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Computational Prediction of Alzheimer's and Parkinson's Disease MicroRNAs in Domestic Animals

  • Wang, Hai Yang ;
  • Lin, Zi Li ;
  • Yu, Xian Feng ;
  • Bao, Yuan ;
  • Cui, Xiang-Shun ;
  • Kim, Nam-Hyung
  • Received : 2015.05.08
  • Accepted : 2015.08.14
  • Published : 2016.06.01

Abstract

As the most common neurodegenerative diseases, Alzheimer's disease (AD) and Parkinson's disease (PD) are two of the main health concerns for the elderly population. Recently, microRNAs (miRNAs) have been used as biomarkers of infectious, genetic, and metabolic diseases in humans but they have not been well studied in domestic animals. Here we describe a computational biology study in which human AD- and PD-associated miRNAs (ADM and PDM) were utilized to predict orthologous miRNAs in the following domestic animal species: dog, cow, pig, horse, and chicken. In this study, a total of 121 and 70 published human ADM and PDM were identified, respectively. Thirty-seven miRNAs were co-regulated in AD and PD. We identified a total of 105 unrepeated human ADM and PDM that had at least one 100% identical animal homolog, among which 81 and 54 showed 100% sequence identity with 241 and 161 domestic animal miRNAs, respectively. Over 20% of the total mature horse miRNAs (92) showed perfect matches to AD/PD-associated miRNAs. Pigs, dogs, and cows have similar numbers of AD/PD-associated miRNAs (63, 62, and 59). Chickens had the least number of perfect matches (34). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses suggested that humans and dogs are relatively similar in the functional pathways of the five selected highly conserved miRNAs. Taken together, our study provides the first evidence for better understanding the miRNA-AD/PD associations in domestic animals, and provides guidance to generate domestic animal models of AD/PD to replace the current rodent models.

Keywords

Alzheimer's Disease;Parkinson's Disease;microRNA;Domestic Animals;Homology

References

  1. Adams, B., A. Chan, H. Callahan, C. Siwak, D. Tapp, C. Ikeda- Douglas, P. Atkinson, E. Head, C. W. Cotman, and N. W. Milgram. 2000. Use of a delayed non-matching to position task to model age-dependent cognitive decline in the dog. Behav. Brain Res. 108:47-56. https://doi.org/10.1016/S0166-4328(99)00132-1
  2. Chang, S. H., I. S. Jung, G. Y. Han, N. H. Kim, H. J. Kim, and C. W. Kim. 2013. Proteomic profiling of brain cortex tissues in a Tau transgenic mouse model of Alzheimer's disease. Biochem. Biophys. Res. Commun. 430:670-675. https://doi.org/10.1016/j.bbrc.2012.11.093
  3. Chatterjee, P., M. Bhattacharyya, S. Bandyopadhyay, and D. Roy. 2014. Studying the system-level involvement of microRNAs in Parkinson's disease. PLoS One 9:e93751. https://doi.org/10.1371/journal.pone.0093751
  4. Cho, H. J., G. Liu, S. M. Jin, L. Parisiadou, C. Xie, J. Yu, L. Sun, B. Ma, J. Ding, R. Vancraenenbroeck, E. Lobbestael, V. Baekelandt, J. M. Taymans, P. He, T. C. Troncoso, Y. Shen, and H. Cai. 2013. MicroRNA-205 regulates the expression of Parkinson's disease-related leucine-rich repeat kinase 2 protein. Hum. Mol. Genet. 22:608-620. https://doi.org/10.1093/hmg/dds470
  5. Cummings, J. L., H. V. Vinters, G. M. Cole, and Z. S. Khachaturian. 1998. Alzheimer's disease: etiologies, pathophysiology, cognitive reserve, and treatment opportunities. Neurology 51:S2-17; discussion S65-7.
  6. Groenen, M. A., A. L. Archibald, H. Uenishi, C. K. Tuggle, Y. Takeuchi, M. F. Rothschild, C. Rogel-Gaillard, C. Park, D. Milan, and H. J. Megens et al. 2012. Analyses of pig genomes provide insight into porcine demography and evolution. Nature 491:393-398. https://doi.org/10.1038/nature11622
  7. Head, E. 2007. Combining an antioxidant-fortified diet with behavioral enrichment leads to cognitive improvement and reduced brain pathology in aging canines: strategies for healthy aging. Ann. NY Acad. Sci. 1114:398-406. https://doi.org/10.1196/annals.1396.004
  8. Head, E. and R. Torp. 2002. Insights into Abeta and presenilin from a canine model of human brain aging. Neurobiol. Dis. 9:1-10. https://doi.org/10.1006/nbdi.2002.0476
  9. Johnstone, E. M., M. O. Chaney, F. H. Norris, R. Pascual, and S. P. Little. 1991. Conservation of the sequence of the Alzheimer's disease amyloid peptide in dog, polar bear and five other mammals by cross-species polymerase chain reaction analysis. Mol. Brain Res. 10:299-305. https://doi.org/10.1016/0169-328X(91)90088-F
  10. Kragh, P. M., A. L. Nielsen, J. Li, Y. Du, L. Lin, M. Schmidt, I. B. Bogh, I. E. Holm, J. E. Jakobsen, M. G. Johansen, S. Purup, L. Bolund, G. Vajta, and A. L. Jorgensen. 2009. Hemizygous minipigs produced by random gene insertion and handmade cloning express the Alzheimer's disease-causing dominant mutation APPsw. Transgenic Res. 18:545-558. https://doi.org/10.1007/s11248-009-9245-4
  11. Li, J., Z. Wu, F. Cheng, W. Li, G. Liu, and Y. Tang. 2014. Computational prediction of microRNA networks incorporating environmental toxicity and disease etiology. Sci. Rep. 4:5576.
  12. Lukiw, W. J. 2007. Micro-RNA speciation in fetal, adult and Alzheimer's disease hippocampus. Neuroreport 18:297-300. https://doi.org/10.1097/WNR.0b013e3280148e8b
  13. Maciotta, S., M. Meregalli, and Y. Torrente. 2013. The involvement of microRNAs in neurodegenerative diseases. Front Cell Neurosci. 7:265.
  14. Mattson, M. P. 2000. Apoptosis in neurodegenerative disorders. Nat. Rev. Mol. Cell Biol. 1:120-130. https://doi.org/10.1038/35040009
  15. Mouradian, M. M. 2012. MicroRNAs in Parkinson's disease. Neurobiol. Dis. 46:279-284. https://doi.org/10.1016/j.nbd.2011.12.046
  16. Muller, M., H. B. Kuiperij, J. A. Claassen, B. Kusters, and M. M. Verbeek. 2014. MicroRNAs in Alzheimer's disease: differential expression in hippocampus and cell-free cerebrospinal fluid. Neurobiol. Aging 35:152-158. https://doi.org/10.1016/j.neurobiolaging.2013.07.005
  17. Peterson, K. J., M. R. Dietrich, and M. A. McPeek. 2009. MicroRNAs and metazoan macroevolution: insights into canalization, complexity, and the Cambrian explosion. Bioessays 31:736-747. https://doi.org/10.1002/bies.200900033
  18. Ramanan, V. K. and A. J. Saykin. 2013. Pathways to neurodegeneration: mechanistic insights from GWAS in Alzheimer's disease, Parkinson's disease, and related disorders. Am. J. Neurodegener. Dis. 2:145-175.
  19. Sarasa, M. and P. Pesini. 2009. Natural non-trasgenic animal models for research in Alzheimer's disease. Curr. Alzheimer Res. 6:171-178. https://doi.org/10.2174/156720509787602834
  20. Shannon, P., A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13:2498-2504. https://doi.org/10.1101/gr.1239303
  21. Shtilbans, A. and C. Henchcliffe. 2012. Biomarkers in Parkinson's disease: An update. Curr. Opin Neurol. 25:460-465. https://doi.org/10.1097/WCO.0b013e3283550c0d
  22. Studzinski, C. M., L. A. Christie, J. A. Araujo, W. M. Burnham, E. Head, C. W. Cotman, and N. W. Milgram. 2006. Visuospatial function in the beagle dog: An early marker of cognitive decline in a model of human aging and dementia. Neurobiol. Learn. Mem. 86:197-204. https://doi.org/10.1016/j.nlm.2006.02.005
  23. Sutherland, G. T., N. A. Matigian, A. M. Chalk, M. J. Anderson, P. A. Silburn, A. Mackay-Sim, C. A. Wells, and G. D. Mellick. 2009. A cross-study transcriptional analysis of Parkinson's disease. PLoS One 4:e4955. https://doi.org/10.1371/journal.pone.0004955
  24. Tan, C. L., J. L. Plotkin, M. T. Veno, M. von Schimmelmann, P. Feinberg, S. Mann, A. Handler, J. Kjems, D. J. Surmeier, D. O'Carroll, P. Greengard, and A. Schaefer. 2013. MicroRNA- 128 governs neuronal excitability and motor behavior in mice. Science 342:1254-1258. https://doi.org/10.1126/science.1244193
  25. Tiribuzi, R., L. Crispoltoni, S. Porcellati, M. Di Lullo, F. Florenzano, M. Pirro, F. Bagaglia, T. Kawarai, M. Zampolini, A. Orlacchio, and A. Orlacchio. 2014. miR128 up-regulation correlates with impaired amyloid beta(1-42) degradation in monocytes from patients with sporadic Alzheimer's disease. Neurobiol. Aging 35:345-56. https://doi.org/10.1016/j.neurobiolaging.2013.08.003
  26. Vasudevan, S., Y. Tong, and J. A. Steitz. 2007. Switching from repression to activation: microRNAs can up-regulate translation. Science 318:1931-1934. https://doi.org/10.1126/science.1149460
  27. Villa, C., E. Ridolfi, C. Fenoglio, L. Ghezzi, R. Vimercati, F. Clerici, A. Marcone, S. Gallone, M. Serpente, C. Cantoni, R. Bonsi, S. Cioffi, S. Cappa, M. Franceschi, I. Rainero, C. Mariani, E. Scarpini, and D. Galimberti. 2013. Expression of the transcription factor Sp1 and its regulatory hsa-miR-29b in peripheral blood mononuclear cells from patients with Alzheimer's disease. J. Alzheimers Dis. 35:487-494. https://doi.org/10.3233/JAD-122263
  28. Wang, H., S. Xiao, M. Wang, N. H. Kim, H. Li, and G. Wang. 2015. In silico identification of conserved microRNAs and their targets in bovine fat tissue. Gene 559:119-128. https://doi.org/10.1016/j.gene.2015.01.021
  29. Wang, H., Y. Zheng, G. Wang, and H. Li. 2013. Identification of microRNA and bioinformatics target gene analysis in beef cattle intramuscular fat and subcutaneous fat. Mol. Biosyst. 9: 2154-2162. https://doi.org/10.1039/c3mb70084d

Acknowledgement

Supported by : Rural Development Administration (RDA), Chubgbuk National University