Detecting Somatic Mutations in Normal Cells

Comprehensive analysis of somatic mutations and structural variations in domestic pig

Understanding somatic mutations and structural variations in domestic pigs (Sus scrofa domestica) is critical due to their increasing importance as model organisms in biomedical research. In this study, we conducted a comprehensive analysis through whole-genome sequencing of skin, organs, and blood samples. By examining two pig pedigrees, we investigated the inheritance and sharedness of structural variants among fathers, mothers, and offsprings. Utilizing single-cell clonal expansion techniques, we observed significant variations in the number of somatic mutations across different tissues. An in-house developed pipeline enabled precise filtering and analysis of these mutations, resulting in the construction of individual phylogenetic trees for two pigs. These trees explored the developmental relationships between different tissues, revealing insights into clonal expansions from various anatomical locations. This study enhances the understanding of pig genomes, affirming their increasing value in clinical and genomic research, and provides a foundation for future studies in other animals, paralleling previous studies in mice and humans. This approach not only deepens our understanding of mammalian genomic variations but also strengthens the role of pigs as a crucial model in human health and disease research.

Genome-wide detection of somatic mosaicism at short tandem repeats

MOTIVATION

Somatic mosaicism has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6 bp and comprise >1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs is lacking.

RESULTS

We introduce prancSTR, a novel method for detecting mosaic STRs from individual high-throughput sequencing datasets. prancSTR is designed to detect loci characterized by a single high-frequency mosaic allele, but can also detect loci with multiple mosaic alleles. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mosaic STRs in simulated data, demonstrate its feasibility by identifying candidate mosaic STRs in Illumina whole genome sequencing data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project, and evaluate the use of prancSTR on Element and PacBio data. In addition to prancSTR, we present simTR, a novel simulation framework which simulates raw sequencing reads with realistic error profiles at STRs.

AVAILABILITY AND IMPLEMENTATION

prancSTR and simTR are freely available at https://github.com/gymrek-lab/trtools. Detailed documentation is available at https://trtools.readthedocs.io/.

A somatic view of the genomic impact of mitochondrial endosymbiosis

The endosymbiosis of mitochondrial ancestors resulted in the transfer of genetic material on an evolutionary scale for eukaryotic species. A new study in PLOS Biology expands this to the genome of somatic cells within individuals and highlights its correlation with aging and disease.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.

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

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

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

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

Initiation of Cancer: The Journey From Mutations in Somatic Cells to Epigenetic Changes in Tissue-resident VSELs

Multiple theories exist to explain cancer initiation, although a consensus on this is crucial for developing effective therapies. 'Somatic mutation theory' suggests that mutations in somatic cells during DNA repair initiates cancer but this concept has several attached paradoxes. Research efforts to identify quiescent cancer stem cells (CSCs) that survive therapy and result in metastasis and recurrence have remained futile. In solid cancers, CSCs are suggested to appear during epithelial-mesenchymal transition by the dedifferentiation and reprogramming of epithelial cells. Pluripotent and quiescent very small embryonic-like stem cells (VSELs) exist in multiple tissues but remain elusive owing to their small size and scarce nature. VSELs are developmentally connected to primordial germ cells, undergo rare, asymmetrical cell divisions and are responsible for the regular turnover of cells to maintain tissue homeostasis throughout life. VSELs are directly vulnerable to extrinsic endocrine insults because they express gonadal and gonadotropin hormone receptors. VSELs undergo epigenetic changes due to endocrine insults and transform into CSCs. CSCs exhibit genomic instability and develop mutations due to errors during DNA replication while undergoing excessive proliferation and clonal expansion to form spheroids. Thus tissue-resident VSELs offer a connection between extrinsic insults and variations in cancer incidence reported in various body tissues. To conclude, cancer is indeed a stem cell disease with mutations occurring as a consequence. In addition to immunotherapy, targeting mutations, and Lgr5 + organoids for developing new therapeutics, targeting CSCs (epigenetically altered VSELs) by improving their niche and epigenetic status could serve as a promising strategy to treat cancer.

From Hematopoietic Stem Cells to Platelets: Unifying Differentiation Pathways Identified by Lineage Tracing Mouse Models

Platelets are the terminal progeny of megakaryocytes, primarily produced in the bone marrow, and play critical roles in blood homeostasis, clotting, and wound healing. Traditionally, megakaryocytes and platelets are thought to arise from multipotent hematopoietic stem cells (HSCs) via multiple discrete progenitor populations with successive, lineage-restricting differentiation steps. However, this view has recently been challenged by studies suggesting that (1) some HSC clones are biased and/or restricted to the platelet lineage, (2) not all platelet generation follows the "canonical" megakaryocytic differentiation path of hematopoiesis, and (3) platelet output is the default program of steady-state hematopoiesis. Here, we specifically investigate the evidence that in vivo lineage tracing studies provide for the route(s) of platelet generation and investigate the involvement of various intermediate progenitor cell populations. We further identify the challenges that need to be overcome that are required to determine the presence, role, and kinetics of these possible alternate pathways.

Current genetic diagnostics in inborn errors of immunity

New technologies in genetic diagnostics have revolutionized the understanding and management of rare diseases. This review highlights the significant advances and latest developments in genetic diagnostics in inborn errors of immunity (IEI), which encompass a diverse group of disorders characterized by defects in the immune system, leading to increased susceptibility to infections, autoimmunity, autoinflammatory diseases, allergies, and malignancies. Various diagnostic approaches, including targeted gene sequencing panels, whole exome sequencing, whole genome sequencing, RNA sequencing, or proteomics, have enabled the identification of causative genetic variants of rare diseases. These technologies not only facilitated the accurate diagnosis of IEI but also provided valuable insights into the underlying molecular mechanisms. Emerging technologies, currently mainly used in research, such as optical genome mapping, single cell sequencing or the application of artificial intelligence will allow even more insights in the aetiology of hereditary immune defects in the near future. The integration of genetic diagnostics into clinical practice significantly impacts patient care. Genetic testing enables early diagnosis, facilitating timely interventions and personalized treatment strategies. Additionally, establishing a genetic diagnosis is necessary for genetic counselling and prognostic assessments. Identifying specific genetic variants associated with inborn errors of immunity also paved the way for the development of targeted therapies and novel therapeutic approaches. This review emphasizes the challenges related with genetic diagnosis of rare diseases and provides future directions, specifically focusing on IEI. Despite the tremendous progress achieved over the last years, several obstacles remain or have become even more important due to the increasing amount of genetic data produced for each patient. This includes, first and foremost, the interpretation of variants of unknown significance (VUS) in known IEI genes and of variants in genes of unknown significance (GUS). Although genetic diagnostics have significantly contributed to the understanding and management of IEI and other rare diseases, further research, exchange between experts from different clinical disciplines, data integration and the establishment of comprehensive guidelines are crucial to tackle the remaining challenges and maximize the potential of genetic diagnostics in the field of rare diseases, such as IEI.

A Challenging Correlation between Tumor Cellularity and Somatic Variant Allele Fraction in Lung and Colorectal Cancers-Specimens of Low Tumor Percentage Should Be Analyzed with Caution

Background and aims: The percentage of tumor cells (tumor cellularity) in a cancerous tissue has been assumed to correlate with the variant allele fraction (VAF) of an identified pathogenic variant. Many laboratories use the tumor cellularity as part of a quality criteria for specimen processing and clinical reporting. However, a systematic study of such correlation has yet to be shown. We performed a relatively large-scale study to determine whether pathologist-estimated tumor cellularity is correlated with next-generation sequencing (NGS)-derived VAF. Materials and Methods: A total of 1511 non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) specimens, including formalin-fixed paraffin-embedded (FFPE) and fine needle aspirated (FNA) tissues, were analyzed by cancer hotspot NGS. For a given specimen, pathogenic variants of BRAF, EGFR, KRAS, and NRAS were identified and the determined VAFs were correlated with the corresponding tissue tumor cellularity. Results: The coefficient of determination R-squared (R2) values were calculated for each correlation. All R2 values were lower than 0.25, indicating poor correlations. Pathogenic variants were found, not uncommonly, in tumor specimens that carried 10% or lower tumor cellularity. There were no apparent differences of R2 values between the FFPE and FNA specimens. Conclusion: In both NSCLC and CRC, the lack of linear relationship between tumor cellularity and VAF was found across a wide range of tumor cell percentages. Caution should be used when using tumor cellularity to triage specimens for NGS testing. The tumor cellularity should be considered in relation to the limit of detection of the specific assay for the proper interpretation of a negative test result.

Clinical relevance of clonal hematopoiesis and its interference in cell-free DNA profiling of patients with gastric cancer

OBJECTIVES

Clonal hematopoiesis (CH) is a condition in which healthy individuals have somatic mutations in hematopoietic stem cells. It has been reported with increased risk of hematologic malignancy and cardiovascular disease in the general population, but studies of Korean populations with comorbid disease entities are scarce.

METHODS

White blood cells (WBCs) from patients with gastric cancer (GC) (n=121) were analyzed using a DNA-based targeted (531 genes) panel with customized pipeline designed to detect single nucleotide variants and small indels with low-allele-frequency of ≥0.2 %. We defined significant CH variants as having variant allele frequency (VAF) ≥2 % among variants found in WBCs. Matched cell-free DNA (cfDNA) samples were also analyzed with the same pipeline to investigate the false-positive results caused by WBC variants in cfDNA profiling.

RESULTS

Significant CH variants were detected in 29.8 % of patients and were associated with age and male sex. The number of CH variants was associated with a history of anti-cancer therapy and age. DNMT3A and TET2 were recurrently mutated. Overall survival rate of treatment-naïve patients with stage IV GC was higher in those with CH, but Cox regression showed no significant association after adjustment for age, sex, anti-cancer therapy, and smoking history. In addition, we analyzed the potential interference of WBC variants in plasma cell-free DNA testing, which has attracted interest as a complementary method for tissue biopsy. Results showed that 37.0 % (47/127) of plasma specimens harbored at least one WBC variant. VAFs of interfering WBC variants in the plasma and WBC were correlated, and WBC variants with VAF ≥4 % in WBC were frequently detected in plasma with the same VAF.

CONCLUSIONS

This study revealed the clinical impact of CH in Korean patients and suggests the potential for its interference in cfDNA tests.

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.

Clonal Somatic Mutations in Chronic Lung Diseases Are Associated with Reduced Lung Function

Rationale: Constantly exposed to the external environment and mutagens such as tobacco smoke, human lungs have one of the highest somatic mutation rates among all human organs. However, the relationship of these mutations to lung disease and function is not known. Objectives: To identify the prevalence and significance of clonal somatic mutations in chronic lung diseases. Methods: We analyzed the clonal somatic mutations from 1,251 samples of normal and diseased noncancerous lung tissue RNA sequencing with paired whole-genome sequencing from the Lung Tissue Research Consortium. We examined the associations of somatic mutations with lung function, disease status, and computationally deconvoluted cell types in two of the most common diseases represented in our dataset, chronic obstructive pulmonary disease (COPD; 29%) and idiopathic pulmonary fibrosis (IPF; 13%). Measurements and Main Results: Clonal somatic mutational burden was associated with reduced lung function in both COPD and IPF. We identified an increased prevalence of clonal somatic mutations in individuals with IPF compared with normal control subjects and individuals with COPD independent of age and smoking status. IPF clonal somatic mutations were enriched in disease-related and airway epithelial-expressed genes such as MUC5B in IPF. Patients who were MUC5B risk variant carriers had increased odds of developing somatic mutations of MUC5B that were explained by increased expression of MUC5B. Conclusions: Our identification of an increased prevalence of clonal somatic mutation in diseased lung that correlates with airway epithelial gene expression and disease severity highlights for the first time the role of somatic mutational processes in lung disease genetics.

Comprehensive benchmarking and guidelines of mosaic variant calling strategies

Rapid advances in sequencing and analysis technologies have enabled the accurate detection of diverse forms of genomic variants represented as heterozygous, homozygous and mosaic mutations. However, the best practices for mosaic variant calling remain disorganized owing to the technical and conceptual difficulties faced in evaluation. Here we present our benchmark of 11 feasible mosaic variant detection approaches based on a systematically designed whole-exome-level reference standard that mimics mosaic samples, supported by 354,258 control positive mosaic single-nucleotide variants and insertion-deletion mutations and 33,111,725 control negatives. We identified not only the best practice for mosaic variant detection but also the condition-dependent strengths and weaknesses of the current methods. Furthermore, feature-level evaluation and their combinatorial usage across multiple algorithms direct the way for immediate to prolonged improvements in mosaic variant detection. Our results will guide researchers in selecting suitable calling algorithms and suggest future strategies for developers.

Genome-wide detection of somatic mosaicism at short tandem repeats

Motivation

Somatic mosaicism, in which a mutation occurs post-zygotically, has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6bp and comprise more than 1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs (mSTRs) is lacking.

Results

We introduce prancSTR, a novel method for detecting mSTRs from individual high-throughput sequencing datasets. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mSTRs in simulated data and demonstrate its feasibility by identifying candidate mSTRs in whole genome sequencing (WGS) data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project. Our analysis identified an average of 76 and 577 non-homopolymer and homopolymer mSTRs respectively per cell line as well as multiple cell lines with outlier mSTR counts more than 6 times the population average, suggesting a subset of cell lines have particularly high STR instability rates.

Availability

prancSTR is freely available at https://github.com/gymrek-lab/trtools.

Documentation

Detailed documentation is available at https://trtools.readthedocs.io/.

Liquid biopsy for early detection of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly prevalent and lethal cancer globally. Over 90% of HCC cases arise in the context of liver cirrhosis, and the severity of the underlying liver disease or advanced tumor stage at diagnosis significantly limits treatment options. Early diagnosis is crucial, and all guidelines stress the importance of screening protocols for HCC early detection as a public health objective. As serum biomarkers are not optimal for early diagnosis, liquid biopsy has emerged as a promising tool for diagnosis, prognostication, and patients' stratification for personalized therapy in various solid tumors, including HCC. While circulating tumor cells (CTCs) are better suited for personalized therapy and prognosis, cell-free DNA (cfDNA) and extracellular vesicle-based technologies show potential for early diagnosis, HCC screening, and surveillance protocols. Evaluating the added value of liquid biopsy genetic and epigenetic biomarkers for HCC screening is a key goal in translational research. Somatic mutations commonly found in HCC can be investigated in cfDNA and plasma exosomes as genetic biomarkers. Unique methylation patterns in cfDNA or cfDNA fragmentome features have been suggested as innovative tools for early HCC detection. Likewise, extracellular vesicle cargo biomarkers such as miRNAs and long non-coding RNAs may serve as potential biomarkers for early HCC detection. This review will explore recent findings on the utility of liquid biopsy for early HCC diagnosis. Combining liquid biopsy methods with traditional serological biomarkers could improve the overall diagnostic accuracy for early HCC detection.

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

Control-independent mosaic single nucleotide variant detection with DeepMosaic

Mosaic variants (MVs) reflect mutagenic processes during embryonic development and environmental exposure, accumulate with aging and underlie diseases such as cancer and autism. The detection of noncancer MVs has been computationally challenging due to the sparse representation of nonclonally expanded MVs. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs and a convolutional neural network-based classification module for control-independent MV detection. DeepMosaic was trained on 180,000 simulated or experimentally assessed MVs, and was benchmarked on 619,740 simulated MVs and 530 independent biologically tested MVs from 16 genomes and 181 exomes. DeepMosaic achieved higher accuracy compared with existing methods on biological data, with a sensitivity of 0.78, specificity of 0.83 and positive predictive value of 0.96 on noncancer whole-genome sequencing data, as well as doubling the validation rate over previous best-practice methods on noncancer whole-exome sequencing data (0.43 versus 0.18). DeepMosaic represents an accurate MV classifier for noncancer samples that can be implemented as an alternative or complement to existing methods.

Somatic mosaicism in inborn errors of immunity: Current knowledge, challenges, and future perspectives

Inborn errors of immunity (IEI) are a diverse group of monogenic disorders of the immune system due to germline variants in genes important for the immune response. Over the past decade there has been increasing recognition that acquired somatic variants present in a subset of cells can also lead to immune disorders or 'phenocopies' of IEI. Discovery of somatic mosaicism causing IEI has largely arisen from investigation of seemingly sporadic cases of IEI with predominant symptoms of autoinflammation and/or autoimmunity in which germline disease-causing variants are not detected. Disease-causing somatic mosaicism has been identified in genes that also cause germline IEI, such as FAS, and in genes without significant corresponding germline disease, such as UBA1 and TLR8. There are challenges in detecting low-level somatic variants, and it is likely that the extent of the somatic mosaicism causing IEI is largely uncharted. Here we review the field of somatic mosaicism leading to IEI and discuss challenges and methods for somatic variant detection, including diagnostic approaches for molecular diagnoses of patients.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

Thalassemia and Nanotheragnostics: Advanced Approaches for Diagnosis and Treatment

Thalassemia is a monogenic autosomal recessive disorder caused by mutations, which lead to abnormal or reduced production of hemoglobin. Ineffective erythropoiesis, hemolysis, hepcidin suppression, and iron overload are common manifestations that vary according to genotypes and dictate, which diagnosis and therapeutic modalities, including transfusion therapy, iron chelation therapy, HbF induction, gene therapy, and editing, are performed. These conventional therapeutic methods have proven to be effective, yet have several disadvantages, specifically iron toxicity, associated with them; therefore, there are demands for advanced therapeutic methods. Nanotechnology-based applications, such as the use of nanoparticles and nanomedicines for theragnostic purposes have emerged that are simple, convenient, and cost-effective methods. The therapeutic potential of various nanoparticles has been explored by developing artificial hemoglobin, nano-based iron chelating agents, and nanocarriers for globin gene editing by CRISPR/Cas9. Au, Ag, carbon, graphene, silicon, porous nanoparticles, dendrimers, hydrogels, quantum dots, etc., have been used in electrochemical biosensors development for diagnosis of thalassemia, quantification of hemoglobin in these patients, and analysis of conventional iron chelating agents. This review summarizes the potential of nanotechnology in the development of various theragnostic approaches to determine thalassemia-causing gene mutations using various nano-based biosensors along with the employment of efficacious nano-based therapeutic procedures, in contrast to conventional therapies.

Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline

A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and copy number alterations using sequencing of multiple related clinical patient samples across diverse tissue, optimizing for sensitivity with specificity. The ith.Variant pipeline can be run on single- or multi-region whole-genome and whole-exome sequencing. For complete details on the use and execution of this protocol, please refer to Sun et al. (2017).1.

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma

BACKGROUND

Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity.

METHODS

Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC.

RESULTS

Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%.

CONCLUSIONS

Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Clonal hematopoiesis, somatic mosaicism, and age-associated disease

Somatic mosaicism, the occurrence of multiple genetically distinct cell clones within the same tissue, is an evitable consequence of human aging. The hematopoietic system is no exception to this, where studies have revealed the presence of expanded blood cell clones carrying mutations in preleukemic driver genes and/or genetic alterations in chromosomes. This phenomenon is referred to as clonal hematopoiesis and is remarkably prevalent in elderly individuals. While clonal hematopoiesis represents an early step toward a hematological malignancy, most individuals will never develop blood cancer. Somewhat unexpectedly, epidemiological studies have found that clonal hematopoiesis is associated with an increase in the risk of all-cause mortality and age-related disease, particularly in the cardiovascular system. Studies using murine models of clonal hematopoiesis have begun to shed light on this relationship, suggesting that driver mutations in mature blood cells can causally contribute to aging and disease by augmenting inflammatory processes. Here we provide an up-to-date review of clonal hematopoiesis within the context of somatic mosaicism and aging and describe recent epidemiological studies that have reported associations with age-related disease. We will also discuss the experimental studies that have provided important mechanistic insight into how driver mutations promote age-related disease and how this knowledge could be leveraged to treat individuals with clonal hematopoiesis.

Functional Assessment of Cancer-Linked Mutations in Sensitive Regions of Regulators of G Protein Signaling Predicted by Three-Dimensional Missense Tolerance Ratio Analysis

Regulators of G protein signaling (RGS) proteins modulate G protein-coupled receptor (GPCR) signaling by acting as negative regulators of G proteins. Genetic variants in RGS proteins are associated with many diseases, including cancers, although the impact of these mutations on protein function is uncertain. Here we analyze the RGS domains of 15 RGS protein family members using a novel bioinformatic tool that measures the missense tolerance ratio (MTR) using a three-dimensional (3D) structure (3DMTR). Subsequent permutation analysis can define the protein regions that are most significantly intolerant (P < 0.05) in each dataset. We further focused on RGS14, RGS10, and RGS4. RGS14 exhibited seven significantly tolerant and seven significantly intolerant residues, RGS10 had six intolerant residues, and RGS4 had eight tolerant and six intolerant residues. Intolerant and tolerant-control residues that overlap with pathogenic cancer mutations reported in the COSMIC cancer database were selected to define the functional phenotype. Using complimentary cellular and biochemical approaches, proteins were tested for effects on GPCR-Gα activation, Gα binding properties, and downstream cAMP levels. Identified intolerant residues with reported cancer-linked mutations RGS14-R173C/H and RGS4-K125Q/E126K, and tolerant RGS14-S127P and RGS10-S64T resulted in a loss-of-function phenotype in GPCR-G protein signaling activity. In downstream cAMP measurement, tolerant RGS14-D137Y and RGS10-S64T and intolerant RGS10-K89M resulted in change of function phenotypes. These findings show that 3DMTR identified intolerant residues that overlap with cancer-linked mutations cause phenotypic changes that negatively impact GPCR-G protein signaling and suggests that 3DMTR is a potentially useful bioinformatics tool for predicting functionally important protein residues. SIGNIFICANCE STATEMENT: Human genetic variant/mutation information has expanded rapidly in recent years, including cancer-linked mutations in regulator of G protein signaling (RGS) proteins. However, experimental testing of the impact of this vast catalogue of mutations on protein function is not feasible. We used the novel bioinformatics tool three-dimensional missense tolerance ratio (3DMTR) to define regions of genetic intolerance in RGS proteins and prioritize which cancer-linked mutants to test. We found that 3DMTR more accurately classifies loss-of-function mutations in RGS proteins than other databases thereby offering a valuable new research tool.

PAM-independent ultra-specific activation of CRISPR-Cas12a via sticky-end dsDNA

Although CRISPR-Cas12a [clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 12a] combining pre-amplification technology has the advantage of high sensitivity in biosensing, its generality and specificity are insufficient, which greatly restrains its application range. Here, we discovered a new targeting substrate for LbaCas12a (Lachnospiraceae bacterium Cas12a), namely double-stranded DNA (dsDNA) with a sticky-end region (PAM-SE+ dsDNA). We discovered that CRISPR-Cas12a had special enzymatic properties for this substrate DNA, including the ability to recognize and cleave it without needing a protospacer adjacent motif (PAM) sequence and a high sensitivity to single-base mismatches in that substrate. Further mechanism studies revealed that guide RNA (gRNA) formed a triple-stranded flap structure with the substrate dsDNA. We also discovered the property of low-temperature activation of CRISPR-Cas12a and, by coupling with the unique DNA hybridization kinetics at low temperature, we constructed a complete workflow for low-abundance point mutation detection in real samples, which was fast, convenient and free of single-stranded DNA (ssDNA) transformation. The detection limits were 0.005-0.01% for synthesized strands and 0.01-0.05% for plasmid genomic DNA, and the mutation abundances provided by our system for 28 clinical samples were in accordance with next-generation sequencing results. We believe that our work not only reveals novel information about the target recognition mechanism of the CRISPR-Cas12a system, but also greatly broadens its application scenarios.

Somatic variation in normal tissues: friend or foe of cancer early detection?

BACKGROUND

Seemingly normal tissues progressively become populated by mutant clones over time. Most of these clones bear mutations in well-known cancer genes but only rarely do they transform into cancer. This poses questions on what triggers cancer initiation and what implications somatic variation has for cancer early detection.

DESIGN

We analysed recent mutational screens of healthy and cancer-free diseased tissues to compare somatic drivers and the causes of somatic variation across tissues. We then reviewed the mechanisms of clonal expansion and their relationships with age and diseases other than cancer. We finally discussed the relevance of somatic variation for cancer initiation and how it can help or hinder cancer detection and prevention.

RESULTS

The extent of somatic variation is highly variable across tissues and depends on intrinsic features, such as tissue architecture and turnover, as well as the exposure to endogenous and exogenous insults. Most somatic mutations driving clonal expansion are tissue-specific and inactivate tumor suppressor genes involved in chromatin modification and cell growth signaling. Some of these genes are more frequently mutated in normal tissues than cancer, indicating a context-dependent cancer promoting or protective role. Mutant clones can persist over a long time or disappear rapidly, suggesting that their fitness depends on the dynamic equilibrium with the environment. The disruption of this equilibrium is likely responsible for their transformation into malignant clones and knowing what triggers this process is key for cancer prevention and early detection. Somatic variation should be considered in liquid biopsy, where it may contribute cancer-independent mutations, and in the identification of cancer drivers, since not all mutated genes favoring clonal expansion also drive tumorigenesis.

CONCLUSIONS

Somatic variation and the factors governing homeostasis of normal tissues should be taken into account when devising strategies for cancer prevention and early detection.

Landscape of somatic mutations in aging human heart muscle cells

Using single-cell whole-genome sequencing, we identified and characterized the landscape of somatic single-nucleotide variants (sSNVs) in single cardiomyocytes from individuals across the human lifespan. Aged cardiomyocytes were found to have a higher burden of sSNVs and show mutational signatures that suggest failed repair of oxidative DNA damage.

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.

Postzygotic mutations and where to find them - Recent advances and future implications in the field of non-neoplastic somatic mosaicism

The technological progress of massively parallel sequencing (MPS) has triggered a remarkable development in the research on postzygotic mutations. Although the overwhelming majority of studies in the field focus on oncogenesis, non-neoplastic diseases are attracting more and more attention. The aim of this review was to summarize some of the most recent findings in the field of somatic mosaicism in diseases other than neoplastic events. We discuss the abundance and role of postzygotic mutations, with a special emphasis on disorders which occur only in a mosaic form (obligatory mosaic diseases; OMDs). Based on the list of OMDs compiled from the published literature and three databases (OMIM, Orphanet and MosaicBase), we demonstrate the prevalence of cancer-related genes across OMDs and suggest other sources to further explore OMDs and OMD-related genes. Additionally, we comment on some practical aspects related to mosaic diseases, such as approaches to tissue sampling, the MPS coverage required to detect variants at a very low frequency, as well as on bioinformatic and molecular tools dedicated to detect somatic mutations in MPS data.

Asymmetric Contribution of Blastomere Lineages of First Division of the Zygote to Entire Human Body Using Post-Zygotic Variants

BACKGROUND

In humans, after fertilization, the zygote divides into two 2n diploid daughter blastomeres. During this division, DNA is replicated, and the remaining mutually exclusive genetic mutations in the genome of each cell are called post-zygotic variants. Using these somatic mutations, developmental lineages can be reconstructed. How these two blastomeres are contributing to the entire body is not yet identified. This study aims to evaluate the cellular contribution of two blastomeres of 2-cell embryos to the entire body in humans using post-zygotic variants based on whole genome sequencing.

METHODS

Tissues from different anatomical areas were obtained from five donated cadavers for use in single-cell clonal expansion and bulk target sequencing. After conducting whole genome sequencing, computational analysis was applied to find the early embryonic mutations of each clone. We developed our in-house bioinformatics pipeline, and filtered variants using strict criteria, composed of mapping quality, base quality scores, depth, soft-clipped reads, and manual inspection, resulting in the construction of embryological phylogenetic cellular trees.

RESULTS

Using our in-house pipeline for variant filtering, we could extract accurate true positive variants, and construct the embryological phylogenetic trees for each cadaver. We found that two daughter blastomeres, L1 and L2 (lineage 1 and 2, respectively), derived from the zygote, distribute unequally to the whole body at the clonal level. From bulk target sequencing data, we validated asymmetric contribution by means of the variant allele frequency of L1 and L2. The asymmetric contribution of L1 and L2 varied from person to person.

CONCLUSION

We confirmed that there is asymmetric contribution of two daughter blastomeres from the first division of the zygote across the whole human body.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

Establishment of reference standards for multifaceted mosaic variant analysis

Detection of somatic mosaicism in non-proliferative cells is a new challenge in genome research, however, the accuracy of current detection strategies remains uncertain due to the lack of a ground truth. Herein, we sought to present a set of ultra-deep sequenced WES data based on reference standards generated by cell line mixtures, providing a total of 386,613 mosaic single-nucleotide variants (SNVs) and insertion-deletion mutations (INDELs) with variant allele frequencies (VAFs) ranging from 0.5% to 56%, as well as 35,113,417 non-variant and 19,936 germline variant sites as a negative control. The whole reference standard set mimics the cumulative aspect of mosaic variant acquisition such as in the early developmental stage owing to the progressive mixing of cell lines with established genotypes, ultimately unveiling 741 possible inter-sample relationships with respect to variant sharing and asymmetry in VAFs. We expect that our reference data will be essential for optimizing the current use of mosaic variant detection strategies and for developing algorithms to enable future improvements.

Measurement(s)	genotype
Technology Type(s)	DNA sequencing
Factor Type(s)	genotyping
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	cell line

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16970041

Comprehensive Approach to Distinguish Patients with Solid Tumors from Healthy Controls by Combining Androgen Receptor Mutation p.H875Y with Cell-Free DNA Methylation and Circulating miRNAs

Liquid biopsy-based tests emerge progressively as an important tool for cancer diagnostics and management. Currently, researchers focus on a single biomarker type and one tumor entity. This study aimed to create a multi-analyte liquid biopsy test for the simultaneous detection of several solid cancers. For this purpose, we analyzed cell-free DNA (cfDNA) mutations and methylation, as well as circulating miRNAs (miRNAs) in plasma samples from 97 patients with cancer (20 bladder, 9 brain, 30 breast, 28 colorectal, 29 lung, 19 ovarian, 12 pancreas, 27 prostate, 23 stomach) and 15 healthy controls via real-time qPCR. Androgen receptor p.H875Y mutation (AR) was detected for the first time in bladder, lung, stomach, ovarian, brain, and pancreas cancer, all together in 51.3% of all cancer samples and in none of the healthy controls. A discriminant function model, comprising cfDNA mutations (COSM10758, COSM18561), cfDNA methylation markers (MLH1, MDR1, GATA5, SFN) and miRNAs (miR-17-5p, miR-20a-5p, miR-21-5p, miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-92a-3p, miR-101-3p, miR-133a-3p, miR-148b-3p, miR-155-5p, miR-195-5p) could further classify healthy and tumor samples with 95.4% accuracy, 97.9% sensitivity, 80% specificity. This multi-analyte liquid biopsy-based test may help improve the simultaneous detection of several cancer types and underlines the importance of combining genetic and epigenetic biomarkers.

Chimeric chromosome landscapes of human somatic cell cultures show dependence on stress and regulation of genomic repeats by CGGBP1

Genomes of somatic cells in culture are prone to spontaneous mutations due to errors in replication and DNA repair. Some of these errors, such as chromosomal fusions, are not rectifiable and subject to selection or elimination in growing cultures. Somatic cell cultures are thus expected to generate background levels of potentially stable chromosomal chimeras. A description of the landscape of such spontaneously generated chromosomal chimeras in cultured cells will help understand the factors affecting somatic mosaicism. Here we show that short homology-associated non-homologous chromosomal chimeras occur in normal human fibroblasts and HEK293T cells at genomic repeats. The occurrence of chromosomal chimeras is enhanced by heat stress and depletion of a repeat regulatory protein CGGBP1. We also present evidence of homologous chromosomal chimeras between allelic copies in repeat-rich DNA obtained by methylcytosine immunoprecipitation. The formation of homologous chromosomal chimeras at Alu and L1 repeats increases upon depletion of CGGBP1. Our data are derived from de novo sequencing from three different cell lines under different experimental conditions and our chromosomal chimera detection pipeline is applicable to long as well as short read sequencing platforms. These findings present significant information about the generation, sensitivity and regulation of somatic mosaicism in human cell cultures.

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.

Somatic mosaics in hereditary tumor predisposition syndromes

Historically, it is estimated that 5-10% of cancer patients carry a causative genetic variant for a tumor predisposition syndrome. These conditions have high clinical relevance as they are actionable regarding risk-specific surveillance, predictive genetic testing, reproductive options, and - in some cases - risk reducing surgery or targeted therapy. Every individual is born with on average 0.5-1 exonic mosaic variants prevalent in single or multiple tissues. Depending on the tissues affected, mosaic conditions can abrogate the clinical phenotype of a tumor predisposition syndrome and can even go unrecognized, because it can be impossible or difficult to detect them with routine genetic testing in blood/leucocytes. On the other hand, it is estimated that at least 4% of presumed de novo variants are the result of low-level mosaicism (variant allele frequency <10%) in a parent, while around 7% are true mosaic variants with a higher variant allele frequency, which can sometimes be confused for heterozygous variants. Clonal hematopoiesis however can simulate a mosaic tumor predisposition in genetic diagnostics and has to be taken into account, especially for TP53 variants. Depending on the technique, variant allele frequencies of 2-3% can be detected for single nucleotide variants by next generation sequencing, copy number variants with variant allele frequencies of 5-30% can be detected by array-based technologies or MLPA. Mosaic tumor predisposition syndromes are more common than previously thought and may often remain undiagnosed. The clinical suspicion and diagnostic procedure for several cases with mosaic tumor predisposition syndromes are presented.

Dissecting single-cell genomes through the clonal organoid technique

The revolution in genome sequencing technologies has enabled the comprehensive detection of genomic variations in human cells, including inherited germline polymorphisms, de novo mutations, and postzygotic mutations. When these technologies are combined with techniques for isolating and expanding single-cell DNA, the landscape of somatic mosaicism in an individual body can be systematically revealed at a single-cell resolution. Here, we summarize three strategies (whole-genome amplification, microdissection of clonal patches in the tissue, and in vitro clonal expansion of single cells) that are currently applied for single-cell mutational analyses. Among these approaches, in vitro clonal expansion, particularly via adult stem cell-derived organoid culture technologies, yields the most sensitive and precise catalog of somatic mutations in single cells. Moreover, because it produces living mutant cells, downstream validation experiments and multiomics profiling are possible. Through the synergistic combination of organoid culture and genome sequencing, researchers can track genome changes at a single-cell resolution, which will lead to new discoveries that were previously impossible.

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers—GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles–SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

Novel next-generation sequencing-based methodologies to characterize the mutational consequences of (prenatal) chemotherapy exposure in noncancerous tissue

PURPOSE OF REVIEW

Although chemotherapeutics are considered as genotoxins for decades, their exact mutagenic impact on the genome of cancerous and normal cells of cancer patients was unknown for a long time. However, this knowledge is necessary to understand the long-term side effects of chemotherapy. A particular condition represents pregnant cancer patients being treated with chemotherapy. Since certain chemotherapeutics can cross the placenta, concerns exist about possible mutational effects on the fetus' genome with potential long-term health consequences.

RECENT FINDINGS

Recent advances of next-generation sequencing (NGS) techniques have opened possibilities to explore the exact mutational footprint of chemotherapies in healthy tissue from treated cancer patients. However, the ultra-low frequency of chemotherapy-induced mutations, introduction of technical artefacts, and inaccessibility of normal tissue has posed important limitations. This review discusses five state-of-the-art approaches that were recently designed to overcome these drawbacks.

SUMMARY

Results of the latest investigations give valuable insights into the genome-wide genotoxicity profile of frequently applied chemotherapies, with most of these drugs being associated with a signature of random base substitutions and small indels. Though these findings still might be limited to extrapolate to healthy tissue, they pave the way for studies on the origin of long-term chemotherapy-related adverse health effects.

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.

Tumor Classification Should Be Based on Biology and Not Consensus: Re-Defining Tumors Based on Biology May Accelerate Progress, An Experience of Gastric Cancer

Simple Summary

Rational treatment of diseases including cancers depends on knowledge of their cause as well as their development. The present review is based upon more than 40 years’ work in clinical gastroenterology, gastric physiology, and pathology. The central role of hormones as well as local endocrine cells in cancer development has become apparent. Moreover, the classification of tumors should focus not only on the organ of origin but also on the cell of origin. All cells with the ability to divide may give rise to tumors. Based upon knowledge of the growth regulation of the cell of origin, prophylaxis and treatment may be tailored. Presently, there is hope for individual treatment of cancer patients based upon genetic analyses of tumors. However, with correct identification of the cell of origin, this may not be necessary.

Abstract

Malignant tumors are a consequence of genetic changes mainly occurring during cell division, sometimes with a congenital component. Therefore, accelerated cell divisions will necessarily predispose individuals, whether due to conditions of chronic cell destruction or hormonal overstimulation. It has been postulated that two genetic hits are necessary for the development of malignancy (Knudson). The correct view is probably that the number of genetic changes needed depends on the role the mutated genes have in proliferation and growth control. Hormones should accordingly be regarded as complete carcinogens. In this review based upon experience of gastric cancer where gastrin is central in the pathogenesis, it is argued that oxyntic atrophy—and not metaplasia as postulated by Correa—is the central precancer change in gastric mucosa. Moreover, the target cell of gastrin, the enterochromaffin-like (ECL) cell, is central in gastric carcinogenesis and most probably the cell of origin of gastric carcinomas of the diffuse type according to Lauren (a classification probable in accordance with biology). The distinction between adenocarcinomas and neuroendocrine carcinomas based upon a certain percentage of cancer cells with neuroendocrine differentiation is questioned. To make progress in the treatment of cancer, a correct classification system and knowledge of the pathogenesis are necessary.

A family with partially penetrant multicentric carpotarsal osteolysis due to gonadal mosaicism: First reported case

Multicentric carpotarsal osteolysis (MCTO) is an autosomal dominant condition characterized by carpal-tarsal abnormalities; over half of affected individuals also develop renal disease. MCTO is caused by mutations of MAFB; however, there is no clear phenotype-genotype correlation. We describe the first reported family of variable MCTO phenotype due to mosaicism: the proband had classical skeletal features and renal involvement due to focal segmental glomerulosclerosis (FSGS), and the father had profound renal impairment due to FSGS, necessitating kidney transplantation. Mosaicism was first suspected in this family due to unequal allele ratios in the sequencing chromatograph of the initial blood sample of proband's father and confirmed by sequencing DNA extracted from the father's hair, collected from different bodily parts. This case highlights the need for a high index of clinical suspicion to detect low-level parental mosaicism, as well as a potential role for MAFB mutation screening in individuals with isolated FSGS.

Next Generation Sequencing for Detecting Somatic FAS Mutations in Patients With Autoimmune Lymphoproliferative Syndrome

Autoimmune lymphoproliferative syndrome (ALPS) is a primary immune regulatory disorder clinically defined by chronic and benign lymphoproliferation, autoimmunity and an increased risk of lymphoma due to a genetic defect in the FAS-FASL apoptotic pathway. Genetic defects associated with ALPS are germinal and somatic mutations in FAS gene, in addition to germinal mutations in FASLG, FADD, CASP8 and CASP10 genes. The accumulation of CD3+TCRαβ+CD4-CD8- double negative T-cells (DNT) is a hallmark of the disease and 20-25% of ALPS patients show heterozygous somatic mutations restricted to DNT in the FAS gene (ALPS-sFAS patients). Nowadays, somatic mutations in the FAS gene are detected through Sanger sequencing in isolated DNT. In this study, we report an ALPS-sFAS patient fulfilling clinical and laboratory ALPS criteria, who was diagnosed through NGS with a targeted gene panel using DNA from whole blood. Data analysis was carried out with Torrent Suite Software and variant detection was performed by both germinal and somatic variant caller plugin. The somatic variant caller correctly detected other six ALPS-sFAS patients previously diagnosed in the authors’ laboratories. In summary, this approach allows the detection of both germline and somatic mutations related to ALPS by NGS, avoiding the isolation of DNT as the first step. The reads of the somatic variants could be detected even in patients with DNT in the cut off limit. Thus, custom-designed NGS panel testing may be a faster and more reliable method for the diagnosis of new ALPS patients, including those with somatic FAS mutations (ALPS-sFAS).

Low-level variant calling for non-matched samples using a position-based and nucleotide-specific approach

Background

The widespread use of next-generation sequencing has identified an important role for somatic mosaicism in many diseases. However, detecting low-level mosaic variants from next-generation sequencing data remains challenging.

Results

Here, we present a method for Position-Based Variant Identification (PBVI) that uses empirically-derived distributions of alternate nucleotides from a control dataset. We modeled this approach on 11 segmental overgrowth genes. We show that this method improves detection of single nucleotide mosaic variants of 0.01–0.05 variant allele fraction compared to other low-level variant callers. At depths of 600 × and 1200 ×, we observed > 85% and > 95% sensitivity, respectively. In a cohort of 26 individuals with somatic overgrowth disorders PBVI showed improved signal to noise, identifying pathogenic variants in 17 individuals.

Conclusion

PBVI can facilitate identification of low-level mosaic variants thus increasing the utility of next-generation sequencing data for research and diagnostic purposes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04090-y.

CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples

Our capacity to study individual cells has enabled a new level of resolution for understanding complex biological systems such as multicellular organisms or microbial communities. Not surprisingly, several methods have been developed in recent years with a formidable potential to investigate the somatic evolution of single cells in both healthy and pathological tissues. However, single-cell sequencing data can be quite noisy due to different technical biases, so inferences resulting from these new methods need to be carefully contrasted. Here, I introduce CellCoal, a software tool for the coalescent simulation of single-cell sequencing genotypes. CellCoal simulates the history of single-cell samples obtained from somatic cell populations with different demographic histories and produces single-nucleotide variants under a variety of mutation models, sequencing read counts, and genotype likelihoods, considering allelic imbalance, allelic dropout, amplification, and sequencing errors, typical of this type of data. CellCoal is a flexible tool that can be used to understand the implications of different somatic evolutionary processes at the single-cell level, and to benchmark dedicated bioinformatic tools for the analysis of single-cell sequencing data. CellCoal is available at https://github.com/dapogon/cellcoal.

Characterization of early postzygotic somatic mutations through multi-organ analysis

Mosaicisms caused by postzygotic mutational events are of increasing interest because of their potential association with various human diseases. Postzygotic somatic mutations have not been well characterized however in terms of their developmental lineage in humans. We conducted whole-genome sequencing (WGS) and targeted deep sequencing in 15 organs across three developmental lineages from a single male fetus with polycystic kidney disease (PKD) of 21 weeks gestational age. This fetus had no detectable neurological abnormalities at autopsy but germline mutations in the PKHD1 gene were identified that may have been associated with the PKD. Eight early embryonic mosaic variants with no alteration of protein function were detected. These variants were thought to have occurred at the two or four cell stages after fertilization with a mutational pattern involving frequent C>T and T>C transitions. In our current analyses, no tendency toward organ-specific mutation occurrences was found as the eight variants were detected in all 15 organs. However different allele fractions of these variants were found in different organs, suggesting a tissue-specific asymmetric growth of cells that reflected the developmental germ layer of each organ. This indicated that somatic mutation occurrences, even in early embryogenesis, can affect specific organ development or disease. Our current analyses demonstrate that multi-organ analysis is helpful for understanding genomic mosaicism. Our results also provide insights into the biological role of mosaicism in embryonic development and disease.

A simple method to estimate the in-house limit of detection for genetic mutations with low allele frequencies in whole-exome sequencing analysis by next-generation sequencing

BACKGROUND

Next-generation sequencing (NGS) has profoundly changed the approach to genetic/genomic research. Particularly, the clinical utility of NGS in detecting mutations associated with disease risk has contributed to the development of effective therapeutic strategies. Recently, comprehensive analysis of somatic genetic mutations by NGS has also been used as a new approach for controlling the quality of cell substrates for manufacturing biopharmaceuticals. However, the quality evaluation of cell substrates by NGS largely depends on the limit of detection (LOD) for rare somatic mutations. The purpose of this study was to develop a simple method for evaluating the ability of whole-exome sequencing (WES) by NGS to detect mutations with low allele frequency. To estimate the LOD of WES for low-frequency somatic mutations, we repeatedly and independently performed WES of a reference genomic DNA using the same NGS platform and assay design. LOD was defined as the allele frequency with a relative standard deviation (RSD) value of 30% and was estimated by a moving average curve of the relation between RSD and allele frequency.

RESULTS

Allele frequencies of 20 mutations in the reference material that had been pre-validated by droplet digital PCR (ddPCR) were obtained from 5, 15, 30, or 40 G base pair (Gbp) sequencing data per run. There was a significant association between the allele frequencies measured by WES and those pre-validated by ddPCR, whose p-value decreased as the sequencing data size increased. By this method, the LOD of allele frequency in WES with the sequencing data of 15 Gbp or more was estimated to be between 5 and 10%.

CONCLUSIONS

For properly interpreting the WES data of somatic genetic mutations, it is necessary to have a cutoff threshold of low allele frequencies. The in-house LOD estimated by the simple method shown in this study provides a rationale for setting the cutoff.