The ongoing spread of highly pathogenic avian influenza (HPAI) H5N1 across a growing range of mammalian hosts emphasizes the urgent need for high-quality genomic data. This study presents a comprehensive quality control (QC) analysis of over 3,000 H5N1 genome assemblies collected from diverse host organisms across the United States, with a particular focus on cattle, poultry, and domestic animals. Leveraging a cloud-based computational pipeline from HIVE, sequence data were evaluated using standardized QC metrics, including GC content and Phred quality scores, to assess data integrity and identify potential sources of sequencing error or contamination. Regional differences in sequencing quality, such as elevated GC content and variable Phred scores in samples from California cattle, highlight inconsistencies in upstream sample handling and laboratory protocols. In addition to QC assessments, Sankey diagrams were used to visualize potential clonal diversity and segment-specific alignment across nearest neighbor pipeline-determined reference genomes. The results of this work provide a method to evaluate H5N1 sequences and address current gaps in influenza genomic data. These findings contribute to enhanced biosurveillance capacity and potential diagnostic uses and offer a scalable framework for evaluating future zoonotic threats.

Author

• Woodside, Christie Rose

Language

• en

Keyword

• Surveillance
• Quality Control
• Highly Pathogenic Avian Influenza
• Zoonotic disease outbreaks
• Zoonotic Pathogens
• Influenza A virus

Date created

• 2025

Type of Work

• Master's Thesis

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Bioinformatics and Molecular Biochemistry

Degree

• M.S.

Advisor

• Simonyan, Vahan
• Mazumder, Raja

Committee Member(s)

• Simonyan, Vahan
• Mazumder, Raja

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/6q182k87k