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Waters, Katrina M

Publications and source records attributed to Waters, Katrina M.

Human Liver Epithelial Cells (HuH7) Response to HCoV-229E Infection Epigenomics (ATAC-Seq) (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-299E) infection alters chromatin accessibility in infected cells. Sample data was obtained from mock-infected cells, UV-inactivated virus treated cells, and replication competent HCoV-229E infected immortalized human liver cells (HuH7) at 24 hours post infection. Samples were processed using ATAC-seq methods for reported bar coded libraries. Sample data was acquired using an Illumina Hi-Seq 2500 sequencer system and further processed for ATAC-Seq expression analysis.

59 BASIC BIOLOGICAL SCIENCES

Human Liver Epithelium Response to HCoV-229E Infection Epigenomics (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-229E) infection alters chromatin accessibility in infected cells only. Sample data was obtained for mock and infected (standard and UV-inactivated) immortalized human liver cells (HuH-7) and collected 24 hrs. post infection. Samples were processed using assay for transposase-accessible chromatin using high-throughput sequencing (ATAC-Seq) and generated bar coded library samples were evaluated for RNA sequencing (RNA-Seq) expression analysis. Processed ATAC-Seq datasets are openly accessible from the download button and contain secondary processed RNA-Seq results files and supporting metadata materials. Data download includes a sample naming key, infection titer metadata, normalized counts, and relevant computational source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES

Predictive Phenomics Initiative Project Dataset Catalog Collection

The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.

59 BASIC BIOLOGICAL SCIENCES

Predictive Phenomics Initiative Project Dataset Catalog Collection

The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.

59 BASIC BIOLOGICAL SCIENCES