Somatic mutation in single human neurons tracks developmental and transcriptional history

Advances in single-cell DNA sequencing enable insights into human somatic mosaicism

DNA sequencing from bulk or clonal human tissues has shown that genetic mosaicism is common and contributes to both cancer and non-cancerous disorders. However, single-cell resolution is required to understand the full genetic heterogeneity that exists within a tissue and the mechanisms that lead to somatic mosaicism. Single-cell DNA-sequencing technologies have traditionally trailed behind those of single-cell transcriptomics and epigenomics, largely because most applications require whole-genome amplification before costly whole-genome sequencing. Now, recent technological and computational advances are enabling the use of single-cell DNA sequencing to tackle previously intractable problems, such as delineating the genetic landscape of tissues with complex clonal patterns, of samples where cellular material is scarce and of non-cycling, postmitotic cells. Single-cell genomes are also revealing the mutational patterns that arise from biological processes or disease states, and have made it possible to track cell lineage in human tissues. These advances in our understanding of tissue biology and our ability to identify disease mechanisms will ultimately transform how disease is diagnosed and monitored.

RNA sequence analysis of somatic mutations in aging and Parkinson's Disease

Parkinson's Disease (PD) is an age-related neurodegenerative disorder that has been associated with increased DNA damage. To test if PD is associated with increased somatic mutations, we analyzed RNA-seq data in whole blood from 5 visits of the Parkinson's Progression Markers Initiative for clonally amplified somatic variants. Comprehensive analysis of RNA-sequencing data revealed a total of 5,927 somatic variants (2.4 variants per sample on average). Mutation frequencies were significantly elevated in PD subjects as compared to age-matched controls at the time of the last visit. This was confirmed by RNA analysis of substantia nigra. By contrast, the fraction of carriers with clonal hematopoiesis, was significantly reduced in old PD patients as compared to old healthy controls. These results indicate that while the overall mutation rate is higher in PD, specific clonally amplified mutations are protective against PD, as has been found for Alzheimer's Disease.

Neuronal somatic mutations are increased in multiple sclerosis lesions

Neuroinflammation underpins neurodegeneration and clinical progression in multiple sclerosis (MS), but knowledge of processes linking these disease mechanisms remains incomplete. Here we investigated somatic single-nucleotide variants (sSNVs) in the genomes of 106 single neurons from post-mortem brain tissue of ten MS cases and 16 controls to determine whether somatic mutagenesis is involved. We observed an increase of 43.9 sSNVs per year in neurons from chronic MS lesions, a 2.5 times faster rate than in neurons from normal-appearing MS and control tissues. This difference was equivalent to 1,291 excess sSNVs in lesion neurons at 70 years of age compared to controls. We performed mutational signature analysis to investigate mechanisms underlying neuronal sSNVs and identified a signature characteristic of lesions with a strong, age-associated contribution to sSNV counts. This research suggests that neuroinflammation is mutagenic in the MS brain, potentially contributing to disease progression.

The strength of organ, tissue, and body field effects determines the frequency of all neoplasia

In 1953, Danely Slaughter proposed the concept of field cancerization, or field effect, to explain the development of additional neoplasia of similar type. A recent theory (de Groen, 2022) states that all DNA is exposed to a constant source of damage, resulting in a constant rate of germline and somatic DNA mutations. If the field effect and constant mutation theories are correct and a single somatic mutation causes the transition from non-neoplastic to neoplastic phenotype, then all rates of neoplasia formation can be modeled by exponential equations containing a single variable that determines the chance of phenotype transition. In this perspective, studies from 1953 till 2021 originating from America, Europe, and Asia about head, chest, abdomen, pelvic, and skin neoplasia were reviewed and showed consistent field effects that are modeled by tapering exponential equations containing a single variable defining field effect strength; Pearson and linear correlation coefficients for observed and modeled data range from 0.994 to 1. Thus, existing data are compatible with a constant rate of DNA damage. Organ-specific, tissue-specific, or body-wide mutagenesis conditions determine the rate of neoplasia development and explain the co-occurrence of seemingly unrelated neoplasia at predictable frequencies. Shared risk factors explain increased risk for additional neoplasia in persons with one neoplastic lesion.

Measuring Longitudinal Genome-wide Clonal Evolution of Pediatric Acute Lymphoblastic Leukemia at Single-Cell Resolution

Over 80% of children with acute lymphoblastic leukemia (pALL) can be cured by treating them with multiple chemotherapeutic agents administered over several years, whereas pALL is incurable with 1-3 medications, suggesting significant variation in drug susceptibility across clonal populations. While bulk sequencing studies indicate that pALL cells contain relatively few genetic variants compared to other cancers, the true extent of genetic diversity at the single-cell level remains unknown. Here, we used three complementary approaches to investigate pALL genetic heterogeneity: error-corrected bulk sequencing, single-cell exome sequencing, and primary template-directed amplification (PTA)-enabled single-cell genome sequencing. We discovered that some ETV6-RUNX1 samples harbor multiple independent ras clones and that individual pALL cells harbor substantially more mutations (mean 3,553 per cell) than detected in bulk samples (mean 965 mutations), with variant signatures suggesting both early and late APOBEC-driven mutagenesis in ETV6-RUNX1 patients. Using PTA-based phylogenetic analysis of over 150 single-cell genomes from four pALL patients, we identified heritable phenotypes associated with specific genetic alterations, including some low-frequency clones that are preferentially selected for during chemotherapy treatment. Our findings reveal previously undetected genetic diversity in pALL and suggest that pre-existing mutations influence treatment response, with implications for future therapeutic strategies. This study provides a high-resolution framework for understanding cancer clonal evolution during treatment, yielding important new insights for developing more effective therapeutic approaches for pALL.

Comparing the predictors of mutability among healthy human tissues inferred from mutations in single-cell genome data

Studying mutation in healthy somatic tissues is the key for understanding the genesis of cancer and other genetic diseases. Mutation rate varies from site to site in the human genome by up to 100-fold and is influenced by numerous epigenetic and genetic factors including GC content, trinucleotide sequence context, and DNAse accessibility. These factors influence mutation at both local and regional scales and are often interrelated with one another, meaning that predicting mutability or uncovering its drivers requires modelling multiple factors and scales simultaneously. Historically, most investigations have focused either on analyzing the local sequence scale through triplet signatures or on examining the impact of epigenetic processes at larger scales, but not both concurrently. Additionally, sequencing technology limitations have restricted analyses of healthy mutations to coding regions (RNA-seq) or to those that have been influenced by selection (e.g. bulk samples from cancer tissue). Here, we leverage single-cell mutations and present a comprehensive analysis of epigenetic and genetic factors at multiple scales in the germline and 3 healthy somatic tissues. We create models that predict mutability with on average 2% error and find up to 63-fold variation among sites within the same tissue. We observe varying degrees of similarity between tissues: the mutability of genomic positions was 93.4% similar between liver and germline tissues, but sites in germline and skin were only 85.9% similar. We observe both universal and tissue-specific mutagenic processes in healthy tissues, with implications for understanding the maintenance of germline vs soma and the mechanisms underlying early tumorigenesis.

The lives of cells, recorded

A paradigm for biology is emerging in which cells can be genetically programmed to write their histories into their own genomes. These records can subsequently be read, and the cellular histories reconstructed, which for each cell could include a record of its lineage relationships, extrinsic influences, internal states and physical locations, over time. DNA recording has the potential to transform the way that we study developmental and disease processes. Recent advances in genome engineering are driving the development of systems for DNA recording, and meanwhile single-cell and spatial omics technologies increasingly enable the recovery of the recorded information. Combined with advances in computational and phylogenetic inference algorithms, the DNA recording paradigm is beginning to bear fruit. In this Perspective, we explore the rationale and technical basis of DNA recording, what aspects of cellular biology might be recorded and how, and the types of discovery that we anticipate this paradigm will enable.

From the genome's perspective: Bearing somatic retrotransposition to leverage the regulatory potential of L1 RNAs

Transposable elements (TEs) are mobile genomic elements constituting a big fraction of eukaryotic genomes. They ignite an evolutionary arms race with host genomes, which in turn evolve strategies to restrict their activity. Despite being tightly repressed, TEs display precisely regulated expression patterns during specific stages of mammalian development, suggesting potential benefits for the host. Among TEs, the long interspersed nuclear element (LINE-1 or L1) has been found to be active in neurons. This activity prompted extensive research into its possible role in cognition. So far, no specific cause-effect relationship between L1 retrotransposition and brain functions has been conclusively identified. Nevertheless, accumulating evidence suggests that interactions between L1 RNAs and RNA/DNA binding proteins encode specific messages that cells utilize to activate or repress entire transcriptional programs. We summarize recent findings highlighting the activity of L1 RNAs at the non-coding level during early embryonic and brain development. We propose a hypothesis suggesting a mutualistic relationship between L1 mRNAs and the host cell. In this scenario, cells tolerate a certain rate of retrotransposition to leverage the regulatory effects of L1s as non-coding RNAs on potentiating their mitotic potential. In turn, L1s benefit from the cell's proliferative state to increase their chance to mobilize.

Somatic Genomic and Transcriptomic Changes in Single Ischemic Human Heart Cardiomyocytes

Heart failure is a multifaceted syndrome contributing significantly to mortality and hospitalization rates among the global population1. One of the prevalent causes of heart failure is ischemic heart disease (IHD), often caused by a blockage in a coronary artery, ultimately leading to the loss of myocardial tissue and contractile force2. The impact of this ischemic ambiance on the cardiomyocyte genome and transcriptome has not been thoroughly studied. During normal aging, cardiomyocytes progressively accumulate somatic mutations faster than many dividing cells, suggesting that internal and external factors specific to cardiomyocytes might influence this accumulation3. In this study, we analyzed single-cell whole-genome and transcriptome data from the left ventricle of 5 individuals with IHD and 10 healthy control individuals. We found that somatic DNA alterations significantly increase in IHD cardiomyocytes, with distinct mutational patterns indicating a disrupted DNA repair system and a cytotoxic environment, potentially associated with increased inflammatory response in the myocardium and a compensatory anti-inflammatory response in IHD. An in vitro iPS-derived hypoxic cardiomyocyte mutational profile indicates similar mutational spectra. Transcriptomic analysis revealed increased expression of EGR1, FOS, and collagen genes in ischemic heart cardiomyocytes, leading to a more fibrotic heart. The aberrant accumulation of DNA alterations and changes in transcriptional patterns in the ischemic heart cardiomyocytes provide insight into the development of IHD.

DNA damage and its links to neuronal aging and degeneration

DNA damage is a major risk factor for the decline of neuronal functions with age and in neurodegenerative diseases. While how DNA damage causes neurodegeneration is still being investigated, innovations over the past decade have provided significant insights into this issue. Breakthroughs in next-generation sequencing methods have begun to reveal the characteristics of neuronal DNA damage hotspots and the causes of DNA damage. Chromosome conformation capture-based approaches have shown that, while DNA damage and the ensuing cellular response alter chromatin topology, chromatin organization at damage sites also affects DNA repair outcomes in neurons. Additionally, neuronal activity results in the formation of programmed DNA breaks, which could burden DNA repair mechanisms and promote neuronal dysfunction. Finally, emerging evidence implicates DNA damage-induced inflammation as an important contributor to the age-related decline in neuronal functions. Together, these discoveries have ushered in a new understanding of the significance of genome maintenance for neuronal function.

Somatic Mosaicism in Brain Disorders

Research efforts over the past decade have defined the genetic landscape of somatic variation in the brain. Neurons accumulate somatic mutations from development through aging with potentially profound functional consequences. Recent studies have revealed the contribution of somatic mosaicism to various brain disorders including focal epilepsy, neuropsychiatric disease, and neurodegeneration. One notable finding is that the effect of somatic mosaicism on clinical outcomes can vary depending on contextual factors, such as the developmental origin of a variant or the number and type of cells affected. In this review, we highlight current knowledge regarding the role of somatic mosaicism in brain disorders and how biological context can mediate phenotypes. First, we identify the origins of brain somatic variation throughout the lifespan of an individual. Second, we explore recent discoveries that suggest somatic mosaicism contributes to various brain disorders. Finally, we discuss neuropathological associations of brain mosaicism in different biological contexts and potential clinical utility.

Single-cell omics: experimental workflow, data analyses and applications

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

Recording Lineage History with Cellular Barcodes in the Mammary Epithelium and in Breast Cancer

Lineage tracing methods have extensively advanced our understanding of physiological cell behaviour in vivo and in situ and have vastly contributed to decipher the phylogeny and cellular hierarchies during normal and tumour development. In recent years, increasingly complex systems have been developed to track thousands of cells within a given tissue or even entire organisms. Cellular barcoding comprises all techniques designed to genetically label single cells with unique DNA sequences or with a combination of fluorescent proteins, in order to trace their history and lineage production in space and time. We distinguish these two types of cellular barcoding as genetic or optical barcodes. Furthermore, transcribed cellular barcodes can integrate the lineage information with single-cell profiling of each barcoded cell. This enables the potential identification of specific markers or signalling pathways defining distinct stem cell states during development, but also signals promoting tumour growth and metastasis or conferring therapy resistance.In this chapter, we describe recent advances in cellular barcoding technologies and outline experimental and computational challenges. We discuss the biological questions that can be addressed using single-cell dynamic lineage tracing, with a focus on the study of cellular hierarchies in the mammary epithelium and in breast cancer.

HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling

Single-cell DNA sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple and accessible assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on a modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 17,000 cells.

Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system

Single-cell and single-nucleus genomic approaches can provide unbiased and multimodal insights. Here, we discuss what constitutes a molecular cell atlas and how to leverage single-cell omics data to generate hypotheses and gain insights into cell transitions in development and disease of the nervous system. We share points of reflection on what to consider during study design and implementation as well as limitations and pitfalls.

Methods and applications of genome-wide profiling of DNA damage and rare mutations

DNA damage is a threat to genome integrity and can be a cause of many human diseases, owing to either changes in the chemical structure of DNA or conversion of the damage into a mutation, that is, a permanent change in DNA sequence. Determining the exact positions of DNA damage and ensuing mutations in the genome are important for identifying mechanisms of disease aetiology when characteristic mutations are prevalent and probably causative in a particular disease. However, this approach is challenging particularly when levels of DNA damage are low, for example, as a result of chronic exposure to environmental agents or certain endogenous processes, such as the generation of reactive oxygen species. Over the past few years, a comprehensive toolbox of genome-wide methods has been developed for the detection of DNA damage and rare mutations at single-nucleotide resolution in mammalian cells. Here, we review and compare these methods, describe their current applications and discuss future research questions that can now be addressed.

Translational Approach to Social Isolation During a Global Pandemic: Hippocampal Somatic Mutation and Stress

OBJECTIVE

The coronavirus disease-2019 (COVID-19) pandemic's social isolation has significantly impacted mental health, increasing depression and anxiety. This study explores the effects of social isolation on both humans and mice, focusing on behavioral changes and hippocampal protein expression. It also investigates genetic alterations through single-cell RNA and whole-genome sequencing (WGS).

METHODS

Here we conducted behavioral studies, protein expression studies, single-nucleus sequencing (snRNAseq), and WGS of the hippocampus of mice that underwent early maternal separation and social isolation, and a demographic study of community populations who had been self-quarantined owing to COVID-19 exposure to investigate the link between somatic mutations and stress due to social isolation.

RESULTS

The demographic study demonstrated more negative mental health findings among individuals who live alone or are single. Mice subjected to early maternal separation and social isolation demonstrated increased anxiety-like behaviors and stress-related corticotropin-releasing hormone receptor 1, and neurogenesis-related sex-determining region Y-box 2 and doublecortin expression. In snRNA-seq, differences, such as transthyretin increase, were observed in the maternal separation group, and somatic mutations, including insertion in the intron site of Tmem267, were observed in the social isolation group on WGS.

CONCLUSION

The results of this study suggest that stress, such as social isolation, can cause changes at the genetic level, as well as behavioral and brain protein changes.

Human Brain Ancestral Barcodes

Dynamic CpG methylation "barcodes" were read from 15,000 to 21,000 single cells from three human male brains. To overcome sparse sequencing coverage, the barcode had ~31,000 rapidly fluctuating X-chromosome CpG sites (fCpGs), with at least 500 covered sites per cell and at least 30 common sites between cell pairs (average of ~48). Barcodes appear to start methylated and record mitotic ages because excitatory neurons and glial cells that emerge later in development were less methylated. Barcodes are different between most cells, with average pairwise differences (PWDs) of ~0.5 between cells. About 10 cell pairs per million were more closely related with PWDs < 0.05. Barcodes appear to record ancestry and reconstruct trees where more related cells had similar phenotypes, albeit some pairs had phenotypic differences. Inhibitory neurons showed more evidence of tangential migration than excitatory neurons, with related cells in different cortical regions. fCpG barcodes become polymorphic during development and can distinguish between thousands of human cells.

Defining heritability, plasticity, and transition dynamics of cellular phenotypes in somatic evolution

Single-cell sequencing has characterized cell state heterogeneity across diverse healthy and malignant tissues. However, the plasticity or heritability of these cell states remains largely unknown. To address this, we introduce PATH (phylogenetic analysis of trait heritability), a framework to quantify cell state heritability versus plasticity and infer cell state transition and proliferation dynamics from single-cell lineage tracing data. Applying PATH to a mouse model of pancreatic cancer, we observed heritability at the ends of the epithelial-to-mesenchymal transition spectrum, with higher plasticity at more intermediate states. In primary glioblastoma, we identified bidirectional transitions between stem- and mesenchymal-like cells, which use the astrocyte-like state as an intermediary. Finally, we reconstructed a phylogeny from single-cell whole-genome sequencing in B cell acute lymphoblastic leukemia and delineated the heritability of B cell differentiation states linked with genetic drivers. Altogether, PATH replaces qualitative conceptions of plasticity with quantitative measures, offering a framework to study somatic evolution.

Somatic mutations in aging and disease

Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.

Building the brain mosaic: an expanded view

The complexity of the brain is closely tied to its nature as a genetic mosaic, wherein each cell is distinguished by a unique constellation of somatic variants that contribute to functional and phenotypic diversity. Postzygotic variation arising during neurogenesis is recognized as a key contributor to brain mosaicism; however, recent advances have broadened our understanding to include sources of neural genomic diversity that develop throughout the entire lifespan, from embryogenesis through aging. Moving beyond the traditional confines of neurodevelopment, in this review, we delve into the complex mechanisms that enable various origins of brain mosaicism.

Neuropathologically directed profiling of PRNP somatic and germline variants in sporadic human prion disease

Creutzfeldt-Jakob Disease (CJD), the most common human prion disease, is associated with pathologic misfolding of the prion protein (PrP), encoded by the PRNP gene. Of human prion disease cases, < 1% were transmitted by misfolded PrP, ~ 15% are inherited, and ~ 85% are sporadic (sCJD). While familial cases are inherited through germline mutations in PRNP, the cause of sCJD is unknown. Somatic mutations have been hypothesized as a cause of sCJD, and recent studies have revealed that somatic mutations accumulate in neurons during aging. To investigate the hypothesis that somatic mutations in PRNP may underlie sCJD, we performed deep DNA sequencing of PRNP in 205 sCJD cases and 170 age-matched non-disease controls. We included 5 cases of Heidenhain variant sporadic CJD (H-sCJD), where visual symptomatology and neuropathology implicate localized initiation of prion formation, and examined multiple regions across the brain including in the affected occipital cortex. We employed Multiple Independent Primer PCR Sequencing (MIPP-Seq) with a median depth of > 5000× across the PRNP coding region and analyzed for variants using MosaicHunter. An allele mixing experiment showed positive detection of variants in bulk DNA at a variant allele fraction (VAF) as low as 0.2%. We observed multiple polymorphic germline variants among individuals in our cohort. However, we did not identify bona fide somatic variants in sCJD, including across multiple affected regions in H-sCJD, nor in control individuals. Beyond our stringent variant-identification pipeline, we also analyzed VAFs from raw sequencing data, and observed no evidence of prion disease enrichment for the known germline pathogenic variants P102L, D178N, and E200K. The lack of PRNP pathogenic somatic mutations in H-sCJD or the broader cohort of sCJD suggests that clonal somatic mutations may not play a major role in sporadic prion disease. With H-sCJD representing a localized presentation of neurodegeneration, this serves as a test of the potential role of clonal somatic mutations in genes known to cause familial neurodegeneration.

Adaptive and Maladaptive DNA Breaks in Neuronal Physiology and Alzheimer's Disease

DNA strand breaks excessively accumulate in the brains of patients with Alzheimer's disease (AD). While traditionally considered random, deleterious events, neuron activity itself induces DNA breaks, and these "adaptive" breaks help mediate synaptic plasticity and memory formation. Recent studies mapping the brain DNA break landscape reveal that despite a net increase in DNA breaks in ectopic genomic hotspots, adaptive DNA breaks around synaptic genes are lost in AD brains, and this is associated with transcriptomic dysregulation. Additionally, relationships exist between mitochondrial dysfunction, a hallmark of AD, and DNA damage, such that mitochondrial dysfunction may perturb adaptive DNA break formation, while DNA breaks may conversely impair mitochondrial function. A failure of DNA break physiology could, therefore, potentially contribute to AD pathogenesis.

Mitochondrial genetics through the lens of single-cell multi-omics

Mitochondria carry their own genetic information encoding for a subset of protein-coding genes and translational machinery essential for cellular respiration and metabolism. Despite its small size, the mitochondrial genome, its natural genetic variation and molecular phenotypes have been challenging to study using bulk sequencing approaches, due to its variation in cellular copy number, non-Mendelian modes of inheritance and propensity for mutations. Here we highlight emerging strategies designed to capture mitochondrial genetic variation across individual cells for lineage tracing and studying mitochondrial genetics in primary human cells and clinical specimens. We review recent advances surrounding single-cell mitochondrial genome sequencing and its integration with functional genomic readouts, including leveraging somatic mitochondrial DNA mutations as clonal markers that can resolve cellular population dynamics in complex human tissues. Finally, we discuss how single-cell whole mitochondrial genome sequencing approaches can be utilized to investigate mitochondrial genetics and its contribution to cellular heterogeneity and disease.

Neuropathologically-directed profiling of PRNP somatic and germline variants in sporadic human prion disease

Creutzfeldt-Jakob Disease (CJD), the most common human prion disease, is associated with pathologic misfolding of the prion protein (PrP), encoded by the PRNP gene. Of human prion disease cases, ~1% were transmitted by misfolded PrP, ~15% are inherited, and ~85% are sporadic (sCJD). While familial cases are inherited through germline mutations in PRNP, the cause of sCJD is unknown. Somatic mutations have been hypothesized as a cause of sCJD, and recent studies have revealed that somatic mutations accumulate in neurons during aging. To investigate the hypothesis that somatic mutations in PRNP may underlie sCJD, we performed deep DNA sequencing of PRNP in 205 sCJD cases and 170 age-matched non-disease controls. We included 5 cases of Heidenhain variant sporadic CJD (H-sCJD), where visual symptomatology and neuropathology implicate focal initiation of prion formation, and examined multiple regions across the brain including in the affected occipital cortex. We employed Multiple Independent Primer PCR Sequencing (MIPP-Seq) with a median depth of >5,000X across the PRNP coding region and analyzed for variants using MosaicHunter. An allele mixing experiment showed positive detection of variants in bulk DNA at a variant allele fraction (VAF) as low as 0.2%. We observed multiple polymorphic germline variants among individuals in our cohort. However, we did not identify bona fide somatic variants in sCJD, including across multiple affected regions in H-sCJD, nor in control individuals. Beyond our stringent variant-identification pipeline, we also analyzed VAFs from raw sequencing data, and observed no evidence of prion disease enrichment for the known germline pathogenic variants P102L, D178N, and E200K. The lack of PRNP pathogenic somatic mutations in H-sCJD or the broader cohort of sCJD suggests that clonal somatic mutations may not play a major role in sporadic prion disease. With H-sCJD representing a focal presentation of neurodegeneration, this serves as a test of the potential role of clonal somatic mutations in genes known to cause familial neurodegeneration.

Impact of double-strand breaks induced by uv radiation on neuroinflammation and neurodegenerative disorders

Exposure to UV affects the development and growth of a wide range of organisms. Nowadays, researchers are focusing on the impact of UV radiation and its underlying molecular mechanisms, as well as devising strategies to mitigate its harmful effects. Different forms of UV radiation, their typical exposure effects, the impact of UV on DNA integrity, and the deterioration of genetic material are discussed in this review; furthermore, we also review the effects of UV radiation that affect the biological functions of the organisms. Subsequently, we address the processes that aid organisms in navigating the damage in genetic material, neuroinflammation, and neurodegeneration brought on by UV-mediated double-strand breaks. To emphasize the molecular pathways, we conclude the review by going over the animal model studies that highlight the genes and proteins that are impacted by UV radiation.

Genomic Mosaicism of the Brain: Origin, Impact, and Utility

Genomic mosaicism describes the phenomenon where some but not all cells within a tissue harbor unique genetic mutations. Traditionally, research focused on the impact of genomic mosaicism on clinical phenotype-motivated by its involvement in cancers and overgrowth syndromes. More recently, we increasingly shifted towards the plethora of neutral mosaic variants that can act as recorders of cellular lineage and environmental exposures. Here, we summarize the current state of the field of genomic mosaicism research with a special emphasis on our current understanding of this phenomenon in brain development and homeostasis. Although the field of genomic mosaicism has a rich history, technological advances in the last decade have changed our approaches and greatly improved our knowledge. We will provide current definitions and an overview of contemporary detection approaches for genomic mosaicism. Finally, we will discuss the impact and utility of genomic mosaicism.

Reconstructing phylogenetic trees from genome-wide somatic mutations in clonal samples

Phylogenetic trees are a powerful means to display the evolutionary history of species, pathogens and, more recently, individual cells of the human body. Whole-genome sequencing of laser capture microdissections or expanded stem cells has allowed the discovery of somatic mutations in clones, which can be used as natural barcodes to reconstruct the developmental history of individual cells. Here we describe Sequoia, our pipeline to reconstruct lineage trees from clones of normal cells. Candidate somatic mutations are called against the human reference genome and filtered to exclude germline mutations and artifactual variants. These filtered somatic mutations form the basis for phylogeny reconstruction using a maximum parsimony framework. Lastly, we use a maximum likelihood framework to explicitly map mutations to branches in the phylogenetic tree. The resulting phylogenies can then serve as a basis for many subsequent analyses, including investigating embryonic development, tissue dynamics in health and disease, and mutational signatures. Sequoia can be readily applied to any clonal somatic mutation dataset, including single-cell DNA sequencing datasets, using the commands and scripts provided. Moreover, Sequoia is highly flexible and can be easily customized. Typically, the runtime of the core script ranges from minutes to an hour for datasets with a moderate number (50,000-150,000) of variants. Competent bioinformatic skills, including in-depth knowledge of the R programming language, are required. A high-performance computing cluster (one that is capable of running mutation-calling algorithms and other aspects of the analysis at scale) is also required, especially if handling large datasets.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Single-nucleus multi-omic profiling of polyploid heart nuclei identifies fusion-derived cardiomyocytes in the human heart

Understanding the mechanisms of polyploidization in cardiomyocytes is crucial for advancing strategies to stimulate myocardial regeneration. Although endoreplication has long been considered the primary source of polyploid human cardiomyocytes, recent animal work suggests the potential for cardiomyocyte fusion. Moreover, the effects of polyploidization on the genomic-transcriptomic repertoire of human cardiomyocytes have not been studied previously. We applied single-nuclei whole genome sequencing, single nuclei RNA sequencing, and multiome ATAC + gene expression (from the same nuclei) techniques to nuclei isolated from 11 healthy hearts. Utilizing post-zygotic non-inherited somatic mutations occurring during development as "endogenous barcodes," to reconstruct lineage relationships of polyploid cardiomyocytes. Of 482 cardiomyocytes from multiple healthy donor hearts 75.7% can be sorted into several developmental clades marked by one or more somatic single-nucleotide variants (SNVs). At least ~10% of tetraploid cardiomyocytes contain cells from distinct clades, indicating fusion of lineally distinct cells, whereas 60% of higher-ploidy cardiomyocytes contain fused cells from distinct clades. Combined snRNA-seq and snATAC-seq revealed transcriptome and chromatin landscapes of polyploid cardiomyocytes distinct from diploid cardiomyocytes, and show some higher-ploidy cardiomyocytes with transcriptional signatures suggesting fusion between cardiomyocytes and endothelial and fibroblast cells. These observations provide the first evidence for cell and nuclear fusion of human cardiomyocytes, raising the possibility that cell fusion may contribute to developing or maintaining polyploid cardiomyocytes in the human heart.

Cerebral organoids display dynamic clonal growth and tunable tissue replenishment

During brain development, neural progenitors expand through symmetric divisions before giving rise to differentiating cell types via asymmetric divisions. Transition between those modes varies among individual neural stem cells, resulting in clones of different sizes. Imaging-based lineage tracing allows for lineage analysis at high cellular resolution but systematic approaches to analyse clonal behaviour of entire tissues are currently lacking. Here we implement whole-tissue lineage tracing by genomic DNA barcoding in 3D human cerebral organoids, to show that individual stem cell clones produce progeny on a vastly variable scale. By using stochastic modelling we find that variable lineage sizes arise because a subpopulation of lineages retains symmetrically dividing cells. We show that lineage sizes can adjust to tissue demands after growth perturbation via chemical ablation or genetic restriction of a subset of cells in chimeric organoids. Our data suggest that adaptive plasticity of stem cell populations ensures robustness of development in human brain organoids.

Scuphr: A probabilistic framework for cell lineage tree reconstruction

Cell lineage tree reconstruction methods are developed for various tasks, such as investigating the development, differentiation, and cancer progression. Single-cell sequencing technologies enable more thorough analysis with higher resolution. We present Scuphr, a distance-based cell lineage tree reconstruction method using bulk and single-cell DNA sequencing data from healthy tissues. Common challenges of single-cell DNA sequencing, such as allelic dropouts and amplification errors, are included in Scuphr. Scuphr computes the distance between cell pairs and reconstructs the lineage tree using the neighbor-joining algorithm. With its embarrassingly parallel design, Scuphr can do faster analysis than the state-of-the-art methods while obtaining better accuracy. The method's robustness is investigated using various synthetic datasets and a biological dataset of 18 cells.

Contrasting somatic mutation patterns in aging human neurons and oligodendrocytes

Characterizing somatic mutations in the brain is important for disentangling the complex mechanisms of aging, yet little is known about mutational patterns in different brain cell types. Here, we performed whole-genome sequencing (WGS) of 86 single oligodendrocytes, 20 mixed glia, and 56 single neurons from neurotypical individuals spanning 0.4-104 years of age and identified >92,000 somatic single-nucleotide variants (sSNVs) and small insertions/deletions (indels). Although both cell types accumulate somatic mutations linearly with age, oligodendrocytes accumulated sSNVs 81% faster than neurons and indels 28% slower than neurons. Correlation of mutations with single-nucleus RNA profiles and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed across the genome similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These stark differences suggest an assortment of active mutagenic processes in oligodendrocytes and neurons.

The molecular map of CLL and Richter's syndrome

Clonal expansion of B-cells, from the early stages of monoclonal B-cell lymphocytosis through to chronic lymphocytic leukemia (CLL), and then in some cases to Richter's syndrome (RS) provides a comprehensive model of cancer evolution, notable for the marked morphological transformation and distinct clinical phenotypes. High-throughput sequencing of large cohorts of patients and single-cell studies have generated a molecular map of CLL and more recently, of RS, yielding fundamental insights into these diseases and of clonal evolution. A selection of CLL driver genes have been functionally interrogated to yield novel insights into the biology of CLL. Such findings have the potential to impact patient care through risk stratification, treatment selection and drug discovery. However, this molecular map remains incomplete, with extant questions concerning the origin of the B-cell clone, the role of the TME, inter- and intra-compartmental heterogeneity and of therapeutic resistance mechanisms. Through the application of multi-modal single-cell technologies across tissues, disease states and clinical contexts, these questions can now be addressed with the answers holding great promise of generating translatable knowledge to improve patient care.

Exploration of cell type-specific somatic mutations in schizophrenia and the impact of maternal immune activation on the somatic mutation profile in the brain

AIM

Schizophrenia (SZ) is a severe psychiatric disorder caused by the interaction of genetic and environmental factors. Although somatic mutations that occur in the brain after fertilization may play an important role in the cause of SZ, their frequencies and patterns in the brains of patients and related animal models have not been well studied. This study aimed to find somatic mutations related to the pathophysiology of SZ.

METHODS

We performed whole-exome sequencing (WES) of neuronal and nonneuronal nuclei isolated from the postmortem prefrontal cortex of patients with SZ (n = 10) and controls (n = 10). After detecting somatic mutations, we explored the similarities and differences in shared common mutations between two cell types and cell type-specific mutations. We also performed WES of prefrontal cortex samples from an animal model of SZ based on maternal immune activation (MIA) and explored the possible impact of MIA on the patterns of somatic mutations.

RESULTS

We did not find quantitative differences in somatic mutations but found higher variant allele fractions of neuron-specific mutations in patients with SZ. In the mouse model, we found a larger variation in the number of somatic mutations in the offspring of MIA mice, with the occurrence of somatic mutations in neurodevelopment-related genes.

CONCLUSION

Somatic mutations occurring at an earlier stage of brain cell differentiation toward neurons may be important for the cause of SZ. MIA may affect somatic mutation profiles in the brain.

Single-cell lineage tracing with endogenous markers

Resolving lineage relationships between cells in an organism provides key insights into the fate of individual cells and drives a fundamental understanding of the process of development and disease. A recent rapid increase in experimental and computational advances for detecting naturally occurring somatic nuclear and mitochondrial mutation at single-cell resolution has expanded lineage tracing from model organisms to humans. This review discusses the advantages and challenges of experimental and computational techniques for cell lineage tracing using somatic mutation as endogenous DNA barcodes to decipher the relationships between cells during development and tumour evolution. We outlook the advantages of spatial clonal evolution analysis and single-cell lineage tracing using endogenous genetic markers.

Genomic variation in neurons

Neurons born during the fetal period have extreme longevity and survive until the death of the individual because the human brain has highly limited tissue regeneration. The brain is comprised of an enormous variety of neurons each exhibiting different morphological and physiological characteristics and recent studies have further reported variations in their genome including chromosomal abnormalities, copy number variations, and single nucleotide mutations. During the early stages of brain development, the increasing number of neurons generated at high speeds has been proposed to lead to chromosomal instability. Additionally, mutations in the neuronal genome can occur in the mature brain. This observed genomic mosaicism in the brain can be produced by multiple endogenous and environmental factors and careful analyses of these observed variations in the neuronal genome remain central for our understanding of the genetic basis of neurological disorders.

Startle: A star homoplasy approach for CRISPR-Cas9 lineage tracing

CRISPR-Cas9-based genome editing combined with single-cell sequencing enables the tracing of the history of cell divisions, or cellular lineage, in tissues and whole organisms. Although standard phylogenetic approaches may be applied to reconstruct cellular lineage trees from this data, the unique features of the CRISPR-Cas9 editing process motivate the development of specialized models that describe the evolution of CRISPR-Cas9-induced mutations. Here, we introduce the "star homoplasy" evolutionary model that constrains a phylogenetic character to mutate at most once along a lineage, capturing the "non-modifiability" property of CRISPR-Cas9 mutations. We derive a combinatorial characterization of star homoplasy phylogenies and use this characterization to develop an algorithm, "Startle", that computes a maximum parsimony star homoplasy phylogeny. We demonstrate that Startle infers more accurate phylogenies on simulated lineage tracing data compared with existing methods and finds parsimonious phylogenies with fewer metastatic migrations on lineage tracing data from mouse metastatic lung adenocarcinoma.

How can cancer research be illuminated by brain research (and vice versa)?

Cancer and brain research have historically followed concrete pathways and converged mostly to studying brain cancer. Nowadays, the fields of neuro-oncology and neuroendocrine regulation of tumorigenesis are both emerging fields of intense research and promising applications. An increasing body of evidence suggests that somatic mutations in cancer-related genes are prevalent in several noncancerous brain disorders. These findings highlighting that certain aspects of cancer development/progression and pathologies of the nervous system share molecular alterations, could assist in elucidating the unique hallmarks of cancer and in cancer drugs repurposing for brain disorders. In so doing, identifying the commonalities in these conditions could be crucial not only for better understanding the basis of these pathologies but also for considering the previously underappreciated and/or neglected possibility of using drugs known to be effective in one type of pathology for the other type.

Somatic Mosaicism in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Reveals Widespread Degeneration from Focal Mutations

Although mutations in dozens of genes have been implicated in familial forms of amyotrophic lateral sclerosis (fALS) and frontotemporal degeneration (fFTD), most cases of these conditions are sporadic (sALS and sFTD), with no family history, and their etiology remains obscure. We tested the hypothesis that somatic mosaic mutations, present in some but not all cells, might contribute in these cases, by performing ultra-deep, targeted sequencing of 88 genes associated with neurodegenerative diseases in postmortem brain and spinal cord samples from 404 individuals with sALS or sFTD and 144 controls. Known pathogenic germline mutations were found in 20.6% of ALS, and 26.5% of FTD cases. Predicted pathogenic somatic mutations in ALS/FTD genes were observed in 2.7% of sALS and sFTD cases that did not carry known pathogenic or novel germline mutations. Somatic mutations showed low variant allele fraction (typically <2%) and were often restricted to the region of initial discovery, preventing detection through genetic screening in peripheral tissues. Damaging somatic mutations were preferentially enriched in primary motor cortex of sALS and prefrontal cortex of sFTD, mirroring regions most severely affected in each disease. Somatic mutation analysis of bulk RNA-seq data from brain and spinal cord from an additional 143 sALS cases and 23 controls confirmed an overall enrichment of somatic mutations in sALS. Two adult sALS cases were identified bearing pathogenic somatic mutations in DYNC1H1 and LMNA, two genes associated with pediatric motor neuron degeneration. Our study suggests that somatic mutations in fALS/fFTD genes, and in genes associated with more severe diseases in the germline state, contribute to sALS and sFTD, and that mosaic mutations in a small fraction of cells in focal regions of the nervous system can ultimately result in widespread degeneration.

The transcriptional legacy of developmental stochasticity

Genetic and environmental variation are key contributors during organism development, but the influence of minor perturbations or noise is difficult to assess. This study focuses on the stochastic variation in allele-specific expression that persists through cell divisions in the nine-banded armadillo (Dasypus novemcinctus). We investigated the blood transcriptome of five wild monozygotic quadruplets over time to explore the influence of developmental stochasticity on gene expression. We identify an enduring signal of autosomal allelic variability that distinguishes individuals within a quadruplet despite their genetic similarity. This stochastic allelic variation, akin to X-inactivation but broader, provides insight into non-genetic influences on phenotype. The presence of stochastically canalized allelic signatures represents a novel axis for characterizing organismal variability, complementing traditional approaches based on genetic and environmental factors. We also developed a model to explain the inconsistent penetrance associated with these stochastically canalized allelic expressions. By elucidating mechanisms underlying the persistence of allele-specific expression, we enhance understanding of development's role in shaping organismal diversity.

Cell lineage analysis with somatic mutations reveals late divergence of neuronal cell types and cortical areas in human cerebral cortex

The mammalian cerebral cortex shows functional specialization into regions with distinct neuronal compositions, most strikingly in the human brain, but little is known in about how cellular lineages shape cortical regional variation and neuronal cell types during development. Here, we use somatic single nucleotide variants (sSNVs) to map lineages of neuronal sub-types and cortical regions. Early-occurring sSNVs rarely respect Brodmann area (BA) borders, while late-occurring sSNVs mark neuron-generating clones with modest regional restriction, though descendants often dispersed into neighboring BAs. Nevertheless, in visual cortex, BA17 contains 30-70% more sSNVs compared to the neighboring BA18, with clones across the BA17/18 border distributed asymmetrically and thus displaying different cortex-wide dispersion patterns. Moreover, we find that excitatory neuron-generating clones with modest regional restriction consistently share low-mosaic sSNVs with some inhibitory neurons, suggesting significant co-generation of excitatory and some inhibitory neurons in the dorsal cortex. Our analysis reveals human-specific cortical cell lineage patterns, with both regional inhomogeneities in progenitor proliferation and late divergence of excitatory/inhibitory lineages.

A Law of Redundancy Compounds the Problem of Cancer and Precision Medicine

Genetics and molecular biology research have progressed for over a century; however, no laws of biology resembling those of physics have been identified, despite the expectations of some physicists. It may be that it is not the properties of matter alone but evolved properties of matter in combination with atomic physics and chemistry that gave rise to the origin and complexity of life. It is proposed that any law of biology must also be a product of evolution that co-evolved with the origin and progression of life. It was suggested that molecular complexity and redundancy exponentially increase over time and have the following relationship: DNA sequence complexity (Cd) < molecular complexity (Cm) < phenotypic complexity (Cp). This study presents a law of redundancy, which together with the law of complexity, is proposed as an evolutionary law of biology. Molecular complexity and redundancy are inseparable aspects of biochemical pathways, and molecular redundancy provides the first line of defense against environmental challenges, including those of deleterious mutations. Redundancy can create problems for precision medicine because in addition to the issues arising from the involvement of multiple genes, redundancy arising from alternate pathways between genotypes and phenotypes can complicate gene detection for complex diseases and mental disorders. This study uses cancer as an example to show how cellular complexity, molecular redundancy, and hidden variation affect the ability of cancer cells to evolve and evade detection and elimination. Characterization of alternate biochemical pathways or "escape routes" can provide a step in the fight against cancer.

Deep exome sequencing identifies enrichment of deleterious mosaic variants in neurodevelopmental disorder genes and mitochondrial tRNA regions in bipolar disorder

Bipolar disorder (BD) is a global medical issue, afflicting around 1% of the population with manic and depressive episodes. Despite various genetic studies, the genetic architecture and pathogenesis of BD have not been fully resolved. Besides germline variants, postzygotic mosaic variants are proposed as new candidate mechanisms contributing to BD. Here, we performed extensive deep exome sequencing (DES, ~300×) and validation experiments to investigate the roles of mosaic variants in BD with 235 BD cases (194 probands of trios and 41 single cases) and 39 controls. We found an enrichment of developmental disorder (DD) genes in the genes hit by deleterious mosaic variants in BD (P = 0.000552), including a ClinVar-registered pathogenic variant in ARID2. An enrichment of deleterious mosaic variants was also observed for autism spectrum disorder (ASD) genes (P = 0.000428). The proteins coded by the DD/ASD genes with non-synonymous mosaic variants in BD form more protein-protein interaction than expected, suggesting molecular mechanisms shared with DD/ASD but restricted to a subset of cells in BD. We also found significant enrichment of mitochondrial heteroplasmic variants, another class of mosaic variants, in mitochondrial tRNA genes in BD (P = 0.0102). Among them, recurrent m.3243 A > G variants known as causal for mitochondrial diseases were found in two unrelated BD probands with allele fractions of 5-12%, lower than in mitochondrial diseases. Despite the limitation of using peripheral tissues, our DES investigation supports the possible contribution of deleterious mosaic variants in the nuclear genome responsible for severer phenotypes, such as DD/ASD, to the risk of BD and further demonstrates that the same paradigm can be applied to the mitochondrial genome. These results, as well as the enrichment of heteroplasmic mitochondrial tRNA variants in BD, add a new piece to the understanding of the genetic architecture of BD and provide general insights into the pathological roles of mosaic variants in human diseases.

Single-cell phylogenies reveal changes in the evolutionary rate within cancer and healthy tissues

Cell lineages accumulate somatic mutations during organismal development, potentially leading to pathological states. The rate of somatic evolution within a cell population can vary due to multiple factors, including selection, a change in the mutation rate, or differences in the microenvironment. Here, we developed a statistical test called the Poisson Tree (PT) test to detect varying evolutionary rates among cell lineages, leveraging the phylogenetic signal of single-cell DNA sequencing (scDNA-seq) data. We applied the PT test to 24 healthy and cancer samples, rejecting a constant evolutionary rate in 11 out of 15 cancer and five out of nine healthy scDNA-seq datasets. In six cancer datasets, we identified subclonal mutations in known driver genes that could explain the rate accelerations of particular cancer lineages. Our findings demonstrate the efficacy of scDNA-seq for studying somatic evolution and suggest that cell lineages often evolve at different rates within cancer and healthy tissues.

Long-read whole-genome analysis of human single cells

Long-read sequencing has dramatically increased our understanding of human genome variation. Here, we demonstrate that long-read technology can give new insights into the genomic architecture of individual cells. Clonally expanded CD8+ T-cells from a human donor were subjected to droplet-based multiple displacement amplification (dMDA) to generate long molecules with reduced bias. PacBio sequencing generated up to 40% genome coverage per single-cell, enabling detection of single nucleotide variants (SNVs), structural variants (SVs), and tandem repeats, also in regions inaccessible by short reads. 28 somatic SNVs were detected, including one case of mitochondrial heteroplasmy. 5473 high-confidence SVs/cell were discovered, a sixteen-fold increase compared to Illumina-based results from clonally related cells. Single-cell de novo assembly generated a genome size of up to 598 Mb and 1762 (12.8%) complete gene models. In summary, our work shows the promise of long-read sequencing toward characterization of the full spectrum of genetic variation in single cells.

LINE-1 regulates cortical development by acting as long non-coding RNAs

Long Interspersed Nuclear Elements-1s (L1s) are transposable elements that constitute most of the genome's transcriptional output yet have still largely unknown functions. Here we show that L1s are required for proper mouse brain corticogenesis operating as regulatory long non-coding RNAs. They contribute to the regulation of the balance between neuronal progenitors and differentiation, the migration of post-mitotic neurons and the proportions of different cell types. In cortical cultured neurons, L1 RNAs are mainly associated to chromatin and interact with the Polycomb Repressive Complex 2 (PRC2) protein subunits enhancer of Zeste homolog 2 (Ezh2) and suppressor of zeste 12 (Suz12). L1 RNA silencing influences PRC2's ability to bind a portion of its targets and the deposition of tri-methylated histone H3 (H3K27me3) marks. Our results position L1 RNAs as crucial signalling hubs for genome-wide chromatin remodelling, enabling the fine-tuning of gene expression during brain development and evolution.

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)-present in some but not all cells-remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e-4), with recurrent somatic deletions of exons 1-5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5' deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk.

Cellular barcoding: From developmental tracing to anti-tumor drug discovery

Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.