Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

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Signal transduction through the RAF-MEK-ERK pathway, the first described mitogen-associated protein kinase (MAPK) cascade, mediates multiple cellular processes and participates in early and late developmental programs. Aberrant signaling through this cascade contributes to oncogenesis and underlies the RASopathies, a family of cancer-prone disorders. Here, we report that de novo missense variants in MAPK1, encoding the mitogen-activated protein kinase 1 (i.e., extracellular signal-regulated protein kinase 2, ERK2), cause a neurodevelopmental disease within the RASopathy phenotypic spectrum, reminiscent of Noonan syndrome in some subjects. Pathogenic variants promote increased phosphorylation of the kinase, which enhances translocation to the nucleus and boosts MAPK signaling in vitro and in vivo. Two variant classes are identified, one of which directly disrupts binding to MKP3, a dual-specificity protein phosphatase negatively regulating ERK function. Importantly, signal dysregulation driven by pathogenic MAPK1 variants is stimulus reliant and retains dependence on MEK activity. Our data support a model in which the identified pathogenic variants operate with counteracting effects on MAPK1 function by differentially impacting the ability of the kinase to interact with regulators and substrates, which likely explains the minor role of these variants as driver events contributing to oncogenesis. After nearly 20 years from the discovery of the first gene implicated in Noonan syndrome, PTPN11, the last tier of the MAPK cascade joins the group of genes mutated in RASopathies.

Enhanced MAPK1 Function Causes a Neurodevelopmental Disorder within the RASopathy Clinical Spectrum

The widespread availability of genetic testing for those with neurodevelopmental disorders has highlighted the importance of many genes necessary for the proper development and function of the nervous system. One gene found to be genetically altered in the X-linked intellectual disability disorder Claes-Jensen syndrome is KDM5C, which encodes a histone demethylase that regulates transcription by altering chromatin. While the genetic link between KDM5C and cognitive (dys)function is clear, how KDM5C functions to control transcriptional programs within neurons to impact their growth and activity remains the subject of ongoing research. Here, we review our current knowledge of Claes-Jensen syndrome and discuss important new data using model organisms that have revealed the importance of KDM5C in regulating aspects of neuronal development and function. Continued research into the molecular and cellular activities regulated by KDM5C is expected to provide critical etiological insights into Claes-Jensen syndrome and highlight potential targets for developing therapies to improve the quality of life of those affected.

Molecular and cellular events linking variants in the histone demethylase KDM5C to the intellectual disability disorder Claes-Jensen syndrome

A fusion gene is the physical juxtaposition of two different genes resulting in a structure consisting of the head of one gene and the tail of the other. Gene fusion is often a primary neoplasia-inducing event in leukemias, lymphomas, solid malignancies as well as benign tumors. Knowledge about fusion genes is crucial not only for our understanding of tumorigenesis, but also for the diagnosis, prognostication, and treatment of cancer. Balanced chromosomal rearrangements, in particular translocations and inversions, are the most frequent genetic events leading to the generation of fusion genes. In the present review, we summarize the existing knowledge on chromosome deletions as a mechanism for fusion gene formation. Such deletions are mostly submicroscopic and, hence, not detected by cytogenetic analyses but by array comparative genome hybridization (aCGH) and/or high throughput sequencing (HTS). They are found across the genome in a variety of neoplasias. As tumors are increasingly analyzed using aCGH and HTS, it is likely that more interstitial deletions giving rise to fusion genes will be found, significantly impacting our understanding and treatment of cancer.

Interstitial Deletions Generating Fusion Genes.

Mosaic mutations contribute to numerous human disorders. As such, the identification and precise quantification of mosaic mutations is essential for a wide range of research applications, clinical diagnoses, and early detection of cancers. Currently, the low-throughput nature of single allele assays (e.g., allele-specific ddPCR) commonly used for genotyping known mutations at very low alternate allelic fractions (AAFs) have limited the integration of low-level mosaic analyses into clinical and research applications. The growing importance of mosaic mutations requires a more rapid, low-cost solution for mutation detection and validation. To overcome these limitations, we developed Multiple Independent Primer PCR Sequencing (MIPP-Seq) which combines the power of ultra-deep sequencing and truly independent assays. The accuracy of MIPP-seq to quantifiable detect and measure extremely low allelic fractions was assessed using a combination of SNVs, insertions, and deletions at known allelic fractions in blood and brain derived DNA samples. The Independent amplicon analyses of MIPP-Seq markedly reduce the impact of allelic dropout, amplification bias, PCR-induced, and sequencing artifacts. Using low DNA inputs of either 25 ng or 50 ng of DNA, MIPP-Seq provides sensitive and quantitative assessments of AAFs as low as 0.025% for SNVs, insertion, and deletions. MIPP-Seq provides an ultra-sensitive, low-cost approach for detecting and validating known and novel mutations in a highly scalable system with broad utility spanning both research and clinical diagnostic testing applications. The scalability of MIPP-Seq allows for multiplexing mutations and samples, which dramatically reduce costs of variant validation when compared to methods like ddPCR. By leveraging the power of individual analyses of multiple unique and independent reactions, MIPP-Seq can validate and precisely quantitate extremely low AAFs across multiple tissues and mutational categories including both indels and SNVs. Furthermore, using Illumina sequencing technology, MIPP-seq provides a robust method for accurate detection of novel mutations at an extremely low AAF.

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MIPP-Seq: ultra-sensitive rapid detection and validation of low-frequency mosaic mutations.

Exome sequencing (ES) has become an important tool in pediatric genomic medicine, improving identification of disease-associated variation due to assay breadth. Depth is also afforded by ES, enabling detection of lower-frequency mosaic variation compared to Sanger sequencing in the studied tissue, thus enhancing diagnostic yield. Within a pediatric tertiary-care hospital, we report two years of clinical ES data from probands evaluated for genetic disease to assess diagnostic yield, characteristics of causal variants, and prevalence of mosaicism among disease-causing variants. Exome-derived, phenotype-driven variant data from 357 probands was analyzed concurrent with parental ES data, when available. Blood was the source of nucleic acid. Sequence read alignments were manually reviewed for all assessed variants. Sanger sequencing was used for suspected de novo or mosaic variation. Clinical provider notes were reviewed to determine concordance between laboratory-reported data and the ordering provider's interpretation of variant-associated disease causality. Laboratory-derived diagnostic yield and provider-substantiated diagnoses had 91.4% concordance. The cohort returned 117 provider-substantiated diagnoses among 115 probands for a diagnostic yield of 32.2%. De novo variants represented 64.9% of disease-associated variation within trio analyses. Among the 115 probands, five harbored disease-associated somatic mosaic variation. Two additional probands were observed to inherit a disease-associated variant from an unaffected mosaic parent. Among inheritance patterns, de novo variation was the most frequent disease etiology. Somatic mosaicism is increasingly recognized as a significant contributor to genetic disease, particularly with increased sequence depth attainable from ES. This report highlights the potential and importance of detecting mosaicism in ES.

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Cecelia R. Miller

Papers

Disease-associated mosaic variation in clinical exome sequencing: a two-year pediatric tertiary care experience.

Genetic Characterization of Pediatric Sarcomas by Targeted RNA Sequencing.