SELF-ORGANIZING MAPS AS TOOLS FOR UNDERSTANDING THE GENETIC VARIABILITY OF POPULATIONS
Palavras-chave:
genetic drift, selection, migration, inbreeding, SOMResumo
The maintenance of genetic diversity is fundamental to ensure the population's viability on the mid- and long-term. Because evolutionary factors (e.g., genetic drift, selection, migration, and inbreeding) can change the genetic structure of a population, it is important to understand how these factors act on populations and to infer about the maintenance of genetic diversity throughout generations. The Self-Organizing Maps (SOM) is an interesting approach to organize the genetic diversity and to highlight the effects caused by dispersive and systematic factors in populations. Briefly, the SOM algorithm maps the data, weighting similarities among inputs while keeps similar inputs close to each other in a topological map. The upside of this approach is that it organizes populations in accordance to biological principles. SOM have shown to be efficient in organizing natural or breeding populations that are subject to processes that reduce variability, such as drift, inbreeding, and selection, and to processes that increase genetic variability, such as migration.
Referências
Barbosa, C. D., Viana, A. P., Quintal, S. S. R., Pereira, M. G. (2011) Artificial neural network analysis of genetic diversity in Carica papaya L. Crop Breeding and Applied Biotechnology, 1(3), 224-231. https://doi.org/10.1590/S1984-70332011000300004
Cruz, C. D., Ferreira, F. M., Pessoni, L. A. (2020). Biometria aplicada ao estudo da diversidade genética (2nd ed.). Suprema.
Flint-Garcia, A. S, Thornsberry, J. M, Buckler, I. V. (2003). Structure of Linkage Disequilibrium in Plants. Annual Review of Plant Biology, 54(1), 357-374. https://doi.org/10.1146/annurev.arplant.54.031902.134907
Fonseca, P. G. F. (2021). Diferenciação genética em populações simuladas sob seleção divergente utilizando mapas auto-organizáveis [Completion of Course Work]. University of Minas Gerais State.
Fonseca, V. P. G., Oliveira, M. S., Cruz, C. D. (2020, October 26-27) Padrão da diversidade gerada pela seleção divergente pelos mapas auto-organizáveis de Kohonen (SOM). [Conference presentation]. XI International Symposium on Genetics and Breeding, Viçosa, UFV. https://ee111266-e722-45e5-a03b-fee372f1afb5.filesusr.com/ugd/7f9ade_c1f6b8d6dd644016829ed4619273da1f.pdf
Ibrahim, O. M., Tawfik, E. M. M., Badr, A., Wali, A. M. (2016). Evaluating the Performance of 16 Egyptian Wheat Varieties Using Self-Organizing Map (SOM) and Cluster Analysis. Journal of Applied Sciences,16(2), 47-53. https://doi.org/10.3923 / jas.2016.47.53
Kim, B. Y., Huber, C. D., Lohmueller, K. E. (2017). Inference of the distribution of selection coefficients for new nonsynonymous mutations using large samples. Genetics, 206(1), 345-361. https://doi.org/10.1534 / genetics.116.197145
Kitani, E. C. (2013). Mapeamento e visualização de dados em alta dimensão com mapas auto-organizados [Doctoral dissertation, Polytechnic School, University of São Paulo]. https://doi.org/10.11606/T.3.2013.tde-11072014-114804
Kohonen, T. (2016). Essentials of the self-organizing map. Neural Networks, 37, 52–65. https://doi.org/10.1016/j.neunet.2012.09.018
Mathieson, L, Mcvean, G. (2013). Estimating selection coefficients in spatially structured populations from time series data of allele frequencies. Genetics, 193(3), 973-984. https://doi.org/10.1534 / genética.112.147611
Moura, M. C. C. L., Azevedo, A. M., Silva, D. J. H., Cruz, C. D. (2015). Potencialidades das redes neurais artificiais na avaliação de recursos genéticos em bancos de germoplasma. Revista RG News: Sociedade Brasileira de Recursos Genéticos. 1(1), 14-19. https://doi.org/10.1590/0102-7786355000009
Nascimento, M., Nascimento, A. C. C., Cruz, C. D. (2018). SOM - Mapas Auto-Organizáveis de Kohonen, In C.D. Cruz, M. Nascimento (Eds.), Inteligência Computacional Aplicada ao Mellhoramento Genético (p. 414) Editora UFV.
Oliveira, M. S., Cruz, C. D. (2021). Genética de populações com o aplicativo GPOP. Brazil Publishing. https://doi.org/10.31012/9786550163563
Oliveira, M. S., Fonseca, V. P. G., Cruz, C. D. (2020, October 26-27). Distância Genética de Nei e Hedrick e mapa auto organizáveis de Kohonen na percepção dos efeitos da seleção divergente. [Conference presentation]. XI International Symposium on Genetics and Breeding; Viçosa: UFV; https://ee111266-e722-45e5-a03b-fee372f1afb5.filesusr.com/ugd/7f9ade_c1f6b8d6dd644016829ed4619273da1f.pdf
Oliveira, M. S., Santos, I. G., Cruz, C. D. (2020). Self-organizing maps: a powerful tool for capturing genetic diversity patterns of populations. Euphytica, 216(3), 1–9. https://doi.org/10.1007/S10681-020-2569-0
Peña-Malavera, A., BRUNO, C., FERNANDEZ, E., BALZARINI, M. (2014). Comparison of algorithms to infer genetic population structure from unlinked molecular markers. Statistical applications in genetics and molecular biology, 13(4), 39-402. https://doi.org/10.1515 / sagmb-2013-0006
Perez, C. C. M. (2008). Measures of genetic differentiation in simulate populations under inbreeding and divergent selection [Mester dissertation, Viçosa Federal University]. http://locus.ufv.br/handle/123456789/2371
Santos, I. G., Carneiro, V. Q., Silva Júnior, A. C., Cruz, C. D. (2019). Self-organizing maps in the study of genetic diversity among irrigated rice genotypes. Acta Sci., 41, e39803. https://doi.org/10.4025/actasciagron.v41i1.39803
Santos, I. G., Rocha, J. R. A. S. C., Vigna, B. B. Z., Cruz, C. D., Ferreira, R. P., Basigalup, D. H., Marchini, R. M. S. (2020). Exploring the diversity of alfalfa within Brazil for tropical production. Euphytica, 216(5), 1–15. https://doi.org/10.1007/S10681-020-02606-W
Silva, M. J., Silva Júnior, A. C. S., Cruz, C. D., Nascimento, M., Oliveira, M. S., Schaffert, R. E., Parrella, R. A. C. (2020). Computational intelligence for studies on genetic diversity between genotypes of biomass sorghum. Pesq. agropec. bras., 55, e01723, https://doi.org/10.1590/S1678-3921.pab2020.v55.01723
Spanoghe M. C., Marique T., Rivière J., Moulin M., Dekuijper C., Nirsha A., Bonnave M., Lanterbecq D. (2020). Genetic patterns recognition in crop species using self-organizing map: the example of the highly heterozygous autotetraploid potato (Solanum tuberosum L.). Genetic Resources of Crop Evolution, 67, 947–966. https://doi.org/10.1007/s10722-020-00894-8.
Vidon, L. R, Pigaiani, M. E. F, Oliveira, M. S. (2021, November 24-26). Mapas auto-organizáveis na percepção da Diferenciação genética causada por migração. [Conference presentation]. 23ª Seminário de Pesquisa e Extensão of the University of Minas Gerais State, Carangola: UEMG.
