Whole-Genome and Long-Read Sequencing Identify a Novel Mechanism in Resulting in CANVAS Syndrome.

Objectives: Cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS) results from biallelic intronic pentanucleotide repeats in We describe an adult male proband with progressive imbalance, cerebellar atrophy, somatosensory neuronopathy, and absence of peripheral vestibular function for whom clinical testing demonstrated a heterozygous expansion consistent with an unaffected carrier.

Methods: We performed whole-genome sequencing (WGS) on peripheral blood DNA samples from the proband and his unaffected mother. We performed DNA long-read sequencing and synthesized complementary DNA from RNA using peripheral blood from the proband.

Discovery of a novel CHD7 CHARGE syndrome variant by integrated omics analyses.

Chromodomain helicase DNA-binding protein 7 (CHD7) pathogenic variants are identified in more than 90% of infants and children with CHARGE (Coloboma of the iris, retina, and/or optic disk; congenital Heart defects, choanal Atresia, Retardation of growth and development, Genital hypoplasia, and characteristic outer and inner Ear anomalies and deafness) syndrome. Approximately, 10% of cases have no known genetic cause identified. We report a male child with clinical features of CHARGE syndrome and nondiagnostic genetic testing that included chromosomal microarray, CHD7 sequencing and deletion/duplication analysis, SEMA3E sequencing, and trio exome and whole-genome sequencing (WGS).

Using Apache Spark on genome assembly for scalable overlap-graph reduction.

Background: De novo genome assembly is a technique that builds the genome of a specimen using overlaps of genomic fragments without additional work with reference sequence. Sequence fragments (called reads) are assembled as contigs and scaffolds by the overlaps. The quality of the de novo assembly depends on the length and continuity of the assembly.

LONGO: an R package for interactive gene length dependent analysis for neuronal identity.

Motivation: Reprogramming somatic cells into neurons holds great promise to model neuronal development and disease. The efficiency and success rate of neuronal reprogramming, however, may vary between different conversion platforms and cell types, thereby necessitating an unbiased, systematic approach to estimate neuronal identity of converted cells. Recent studies have demonstrated that long genes (>100 kb from transcription start to end) are highly enriched in neurons, which provides an opportunity to identify neurons based on the expression of these long genes.