@article{OmolaoyeOmolaoyeKandasamyetal.2022,
  author    = {Omolaoye, Temidayo S. and Omolaoye, Victor Adelakun and Kandasamy, Richard K. and Hachim, Mahmood Yaseen and Du Plessis, Stefan S.},
  title     = {Omics and male infertility},
  series = {Life : open access journal},
  volume    = {12},
  journal   = {Life : open access journal},
  number    = {2},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2075-1729},
  doi       = {10.3390/life12020280},
  pages     = {21},
  year      = {2022},
  abstract  = {Male infertility is a multifaceted disorder affecting approximately 50\% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30\% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (LDHC, PDHA2, TNP1, TNP2, ODF1, ODF2, SPINK2, PCDHB3) were commonly differentially expressed between all disease groups. Likewise, 56 genes were common between NOA versus NOA and OA (ADAD1, BANF2, BCL2L14, C12orf50, C20orf173, C22orf23, C6orf99, C9orf131, C9orf24, CABS1, CAPZA3, CCDC187, CCDC54, CDKN3, CEP170, CFAP206, CRISP2, CT83, CXorf65, FAM209A, FAM71F1, FAM81B, GALNTL5, GTSF1, H1FNT, HEMGN, HMGB4, KIF2B, LDHC, LOC441601, LYZL2, ODF1, ODF2, PCDHB3, PDHA2, PGK2, PIH1D2, PLCZ1, PROCA1, RIMBP3, ROPN1L, SHCBP1L, SMCP, SPATA16, SPATA19, SPINK2, TEX33, TKTL2, TMCO2, TMCO5A, TNP1, TNP2, TSPAN16, TSSK1B, TTLL2, UBQLN3). These genes, particularly the above-mentioned 8 genes, are involved in diverse biological processes such as germ cell development, spermatid development, spermatid differentiation, regulation of proteolysis, spermatogenesis and metabolic processes. Owing to the stage-specific expression of these genes, any mal-expression can ultimately lead to male infertility. Therefore, currently available data on all branches of omics relating to male fertility can be used to identify biomarkers for diagnosing male infertility, which can potentially help in unravelling some idiopathic cases.},
  language  = {en}
}
@article{WestburyHartmannBarlowetal.2018,
  author    = {Westbury, Michael V. and Hartmann, Stefanie and Barlow, Axel and Wiesel, Ingrid and Leo, Viyanna and Welch, Rebecca and Parker, Daniel M. and Sicks, Florian and Ludwig, Arne and Dalen, Love and Hofreiter, Michael},
  title     = {Extended and continuous decline in effective population size results in low genomic diversity in the world's rarest hyena species, the brown hyena},
  series = {Molecular biology and evolution},
  volume    = {35},
  journal   = {Molecular biology and evolution},
  number    = {5},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0737-4038},
  doi       = {10.1093/molbev/msy037},
  pages     = {1225 -- 1237},
  year      = {2018},
  abstract  = {Hyenas (family Hyaenidae), as the sister group to cats (family Felidae), represent a deeply diverging branch within the cat-like carnivores (Feliformia). With an estimated population size of <10,000 individuals worldwide, the brown hyena (Parahyaena brunnea) represents the rarest of the four extant hyena species and has been listed as Near Threatened by the IUCN. Here, we report a high-coverage genome from a captive bred brown hyena and both mitochondrial and low-coverage nuclear genomes of 14 wild-caught brown hyena individuals from across southern Africa. We find that brown hyena harbor extremely low genetic diversity on both the mitochondrial and nuclear level, most likely resulting from a continuous and ongoing decline in effective population size that started similar to 1 Ma and dramatically accelerated towards the end of the Pleistocene. Despite the strikingly low genetic diversity, we find no evidence of inbreeding within the captive bred individual and reveal phylogeographic structure, suggesting the existence of several potential subpopulations within the species.},
  language  = {en}
}