Biology subjects

Seplyarskiy, V.

Publications and source records attributed to Seplyarskiy, V..

9 recordsLinked to original sources

bioRxiv2026

Extrachromosomal Circular DNA Function as Mobile Elements to Alter the Mammalian Germline Genome

The viability of any species including the human requires that the germline genome is kept stable as it is transmitted across generations by the germ cells. Failure to safeguard the genome integrity and stability would lead to inherited diseases and infertility. Thus, a better understanding of the mechanisms that alter the germline genome is crucial to ensure human health and our continuation as a species. Here, we show that the extrachromosomal circular DNA (eccDNA) in the mouse and human male germline represents a new mechanism in altering the mammalian germline genome. To enable the tracking of germline eccDNA in vivo, we established a novel mouse model that allows the generation of a reporter eccDNA in a cell type-specific manner. Using this mouse model, we showed that eccDNA formed in the developing male germ cells can integrate into the germline genome. Using eccDNA-containing sperm for in vitro fertilization led to the eccDNA sequence being inherited by the embryos. By analyzing a large cohort of long-read whole genome sequencing data, we showed that eccDNA-mediated germline genome insertions represent an important source of human genome structural variations. Finally, by leveraging human sperm samples, we found that diabetes induces an increase in sperm eccDNA quantity, which is mediated at least in part through poly (ADP-ribose) polymerases. Together, our results provide new insights into how the mammalian germline genome can be altered, with important implications for human health and genome evolution.

developmental biology↗

bioRxiv2026

Inference of elevated mutation rates and variant effects using 700k exomes

Genomic sequencing is now widely accessible for genetic diagnostics and is emerging as a component of newborn screening. This technological development generates the need to characterize incoming mutations, create comprehensive datasets of genes causing rare Mendelian disorders, and identify pathogenic variants. Large-scale exome sequencing datasets such as Genome Aggregation Database (gnomAD) have been assembled to help address these challenges. The recent release of gnomAD (v4; n = 730,947) uncovers millions of rare coding variants, many of which have arisen more than once by independent recurrent mutations in the rapidly growing recent human population. Here, we use newly developed theoretical understanding of sampling properties of rare variants to estimate key population genetics parameters of practical importance to human genetics such as demography history, mutation rate, and selection. Solely relying on population data, our method Population Inferred Estimates of Selection (PIES) identifies novel genes with loss-of-function mutational hotspots likely due to selection in spermatogonia. PIES efficiently estimates selection coefficients for heterozygous loss-of-function variants. Combining population genetics inference with variant effect predictors, PIES predicts pathogenic missense mutations and improves variant prioritization for genetic diagnostics and newborn screening.

genetics↗

bioRxiv2025

Segregating DNA lesions point to high selective advantage of tumor initiating cells

The complications with identifying cells at the origin of cancer and tracking their early divisions impede studies of cancer initiation. Recently, it was shown that some DNA lesions generated by a pulse of damage-inducing mutagen persist over multiple rounds of replication. Segregation of DNA lesions in the early genealogy of an expanding clone leaves a statistically interpretable footprint of cancer initiating events. Specifically, it allows for estimating the number of cell divisions between the initiating DNA lesion and the most recent common ancestor of the tumor. Here, we analyze footprints of segregating lesions from a previously published experimental mouse system, as well as post-chemotherapy human metastatic tumors and the blood of chemotherapy treated patients. In all contexts, clones tend to start early, usually within the span of 4 cell generations from mutagen exposure. Using a branching process model, we show that fitness advantage of early cancer drivers exceeds 30%, with each early division leading to at least 1.3 self-renewing cells. We highlight an example of a blood-derived single cell phylogeny with major subclones separated by just two cell divisions. Broadly, our approach allows inference of tumor initiation and growth parameters based on events preceding the most recent common ancestor of the initiating clone as opposed to characteristics of fully grown tumors.

cancer biology↗

bioRxiv2025

Transcription start sites experience a high influx of heritable variants fuelled by early development

Mutations drive evolution and genetic diversity, but the impact of transcription on germline mutagenesis remains poorly understood. Here, we identify a hypermutation phenomenon at transcription start sites in the human germline, spanning several hundred base pairs in both directions. We link this TSS mutational hotspot to divergent transcription, RNA polymerase II stalling, R-loops, and mitotic--but not meiotic--double-strand breaks, revealing a recombination-independent mechanism distinct from known processes. Notably, the hotspot is absent in de novo mutation data. We reconcile this by showing that TSS mutations are significantly enriched with early mosaic variants often filtered out in de novo mutation calls, indicating that the hotspot arises during early embryogenesis. Mutational signature analysis reinforces these findings and implicates alternative non-homologous end joining and maternal mutation clusters. Our study provides the first detailed description of a germline TSS mutation hotspot, with broad evolutionary and biomedical implications.

genomics↗

bioRxiv2024

A Phylogeny-Based Approach to Discover Mutational Processes in Primates

The accumulation of germline mutations underpins population diversity and drives genetic evolution. Despite the availability of extensive phylogenetic data, the lack of suitable methodologies has hindered the comprehensive characterization of germline mutational processes across evolutionary trees. To address this, we develop a robust three-step methodology that extracts germline mutational processes from alignments of closely related species. First, we estimate regional, branch-specific trinucleotide mutational spectra from a multispecies alignment. Second, we extract mutational processes jointly across an evolutionary clade by analyzing mutation rate variation along the genome using Reciprocal Principal Components Analysis (RPCA). Finally we filter artifactual mutational signatures using DNA symmetry. Applying this method to five primate clades and a rodent outgroup clade revealed nine distinct mutational processes. Notably, five of these processes were consistently observed across all six groups. We identified underling biological mechanism for at least seven of the processes, highlighting phenomena such as biased gene conversion, bulky lesion resolution, and maternal mutagenesis. We validated identified processes using human and non-human polymorphism data. This study offers new insights into the biology and evolution of mutagenesis in primates and introduces a methodological toolkit to investigate mutational processes across phylogenies.

evolutionary biology↗

bioRxiv2023

Mutational signature decomposition with deep neural networks reveals origins of clock-like processes and hypoxia dependencies

DNA mutational processes generate patterns of somatic and germline mutations. A multitude of such mutational processes has been identified and linked to biochemical mechanisms of DNA damage and repair. Cancer genomics relies on these so-called mutational signatures to classify tumours into subtypes, navigate treatment, determine exposure to mutagens, and characterise the origin of individual mutations. Yet, state-of-the-art methods to quantify the contributions of different mutational signatures to a tumour sample frequently fail to detect certain mutational signatures, work well only for a relatively high number of mutations, and do not provide comprehensive error estimates of signature contributions. Here, we present a novel approach to signature decomposition using artificial neural networks that addresses these problems. We show that our approach, SigNet, outperforms existing methods by learning the prior frequencies of signatures and their correlations present in real data. Unlike any other method we tested, SigNet achieves high prediction accuracy even with few mutations. We used this to generate estimates of signature weights for more than 7500 tumours for which only whole-exome sequencing data are available. We then identified systematic differences in signature activity both as a function of epigenetic covariates and over the course of tumour evolution. This allowed us to decipher the origins of signatures SBS3, SBS5 and SBS40. We further discovered novel associations of mutational signatures with hypoxia, including strong positive correlations with the activities of clock-like and defective DNA repair mutational processes. These results provide new insights into the interplay between tumour biology and mutational processes and demonstrate the utility of our novel approach to mutational signature decomposition, a crucial part of cancer genomics studies.

genomics↗

bioRxiv2022

A mutation rate model at the basepair resolution identifies the mutagenic effect of Polymerase III transcription

De novo mutations occur with substantially different rates depending on genomic location, sequence context and DNA strand1-4. The success of many human genetics techniques, especially when applied to large population sequencing datasets with numerous recurrent mutations5-7, depends strongly on assumptions about the local mutation rate. Such techniques include estimation of selection intensity8, inference of demographic history9, and mapping of rare disease genes10. Here, we present Roulette, a genome-wide mutation rate model at the basepair resolution that incorporates known determinants of local mutation rate (http://genetics.bwh.harvard.edu/downloads/Vova/Roulette/). Roulette is shown to be more accurate than existing models1,6. Roulette has sufficient resolution at high mutation rate sites to model allele frequencies under recurrent mutation. We use Roulette to refine estimates of population growth within Europe by incorporating the full range of human mutation rates. The analysis of significant deviations from the model predictions revealed a 10-fold increase in mutation rate in nearly all genes transcribed by Polymerase III, suggesting a new mutagenic mechanism. We also detected an elevated mutation rate within transcription factor binding sites restricted to sites actively utilized in testis and residing in promoters.

genetics↗

bioRxiv2022

Enrichment of somatic mutations in schizophrenia brain targets prenatally active transcription factor bindings sites

Schizophrenia (SCZ) is a complex neuropsychiatric disorder in which both germline genetic mutations and maternal factors, such as infection and immune activation, have been implicated, but how these two strikingly different mechanisms might converge on the same phenotype is unknown. During development, cells accumulate somatic, mosaic mutations in ways that can be shaped by the cellular environment or endogenous processes, but these early developmental mutational patterns have not been studied in SCZ. Here we analyzed deep (267x) whole-genome sequencing (WGS) of DNA from cerebral cortical neurons isolated from 61 SCZ and 25 control postmortem brains to capture mutations occurring before or during fetal neurogenesis. SCZ cases showed a >15% increase in genome-wide sSNV compared to controls (p < 2e-10). Remarkably, mosaic T>G mutations and CpG transversions (CpG>GpG or CpG>ApG) were 79- and 62-fold enriched, respectively, at transcription factor binding sites (TFBS) in SCZ, but not in controls. The pattern of T>G mutations resembles mutational processes in cancer attributed to oxidative damage that is sterically blocked from DNA repair by transcription factors (TFs) bound to damaged DNA. The CpG transversions similarly suggest unfinished DNA demethylation resulting in abasic sites that can also be blocked from repair by bound TFs. Allele frequency analysis suggests that both localized mutational spikes occur in the first trimester. We call this prenatal mutational process "skiagenesis" (from the Greek skia, meaning shadow), as these mutations occur in the shadow of bound TFs. Skiagenesis reflects as-yet unidentified prenatal factors and is associated with SCZ risk in a subset ([~]13%) of cases. In turn, mutational disruption of key TFBS active in fetal brain is well positioned to create SCZ-specific gene dysregulation in concert with germline risk genes. Skiagenesis provides a fingerprint for exploring how epigenomic regulation and prenatal factors such as maternal infection or immune activation may shape the developmental mutational landscape of human brain.

genomics↗

bioRxiv2017

Error-prone bypass of DNA lesions during lagging strand replication is a common source of germline and cancer mutations

Spontaneously occurring mutations are of great relevance in diverse fields including biochemistry, oncology, evolutionary biology, and human genetics. Studies in experimental systems have identified a multitude of mutational mechanisms including DNA replication infidelity as well as many forms of DNA damage followed by inefficient repair or replicative bypass. However, the relative contributions of these mechanisms to human germline mutations remain completely unknown. Here, based on the mutational asymmetry with respect to the direction of replication and transcription, we suggest that error-prone damage bypass on the lagging strand plays a major role in human mutagenesis. Asymmetry with respect to transcription is believed to be mediated by the action of transcription-coupled DNA repair (TC-NER). TC-NER selectively repairs DNA lesions on the transcribed strand; as a result, lesions on the non-transcribed strand are preferentially converted into mutations. In human polymorphism we detect a striking similarity between transcriptional asymmetry and asymmetry with respect to replication fork direction. This parallels the observation that damage-induced mutations in human cancers accumulate asymmetrically with respect to the direction of replication, suggesting that DNA lesions are asymmetrically resolved during replication. Re-analysis of XR-seq data, Damage-seq data and cancers with defective NER corroborate the preferential error-prone bypass of DNA lesions on the lagging strand. We experimentally demonstrate that replication delay greatly attenuates the mutagenic effect of UV-irradiation, in line with the key role of replication in conversion of DNA damage to mutations. We conservatively estimate that at least 10% of human germline mutations arise due to DNA damage rather than replication infidelity. The number of these damage-induced mutations is expected to scale with the number of replications and, consequently, paternal age.

biochemistry↗