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Genome sequencing of C. elegans balancer strains reveals previously unappreciated complex genomic rearrangements.

Tatiana Maroilley | Stephane Flibotte | Francesca Jean | Victoria Rodrigues Alves Barbosa | Andrew Galbraith | Afiya Razia Chida | Filip Cotra | Xiao Li | Larisa Oncea | Mark Edgley | Don Moerman | Maja Tarailo-Graovac
Genome research | 2023

Genetic balancers in Caenorhabditis elegans are complex variants that allow lethal or sterile mutations to be stably maintained in a heterozygous state by suppressing crossover events. Balancers constitute an invaluable tool in the C. elegans scientific community and have been widely used for decades. The first/traditional balancers were created by applying X-rays, UV, or gamma radiation on C. elegans strains, generating random genomic rearrangements. Their structures have been mostly explored with low-resolution genetic techniques (e.g., fluorescence in situ hybridization or PCR), before genomic mapping and molecular characterization through sequencing became feasible. As a result, the precise nature of most chromosomal rearrangements remains unknown, whereas, more recently, balancers have been engineered using the CRISPR-Cas9 technique for which the structure of the chromosomal rearrangement has been predesigned. Using short-read whole-genome sequencing (srWGS) and tailored bioinformatic analyses, we previously interpreted the structure of four chromosomal balancers randomly created by mutagenesis processes. Here, we have extended our analyses to five CRISPR-Cas9 balancers and 17 additional traditional balancing rearrangements. We detected and experimentally validated their breakpoints and have interpreted the balancer structures. Many of the balancers were found to be more intricate than previously described, being composed of complex genomic rearrangements (CGRs) such as chromoanagenesis-like events. Furthermore, srWGS revealed additional structural variants and CGRs not known to be part of the balancer genomes. Altogether, our study provides a comprehensive resource of complex genomic variations in C. elegans and highlights the power of srWGS to study the complexity of genomes by applying tailored analyses.

Pubmed ID: 36617680

Research resources used in this publication

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Antibodies used in this publication

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Associated grants

  • Agency: CIHR, Canada
    Id: PJT-156068

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This is a list of tools and resources that we have found mentioned in this publication.


SAMTOOLS (tool)

RRID:SCR_002105

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

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Circos (tool)

RRID:SCR_011798

A software package for visualizing data and information. It visualizes data in a circular layout - this makes Circos ideal for exploring relationships between objects or positions.

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Trimmomatic (tool)

RRID:SCR_011848

Software Java pipeline for trimming tasks for Illumina paired end and single ended data. Flexible Trimmer for Illumina Sequence Data. Pair aware preprocessing tool optimized for Illumina next generation sequencing data. Includes several processing steps for read trimming and filtering. Operating systems Unix/Linux, Mac OS, Windows.

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BLAT (tool)

RRID:SCR_011919

Software designed to quickly find sequences of 95% and greater similarity of length 25 bases or more.

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FastQC (tool)

RRID:SCR_014583

Quality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.

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BWA-MEM2 (tool)

RRID:SCR_022192

Software tool for sequence mapping.The next version of BWA-MEM. Used for aligning sequencing reads against large reference genome.

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