Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2-5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6-8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers

Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub’s primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers.

Degradation of high loads of crystalline cellulose and of unpretreated plant biomass by the thermophilic bacterium Caldicellulosiruptor bescii

The thermophilic bacterium Caldicellulosiruptor bescii grows at 78 °C on high concentrations (200 g L(-1)) of both crystalline cellulose and unpretreated switchgrass, while low concentrations (<20 g L(-1)) of acid-pretreated switchgrass inhibit growth. Degradation of crystalline cellulose, but not that of unpretreated switchgrass, was limited by nitrogen and vitamin (folate) availability. Under optimal conditions, C. bescii solubilized approximately 60% of the crystalline cellulose and 30% of the unpretreated switchgrass using initial substrate concentrations of 50 g L(-1). Further fermentation of crystalline cellulose and of switchgrass was inhibited by organic acid end-products and by a specific inhibitor of C. bescii growth that did not affect other thermophilic bacteria, respectively. Soluble mono- and oligosaccharides, organic acids, carbon dioxide, and microbial biomass, quantitatively accounted for the crystalline cellulose and plant biomass carbon utilized. C. bescii therefore degrades industrially-relevant concentrations of lignocellulosic biomass that have not undergone pretreatment thereby demonstrating its potential utility in biomass conversion.