The gut microbiome modifies the associations of short- and long-term physical activity with body weight changes.

Background: The gut microbiome regulates host energy balance and adiposity-related metabolic consequences, but it remains unknown how the gut microbiome modulates body weight response to physical activity (PA).

Methods: Nested in the Health Professionals Follow-up Study, a subcohort of 307 healthy men (mean[SD] age, 70[4] years) provided stool and blood samples in 2012-2013. Data from cohort long-term follow-ups and from the accelerometer, doubly labeled water, and plasma biomarker measurements during the time of stool collection were used to assess long-term and short-term associations of PA with adiposity.

High-sensitivity pattern discovery in large, paired multiomic datasets.

Motivation: Modern biological screens yield enormous numbers of measurements, and identifying and interpreting statistically significant associations among features are essential. In experiments featuring multiple high-dimensional datasets collected from the same set of samples, it is useful to identify groups of associated features between the datasets in a way that provides high statistical power and false discovery rate (FDR) control.

Results: Here, we present a novel hierarchical framework, HAllA (Hierarchical All-against-All association testing), for structured association discovery between paired high-dimensional datasets.

Strain Identification and Quantitative Analysis in Microbial Communities.

Microbiology has long studied the ways in which subtle genetic differences between closely related microbial strains can have profound impacts on their phenotypes and those of their surrounding environments and communities. Despite the growth in high-throughput microbial community profiling, however, such strain-level differences remain challenging to detect. Once detected, few quantitative approaches have been well-validated for associating strain variants from microbial communities with phenotypes of interest, such as medication usage, treatment efficacy, host environment, or health.

Bayesian modelling of high-throughput sequencing assays with malacoda.

NGS studies have uncovered an ever-growing catalog of human variation while leaving an enormous gap between observed variation and experimental characterization of variant function. High-throughput screens powered by NGS have greatly increased the rate of variant functionalization, but the development of comprehensive statistical methods to analyze screen data has lagged. In the massively parallel reporter assay (MPRA), short barcodes are counted by sequencing DNA libraries transfected into cells and the cell's output RNA in order to simultaneously measure the shifts in transcription induced by thousands of genetic variants.

Functionalization of CD36 cardiovascular disease and expression associated variants by interdisciplinary high throughput analysis.

CD36 is a platelet membrane glycoprotein whose engagement with oxidized low-density lipoprotein (oxLDL) results in platelet activation. The CD36 gene has been associated with platelet count, platelet volume, as well as lipid levels and CVD risk by genome-wide association studies. Platelet CD36 expression levels have been shown to be associated with both the platelet oxLDL response and an elevated risk of thrombo-embolism.

Design tools for MPRA experiments.

Motivation: Genetic reporter assays are a convenient, relatively inexpensive method for studying the regulation of gene expression. Massively Parallel Reporter Assays (MPRA) are high-throughput functionalization assays that interrogate the transcriptional activity of many genetic variants at once using a library of synthetic barcoded constructs. Despite growing interest in this area, there are few computational tools to design and execute MPRA studies.

Use of Exome Sequencing for Infants in Intensive Care Units: Ascertainment of Severe Single-Gene Disorders and Effect on Medical Management.

Importance: While congenital malformations and genetic diseases are a leading cause of early infant death, to our knowledge, the contribution of single-gene disorders in this group is undetermined.

Objective: To determine the diagnostic yield and use of clinical exome sequencing in critically ill infants.

Design, Setting, And Participants: Clinical exome sequencing was performed for 278 unrelated infants within the first 100 days of life who were admitted to Texas Children's Hospital in Houston, Texas, during a 5-year period between December 2011 and January 2017.