Quiescence unveils a novel mutational force in fission yeast

To maintain life across a fluctuating environment, cells alternate between phases of cell division and quiescence. During cell division, the spontaneous mutation rate is expressed as the probability of mutations per generation (Luria and Delbrück, 1943; Lea and Coulson, 1949), whereas during quiescence it will be expressed per unit of time. In this study, we report that during quiescence, the unicellular haploid fission yeast accumulates mutations as a linear function of time. The novel mutational landscape of quiescence is characterized by insertion/deletion (indels) accumulating as fast as single nucleotide variants (SNVs), and elevated amounts of deletions. When we extended the study to 3 months of quiescence, we confirmed the replication-independent mutational spectrum at the whole-genome level of a clonally aged population and uncovered phenotypic variations that subject the cells to natural selection. Thus, our results support the idea that genomes continuously evolve under two alternating phases that will impact on their size and composition.

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Quiescence unveils a novel mutational force in fission yeast

10.1101/126755 ◽

2017 ◽

Author(s):

Serge Gangloff ◽

Guillaume Achaz ◽

Adrien Villain ◽

Samia Miled ◽

Claire Denis ◽

...

Keyword(s):

Fission Yeast ◽

Spontaneous Mutation ◽

The Novel ◽

Single Nucleotide Variants ◽

Spontaneous Mutation Rate ◽

Single Nucleotide ◽

Mutational Landscape ◽

Evolutionary Force ◽

Phenotypic Variations ◽

Genome Level

One Sentence SummaryThe quiescence-driven mutational landscape reveals a novel evolutionary force.AbstractDuring cell division, the spontaneous mutation rate is expressed as the probability of mutations per generation, whereas during quiescence it will be expressed per unit of time. In this study, we report that during quiescence, the unicellular haploid fission yeast accumulates mutations as a linear function of time. We determined that 3 days of quiescence generate a number of invalidating mutations equivalent to that of one round of DNA replication. The novel mutational landscape of quiescence is characterized by insertion/deletion accumulating as fast as single nucleotide variants, and elevated amounts of deletions. When we extended the study to 3 months of quiescence, we confirmed the replication-independent mutational spectrum at the whole-genome level of a clonally aged population and uncovered phenotypic variations that subject the cells to natural selection. Thus, our results support the idea that genomes continuously evolve under two alternating phases that will impact on their size and composition.

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Base editing generates substantial off-target single nucleotide variants

10.1101/480145 ◽

2018 ◽

Cited By ~ 5

Author(s):

Erwei Zuo ◽

Yidi Sun ◽

Wu Wei ◽

Tanglong Yuan ◽

Wenqin Ying ◽

...

Keyword(s):

Mammalian Cells ◽

Biomedical Application ◽

Spontaneous Mutation ◽

Great Promise ◽

Single Nucleotide Variants ◽

Spontaneous Mutation Rate ◽

Single Nucleotide ◽

Base Editing ◽

Genome Wide ◽

Target Effects

AbstractGenome editing tools including CRISPR/Cas9 and base editors hold great promise for correcting pathogenic mutations. Unbiased genome-wide off-target effects of the editing in mammalian cells is required before clinical applications, but determination of the extent of off-target effects has been difficult due to the existence of single nucleotide polymorphisms (SNPs) in individuals. Here, we developed a method named GOTI (Genome-wide Off-target analysis by Two-cell embryo Injection) to detect off-target mutations without interference of SNPs. We applied GOTI to both the CRISPR-Cas9 and base editing (BE3) systems by editing one blastomere of the two-cell mouse embryo and then compared whole genome sequences of progeny-cell populations at E14.5 stage. Sequence analysis of edited and non-edited cell progenies showed that undesired off-target single nucleotide variants (SNVs) are rare (average 10.5) in CRISPR-edited mouse embryos, with a frequency close to the spontaneous mutation rate. By contrast, BE3 editing induced over 20-fold higher SNVs (average 283), raising the concern of using base-editing approaches for biomedical application.

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Cytosine base editor generates substantial off-target single-nucleotide variants in mouse embryos

Science ◽

10.1126/science.aav9973 ◽

2019 ◽

pp. eaav9973 ◽

Cited By ~ 84

Author(s):

Erwei Zuo ◽

Yidi Sun ◽

Wu Wei ◽

Tanglong Yuan ◽

Wenqin Ying ◽

...

Keyword(s):

Spontaneous Mutation ◽

Mouse Embryos ◽

Single Nucleotide Variants ◽

Spontaneous Mutation Rate ◽

Single Nucleotide ◽

Base Editing ◽

Genome Wide ◽

Cell Embryo ◽

Adenine Base ◽

Target Effects

Genome editing holds promise for correcting pathogenic mutations. However, it is difficult to determine off-target effects of editing due to single nucleotide polymorphism in individuals. Here, we developed a method named GOTI (Genome-wide Off-target analysis by Two-cell embryo Injection) to detect off-target mutations by editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or base editors. Comparison of the whole genome sequences of progeny cells of edited vs. non-edited blastomeres at E14.5 showed that off-target single nucleotide variants (SNVs) were rare in embryos edited by CRISPR-Cas9 or adenine base editor, with a frequency close to the spontaneous mutation rate. In contrast, cytosine base editing induced SNVs with over 20-fold higher frequencies, requiring a solution to address its fidelity.

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Accurate detection of subclonal single nucleotide variants in whole genome amplified and pooled cancer samples using HaloPlex target enrichment

BMC Genomics ◽

10.1186/1471-2164-14-856 ◽

2013 ◽

Vol 14 (1) ◽

pp. 856 ◽

Cited By ~ 15

Author(s):

Eva C Berglund ◽

Carl Lindqvist ◽

Shahina Hayat ◽

Elin Övernäs ◽

Niklas Henriksson ◽

...

Keyword(s):

Whole Genome ◽

Target Enrichment ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Accurate Detection

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Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

10.1101/316976 ◽

2018 ◽

Cited By ~ 4

Author(s):

Maxime Garcia ◽

Szilveszter Juhos ◽

Malin Larsson ◽

Pall I. Olason ◽

Marcel Martin ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Open Source ◽

Genome Sequencing ◽

Development Project ◽

Whole Genome ◽

Sequencing Analysis ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Insertion And Deletion ◽

Sample Heterogeneity

AbstractSummaryWhole-genome sequencing (WGS) is a cornerstone of precision medicine, but portable and reproducible open-source workflows for WGS analyses of germline and somatic variants are lacking. We present Sarek, a modular, comprehensive, and easy-to-install workflow, combining a range of software for the identification and annotation of single-nucleotide variants (SNVs), insertion and deletion variants (indels), structural variants, tumor sample heterogeneity, and karyotyping from germline or paired tumor/normal samples. Sarek is implemented in a bioinformatics workflow language (Nextflow) with Docker and Singularity compatible containers, ensuring easy deployment and full reproducibility at any Linux based compute cluster or cloud computing environment. Sarek supports the human reference genomes GRCh37 and GRCh38, and can readily be used both as a core production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups.AvailabilitySource code and instructions for local installation are available at GitHub (https://github.com/SciLifeLab/Sarek) under the MIT open-source license, and we invite the research community to contribute additional functionality as a collaborative open-source development project.

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Integration of single nucleotide variants and whole-genome DNA methylation profiles for classification of rheumatoid arthritis cases from controls

Heredity ◽

10.1038/s41437-020-0301-4 ◽

2020 ◽

Vol 124 (5) ◽

pp. 658-674 ◽

Cited By ~ 1

Author(s):

Mahmoud Amiri Roudbar ◽

Mohammad Reza Mohammadabadi ◽

Ahmad Ayatollahi Mehrgardi ◽

Rostam Abdollahi-Arpanahi ◽

Mehdi Momen ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Dna Methylation ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Single Nucleotide

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Genome aging: somatic mutation in the brain links age-related decline with disease and nominates pathogenic mechanisms

Human Molecular Genetics ◽

10.1093/hmg/ddz191 ◽

2019 ◽

Vol 28 (R2) ◽

pp. R197-R206 ◽

Cited By ~ 10

Author(s):

Michael A Lodato ◽

Christopher A Walsh

Keyword(s):

Human Brain ◽

Somatic Mutation ◽

Somatic Mutations ◽

Late Onset ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Age Related ◽

The Brain ◽

Over Time

AbstractAging is a mysterious process, not only controlled genetically but also subject to random damage that can accumulate over time. While DNA damage and subsequent mutation in somatic cells were first proposed as drivers of aging more than 60 years ago, whether and to what degree these processes shape the neuronal genome in the human brain could not be tested until recent technological breakthroughs related to single-cell whole-genome sequencing. Indeed, somatic single-nucleotide variants (SNVs) increase with age in the human brain, in a somewhat stochastic process that may nonetheless be controlled by underlying genetic programs. Evidence from the literature suggests that in addition to demonstrated increases in somatic SNVs during aging in normal brains, somatic mutation may also play a role in late-onset, sporadic neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. In this review, we will discuss somatic mutation in the human brain, mechanisms by which somatic mutations occur and can be controlled, and how this process can impact human health.

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Accurate identification of single-nucleotide variants in whole-genome-amplified single cells

Nature Methods ◽

10.1038/nmeth.4227 ◽

2017 ◽

Vol 14 (5) ◽

pp. 491-493 ◽

Cited By ~ 87

Author(s):

Xiao Dong ◽

Lei Zhang ◽

Brandon Milholland ◽

Moonsook Lee ◽

Alexander Y Maslov ◽

...

Keyword(s):

Single Cells ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Accurate Identification ◽

Single Nucleotide

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Post-lingual non-syndromic hearing loss phenotype: a novel homozygous missense mutation in MITF

10.21203/rs.2.13328/v2 ◽

2019 ◽

Author(s):

Athar Khalil ◽

Samer Bou Karroum ◽

Rana Barake ◽

Gabriel Dunya ◽

Samer Abou-Rizk ◽

...

Keyword(s):

Hearing Loss ◽

Exome Sequencing ◽

Missense Mutation ◽

The Novel ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Whole Exome ◽

Genetic Hearing Loss ◽

Syndromic Hearing Loss ◽

And Function

Abstract Background Hearing loss (HL) represents the most common congenital sensory impairment with an incidence of 1-5 per 1000 live births. Non-syndromic hearing loss (NSHL) is an isolated finding that is not part of any other disorder accounting for 70% of all genetic hearing loss cases. Methods In the current study, we report a multifactorial genetic mode of inheritance in a NSHL consanguineous family using exome sequencing technology. We evaluated the possible effects of the single nucleotide variants (SNVs) detected in our patients using in silico methods. Results Two bi-allelic SNVs were detected in the affected patients; a MYO15A (. p.V485A) variant, and a novel MITF (p.P338L) variant. Along with these homozygous mutations, we detected two heterozygous variants in well described hearing loss genes (MYO7A and MYH14). The novel p. Pro338Leu missense mutation on the MITF protein was predicted to change the protein structure and function. Conclusion The novel MITF variant is the first bi-allelic SNV in this gene to be associated with an autosomal recessive non-syndromic HL case with a post-lingual onset. Our findings highlight the importance of whole exome sequencing for a comprehensive assessment of the genetic heterogeneity of HL.

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MethylExtract: High-Quality methylation maps and SNV calling from whole genome bisulfite sequencing data

F1000Research ◽

10.12688/f1000research.2-217.v2 ◽

2014 ◽

Vol 2 ◽

pp. 217 ◽

Cited By ~ 8

Author(s):

Guillermo Barturen ◽

Antonio Rueda ◽

José L. Oliver ◽

Michael Hackenberg

Keyword(s):

High Throughput ◽

Sequence Variation ◽

High Throughput Sequencing ◽

Whole Genome ◽

Single Nucleotide Variants ◽

High Quality ◽

Single Nucleotide ◽

Error Sources ◽

Link Type ◽

Genome Methylation

Whole genome methylation profiling at a single cytosine resolution is now feasible due to the advent of high-throughput sequencing techniques together with bisulfite treatment of the DNA. To obtain the methylation value of each individual cytosine, the bisulfite-treated sequence reads are first aligned to a reference genome, and then the profiling of the methylation levels is done from the alignments. A huge effort has been made to quickly and correctly align the reads and many different algorithms and programs to do this have been created. However, the second step is just as crucial and non-trivial, but much less attention has been paid to the final inference of the methylation states. Important error sources do exist, such as sequencing errors, bisulfite failure, clonal reads, and single nucleotide variants.We developed MethylExtract, a user friendly tool to: i) generate high quality, whole genome methylation maps and ii) detect sequence variation within the same sample preparation. The program is implemented into a single script and takes into account all major error sources. MethylExtract detects variation (SNVs – Single Nucleotide Variants) in a similar way to VarScan, a very sensitive method extensively used in SNV and genotype calling based on non-bisulfite-treated reads. The usefulness of MethylExtract is shown by means of extensive benchmarking based on artificial bisulfite-treated reads and a comparison to a recently published method, called Bis-SNP.MethylExtract is able to detect SNVs within High-Throughput Sequencing experiments of bisulfite treated DNA at the same time as it generates high quality methylation maps. This simultaneous detection of DNA methylation and sequence variation is crucial for many downstream analyses, for example when deciphering the impact of SNVs on differential methylation. An exclusive feature of MethylExtract, in comparison with existing software, is the possibility to assess the bisulfite failure in a statistical way. The source code, tutorial and artificial bisulfite datasets are available at http://bioinfo2.ugr.es/MethylExtract/ and http://sourceforge.net/projects/methylextract/, and also permanently accessible from 10.5281/zenodo.7144.

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