Parental selection based on molecular information under a population genetics approach

  • Renato Domiciano Silva Rosado Universidade Federal de Viçosa, Departamento de Estatística https://orcid.org/0000-0002-8157-9581
  • Ana Maria Cruz Oliveira Universidade Federal de Viçosa, Departamento de Biologia Geral
  • Iara Gonçalves Santos Universidade Federal de Viçosa, Departamento de Biologia Geral
  • Pedro Crescêncio Souza Carneiro Universidade Federal de Viçosa, Departamento de Biologia Geral
  • Cosme Damião Cruz Universidade Federal de Viçosa, Departamento de Estatística
  • Paulo Roberto Cecon Universidade Federal de Viçosa, Departamento de Estatística https://orcid.org/0000-0001-8213-0199
Keywords: Genetic diversity, quantitative genetic, biometric genetic, biometrical techniques, germplasm, molecular data

Abstract

The correct choice of parents that will compose optimal segregating populations is the key to success for breeding programs. It was postulated the hypothesis that this choice of these parents could be made based on information of molecular markers analyzed in the context of population structure. Ten parental populations were simulated and 45 hybrid combinations were obtained from the dialel crosses. Each population consisted of 200 individuals with 50 independent loci. The populations were evaluated for the Hardy-Weinberg Equilibrium (HWE), Coefficient of Inbreeding (F), Heterozygosity (H), and the Polymorphic Information Content (PIC). Genetic diversity between pairs of parental populations was evaluated using five dissimilarity measures. Values of Mantel correlation were obtained for the pairs of the dissimilarity matrices, and the PIC, H, and F values �??�??were obtained in the hybrid combinations. All parental populations were under HWE, and the combination that emerged from this condition was the hybrid 3x5, with only 26% of the loci manifesting HWE. This same hybrid was among those with lower F estimates and higher values �??�??of H, which indicated the existence of greater divergence between their parentals. There was agreement on the indication of the more and less divergent hybrid combinations for the dissimilarity measures. This fact is important because the variability, associated with the good average potential, are important criteria for the formation of an initial population in breeding programs of any kind, involving sexual processes.

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References

Annicchiarico, P., Nazzicari, N., Carelli, M., Wei, Y., & Brummer, E.C. (2016) Assessment of cultivar distinctness in alfalfa: A comparison of genotyping-by-sequencing, simple-sequence repeat marker, and morphophysiological observations. The Plant Genome, 9, 1-12. https://doi.org/10.3835/plantgenome2015.10.0105

Bertan, I., Carvalho, F. I. F., & Oliveira, A. C. (2007) Parental selection strategies in plant breeding programs. Journal of Crop Science and Biotechnology, 10, 211�??222.

Botstein, D., R. L., Skolnick, M., & Davis, R. W. (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics, 32, 314-331.

Carovi�?-Stanko, K., Liber, Z., Vidak, M., Baresic, A., Grdisa, M., Lazarevi�?, B., & Satovi�?, Z. (2017) Genetic Diversity of Croatian Common Bean Landraces. Frontiers on Plant Science, 8,1-8. https://doi.org/10.3389/fpls.2017.00604

Crispim, B. A., Silva, D. B. S., Banari, A. C. B., Seno, L. O., & Grisolia, A. B. (2012) Discriminação alélica em ovinos naturalizados do Pantanal Sul-Matogrossense por meio de marcadores microssatélites. Journal of the Selva Andina Research Society, 3, 3-13.

Cruz, C. D. (2006) Programa Genes - Análise Multivariada e simulação. Viçosa, MG: Editora UFV.

Cruz, C. D., Ferreira, F. M., & Pessoni, L. A. (2011) Biometria aplicada ao estudo da diversidade genética. Visconde do Rio Branco, MG: Editora Suprema.

Cruz, C. D. (2013) GENES: a software package for analysis in experimental statistics and quantitative genetics. Acta Scientiarum Agronomy, 35, 271-276. https://doi.org/10.4025/actasciagron.v35i3.21251

Cruz, C.D. (2016) Genes Software �?? extended and integrated with the R, Matlab and Selegen. Acta Scientiarum Agronomy, 38:547-552. https://doi.org/10.4025/actasciagron.v38i4.32629

Cruz, C. D., Carneiro, P. C. S., & Regazzi, A. J. (2014) Modelos Biométricos Aplicados ao Melhoramento Genético. (3rd ed.). Viçosa, MG: Editora UFV.

Ferreira, C. B. B., Lopes, M. T. G., Lopes, R., Cunha, R. N. V., Moreira, D. A. M., Barros, W. S., & Matiello, R. R. (2012) Diversidade genética molecular de progênies de dendezeiro. Pesquisa Agropecuária Brasileira, 47, 378-384. https://doi.org/10.1590/S0100-204X2012000300009

Garner, B. A., Hand, B. K., Amish, S. J., Bernatchez, L., Foster, J. T., Miller, K. M., Morin, P. A., Narum, S. R., O�??brien, S. J., Roffler, G., Templin, W. D., Sunnucks, P., Strait, J., Warheit, K. I., Seamons, T.R., Wenburg, J., Olsen, J., & Luikart, G. (2016) Genomics in conservation: Case studies and bridging the gap between data and application. Trends in Ecology and Evolution, 31, 81�??83. http://dx.doi.org/10.1016/j.tree.2015.10.009

Hedrick, P. W. (1971) A new approach to measuring genetic similarity. Evolution, 25:276-280. https://doi.org/10.2307/2406918

Hiremath, G., & Nagaraja, T. E. (2016) Genetic variability and heritability analysis in selected clones of sugarcane. International Journal of Science Technology & Engineering, 2, 341-343.

Mayo, O. (2008) A century of Hardy�??Weinberg equilibrium. Twin Research and Human Genetics, 11, 249-256. 10.1375/twin.11.3.249. https://doi.org/10.1375/twin.11.3.249

Meirmans, P. G. (2015) Seven common mistakes in population genetics and how to avoid them. Molecular Ecology, 24, 3223-3231. https://doi.org/10.1111/mec.13243

Milligan, B. G., Archer, F. I., Ferchaud, A. L., Hand, B. K., Kierepka, E. M., & Waples, R. S. (2018) Disentangling genetic structure for genetic monitoring of complex populations. Evolutionary Applications, 11, 1149-1161. https://doi.org/10.1111/eva.12622

Mohammadi, S. A., & Prasanna, B. M. (2003). Analysis of genetic diversity in crop plants�??salient statistical tools and considerations. Crop science, 43(4), 1235-1248.

https://doi.org/10.2135/cropsci2003.1235

Narum, S.R., Buerkle, C. A., Davey, J. W., Miller, M. R., & Hohenlohe, P. A. (2013) Genotyping�?�by�?�sequencing in ecological and conservation genomics. Molecular Ecology, 22, 2841-2847. https://doi.org/10.1111/mec.12350

Nei, M. (1973) Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences of USA, 70, 3321-3323. https://doi.org/10.1073/pnas.70.12.3321

Pereira, H.S., Santos, J. B., Abreu, A. F. B., & Couto, K. R. (2007) Informações fenotípicas e marcadores microssatélites de QTL na escolha de populações segregantes de feijoeiro. Pesquisa Agropecuária Brasileira, 42, 707-713. https://doi.org/10.1590/S0100-204X2007000500014

Pimentel, A. J. B., Ribeiro, G., Souza, M. A., Moura, L. M., Assis, J. C., & Machado, J. C. (2013) Comparação de métodos de seleção de genitores e populações segregantes aplicados ao melhoramento de trigo. Bragantia, 72, 113-121. https://doi.org/10.1590/S0006-87052013005000026

Reis, R. V., Oliveira, E. J., Viana, A. P., Pereira, T. N. S., Pereira, M. G., & Silva, M. G. M. (2011) Diversidade genética em seleção recorrente de maracujazeiro-amarelo detectada por marcadores microssatélites. Pesquisa Agropecuária Brasileira, 46:51-57. https://doi.org/10.1590/S0100-204X2011000100007

Rigon, J. P. G., Capuani, S., Brito-Neto, J. F., Rosa, G. M., Wastowski, A. D., & Rigon, C. A. G. (2012) Dissimilaridade genética e análise de trilha de cultivares de soja avaliada por meio de descritores quantitativos. Revista Ceres, 59:233-240. https://doi.org/10.1590/S0034-737X2012000200012

Santos, I. G., Teodoro, P. E., Farias, F. J. C., Carvalho, L. P., Rodrigues, J. I., & Cruz, C. D. (2017) Genetic diversity among cotton cultivars in two environments in the State of Mato Grosso. Genetics and Molecular Research, 16:gmr16029628. http://dx.doi.org/10.4238/gmr16029628

Santos, I. G., Carneiro, V. Q., Silva Junior, A. C., Cruz, C. D., & Soares, P. C. (2019) Self-organizing maps in the study of genetic diversity among irrigated rice genotypes. Acta Scientiarum Agronomy, 41:e39803. https://doi.org/10.4025/actasciagron.v41i1.39803

Santos, J. A. S., Teodoro, P. E., Correa, A. M., Soares, C. M. G., Ribeiro, L. P., & Abreu, H. K. A. (2014) Desempenho agronômico e divergência genética entre genótipos de feijão-caupi cultivados no ecótono Cerrado/Pantanal. Bragantia, 73:377-382. https://doi.org/10.1590/1678-4499.0250

Santos, L. H., Oliveira, S. M. P., Malhado, C. H. M., Carneiro, P. L., Martins Filho, R., Lôbo, R. N. B., & Rodrigues, D. S. (2012) Estrutura populacional e tendências genéticas e fenotípicas da raça Guzerá no Nordeste do Brasil. Revista Brasileira Saúde Produção Animal, 13:1032-1043. https://doi.org/10.1590/S1519-99402012000400007

Signorini, T., Renesto, E., Machado, M. F. P. S., Bespalhok, D. N., & Monteiro, E. R. (2013) Diversidade genética de espécies de Capsicum com base em dados de isozimas. Horticultura Brasileira, 31:534-539. https://doi.org/10.1590/S0102-05362013000400005

Silva, M. J., Pastina, M. M., Souza, V. F., Schaffert, R. E., Carneiro, P. C. S., Noda, R. W., Carneiro, J. E. S., Damasceno, C. M. B., & Parrella, R. A. C. (2017) Phenotypic and molecular characterization of sweet sorghum accessions for bioenergy production. PLoS ONE, 12:e0183504. https://doi.org/10.1371/journal.pone.0183504

Teixeira-Neto, M. R., Cruz, J. F., Carneiro, P. L. S., Malhado, C. H. M., & Faria, H. H. N. (2013) Parâmetros populacionais da raça ovina Santa Inês no Brasil. Pesquisa Agropecuária Brasileira, 48:1589-1595. https://doi.org/10.1590/S0100-204X2013001200008

Wright, S. (1965) The interpretation of population structure by F-Statistics with special regard to systems of mating. Evolution, 19: 395-420 https://doi.org/10.2307/2406450

Published
2021-05-22
How to Cite
Rosado, R. D. S., Oliveira, A. M. C., Santos, I. G., Carneiro, P. C. S., Cruz, C. D., & Cecon, P. R. (2021). Parental selection based on molecular information under a population genetics approach. Agronomy Science and Biotechnology, 7, 1-9. https://doi.org/10.33158/ASB.r131.v7.2021