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Comprehensive identification of sexually dimorphic genes in diverse cattle tissues using RNA-seq

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...

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Detalles Bibliográficos
Autores principales: Seo, Minseok, Caetano-Anolles, Kelsey, Rodriguez-Zas, Sandra, Ka, Sojeong, Jeong, Jin Young, Park, Sungkwon, Kim, Min Ji, Nho, Whan-Gook, Cho, Seoae, Kim, Heebal, Lee, Hyun-Jeong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4728830/
https://www.ncbi.nlm.nih.gov/pubmed/26818975
http://dx.doi.org/10.1186/s12864-016-2400-4
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2400-4) contains supplementary material, which is available to authorized users.