Two Patients with Complex Rearrangements Suggestive of Germline Chromoanagenesis

A Maternally Inherited Rare Case with Chromoanagenesis-Related Complex Chromosomal Rearrangements and De Novo Microdeletions

Chromoanagenesis is a phenomenon of highly complex rearrangements involving the massive genomic shattering and reconstitution of chromosomes that has had a great impact on cancer biology and congenital anomalies. Complex chromosomal rearrangements (CCRs) are structural alterations involving three or more chromosomal breakpoints between at least two chromosomes. Here, we present a 3-year-old boy exhibiting multiple congenital malformations and developmental delay. The cytogenetic analysis found a highly complex CCR inherited from the mother involving four chromosomes and five breakpoints due to forming four derivative chromosomes (2, 3, 6 and 11). FISH analysis identified an ultrarare derivative chromosome 11 containing three parts that connected the 11q telomere to partial 6q and 3q fragments. We postulate that this derivative chromosome 11 is associated with chromoanagenesis-like phenomena by which DNA repair can result in a cooccurrence of inter-chromosomal translocations. Additionally, chromosome microarray studies revealed that the child has one subtle maternal-inherited deletion at 6p12.1 and two de novo deletions at 6q14.1 and 6q16.1~6q16.3. Here, we present a familial CCR case with rare rearranged chromosomal structures and the use of multiple molecular techniques to delineate these genomic alterations. We suggest that chromoanagenesis may be a possible mechanism involved in the repair and reconstitution of these rearrangements with evidence for increasing genomic imbalances such as additional deletions in this case.

Deciphering complex genome rearrangements in C. elegans using short-read whole genome sequencing

Genomic rearrangements cause congenital disorders, cancer, and complex diseases in human. Yet, they are still understudied in rare diseases because their detection is challenging, despite the advent of whole genome sequencing (WGS) technologies. Short-read (srWGS) and long-read WGS approaches are regularly compared, and the latter is commonly recommended in studies focusing on genomic rearrangements. However, srWGS is currently the most economical, accurate, and widely supported technology. In Caenorhabditis elegans (C. elegans), such variants, induced by various mutagenesis processes, have been used for decades to balance large genomic regions by preventing chromosomal crossover events and allowing the maintenance of lethal mutations. Interestingly, those chromosomal rearrangements have rarely been characterized on a molecular level. To evaluate the ability of srWGS to detect various types of complex genomic rearrangements, we sequenced three balancer strains using short-read Illumina technology. As we experimentally validated the breakpoints uncovered by srWGS, we showed that, by combining several types of analyses, srWGS enables the detection of a reciprocal translocation (eT1), a free duplication (sDp3), a large deletion (sC4), and chromoanagenesis events. Thus, applying srWGS to decipher real complex genomic rearrangements in model organisms may help designing efficient bioinformatics pipelines with systematic detection of complex rearrangements in human genomes.

Chromoanagenesis Landscape in 10,000 TCGA Patients

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor's nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.