Patel, J. A. | bioRxiv Science

bioRxiv2024

Functional Genomics Validation of PPAR gamma Signalling in PASMCs: Therapeutic Implications for Pulmonary Arterial Hypertension

Gene Ontology (GO) is a tool which provides gene functional annotations, an essential resource for knowledge discovery and the analysis of biological datasets. Although considerable research has quantified the functional similarity between gene products and physiological processes, there is a need to identify which of these may contribute to pathophysiological states in humans. Previous studies have identified the role of PPARG in multiple signalling pathways, particularly those of TGFB1 and BMP2, in pulmonary artery smooth muscle cells and their relation to pulmonary arterial hypertension (PAH). To enhance the description of PPARG in the GO resource we systematically curated the proteins it interacts with and its physiological role in PASMCs. In addition, we curated the microRNAs that play a role in PAH through their regulation of PPARG expression and their downstream impact on cellular processes. This project curated experimental evidence describing 101 human miRNAs that regulate the expression of 17 PPARG signalling pathway-relevant proteins. Of these, 91 of our curated miRNAs were previously unannotated in terms of directly regulating the expression of these priority proteins. By submitting these annotations to the GO Consortium database, we have significantly expanded the breadth and depth of the GO description of PPARG-associated signalling pathways.

genomics↗

bioRxiv2021

BioCompute Objects to communicate a viral detection pipeline with potential for use in a regulatory environment

The volume of nucleic acid sequence data has exploded in recent years, and with it, the challenge of finding and transforming relevant data into meaningful information. Processing the abundance of data can require a dynamic ecosystem of customized tools. As analysis pipelines become more complex, there is an increased difficulty in communicating analysis details in a way that is understandable yet of sufficient detail to make informed decisions about results or repeat the analysis. This may be of particular interest to institutions and private companies that need to communicate complex computations in a regulatory environment. To meet this need for standard reporting, the open source BioCompute framework was developed as a standardized mechanism for communicating the details of an analysis in a concise and organized way, and other tools and interfaces were subsequently developed according to the standard. The goal of BioCompute is to streamline the process of communicating computational analyses. Reports that conform to the BioCompute standard are called BioCompute Objects (BCOs). Here, a comprehensive suite of BCOs is presented, representing interconnected elements of a computation that is modeled after those that might be found in a regulatory submission, but which can be shared publicly. Because BCOs are human and machine readable, they can be displayed in customized ways to further improve their utility, and an example of a collapsible format is shown. The work presented here serves as a real world implementation that imitates actual submissions, providing concrete examples. As an example, a pipeline designed to identify viral contaminants in biological manufacturing, such as for vaccines, is developed and rigorously tested to establish a rate of false positive detection, and is described in a BCO report. That pipeline relies on a specially curated database for alignment, and a set of synthetic reads for testing, both of which are also descriptively packaged in their own BCOs. All of the sufficiently complex processes associated with this analysis are therefore represented as BCOs that can be cross-referenced, demonstrating the modularity of BCOs, their ability to organize tremendous complexity, and their use in a lifelike regulatory environment.

bioinformatics↗