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A Bioinformatics Model of Human Diseases on the Basis of Differentially Expressed Genes (of Domestic Versus Wild Animals) That Are Orthologs of Human Genes Associated with Reproductive-Potential Changes.

Gennady VasilievIrina ChadaevaDmitry RasskazovPetr PonomarenkoEkaterina SharypovaIrina DrachkovaAnton BogomolovLudmila SavinkovaMikhail P PonomarenkoNikolay KolchanovAlexander OsadchukDmitry OshchepkovLudmila Osadchuk
Published in: International journal of molecular sciences (2021)
Earlier, after our bioinformatic analysis of single-nucleotide polymorphisms of TATA-binding protein-binding sites within gene promoters on the human Y chromosome, we suggested that human reproductive potential diminishes during self-domestication. Here, we implemented bioinformatics models of human diseases using animal in vivo genome-wide RNA-Seq data to compare the effect of co-directed changes in the expression of orthologous genes on human reproductive potential and during the divergence of domestic and wild animals from their nearest common ancestor (NCA). For example, serotonin receptor 3A (HTR3A) deficiency contributes to sudden death in pregnancy, consistently with Htr3a underexpression in guinea pigs (Cavia porcellus) during their divergence from their NCA with cavy (C. aperea). Overall, 25 and three differentially expressed genes (hereinafter, DEGs) in domestic animals versus 11 and 17 DEGs in wild animals show the direction consistent with human orthologous gene-markers of reduced and increased reproductive potential. This indicates a reliable association between DEGs in domestic animals and human orthologous genes reducing reproductive potential (Pearson's χ2 test p < 0.001, Fisher's exact test p < 0.05, binomial distribution p < 0.0001), whereas DEGs in wild animals uniformly match human orthologous genes decreasing and increasing human reproductive potential (p > 0.1; binomial distribution), thus enforcing the norm (wild type).
Keyphrases
  • endothelial cells
  • genome wide
  • induced pluripotent stem cells
  • pluripotent stem cells
  • poor prognosis
  • copy number
  • climate change
  • deep learning
  • density functional theory