RNA splicing analysis using heterogeneous and large RNA-seq datasets.

The ubiquity of RNA-seq has led to many methods that use RNA-seq data to analyze variations in RNA splicing. However, available methods are not well suited for handling heterogeneous and large datasets. Such datasets scale to thousands of samples across dozens of experimental conditions, exhibit increased variability compared to biological replicates, and involve thousands of unannotated splice variants resulting in increased transcriptome complexity.

Analysis of histone variant constraint and tissue expression suggests five potential novel human disease genes: H2AFY2, H2AFZ, H2AFY, H2AFV, H1F0.

While germline variants in histone protein-encoding genes are emerging as the pathogenic mutations underlying rare, Mendelian disorders characterized by a conserved phenotype of neurodevelopmental syndrome coupled with craniofacial abnormalities, a systematic assessment of all human genes encoding histone proteins has not been performed to predict novel disease-candidate genes. We first defined a comprehensive list of 89 histone-encoding genes. We then analyzed which are most likely to underlay this conserved phenotype when mutated based on their intolerance to either missense or loss-of-function variation and based on their tissue expression profile.

Mapping RNA splicing variations in clinically accessible and nonaccessible tissues to facilitate Mendelian disease diagnosis using RNA-seq.

Purpose: RNA-seq is a promising approach to improve diagnoses by detecting pathogenic aberrations in RNA splicing that are missed by DNA sequencing. RNA-seq is typically performed on clinically accessible tissues (CATs) from blood and skin. RNA tissue specificity makes it difficult to identify aberrations in relevant but nonaccessible tissues (non-CATs).

Random Forest Analysis of Untargeted Metabolomics Data Suggests Increased Use of Omega Fatty Acid Oxidation Pathway in Drosophila Melanogaster Larvae Fed a Medium Chain Fatty Acid Rich High-Fat Diet.

Obesity is a complex disease, shaped by both genetic and environmental factors such as diet. In this study, we use untargeted metabolomics and Drosophila melanogaster to model how diet and genotype shape the metabolome of obese phenotypes. We used 16 distinct outbred genotypes of Drosophila larvae raised on normal (ND) and high-fat (HFD) diets, to produce three distinct phenotypic classes; genotypes that stored more triglycerides on a ND relative to the HFD, genotypes that stored more triglycerides on a HFD relative to ND, and genotypes that showed no change in triglyceride storage on either of the two diets.

ChromoShake: a chromosome dynamics simulator reveals that chromatin loops stiffen centromeric chromatin.

ChromoShake is a three-dimensional simulator designed to find the thermodynamically favored states for given chromosome geometries. The simulator has been applied to a geometric model based on experimentally determined positions and fluctuations of DNA and the distribution of cohesin and condensin in the budding yeast centromere. Simulations of chromatin in differing initial configurations reveal novel principles for understanding the structure and function of a eukaryotic centromere.

Variant non ketotic hyperglycinemia is caused by mutations in LIAS, BOLA3 and the novel gene GLRX5.

Patients with nonketotic hyperglycinemia and deficient glycine cleavage enzyme activity, but without mutations in AMT, GLDC or GCSH, the genes encoding its constituent proteins, constitute a clinical group which we call 'variant nonketotic hyperglycinemia'. We hypothesize that in some patients the aetiology involves genetic mutations that result in a deficiency of the cofactor lipoate, and sequenced genes involved in lipoate synthesis and iron-sulphur cluster biogenesis. Of 11 individuals identified with variant nonketotic hyperglycinemia, we were able to determine the genetic aetiology in eight patients and delineate the clinical and biochemical phenotypes.