Integrated analysis of a compendium of RNA-Seq datasets for splicing factors

Efficient Analysis of Overdispersed Data Using an Accurate Computation of the Dirichlet Multinomial Distribution

Modeling count data using suitable statistical distributions has been instrumental for analyzing the patterns it conveys. However, failing to address critical aspects, like overdispersion, jeopardizes the effectiveness of such an analysis. In this paper, overdispersed count data is modeled using the Dirichlet Multinomial (DM) distribution by maximizing its likelihood using a fixed-point iteration algorithm. This is achieved by estimating the DM distribution parameters while comparing the recent Languasco-Migliardi (LM), and the Yu-Shaw (YS) procedures, which address the well-known computational difficulties of evaluating its log-likelihood. Experiments were conducted using multiple datasets from different domains spanning polls, images, and IoT network traffic. They all showed the superiority of the LM procedure as it succeeded at estimating the DM parameters at the designated level of accuracy in all experiments, while the YS procedure failed to produce sufficiently accurate results (or any results at all) in several experiments. Moreover, the LM procedure achieved a speedup that ranged from 2-fold to 20-fold over YS.

Escherichia coli transcriptome assembly from a compendium of RNA-seq data sets

Owing to the complexities of bacterial RNA biology, the transcriptomes of even the best studied bacteria are not fully understood. To help elucidate the transcriptional landscape of E. coli, we compiled a compendium of 3,376 RNA-seq data sets composed of more than 7 trillion sequenced bases, which we evaluate with a transcript assembly pipeline. We report expression profiles for all annotated E. coli genes as well as 5,071 other transcripts. Additionally, we observe hundreds of instances of co-transcribed genes that are novel with respect to existing operon databases. By integrating data from a large number of sequencing experiments corresponding to a wide range of conditions, we are able to obtain a comprehensive view of the E. coli transcriptome.

Spatial Regulation of Reactive Oxygen Species via G6PD in Brown Adipocytes Supports Thermogenic Function

Reactive oxygen species (ROS) are associated with various roles of brown adipocytes. Glucose-6-phosphate dehydrogenase (G6PD) controls cellular redox potentials by producing NADPH. Although G6PD upregulates cellular ROS levels in white adipocytes, the roles of G6PD in brown adipocytes remain elusive. Here, we found that G6PD defect in brown adipocytes impaired thermogenic function through excessive cytosolic ROS accumulation. Upon cold exposure, G6PD-deficient mutant (G6PD^mut) mice exhibited cold intolerance and downregulated thermogenic gene expression in brown adipose tissue (BAT). In addition, G6PD-deficient brown adipocytes had increased cytosolic ROS levels, leading to extracellular signal-regulated kinase (ERK) activation. In BAT of G6PD^mut mice, administration of antioxidant restored the thermogenic activity by potentiating thermogenic gene expression and relieving ERK activation. Consistently, body temperature and thermogenic execution were rescued by ERK inhibition in cold-exposed G6PD^mut mice. Taken together, these data suggest that G6PD in brown adipocytes would protect against cytosolic oxidative stress, leading to cold-induced thermogenesis.