title: Identification and analysis of the human sex-biased genes.
abstract: Tremendous differences between human sexes are universally observed. Therefore, identifying and analyzing the sex-biased genes are becoming basically important for uncovering the mystery of sex differences and personalized medicine. Here, we presented a computational method to identify sex-biased genes from public gene expression databases. We obtained 1407 female-biased genes (FGs) and 1096 male-biased genes (MGs) across 14 different tissues. Bioinformatics analysis revealed that compared with MGs, FGs have higher evolutionary rate, higher single-nucleotide polymorphism density, less homologous gene numbers and smaller phyletic age. FGs have lower expression level, higher tissue specificity and later expressed stage in body development. Moreover, FGs are highly involved in immune-related functions, whereas MGs are more enriched in metabolic process. In addition, cellular network analysis revealed that MGs have higher degree, more cellular activating signaling and tend to be located in cellular inner space, whereas FGs have lower degree, more cellular repressing signaling and tend to be located in cellular outer space. Finally, the identified sex-biased genes and the discovered biological insights together can be a valuable resource helpful for investigating sex-biased physiology and medicine, for example sex-biased disease diagnosis and therapy, which represents one important aspect of personalized and precision medicine.
authors.affiliation: Department of Biomedical Informatics, Department of Physiology and Pathophysiology, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing, China.
authors.forename: Sisi
authors.initials: S
authors.lastname: Guo
authors.affiliation: Department of Biomedical Informatics, Department of Physiology and Pathophysiology, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Department of Biomedical Informatics, Department of Physiology and Pathophysiology, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing, China.
authors.forename: Pan
authors.initials: P
authors.lastname: Zeng
authors.affiliation: Department of Biomedical Informatics, Department of Physiology and Pathophysiology, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing, China.
authors.forename: Guoheng
authors.initials: G
authors.lastname: Xu
authors.affiliation: Department of Pathogenobiology, College of Basic Medicine, Jilin University, Changchun, Jilin, China.
authors.forename: Guoqing
authors.initials: G
authors.lastname: Wang
authors.affiliation: Department of Biomedical Informatics, Department of Physiology and Pathophysiology, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, 38 Xueyuan Rd, Beijing, China.
authors.forename: Qinghua
authors.initials: Q
authors.lastname: Cui
mesh_terms: D019143:Evolution, Molecular; D005260:Female; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D050172:Genes, X-Linked; D015894:Genome, Human; D006801:Humans; D008297:Male; D009928:Organ Specificity; D012727:Sex Characteristics; D059467:Transcriptome