Single-cell whole-genome sequencing reveals the functional landscape of somatic mutations in B lymphocytes across the human lifespan

Recent Innovations and Technical Advances in High-Throughput Parallel Single-Cell Whole-Genome Sequencing Methods

Single-cell whole-genome sequencing (scWGS) detects cell heterogeneity at the aspect of genomic variations, which are inheritable and play an important role in life processes such as aging and cancer progression. The recent explosive development of high-throughput single-cell sequencing methods has enabled high-performance heterogeneity detection through a vast number of novel strategies. Despite the limitation on total cost, technical advances in high-throughput single-cell whole-genome sequencing methods are made for higher genome coverage, parallel throughput, and level of integration. This review highlights the technical advancements in high-throughput scWGS in the aspects of strategies design, data efficiency, parallel handling platforms, and their applications on human genome. The experimental innovations, remaining challenges, and perspectives are summarized and discussed.

Single-cell sequencing advances in research on mesenchymal stem/stromal cells

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

Biochemical reconstitution of a major age-related cancer mutational signature by heat-induced spontaneous deamination of 5-methylcytosine residues, repair of uracil residues, and DNA replication

Non-enzymatic spontaneous deamination of 5-methylcytosine, producing thymine, is the proposed etiology of cancer mutational signature 1, which is the most predominant signature in all cancers. Here, the proposed mutational process was reconstituted using synthetic DNA and purified proteins. First, single-stranded DNA containing 5-methylcytosine at CpG context was incubated at an elevated temperature to accelerate spontaneous DNA damage. Then, the DNA was treated with uracil DNA glycosylase to remove uracil residues that were formed by deamination of cytosine. The resulting DNA was then used as a template for DNA synthesis by yeast DNA polymerase δ. The DNA products were analyzed by next-generation DNA sequencing, and mutation frequencies were quantified. The observed mutations after this process were exclusively C>T mutations at CpG context, which was very similar to signature 1. When 5-methylcytosine modification and uracil DNA glycosylase were both omitted, C>T mutations were produced on C residues in all sequence contexts, but these mutations were diminished by uracil DNA glycosylase-treatment. These results indicate that the CpG>TpG mutations were produced by the deamination of 5-methylcytosine. Additional mutations, mainly C>G, were introduced by yeast DNA polymerase ζ on the heat-damaged DNA, indicating that G residues of the templates were also damaged. However, the damage on G residues was not converted to mutations with DNA polymerase δ or ε. These results provide biochemical evidence to support that the majority of mutations in cancers are produced by ordinary DNA replication on spontaneously damaged DNA.

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse Fibroblasts In Vitro to Tolerate High Levels of Somatic Mutations

Substantial numbers of somatic mutations have been found to accumulate with age in different human tissues. Clonal cellular amplification of some of these mutations can cause cancer and other diseases. However, it is as yet unclear if and to what extent an increased burden of random mutations can affect cellular function without clonal amplification. We tested this in cell culture, which avoids the limitation that an increased mutation burden in vivo typically leads to cancer. We performed single-cell whole-genome sequencing of primary fibroblasts from DNA mismatch repair (MMR) deficient Msh2-/- mice and littermate control animals after long-term passaging. Apart from analyzing somatic mutation burden we analyzed clonality, mutational signatures, and hotspots in the genome, characterizing the complete landscape of somatic mutagenesis in normal and MMR-deficient mouse primary fibroblasts during passaging. While growth rate of Msh2-/- fibroblasts was not significantly different from the controls, the number of de novo single-nucleotide variants (SNVs) increased linearly up until at least 30,000 SNVs per cell, with the frequency of small insertions and deletions (INDELs) plateauing in the Msh2-/- fibroblasts to about 10,000 INDELS per cell. We provide evidence for negative selection and large-scale mutation-driven population changes, including significant clonal expansion of preexisting mutations and widespread cell-strain-specific hotspots. Overall, our results provide evidence that increased somatic mutation burden drives significant cell evolutionary changes in a dynamic cell culture system without significant effects on growth. Since similar selection processes against mutations preventing organ and tissue dysfunction during aging are difficult to envision, these results suggest that increased somatic mutation burden can play a causal role in aging and diseases other than cancer.

Somatic mutations in human ageing: New insights from DNA sequencing and inherited mutations

The accumulation of somatic mutations is a driver of cancer and has long been associated with ageing. Due to limitations in quantifying mutation burden with age in non-cancerous tissues, the impact of somatic mutations in other ageing phenotypes is unclear. Recent advances in DNA sequencing technologies have allowed the large-scale quantification of somatic mutations in ageing tissues. These studies have revealed a gradual accumulation of mutations in normal tissues with age as well as a substantial clonal expansion driven mostly by cancer-related mutations. Nevertheless, it is difficult to envision how the burden and stochastic nature of age-related somatic mutations identified so far can explain most ageing phenotypes that develop gradually. Studies across species have also found that longer-lived species have lower somatic mutation rates, though these could be due to selective pressures acting on other phenotypes such as perhaps cancer. Recent studies in patients with higher somatic mutation burden and no signs of accelerated ageing further question the role of somatic mutations in ageing. Overall, with a few exceptions like cancer, recent DNA sequencing studies and inherited mutations do not support the idea that somatic mutations accumulating with age drive ageing phenotypes, and the phenotypic role, if any, of somatic mutations in ageing remains unclear.

Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing

Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.

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.

Toolkit for mapping the clonal landscape of tumor-infiltrating B cells

Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Analyzing somatic mutations by single-cell whole-genome sequencing

Somatic mutations are the cause of cancer and have been implicated in other, noncancerous diseases and aging. While clonally expanded mutations can be studied by deep sequencing of bulk DNA, very few somatic mutations expand clonally, and most are unique to each cell. We describe a detailed protocol for single-cell whole-genome sequencing to discover and analyze somatic mutations in tissues and organs. The protocol comprises single-cell multiple displacement amplification (SCMDA), which ensures efficiency and high fidelity in amplification, and the SCcaller software tool to call single-nucleotide variations and small insertions and deletions from the sequencing data by filtering out amplification artifacts. With SCMDA and SCcaller at its core, this protocol describes a complete procedure for the comprehensive analysis of somatic mutations in a single cell, covering (1) single-cell or nucleus isolation, (2) single-cell or nucleus whole-genome amplification, (3) library preparation and sequencing, and (4) computational analyses, including alignment, variant calling, and mutation burden estimation. Methods are also provided for mutation annotation, hotspot discovery and signature analysis. The protocol takes 12-15 h from single-cell isolation to library preparation and 3-7 d of data processing. Compared with other single-cell amplification methods or single-molecular sequencing, it provides high genomic coverage, high accuracy in single-nucleotide variation and small insertions and deletion calling from the same single-cell genome, and fewer processing steps. SCMDA and SCcaller require basic experience in molecular biology and bioinformatics. The protocol can be utilized for studying mutagenesis and genome mosaicism in normal and diseased human and animal tissues under various conditions.

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.

Genome Instability and DNA Repair in Somatic and Reproductive Aging

Genetic material is constantly subjected to genotoxic insults and is critically dependent on DNA repair. Genome maintenance mechanisms differ in somatic and germ cells as the soma only requires maintenance during an individual's lifespan, while the germline indefinitely perpetuates its genetic information. DNA lesions are recognized and repaired by mechanistically highly diverse repair machineries. The DNA damage response impinges on a vast array of homeostatic processes and can ultimately result in cell fate changes such as apoptosis or cellular senescence. DNA damage causally contributes to the aging process and aging-associated diseases, most prominently cancer. By causing mutations, DNA damage in germ cells can lead to genetic diseases and impact the evolutionary trajectory of a species. The mechanisms ensuring tight control of germline DNA repair could be highly instructive in defining strategies for improved somatic DNA repair. They may provide future interventions to maintain health and prevent disease during aging.

Scrutiny of genome-wide somatic mutation profiles in centenarians identifies the key genomic regions for human longevity

Somatic mutations accumulate with age and are associated closely with human health, their characterization in longevity cohorts remains largely unknown. Here, by analyzing whole genome somatic mutation profiles in 73 centenarians and 51 younger controls in China, we found that centenarian genomes are characterized by a markedly skewed distribution of somatic mutations, with many genomic regions being specifically conserved but displaying a high function potential. This, together with the observed more efficient DNA repair ability in the long-lived individuals, supports the existence of key genomic regions for human survival during aging, with their integrity being of essential to human longevity.

The ticking of aging clocks

Computational models that measure biological age and aging rate regardless of chronological age are called aging clocks. The underlying counting mechanisms of the intrinsic timers of these clocks are still unclear. Molecular mediators and determinants of aging rate point to the key roles of DNA damage, epigenetic drift, and inflammation. Persistent DNA damage leads to cellular senescence and the senescence-associated secretory phenotype (SASP), which induces cytotoxic immune cell infiltration; this further induces DNA damage through reactive oxygen and nitrogen species (RONS). I discuss the possibility that DNA damage (or the response to it, including epigenetic changes) is the fundamental counting unit of cell cycles and cellular senescence, that ultimately accounts for cell composition changes and functional decline in tissues, as well as the key intervention points.

Somatic mutation as an explanation for epigenetic aging

DNA methylation marks have recently been used to build models known as "epigenetic clocks" which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In analysis of multimodal data from 9,331 human individuals, we find that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but also with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping enables mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging faster or slower than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.

Somatic mutation burden in relation to aging and functional life span: implications for cellular reprogramming and rejuvenation

The accrual of somatic mutations has been implicated as causal factors in aging since the 1950s. However, the quantitative analysis of somatic mutations has posed a major challenge due to the random nature of de novo mutations in normal tissues, which has limited analysis to tumors and other clonal lineages. Advances in single-cell and single-molecule next-generation sequencing now allow to obtain, for the first time, detailed insights into the landscape of somatic mutations in different human tissues and cell types as a function of age under various conditions. Here, we will briefly recapitulate progress in somatic mutation analysis and discuss the possible relationship between somatic mutation burden with functional life span, with a focus on differences between germ cells, stem cells, and differentiated cells.

Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer

Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.

Single-cell transcriptomic and genomic changes in the aging human brain

Aging brings dysregulation of various processes across organs and tissues, often stemming from stochastic damage to individual cells over time. Here, we used a combination of single-nucleus RNA-sequencing and single-cell whole-genome sequencing to identify transcriptomic and genomic changes in the prefrontal cortex of the human brain across life span, from infancy to centenarian. We identified infant-specific cell clusters enriched for the expression of neurodevelopmental genes, and a common down-regulation of cell-essential homeostatic genes that function in ribosomes, transport, and metabolism during aging across cell types. Conversely, expression of neuron-specific genes generally remains stable throughout life. We observed a decrease in specific DNA repair genes in aging, including genes implicated in generating brain somatic mutations as indicated by mutation signature analysis. Furthermore, we detected gene-length-specific somatic mutation rates that shape the transcriptomic landscape of the aged human brain. These findings elucidate critical aspects of human brain aging, shedding light on transcriptomic and genomics dynamics.

Stem cell mutations, associated cancer risk, and consequences for regenerative medicine

Mutation accumulation in stem cells has been associated with cancer risk. However, the presence of numerous mutant clones in healthy tissues has raised the question of what limits cancer initiation. Here, we review recent developments in characterizing mutation accumulation in healthy tissues and compare mutation rates in stem cells during development and adult life with corresponding cancer risk. A certain level of mutagenesis within the stem cell pool might be beneficial to limit the size of malignant clones through competition. This knowledge impacts our understanding of carcinogenesis with potential consequences for the use of stem cells in regenerative medicine.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Aging and Age-Related Epigenetic Drift in the Pathogenesis of Leukemia and Lymphomas: New Therapeutic Targets

One of the traits of cancer cells is abnormal DNA methylation patterns. The idea that age-related epigenetic changes may partially explain the increased risk of cancer in the elderly is based on the observation that aging is also accompanied by comparable changes in epigenetic patterns. Lineage bias and decreased stem cell function are signs of hematopoietic stem cell compartment aging. Additionally, aging in the hematopoietic system and the stem cell niche have a role in hematopoietic stem cell phenotypes linked with age, such as leukemia and lymphoma. Understanding these changes will open up promising pathways for therapies against age-related disorders because epigenetic mechanisms are reversible. Additionally, the development of high-throughput epigenome mapping technologies will make it possible to identify the "epigenomic identity card" of every hematological disease as well as every patient, opening up the possibility of finding novel molecular biomarkers that can be used for diagnosis, prediction, and prognosis.

Genomic Instability and Epigenetic Changes during Aging

Aging is considered the deterioration of physiological functions along with an increased mortality rate. This scientific review focuses on the central importance of genomic instability during the aging process, encompassing a range of cellular and molecular changes that occur with advancing age. In particular, this revision addresses the genetic and epigenetic alterations that contribute to genomic instability, such as telomere shortening, DNA damage accumulation, and decreased DNA repair capacity. Furthermore, the review explores the epigenetic changes that occur with aging, including modifications to histones, DNA methylation patterns, and the role of non-coding RNAs. Finally, the review discusses the organization of chromatin and its contribution to genomic instability, including heterochromatin loss, chromatin remodeling, and changes in nucleosome and histone abundance. In conclusion, this review highlights the fundamental role that genomic instability plays in the aging process and underscores the need for continued research into these complex biological mechanisms.

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.

Urgent needs of caregiving in ageing populations with Alzheimer's disease and other chronic conditions: Support our loved ones

The ageing process begins at birth. It is a life-long process, and its exact origins are still unknown. Several hypotheses attempt to describe the normal ageing process, including hormonal imbalance, formation of reactive oxygen species, DNA methylation & DNA damage accumulation, loss of proteostasis, epigenetic alterations, mitochondrial dysfunction, senescence, inflammation, and stem cell depletion. With increased lifespan in elderly individuals, the prevalence of age-related diseases including, cancer, diabetes, obesity, hypertension, Alzheimer's, Alzheimer's disease and related dementias, Parkinson's, and other mental illnesses are increased. These increased age-related illnesses, put tremendous pressure & burden on caregivers, family members, and friends who are living with patients with age-related diseases. As medical needs evolve, the caregiver is expected to experience an increase in duties and challenges, which may result in stress on themselves, and impact their own family life. In the current article, we assess the biological mechanisms of ageing and its effect on body systems, exploring lifestyle and ageing, with a specific focus on age-related disorders. We also discussed the history of caregiving and specific challenges faced by caregivers in the presence of multiple comorbidities. We also assessed innovative approaches to funding caregiving, and efforts to improve the medical system to better organize chronic care efforts, while improving the skill and efficiency of both informal and formal caregivers. We also discussed the role of caregiving in end-of-life care. Our critical analysis strongly suggests that there is an urgent need for caregiving in aged populations and support from local, state, and federal agencies.

Barcoded multiple displacement amplification for high coverage sequencing in spatial genomics

Determining mutational landscapes in a spatial context is essential for understanding genetically heterogeneous cell microniches. Current approaches, such as Multiple Displacement Amplification (MDA), offer high genome coverage but limited multiplexing, which hinders large-scale spatial genomic studies. Here, we introduce barcoded MDA (bMDA), a technique that achieves high-coverage genomic analysis of low-input DNA while enhancing the multiplexing capabilities. By incorporating cell barcodes during MDA, bMDA streamlines library preparation in one pot, thereby overcoming a key bottleneck in spatial genomics. We apply bMDA to the integrative spatial analysis of triple-negative breast cancer tissues by examining copy number alterations, single nucleotide variations, structural variations, and kataegis signatures for each spatial microniche. This enables the assessment of subclonal evolutionary relationships within a spatial context. Therefore, bMDA has emerged as a scalable technology with the potential to advance the field of spatial genomics significantly.

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.

Decoding Aging Hallmarks at the Single-Cell Level

Organismal aging exhibits wide-ranging hallmarks in divergent cell types across tissues, organs, and systems. The advancement of single-cell technologies and generation of rich datasets have afforded the scientific community the opportunity to decode these hallmarks of aging at an unprecedented scope and resolution. In this review, we describe the technological advancements and bioinformatic methodologies enabling data interpretation at the cellular level. Then, we outline the application of such technologies for decoding aging hallmarks and potential intervention targets and summarize common themes and context-specific molecular features in representative organ systems across the body. Finally, we provide a brief summary of available databases relevant for aging research and present an outlook on the opportunities in this emerging field.

Concurrent analysis of genome and transcriptome in one single cell

Thus far, multiple techniques for single cell analysis have been developed, yet we lack a relatively simple tool to assess DNA and RNA from the same cell at whole-transcriptome and whole-genome depths. Here we present an updated method for physical separation of cytoplasmic RNA from the nuclei, which allows for simultaneous studies of DNA and RNA from the same single cell. The method consists of three steps - 1) immobilization of a single cell on solid substrate, 2) hypotonic lysis of immobilized single cell, and 3) separation of cytosol containing aqueous phase and immobilized nucleus. We found that DNA and RNA extracted from single cell using our approach is suitable for downstream sequencing-based applications. We demonstrated that the coverage of transcriptome and genome sequencing data obtained after DNA/RNA separation is similar to that observed without separation. We also showed that the separation procedure does not create any noticeable bias in observed mutational load or mutation spectra. Thus, our method can serve as a tool for simultaneous complex analysis of the genome and transcriptome, providing necessary information on the relationship between somatic mutations and the regulation of gene expression.

A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures

Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation "clocks" in data from aging muscle stem cells, Alzheimer's disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

Transcriptome-based measurement of CD8+ T cell age and its applications

The ability of T cells to undergo robust cell division in response to antigenic stimulation is essential for competent T cell function. However, this ability is reduced with aging and contributes to increased susceptibility to infectious diseases, cancers, and other diseases among older adults. To better understand T cell aging, improved measurements of age-related cellular changes in T cells are necessary. The recent development of machine learning (ML)-assisted transcriptome-based quantification of individual CD8+ T cell age represents a significant step forward in this regard. It reveals both prominent and subtle changes in gene expression and points to potential functional alterations of CD8+ T cells with aging. I argue that single-cell transcriptome-based age prediction in the immune system may have promising future applications.

The landscape of somatic mutations in lymphoblastoid cell lines

Somatic mutations have important biological ramifications while exerting substantial rate, type, and genomic location heterogeneity. Yet, their sporadic occurrence makes them difficult to study at scale and across individuals. Lymphoblastoid cell lines (LCLs), a model system for human population and functional genomics, harbor large numbers of somatic mutations and have been extensively genotyped. By comparing 1,662 LCLs, we report that the mutational landscape of the genome varies across individuals in terms of the number of mutations, their genomic locations, and their spectra; this variation may itself be modulated by somatic trans-acting mutations. Mutations attributed to the translesion DNA polymerase η follow two different modes of formation, with one mode accounting for the hypermutability of the inactive X chromosome. Nonetheless, the distribution of mutations along the inactive X chromosome appears to follow an epigenetic memory of the active form.

Cell-type specificity of the human mutation landscape with respect to DNA replication dynamics

The patterns of genomic mutations are associated with various genomic features, most notably late replication timing, yet it remains contested which mutation types and signatures relate to DNA replication dynamics and to what extent. Here, we perform high-resolution comparisons of mutational landscapes between lymphoblastoid cell lines, chronic lymphocytic leukemia tumors, and three colon adenocarcinoma cell lines, including two with mismatch repair deficiency. Using cell-type-matched replication timing profiles, we demonstrate that mutation rates exhibit heterogeneous replication timing associations among cell types. This cell-type heterogeneity extends to the underlying mutational pathways, as mutational signatures show inconsistent replication timing bias between cell types. Moreover, replicative strand asymmetries exhibit similar cell-type specificity, albeit with different relationships to replication timing than mutation rates. Overall, we reveal an underappreciated complexity and cell-type specificity of mutational pathways and their relationship to replication timing.

Mitigating age-related somatic mutation burden

Genomes are inherently unstable and require constant DNA repair to maintain their genetic information. However, selective pressure has optimized repair mechanisms in somatic cells only to allow transmitting genetic information to the next generation, not to maximize sequence integrity long beyond the reproductive age. Recent studies have confirmed that somatic mutations, due to errors during genome repair and replication, accumulate in tissues and organs of humans and model organisms. Here, we describe recent advances in the quantitative analysis of somatic mutations in vivo. We also review evidence for or against a possible causal role of somatic mutations in aging. Finally, we discuss options to prevent, delay or eliminate de novo, random somatic mutations as a cause of aging.

The Molecular Mechanism of Polyphenols in the Regulation of Ageing Hallmarks

Ageing is a complex process characterized mainly by a decline in the function of cells, tissues, and organs, resulting in an increased risk of mortality. This process involves several changes, described as hallmarks of ageing, which include genomic instability, telomere attrition, epigenetic changes, loss of proteostasis, dysregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell depletion, and altered intracellular communication. The determining role that environmental factors such as diet and lifestyle play on health, life expectancy, and susceptibility to diseases, including cancer and neurodegenerative diseases, is wellestablished. In view of the growing interest in the beneficial effects of phytochemicals in the prevention of chronic diseases, several studies have been conducted, and they strongly suggest that the intake of dietary polyphenols may bring numerous benefits due to their antioxidant and anti-inflammatory properties, and their intake has been associated with impaired ageing in humans. Polyphenol intake has been shown to be effective in ameliorating several age-related phenotypes, including oxidative stress, inflammatory processes, impaired proteostasis, and cellular senescence, among other features, which contribute to an increased risk of ageing-associated diseases. This review aims to address, in a general way, the main findings described in the literature about the benefits of polyphenols in each of the hallmarks of ageing, as well as the main regulatory mechanisms responsible for the observed antiageing effects.

Lymphoma-associated mutations in autoreactive memory B cells of patients with Sjögren's syndrome

We recently demonstrated that normal memory B lymphocytes carry a substantial number of de novo mutations in the genome. Here, we performed exome-wide somatic mutation analyses of bona fide autoreactive rheumatoid factor (RF)-expressing memory B cells retrieved from patients with Sjӧgren's syndrome (SS). The amount and repertoire of the de novo exome mutations of RF B cells were found to be essentially different from those detected in healthy donor memory B cells. In contrast to the mutation spectra of normal B cells, which appeared random and non-selected, the mutations of the RF B cells were greater in number and enriched for mutations in genes also found mutated in B-cell non-Hodgkin lymphomas. During the study, one of the SS patients developed a diffuse large B-cell lymphoma (DLBCL) out of an RF clone that was identified 2 years earlier in an inflamed salivary gland biopsy. The successive oncogenic events in the RF precursor clone and the DLBCL were assessed. In conclusion, our findings of enhanced and selected genomic damage in growth-regulating genes in RF memory B cells of SS patients together with the documented transformation of an RF-precursor clone into DLBCL provide unique novel insight into the earliest stages of B-cell derailment and lymphomagenesis. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The role of structural variations in Alzheimer's disease and other neurodegenerative diseases

Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.

Single-cell omics: A new direction for functional genetic research in human diseases and animal models

Over the past decade, with the development of high-throughput single-cell sequencing technology, single-cell omics has been emerged as a powerful tool to understand the molecular basis of cellular mechanisms and refine our knowledge of diverse cell states. They can reveal the heterogeneity at different genetic layers and elucidate their associations by multiple omics analysis, providing a more comprehensive genetic map of biological regulatory networks. In the post-GWAS era, the molecular biological mechanisms influencing human diseases will be further elucidated by single-cell omics. This review mainly summarizes the development and trend of single-cell omics. This involves single-cell omics technologies, single-cell multi-omics technologies, multiple omics data integration methods, applications in various human organs and diseases, classic laboratory cell lines, and animal disease models. The review will reveal some perspectives for elucidating human diseases and constructing animal models.

Predicting mutational function using machine learning

Genetic variations are one of the major causes of phenotypic variations between human individuals. Although beneficial as being the substrate of evolution, germline mutations may cause diseases, including Mendelian diseases and complex diseases such as diabetes and heart diseases. Mutations occurring in somatic cells are a main cause of cancer and likely cause age-related phenotypes and other age-related diseases. Because of the high abundance of genetic variations in the human genome, i.e., millions of germline variations per human subject and thousands of additional somatic mutations per cell, it is technically challenging to experimentally verify the function of every possible mutation and their interactions. Significant progress has been made to solve this problem using computational approaches, especially machine learning (ML). Here, we review the progress and achievements made in recent years in this field of research. We classify the computational models in two ways: one according to their prediction goals including protein structural alterations, gene expression changes, and disease risks, and the other according to their methodologies, including non-machine learning methods, classical machine learning methods, and deep neural network methods. For models in each category, we discuss their architecture, prediction accuracy, and potential limitations. This review provides new insights into the applications and future directions of computational approaches in understanding the role of mutations in aging and disease.

Research priorities for measuring biologic age: summary and future directions from the Research Centers Collaborative Network Workshop

Biologic aging reflects the genetic, molecular, and cellular changes underlying the development of morbidity and mortality with advancing chronological age. As several potential mechanisms have been identified, there is a growing interest in developing robust measures of biologic age that can better reflect the underlying biology of aging and predict age-related outcomes. To support this endeavor, the Research Centers Collaborative Network (RCCN) conducted a workshop in January 2022 to discuss emerging concepts in the field and identify opportunities to move the science forward. This paper presents workshop proceedings and summarizes the identified research needs, priorities, and recommendations for measuring biologic age. The highest priorities identified were the need for more robust measures, longitudinal studies, multidisciplinary collaborations, and translational approaches.

Reducing the aneuploid cell burden - cell competition and the ribosome connection

Aneuploidy, the gain or loss of chromosomes, is the cause of birth defects and miscarriage and is almost ubiquitous in cancer cells. Mosaic aneuploidy causes cancer predisposition, as well as age-related disorders. Despite the cell-intrinsic mechanisms that prevent aneuploidy, sporadic aneuploid cells do arise in otherwise normal tissues. These aneuploid cells can differ from normal cells in the copy number of specific dose-sensitive genes, and may also experience proteotoxic stress associated with mismatched expression levels of many proteins. These differences may mark aneuploid cells for recognition and elimination. The ribosomal protein gene dose in aneuploid cells could be important because, in Drosophila, haploinsufficiency for these genes leads to elimination by the process of cell competition. Constitutive haploinsufficiency for human ribosomal protein genes causes Diamond Blackfan anemia, but it is not yet known whether ribosomal protein gene dose contributes to aneuploid cell elimination in mammals. In this Review, we discuss whether cell competition on the basis of ribosomal protein gene dose is a tumor suppressor mechanism, reducing the accumulation of aneuploid cells. We also discuss how this might relate to the tumor suppressor function of p53 and the p53-mediated elimination of aneuploid cells from murine embryos, and how cell competition defects could contribute to the cancer predisposition of Diamond Blackfan anemia.

The two faces of DNA oxidation in genomic and functional mosaicism during aging in human neurons

Maintaining genomic integrity in post-mitotic neurons in the human brain is paramount because these cells must survive for an individual's entire lifespan. Due to life-long synaptic plasticity and electrochemical transmission between cells, the brain engages in an exceptionally high level of mitochondrial metabolic activity. This activity results in the generation of reactive oxygen species with 8-oxo-7,8-dihydroguanine (8-oxoG) being one of the most prevalent oxidation products in the cell. 8-oxoG is important for the maintenance and transfer of genetic information into proper gene expression: a low basal level of 8-oxoG plays an important role in epigenetic modulation of neurodevelopment and synaptic plasticity, while a dysregulated increase in 8-oxoG damages the genome leading to somatic mutations and transcription errors. The slow yet persistent accumulation of DNA damage in the background of increasing cellular 8-oxoG is associated with normal aging as well as neurological disorders such as Alzheimer's disease and Parkinson's disease. This review explores the current understanding of how 8-oxoG plays a role in brain function and genomic instability, highlighting new methods being used to advance pathological hallmarks that differentiate normal healthy aging and neurodegenerative disease.

Prevalence and mechanisms of somatic deletions in single human neurons during normal aging and in DNA repair disorders

Replication errors and various genotoxins cause DNA double-strand breaks (DSBs) where error-prone repair creates genomic mutations, most frequently focal deletions, and defective repair may lead to neurodegeneration. Despite its pathophysiological importance, the extent to which faulty DSB repair alters the genome, and the mechanisms by which mutations arise, have not been systematically examined reflecting ineffective methods. Here, we develop PhaseDel, a computational method to detect focal deletions and characterize underlying mechanisms in single-cell whole genome sequences (scWGS). We analyzed high-coverage scWGS of 107 single neurons from 18 neurotypical individuals of various ages, and found that somatic deletions increased with age and in highly expressed genes in human brain. Our analysis of 50 single neurons from DNA repair-deficient diseases with progressive neurodegeneration (Cockayne syndrome, Xeroderma pigmentosum, and Ataxia telangiectasia) reveals elevated somatic deletions compared to age-matched controls. Distinctive mechanistic signatures and transcriptional associations suggest roles for somatic deletions in neurodegeneration.

Age-related somatic mutation burden in human tissues

The genome of multicellular organisms carries the hereditary information necessary for the development of all organs and tissues and to maintain function in adulthood. To ensure the genetic stability of the species, genomes are protected against changes in sequence information. However, genomes are not static. De novo mutations in germline cells are passed on to offspring and generate the variation needed in evolution. Moreover, postzygotic mutations occur in all somatic cells during development and aging. These somatic mutations remain limited to the individual, generating tissues that are genome mosaics. Insight into such mutations and their consequences has been limited due to their extremely low abundance, with most mutations unique for each cell. Recent advances in sequencing, including whole genome sequencing at the single-cell level, have now led to the first insights into somatic mutation burdens in human tissues. Here, we will first briefly describe the latest methodology for somatic mutation analysis, then review our current knowledge of somatic mutation burden in human tissues and, finally, briefly discuss the possible functional impact of somatic mutations on the aging process and age-related diseases, including cancer and diseases other than cancer.

Heterogeneity and transcriptome changes of human CD8+ T cells across nine decades of life

The decline of CD8⁺ T cell functions contributes to deteriorating health with aging, but the mechanisms that underlie this phenomenon are not well understood. We use single-cell RNA sequencing with both cross-sectional and longitudinal samples to assess how human CD8⁺ T cell heterogeneity and transcriptomes change over nine decades of life. Eleven subpopulations of CD8⁺ T cells and their dynamic changes with age are identified. Age-related changes in gene expression result from changes in the percentage of cells expressing a given transcript, quantitative changes in the transcript level, or a combination of these two. We develop a machine learning model capable of predicting the age of individual cells based on their transcriptomic features, which are closely associated with their differentiation and mutation burden. Finally, we validate this model in two separate contexts of CD8⁺ T cell aging: HIV infection and CAR T cell expansion in vivo.

The characterisation of T cells during aging is important to predict functional outcomes in vaccination or infection. Here the authors use flow cytometry and scRNA sequencing to transcriptionally age CD8 T cells and then use a machine learning model to interpret cell age from transcriptional profiles.

Somatic mutations in single human cardiomyocytes reveal age-associated DNA damage and widespread oxidative genotoxicity

The accumulation of somatic DNA mutations over time is a hallmark of aging in many dividing and nondividing cells but has not been studied in postmitotic human cardiomyocytes. Using single-cell whole-genome sequencing, we identified and characterized the landscape of somatic single-nucleotide variants (sSNVs) in 56 single cardiomyocytes from 12 individuals (aged from 0.4 to 82 years). Cardiomyocyte sSNVs accumulate with age at rates that are faster than in many dividing cell types and nondividing neurons. Cardiomyocyte sSNVs show distinctive mutational signatures that implicate failed nucleotide excision repair and base excision repair of oxidative DNA damage, and defective mismatch repair. Since age-accumulated sSNVs create many damaging mutations that disrupt gene functions, polyploidization in cardiomyocytes may provide a mechanism of genetic compensation to minimize the complete knockout of essential genes during aging. Age-related accumulation of cardiac mutations provides a paradigm to understand the influence of aging on cardiac dysfunction.

Diverse mutational landscapes in human lymphocytes

The lymphocyte genome is prone to many threats, including programmed mutation during differentiation1, antigen-driven proliferation and residency in diverse microenvironments. Here, after developing protocols for expansion of single-cell lymphocyte cultures, we sequenced whole genomes from 717 normal naive and memory B and T cells and haematopoietic stem cells. All lymphocyte subsets carried more point mutations and structural variants than haematopoietic stem cells, with higher burdens in memory cells than in naive cells, and with T cells accumulating mutations at a higher rate throughout life. Off-target effects of immunological diversification accounted for approximately half of the additional differentiation-associated mutations in lymphocytes. Memory B cells acquired, on average, 18 off-target mutations genome-wide for every on-target IGHV mutation during the germinal centre reaction. Structural variation was 16-fold higher in lymphocytes than in stem cells, with around 15% of deletions being attributable to off-target recombinase-activating gene activity. DNA damage from ultraviolet light exposure and other sporadic mutational processes generated hundreds to thousands of mutations in some memory cells. The mutation burden and signatures of normal B cells were broadly similar to those seen in many B-cell cancers, suggesting that malignant transformation of lymphocytes arises from the same mutational processes that are active across normal ontogeny. The mutational landscape of normal lymphocytes chronicles the off-target effects of programmed genome engineering during immunological diversification and the consequences of differentiation, proliferation and residency in diverse microenvironments.

Human Variation in DNA Repair, Immune Function, and Cancer Risk

DNA damage constantly threatens genome integrity, and DNA repair deficiency is associated with increased cancer risk. An intuitive and widely accepted explanation for this relationship is that unrepaired DNA damage leads to carcinogenesis due to the accumulation of mutations in somatic cells. But DNA repair also plays key roles in the function of immune cells, and immunodeficiency is an important risk factor for many cancers. Thus, it is possible that emerging links between inter-individual variation in DNA repair capacity and cancer risk are driven, at least in part, by variation in immune function, but this idea is underexplored. In this review we present an overview of the current understanding of the links between cancer risk and both inter-individual variation in DNA repair capacity and inter-individual variation in immune function. We discuss factors that play a role in both types of variability, including age, lifestyle, and environmental exposures. In conclusion, we propose a research paradigm that incorporates functional studies of both genome integrity and the immune system to predict cancer risk and lay the groundwork for personalized prevention.

Selecting Representative Samples From Complex Biological Datasets Using K-Medoids Clustering

Rapid growth of single-cell sequencing techniques enables researchers to investigate almost millions of cells with diverse properties in a single experiment. Meanwhile, it also presents great challenges for selecting representative samples from massive single-cell populations for further experimental characterization, which requires a robust and compact sampling with balancing diverse properties of different priority levels. The conventional sampling methods fail to generate representative and generalizable subsets from a massive single-cell population or more complicated ensembles. Here, we present a toolkit called Cookie which can efficiently select out the most representative samples from a massive single-cell population with diverse properties. This method quantifies the relationships/similarities among samples using their Manhattan distances by vectorizing all given properties and then determines an appropriate sample size by evaluating the coverage of key properties from multiple candidate sizes, following by a k-medoids clustering to group samples into several clusters and selects centers from each cluster as the most representatives. Comparison of Cookie with conventional sampling methods using a single-cell atlas dataset, epidemiology surveillance data, and a simulated dataset shows the high efficacy, efficiency, and flexibly of Cookie. The Cookie toolkit is implemented in R and is freely available at https://wilsonimmunologylab.github.io/Cookie/.

The Dynamics of Somatic Mutagenesis During Life in Humans

From conception to death, human cells accumulate somatic mutations in their genomes. These mutations can contribute to the development of cancer and non-malignant diseases and have also been associated with aging. Rapid technological developments in sequencing approaches in the last few years and their application to normal tissues have greatly advanced our knowledge about the accumulation of these mutations during healthy aging. Whole genome sequencing studies have revealed that there are significant differences in mutation burden and patterns across tissues, but also that the mutation rates within tissues are surprisingly constant during adult life. In contrast, recent lineage-tracing studies based on whole-genome sequencing have shown that the rate of mutation accumulation is strongly increased early in life before birth. These early mutations, which can be shared by many cells in the body, may have a large impact on development and the origin of somatic diseases. For example, cancer driver mutations can arise early in life, decades before the detection of the malignancy. Here, we review the recent insights in mutation accumulation and mutagenic processes in normal tissues. We compare mutagenesis early and later in life and discuss how mutation rates and patterns evolve during aging. Additionally, we outline the potential impact of these mutations on development, aging and disease.