Biology subjects

Arndt, P. F.

Publications and source records attributed to Arndt, P. F..

8 recordsLinked to original sources

bioRxiv2026

Inferring evolutionary distances from whole prokaryotic genome alignments, accounting for among-locus substitution rate heterogeneity

Ever since the rise of next generation sequencing technologies, the number of prokaryotic genomes in databases has increased tremendously. In order to leverage those vast quantities of data, an approach was previously introduced to estimate evolutionary divergences by modeling the genomic distances between substitutions in many whole genome alignments. However, this proof of concept study was conducted on the Enterobacterales clade only, such that its applicability to other clades remained to be established. In this study, we demonstrate the broad applicability of this method to a wider range of clades and to species with larger evolutionary divergences. We also show that relaxing a hypothesis on the substitution rate distribution, with a single additional free parameter, drastically improves both the estimation of evolutionary divergences and the quality of the inferred trees. We use simulations to show that our method can correctly recover the tree topology in cases where substitution rates evolve along the tree. Finally, our results also have theoretical implications for our understanding of substitution rate heterogeneity in genomes, since we found differences in the range of substitution rate distribution in our three examples Bacillales, Enterobacterales and Methanobacteriota whose causes remain to be identified.

evolutionary biology↗

bioRxiv2026

commonPeak: Equivalence testing to identify common ChIP-seq peaks across conditions and protocols

BackgroundNew ChIP-seq protocols are increasingly adopted alongside established workflows. However, dedicated methods are lacking to quantify the agreement of peak location and intensity across datasets, including comparisons across protocols and biological conditions. ObjectivesWe present commonPeak, a statistical framework that identifies shared peaks across samples and tests whether their enrichment is similar across conditions, thereby supporting bench-marking of ChIP-seq protocols and cross-condition comparisons. ResultscommonPeak operates on BED peak sets and BAM files. As a use case, we applied it to an estrogen receptor alpha (ER) ChIP-seq dataset from tamoxifen-sensitive and -resistant breast cancer cell line MCF-7 cells and identified 225 shared peaks with significantly similar enrichment. These peaks were largely distinct from differentially bound sites and enriched for estrogen signaling. This illustrates how equivalence-based peak selection can help separate conserved ER-driven programs from condition-specific changes in ER-targeting endocrine drugs such as tamoxifen. Availability and implementationcommonPeak is freely available for non-commercial use via GitHub, with documentation and usage examples.

genomics↗

bioRxiv2025

Reconstructing the network of horizontal gene exchange in bacteria to differentiate direct and indirect transfers

Horizontal gene transfer (HGT) plays a central role in bacterial evolution. Yet, its large-scale dynamics and underlying network structure remain poorly characterized. We present a theoretical framework that models HGT as a continuous stochastic process over a network of bacterial genera and analyze its genomic footprint via the distribution of exact sequence matches shared across taxa--the match length distribution (MLD). We show that different evolutionary regimes imprint distinct statistical signatures on the MLD: single episodic gene transfer events yield exponential distributions, while continuous sustained HGT processes lead to power-law tails. The power-law exponent is analytically linked to the topology of the transfer network, distinguishing between intraclade transfers and hub-mediated dissemination. Empirical MLDs derived from bacterial genomes recapitulate these predicted patterns. Moreover, we find that defining a genus-specific "transferability" parameter that governs pairwise HGT rates and incorporating a high-transferability hub accurately reproduces the observed data. Our approach provides a general framework for inferring hidden structure in genomic horizontal transfer processes, enabling quantitative analysis of microbial evolution.

genomics↗

bioRxiv2023

An analytical derivation of the distribution of distances between heterozygous sites in diploid species to efficiently infer demographic history

Heterozygous sites are not uniformly distributed along a diploid genome. Rather, their density varies as a result of recombination events, and their local density reflects the time to the last common ancestor of the maternal and paternal copies of a genomic region. The distribution of the density of heterozygous sites therefore carries information about the history of the population size. Despite previous efforts, an exact derivation of the distribution of heterozygous sites is still lacking. As a consequence, the estimation of population size variation is difficult and requires several simplifying assumptions. Using a novel theoretical framework, we are able to derive an analytical formula for the distribution of distances between heterozygous sites. Our theory can account for arbitrary demographic histories, including bottlenecks. In the case of a constant population size the distribution follows a simple function and exhibits a power-law tail proportional to r with =-3, where r is the distance between heterozygous sites. This prediction is accurately validated when considering heterozygous sites in individuals of African descent. Other populations migrated out of Africa and underwent at least one bottleneck which left a distinct mark on their interval distribution between heterozygous sites, i.e., an overrepresentation of intervals between 10 and 100 kbp in length. Our analytical theory for non-constant population sizes reproduces this behavior and can be used to study historical changes in population size with high accuracy. The simplicity of our approach facilitates the analysis of demographic histories for diploid species, requiring only a single unphased genome.

genomics↗

bioRxiv2023

Modeling the mosaic structure of bacterial genomes to infer their evolutionary history

The timing and phylogeny of bacterial evolution is difficult to reconstruct because of a scarce fossil record, deep genomic divergences and complexities associated with molecular clocks. Studying bacterial evolutionary history using rich and rapidly accumulating genomic data requires accurate modeling of genome evolution, taking into account that different parts of bacterial genomes have different history. In particular, along the genome, different loci are subject to different selective pressure. In addition, some are horizontally transferred from one bacterium to another, resulting in a mosaic-like genome structure. An important technical aspect is that loci with high effective mutation rates can diverge beyond the aligner detection limit, biasing the genome-wide divergence estimate towards more conserved loci. Therefore, the genome-wide molecular clock cannot be directly applied to study bacterial evolutionary history. In this article, we propose a novel method to gain insight into bacterial evolution based on statistical properties of genomic sequences comparisons. The length distribution of the sequence matches is shaped by the effective mutation rates of different loci, by the horizontal transfers and by the aligner sensitivity. Based on these inputs we build a model and demonstrate that it accounts for the empirically observed distributions, taking the Enterobacteriaceae family as an example. Using the model and the empirical data we fit the evolutionary parameters: time divergences and horizontal transfer rates. Based on the estimated time divergences we build a time-calibrated phylogenetic tree, demonstrating the accuracy of the method and its ability to unravel vertical and horizontal transfers in bacterial genomes.

evolutionary biology↗

bioRxiv2023

Reconstruction of segmental duplication rates and associated genomic features by network analysis

AO_SCPLOWBSTRACTC_SCPLOWSegmental duplications (SDs) are long genomic duplications fixed in a genome. SDs play an important evolutionary role: entire genes together with regulatory sequences can be duplicated. Ancestral segmental duplications gave rise to genes involved in human brain development, as well as provided sites for further genomic rearrangements. Some duplicated loci were extensively studied, however, universal principles or biological factors of SDs propagation are not fully described yet. Segmental duplications can be arranged into a network where edges correspond to real duplication events, while nodes to affected genomic sites. This gave us an opportunity to estimate how many duplications happened in each locus. We studied genomic features associated with increased duplication rates with especial interest in high-copy repeats distribution relative to duplicated regions breakpoints. Our comprehensive study of genomic features associated with duplications and those associated with increased duplication rates allowed us to identify several biological factors affecting a segmental duplication process. We found genomic features associated with increased duplication rates, three signatures of duplication process and associations of SDs with different classes of high-copy repeats.

genomics↗

bioRxiv2020

Long identical sequences found in multiple bacterial genomes reveal frequent and widespread exchange of genetic material between distant species.

Horizontal transfer of genomic elements is an essential force that shapes microbial genome evolution. Horizontal Gene Transfer (HGT) occurs via various mechanisms and has been studied in detail for a variety of systems. However, a coarse-grained, global picture of HGT in the microbial world is still missing. One reason is the difficulty to process large amounts of genomic microbial data to find and characterise HGT events, especially for highly distant organisms. Here, we exploit the fact that HGT between distant species creates long identical DNA sequences in genomes of distant species, which can be found efficiently using alignment-free methods. We analysed over 90 000 bacterial genomes and thus identified over 100 000 events of HGT. We further developed a mathematical model to analyse the statistical properties of those long exact matches and thus estimate the transfer rate between any pair of taxa. Our results demonstrate that long-distance gene exchange (across phyla) is very frequent, as more than 8% of the bacterial genomes analysed have been involved in at least one such event. Finally, we confirm that the function of the transferred sequences strongly impact the transfer rate, as we observe a 3.5 order of magnitude variation between the most and the least transferred categories. Overall, we provide a unique view of horizontal transfer across the bacterial tree of life, illuminating a fundamental process driving bacterial evolution.

bioinformatics↗

bioRxiv2019

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗