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College of Arts & Sciences
Department of Biological Sciences

Graduate student Weier Bao authors paper in "Functional & Integrative Genomics"

PhD Candidate Weier Bao, a student in Prof. Roger Sawyer's lab, is lead author of a manuscript in the journal Functional & Integrative Genomics.  The manuscript, "Using scale and feather traits for module construction provides a functional approach to chicken epidermal development," describes use of the Weighted Gene Co-expression Network Analysis approach to explore correlation between gene expression and development traits in the scales and feathers of chicken during epidermal embryogenesis.  The abstract of the manuscript appears below, and the manuscript can be viewed at Functional & Integrative Genomics.

"Using scale and feather traits for module construction provides a functional approach to chicken epidermal development"

Authors: Weier Bao, Matthew J. Greenwold, and Roger H. Sawyer

Abstract: Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified 2 distinct modules that are highly correlated with scale or feather development traits.  Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale and feather trait related modules.