Somatic mutation in single human neurons tracks developmental and transcriptional history

Somatic Mosaicism in Biology and Disease

Contrary to earlier beliefs, every cell in the individual is genetically different due to somatic mutations. Consequently, tissues become a mixture of cells with distinct genomes, a phenomenon termed somatic mosaicism. Recent advances in genome sequencing technology have unveiled possible causes of mutations and how they shape the unique mutational landscape of the tissues. Moreover, the analysis of sequencing data in combination with clinical information has revealed the impacts of somatic mosaicism on disease processes. In this review, we discuss somatic mosaicism in various tissues and its clinical implications for human disease.

Aging and Clonal Behavior of Hematopoietic Stem Cells

Hematopoietic stem cells (HSCs) are the only cell population that possesses both a self-renewing capacity and multipotency, and can give rise to all lineages of blood cells throughout an organism's life. However, the self-renewal capacity of HSCs is not infinite, and cumulative evidence suggests that HSCs alter their function and become less active during organismal aging, leading ultimately to the disruption of hematopoietic homeostasis, such as anemia, perturbed immunity and increased propensity to hematological malignancies. Thus, understanding how HSCs alter their function during aging is a matter of critical importance to prevent or overcome these age-related changes in the blood system. Recent advances in clonal analysis have revealed the functional heterogeneity of murine HSC pools that is established upon development and skewed toward the clonal expansion of functionally poised HSCs during aging. In humans, next-generation sequencing has revealed age-related clonal hematopoiesis that originates from HSC subsets with acquired somatic mutations, and has highlighted it as a significant risk factor for hematological malignancies and cardiovascular diseases. In this review, we summarize the current fate-mapping strategies that are used to track and visualize HSC clonal behavior during development or after stress. We then review the age-related changes in HSCs that can be inherited by daughter cells and act as a cellular memory to form functionally distinct clones. Altogether, we link aging of the hematopoietic system to HSC clonal evolution and discuss how HSC clones with myeloid skewing and low regenerative potential can be expanded during aging.

The threat of programmed DNA damage to neuronal genome integrity and plasticity

The neuronal genome is particularly sensitive to loss or attenuation of DNA repair, and many neurological diseases ensue when DNA repair is impaired. It is well-established that the neuronal genome is subjected to stochastic DNA damage, most likely because of extensive oxidative stress in the brain. However, recent studies have identified unexpected high levels of 'programmed' DNA breakage in neurons, which we propose arise during physiological DNA metabolic processes intrinsic to neuronal development, differentiation and maintenance. The role of programmed DNA breaks in normal neuronal physiology and disease remains relatively unexplored thus far. However, bulk and single-cell sequencing analyses of neurodegenerative diseases have revealed age-related somatic mutational signatures that are enriched in regulatory regions of the genome. Here, we explore a paradigm of DNA repair in neurons, in which the genome is safeguarded from erroneous impacts of programmed genome breakage intrinsic to normal neuronal function.

LINEAGE: Label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis

Lineage analysis is an important assay for developmental biology, cancer biology, etc. Traditional tools in this field are time consuming, technically challenging, and in demand of preexisting knowledge. By integrating exogenous barcodes into cells, single-cell RNA-sequencing (scRNA-seq) can be used to conduct such tasks, but these assays required significant expertise in both wet- and dry-laboratory experiments. We developed a user-friendly algorithm to conduct cell-lineage inference solely based on endogenous markers of label-free scRNA-seq. This algorithm is able to identify lineage-informative mutations from a bunch of interfering mitochondrial RNA variants with high accuracy and efficiency. With this algorithm, we removed most of the technical hurdles of lineage analysis on scRNA-seq and will dramatically accelerate its application in biological research.

Single-cell RNA-sequencing (scRNA-seq) has become a powerful tool for biomedical research by providing a variety of valuable information with the advancement of computational tools. Lineage analysis based on scRNA-seq provides key insights into the fate of individual cells in various systems. However, such analysis is limited by several technical challenges. On top of the considerable computational expertise and resources, these analyses also require specific types of matching data such as exogenous barcode information or bulk assay for transposase-accessible chromatin with high throughput sequencing (ATAC-seq) data. To overcome these technical challenges, we developed a user-friendly computational algorithm called “LINEAGE” (label-free identification of endogenous informative single-cell mitochondrial RNA mutation for lineage analysis). Aiming to screen out endogenous markers of lineage located on mitochondrial reads from label-free scRNA-seq data to conduct lineage inference, LINEAGE integrates a marker selection strategy by feature subspace separation and de novo “low cross-entropy subspaces” identification. In this process, the mutation type and subspace–subspace “cross-entropy” of features were both taken into consideration. LINEAGE outperformed three other methods, which were designed for similar tasks as testified with two standard datasets in terms of biological accuracy and computational efficiency. Applied on a label-free scRNA-seq dataset of BRAF-mutated cancer cells, LINEAGE also revealed genes that contribute to BRAF inhibitor resistance. LINEAGE removes most of the technical hurdles of lineage analysis, which will remarkably accelerate the discovery of the important genes or cell-lineage clusters from scRNA-seq data.

Recent advances on single-cell sequencing technologies

Single-cell omics sequencing was first achieved for transcriptome in 2009, which was followed by fast development of technologies for profiling genome, DNA methylome, 3D genome architecture, chromatin accessibility, histone modifications and so on, in an individual cell. In this review we mainly focus on the recent progresses in four topics in single cell omics field- single-cell epigenome sequencing, single-cell genome sequencing for lineage tracing, spatially resolved single-cell transcriptomics, and third-generation sequencing platform-based single cell omics sequencing. We also discuss the potential applications and future directions of these single cell omics sequencing technologies for different biomedical systems, especially for the human stem cell field.

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data

We introduce CellPhy, a maximum likelihood framework for inferring phylogenetic trees from somatic single-cell single-nucleotide variants. CellPhy leverages a finite-site Markov genotype model with 16 diploid states and considers amplification error and allelic dropout. We implement CellPhy into RAxML-NG, a widely used phylogenetic inference package that provides statistical confidence measurements and scales well on large datasets with hundreds or thousands of cells. Comprehensive simulations suggest that CellPhy is more robust to single-cell genomics errors and outperforms state-of-the-art methods under realistic scenarios, both in accuracy and speed. CellPhy is freely available at https://github.com/amkozlov/cellphy .

Cortical Dysplasia and the mTOR Pathway: How the Study of Human Brain Tissue Has Led to Insights into Epileptogenesis

Type II focal cortical dysplasia (FCD) is a neuropathological entity characterised by cortical dyslamination with the presence of dysmorphic neurons only (FCDIIA) or the presence of both dysmorphic neurons and balloon cells (FCDIIB). The year 2021 marks the 50th anniversary of the recognition of FCD as a cause of drug resistant epilepsy, and it is now the most common reason for epilepsy surgery. The causes of FCD remained unknown until relatively recently. The study of resected human FCD tissue using novel genomic technologies has led to remarkable advances in understanding the genetic basis of FCD. Mechanistic parallels have emerged between these non-neoplastic lesions and neoplastic disorders of cell growth and differentiation, especially through perturbations of the mammalian target of rapamycin (mTOR) signalling pathway. This narrative review presents the advances through which the aetiology of FCDII has been elucidated in chronological order, from recognition of an association between FCD and the mTOR pathway to the identification of somatic mosaicism within FCD tissue. We discuss the role of a two-hit mechanism, highlight current challenges and future directions in detecting somatic mosaicism in brain and discuss how knowledge of FCD may inform novel precision treatments of these focal epileptogenic malformations of human cortical development.

Sensitivity to copy number variation analysis in single cell genomics

While previous studies have given some guidance, the sensitivity of copy number calling in single-cell genomics is still not comprehensive. We studied the impact of sequencing depth and other factors on single-cell copy number analysis. Sequencing Data from 26 datasets were retrieved, and 2946 single cells passed the filter. Thirty-eight single cells were independently downscaled to evaluate copy number variation (CNV) detection sensitivity at different bin sizes. The sensitivity of whole genome amplification (WGA) approaches and cell types to CNV calling were evaluated using downsampling of 101 and 70 cells. Cluster analysis based on t-SNE was executed to evaluate CNV calling performance. Our results suggest 0.75× sequencing depth with moderate resolution (250 kb bin size) may be a practical guideline considering both sequencing cost and performance of copy number calling, which can be appropriately optimized based on amplification approach, cell type, and sample complexity.

Modeling Somatic Mutations Associated With Neurodevelopmental Disorders in Human Brain Organoids

Neurodevelopmental disorders (NDDs) are a collection of diseases with early life onset that often present with developmental delay, cognitive deficits, and behavioral conditions. In some cases, severe outcomes such as brain malformations and intractable epilepsy can occur. The mutations underlying NDDs may be inherited or de novo, can be gain- or loss-of-function, and can affect one or more genes. Recent evidence indicates that brain somatic mutations contribute to several NDDs, in particular malformations of cortical development. While advances in sequencing technologies have enabled the detection of these somatic mutations, the mechanisms by which they alter brain development and function are not well understood due to limited model systems that recapitulate these events. Human brain organoids have emerged as powerful models to study the early developmental events of the human brain. Brain organoids capture the developmental progression of the human brain and contain human-enriched progenitor cell types. Advances in human stem cell and genome engineering provide an opportunity to model NDD-associated somatic mutations in brain organoids. These organoids can be tracked throughout development to understand the impact of somatic mutations on early human brain development and function. In this review, we discuss recent evidence that somatic mutations occur in the developing human brain, that they can lead to NDDs, and discuss how they could be modeled using human brain organoids.

Single-cell delineation of lineage and genetic identity in the mouse brain

During neurogenesis, mitotic progenitor cells lining the ventricles of the embryonic mouse brain undergo their final rounds of cell division, giving rise to a wide spectrum of postmitotic neurons and glia^1,2. The link between developmental lineage and cell-type diversity remains an open question. Here we used massively parallel tagging of progenitors to track clonal relationships and transcriptomic signatures during mouse forebrain development. We quantified clonal divergence and convergence across all major cell classes postnatally, and found diverse types of GABAergic neuron that share a common lineage. Divergence of GABAergic clones occurred during embryogenesis upon cell-cycle exit, suggesting that differentiation into subtypes is initiated as a lineage-dependent process at the progenitor cell level.

Unraveling the complex interplay between genes, environment, and climate in ALS

Various genetic and environmental risk factors have been implicated in the pathogenesis of amyotrophic lateral sclerosis (ALS). Despite this, the cause of most ALS cases remains obscure. In this review, we describe the current evidence implicating genetic and environmental factors in motor neuron degeneration. While the risk exerted by many environmental factors may appear small, their effect could be magnified by the presence of a genetic predisposition. We postulate that gene-environment interactions account for at least a portion of the unknown etiology in ALS. Climate underlies multiple environmental factors, some of which have been implied in ALS etiology, and the impact of global temperature increase on the gene-environment interactions should be carefully monitored. We describe the main concepts underlying such interactions. Although a lack of large cohorts with detailed genetic and environmental information hampers the search for gene-environment interactions, newer algorithms and machine learning approaches offer an opportunity to break this stalemate. Understanding how genetic and environmental factors interact to cause ALS may ultimately pave the way towards precision medicine becoming an integral part of ALS care.

Individual human cortical progenitors can produce excitatory and inhibitory neurons

The cerebral cortex is a cellularly complex structure comprising a rich diversity of neuronal and glial cell types. Cortical neurons can be broadly categorized into two classes-excitatory neurons that use the neurotransmitter glutamate, and inhibitory interneurons that use γ-aminobutyric acid (GABA). Previous developmental studies in rodents have led to a prevailing model in which excitatory neurons are born from progenitors located in the cortex, whereas cortical interneurons are born from a separate population of progenitors located outside the developing cortex in the ganglionic eminences^1-5. However, the developmental potential of human cortical progenitors has not been thoroughly explored. Here we show that, in addition to excitatory neurons and glia, human cortical progenitors are also capable of producing GABAergic neurons with the transcriptional characteristics and morphologies of cortical interneurons. By developing a cellular barcoding tool called 'single-cell-RNA-sequencing-compatible tracer for identifying clonal relationships' (STICR), we were able to carry out clonal lineage tracing of 1,912 primary human cortical progenitors from six specimens, and to capture both the transcriptional identities and the clonal relationships of their progeny. A subpopulation of cortically born GABAergic neurons was transcriptionally similar to cortical interneurons born from the caudal ganglionic eminence, and these cells were frequently related to excitatory neurons and glia. Our results show that individual human cortical progenitors can generate both excitatory neurons and cortical interneurons, providing a new framework for understanding the origins of neuronal diversity in the human cortex.

DNA methylation-based classification of malformations of cortical development in the human brain

Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definition and diagnosis remain challenging and are often prone to arbitrary judgment. Molecular classification of histopathological entities may help rationalize the diagnostic process. We present a retrospective, multi-center analysis of genome-wide DNA methylation from human brain specimens obtained from epilepsy surgery using EPIC 850 K BeadChip arrays. A total of 308 samples were included in the study. In the reference cohort, 239 formalin-fixed and paraffin-embedded (FFPE) tissue samples were histopathologically classified as MCD, including 12 major subtype pathologies. They were compared to 15 FFPE samples from surgical non-MCD cortices and 11 FFPE samples from post-mortem non-epilepsy controls. We applied three different statistical approaches to decipher the DNA methylation pattern of histopathological MCD entities, i.e., pairwise comparison, machine learning, and deep learning algorithms. Our deep learning model, which represented a shallow neuronal network, achieved the highest level of accuracy. A test cohort of 43 independent surgical samples from different epilepsy centers was used to test the precision of our DNA methylation-based MCD classifier. All samples from the test cohort were accurately assigned to their disease classes by the algorithm. These data demonstrate DNA methylation-based MCD classification suitability across major histopathological entities amenable to epilepsy surgery and age groups and will help establish an integrated diagnostic classification scheme for epilepsy-associated MCD.

Lineage recording in human cerebral organoids

Induced pluripotent stem cell (iPSC)-derived organoids provide models to study human organ development. Single-cell transcriptomics enable highly resolved descriptions of cell states within these systems; however, approaches are needed to directly measure lineage relationships. Here we establish iTracer, a lineage recorder that combines reporter barcodes with inducible CRISPR-Cas9 scarring and is compatible with single-cell and spatial transcriptomics. We apply iTracer to explore clonality and lineage dynamics during cerebral organoid development and identify a time window of fate restriction as well as variation in neurogenic dynamics between progenitor neuron families. We also establish long-term four-dimensional light-sheet microscopy for spatial lineage recording in cerebral organoids and confirm regional clonality in the developing neuroepithelium. We incorporate gene perturbation (iTracer-perturb) and assess the effect of mosaic TSC2 mutations on cerebral organoid development. Our data shed light on how lineages and fates are established during cerebral organoid formation. More broadly, our techniques can be adapted in any iPSC-derived culture system to dissect lineage alterations during normal or perturbed development.

Genomics of Alzheimer's disease implicates the innate and adaptive immune systems

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterised by cognitive impairment, behavioural alteration, and functional decline. Over 130 AD-associated susceptibility loci have been identified by genome-wide association studies (GWAS), while whole genome sequencing (WGS) and whole exome sequencing (WES) studies have identified AD-associated rare variants. These variants are enriched in APOE, TREM2, CR1, CD33, CLU, BIN1, CD2AP, PILRA, SCIMP, PICALM, SORL1, SPI1, RIN3, and more genes. Given that aging is the single largest risk factor for late-onset AD (LOAD), the accumulation of somatic mutations in the brain and blood of AD patients have also been explored. Collectively, these genetic findings implicate the role of innate and adaptive immunity in LOAD pathogenesis and suggest that a systemic failure of cell-mediated amyloid-β (Aβ) clearance contributes to AD onset and progression. AD-associated variants are particularly enriched in myeloid-specific regulatory regions, implying that AD risk variants are likely to perturbate the expression of myeloid-specific AD-associated genes to interfere Aβ clearance. Defective phagocytosis, endocytosis, and autophagy may drive Aβ accumulation, which may be related to naturally-occurring antibodies to Aβ (Nabs-Aβ) produced by adaptive responses. Passive immunisation is providing efficiency in clearing Aβ and slowing cognitive decline, such as aducanumab, donanemab, and lecanemab (ban2401). Causation of AD by impairment of the innate immunity and treatment using the tools of adaptive immunity is emerging as a new paradigm for AD, but immunotherapy that boosts the innate immune functions of myeloid cells is highly expected to modulate disease progression at asymptomatic stage.

Molecular Damage in Aging

Cellular metabolism generates molecular damage affecting all levels of biological organization. Accumulation of this damage over time is thought to play a central role in the aging process, but damage manifests in diverse molecular forms complicating its assessment. Insufficient attention has been paid to date to the role of molecular damage in aging-related phenotypes, particularly in humans, in part because of the difficulty in measuring its various forms. Recently, omics approaches have been developed that begin to address this challenge, because they are able to assess a sizeable proportion of age-related damage at the level of small molecules, proteins, RNA, DNA, organelles and cells. This review describes the concept of molecular damage in aging and discusses its diverse aspects from theoretical models to experimental approaches. Measurement of multiple types of damage enables studies of the role of damage in human aging outcomes and lays a foundation for testing interventions to reduce the burden of molecular damage, opening new approaches to slowing aging and reducing its consequences.

Recent advances in lineage tracing for the kidney

Lineage tracing was originally developed by developmental biologists to identify all progeny of a single cell during morphogenesis. More recently this approach has been applied to other fields, including organ homeostasis and recovery from injury. Modern lineage tracing techniques typically rely on reporter gene expression induced by cell-specific DNA recombination. There have been important scientific advances in the last 10 years that have impacted lineage tracing approaches, including intersectional genetics, optical clearing techniques, and the use of sequencing-based genomic lineage tracing. The latter combines CRISPR-Cas9-based genetic scarring with single-cell RNA-sequencing that, in theory, could allow comprehensive reconstruction of a lineage tree for an entire organism. This review summarizes recent advances in lineage tracing technologies and outlines potential applications for kidney research.

Accurate and scalable variant calling from single cell DNA sequencing data with ProSolo

Accurate single cell mutational profiles can reveal genomic cell-to-cell heterogeneity. However, sequencing libraries suitable for genotyping require whole genome amplification, which introduces allelic bias and copy errors. The resulting data violates assumptions of variant callers developed for bulk sequencing. Thus, only dedicated models accounting for amplification bias and errors can provide accurate calls. We present ProSolo for calling single nucleotide variants from multiple displacement amplified (MDA) single cell DNA sequencing data. ProSolo probabilistically models a single cell jointly with a bulk sequencing sample and integrates all relevant MDA biases in a site-specific and scalable-because computationally efficient-manner. This achieves a higher accuracy in calling and genotyping single nucleotide variants in single cells in comparison to state-of-the-art tools and supports imputation of insufficiently covered genotypes, when downstream tools cannot handle missing data. Moreover, ProSolo implements the first approach to control the false discovery rate reliably and flexibly. ProSolo is implemented in an extendable framework, with code and usage at: https://github.com/prosolo/prosolo.

Aging, Bone Marrow and Next-Generation Sequencing (NGS): Recent Advances and Future Perspectives

The aging of bone marrow (BM) remains a very imperative and alluring subject, with an ever-increasing interest among fellow scientists. A considerable amount of progress has been made in this field with the established ‘hallmarks of aging’ and continued efforts to investigate the age-related changes observed within the BM. Inflammaging is considered as a low-grade state of inflammation associated with aging, and whilst the possible mechanisms by which aging occurs are now largely understood, the processes leading to the underlying changes within aged BM remain elusive. The ability to identify these changes and detect such alterations at the genetic level are key to broadening the knowledgebase of aging BM. Next-generation sequencing (NGS) is an important molecular-level application presenting the ability to not only determine genomic base changes but provide transcriptional profiling (RNA-seq), as well as a high-throughput analysis of DNA–protein interactions (ChIP-seq). Utilising NGS to explore the genetic alterations occurring over the aging process within alterative cell types facilitates the comprehension of the molecular and cellular changes influencing the dynamics of aging BM. Thus, this review prospects the current landscape of BM aging and explores how NGS technology is currently being applied within this ever-expanding field of research.

Nine Levels of Explanation : A Proposed Expansion of Tinbergen's Four-Level Framework for Understanding the Causes of Behavior

Tinbergen's classic "On Aims and Methods of Ethology" (Zeitschrift für Tierpsychologie, 20, 1963) proposed four levels of explanation of behavior, which he thought would soon apply to humans. This paper discusses the need for multilevel explanation; Huxley and Mayr's prior models, and others that followed; Tinbergen's differences with Lorenz on "the innate"; and Mayr's ultimate/proximate distinction. It synthesizes these approaches with nine levels of explanation in three categories: phylogeny, natural selection, and genomics (ultimate causes); maturation, sensitive period effects, and routine environmental effects (intermediate causes); and hormonal/metabolic processes, neural circuitry, and eliciting stimuli (proximate causes), as a respectful extension of Tinbergen's levels. The proposed classification supports and builds on Tinbergen's multilevel model and Mayr's ultimate/proximate continuum, adding intermediate causes in accord with Tinbergen's emphasis on ontogeny. It requires no modification of Standard Evolutionary Theory or The Modern Synthesis, but shows that much that critics claim was missing was in fact part of Neo-Darwinian theory (so named by J. Mark Baldwin in The American Naturalist in 1896) all along, notably reciprocal causation in ontogeny, niche construction, cultural evolution, and multilevel selection. Updates of classical examples in ethology are offered at each of the nine levels, including the neuroethological and genomic findings Tinbergen foresaw. Finally, human examples are supplied at each level, fulfilling his hope of human applications as part of the biology of behavior. This broad ethological framework empowers us to explain human behavior-eventually completely-and vindicates the idea of human nature, and of humans as a part of nature.

Single-cell multi-omics sequencing: application trends, COVID-19, data analysis issues and prospects

Single-cell sequencing is a biotechnology to sequence one layer of genomic information for individual cells in a tissue sample. For example, single-cell DNA sequencing is to sequence the DNA from every single cell. Increasing in complexity, single-cell multi-omics sequencing, or single-cell multimodal omics sequencing, is to profile in parallel multiple layers of omics information from a single cell. In practice, single-cell multi-omics sequencing actually detects multiple traits such as DNA, RNA, methylation information and/or protein profiles from the same cell for many individuals in a tissue sample. Multi-omics sequencing has been widely applied to systematically unravel interplay mechanisms of key components and pathways in cell. This survey overviews recent developments in single-cell multi-omics sequencing, and their applications to understand complex diseases in particular the COVID-19 pandemic. We also summarize machine learning and bioinformatics techniques used in the analysis of the intercorrelated multilayer heterogeneous data. We observed that variational inference and graph-based learning are popular approaches, and Seurat V3 is a commonly used tool to transfer the missing variables and labels. We also discussed two intensively studied issues relating to data consistency and diversity and commented on currently cared issues surrounding the error correction of data pairs and data imputation methods. The survey is concluded with some open questions and opportunities for this extraordinary field.

Independent somatic evolution underlies clustered neuroendocrine tumors in the human small intestine

Small intestine neuroendocrine tumor (SI-NET), the most common cancer of the small bowel, often displays a curious multifocal phenotype with several tumors clustered together in a limited intestinal segment. SI-NET also shows an unusual absence of driver mutations explaining tumor initiation and metastatic spread. The evolutionary trajectories that underlie multifocal SI-NET lesions could provide insight into the underlying tumor biology, but this question remains unresolved. Here, we determine the complete genome sequences of 61 tumors and metastases from 11 patients with multifocal SI-NET, allowing for elucidation of phylogenetic relationships between tumors within single patients. Intra-individual comparisons revealed a lack of shared somatic single-nucleotide variants among the sampled intestinal lesions, supporting an independent clonal origin. Furthermore, in three of the patients, two independent tumors had metastasized. We conclude that primary multifocal SI-NETs generally arise from clonally independent cells, suggesting a contribution from a cancer-priming local factor.

The H3.3K27M oncohistone affects replication stress outcome and provokes genomic instability in pediatric glioma

While comprehensive molecular profiling of histone H3.3 mutant pediatric high-grade glioma has revealed extensive dysregulation of the chromatin landscape, the exact mechanisms driving tumor formation remain poorly understood. Since H3.3 mutant gliomas also exhibit high levels of copy number alterations, we set out to address if the H3.3K27M oncohistone leads to destabilization of the genome. Hereto, we established a cell culture model allowing inducible H3.3K27M expression and observed an increase in mitotic abnormalities. We also found enhanced interaction of DNA replication factors with H3.3K27M during mitosis, indicating replication defects. Further functional analyses revealed increased genomic instability upon replication stress, as represented by mitotic bulky and ultrafine DNA bridges. This co-occurred with suboptimal 53BP1 nuclear body formation after mitosis in vitro, and in human glioma. Finally, we observed a decrease in ultrafine DNA bridges following deletion of the K27M mutant H3F3A allele in primary high-grade glioma cells. Together, our data uncover a role for H3.3 in DNA replication under stress conditions that is altered by the K27M mutation, promoting genomic instability and potentially glioma development.

The Mutagenic Impact of Environmental Exposures in Human Cells and Cancer: Imprints Through Time

During life, the DNA of our cells is continuously exposed to external damaging processes. Despite the activity of various repair mechanisms, DNA damage eventually results in the accumulation of mutations in the genomes of our cells. Oncogenic mutations are at the root of carcinogenesis, and carcinogenic agents are often highly mutagenic. Over the past decade, whole genome sequencing data of healthy and tumor tissues have revealed how cells in our body gradually accumulate mutations because of exposure to various mutagenic processes. Dissection of mutation profiles based on the type and context specificities of the altered bases has revealed a variety of signatures that reflect past exposure to environmental mutagens, ranging from chemotherapeutic drugs to genotoxic gut bacteria. In this review, we discuss the latest knowledge on somatic mutation accumulation in human cells, and how environmental mutagenic factors further shape the mutation landscapes of tissues. In addition, not all carcinogenic agents induce mutations, which may point to alternative tumor-promoting mechanisms, such as altered clonal selection dynamics. In short, we provide an overview of how environmental factors induce mutations in the DNA of our healthy cells and how this contributes to carcinogenesis. A better understanding of how environmental mutagens shape the genomes of our cells can help to identify potential preventable causes of cancer.

Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions

Human accelerated regions (HARs) are the fastest-evolving regions of the human genome, and many are hypothesized to function as regulatory elements that drive human-specific gene regulatory programs. We interrogate the in vitro enhancer activity and in vivo epigenetic landscape of more than 3,100 HARs during human neurodevelopment, demonstrating that many HARs appear to act as neurodevelopmental enhancers and that sequence divergence at HARs has largely augmented their neuronal enhancer activity. Furthermore, we demonstrate PPP1R17 to be a putative HAR-regulated gene that has undergone remarkable rewiring of its cell type and developmental expression patterns between non-primates and primates and between non-human primates and humans. Finally, we show that PPP1R17 slows neural progenitor cell cycle progression, paralleling the cell cycle length increase seen predominantly in primate and especially human neurodevelopment. Our findings establish HARs as key components in rewiring human-specific neurodevelopmental gene regulatory programs and provide an integrated resource to study enhancer activity of specific HARs.

Single-genome sequencing reveals within-host evolution of human malaria parasites

Population genomics of bulk malaria infections is unable to examine intrahost evolution; therefore, most work has focused on the role of recombination in generating genetic variation. We used single-cell sequencing protocol for low-parasitaemia infections to generate 406 near-complete single Plasmodium vivax genomes from 11 patients sampled during sequential febrile episodes. Parasite genomes contain hundreds of de novo mutations, showing strong signatures of selection, which are enriched in the ApiAP2 family of transcription factors, known targets of adaptation. Comparing 315 P. falciparum single-cell genomes from 15 patients with our P. vivax data, we find broad complementary patterns of de novo mutation at the gene and pathway level, revealing the importance of within-host evolution during malaria infections.

Decoding and recoding plant development

The development of multicellular organisms has been studied for centuries, yet many critical events and mechanisms of regulation remain challenging to observe directly. Early research focused on detailed observational and comparative studies. Molecular biology has generated insights into regulatory mechanisms, but only for a limited number of species. Now, synthetic biology is bringing these two approaches together, and by adding the possibility of sculpting novel morphologies, opening another path to understanding biology. Here, we review a variety of recently invented techniques that use CRISPR/Cas9 and phage integrases to trace the differentiation of cells over various timescales, as well as to decode the molecular states of cells in high spatiotemporal resolution. Most of these tools have been implemented in animals. The time is ripe for plant biologists to adopt and expand these approaches. Here, we describe how these tools could be used to monitor development in diverse plant species, as well as how they could guide efforts to recode programs of interest.

Common Postzygotic Mutational Signatures in Healthy Adult Tissues Related to Embryonic Hypoxia

Postzygotic mutations are acquired in normal tissues throughout an individual’s lifetime and hold clues for identifying mutagenic factors. Here, we investigated postzygotic mutation spectra of healthy individuals using optimized ultra-deep exome sequencing of the time-series samples from the same volunteer as well as the samples from different individuals. In blood, sperm, and muscle cells, we resolved three common types of mutational signatures. Signatures A and B represent clock-like mutational processes, and the polymorphisms of epigenetic regulation genes influence the proportion of signature B in mutation profiles. Notably, signature C, characterized by C>T transitions at GpCpN sites, tends to be a feature of diverse normal tissues. Mutations of this type are likely to occur early during embryonic development, supported by their relatively high allelic frequencies, presence in multiple tissues, and decrease in occurrence with age. Almost none of the public datasets for tumors feature this signature, except for 19.6% of samples of clear cell renal cell carcinoma with increased activation of the hypoxia-inducible factor 1 (HIF-1) signaling pathway. Moreover, the accumulation of signature C in the mutation profile was accelerated in a human embryonic stem cell line with drug-induced activation of HIF-1α. Thus, embryonic hypoxia may explain this novel signature across multiple normal tissues. Our study suggests that hypoxic condition in an early stage of embryonic development is a crucial factor inducing C>T transitions at GpCpN sites; and individuals’ genetic background may also influence their postzygotic mutation profiles.

Advances in the genetic classification of amyotrophic lateral sclerosis

PURPOSE OF REVIEW

Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease wherein disease risk and severity are, for the majority of patients, the product of interaction between multiple genetic and environmental factors. We are in a period of unprecedented discovery with new large-scale genome-wide association study (GWAS) and accelerating discovery of risk genes. However, much of the observed heritability of ALS is undiscovered and we are not yet approaching elucidation of the total genetic architecture, which will be necessary for comprehensive disease subclassification.

RECENT FINDINGS

We summarize recent developments and discuss the future. New machine learning models will help to address nonlinear genetic interactions. Statistical power for genetic discovery may be boosted by reducing the search-space using cell-specific epigenetic profiles and expanding our scope to include genetically correlated phenotypes. Structural variation, somatic heterogeneity and consideration of environmental modifiers represent significant challenges which will require integration of multiple technologies and a multidisciplinary approach, including clinicians, geneticists and pathologists.

SUMMARY

The move away from fully penetrant Mendelian risk genes necessitates new experimental designs and new standards for validation. The challenges are significant, but the potential reward for successful disease subclassification is large-scale and effective personalized medicine.

Developmental dysregulation of excitatory-to-inhibitory GABA-polarity switch may underlie schizophrenia pathology: A monozygotic-twin discordant case analysis in human iPS cell-derived neurons

Schizophrenia is a major psychiatric disorder, but the molecular mechanisms leading to its initiation or progression remain unclear. To elucidate the pathophysiology of schizophrenia, we used an in vitro neuronal cell culture model involving human induced pluripotent stem cells (hiPSCs) derived from a monozygotic-twin discordant schizophrenia pair. The cultured neurons differentiated from hiPSCs were composed of a mixture of glutamatergic excitatory neurons and gamma aminobutyric acid (GABA)ergic inhibitory neurons. In the electrophysiological analysis, a different pattern of spontaneous neuronal activity was observed under the condition without any stimulants. The frequency of spontaneous excitatory post-synaptic currents (sEPSCs) was significantly higher in the hiPSC-derived neurons of the patient with schizophrenia than in the control sibling at day-in-vitro 30. However, the synaptic formation was not different between the patient with schizophrenia and the control sibling during the same culture period. To explain underlying mechanisms of higher excitability of presynaptic cells, we focused on the potassium-chloride co-transporter KCC2, which contributes to excitatory-to-inhibitory GABA polarity switch in developing neurons. We also revealed the altered expression pattern of KCC2 in hiPSC-derived neurons from the patient with schizophrenia, which could contribute to understanding the pathology of schizophrenia in the developing nervous system.

Extensive phylogenies of human development inferred from somatic mutations

Starting from the zygote, all cells in the human body continuously acquire mutations. Mutations shared between different cells imply a common progenitor and are thus naturally occurring markers for lineage tracing1,2. Here we reconstruct extensive phylogenies of normal tissues from three adult individuals using whole-genome sequencing of 511 laser capture microdissections. Reconstructed embryonic progenitors in the same generation of a phylogeny often contribute to different extents to the adult body. The degree of this asymmetry varies between individuals, with ratios between the two reconstructed daughter cells of the zygote ranging from 60:40 to 93:7. Asymmetries pervade subsequent generations and can differ between tissues in the same individual. The phylogenies resolve the spatial embryonic patterning of tissues, revealing contiguous patches of, on average, 301 crypts in the adult colonic epithelium derived from a most recent embryonic cell and also a spatial effect in brain development. Using data from ten additional men, we investigated the developmental split between soma and germline, with results suggesting an extraembryonic contribution to primordial germ cells. This research demonstrates that, despite reaching the same ultimate tissue patterns, early bottlenecks and lineage commitments lead to substantial variation in embryonic patterns both within and between individuals.

Applications of Single-Cell DNA Sequencing

Over the past decade, genomic analyses of single cells-the fundamental units of life-have become possible. Single-cell DNA sequencing has shed light on biological questions that were previously inaccessible across diverse fields of research, including somatic mutagenesis, organismal development, genome function, and microbiology. Single-cell DNA sequencing also promises significant future biomedical and clinical impact, spanning oncology, fertility, and beyond. While single-cell approaches that profile RNA and protein have greatly expanded our understanding of cellular diversity, many fundamental questions in biology and important biomedical applications require analysis of the DNA of single cells. Here, we review the applications and biological questions for which single-cell DNA sequencing is uniquely suited or required. We include a discussion of the fields that will be impacted by single-cell DNA sequencing as the technology continues to advance.

Clonal dynamics in early human embryogenesis inferred from somatic mutation

Cellular dynamics and fate decision in early human embryogenesis remain largely unknown owing to the challenges of performing studies in human embryos¹. Here, we explored whole-genomes of 334 single-cell colonies and targeted deep sequences of 379 bulk tissues obtained from various anatomical locations of seven recently deceased adult human donors. Using somatic mutations as an intrinsic barcode, we reconstructed early cellular phylogenies that demonstrate (1) an endogenous mutational rate that is higher in the first cell division but decreases to approximately one per cell per cell division later in life; (2) universal unequal contribution of early cells to embryo proper, resulting from early cellular bottlenecks that stochastically set aside epiblast cells within the embryo; (3) examples of varying degrees of early clonal imbalances between tissues on the left and right sides of the body, different germ layers and specific anatomical parts and organs; (4) emergence of a few ancestral cells that will substantially contribute to adult cell pools in blood and liver; and (5) presence of mitochondrial DNA heteroplasmy in the fertilized egg. Our approach also provides insights into the age-related mutational processes and loss of sex chromosomes in normal somatic cells. In sum, this study provides a foundation for future studies to complete cellular phylogenies in human embryogenesis.

A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing

Lineage reconstruction is central to understanding tissue development and maintenance. To overcome the limitations of current techniques that typically reconstruct clonal trees using genetically encoded reporters, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single-cell-division resolution by using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell pre-implantation mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy. In addition, we developed scH&G-seq to sequence both 5hmC and genomic DNA from the same cell. Given that genomic DNA sequencing yields information on both copy number variations and single-nucleotide polymorphisms, when combined with scPECLR it enables more accurate lineage reconstruction of larger trees. Finally, we show that scPECLR can also be used to map chromosome strand segregation patterns during cell division, thereby providing a strategy to test the "immortal strand" hypothesis. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual-cell-division resolution.

Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees

The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.

Balancing DNA repair to prevent ageing and cancer

DNA damage is a constant stressor to the cell. Persistent damage to the DNA over time results in an increased risk of mutation and an accumulation of mutations with age. Loss of efficient DNA damage repair can lead to accelerated ageing phenotypes or an increased cancer risk, and the trade-off between cancer susceptibility and longevity is often driven by the cell's response to DNA damage. High levels of mutations in DNA repair mutants often leads to excessive cell death and stem cell exhaustion which may promote premature ageing. Stem cells themselves have distinct characteristics that enable them to retain low mutation rates. However, when mutations do arise, stem cell clonal expansion can also contribute to age-related tissue dysfunction as well as heightened cancer risk. In this review, we will highlight increasing DNA damage and mutation accumulation as hallmarks common to both ageing and cancer. We will propose that anti-ageing interventions might be cancer preventative and discuss the mechanisms through which they may act.

Rates and patterns of clonal oncogenic mutations in the normal human brain

While oncogenic mutations have been found in non-diseased, proliferative non-neural tissues, their prevalence in the human brain is unknown. Targeted sequencing of genes implicated in brain tumors in 418 samples derived from 110 individuals of varying ages, without tumor diagnoses, detected oncogenic somatic single-nucleotide variants (sSNVs) in 5.4% of the brains, including IDH1 R132H. These mutations were largely present in subcortical white matter and enriched in glial cells, and surprisingly, were less common in older individuals. A depletion of high-allele frequency sSNVs representing macroscopic clones with age was replicated by analysis of bulk RNAseq data from 1,816 non-diseased brain samples ranging from fetal to old age. We also describe large clonal copy number variants, and that sSNVs show mutational signatures resembling those found in gliomas, suggesting that mutational processes of the normal brain drive early glial oncogenesis. This study helps understand the origin and early evolution of brain tumors.

Accurate SNV detection in single cells by transposon-based whole-genome amplification of complementary strands

The boom of single-cell sequencing technologies in the past decade has profoundly expanded our understanding of fundamental biology. Today, tens of thousands of cells can be measured by single-cell RNA-seq in one experiment. However, single-cell DNA-sequencing studies have been limited by false positives and cost. Here we report META-CS, a single-cell whole-genome amplification method that takes advantage of the complementary strands of double-stranded DNA to filter out false positives and reduce sequencing cost. META-CS achieved the highest accuracy in terms of detecting single-nucleotide variations, and provided potential solutions for the identification of other genomic variants, such as insertions, deletions, and structural variations in single cells.

Single-nucleotide variants (SNVs), pertinent to aging and disease, occur sporadically in the human genome, hence necessitating single-cell measurements. However, detection of single-cell SNVs suffers from false positives (FPs) due to intracellular single-stranded DNA damage and the process of whole-genome amplification (WGA). Here, we report a single-cell WGA method termed multiplexed end-tagging amplification of complementary strands (META-CS), which eliminates nearly all FPs by virtue of DNA complementarity, and achieved the highest accuracy thus far. We validated META-CS by sequencing kindred cells and human sperm, and applied it to other human tissues. Investigation of mature single human neurons revealed increasing SNVs with age and potentially unrepaired strand-specific oxidative guanine damage. We determined SNV frequencies along the genome in differentiated single human blood cells, and identified cell type-dependent mutational patterns for major types of lymphocytes.

Molecular foundations of prion strain diversity

Despite being caused by a single protein, prion diseases are strikingly heterogenous. Individual prion variants, known as strains, possess distinct biochemical properties, form aggregates with characteristic morphologies and preferentially seed certain brain regions, causing markedly different disease phenotypes. Strain diversity is determined by protein structure, post-translational modifications and the presence of extracellular matrix components, with single amino acid substitutions or altered protein glycosylation exerting dramatic effects. Here, we review recent advances in the study of prion strains and discuss how a deeper knowledge of the molecular origins of strain heterogeneity is providing a foundation for the development of anti-prion therapeutics.

Retrospective cell lineage reconstruction in humans by using short tandem repeats

Cell lineage analysis aims to uncover the developmental history of an organism back to its cell of origin. Recently, novel in vivo methods utilizing genome editing enabled important insights into the cell lineages of animals. In contrast, human cell lineage remains restricted to retrospective approaches, which still lack resolution and cost-efficient solutions. Here, we demonstrate a scalable platform based on short tandem repeats targeted by duplex molecular inversion probes. With this human cell lineage tracing method, we accurately reproduced a known lineage of DU145 cells and reconstructed lineages of healthy and metastatic single cells from a melanoma patient who matched the anatomical reference while adding further refinements. This platform allowed us to faithfully recapitulate lineages of developmental tissue formation in healthy cells. In summary, our lineage discovery platform can profile informative somatic mutations efficiently and provides solid lineage reconstructions even in challenging low-mutation-rate healthy single cells.

Non-Cell Autonomous Epileptogenesis in Focal Cortical Dysplasia

OBJECTIVE

Low-level somatic mosaicism in the brain has been shown to be a major genetic cause of intractable focal epilepsy. However, how a relatively few mutation-carrying neurons are able to induce epileptogenesis at the local network level remains poorly understood.

METHODS

To probe the origin of epileptogenesis, we measured the excitability of neurons with MTOR mutation and nearby nonmutated neurons recorded by whole-cell patch-clamp and array-based electrodes comparing the topographic distribution of mutation. Computational simulation is used to understand neural network-level changes based on electrophysiological properties. To examine the underlying mechanism, we measured inhibitory and excitatory synaptic inputs in mutated neurons and nearby neurons by electrophysiological and histological methods using the mouse model and postoperative human brain tissue for cortical dysplasia. To explain non-cell-autonomous hyperexcitability, an inhibitor of adenosine kinase was injected into mice to enhance adenosine signaling and to mitigate hyperactivity of nearby nonmutated neurons.

RESULTS

We generated mice with a low-level somatic mutation in MTOR presenting spontaneous seizures. The seizure-triggering hyperexcitability originated from nonmutated neurons near mutation-carrying neurons, which proved to be less excitable than nonmutated neurons. Interestingly, the net balance between excitatory and inhibitory synaptic inputs onto mutated neurons remained unchanged. Additionally, we found that inhibition of adenosine kinase, which affects adenosine metabolism and neuronal excitability, reduced the hyperexcitability of nonmutated neurons.

INTERPRETATION

This study shows that neurons carrying somatic mutations in MTOR lead to focal epileptogenesis via non-cell-autonomous hyperexcitability of nearby nonmutated neurons. ANN NEUROL 2021;90:285-299.

Genomic Mosaicism Formed by Somatic Variation in the Aging and Diseased Brain

Over the past 20 years, analyses of single brain cell genomes have revealed that the brain is composed of cells with myriad distinct genomes: the brain is a genomic mosaic, generated by a host of DNA sequence-altering processes that occur somatically and do not affect the germline. As such, these sequence changes are not heritable. Some processes appear to occur during neurogenesis, when cells are mitotic, whereas others may also function in post-mitotic cells. Here, we review multiple forms of DNA sequence alterations that have now been documented: aneuploidies and aneusomies, smaller copy number variations (CNVs), somatic repeat expansions, retrotransposons, genomic cDNAs (gencDNAs) associated with somatic gene recombination (SGR), and single nucleotide variations (SNVs). A catch-all term of DNA content variation (DCV) has also been used to describe the overall phenomenon, which can include multiple forms within a single cell's genome. A requisite step in the analyses of genomic mosaicism is ongoing technology development, which is also discussed. Genomic mosaicism alters one of the most stable biological molecules, DNA, which may have many repercussions, ranging from normal functions including effects of aging, to creating dysfunction that occurs in neurodegenerative and other brain diseases, most of which show sporadic presentation, unlinked to causal, heritable genes.

Single-cell damagenome profiling unveils vulnerable genes and functional pathways in human genome toward DNA damage

We report a novel single-cell whole-genome amplification method (LCS-WGA) that can efficiently capture spontaneous DNA damage existing in single cells. We refer to these damage-associated single-nucleotide variants as "damSNVs," and the whole-genome distribution of damSNVs as the damagenome. We observed that in single human neurons, the damagenome distribution was significantly correlated with three-dimensional genome structures. This nonuniform distribution indicates different degrees of DNA damage effects on different genes. Next, we identified the functionals that were significantly enriched in the high-damage genes. Similar functionals were also enriched in the differentially expressed genes (DEGs) detected by single-cell transcriptome of both Alzheimer's disease (AD) and autism spectrum disorder (ASD). This result can be explained by the significant enrichment of high-damage genes in the DEGs of neurons for both AD and ASD. The discovery of high-damage genes sheds new lights on the important roles of DNA damage in human diseases and disorders.

Application of single cell genomics to focal epilepsies: A call to action

Focal epilepsies are the largest epilepsy subtype and associated with significant morbidity. Somatic variation is a newly recognized genetic mechanism underlying a subset of focal epilepsies, but little is known about the processes through which somatic mosaicism causes seizures, the cell types carrying the pathogenic variants, or their developmental origin. Meanwhile, the inception of single cell biology has completely revolutionized the study of neurological diseases and has the potential to answer some of these key questions. Focusing on single cell genomics, transcriptomics, and epigenomics in focal epilepsy research, circumvents the averaging artifact associated with studying bulk brain tissue and offers the kind of granularity that is needed for investigating the consequences of somatic mosaicism. Here we have provided a brief overview of some of the most developed single cell techniques and the major considerations around applying them to focal epilepsy research.

Assessment of the gene mosaicism burden in blood and its implications for immune disorders

There are increasing evidences showing the contribution of somatic genetic variants to non-cancer diseases. However, their detection using massive parallel sequencing methods still has important limitations. In addition, the relative importance and dynamics of somatic variation in healthy tissues are not fully understood. We performed high-depth whole-exome sequencing in 16 samples from patients with a previously determined pathogenic somatic variant for a primary immunodeficiency and tested different variant callers detection ability. Subsequently, we explored the load of somatic variants in the whole blood of these individuals and validated it by amplicon-based deep sequencing. Variant callers allowing low frequency read thresholds were able to detect most of the variants, even at very low frequencies in the tissue. The genetic load of somatic coding variants detectable in whole blood is low, ranging from 1 to 2 variants in our dataset, except for one case with 17 variants compatible with clonal haematopoiesis under genetic drift. Because of the ability we demonstrated to detect this type of genetic variation, and its relevant role in disorders such as primary immunodeficiencies, we suggest considering this model of gene mosaicism in future genetic studies and considering revisiting previous massive parallel sequencing data in patients with negative results.

Neuronal enhancers get a break

Emerging evidence shows that neuronal DNA is continuously broken and repaired in a non-random fashion within the genome. Two recent studies, Wu et al. (2021) and Reid et al. (2021), use sequencing of newly synthesized DNA in post-mitotic neurons to map hotspots of DNA repair across the genome. Wu et al. (2021) further show that the repair sites are associated with single-stranded DNA breaks that predominantly occur on neuronal enhancers at sites of CpG methylation.

Brain Somatic Mutation in Aging and Alzheimer's Disease

Somatic mutations arise postzygotically, producing genetic differences between cells in an organism. Well established as a driver of cancer, somatic mutations also exist in nonneoplastic cells, including in the brain. Technological advances in nucleic acid sequencing have enabled recent break-throughs that illuminate the roles of somatic mutations in aging and degenerative diseases of the brain. Somatic mutations accumulate during aging in human neurons, a process termed genosenium. A number of recent studies have examined somatic mutations in Alzheimer’s disease (AD), primarily from the perspective of genes causing familial AD. We have also gained new information on genome-wide mutations, providing insights into the cellular events driving somatic mutation and cellular dysfunction. This review highlights recent concepts, methods, and findings in the progress to understand the role of brain somatic mutation in aging and AD.