Genetic Variability of MAOA Gene among Aggressive Animals from the Non-Canonical Behavioral Model Neogale vison

Capa

Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Somente assinantes

Resumo

The MAOA gene is widely known regulator of aggressive behavior among human and animals. Here, we analyzed the genetic variability of the MAOA gene and its promoter region in non-canonical behavioral model – American mink (Neogale vison). We didn’t observe any significant genetic variations among animals with aggressive behavior, that suggests the presence of genetic and/or epigenetic variations in other systems involved in regulation of aggression in this model.

Sobre autores

A. Manakhov

Center for Genetics and Life Science, “Sirius University of Science and Technology”; Center for Genetics and Genetic Technologies, Lomonosov Moscow State University; Vavilov Institute of General Genetics, Russian Academy of Sciences

Autor responsável pela correspondência
Email: manakhov@rogaevlab.ru
Russia, 354340, Krasnodar region, pgt. Sirius; Russia, 119234, Moscow; Russia, 119991, Moscow

N. Dudko

Center for Genetics and Life Science, “Sirius University of Science and Technology”; Vavilov Institute of General Genetics, Russian Academy of Sciences

Email: rogaev@vigg.ru
Russia, 354340, Krasnodar region, pgt. Sirius; Russia, 119991, Moscow

F. Gusev

Center for Genetics and Life Science, “Sirius University of Science and Technology”; Vavilov Institute of General Genetics, Russian Academy of Sciences

Email: rogaev@vigg.ru
Russia, 354340, Krasnodar region, pgt. Sirius; Russia, 119991, Moscow

T. Andreeva

Center for Genetics and Life Science, “Sirius University of Science and Technology”; Center for Genetics and Genetic Technologies, Lomonosov Moscow State University; Vavilov Institute of General Genetics, Russian Academy of Sciences

Email: rogaev@vigg.ru
Russia, 354340, Krasnodar region, pgt. Sirius; Russia, 119234, Moscow; Russia, 119991, Moscow

O. Trapezov

Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian
Academy of Sciences; Novosibirsk State University

Email: rogaev@vigg.ru
Russia, 630090, Novosibirsk; Russia, 630039, Novosibirsk

E. Rogaev

Vavilov Institute of General Genetics, Russian Academy of Sciences; Department of Psychiatry, UMass Chan Medical School

Autor responsável pela correspondência
Email: rogaev@vigg.ru
Russia, 119991, Moscow; USA, 01545, MA, Worcester

Bibliografia

  1. Kolla N.J., Bortolato M. The role of monoamine oxidase A in the neurobiology of aggressive, antisocial, and violent behavior: A tale of mice and men // Prog. Neurobiol. 2020. V. 194. P. 101875. https://doi.org/10.1016/j.pneurobio.2020.101875
  2. Nelson R.J., Trainor B.C. Neural mechanisms of aggression // Nat. Rev. Neurosci. 2007. V. 8. № 7. P. 536–546. https://doi.org/10.1038/nrn2174
  3. Brunner H.G., Nelen M.R., van Zandvoort P. et al. X‑linked borderline mental retardation with prominent behavioral disturbance: Phenotype, genetic localization, and evidence for disturbed monoamine metabolism // Am. J. Hum. Genet. 1993. V. 52. № 6. P. 1032–1039.
  4. Brunner H.G., Nelen M., Breakefield X.O. et al. Abnormal behavior associated with a point mutation in the structural gene for monoamine oxidase A // Science. 1993. V. 262. № 5133. P. 578–580. https://doi.org/10.1126/science.8211186
  5. Cases O., Seif I., Grimsby J. et al. Aggressive behavior and altered amounts of brain serotonin and norepinephrine in mice lacking MAOA // Science. 1995. V. 268. № 5218. P. 1763–1766. https://doi.org/10.1126/science.7792602
  6. Palmer E.E., Leffler M., Rogers C. et al. New insights into Brunner syndrome and potential for targeted therapy // Clin. Genet. 2016. V. 89. № 1. P. 120–127. https://doi.org/10.1111/cge.12589
  7. Piton A., Poquet H., Redin C. et al. 20 ans après: A second mutation in MAOA identified by targeted high-throughput sequencing in a family with altered behavior and cognition // Eur. J. Hum. Genet. 2014. V. 22. № 6. P. 776–783. https://doi.org/10.1038/ejhg.2013.243
  8. Bortolato M., Godar S.C., Alzghoul L. et al. Monoamine oxidase A and A/B knockout mice display autistic-like features // Int. J. Neuropsychopharmacol. 2013. V. 16. № 4. P. 869–888. https://doi.org/10.1017/S1461145712000715
  9. Eusebi P.G., Sevane N., Cortés O. et al. Aggressive behavior in cattle is associated with a polymorphism in the MAOA gene promoter // Anim. Genet. 2020. V. 51. № 1. P. 14–21. https://doi.org/10.1111/age.12867
  10. Chen R., Chu Q., Shen C. et al. Identification of single nucleotide polymorphisms in porcine MAOA gene associated with aggressive behavior of weaned pigs after group mixing // Animals (Basel). 2019. V. 9. № 11. P. 952. https://doi.org/10.3390/ani9110952
  11. Kulikov A.V., Bazhenova E.Y., Kulikova E.A. et al. Interplay between aggression, brain monoamines and fur color mutation in the American mink // Genes, Brain and Behavior. 2016. V. 15. № 8. P. 733–740. https://doi.org/10.1111/gbb.12313
  12. Трапезов О.В. Гомологические ряды изменчивости окраски меха у американской норки (Mustela vison Schreber, 1777) в условиях доместикации // Вестник ВОГиС. 2007. Т. 11. № 3/4. C. 547–560.
  13. Manakhov A.D., Andreeva T.V., Trapezov O.V. et al. Genome analysis identifies the mutant genes for common industrial Silverblue and Hedlund white coat colours in American mink // Sci. Reports. 2019. V. 9. № 1. P. 4581. https://doi.org/10.1038/s41598-019-40918-7
  14. Manakhov A.D., Mintseva M.Y., Andreev I.A. et al. Genome analysis of American minks reveals link of mutations in Ras-related protein-38 gene to Moyle brown coat phenotype // Sci. Reports. 2020. V. 10. № 1. P. 15876. https://doi.org/10.1038/s41598-020-72239-5
  15. Manakhov A.D., Mintseva M.Y., Andreeva T.V. et al. Shadow coat colour in American mink associated with a missense mutation in the KIT gene // Animal Genetics. 2022. V. 53. № 4. P. 522–525. https://doi.org/10.1111/age.13202
  16. Li H., Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform // Bioinformatics. 2009. V. 25. № 14. P. 1754–1760. https://doi.org/10.1093/bioinformatics/btp324
  17. McKenna A., Hanna M., Banks E. et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data // Genome Research. 2010. V. 20. № 9. P. 1297–1303. https://doi.org/10.1101/gr.107524.110
  18. Purcell S., Neale B., Todd-Brown K. et al. PLINK: A tool set for whole-genome association and population-based linkage analyses // Am. J. Hum. Genetics. 2007. V. 81. № 3. P. 559–575. https://doi.org/10.1086/519795
  19. Ramírez F., Ryan D.P., Grüning B. et al. DeepTools2: A next generation web server for deep-sequencing data analysis // Nucl. Ac. Res. 2016. V. 44. № W1. P. 160–165. https://doi.org/10.1093/nar/gkw257
  20. Zhang Y., Liu T., Meyer C.A. et al. Model-based analysis of ChIP-Seq (MACS) // Genome Biol. 2008. V. 9. № 9. P. R137. https://doi.org/10.1186/gb-2008-9-9-r137
  21. Quinlan A.R., Hall I.M. BEDTools: A flexible suite of utilities for comparing genomic features // Bioinformatics (Oxford, England). 2010. V. 26. № 6. P. 841–842. https://doi.org/10.1093/bioinformatics/btq033

Arquivos suplementares

Arquivos suplementares
Ação
1. JATS XML
Baixar
2.

Baixar (225KB)
Metadados

Declaração de direitos autorais © А.Д. Манахов, Н.А. Дудко, Ф.Е. Гусев, Т.В. Андреева, О.В. Трапезов, Е.И. Рогаев, 2023

Este site utiliza cookies

Ao continuar usando nosso site, você concorda com o procedimento de cookies que mantêm o site funcionando normalmente.

Informação sobre cookies