Comprehensive identification of sexually dimorphic genes in diverse cattle tissues using RNA-seq. (December 2016)

• Record Type: Journal Article
• Authors: Seo, Minseok; Caetano-Anolles, Kelsey; Rodriguez-Zas, Sandra; Ka, Sojeong; Jeong, Jin; Park, Sungkwon; Kim, Min; Nho, Whan-Gook; Cho, Seoae; Kim, Heebal; Lee, Hyun-Jeong
• Is Part Of: BMC genomics. Volume 17:Number 1(2016)
• Page Start: 1
• Page End: 18
• Publication Date: 2016-12
• Subjects: RNA-seq -- Sexual dimorphism -- Tissue-specific gene expression -- ANODEV; Genomes -- Periodicals; Gene mapping -- Periodicals; Genomics -- Periodicals; Base Sequence -- Periodicals; Chromosome Mapping -- Periodicals; Genetic Techniques -- Periodicals; Sequence Analysis, DNA -- Periodicals; 572.8605
• DOI: 10.1186/s12864-016-2400-4
• Languages: English
• ISSNs: 1471-2164

Abstract

Abstract Background Molecular mechanisms associated with sexual dimorphism in cattle have not been well elucidated. Furthermore, as recent studies have implied that gene expression patterns are highly tissue specific, it is essential to investigate gene expression in a variety of tissues using RNA-seq. Here, we employed and compared two statistical methods, a simple two group test and Analysis of deviance (ANODEV), in order to investigate bovine sexually dimorphic genes in 40 RNA-seq samples distributed across two factors: sex and tissue. Results As a result, we detected 752 sexually dimorphic genes across tissues from two statistical approaches and identified strong tissue-specific patterns of gene expression. Additionally, significantly detected sex-related genes shared between two mammal species (cattle and rat) were identified using qRT-PCR. Conclusions Results of our analyses reveal that sexual dimorphism of metabolic tissues and pituitary gland in cattle involves various biological processes. Several differentially expressed genes between sexes in cattle and rat species are shared, but show tissue-specific patterns. Finally, we concluded that two distinct statistical approaches have their advantages and disadvantages in RNA-seq studies investigating multiple tissues.