Age-related somatic mutation burden in human tissues

Abstract

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.

Methods and applications for single-cell and spatial multi-omics

“…Beyond the field of oncology, these multi-omics methods are important for understanding the pathogenesis of other disorders in which somatic genetic variation plays a putative role, including in neurological disorders such as Alzheimer disease, Parkinson disease and others 23 – 25 . With the recent discovery that normal tissues are also subjected to an extraordinary amount of mutation, technologies enabling the analysis of the genome and transcriptome of the same single cells will be important to study the role or impact of acquired mutations on phenotypic and functional cellular states, and how these in turn impact development 26 , cellular competition between normal and genetically aberrant cells 27 , tissue homeostasis, normal phenotypic variation and ageing 28 . The power of multi-omics methods in this respect is illustrated by the detection of different transcriptional responses to acquired DNA copy number aberrations 6 , 7 , 14 , 18 and other forms of mutations 9 .…”

Unraveling Heterogeneity in the Aging Hematopoietic Stem Cell Compartment: An Insight From Single-cell Approaches

“…113 Contributing further to MPN biology by using scRNA-Seq and genotyping of JAK2V617F mutation status showed increases in the expression of interferon-response genes. 99,114 In human cells, genotyping of the mitochondrial genome at the single-cell level has been recently combined with scATAC-Seq to study cell population dynamics and clonal properties in cancer of the hematopoietic system, showing that it is possible to infer subclonal population structures using natural genetic mitochondrial DNA barcodes. 115 The simultaneous single-cell profiling of gene expression, cell surface protein markers, and somatic mutation status is now possible and has been used to investigate the impact of splicing aberrations in human age-related clonal hematopoiesis by combing Genotyping of Transcriptomes (GoT), utilizing long-read single-cell transcriptome profiling in addition to proteo-genomics using CITE-Seq.…”

“…113 Contributing further to MPN biology by using scRNA-Seq and genotyping of JAK2V617F mutation status showed increases in the expression of interferon-response genes. 99,114…”

“…An alternative approach uses a combination of genotyping of targeted loci with single‐cell ChA (GoT‐ChA) and was able to show both cell‐intrinsic and cell state‐specific shifts within mutant human hematopoietic HSPCs in the context of JAK2V617F ‐mutated MPN 113 . Contributing further to MPN biology by using scRNA‐Seq and genotyping of JAK2V617F mutation status showed increases in the expression of interferon‐response genes 99,114 …”

“…3,93 Single-cell DNA sequencing (scDNA-Seq) encompasses a number of techniques that have been used to detect various genomic alterations such as single nucleotide polymorphisms, insertions, and deletions. 99 Many scDNA-Seq techniques are error prone due to technical biases arising from uneven sequence coverage, allelic dropout, and the introduction of errors during amplification steps in sequence library construction. 100 Despite the error-prone nature of scDNA-Seq data, genotyping studies targeting the somatic mutations of single cells in human clonal hematopoiesis and acute myeloid leukemia have revealed the dominance of a small number of clones that frequently contain co-occurring mutations in epigenetic regulators, thereby promoting clonal expansion.…”