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Abyzov, A.

Publications and source records attributed to Abyzov, A..

At least 19 recordsLinked to original sources

Somatic mutation landscape revealed by non-invasive iPSC derivation from urine cells

Somatic mutations that arise post-zygotically create genetic diversity among normal human cells and provide key insights into human development and aging. Fibroblast-derived induced pluripotent stem cells (iPSCs) have proved to be a useful system for disease modelling; however, due to their clonal nature, iPSC lines carry somatic mutations inherited from the founder cells, raising concerns about their genomic integrity. At the same time, this clonality enables single-cell-level discovery of somatic mutations and the reconstruction of developmental lineages. In living individuals, though, this approach requires invasive biopsies and is limited to skin-derived lineages. Here, we generated 33 urine-derived iPSC lines from four males representing two father- son relationships, performed shallow whole-genome sequencing of the lines and analyzed somatic mutations. Derived iPSCs representing single cells from urine carried a few hundred of somatic single-nucleotide variants per genome, dominated by endogenous, clock-like mutational signatures and lacking environmental imprints such as UV-associated mutations. Copy-number analysis identified somatic CNVs in most of the lines and revealed higher CNV burdens in fathers than in sons, consistent with age-related structural mosaicism. Shared mutations across lines enabled reconstruction of cell lineage phylogenetic trees. In summary, urine-derived iPSCs showed genomic alterations comparable to those in fibroblast-derived iPSC lines and represent a valuable non-invasive alternative for disease modeling. Overall, this study provides the first genome-wide characterization of somatic mutations in urine-derived iPSCs and establishes them as a practical and non-invasive platform for charting somatic mutation landscapes and tracing developmental lineages in living humans.

genomics↗

Decoding conformational heterogeneity across disordered proteomes

Intrinsically disordered proteins (IDPs) comprise nearly one-third of the human proteome and play key roles in regulation, signaling, and disease, yet their dynamic nature has resisted accurate structural prediction even by the state of the art deep-learning methods. Here we introduce AI-IDP, a framework combining established deep-learning structure prediction of isolated short IDP fragments with their flexible physical restrains-aware assembly to transform sequence information into experiment-consistent conformational ensembles of disordered proteins. AI-IDP reproduces experimental observables across local, medium-range, and global scales, including transient secondary structure, mutation sensitivity, and overall chain dimensions. Applied to more than 3,000 disordered regions across human and non-human proteomes, AI-IDP reveals that transient -helices and polyproline-II conformations are pervasive and evolutionarily tuned features of disorder. By uncovering how sequence encodes conformational heterogeneity, AI-IDP provides a practical framework for understanding the structural and functional logic of disordered proteomes and enables rationally targeting the dynamic protein states that underlie health and disease.

bioinformatics↗

Single cell whole genome and transcriptome sequencing links somatic mutations to cell identity and ancestry

The role of somatic mutations in human development and disease is obscured by difficulties in characterizing mutations at the single cell level and identifying cell types carrying them. Here we analysed somatic genomes of clonal iPSC lines and of single-cells after whole-genome amplification (scWGA) by PTA and ResolveOme from skin fibroblasts, blood and urine of a live donor. Mutation burden and spectra converged across approaches, revealing heterogeneous mutational footprints across cells driven by environmental exposures (UV damage and chemotherapy) and lymphocyte differentiation. Aneuploidies in single cells were detected by all the approaches and were orthogonally validated by Strand-seq. Uniquely, ResolveOme enabled cell-type identification using single-cell transcriptomes. Using a newly developed method accounting for noise and allele drop-out in scWGA, we de novo reconstructed the cell phylogenetic tree for this donor. Together, scWGA establishes a powerful foundation for comprehensive, cell type-aware, lineage-aware profiling of somatic mutations at single cell level.

genomics↗

Allele-specific correction of ATAD3A pathogenic variants via template-free CRISPR-Cas9 editing and gene conversion

Gene conversion is a specific form of homologous recombination (HR), involving the unidirectional transfer of genetic information from one genomic locus to another. CRISPR-Cas9-directed double strand breaks (DSBs) induce both interallelic and interlocus gene conversion in early human embryos and somatic cells, suggesting its potential for correcting pathogenic mutations. However, the key features in mitotic gene conversion, including its efficiency, the length of conversion track, and its dependency on specific recombination proteins, remain largely undefined. Here, we show that allele-specific CRISPR-Cas9-induced DSBs, without exogenous donor templates, can efficiently correct a heterozygous pathogenic variant (c.1582C>T; p.Arg528Trp) in the ATAD3A gene of patient-derived induced pluripotent stem cells (iPSCs). Amplicon-based next-generation sequencing (NGS) revealed that approximately 38%[~]53% of edited iPSCs carried two wild-type ATAD3A alleles. Notably, over 99% of the corrected alleles derived from the homologous chromosome, indicating that the repair occurred mainly via interallelic gene conversion. Long-range amplicon nanopore sequencing coupled with haplotype analysis showed that the majority of gene conversion tracts was less than 2 kilobases in length. Whole-genome sequencing of three corrected iPSC clones showed the absence of large deletions or structural rearrangements at the ATAD3A target site. However, one clone carried a heterozygous deletion in ATAD3B locus, suggesting that CRISPR-Cas9 can introduce off-target genomic alterations. Knockdown of key HR proteins, including RAD51, CtIP, and BRCA1/2, significantly reduced the correction efficiency, indicating that the gene conversion relies on a RAD51-dependent HR pathway. Together, our findings provide compelling evidence that template-free CRISPR-Cas9-mediated interallelic gene conversion can be harnessed to correct disease causing variants in human iPSCs.

genomics↗

Comprehensive benchmarking of somatic mutation detection by the SMaHT Network

Somatic mosaicism is increasingly recognized as a fundamental feature of human biology, yet the detection of somatic mutations remains challenging. The SMaHT Network conducted four large-scale benchmarking experiments involving cell-lines and donor tissues, to evaluate sequencing technologies, experimental approaches, and computational methods for detecting different types of somatic mutations, generating community resource with >1,000x short-read and 100-400x long-read data for each of the nine analyzed samples. We determined effective strategies for utilizing short- and long-reads sequencing for mutation detection and demonstrated that using donor-specific assemblies and human pangenome improved calling, extending mutation catalogs to challenging genomic regions. We benchmarked six duplex technologies and showed that single-cell sequencing resolves cell type-specific mutational patterns and heterogeneity. Our results indicate that bulk, single-cell, and duplex analyses are complementary - and leveraging all three provides comprehensive characterization of mosaicism within tissues. Together, these findings provide a roadmap for accurate, genome-wide somatic mutation discovery and analysis.

genomics↗

Transgenerational transmission of post-zygotic mutations suggests symmetric contribution of first two blastomeres to human germline

Little is known about the origin of germ cells in humans. We previously leveraged post-zygotic mutations to reconstruct zygote-rooted cell lineage ancestry trees in a phenotypically normal woman, termed NC0. Here, by sequencing the genome of her children and their father, we analyzed the transmission of early pre-gastrulation lineages and corresponding mutations across human generations. We found that the germline in NC0 is polyclonal and is founded by at least two cells likely descending from the two blastomeres arising from the first zygotic cleavage. Analyses of public data from several multi-children families and from 1,934 familial quads confirmed this finding in larger cohorts, revealing that known imbalances of up to 90:10 in early lineages allocation in somatic tissues are not reflected in transmission to offspring, establishing a fundamental difference in lineage allocation between the soma and the germline. Analyses of all the data consistently suggest that germline has a balanced 50:50 lineage allocation from the first two blastomeres.

genetics↗

Specification of human regional brain lineages using orthogonal gradients of WNT and SHH in organoids

The repertory of neurons generated by progenitor cells depends on their location along antero-posterior and dorso-ventral axes of the neural tube. To understand if recreating those axes was sufficient to specify human brain neuronal diversity, we designed a mesofluidic device termed Duo-MAPS to expose induced pluripotent stem cells (iPSC) to concomitant orthogonal gradients of a posteriorizing and a ventralizing morphogen, activating WNT and SHH signaling, respectively. Comparison of single cell transcriptomes with fetal human brain revealed that Duo-MAPS-patterned organoids generated the major neuronal lineages of the forebrain, midbrain, and hindbrain. Morphogens crosstalk translated into early patterns of gene expression programs predicting the generation of specific brain lineages. Human iPSC lines from six different genetic backgrounds showed substantial differences in response to morphogens, suggesting that interindividual genomic and epigenomic variations could impact brain lineages formation. Morphogen gradients promise to be a key approach to model the brain in its entirety.

neuroscience↗

Interneuron loss and microglia activation by transcriptome analyses in the basal ganglia of Tourette syndrome

Tourette syndrome (TS) is a disorder of high-order integration of sensory, motor, and cognitive functions afflicting as many as 1 in 150 children and characterized by motor hyperactivity and tics. Despite high familial recurrence rates, a few risk genes and no biomarkers have emerged as causative or predisposing factors. The syndrome is believed to originate in basal ganglia, where patterns of motor programs are encoded. Postmortem immunocytochemical analyses of brains with severe TS revealed decreases in cholinergic, fast-spiking parvalbumin, and somatostatin interneurons within the striatum (caudate and putamen nuclei). Here, we performed single cell transcriptomic and chromatin accessibility analyses of the caudate nucleus from 6 adult TS and 6 control post-mortem brains. The data reproduced the known cellular composition of the adult human striatum, including a majority of medium spiny neurons (MSN) and small populations of GABAergic and cholinergic interneurons. Comparative analysis revealed that interneurons were decreased by roughly 50% in TS brains, while no difference was observed for other cell types. Differential gene expression analysis suggested that mitochondrial function, and specifically oxidative metabolism, in MSN and synaptic function in interneurons are both impaired in TS subjects. Furthermore, such an impairment was coupled with activation of immune response pathways in microglia. Also, our data explicitly link gene expression changes to changes in cis-regulatory activity in the corresponding cell types, suggesting de-regulation as a factor for the etiology of TS. These findings expand on previous research and suggest that impaired modulation of striatal function by interneurons may be the origin of TS symptoms.

neuroscience↗

Enhancer-driven regulatory network of forebrain human development provides insights into autism

Cell differentiation is orchestrated by transcription factors (TFs) binding to enhancers, shaping gene regulatory networks that drive neuronal lineage specification. Deciphering these enhancer-driven networks in human forebrain development is essential for understanding the genetic basis of neurodevelopmental disorders. Through integrative epigenomic and transcriptomic analyses of human forebrain organoids derived from 10 individuals with autism spectrum disorder (ASD) and their neurotypical fathers, we constructed a comprehensive enhancer-driven gene regulatory network (GRN) of early neurodevelopment. This GRN revealed hierarchical regulatory transitions guiding neuronal differentiation and was experimentally validated via CRISPR interference (CRISPRi) and loss-of-function analyses. A subnetwork linked ASD-associated transcriptomic alterations to dysregulated TF activity, implicating FOXG1, BHLHE22, EOMES, and NEUROD2 as key regulators of excitatory neuron specification in macrocephalic ASD. These findings suggest that ASD disrupts enhancer-driven regulatory frameworks, altering neuronal cell fate decisions in the developing fetal brain.

genomics↗

Characterization of enhancer activity in early human neurodevelopment using Massively parallel reporter assay (MPRA) and forebrain organoids

AO_SCPLOWBSTRACTC_SCPLOWRegulation of gene expression through enhancers is one of the major processes shaping the structure and function of the human brain during development. High-throughput assays have predicted thousands of enhancers involved in neurodevelopment, and confirming their activity through orthogonal functional assays is crucial. Here, we utilized Massively Parallel Reporter Assays (MPRAs) in stem cells and forebrain organoids to evaluate the activity of [~]7,000 gene-linked enhancers previously identified in human fetal tissues and brain organoids. We used a Gaussian mixture model to evaluate the contribution of background noise in the measured activity signal to confirm the activity of [~]35% of the tested enhancers, with most showing temporal-specific activity, suggesting their evolving role in neurodevelopment. The temporal specificity was further supported by the correlation of activity with gene expression. Our findings provide a valuable gene regulatory resource to the scientific community. AO_SCPLOWUTHORC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSUMMARYC_SCPLOWEnhancers are non-coding elements that play a crucial role in the regulation of gene expression during brain development. Despite the availability of various techniques available to identify enhancers, their functional activity is relatively less understood, leaving a gap in our understanding of how enhancer behavior might regulate complex transitions of neurodevelopment. To address this, we utilized forebrain organoids, a 3D model system which closely mimics the complex cellular environment of the developing human brain, and employed Massively Parallel Reporter Assay (MPRA) to validate enhancer activity at various stages of forebrain differentiation, from induced pluripotent stem cells (iPSCs) to neuronal progenitors and cortical neurons. Our study provides a comprehensive catalog of over 2,300 enhancers, showcasing their temporal activity profiles during early neuronal development and offering valuable insights into their likely biological functions. This research advances our understanding of enhancer dynamics in brain development and offers new avenues for further investigations in this field.

genomics↗

Clonally selected lines after CRISPR/Cas editing are not isogenic

The CRISPR-Cas9 system has enabled researchers to precisely modify/edit the sequence of a genome. A typical editing experiment consists of two steps: (i) editing cultured cells; (ii) cell cloning and selection of clones with and without intended edit, presumed to be isogenic. The application of CRISPR-Cas9 system may result in off-target edits, while cloning will reveal culture-acquired mutations. We analyzed the extent of the former and the latter by whole genome sequencing in three experiments involving separate genomic loci and conducted by three independent laboratories. In all experiments we hardly found any off-target edits, while detecting hundreds to thousands of single nucleotide mutations unique to each clone after relatively short culture of 10-20 passages. Notably, clones also differed in copy number alterations that were several kb to several mb in size and represented the largest source of genomic divergence among clones. We suggest that screening of clones for mutations and copy number alterations acquired in culture is a necessary step to allow correct interpretation of DNA editing experiments. Furthermore, since culture associated mutations are inevitable, we propose that experiments involving derivation of clonal lines should compare a mix of multiple unedited lines and a mix of multiple edited lines.

genomics↗

Comprehensive multiomic profiling of somatic mutations in malformations of cortical development

Malformations of cortical development (MCD) are neurological conditions displaying focal disruption of cortical architecture and cellular organization arising during embryogenesis, largely from somatic mosaic mutations. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fractions in brain tissue resected to treat epilepsy. Here, we report a genetic atlas from 317 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation and single-cell sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associating distinct pathophysiological and clinical phenotypes. The unique spatiotemporal expression patterns identified by comparing single-nucleus transcriptional sequences of mutated genes in control and patient brains implicate critical roles in excitatory neurogenic pools during brain development, and in promoting neuronal hyperexcitability after birth.

genetics↗

ASD modelling in organoids reveals imbalance of excitatory cortical neuron subtypes during early neurogenesis

There is no clear genetic etiology or convergent pathophysiology for autism spectrum disorders (ASD). Using cortical organoids and single-cell transcriptomics, we modeled alterations in the formation of the forebrain between sons with idiopathic ASD and their unaffected fathers in thirteen families. Alterations in the transcriptome suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between the excitatory neurons of the dorsal cortical plate and other lineages such as the early-generated neurons from the putative preplate. The imbalance stemmed from a divergent expression of transcription factors driving cell fate during early cortical development. While we did not find probands genomic variants explaining the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and developmental transcriptome in idiopathic ASD.

neuroscience↗

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↗

All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons

Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing cells genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell from exhaustive comparison of cells genomes to each other without data for bulk(s). Based on all pair-wise comparisons, every variant call (point mutation, indel, and structural variant) is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing. All2 is freely available at https://github.com/abyzovlab/All2.

bioinformatics↗

CNVpytor: a tool for CNV/CNA detection and analysis from read depth and allele imbalance in whole genome sequencing

Detecting copy number variations (CNVs) and copy number alterations (CNAs) based on whole genome sequencing data is important for personalized genomics and treatment. CNVnator is one of the most popular tools for CNV/CNA discovery and analysis based on read depth (RD). Herein, we present an extension of CNVnator developed in Python -- CNVpytor. CNVpytor inherits the reimplemented core engine of its predecessor and extends visualization, modularization, performance, and functionality. Additionally, CNVpytor uses B-allele frequency (BAF) likelihood information from single nucleotide polymorphism and small indels data as additional evidence for CNVs/CNAs and as primary information for copy number neutral losses of heterozygosity. CNVpytor is significantly faster than CNVnator--particularly for parsing alignment files (2 to 20 times faster)--and has (20-50 times) smaller intermediate files. CNV calls can be filtered using several criteria and annotated. Modular architecture allows it to be used in shared and cloud environments such as Google Colab and Jupyter notebook. Data can be exported into JBrowse, while a lightweight plugin version of CNVpytor for JBrowse enables nearly instant and GUI-assisted analysis of CNVs by any user. CNVpytor release and the source code are available on GitHub at https://github.com/abyzovlab/CNVpytor under the MIT license.

bioinformatics↗

DeepMosaic: Control-independent mosaic single nucleotide variant detection using deep convolutional neural networks

Introductory paragraphMosaic variants (MVs) reflect mutagenic processes during embryonic development1 and environmental exposure2, accumulate with aging, and underlie diseases such as cancer and autism3. The detection of MVs has been computationally challenging due to sparse representation in non-clonally expanded tissues. While heuristic filters and tools trained on clonally expanded MVs with high allelic fractions are proposed, they show relatively lower sensitivity and more false discoveries4-9. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs, and a convolutional neural networks-based classification module for control-independent MV detection. DeepMosaic achieved higher accuracy compared with existing methods on biological and simulated sequencing data, with a 96.34% (158/164) experimental validation rate. Of 932 mosaic variants detected by DeepMosaic in 16 whole genome sequenced samples, 21.89-58.58% (204/932-546/932) MVs were overlooked by other methods. Thus, DeepMosaic represents a highly accurate MV classifier that can be implemented as an alternative or complement to existing methods.

genomics↗

Early developmental asymmetries in cell lineage trees in living individuals

Post-zygotic mosaic mutations can be used to track cell lineages in humans. By using cell cloning and induced pluripotent cell lines, we analyzed early cell lineages in two living individuals (a patient and a control), and a postmortem human specimen. Of ten reconstructed post-zygotic divisions, none resulted in balanced contributions of daughter lineages to tissues. In both living individuals one of two lineages from the first cleavage was dominant across tissues, with 90% frequency in blood. We propose that the efficiency of DNA repair contributes to lineage imbalance. Allocation of lineages in postmortem brain correlated with anterior-posterior axis, associating lineage history with cell fate choices in embryos. Recurrence of germline variants as mosaic suggested that certain loci may be particularly susceptible to mutagenesis. We establish a minimally invasive framework for defining cell lineages in any living individual, which paves the way for studying their relevance in health and disease.

genomics↗