As part of the Pacific Northwest National Laboratory’s (PNNL) Science Focus Area program, we are investigating the impact of environmental change on microbial community function in grassland soils. Three grassland soils, representing different moisture regimes, were selected for ultra-deep...
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"DNA Viral Diversity, Abundance, and Functional Potential Vary across Grassland Soils with a Range of Historical Moisture Regimes" Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the...
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Publication
A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery...
The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...
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The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...
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Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...
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Dataset
Please cite as : Anderson L.N., W.C. Nelson, J.E. McDermott, R. Wu, S.J. Fansler, Y. Farris, and J.K. Jansson, et al. 2020. IA-TmG.1.0 (Metagenome, IA). [Data Set] PNNL DataHub. https://doi.org/10.25584/IATmG1/1635005 To enable a comprehensive survey of the metabolic potential of complex soil...
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Dataset
Please cite as : Anderson L.N., W.C. Nelson, J.E. McDermott, R. Wu, S.J. Fansler, Y. Farris, and J.K. Jansson, et al. 2020. KS-TmG.1.0 (Metagenome, KS). [Data Set] PNNL DataHub. https://doi.org/10.25584/KSTmG1/1635004 To enable a comprehensive survey of the metabolic potential of complex soil...
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Dataset
Please cite as : Anderson L.N., W.C. Nelson, J.E. McDermott, R. Wu, S.J. Fansler, Y. Farris, and J.K. Jansson, et al. 2020. WA-TmG.1.0 (Metagenome, WA). [Data Set] PNNL DataHub. https://doi.org/10.25584/WATmG1/1635002 To enable a comprehensive survey of the metabolic potential of complex soil...
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Dataset
Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. WA-TmG.2.0 (Metagenome, WA). [Data Set] PNNL DataHub. https://doi.org/10.25584/WATmG2/1770324 Soil samples were collected in triplicate in the fall of 2017 across the three grassland...
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Dataset
Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. KS-TmG.2.0 (Metagenome, KS). [Data Set] PNNL DataHub. https://doi.org/10.25584/KSTmG2/1770332 Soil samples were collected in triplicate in the fall of 2017 across the three grassland locations...
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Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. Iso-VIG14.1.0 (Metagenome Derived Viral Genomes, WA/IA/KS). [Data Set] PNNL DataHub. https://doi.org/10.25584/IsoVIG14/1770369 Soil samples were collected in triplicate in the Fall of 2017...
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Dataset
Please cite as : Anderson L.N., R. Wu, W.C. Nelson, J.E. McDermott, K.S. Hofmockel, and J.K. Jansson. 2021. IA-TmG.2.0 (Metagenome, IA). [Data Set] PNNL DataHub. https://doi.org/10.25584/IATmG2/1770333 Soil samples were collected in triplicate in the fall of 2017 across the three grassland locations...
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Inclusion levels of alternative splicing (AS) events of five different varieties (i.e. skipped exon (SE), retained intron (RI), alternative 5’ splice site (A5SS), alternative 3’ splice site (A3SS), and mutually exclusive exons (MXE)) were measured in human blood samples from two separate cohorts of...
Comprised of 6,426 sample runs, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics studies in the literature to date. Making quality control (QC) and donor sample data available to researchers aligns with...
