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

• Published in: Functional & integrative genomics Vol. 17; no. 6; pp. 641 - 651
• Main Authors: Bao, Weier, Greenwold, Matthew J., Sawyer, Roger H.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2017; Springer Nature B.V
• Subjects: Animal Genetics and Genomics; Animal Scales - growth & development; Animal Scales - metabolism; Animals; Avian Proteins - genetics; Avian Proteins - metabolism; Biochemistry; Bioinformatics; Biomedical and Life Sciences; Cell Biology; chickens; Chickens - genetics; DNA microarrays; Embryogenesis; Epidermis - growth & development; Epidermis - metabolism; feathers; Feathers - growth & development; Feathers - metabolism; Gene expression; gene ontology; Genes; Life Sciences; Medical Subject Headings-MeSH; microarray technology; Microbial Genetics and Genomics; microRNA; Original Article; Plant Genetics and Genomics; Poultry; prediction; Quantitative Trait, Heritable; Regulatory sequences; signal transduction; transcription (genetics); Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; Transcriptome; Epidermal development; Enrichment analysis; Microarray; Co-expression network
• ISSN: 1438-793X; 1438-7948; 1438-7948
• DOI: 10.1007/s10142-017-0561-0

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 two 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.