Quantitative Analysis of the Rates for Repeat-Mediated Genome Instability in a Yeast Experimental System
Open accessAbstract
Instability of repetitive DNA sequences causes numerous hereditary disorders in humans, the majority of which are associated with trinucleotide repeat expansions. Here, we describe a unique system to study instability of triplet repeats in a yeast experimental setting. Using fluctuation assay and the novel program FluCalc we are able to accurately estimate the rates of large-scale expansions, as well as repeat-mediated mutagenesis and gross chromosomal rearrangements for different repeat sequences.
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Similar results were obtained in the Barna analysis (phenotypic lag of 0.6-1).
“Similar results were obtained in the Barna analysis (phenotypic lag of 0.6-1) [49].”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [49]
The Introduction describes a yeast fluctuation assay, and the Notes discuss variation in measured expansion rates, but neither reports a Barna analysis or a phenotypic lag of 0.6–1. Searches for “Barna,” “phenotypic lag,” and “0.6–1” found no passage addressing the claim; page numbers were unavailable in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe 3.5-fold difference between glucose and maltose mutation rate estimates has been ascribed to phenotypic lag, estimated between 1.58 and 2 generations.
“The 3.5-fold difference has been ascribed to the existence of phenotypic lag, which was estimated to be anywhere between 1.58 and 2 generations.”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [49]
The Introduction discusses mutation-rate estimation, and the Notes discuss factors that can skew estimates, but neither addresses a glucose–maltose comparison or phenotypic lag. Searches for those terms and for the claimed 3.5-fold difference and 1.58–2-generation estimate found no supporting passage in our copy; page numbers were unavailable. (LLM, conf=0.74)
Experimental — accuracy not yet measuredBarna performed two experiments with E. coli cells growing in defined medium containing either glucose or maltose as a carbon source.
“Barna also performed two experiments with E. coli cells growing in defined medium containing either glucose or maltose as a carbon source.”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [49]
The Methods (§3.1; page unavailable) describe growing yeast on YPD plates, and the Materials (§2.2; page unavailable) list yeast media. Searches for Barna and for E. coli grown with glucose or maltose found no passage about the claimed experiments. The copy therefore does not verify what Barna did. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe change in carbon source affects the population doubling time from ~23 to ~48 min.
“This change affects the population doubling time (from ~23 to ~48 min, respectively)”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [49]
The Materials section (2.2) lists media containing dextrose, and the Notes (section 4) allow for alternate growth conditions and slow-growing strains. Neither passage reports that a change in carbon source shifts population doubling time from approximately 23 to 48 minutes; searches for those times and for doubling time found no such result in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn the Newcombe experiment, the extent of phenotypic delay has been estimated at 3-4 generations, in agreement with Armitage, and the adjusted mutation rate between 1.34×10^-8 and 2.72×10^-8.
“The extent of phenotypic delay has been estimated at 3-4 generations, in agreement with analysis by Armitage [10], and the adjusted mutation rate between 1.34×10 -8 and 2.72×10 -8 .”
From Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur) (2023) · cites this paper as [49]
The Introduction discusses fluctuation tests generally, and the Notes describe mutation-rate corrections for a yeast repeat-expansion assay. Neither section addresses Newcombe’s experiment, a 3–4-generation phenotypic delay, Armitage’s analysis, or the stated adjusted rate; searches for those names and numbers found no matching passage in our copy. (LLM, conf=0.77)
Experimental — accuracy not yet measured
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Cites
Hall, B. M., Ma, C.-X., Liang, P., & Singh, K. K. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp253 · Cited by 375 · see citing works
Sarkar, S., Ma, W. T., & Sandri, G. V. H. (1992) · Genetica · doi:10.1007/bf00120324 · Cited by 181 · see citing works
Analysis of Gross‐Chromosomal Rearrangements in Saccharomyces cerevisiae
Schmidt, K. H., Pennaneach, V., Putnam, C. D., & Kolodner, R. D. (2006) · Methods in Enzymology · doi:10.1016/s0076-6879(05)09027-0 · Cited by 52 · see citing works
Flagged first, then by citations
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Cited by
Sorted by citations
Łazowski, K. (2023) · Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis · doi:10.1016/j.mrfmmm.2023.111816 · Cited by 10 · see citing works
- Authors
- Radchenko, E. A., McGinty, R. J., Aksenova, A. Y., Neil, A. J., & Mirkin, S. M.
- Affiliations
- Tufts University (US)
- St Petersburg University (RU)
- Corresponding author
- Mirkin, Sergei M.
- Venue
- Methods in Molecular Biology
- Publisher
- Springer New York
- Published
- 2017-10-17
- Volume
- 1672
- Pages
- 421-438
- ISSN
- 1064-3745 (ISSN-L)
- 1940-6029
- PMC
- PMC5741187
- OpenAlex
- W2767069626
- Cited by
- 57
- References
- 3
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 8 · 2023: 7 · 2022: 8 · 2021: 8 · 2020: 7 · 2019: 6 · 2018: 1
- FWCI
- 7.86
- Type
- book chapter
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Methods in molecular biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Russian Foundation for Basic Research
- Saint Petersburg State University
- National Institutes of Health
- National Institute of General Medical Sciences (R01GM060987, P01GM105473)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Genetic Neurodegenerative Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA Repair Mechanisms
- Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
- Keywords
- trinucleotide repeat expansion, trinucleotide repeats, yeast, gross chromosomal rearrangements, expansion rate
- MeSH terms
- Repetitive Sequences, Nucleic Acid, Saccharomyces cerevisiae, Yeasts, Mutagenesis, Genome, Fungal, Trinucleotide Repeats, Trinucleotide Repeat Expansion, Genomic Instability, Mutation Rate
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