Analyzing somatic mutations by single-cell whole-genome sequencing

Zhang, Lei; Lee, Moonsook; Maslov, Alexander Y.; Montagna, Cristina; Vijg, Jan; Dong, Xiao

doi:10.1038/s41596-023-00914-8

Cited by 5 publications

(6 citation statements)

References 66 publications

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“…1A; Methods). Of note, the Single-Cell Multiple Displacement Amplification (SCMDA) and variant calling procedure (SCcaller) have been designed to avoid artificial mutations, previously the major problem in somatic mutation analysis (Dong et al, 2017;Zhang et al, 2023). For each cell strain, we also performed whole-genome sequencing of tail DNA from the same mice to identify germline polymorphisms, which were filtered out in calling de novo somatic mutations from the single cells.…”

Section: Resultsmentioning

confidence: 99%

“…The aligned reads were then INDEL-realigned and base-pair score quality recalibrated using GATK (McKenna et al, 2010). SNVs and INDELs observed in a cell but not presented in the corresponding bulk DNA of the tail were called by comparing the aligned sequences of the cell to the bulk using SCcaller (version 2.0) (Zhang et al ., 2023): (i) from genomic regions covered with a minimum depth of 20x in both the cell and the bulk; (ii) with default parameters for SNVs; and (iii) requiring a variant calling quality ≥ 30 for INDELs. Mutation burden per cell were estimated based on the number of observed mutations adjusting coverage of the genome and variant calling sensitivity.…”

Section: Methodsmentioning

confidence: 99%

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Negative Selection Allows DNA Mismatch Repair-Deficient Mouse FibroblastsIn Vitroto Tolerate High Levels of Somatic Mutations

Zhang,

Lee,

Hao

et al. 2024

Preprint

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse FibroblastsIn Vitroto Tolerate High Levels of Somatic Mutations

Zhang,

Lee,

Hao

et al. 2024

Preprint

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“…Since somatic DNA mutations are random, they cannot be distinguished from sequencing artifacts after direct whole genome sequencing. Hence, we used our established and highly accurate singlecell whole genome sequencing assay [20,21] to analyze mutation burden in 21 single-cells from control and ENU-treated groups collected in 3 independent batches at cycles 3, 6, and 9 (Figure 1A, Table S3). Mutation frequencies were assessed at the 7-day time point after each treatment, as DNA damage responses should be abated by that time and all mutations fixed (Figures S1B-D).…”

Section: Repeated Mutagen Treatment Results In Extremely High Mutatio...mentioning

confidence: 99%

Negative selection allows human primary fibroblasts to tolerate high somatic mutation loads induced by N-ethyl-N-nitrosourea

Heid,

Cutler,

Sun

et al. 2024

Preprint

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High-throughput sequencing at the single-cell and single-molecule level has shown that mutation rate is much higher in somatic cells than in the germline, with thousands of mutations accumulating with age in most human tissues. While there is now ample evidence that some of these mutations can clonally amplify and lead to disease, most notably cancer, the total burden of mutations a cell can tolerate without functional decline remains unknown. Here we addressed this question by exposing human primary fibroblasts multiple times to low doses of N-ethyl-N-nitrosourea (ENU) and quantitatively analyzing somatic mutation burden using single-cell whole genome sequencing. The results indicate that individual cells can sustain ~60,000 single-nucleotide variants (SNVs) with only a slight adverse effect on growth rate. We found evidence for selection against potentially deleterious variants in gene coding regions as well as depletion of mutations in sequences associated with genetic pathways expressed in these human fibroblasts, most notably those relevant for maintaining basic cellular function and growth. However, no evidence of negative selection was found for variants in non-coding regions. We conclude that actively proliferating fibroblasts can tolerate very high levels of somatic mutations without major adverse effects on growth rate via negative selection against damaging coding mutations. Since most tissues in adult organisms have very limited capacity to select against mutations based on a growth disadvantage, these results suggest that a causal effect of somatic mutations in aging and disease cannot be ruled out.

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“…Single-cell genomics is the study of cellular uniqueness and utilizes omics techniques such as single-cell RNA sequencing (scRNA-seq) and single-cell DNA sequencing (scDNA-seq), which allow for the analysis of genetic variants and gene expression patterns at the single-cell level [ 120 ]. Spatial transcriptomics features other techniques, including in situ hybridization, digital optical barcoding, conventional immunofluorescence methods, and next-generation sequencing [ 121 ]. Single-cell genomics possesses the potential to expand the current knowledge of disease pathogenesis, opening the door for improved personalized medicine and targeted therapeutic interventions [ 120 , 121 ].…”

Section: Fourth-generation Technologies and Future Directionsmentioning

confidence: 99%

“…Spatial transcriptomics features other techniques, including in situ hybridization, digital optical barcoding, conventional immunofluorescence methods, and next-generation sequencing [ 121 ]. Single-cell genomics possesses the potential to expand the current knowledge of disease pathogenesis, opening the door for improved personalized medicine and targeted therapeutic interventions [ 120 , 121 ]. Similarly, spatially resolved transcriptomics has the potential to supply a thorough understanding of the molecular architecture of tissues, providing novel insights into organ growth, function, and disease mechanisms [ 122 ].…”

Section: Fourth-generation Technologies and Future Directionsmentioning

confidence: 99%

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

Brlek,

Bulić,

Bračić

et al. 2024

Cells

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The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype–phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

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Analyzing somatic mutations by single-cell whole-genome sequencing

Cited by 5 publications

References 66 publications

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse FibroblastsIn Vitroto Tolerate High Levels of Somatic Mutations

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse FibroblastsIn Vitroto Tolerate High Levels of Somatic Mutations

Negative selection allows human primary fibroblasts to tolerate high somatic mutation loads induced by N-ethyl-N-nitrosourea

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

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