularly challenging due to the short sequence length and chemical damage which creates a specific pattern of substitution (C[->]T and G[->]A) in addition to the heightened divergence between the sample and the reference genome thus exacerbating reference bias. This bias can be mitigated by aligning to pangenome graphs to incorporate documented organismic variation, but this approach still suffers from substitution patterns due to chemical damage. We introduce a novel methodology introducing the RYmer index, a variant of the commonly-used minimizer index which represents purines (A,G) and pyrimidines (C,T) as R and Y respectively. This creates an indexing scheme robust to the aforementioned chemical damage. We implemented SAFARI, an ancient DNA damage-aware version of the pangenome aligner vg giraffe which uses RYmers to rescue alignments containing deaminated seeds. We show that our approach produces more correct alignments from ancient DNA sequences than current approaches while maintaining a tolerable rate of spurious alignments. In addition, we demonstrate that our algorithm improves the estimate of the rate of ancient DNA damage, especially for highly damaged samples. Crucially, we show that this improved alignment can directly translate into better insights gained from the data by showcasing its integration with a number of extant pangenome tools.

bioinformatics↗

bioRxiv2024

CarpeDeam: A De Novo Metagenome Assemblerfor Heavily Damaged Ancient Datasets

De novo assembly of ancient metagenomic datasets is a challenging task. Ultra-short fragment size and characteristic postmortem damage patterns of sequenced ancient DNA molecules leave current tools ill-equipped for ideal assembly. We present CarpeDeam, a novel damage-aware de novo assembler designed specifically for ancient metagenomic samples. Utilizing maximum-likelihood frameworks that integrate sample-specific damage patterns, CarpeDeam demonstrates improved recovery of longer continuous sequences and protein sequences in many simulated and empirical datasets compared to existing assemblers. As a pioneering ancient metagenome assembler, CarpeDeam opens the door for new opportunities in functional and taxonomic analyses of ancient microbial communities.

genomics↗

bioRxiv2024

soibean: High-resolution Taxonomic Identification of Ancient Environmental DNA Using Mitochondrial Pangenome Graphs

Ancient environmental DNA (aeDNA) is becoming a powerful tool to gain insights about past ecosystems. However, several methodological challenges remain, particularly for classifying the DNA to species level and conducting phylogenetic placement. Current methods, primarily tailored for modern datasets, fail to capture several idiosyncrasies of aeDNA, including species mixtures from closely related species and ancestral divergence. We introduce soibean, a novel tool that utilises pangenomic graphs for identifying species from ancient environmental mitochondrial reads. It outperforms existing methods in accurately identifying species from multiple sources within a sample, enhancing phylogenetic analysis for aeDNA. soibean employs a damage-aware likelihood model for precise identification at low-coverage with high damage rate, demonstrating effectiveness through simulated data tests and empirical validation. Notably, our method uncovered new empirical results in published datasets, including using porpoise whales as food in a Mesolithic community in Sweden, demonstrating its potential to reveal previously unrecognised findings in aeDNA studies.

bioinformatics↗

bioRxiv2023

Benchmarking software tools for trimming adapters and merging next-generation sequencing data for ancient DNA

Ancient DNA is highly degraded, resulting in very short sequences. Reads generated with modern high-throughput sequencing machines are generally longer than ancient DNA molecules, therefore the reads often contain some portion of the sequencing adaptors. It is crucial to remove those adaptors, as they can interfere with downstream analysis. Furthermore, overlapping portions when DNA has been read forward and backward (paired-end) can be merged to correct sequencing errors and improve read quality. Several tools have been developed for adapter trimming and read merging, however, no one has attempted to evaluate their accuracy and evaluate their potential impact on downstream analyses. Through the simulation of sequencing data, seven commonly used tools were analyzed in their ability to reconstruct ancient DNA sequences through read merging. The analyzed tools exhibit notable differences in their abilities to correct sequence errors and identify the correct read overlap, but the most substantial difference is observed in their ability to calculate quality scores for merged bases. Selecting the most appropriate tool for a given project depends on several factors, although some tools such as fastp have some shortcomings, whereas others like leeHom outperform the other tools in most aspects. While the choice of tool did not result in a measurable difference when analyzing population genetics using principal component analysis, it is important to note that downstream analyses that rely on quality scores can be significantly impacted by the choice of tool.

bioinformatics↗

bioRxiv2023

The Limits of Haplotype-Based Approaches: Exploring the Applicability of the Li and Stephens Haplotype-Copying Model to Ancient Samples

The Li and Stephens (LS) haplotype-copying model is a seminal framework that represents a target haplotype as an imperfect mosaic of a set of reference haplotypes. Using a hidden Markov model, it can switch from different source haplotypes to model recombinations. This model has been used in several applications in modern populations including phasing and inference of ancestry. However, recent publications have looked at the applicability of the model to using ancient individuals as targets and modern reference panels as source data. Previous research exploring the impact of time separation between the modern references and the ancient target on the models behavior relied on coalescent simulation to generate genetic variation data, which could lead to an underestimation of the ancient populations genetic diversity. Further, these simulations were restricted to a relatively short time period of anatomically modern human history. To overcome these limitations, our study evaluates the robustness of the LS model using forward-simulated data enabling us to sample haplotypes that do not have direct descendants among the modern population. Additionally, we evaluate the model under the simple demographic scenario of a constant-sized continuous population starting 1.5M years ago to isolate the effect of time separation. Results indicate good performance for target haplotypes up to 900,000 years old, suggesting potential applicability to ancient DNA (aDNA) from anatomically modern humans. Although more complex demographic scenarios should be considered for a definitive answer, this research serves as a starting point for evaluating the haplotype-copying framework in aDNA data analysis.

genomics↗

bioRxiv2023

euka: Robust detection of eukaryotic taxa from modern and ancient environmental DNA using pangenomic reference graphs.

1. Ancient environmental DNA (eDNA) is a crucial source of in-formation for past environmental reconstruction. However, the com-putational analysis of ancient eDNA involves not only the inherited challenges of ancient DNA (aDNA) but also the typical difficulties of eDNA samples, such as taxonomic identification and abundance esti-mation of identified taxonomic groups. Current methods for ancient eDNA fall into those that only perform mapping followed by taxo-nomic identification and those that purport to do abundance estima-tion. The former leaves abundance estimates to users, while methods for the latter are not designed for large metagenomic datasets and are often imprecise and challenging to use. 2. Here, we introduce euka, a tool designed for rapid and accurate characterisation of ancient eDNA samples. We use a taxonomy-based pangenome graph of reference genomes for robustly assigning DNA sequences and use a maximum-likelihood framework for abundance estimation. At the present time, our database is restricted to mito-chondrial genomes of tetrapods and arthropods but can be expanded in future versions. 3. We find euka to outperform current taxonomic profiling tools as well as their abundance estimates. Crucially, we show that regardless of the filtering threshold set by existing methods, euka demonstrates higher accuracy. Furthermore, our approach is robust to sparse data, which is idiosyncratic of ancient eDNA, detecting a taxon with an average of fifty reads aligning. We also show that euka is consistent with competing tools on empirical samples and about ten times faster than current quantification tools. 4. eukas features are fine-tuned to deal with the challenges of ancient eDNA, making it a simple-to-use, all-in-one tool. It is available on GitHub: https://github.com/grenaud/vgan. euka enables re-searchers to quickly assess and characterise their sample, thus allowing it to be used as a routine screening tool for ancient eDNA.

bioinformatics↗

bioRxiv2022

HaploCart: Human mtDNA Haplogroup Classification Using a Pangenomic Reference Graph

Current mitochondrial DNA (mtDNA) haplogroup classification tools map reads to a single reference genome and perform inference based on the detected mutations to this reference. This approach biases haplogroup assignments towards the reference and prohibits accurate calculations of the uncertainty in assignment. We present HaploCart, an mtDNA haplogroup classifier which uses VGs pangenomic reference graph framework together with principles of Bayesian inference. We demonstrate that our approach significantly outperforms available tools by being more robust to lower coverage or incomplete consensus sequences and producing phylogenetically-aware confidence scores that are unbiased towards any haplogroup. HaploCart is available both as a command-line tool and through a user-friendly web interface. The program written in C++ accepts as input consensus FASTA, FASTQ, or GAM files, and outputs a text file with the haplogroup assignments along with confidence estimates. Our work considerably reduces the amount of data required to obtain a confident mitochondrial haplogroup assignment. HaploCart is available as a command-line tool at https://github.com/grenaud/vgan and as a web server at https://services.healthtech.dtu.dk/service. php?HaploCart.

bioinformatics↗

bioRxiv2022

Benchmarking freely available human leukocyte antigen typing algorithms across varying genes, coverages and typing resolutions

The human leukocyte antigen (HLA) system is a group of genes coding for proteins that are central to the adaptive immune system and identifying the specific HLA allele combination of a patient is relevant in organ donation, risk assessment of autoimmune and infectious diseases and cancer immunotherapy. However, due to the high genetic polymorphism in this region, HLA typing requires specialized methods. We investigated the performance of five next-generation-sequencing (NGS) based HLA typing tools with a non-restricted license namely HLA*LA, Optitype, HISAT-genotype, Kourami and STC-Seq. This evaluation was done for the five HLA loci, HLA-A, -B, -C, -DRB1 and -DQB1 using whole-exome sequencing (WES) samples from 829 individuals. The robustness of the tools to lower coverage was evaluated by subsampling and HLA typing 230 WES samples at coverages ranging from 1X to 100X. The typing accuracy was measured across four typing resolutions. Among these, we present two clinically-relevant typing resolutions, which specifically focus on the peptide binding region. On average, across the five HLA genes, HLA*LA was found to have the highest typing accuracy. For the individual genes, HLA-A, -B and -C, Optitypes typing accuracy was highest and HLA*LA had the highest typing accuracy for HLA-DRB1 and -DQB1. The tools robustness to lower coverage data varied widely and further depended on the specific HLA locus. For all class I loci, Optitype had a typing accuracy above 95% (according to the modification of the amino acids in the functionally relevant portion of the protein) at 50X, but increasing the depth of coverage beyond even 100X could still improve the typing accuracy of HISAT-genotype, Kourami, and STC-seq across all five HLA genes as well as HLA*LAs typing accuracy for HLA-DQB1. HLA typing is also used in studies of ancient DNA (aDNA), which often is based on lower quality sequencing data. Interestingly, we found that Optitypes typing accuracy is not notably impaired by short read length or by DNA damage, which is typical of aDNA, as long as the depth of coverage is sufficiently high.

bioinformatics↗

bioRxiv2022

Ancient Clostridium DNA and variants of tetanus neurotoxins associated with human archaeological remains

The analysis of microbial genomes from human archaeological samples offers a historic snapshot of ancient pathogens and provides insights into the origins of modern infectious diseases. Here, through a large-scale metagenomic analysis of archeological samples, we discovered bacterial species related to modern-day Clostridium tetani, which produces the tetanus neurotoxin (TeNT) and causes the disease tetanus. We assembled draft genomes from 38 distinct human archeological samples spanning five continents and dating to as early as ~4000 BCE. These genomes had varying levels of completeness and a subset of them displayed hallmarks of ancient DNA damage. While 24 fall into known C. tetani clades, phylogenetic analysis revealed novel C. tetani lineages, as well as two novel Clostridium species ("Clostridium sp. X and Y") closely related to C. tetani. Within these genomes, we found 13 TeNT variants with unique substitution profiles, including a subgroup of TeNT variants found exclusively in ancient samples from South America. We experimentally tested a TeNT variant selected from a ~6000-year-old Chilean mummy sample and found that it induced tetanus muscle paralysis in mice with potency comparable to modern TeNT. Our work identifies neurotoxigenic C. tetani in ancient DNA, new Clostridium species unique to ancient human samples, and a novel variant of TeNT that can cause disease in mammals.

genomics↗

bioRxiv2022

Population Genomics of Stone Age Eurasia

Western Eurasia witnessed several large-scale human migrations during the Holocene1-5. To investigate the cross-continental impacts we shotgun-sequenced 317 primarily Mesolithic and Neolithic genomes from across Northern and Western Eurasia. These were imputed alongside published data to obtain diploid genotypes from >1,600 ancient humans. Our analyses revealed a Great Divide genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers (HGs) were highly genetically differentiated east and west of this zone, and the impact of the neolithisation was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacements of HGs in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, while east of the Urals relatedness remained high until [~]4,000 BP, consistent with persistence of localised HG groups. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive but we demonstrate that HGs from the Middle Don region contributed ancestry to them. Yamnaya-groups later admixed with individuals associated with the Globular Amphora Culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a Neolithic steppe cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

evolutionary biology↗

bioRxiv2021

Discovering fragment length signatures of circulating tumor DNA using Non-negative Matrix Factorization

Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel method to study fragment lengths in cfDNA samples. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC=0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

bioinformatics↗

bioRxiv2021

Revealing intraosseous blood flow in the human tibia with ultrasound

Intraosseous blood circulation is thought to have a critical role in bone growth and remodeling, fracture healing, and bone disorders. However, it is rarely considered in clinical practice due to the absence of a suitable non-invasive in vivo measurement technique. In this work, we assessed blood perfusion in tibial cortical bone simultaneously with blood flow in the superficial femoral artery with ultrasound imaging in 5 healthy volunteers. After suppression of stationary signal with Singular-Value-Decomposition, pulsatile blood flow in cortical bone tissue is revealed, following the heart rate measured in the femoral artery. Using a method combining transverse oscillations and phase-based motion estimation, two-dimensional vector flow was obtained in the cortex of the tibia. After spatial averaging over the cortex, the peak blood velocity along the long axis of the tibia was measured four times larger than the peak blood velocity across the bone cortex. This suggests that blood flow in central (Haversian) canals is larger than in perforating (Volkmanns) canals, as expected from the intracortical vascular organization in humans. The peak blood velocity indicates a flow from the endosteum to the periosteum and from the heart to the foot for all subjects. Because aging and the development of bone disorders are thought to modify the direction and velocity of intra-cortical blood flow, their quantification is crucial. This work reports for the first time an in vivo quantification of the direction and velocity of blood flow in human cortical bone.

bioengineering↗

bioRxiv2019

The genetic origins of Saint Helena’s liberated Africans

Between the early 16th and late 19th centuries, an estimated 12 million Africans were transported to the Americas as part of the transatlantic slave trade. Following Britains abolition of slave trade in 1807, the Royal Navy patrolled the Atlantic and intercepted slave ships that continued to operate. During this period, the island of St Helena in the middle of the South Atlantic served as a depot for \"liberated\" Africans. Between 1840 and 1867, approximately 27,000 Africans were disembarked on the island. To investigate their origins, we generated genome-wide ancient DNA data for 20 individuals recovered from St Helena. The genetic data indicate that they came from West Central Africa, possibly the area of present-day Gabon and Angola. The data further suggest that they did not belong to a single population, confirming historical reports of cultural heterogeneity among the islands African community. Our results shed new light on the origins of enslaved Africans during the final stages of the slave trade and illustrate how genetic data can be used to complement and validate existing historical sources.

genomics↗