Biology subjects

Nordgren, E.

Publications and source records attributed to Nordgren, E..

2 recordsLinked to original sources

bioRxiv2026

The HuBMAP Framework for Advancing Data FAIRness

Since publication of the FAIR Guiding Principles in 2016, the scientific community has increasingly sought to make experimental data findable, accessible, interoperable, and reusable. Operationalizing the FAIR principles in routine scientific workflows remains challenging without a standardized, workable infrastructure. With over 10,000 datasets from over 40 institutions, spanning more than 50 diverse assay types ranging from single-cell sequencing technologies to 2D and 3D spatial omics, the U.S. National Institutes of Health (NIH) Human Bio-Molecular Atlas Program (HuBMAP) consortium has been ideally situated to create a FAIR ecosystem. With the goal of achieving data "FAIRness," HuBMAP developed and implemented well-defined, community-endorsed metadata reporting standards across the research lifecycle. These reporting standards include detailed schemas, harmonized across a multitude of assays, that define the metadata associated with a dataset and the organization of the corresponding data files. These standards ensure documentation of the data collection process, of the data themselves, and of the manner in which the data are packaged for sharing, while remaining compliant with the Health Insurance Portability and Accountability Act (HIPAA). The use of these reporting standards, in tandem with technology to foster adherence, allows HuBMAP to fulfill its goal of generating FAIR data for open dissemination through its Data Portal and Human Reference Atlas. The procedures and simple workflow adopted by HuBMAP investigators serve as a model for other scientific communities aiming to maximize the value of varied datasets addressing a shared research question. The HuBMAP end-to-end, metadata-centered workflow has been replicated and enhanced by the NIH Cellular Senescence Network (SenNet) consortium and is readily available through open-source technology for others to utilize.

cell biology↗

bioRxiv2024

Single-Mitochondrion Sequencing Uncovers Distinct Mutational Patterns and Heteroplasmy Landscape in Mouse Astrocytes and Neurons.

BackgroundMitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting normal mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes In this study we amplified mt-genomes from 1,645 single mitochondria (mts) isolated from mouse single astrocytes and neurons to 1. determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, 2. assess differences in mtDNA SNVs between neurons and astrocytes, and 3. Study cosegregation of variants in the mouse mtDNA. Results1. The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. 2. Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G>A and 9419:C>T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. 3. Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. f ConclusionThis study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

neuroscience↗