Biology subjects

Rahbari, R.

Publications and source records attributed to Rahbari, R..

18 recordsLinked to original sources

bioRxiv2026

Multi-scale modeling of human tissues from spatial transcriptomics with TERRA

Spatial transcriptomics maps gene expression at cellular resolution, revealing how cells organize into multicellular niches. Yet computational analyses remain dataset-specific, without a transferable representation of tissue organization that generalizes across datasets, tasks and tissues or predicts how tissues behave under perturbation. We present TERRA, a foundation model pretrained on 112 million human cells profiled by spatial transcriptomics. From a single pretrained backbone, TERRA yields embeddings at the scale of cells, the genes they express and the neighborhoods in which they reside, and supports spatial in silico perturbation, all applied zero-shot to unseen tissues. At the cell level, in newly generated spatial data for developing pancreas, TERRA identified an islet-associated capillary state which we posit represents a developmental precursor of the mature islet microvasculature. At the gene level, in untreated kidney sections, in silico knockout of immune-checkpoint targets predicted a gene program of immune-checkpoint-blockade-associated nephrotoxicity, which we validated in treatment-exposed tissue and recovered in blood. At the neighborhood level, TERRA mapped macrophages across tissues to identify recurring cross-organ niches, which we term archetypes, including a tumor-boundary niche associated with poor prognosis in kidney cancer. Together, TERRA captures the spatial and multicellular logic of human tissue and predicts, in silico, its response to perturbation, providing a multi-scale framework for tissue biology, therapeutic development and clinical application.

genomics↗

bioRxiv2026

Using somatic data to aid germline clinical variant interpretation in developmental disorders

Accurate interpretation of rare germline variants remains a major challenge in developmental disorders (DD). Somatic mutation data represent a largely untapped source of evidence for germline variant classi-fication. Identical or nearby mutations that drive positive selection when present in somatic tissues can cause developmental disorders when present in the germline. We integrated somatic mutation data from the Catalogue Of Somatic Mutations In Cancer (COSMIC), and healthy tissues (sperm and buccal epithelium) with germline variant datasets from ClinVar and large studies of de novo mutations in DD patients. Across 970 dominant DD genes, 195 have evidence of somatic selection, with a majority demonstrating concordant mechanisms between germline and somatic contexts. We benchmark the ability of somatic data to discriminate pathogenic from benign germline missense variation across dominant DD genes, identifying 145 genes in which somatic data are informative. The strongest utility is in altered-function genes where germline and somatic mechanisms are concordant, for example the RASopathy genes. In these genes, codon-level aggregation of somatic missense counts yields predictive performance comparable to computational predictors or MAVE assays (AUC-ROC 0.895 for somatic data, versus 0.893 for REVEL). Combining somatic features with computational scores improves discrimination further. Using likelihood ratios, we map COSMIC missense codon count thresholds onto American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP)-style evidence strengths, showing that somatic data can reach strong levels of evidence in germline variant interpretation in DD and enable reclassification of variants of uncertain significance. Together, these results establish somatic mutation data as a scalable and clinically actionable evidence source for germline variant interpretation in select DD genes. Graphical abstract(Generated using FigureLabs) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/732808v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1d65659org.highwire.dtl.DTLVardef@beff70org.highwire.dtl.DTLVardef@174396dorg.highwire.dtl.DTLVardef@1662b08_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Ultra-deep duplex sequencing reveals unique features of somatic evolution in the normal tissues of a family with Li-Fraumeni syndrome

Li-Fraumeni Syndrome (LFS) is caused by germline pathogenic variants in TP53 which predispose carriers to early onset cancer across multiple tissues. While genomically profiling those cancers has revealed factors contributing to their formation, little is understood about how LFS impacts clonal evolution in healthy tissues preceding cancer. Here, we use ultra-deep duplex sequencing (mean [~]15,000x depth) to investigate somatic mutation and selection in a family carrying the germline TP53 p.R181H pathogenic variant and a cohort of non-carrier controls. In blood samples, the germline variant is associated with more mutations in a panel designed to capture genomewide mutagenesis, and with reduced positive selection on somatic TP53 mutations, despite confounding by chemotherapy treatment in one individual. DNMT3A and TET2 mutations appear positively selected and GATA2 mutations negatively selected across the cohort, independent of the p.R181H status. Extensive multi-tissue sampling of 22 non-cancerous and 6 cancerous samples was also performed at autopsy in one individual with LFS who succumbed to esophageal cancer. Cross-tissue analysis reveals excess mutations in sun-exposed skin, esophagus and chronically-inflamed stomach tissue, and concordant mutations in the p.R248 hotspot of TP53 across most (18/28) tissue samples. Most somatic TP53 mutations in LFS that can be assessed for phase arose on the chromosomal copy lacking the p.R181H variant. Our study reveals how the germline p.R181H variant reshapes baseline somatic mutation and selection in normal tissues and highlights the importance of understanding early somatic evolution in LFS prior to cancer development and treatment.

cancer biology↗

bioRxiv2024

Insights into non-crossover recombination from long-read sperm sequencing

Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. Although human crossovers have been studied at the pedigree, population and single-cell level, the more frequent non-crossover events that lead to gene conversion are harder to study, particularly at the individual level. Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, allowing effectively arbitrary sample sizes for analysis from one male. Using fifteen sperm samples from thirteen donors we demonstrate variation between and within donors for the rates of different types of recombination. Intriguingly, we observe a tendency for non-crossover gene conversions to occur upstream of nearby PRDM9 binding sites, whereas crossover locations have a slight downstream bias. We further provide evidence for two distinct non-crossover processes. One gives rise to the vast majority of non-crossovers with mean conversion tract length under 50bp, which we suggest is an outcome of standard PRDM9-induced meiotic recombination. In contrast [~]2% of non-crossovers have much longer mean tract length, and potentially originate from the same process as complex events with more than two haplotype switches, which is not associated with PRDM9 binding sites and is also seen in somatic cells.

genetics↗

bioRxiv2024

The impact of ancestral, environmental and genetic influences on germline de novo mutation rates and spectra

De novo germline mutation is an important factor in the evolution of allelic diversity and disease predisposition in a population. Here, we study the influence of genetically-inferred ancestry and environmental factors on de novo mutation rates and spectra. Using a genetically diverse sample of [~]10K whole-genome sequenced trios, one of the largest de novo mutation catalogues to date, we found that genetically-inferred ancestry is associated with modest but significant changes in both germline mutation rate and spectra across continental populations. These effects may be due to genetic or environmental factors correlated with ancestry. We find epidemiological evidence that exposure to tobacco smoke is significantly associated with increased de novo mutation rate, but it does not mediate the observed ancestry effects. Investigation of several other potential mutagenic factors using Mendelian randomisation showed no consistent effects, except for age of menopause, where increased age corresponded to a reduction in de novo mutation rate. Overall, our study presents evidence on new factors influencing de novo mutational rate and spectra.

genetics↗

bioRxiv2024

The long-term effects of chemotherapy on normal blood cells

In developed countries, [~]10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, triggering cell death. However, there is limited understanding of the extent and long-term consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

cell biology↗

bioRxiv2024

Deciphering the role of germline complex de novo structural variations in rare disorders

De novo structural variants (dnSVs) have emerged as crucial genetic factors in the context of rare disorders. However, these variations often go undiagnosed in routine genetic screening practices. To shed light on their significance in rare disease, we conducted a comprehensive analysis of the largest cohort of parent-offspring whole-genome sequencing data from the UK 100,000 Genomes Project. Our study encompassed a vast cohort of 12,568 families, including 13,702 offspring affected by rare genetic diseases. We identified a total of 1,872 dnSVs, revealing that approximately 12% of the probands harboured at least one dnSV, of which 9% were identified as likely pathogenic in affected probands (151/1696). Advanced parents age was found to be associated with an increased chance of having dnSVs in probands. We discovered 148 clustered breakpoints resulting from a single event. 60% of these complex dnSVs were classified into 9 major SV types, and could be observed in multiple individuals, while the remaining 40% were private events and had not been previously reported. We found 12% of pathogenic dnSVs are complex SVs, emphasising the critical importance of thoroughly examining and considering complex dnSVs in the context of rare disorders. Furthermore, we discovered an enrichment of maternal dnSVs at subtelometric, early-replicating regions of chromosome 16, suggesting possible sex-specific mechanisms in generation of dnSVs. This study sheds light on the extent of diversity of dnSVs in the germline and their contribution to rare genetic disorders.

genomics↗

bioRxiv2023

A naturally occurring variant of MBD4 causes maternal germline hypermutation in primates

As part of an ongoing genome sequencing project at the Oregon National Primate Research Center, we identified a rhesus macaque with a rare homozygous frameshift mutation in the gene Methyl-CpG binding domain 4 (MBD4). MBD4 is responsible for the repair of C>T deamination mutations at CpG locations and has been linked to somatic hypermutation and cancer predisposition in humans. We show here that MBD4-associated hypermutation also affects the germline: the 6 offspring of the MBD4-null dam have a 4-6 fold increase in de novo mutation burden. This excess burden was predominantly C>T mutations at CpG locations consistent with MBD4 loss-of-function in the dam. There was also a significant excess of C>T at CpA sites, indicating an important, underappreciated role for MBD4 to repair deamination in CpA contexts. The MBD4-null dam developed sustained eosinophilia later in life, but we saw no other signs of neoplastic processes associated with MBD4 loss-of-function in humans, nor any obvious disease in the hypermutated offspring. This work provides what is likely the first evidence for a genetic factor causing hypermutation in the maternal germline of a mammal, and adds to the very small list of naturally occurring variants known to modulate germline mutation rates in mammals.

genetics↗

bioRxiv2022

Accurate de novo detection of somatic mutations in high-throughput single-cell profiling data sets

Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism, and cell plasticity. However, detection of mutations in single cells remains technically challenging. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq data sets without requiring matched bulk or single-cell DNA sequencing data. Using >1.5M single cells from 383 single-cell RNAseq and single-cell ATAC-seq data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells, even in differentiated cells from polyclonal tissues not amenable to mutation detection using existing methods. In addition, SComatic permits the estimation of mutational burdens and de novo mutational signature analysis at single-cell and cell-type resolution. Notably, using matched exome and single-cell RNAseq data, we show that SComatic achieves a 20 to 40-fold increase in precision as compared to existing algorithms for somatic SNV calling without compromising sensitivity. Overall, SComatic opens the possibility to study somatic mutagenesis at unprecedented scale and resolution using high-throughput single-cell profiling data sets.

genomics↗

bioRxiv2022

Clonal diversification and histogenesis of malignant germ cell tumours

Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells. They are uniquely able to recapitulate embryonic and extraembryonic tissues, which carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the relationship of histogenesis and clonal diversification in GCTs by analysing the genome and transcriptome of 547 microdissected histological units. We found that the extensive diversification of tissues and genetic subclones were not correlated. However, we identified unifying features including the retention of fetal developmental transcripts across tissues, expression changes on chromosome 12p, and a conserved somatic evolutionary sequence of whole genome duplication followed by clonal diversification. Whilst this pattern was preserved across all GCTs, the developmental timing of the duplication varied between prepubertal and postpubertal cases. In addition, tumours of younger children exhibited distinct substitution signatures, including a novel one, which may lend themselves as potential biomarkers for risk stratification. Our findings portray the extensive diversification of GCT tissues and genetic subclones as randomly distributed, whilst identifying overarching tissue and tumour transcriptional and genomic features.

cancer biology↗

bioRxiv2021

Genetic and pharmacological causes of germline hypermutation

Mutation in the germline is the source of all evolutionary genetic variation and a cause of genetic disease. Previous studies have shown parental age to be the primary determinant of the number of new germline mutations seen in an individuals genome. Here we analysed the genome-wide sequences of 21,879 families with rare genetic diseases and identified 12 hypermutated individuals with between two and seven times more de novo single nucleotide variants (dnSNVs) than expected. In most of these families (8/12) the excess mutations could be attributed to the father. We determined that two of these families had genetic drivers of germline hypermutation, with the fathers carrying damaging genetic variation in known DNA repair genes, causing distinctive mutational signatures. For five families, by analysing clinical records and mutational signatures, we determined that paternal exposure to chemotherapeutic agents prior to conception was a key driver of hypermutation. Our results suggest that the germline is well protected from mutagenic effects, hypermutation is rare and relatively modest in degree and that most hypermutated individuals will not have a genetic disease.

genomics↗

bioRxiv2021

Somatic mutations reveal widespread mosaicism and mutagenesis in human placentas

Clinical investigations of human fetuses have revealed that placentas occasionally harbour chromosomal aberrations that are absent from the fetus1. The basis of this genetic segregation of the placenta, termed confined placental mosaicism, remains unknown. Here, we investigated the phylogeny of human placentas reconstructed from somatic mutations, using whole genome sequencing of 86 placental biopsies and of 106 microdissections. We found that every placental biopsy represented a clonal expansion that is genetically distinct. Biopsies exhibited a genomic landscape akin to childhood cancer, in terms of mutation burden and mutational imprints. Furthermore, unlike any other human normal tissue studied to date, placental genomes commonly harboured copy number changes. Reconstructing phylogenetic relationships between tissues from the same pregnancy, revealed that developmental bottlenecks confined placental tissues, by separating trophectodermal from inner cell mass-derived lineages. Of particular note were cases in which inner cell mass-derived and placental lineages fully segregated within a few cell divisions of the zygote. Such early embryonic bottlenecks may enable the normalisation of zygotic aneuploidy. We observed direct evidence for this in a case of mosaic trisomic rescue. Our findings reveal cancer-like mutagenesis in placental tissues and portray confined mosaicism as the normal outcome of placental development.

genomics↗

bioRxiv2021

Signatures of Mutational Processes in Human DNA Evolution

The human genome contains over 100 million SNPs, most of which are C/T (G/A) variations. The type and sequence context of these SNPs are not random, suggesting that they are caused by distinct mutational processes. Deciphering the mutational signatures is a crucial step to discovering the molecular processes responsible for DNA variations across human populations, and potentially for causing genetic diseases. Our analyses of the 1000 Genomes Project SNPs and germline de novo mutations suggest that at least four mutational processes are responsible for human genetic variations. One process is European-specific and no longer active. The remaining three processes are currently active in all human populations. Two of the active processes co-occur and leave a single joint mutational signature in human nuclear DNA. The third active process is specific to mitochondrial DNA, and inflicts C-to-T mutations at mostly non-CG sites. We found neither evidence of APOBEC-induced cytosine deamination in the human germline, nor de novo mutation enrichment within certain regions of the human genome.

evolutionary biology↗

bioRxiv2020

Extensive phylogenies of human development reveal variable embryonic patterns

Starting from the zygote, all cells in the developing and adult human body continuously acquire mutations. A mutation shared between two different cells implies a shared progenitor cell and can thus be used as a naturally occurring marker for lineage tracing. Here, we reconstruct extensive phylogenies of normal tissues from three adult individuals using whole-genome sequencing of 511 laser capture microdissected samples from multiple organs. Early embryonic progenitor cells inferred from the phylogenies often contribute in different proportions to the adult body and the extent of this asymmetry is variable between individuals, with ratios between the first two reconstructed cells ranging from 56:44 to 92:8. Asymmetries also pervade subsequent cell generations and can differ between tissues in the same individual. The phylogenies also resolve the spatial embryonic origins and patterning of tissues, revealing a spatial effect in the development of the human brain. Supplemented by data on eleven men, we timed the split between soma and germline, with the earliest observed segregation occurring at the first cell divisions. This research demonstrates that, despite reaching the same ultimate tissue patterns, early bottlenecks and lineage commitments lead to substantial variation in embryonic patterns both within and between individuals.

genomics↗

bioRxiv2020

The mutational landscape of human somatic and germline cells

During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

genomics↗

bioRxiv2019

LINE-1 retrotransposition impacts the genome of human pre implantation embryos and extraembryonic tissues

Long Interspersed Element 1 (LINE-1/L1) is an abundant retrotransposon that has greatly impacted human genome evolution. LINE-1s are responsible for the generation of millions of insertions in the current human population. The characterization of sporadic cases of mosaic individuals carrying pathogenic L1-insertions, suggest that heritable insertions occurs during early embryogenesis. However, the timing and potential genomic impact of LINE-1 mobilization during early embryogenesis is unknown. Here, we demonstrate that inner cell mass of human pre-implantation embryos support the expression and retrotransposition of LINE -1s. Additionally, we show that LINE-1s are expressed in trophectoderm cells of embryos, and identify placenta-restricted endogenous LINE-1 insertions in newborns. Using human embryonic stem cells as a model of post-implantation epiblast cells, we demonstrate ongoing LINE-1 retrotransposition, which can impact expression of targeted genes. Our data demonstrate that LINE-1 retrotransposition starts very shortly after fertilization and may represent a previously underappreciated factor in human biology and disease.

genomics↗

bioRxiv2018

The mutational landscape of normal human endometrial epithelium

All normal somatic cells are thought to acquire mutations. However, characterisation of the patterns and consequences of somatic mutation in normal tissues is limited. Uterine endometrium is a dynamic tissue that undergoes cyclical shedding and reconstitution and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands showed that most are clonal cell populations derived from a recent common ancestor with mutation burdens differing from other normal cell types and manyfold lower than endometrial cancers. Mutational signatures found ubiquitously account for most mutations. Many, in some women potentially all, endometrial glands are colonised by cell clones carrying driver mutations in cancer genes, often with multiple drivers. Total and driver mutation burdens increase with age but are also influenced by other factors including body mass index and parity. Clones with drivers often originate during early decades of life. The somatic mutational landscapes of normal cells differ between cell types and are revealing the procession of neoplastic change leading to cancer.

cancer biology↗

bioRxiv2016

Striking differences in patterns of germline mutation between mice and humans

Recent whole genome sequencing (WGS) studies have estimated that the human germline mutation rate per basepair per generation ([~]1.2-10-8) 1,2 is substantially higher than in mice (3.5-5.4-10-9) 3,4, which has been attributed to more efficient purifying selection due to larger effective population sizes in mice compared to humans.5,6,7. In humans, most germline mutations are paternal in origin and the numbers of mutations per offspring increase markedly with paternal age 2,8,9 and more weakly with maternal age 10. Germline mutations can arise at any stage of the cellular lineage from zygote to gamete, resulting in mutations being represented in different proportion and types of cells, with the earliest embryonic mutations being mosaic in both somatic and germline cells. Here we use WGS of multi-sibling mouse and human pedigrees to show striking differences in germline mutation rate and spectra between the two species, including a dramatic reduction in mutation rate in human spermatogonial stem cell (SSC) divisions, which we hypothesise was driven by selection. The differences we observed between mice and humans result from both biological differences within the same stage of embryogenesis or gametogenesis and species-specific differences in cellular genealogies of the germline.

genomics↗