Chowdhury, L. | Search bioRxiv

bioRxiv2024

PANOMIQ: A Unified Approach to Whole-Genome, Exome, and Microbiome Data Analysis

The integration of whole-genome sequencing (WGS), whole-exome sequencing (WES), and microbiome analysis has become essential for advancing our understanding of complex biological systems. However, the fragmented nature of current analytical tools often complicates the process, leading to inefficiencies and potential data loss. To address this challenge, we present PANOMIQ, a comprehensive software solution that unifies the analysis of WGS, WES, and microbiome data into a single, streamlined pipeline. PANOMIQ is designed to facilitate the entire analysis process from raw data to interpretable results. It is the fastest algorithm that can achieve results much more quickly compared to traditional pipeline approaches of WGS and WES analysis. It incorporates advanced algorithms for high-accuracy variant calling in both WGS and WES, along with robust tools for characterizing microbial communities. The softwares modular architecture allows for seamless integration of these diverse data types, enabling researchers to uncover complex interactions between host genomics and microbiomes. In this study, we demonstrate the capabilities of PANOMIQ by applying it to a series of datasets encompassing a wide range of applications, including disease association studies and environmental microbiome profiling. Our results highlight PANOMIQs ability to deliver comprehensive insights, significantly reducing the time and computational resources required for multi-omic analysis. By providing a unified platform for WGS, WES, and microbiome analysis, PANOMIQ offers a powerful tool for researchers aiming to explore the full spectrum of genomic and microbial diversity. This software not only simplifies the analytical workflow but also enhances the depth of biological interpretation, paving the way for more integrated and holistic studies in genomics and microbiology.

bioinformatics↗

bioRxiv2022

Pre-Germinal Center Interactions with T Cells are Natural Checkpoints to Limit Autoimmune B Cell Responses

Interactions with antigen-specific T cells drive B cells activation and fate choices that ultimately determine the quality of high-affinity antibody responses. As such, thse interactions, and especially the long-lived interactions that occur prior to germinal center formation, may be important checkpoints to regulate undesirable responses. We directly observed interactions between T and B cells responding to the self-antigen Myelin Oligodendrocyte Glycoprotein (MOG) and found that they are of lower quality compared to interactions between cells responding to the model foreign antigen NP-ovalbumin (NP-OVA). This was associated with reduced expression of molecules that facilitate these interactions on the B cells but not on T cells. B cell expression of these molecules was not dictated by the T cell partner, nor could the relative lack of expression on MOG-sp. B cells be reversed by a multivalent antigen. Instead, MOG-sp. B cells were inherently less responsive to B cell Receptor stimulation than MOG-non-sp. cells. However, the phenotype of MOG-sp. B cells was not consistent with previous descriptions of autoimmune B cells that had been tolerized via regular exposure to systemically-expressed self-antigen. This suggests that alternate anergy pathways may exist to limit B cell responses to tissue-restricted self-antigens.

immunology↗