Direct, genome-wide assessment of DNA mutations in single cells

Gundry, Michael C.; Li, Wenge; Maqbool, Shahina; Vijg, Jan

doi:10.1093/nar/gkr949

Cited by 70 publications

(78 citation statements)

References 38 publications

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“…a The A]G mutation of interest (red check mark in one of the cells in the whole tissue) cannot be distinguished from the sequencing errors. b When sequencing the genome of the single cell containing the mutation (red check mark in the single cell) after whole genome amplification, the A]G mutation can now be distinguished from the sequencing errors because it shows up in approximately 50% of the reads (box), corresponding to one allele [42].…”

Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Measuring Genome Instability in Aging – A Mini-Review

Vijg²

2011

Gerontology

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Background: There is mounting evidence for an age-dependent accumulation of somatic mutations as a result of the inherent imperfection of DNA replication and repair. A possible age-related decline in genome maintenance systems may exacerbate this age-related loss of genome integrity. A review of the current methods of mutation detection is timely in view of the lack of insight as to the magnitude of somatic mutation accumulation, the types of mutations that accumulate, and their functional consequences. Objective: In this paper we review the current methods for measuring genome instability in organisms during aging or in relation to life span. Methods: The review is based on established and novel concepts from the existing literature, with some examples from our own laboratory. Results: Studies using cytogenetic assays and endogenous or transgenic mutation reporter assays provide strong evidence for age-related increases of different types of mutations in animals and humans during aging. This increase in DNA mutations is tissue-specific and also differs between species. Conclusion: Today, our knowledge of somatic mutation profiles in aging is mainly derived from cytogenetics and the use of endogenous and transgenic mutation reporter assays. The emergence of new approaches, most notably massively parallel sequencing, will give us deeper insight into the nature of spontaneous genome instability and its possible causal relationship to aging and age-related disease.

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Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Measuring Genome Instability in Aging – A Mini-Review

Vijg²

2011

Gerontology

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“…Biases lead to uneven coverage and consequent difficulties for identifying somatic alterations, including SNVs, CNAs and structural aberrations. Sensitivity is most affected by allele dropout, owing to the preferential amplification of one of two alleles, with rates of 8 to 40% 16,18 reported. Large CNAs can still be examined with low genome coverage (e.g., 5–6%) by computing read counts in variable-sized bins 19 , whereas unequal coverage renders analysis of smaller copy number and structural variants extremely difficult.…”

Section: Sequencing Strategiesmentioning

confidence: 99%

Expanding the computational toolbox for mining cancer genomes

et al. 2014

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High-throughput DNA sequencing has revolutionized cancer genomics with numerous discoveries relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations including single nucleotide variants (SNVs), insertions and deletions (indels), structural aberrations, and gene fusions. Additional computational techniques have proved useful to define those mutations, genes, and molecular networks that drive diverse cancer phenotypes as well as determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic, epigenomic alterations and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.

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“…Although genome analyses at the single cell level can resolve ambiguities associated with data generated from average population, such analyses are error prone due to WGA artifacts and are also limited in the types of identifiable DNA mutations [98,99]. Researchers have been able to develop methods for paired-end sequence analysis of single cell WGA products to detect multiple classes of DNA mutation, discriminate the CNVs from allelic WGA artifacts and specify the break points and architecture of structural variants [100].…”

Section: Challenges In Single Cell Genomic Studiesmentioning

confidence: 99%

The Promise of Single Cell Omics for Onco-therapy

Azizi¹,

Clouthier

Wicha³

2014

J Mol Genet Med

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Despite extensive research effort and considerable progress, the "war on cancer" that president Nixon declared in 1971 has yet to be optimally integrated into cancer therapeutics and as such cancer remains a major medical challenge for oncologists. The dynamic and complex biology of tumor cells undergoing clonal evolution generates cells with diverse degrees of drug resistance and metastatic potential. This highlights the need to be able to access this clonal density in order to develop effective therapeutics. With this prospective, early phase single cell studies are vital for thoroughly interrogating tumor heterogeneity to uncover more about cancer cell biology and to explore new therapeutic targets leading to more successful treatments. Current evidence supports the notion that clonogenic cells within the tumor mass may potentially give rise to a population of cells with unique genomic, transcriptomic and proteomic features distinct from the rest of the tumor mass. This observation can explain drug resistance after an initial period of primary tumor response. Therefore, completely abrogating or at a minimum achieving long-term, durable control over cancer requires researchers and oncologists to employ a personalized medicine approach that includes both tumor and patient-associated variables to modify current therapeutic regimens. In this review we discuss the importance of omics and in particular single cell genomics which are increasingly promising given recently developed technology advancements to facilitate exploration of cellular heterogeneity and tumor complexity. Keywords: Cancer genomics; Single cell; Tumor heterogeneity; Oncology therapy The Combinatorial Nature of CancerCancer is a catch all term for a collection of many related, but discrete diseases that share some degree of commonality, but can no longer be considered a single disease [1]. Although tumors may initiate following malignant transformation of even a single normal cell, more probably continuous genetic mutations and gene expression alterations during tumor progression lead to a metastatic phenotype composed of multiple subsets of tumor cells with distinct characteristics. In fact, each of the genetic and epigenetic events that happen to the tumor cells after tumor initiation result in a disease that collectively is termed cancer. Yet each discrete cancer shares certain characteristics with other malignancies. In this context, malignancy of tumor cells increase as a result of the cumulative formation of a series of tumor clones. Multi-step Cancer DevelopmentThe six elements of the model of multi-step cancer development [2] including uncontrolled proliferation, growth suppressor inactivation, cell death resistance, replicative immortality, angiogenesis induction and acquisition of an invasive and metastatic phenotype should be considered when defining a novel therapeutic regimen to eradicate primary and metastatic disease. Furthermore, these elements are important considerations for successful cancer therapy in the context propo...

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Direct, genome-wide assessment of DNA mutations in single cells

Cited by 70 publications

References 38 publications

Measuring Genome Instability in Aging – A Mini-Review

Measuring Genome Instability in Aging – A Mini-Review

Expanding the computational toolbox for mining cancer genomes

The Promise of Single Cell Omics for Onco-therapy

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