Identificación de marcadores asociados a la producción de leche en el genoma de las razas Guaymí y Guabalá
DOI:
https://doi.org/10.34188/bjaerv8n2-043Palavras-chave:
producción de leche, ganado criollo, diversidad genética, SNP, marcadores, producción animalResumo
Este estudio identificó polimorfismos de un solo nucleótido (SNP) asociados con la producción de leche en las razas de ganado criollo panameño Guaymí y Guabalá. Se analizaron 8416 SNP de alta calidad, revelando diferencias genéticas significativas relevantes para programas de mejoramiento genético y conservación. La raza Guaymí presentó una mayor diversidad genética, lo que destaca su potencial para el mejoramiento ganadero sostenible. Se identificaron genes clave como KIT, LPIN1 y PAEP asociados con características de calidad de la leche. Los resultados proporcionan una base molecular para el desarrollo de estrategias sostenibles de mejoramiento genético en ambientes tropicales.
Referências
Andersson, L., & Georges, M. (2004). Domestic-animal genomics: deciphering the genetics of complex traits. Nature reviews. Genetics. https://doi.org/10.1038/nrg1294
Ayalew, W., Wu, X., Tarekegn, G. M., Sisay Tessema, T., Naboulsi, R., Van Damme, R., Bongcam-Rudloff, E., Edea, Z., Enquahone, S., & Yan, P. (2023). Whole-Genome Resequencing Reveals Selection Signatures of Abigar Cattle for Local Adaptation. Animals, 13(20), 3269. https://doi.org/10.3390/ani13203269
Avanus K, Yılmaz A, Güneş H, Altınel A, Ekiz B, Yalçıntan H, Keçici D, Doğan N: CXCR1 Gene SNP variability that affects mastitis resistance in Holstein cows in Türkiye. Kafkas Univ Vet Fak Derg, 31 (1): 119-124, 2025. https://doi.org/10.9775/kvfd.2024.32948
Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N., & Bonhomme, F. (2003). Genetix: 4.05 Logiciel sous WindowsTM pour la genetique des populations. Montpellier, France: Laboraoire Genoma Populations, Interactions, Adaptations.
Chen, B., Cole, J., & Grond-Ginsbach, C. (2017). Departure from Hardy-Weinberg Equilibrium and Genotyping Error. Frontiers in Genetics, 8, 167. https://doi.org/10.3389/fgene.2017.00167
Corredor, F. A., Figueroa, D., Estrada, R., & Burgos-Paz, W. (2024). Genome-wide single nucleotide polymorphisms reveal the genetic diversity and population structure of Creole goats from northern Peru. Livestock Science. https://doi.org/10.1016/j.livsci.2024.104965
Cosenza, G., & Pauciullo, A. (2024). A Comprehensive Analysis of CSN1S2 I and II Transcripts Reveals Significant Genetic Diversity and Allele-Specific Exon Skipping in Ragusana and Amiatina Donkeys. Animals, 14(20), 2918. https://doi.org/10.3390/ani14202918
Cui, Y.Z., & Man, X.Y. (2023). Biology of melanocytes in mammals. Frontiers in Cell and Developmental Biology. https://www.frontiersin.org/articles/10.3389/fcell.2023.1309557/full
El-Magd, M. (2015). Effect of SNPs in Prolactin Promoter on Milk Traits in Egyptian Buffalo. Advances in Dairy Research. https://doi.org/10.4172/2329-888X.1000128
Elsik, C. G., Unni, D. R., Diesh, C. M., Tayal, A., Emery, M. L., Nguyen, H. N., & Hagen, D. E. (2016). Bovine Genome Database: new tools for gleaning function from the Bos taurus genome. Nucleic Acids Research. https://doi.org/10.1093/nar/gkv1077
Excoffier, L., Laval, G., & Schneider, S. (2007). Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online. https://pubmed.ncbi.nlm.nih.gov/19325852/
Frazer, K. A., Murray, S. S., Schork, N. J., & Topol, E. J. (2009). Human genetic variation and its Acontribution to complex traits. Nature reviews. Genetics. https://doi.org/10.1038/nrg2554
Fontanesi, L., Calò, D., Galimberti, G., Negrini, R., Marino, R., Nardone, A., Ajmone-Marsan, P., & Russo, V. (2014). A candidate gene association study for nine economically important traits in Italian Holstein cattle. Anim Genet. https://doi.org/10.1111/age.12164
Ginja, C., Gama, L. T., Cortés, O., Burriel, I. M., & Vega-Pla, J. L. (2019). The genetic ancestry of American Creole cattle inferred from uniparental and autosomal genetic markers. Scientific Reports, 9, 20365. https://doi.org/10.1038/s41598-019-47636-0
Good, B. H., Walczak, A. M., Neher, R. A., & Desai, M. M. (2013). Interference limits resolution of selection pressures from linked neutral diversity. ArXiv.
https://doi.org/10.48550/arXiv.1306.1215
Guo, S. W., & E. A. Thompson. (1992). Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics. https://doi.org/10.2307/2532296
Gutierrez-Reinoso, M., Aponte, P., & García-Herreros, M. (2021). Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review. Animals : an Open Access Journal from MDPI, 11. https://doi.org/10.3390/ani11030599.
Howe, K. L., Achuthan, P., Allen, J., Allen, J., Alvarez-Jarreta, J., Amode, M. R., Armean, I. M., Azov, A. G., Bennett, R., Bhai, J., Billis, K., Boddu, S., Charkhchi, M., Cummins, C., Da Rin Fioretto, L., Davidson, C., Dodiya, K., El Houdaigui, B., Fatima, R., Gall, A., & Flicek, P. (2021). Ensembl 2021. Nucleic acids research. https://doi.org/10.1093/nar/gkaa942
Ibeagha-Awemu, E. M., Peters, S. O., Akwanji, K. A., Imumorin, I. G., & Zhao, X. (2016). High density genome wide genotyping-by-sequencing and association identifies common and low frequency SNPs, and novel candidate genes influencing cow milk traits. Scientific Reports, 6, 31109. https://doi.org/10.1038/srep31109
Kim, E. S., Cole, J. B., Huson, H. J., et al. (2015). "Effect of Artificial Selection on Runs of Homozygosity in U.S. Holstein Cattle." PLOS ONE, 10(8), e0135989. https://doi.org/10.1371/journal.pone.0080813
Kirsanova, E., Boysen, P., Johansen, G. M., Heringstad, B., Lewandowska-Sabat, A., & Olsaker, I. (2020). Expression analysis of candidate genes for chronic subclinical mastitis in Norwegian Red cattle. Journal of Dairy Science, 103(10), 9142–9149. https://doi.org/10.3168/jds.2020-18170
Kolenda, M., & Sitkowska, B. (2021). The Polymorphism in Various Milk Protein Genes in Polish Holstein-Friesian Dairy Cattle. Animals, 11(2), 389. https://doi.org/10.3390/ani11020389
Lamara, M., Zarubezhnova, D., Ahmetov, T., Shaydullin, R., & Tyulkin, S. (2023). Milk productivity and milk quality of cows with different LEP genotypes and linear affiliation. Agrobiotechnologies and digital farming. https://doi.org/10.12737/2782-490x-2023-56-61
Larina, O., Fedorova, M., Rodionova, V., & Voevodin, A. (2022). Genotyping of cattle of Holstein breed to LEP gene and analysis its association with milk productivity. Glavnyj zootehnik (Head of Animal Breeding). https://doi.org/10.33920/sel-03-2208-03.
Li, Q., Liang, R., Li, Y., Gao, Y., Li, Q., Sun, D., & Li, J. (2020). Identification of candidate genes for milk production traits by RNA sequencing on bovine liver at different lactation stages. BMC Genetics. https://doi.org/10.1186/s12863-020-00882-y
Lischer, H.E.L., & Excoffier, L. (2011). An automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics. https://doi.org/10.1093/bioinformatics/btr642
Luna-Azuara, C. G., Gudiño-Escandón, R. S., Díaz Oviedo, H. Y., Estrada-Rojas, F., Méndez-Ojeda, M. L., & Vega-Murillo, V. E. (2025). Diversidad genética de SNPs y su relación con enfermedades en ganado lechero de Veracruz, México. Brazilian Journal of Animal and Environmental Research, 8(1), 1–16. https://doi.org/10.34188/bjaerv8n1-118
Marete, A., Lund, M. S., Boichard, D., & Ramayo-Caldas, Y. (2018). A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds. PLOS ONE, 13(7), e0199931. https://doi.org/10.1371/journal.pone.0199931
Maiorano AM, Lourenco DL, Tsuruta S, Ospina AMT, Stafuzza NB, Masuda Y, et al. (2018) Assessing genetic architecture and signatures of selection of dual purpose Gir cattle populations using genomic information. PLoS ONE 13(8): e0200694. https://doi.org/10.1371/journal. pone.020069
Makamu, T., & Tyasi, T. (2024). Systematic Review of Single Nucleotide Polymorphisms of Cattle Beta-Lactoglobulin Gene and their Association with Milk Production Traits. American Journal of Animal and Veterinary Sciences. https://doi.org/10.3844/ajavsp.2024.121.132.
Miglior, F., Fleming, A., Malchiodi, F., Brito, L. F., Martin, P., & Baes, C. F. (2017). A 100-Year Review: Identification and Genetic Selection of Economically Important Traits in Dairy Cattle. Journal of Dairy Science, 100(12), 10251–10271. https://doi.org/10.3168/jds.2017-12968
Moradian, H., Esmailizadeh Koshkoiyeh, A., Mohammadabadi, M., & Asadi Fozi, M. (2019). Whole genome detection of recent selection signatures in Sarabi cattle: A unique Iranian taurine breed. Genes & Genomics, 41(12), 1409–1419. https://doi.org/10.1007/s13258-019-00888-6
More, M., Kuralkar, S. V., Bankar, P. S., Kuralkar, P., & Deshmukh, S. G. Study Of Genetic Polymorphism Of Dgat1 Gene In Gaolao Cattle. Google Scholar
Neher, R. A., & Hallatschek, O. (2012). Genealogies of rapidly adapting populations. ArXiv. https://doi.org/10.1073/pnas.1213113110
Parra-Bracamonte, G. M., Sifuentes-Rincón, A. M., Magaña-Monforte, J. G., & Martínez-González, J. C. (2023). Mejoramiento genético asistido para características reproductivas de animales domésticos. Brazilian Journal of Animal and Environmental Research, 6(1), 273–286. https://doi.org/10.34188/bjaerv6n1-024
Peakall, R. & Smouse, P.E. (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics. http://bioinformatics.oxfordjournals.org/content/28/19/2537
Pegolo S, Dadousis C, Mach N, et al. SNP co-association and network analyses identify E2F3, KDM5A and BACH2 as key regulators of the bovine milk fatty acid profile. Scientific Reports. 2017 Dec;7(1):17317. https://doi.org/10.1038/s41598-017-17434-7
Purfield, D.C., Berry, D.P., McParland, S. et al. Runs of homozygosity and population history in cattle. BMC Genet 13, 70 (2012). https://doi.org/10.1186/1471-2156-13-70
Rivera, T., Valdovinos, M., Morales, R. A. A., Vázquez, A., Ponce, A., & Pérez, C. (2016). Frecuencias genotípicas y alélicas de la β-caseína en el bovino Criollo Lechero Tropical de México. Archivos De Zootecnia, 65(251), 409-411. https://doi.org/10.21071/az.v65i251.704
Rauw, W. M., & Gomez-Raya, L. (2015). Genotype by environment interaction and breeding for robustness in livestock. Frontiers in Genetics, 6, 310. https://doi.org/10.3389/fgene.2015.00310
Robinson, J., Thorvaldsdóttir, H., Winckler, W., Guttman, M., Lander, E., Getz, G., & Mesirov, J. P. (2011). Integrative Genomics Viewer. Nature Biotechnology. https://doi.org/10.1038/nbt.1754
Rogers, R. L., Grizzard, S. L., & Garner, J. T. (2021). Strong, recent selective sweeps reshape genetic diversity in freshwater bivalve Megalonaias nervosa. ArXiv. https://doi.org/10.48550/arXiv.2107.08010
Roh, H., Kim, S., & Cho, C. (2020). Estimating genetic diversity and population structure of 22 chicken breeds in Asia using microsatellite markers. Anim Biosci. https://doi.org/10.5713/ajas.19.0958
Rosendo-Ponce, Adalberto, & Becerril-Pérez, Carlos Miguel. (2015). Avance en el conocimiento del bovino criollo lechero tropical de México. Ecosistemas y recursos agropecuarios, 2(5), 233-243. Recuperado en 23 de enero de 2025, de http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S2007-90282015000200012&lng=es&tlng=es
Safina, N., Sharafutdinov, G., Akhmetov, T., Ravilov, R., & Vafin, F. (2021). Association of LEP gene polymorphism with biochemical parameters of lipid metabolism and milk productivity of Holstein cattle. E3S Web of Conferences. https://doi.org/10.1051/E3SCONF/202125401007.
Schroder Figueira, L. (2024). Genomic diversity level and relationship of selected European indigenous sheep breeds [Tesis de Licenciatura, University of Debrecen]. Centre of Agricultural Genomics and Biotechnology.
Teneva, A., & Petrović, M. P. (2010). Application of molecular markers in livestock improvement. Biotechnology in Animal Husbandry, 26(3-4), 135–154. https://doi.org/10.2298/BAH1004135T
Trakovická, A., Moravčíková, N., & Kasarda, R. (2013). Genetic polymorphisms of leptin and leptin receptor genes in relation with production and reproduction traits in cattle. Acta Biochimica Polonica, 60(4), 783–787. https://doi.org/10.18388/abp.2013_1962
Valdez-Torres, J. M., Grado Ahuir, J. A., Castro-Valenzuela, B. E., & Burrola-Barraza, M. E. (2020). QTL analysis associated to single nucleotide polymorphisms (SNP) involved in the dairy phenotype of Holstein cattle. Revista Mexicana de Ciencias Pecuarias, 11(4), 1192–1207. https://doi.org/10.22319/rmcp.v11i4.5295
Weller, J., & Ron, M. (2011). Invited review: quantitative trait nucleotide determination in the era of genomic selection.. Journal of dairy science, 94 3, 1082-90
Villalobos-Cortés, A. I., Martínez, A. M., & Delgado, J. V. (2009). Historia de los bovinos en Panamá y su relación con las poblaciones bovinas de iberoamérica. Archivos de Zootecnia. https://doi.org/10.21071/az.v58i224.5078
Villalobos-Cortés, A., González, R., Murillo, M., & Castillo, H. (2020). Panel reducido de polimorfismos de nucleótido simple para estudios de biodiversidad en bovinos. Ciencia Agropecuaria. http://www.revistacienciaagropecuaria.ac.pa/index.php/ciencia-agropecuaria/article/view/298
Villalobos-Cortés, A., Castillo Mayorga, H., & González Herrera, R. (2021). Identificación de polimorfismos de cuatro enfermedades genéticas en Guaymí, Guabalá y razas transfronterizas en Panamá. Brazilian Journal of Animal and Environmental Research, 4(1), 342–354. https://doi.org/10.34188/bjaerv4n1-030
Villalobos-Cortés, A., Castillo, H., Murillo, M., & González-Herrera, R. (2021). Polimorfismos de marcadores asociados a la calidad de leche en poblaciones criollas y transfronterizas. Ciencia Agropecuaria.
http://www.revistacienciaagropecuaria.ac.pa/index.php/ciencia-agropecuaria/article/view/487
Weikard, R., Kühn, C., Goldammer, T., Freyer, G., & Schwerin, M. (2005). The bovine PPARGC1A gene: molecular characterization and association of an SNP with variation of milk fat synthesis. Physiological genomics. https://doi.org/10.1152/physiolgenomics.00103.2004
Weir, B. S., & Cockerham, C. C. (1984). Estimating F-statistics for the analysis of population structure. Evolution. https://doi.org/10.2307/2408641
Worku, A. (2017). A Review on Population Structure, Genetic Diversity Analysis, Genetic Distance between Population and Genetic Singularity in Livestock. Advances in Life Science and Technology, 54, 1-6.
Wright, S. (1949), The genetical structure of populations. Annals of Eugenics, 15: 323-354. https://doi.org/10.1111/j.1469-1809.1949.tb02451.x
Zinovieva, N. A., Sermyagin, A. A., Dotsev, A. V., Boronetslaya, O. I., Petrikeeva, L. V., Abdelmanova, A. S., & Brem, G. (2019). Animal genetic resources: Developing the research of allele pool of Russian cattle breeds-Minireview. Agric. Bio. http://www.agrobiology.ru/6-2016zinovieva-eng.html
Zhi-Liang, H., Fritz, E., & Reecy, J. (2007). AnimalQTLdb: a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Research. https://doi.org/10.1093/nar/gkl946
Zhao, Z., Niu, Q., Wu, T., Liu, F., Wang, Z., Gao, H., Li, J., Zhu, B., & Xu, L. (2024). Comparative Analysis of Genomic Prediction for Production Traits Using Genomic Annotation and a Genome-Wide Association Study at Sequencing Levels in Beef Cattle. Agriculture, 14(12), 2255. https://doi.org/10.3390/agriculture14122255
Downloads
Publicado
Como Citar
Edição
Seção
Licença
- O conteúdo dos artigos é de responsabilidade exclusiva dos autores.
- É permitida a reprodução total ou parcial do conteúdo dos artigos, desde que citada a fonte.
- Artigos com plágio serão recusados, e o autor do plágio perderá o direito de publicar nesta revista.
- Os nomes e endereços informados nesta revista serão utilizados exclusivamente para os serviços prestados por esta publicação e não estão disponíveis para outros fins ou a terceiros.
- Depois de enviar os artigos, os autores cedem os direitos autorais de seus artigos ao BJAER. Se você se arrepender da submissão, o autor tem o direito de solicitar ao BJAER que não publique seu artigo. Porém, essa solicitação deve ocorrer até dois meses antes da divulgação do número que o artigo será publicado.
- O BJAER usa a licença Creative Commons CC BY. Informações sobre esta licença podem ser encontradas em: https://creativecommons.org/licenses/by/3.0/br/
Brazilian Journal of Animal and Environmental Research (BJAER) se reserva o direito de efetuar nos originais alterações de ordem normativa, ortográfica e gramatical, com vistas a manter o padrão culto da língua, respeitando, porém, o estilo dos autores. Os trabalhos finais não serão enviadas aos autores.
