Single variant, yet "double trouble": TSC and KBG syndrome because of a large de novo inversion.

Despite the advances in high-throughput sequencing, many rare disease patients remain undiagnosed. In particular, the patients with well-defined clinical phenotypes and established clinical diagnosis, yet missing or partial genetic diagnosis, may hold a clue to more complex genetic mechanisms of a disease that could be missed by available clinical tests. Here, we report a patient with a clinical diagnosis of Tuberous sclerosis, combined with unusual secondary features, but negative clinical tests including TSC1 and TSC2 Short-read whole-genome sequencing combined with advanced bioinformatics analyses were successful in uncovering a de novo pericentric 87-Mb inversion with breakpoints in TSC2 and ANKRD11, which explains the TSC clinical diagnosis, and confirms a second underlying monogenic disorder, KBG syndrome. Our findings illustrate how complex variants, such as large inversions, may be missed by clinical tests and further highlight the importance of well-defined clinical diagnoses in uncovering complex molecular mechanisms of a disease, such as complex variants and "double trouble" effects.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans.

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

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

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.