MYC oncoprotein is a multifunctional transcription factor that regulates the expression of a large number of genes involved in cellular growth, proliferation and metabolism. Altered MYC protein level lead to cellular transformation and tumorigenesis. MYC is deregulated in > 50% of human cancers, rendering it an attractive drug target. However, direct inhibition of this class of proteins using conventional small molecules is challenging due to their intrinsically disordered state. To discover novel posttranslational regulators of MYC protein stability and turnover, we established a genetic screen in mammalian cells by combining a fluorescent protein-based MYC abundance sensor, CRISPR/Cas9-based gene knockouts and next-generation sequencing. Our screen identifies UBR5, an E3 ligase of the HECT-type family, as a novel regulator of MYC degradation. Even in the presence of the well-described and functional MYC ligase, FBXW7, UBR5 depletion leads to accumulation of MYC in cells. We demonstrate interaction of UBR5 with MYC and reduced K48-linked ubiquitination of MYC upon loss of UBR5 in cells. Interestingly, in cancer cell lines with amplified MYC expression, depletion of UBR5 resulted in reduced cell survival, as a consequence of MYC stabilization. Finally, we show that MYC and UBR5 are co-amplified in more than 40% of cancer cells and that MYC copy number amplification correlates with enhanced transcriptional output of UBR5. This suggests that UBR5 acts as a buffer in MYC amplified settings and protects these cells from apoptosis.

Knobloch syndrome is an autosomal recessive phenotype mainly characterized by retinal detachment and encephalocele caused by biallelic pathogenic variants in the COL18A1 gene. However, there are patients clinically diagnosed as Knobloch syndrome with unknown molecular etiology not linked to COL18A1. We studied an historical pedigree (published in 1998) designated as KNO2 (Knobloch type 2 syndrome with intellectual disability, autistic behavior, retinal degeneration, encephalocele). Whole exome sequencing of the two affected siblings and the normal parents resulted in the identification of a PAK2 non-synonymous substitution p.(Glu435Lys) as a causative variant. The variant was monoallelic and apparently de novo in both siblings indicating a likely germline mosaicism in one of the parents; the mosaicism however could not be observed after deep sequencing of blood parental DNA. PAK2 encodes a member of a small group of serine/threonine kinases; these P21-activating kinases (PAKs) are essential in signal transduction and cellular regulation (cytoskeletal dynamics, cell motility, death and survival signaling, and cell cycle progression). Structural analysis of the PAK2 p.(Glu435Lys) variant which is located in the kinase domain of the protein predicts a possible compromise in the kinase activity. Functional analysis of the p.(Glu435Lys) PAK2 variant in transfected HEK293T cells results in a partial loss of the kinase activity. PAK2 has been previously suggested as an autism related gene. Our results show that PAK2 induced phenotypic spectrum is broad and not fully understood. We conclude that the KNO2 syndrome in the studied family is dominant and caused by a deleterious variant in the PAK2 gene.

CoverageMaster (CoM) is a copy number variation (CNV) calling algorithm based on depth-of-coverage maps designed to detect CNVs of any size in exome [whole exome sequencing (WES)] and genome [whole genome sequencing (WGS)] data. The core of the algorithm is the compression of sequencing coverage data in a multiscale Wavelet space and the analysis through an iterative Hidden Markov Model. CoM processes WES and WGS data at nucleotide scale resolution and accurately detects and visualizes full size range CNVs, including single or partial exon deletions and duplications. The results obtained with this approach support the possibility for coverage-based CNV callers to replace probe-based methods such as array comparative genomic hybridization and multiplex ligation-dependent probe amplification in the near future.

CoverageMaster (CoM) is a Copy Number Variation (CNV) calling algorithm based on depth-of-coverage maps designed to detect CNVs of any size in exome (WES) and genome (WGS) data. The core of the algorithm is the compression of sequencing coverage data in a multiscale Wavelet space and the analysis through an iterative Hidden Markov Model (HMM). CoM processes WES and WGS data at nucleotide scale resolution and accurately detect and visualize full size range CNVs, including single or partial exon deletions and duplications. The results obtained with this approach support the possibility for coverage-based CNV callers to replace probe-based methods such array CGH and MLPA in the near future.