PANEL REDUCIDO DE POLIMORFISMOS DE NUCLEÓTIDO SIMPLE PARA ESTUDIOS DE BIODIVERSIDAD EN BOVINOS
Resumen
El objetivo de este trabajo fue evaluar un panel reducido de 200 marcadores de polimorfismo de nucleótido simple recomendados por la Sociedad Internacional de Genética Animal y el Comité Internacional de Registro de Animales, mediante secuenciación de siguiente generación. Se utilizaron parámetros como número de loci utilizables, polimorfismo de loci, heterocigosis observada (Hob) y esperada (He), diversidad molecular media por loci (DML), distancia entre poblaciones, índice de fijación que estima el coeficiente de endogamia (Fis) y valor de diferenciación genética entre poblaciones (Fst). Del total de loci utilizados, se observó un promedio de 186 alelos utilizables; máximo de 187 en la raza Guabalá y un mínimo de 183 en la Brahman. Una media de 174 loci polimórficos con un máximo de 184 en genotipos cruzados y un mínimo de 149 en la raza Guabalá. Los valores de Hob, He y DML fueron 0,378, 0,439 y 0,438, respectivamente. El Análisis Molecular de Varianza (AMOVA) mostró un porcentaje de variación entre poblaciones de 19,25 e índice Fst de 0,19. El porcentaje de variación y Fst entre las razas criollas panameñas y cebuinas fueron de 5,22% y 0,22, respectivamente y el porcentaje de variación entre razas criollas y taurinas fue 1,82 con índice de diferenciación genética Fst de 0,163, respectivamente. Los valores de endogamia (Fis) oscilaron entre 0,00302 (Guaymí) a 0,04333 (Holstein); valores negativos de Fis se observaron en la raza Senepol y Guabalá por lo que se presume un efecto Wahlund. El árbol de distancias circulares mostró un comportamiento similar a los reportados en trabajos realizados con microsatélites al igual que lo observado en el AMOVA y Fst en las poblaciones. Los resultados preliminares apuntan a que los marcadores de polimorfismo de nucleótido simple utilizados tienen potencial para estudios de diversidad genética y se recomienda ampliar el estudio a más razas y números de animales.
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Allen, A.R., M. Taylor, B. McKeown, A.L. Curry, J.F. Lavery, A. Mitchell, D. Hartshorne, R. Fries, and R.A. Skuce. 2010. Compilation of a panel of informative single nucleotide polymorphisms for bovine identification in the Northern Irish cattle population. BioMed Central Genetics 11: e5. https://doi.org/10.1186/1471-2156-11-5 (consultado 20 jul. 2019).
Baumung, R., H. Simianer, and I. Hoffmann. 2004. Genetic diversity studies in farm animals–a survey. Journal of Animal Breeding and Genetics 121(6): 361-373. https://doi.org/10.1111/j.1439-0388.2004.00479.x
Belkhir, K., P. Borsa, L. Chikhi, N. Raufaste, and F. Bonhomme. 2004. GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations. Laboratoire Génome, Populations, Interactions, CNRS UMR 5000, Université de Montpellier II, Montpellier. https://kimura.univ-montp2.fr/genetix/ (consultado 20 jul. 2019).
Brookes, A.J. 1999. The essence of SNPs. Gene, 234(2): 177-186. https://doi.org/10.1016/s0378-1119(99)00219-x
Bryant, D., and V. Moulton. 2004. Neighbor-Net: an agglomerative method for the construction of phylogenetic networks. Molecular Biology Evolution. 21: 255-265. https://doi.org/10.1093/molbev/msh018
Buick, W., 2004. Animal Passports and Identification. Defra Veterinary Journal 15: 20–26. http://www.defra.gov.uk/animalh/svj/vol1501/chap4.pdf (consultado 21 sept. 2018).
Caporale, V., A. Giovannini, C. Di Francesco, and P. Calistri. 2001. Importance of the traceability of animal products in epidemiology. Revue Scientifique et Technique. 20: 372-378. https://doi.org/10.20506/rst.20.2.1279
Delgado, J.V., A.M. Martinez, A. Acosta, L.A. Alvarez, E. Armstrong, E. Camacho, J. Canon, O. Cortes, S. Dunner, V. Landi, J.R. Marques, I. Martín-Burriel, O.R. Martínez, R.D. Martínez, L. Melucci, J.E. Muñoz, M.C. Penedo, A. Postiglioni, J. Quiróz, C. Rodellar, P. Sponenberg, O. Uffo, R. Ulloa-Arvizu, J.L. Vega-Pla, A. Villalobos, D. Zambrano, P. Zaragoza, L.T. Gama, and C. Ginja. 2011. Genetic characterization of Latin-American Creole cattle using microsatellite markers. Animal Genetics. 43:2–10. https://doi.org/10.1111/j.1365-2052.2011.02207.x
Edea, Z., H. Dadi, S.W. Kim, T. Dessie, T. Lee, H. Kim, J.J. Kim, and K.S. Kim. 2013. Genetic diversity, population structure and relationships in indigenous cattle populations of Ethiopia and Korean Hanwoo breeds using SNP markers. Frontier Genetics. 4:35. https://doi.org/10.3389/fgene.2013.00035.
El Moutchou, N., A. González, M. Chentouf, K. Lairini, M.E. Muñoz-Mejías, and E. Rodero. 2018. Exploring the genetic diversity and relationships between Spanish and Moroccan goats using microsatellite markers. Small Ruminant Research, 165, 115-123. https://doi.org/10.1016/j.smallrumres.2018.04.003.
Evanno, G., S. Regnaut, and J. Goudet. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology. 14:2611-2620. https://doi.org/10.1111/j.1365-294x.2005.02553.x10.1111/j.1365-294x.2005.02553.x
Excoffier, L., P.E. Smouse, J.M. Quattiro. 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479 - 491. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1205020/pdf/ge1312479.pdf (consultado 15 mayo 2017).
Excoffier, L., G. Laval, and S. Schneider. 2005. Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol. Bioinform. 1:47-50. Excoffier, L., Laval, G., & Schneider, S. (2005). Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evolutionary Bioinformatics, 1, 117693430500100. https://doi.org/10.1177/117693430500100003
Frkonja, A., B. Gredler, U. Schnyder, I. Curik, and J. Sölkner. 2012. Prediction of breed composition in an admixed cattle population. Animal Genetics. 43:696–703. https://doi.org/10.1111/j.1365-2052.2012.02345.x
Fresno, M.R., V. Landi, A.M. Martínez, M.M. Gómez, J.A. Bouzada, M.E. Camacho, J.Capote, and J.V. Delgado. 2017. Validación de marcadores SNP como herramienta para la identificación de productos en caprinos autóctonos españoles. En: XX Simposio Iberoamericano sobre conservación y utilización de recursos zoogenéticos. Validación de marcadores SNP´s como herramienta para la identificación de productos en caprinos autóctonos españoles. Red Conbiand. Chiquimula, Guatemala. p.16 http://www.uco.es/conbiand/pdf/acta_guatemala2017.pdf 10.1111/j.1365-2052.2012.02345.x (consultado 20 ago. 2019).
Gautier, M., T. Faraut, K. Moazami-Goudarzi, V. Navratil, M. Foglio, C. Grohs, A. Boland, J.G. Garnier, D. Boichard, G.M. Lathrop, I.G. Gut, and A. Eggen, A. 2007. Genetic and haplotypic structure in 14 European and African cattle breeds Genetics 177:1059–1070. https://doi.org/10.1534/genetics.107.075804
Gorbach, D. M., M.L. Makgahlela, J.M. Reecy, S.J. Kemp, I. Baltenweck, R. Ouma, O. Mwai, K. Marshall, B. Murdoch, S. Moore, and M.F. Rothschild. 2010. Use of SNP genotyping to determine pedigree and breed composition of dairy cattle in Kenya. Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 127(5), 348–351. https://doi.org/10.1111/j.1439-0388.2010.00864.x
Heaton, M.P., G.P. Harhay, G.L. Bennett, R.T. Stone, W.M. Grosse, E. Casas, J.W. Keele, T.P. Smith, C.G. Chitko-McKown, and W.W. Laegreid. 2002. Selection and use of SNP markers for animal identification and paternity analysis in U.S. beef cattle. Mammalian Genome 13:272-281. https://doi.org/10.1007/s00335-001-2146-3
Heaton, M.P., J.E. Keen, M.L. Clawson, G.P. Harhay, N. Bauer, C. Shultz, B.T. Green, L. Durso, C.G. Chitko-McKown, and W.W. Laegreid. 2005. Use of bovine single nucleotide polymorphism markers to verify sample tracking in beef processing. Journal of the American Veterinary Medical Association 226(8): 1311-1314. https://doi.org/10.2460/javma.2005.226.1311
Houston, R. 2001. A computerised database system for bovine traceability. Revue Scientifique et Technique. 20:652-661. https://doi.org/10.20506/rst.20.2.1293.
Hulsegge, B., M.P.L. Calus, J.J. Windig, A.H. Hoving-Bolink, M.H.T. Maurice-van Eijndhoven, and S.J. Hiemstra. 2013. Selection of SNP from 50 K and 777 K arrays to predict breed of origin in cattle. Journal of Animal Science. 91:5128–5134. https://doi.org/10.2527/jas.2013-6678
Hulsegge, I., M. Schoon, J. Windig, M. Neuteboom, S.J. Hiemstra, & A. Schurink. 2019. Development of a genetic tool for determining breed purity of cattle. Livestock Science, 223, 60-67. https://doi.org/10.1016/j.livsci.2019.03.002
Huson, D.H., and D. Bryant. 2006. Application of phylogenetic networks in evolutionary studies. Molecular Biology Evolution. 23:254-267. https://doi.org/10.1093/molbev/msj030
ISAG (International Society of Animal Genetics). 2013. ISAG cattle core and additional SNP panel. http://www.isag.us/committees.asp?autotry=true&ULnotkn=true
Jakobsson, M., and N.A. Rosenberg. 2007. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806. https://doi.org/10.1093/bioinformatics/btm233
Li, M.H., K. Sternbauer, P. Haahr, and L. Kantanen. 2005. Genetic components in contemporary Faroe Islands Cattle as revealed by microsatellite analysis. Journal Animal Breeding and Genetics 122:309-317. https://doi.org/10.1111/j.1439-0388.2005.00534.x
Lindblad-Toh, K., E. Winchester, M.J. Daly, D.G. Wang, J.N. Hirschhorn, J.P. Laviolette, K. Ardlie, D.E. Reich, E. Robinson, and P. Sklar. 2000. Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse. Nature genetics 24(4): 381-386. https://doi.org/10.1038/74215
Markovtsova, L., P. Marjoram, and S. Tavaré. 2000. The age of a unique event polymorphism. Genetics 156(1): 401. https://www.genetics.org/content/genetics/156/1/401.full.pdf (consultada 18 mar. 2018).
McKean, J.D. 2001. The importance of traceability for public health and consumer protection. Revue Scientifique et Technique. 20:363-371. https://doi.org/10.20506/rst.20.2.1280
Makina, S.O., F.C. Muchadeyi, E. van Marle-Köster, M.D. MacNeil, and A. Maiwashe. 2014. Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel. Frontiers in Genetics, 5: 333. https://doi.org/10.3389/fgene.2014.00333
Manunza, A., T. Cardoso, A. Noce, A. Martínez, A. Pons, L.A. Bermejo, V. Landi, A. Sànchez, J. Jordana, J.V. Delgado, S. Adán, J. Capote, O. Vidal, E. Ugarte, J.J. Arranz, J.H. Calvo, J. Casellas, and M. Amills. 2016. Population structure of eleven Spanish ovine breeds and detection of selective sweeps with BayeScan and hapFLK. Scientific Report 6, 27296. https://doi.org/10.1038/srep27296
Martínez, AM., L.T. Gama, J. Canon, C. Ginja, J.V. Delgado, S. Dunner, V. Landi, I. Martin-Burriel, I., M.C.T. Penedo, C. Rodellar, J.L. Vega-Pla, A. Acosta, L.A. Alvarez, E. Camacho, O. Cortés, J.R. Marques, R. Martínez, R.D. Martínez, L. Melucci, G. Martínez-Velázquez, J.E. Muñoz, A. Postiglioni, J. Quiroz, P. Sponenberg, O. Uffo, A. Villalobos, D. Zambrano, and P. Zaragoza. 2012. Genetic footprints of Iberian cattle in America 500 years after the arrival of Columbus. PLoS One. 7: e49066. https://doi.org/10.1111/j.1365-2052.2011.02207.x
Martínez, C.P. 2015. Estimación de la diversidad genética mediante marcadores SNP en bovino Criollo Coreño (Bos taurus). Tesis Licenciatura. Universidad de Guadalajara. http://repositorio.cucba.udg.mx:8080/xmlui/bitstream/handle/123456789/5982/Martinez_Ruiz_Claudia_Patricia.pdf?sequence=1&isAllowed=y (consulta 10 mar. 2020)
Matukumalli, L.K., C.T. Lawley, R.D. Schnabel, J.F. Taylor, M.F. Allan, M.P. Heaton, J. O'Connell, S.S. Moore, T.P.L. Smith, T.S. Sonstegard, and C.P. Van Tassell. 2009. Development and characterization of a high-density SNP genotyping assay for cattle. PLoS ONE 4 (4), e5350. https://doi.org/10.3168/jds.2008-1758
Nielsen, R. 2000. Estimation of population parameters and recombination rates from single nucleotide polymorphisms. Genetics 154(2): 931. https://www.genetics.org/content/154/2/931.long (consultado 10 jul. 2018).
Pritchard, J.K., M. Stephens, and P. Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945-959. https://www.genetics.org/content/155/2/945 (consultado 21 sept. 2018).
Peakall, R., and P.E. Smouse. 2012. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537-2539. https://doi.org/10.1093/bioinformatics/bts460
Rosenberg, N.A. 2004. Distruct: a program for the graphical display of population structure. Mol. Ecol. Notes 4: 137–138. https://doi.org/10.1046/j.1471-8286.2003.00566.x
Sachidanandam, R., D. Weissman, S.C. Schmidt, J.M. Kakol, L.D. Stein, G. Marth, S. Sherry, J.C. Mullikin, B.J. Mortimore, and D.L. Willey. 2001. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 409 (6822): 928-933. https://doi.org/10.1038/35057149
Strucken, EM; B. Gudex, M.H. Ferdosi, H.K. Lee, K.D. Song, J.P. Gibson, M. Kelly, E.K. Piper, L.R. Porto-Neto, S.H. Lee, and C. Gondro. 2013. Performance of different SNP panels for parentage testing in two East Asian cattle breeds. Anim Genet. 45: 572–5. https://doi.org/10.1111/age.12154
Terry, B. 2008. Genomas. 3a Ed. Buenos Aires: Médica Panamericana. 760 p.
Tian, F., D. Sun, and Y. Zhang. 2008. Establishment of paternity testing system using microsatellite markers in Chinese Holstein. Journal of Genetics and Genomics, 35(5), 279-284. https://doi.org/10.1016/s1673-8527(08)60040-5
Thomson, R., J.K. Pritchard, P. Shen, P.J. Oefner, and M.W. Feldman. 2000. Recent common ancestry of human Y chromosomes: evidence from DNA sequence data. Proceedings of the National Academy of Sciences of the United States of America 97(13): 7360. https://doi.org/10.1073/pnas.97.13.7360
Vignal, A., D. Milan, M. San Cristobal, and A. Eggen. 2002. A review on SNP and other molecular markers and their use in animal genetics. Genetic Selection Evolution 43:275-305. https://doi.org/10.1186/1297-9686-34-3-275
Wang, D.G., J.B. Fan, C.J. Siao, A. Berno, P. Young, R. Sapolsky, G. Ghandour, N. Perkins, E. Winchester, and J. Spencer. 1998. Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science 280(5366): 1077. https://doi.org/10.1126/science.280.5366.1077
Weir, B.S. 1996. Genetic Data Analysis II: Methods for Discrete Population Genetic Data. Sinauer Assoc., Inc; Sunderland, MA, USA: 1996. https://archive.org/details/geneticdataanaly00weir/page/n9/mode/2up (consultado 18 mar. 2019).
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