Mostrar el registro sencillo del ítem
dc.contributor.author | Sosa-Madrid, Bolivar Samuel | es_ES |
dc.contributor.author | Varona, L. | es_ES |
dc.contributor.author | Blasco Mateu, Agustín | es_ES |
dc.contributor.author | Hernández, Pilar | es_ES |
dc.contributor.author | Casto-Rebollo, Cristina | es_ES |
dc.contributor.author | Ibáñez-Escriche, Noelia | es_ES |
dc.date.accessioned | 2021-04-20T03:30:57Z | |
dc.date.available | 2021-04-20T03:30:57Z | |
dc.date.issued | 2020-11 | es_ES |
dc.identifier.issn | 1751-7311 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/165355 | |
dc.description.abstract | [EN] An experiment of divergent selection for intramuscular fat was carried out at Universitat Politecnica de Valencia. The high response of selection in intramuscular fat content, after nine generations of selection, and a multidimensional scaling analysis showed a high degree of genomic differentiation between the two divergent populations. Therefore, local genomic differences could link genomic regions, encompassing selective sweeps, to the trait used as selection criterion. In this sense, the aim of this study was to identify genomic regions related to intramuscular fat through three methods for detection of selection signatures and to generate a list of candidate genes. The methods implemented in this study were Wright's fixation index, cross population composite likelihood ratio and cross population - extended haplotype homozygosity. Genomic data came from the 9th generation of the two populations divergently selected, 237 from Low line and 240 from High line. A high single nucleotide polymorphism (SNP) density array, Affymetrix Axiom OrcunSNP Array (around 200k SNPs), was used for genotyping samples. Several genomic regions distributed along rabbit chromosomes (OCU) were identified as signatures of selection (SNPs having a value above cut-off of 1%) within each method. In contrast, 8 genomic regions, harbouring 80 SNPs (OCU1, OCU3, OCU6, OCU7, OCU16 and OCU17), were identified by at least 2 methods and none by the 3 methods. In general, our results suggest that intramuscular fat selection influenced multiple genomic regions which can be a consequence of either only selection effect or the combined effect of selection and genetic drift. In addition, 73 genes were retrieved from the 8 selection signatures. After functional and enrichment analyses, the main genes into the selection signatures linked to energy, fatty acids, carbohydrates and lipid metabolic processes wereACER2, PLIN2, DENND4C, RPS6, RRAGA(OCU1),ST8SIA6, VIM(OCU16),RORA, GANCandPLA2G4B(OCU17). This genomic scan is the first study using rabbits from a divergent selection experiment. Our results pointed out a large polygenic component of the intramuscular fat content. Besides, promising positional candidate genes would be analysed in further studies in order to bear out their contributions to this trait and their feasible implications for rabbit breeding programmes. | es_ES |
dc.description.sponsorship | The authors thank Federico Pardo, Veronica Juste and Marina Morini for technical assistance. The work was funded by project AGL2014-55921-C2-1-P and AGL2017-86083-C2-P1 from National Programme for Fostering Excellence in Scientific and Technical Research - Project I+D. B. Samuel Sosa-Madrid was supported by a FPI grant from the Economy Ministry of Spain (BES-2015-074194). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Cambridge University Press | es_ES |
dc.relation.ispartof | Animal | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Genome scan | es_ES |
dc.subject | Genomic divergence | es_ES |
dc.subject | Lagomorph | es_ES |
dc.subject | Meat quality | es_ES |
dc.subject | Selection signatures | es_ES |
dc.subject.classification | PRODUCCION ANIMAL | es_ES |
dc.title | The effect of divergent selection for intramuscular fat on the domestic rabbit genome | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1017/S1751731120001263 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//AGL2014-55921-C2-1-P/ES/ESTUDIO GENOMICO Y METABOLOMICO DE VARIAS LINEAS DE SELECCION DIVERGENTE EN CONEJO: EL CONEJO COMO MODELO EXPERIMENTAL/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//BES-2015-074194/ES/BES-2015-074194/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/AGL2017-86083-C2-1-P/ES/ESTUDIO MULTIOMICO SOBRE SENSIBILIDAD AMBIENTAL, LONGEVIDAD Y DEPOSICION GRASA EN LINEAS SELECCIONADAS DE CONEJO/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ciencia Animal - Departament de Ciència Animal | es_ES |
dc.description.bibliographicCitation | Sosa-Madrid, BS.; Varona, L.; Blasco Mateu, A.; Hernández, P.; Casto-Rebollo, C.; Ibáñez-Escriche, N. (2020). The effect of divergent selection for intramuscular fat on the domestic rabbit genome. Animal. 14(11):2225-2235. https://doi.org/10.1017/S1751731120001263 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1017/S1751731120001263 | es_ES |
dc.description.upvformatpinicio | 2225 | es_ES |
dc.description.upvformatpfin | 2235 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 14 | es_ES |
dc.description.issue | 11 | es_ES |
dc.identifier.pmid | 32618550 | es_ES |
dc.relation.pasarela | S\395343 | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.description.references | Beissinger, T. M., Rosa, G. J., Kaeppler, S. M., Gianola, D., & de Leon, N. (2015). Defining window-boundaries for genomic analyses using smoothing spline techniques. Genetics Selection Evolution, 47(1). doi:10.1186/s12711-015-0105-9 | es_ES |
dc.description.references | Carneiro, M., Albert, F. W., Afonso, S., Pereira, R. J., Burbano, H., Campos, R., … Ferrand, N. (2014). The Genomic Architecture of Population Divergence between Subspecies of the European Rabbit. PLoS Genetics, 10(8), e1003519. doi:10.1371/journal.pgen.1003519 | es_ES |
dc.description.references | Carneiro M, Rubin CJ, Di Palma F, Albert FW, Alföldi J, Barrio AM, Pielberg G, Rafati N, Sayyab S, Turner-Maier J, Younis S, Afonso S, Aken B, Alves JM, Barrell D, Bolet G, Boucher S, Burbano HA, Campos R, Chang JL, Duranthon V, Fontanesi L, Garreau H, Heiman D, Johnson J, Mage RG, Peng Z, Queney G, Rogel-Gaillard C, Ruffier M, Searle S, Villafuerte R, Xiong A, Young S, Forsberg-Nilsson K, Good JM, Lander ES, Ferrand N, Lindblad-Toh K and Andersson L 2014b. Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication. Science 345, 1074–1079. | es_ES |
dc.description.references | Cesar, A. S., Regitano, L. C., Mourão, G. B., Tullio, R. R., Lanna, D. P., Nassu, R. T., … Coutinho, L. L. (2014). Genome-wide association study for intramuscular fat deposition and composition in Nellore cattle. BMC Genetics, 15(1). doi:10.1186/1471-2156-15-39 | es_ES |
dc.description.references | Chen, H., Patterson, N., & Reich, D. (2010). Population differentiation as a test for selective sweeps. Genome Research, 20(3), 393-402. doi:10.1101/gr.100545.109 | es_ES |
dc.description.references | Damon, M., Wyszynska-Koko, J., Vincent, A., Hérault, F., & Lebret, B. (2012). Comparison of Muscle Transcriptome between Pigs with Divergent Meat Quality Phenotypes Identifies Genes Related to Muscle Metabolism and Structure. PLoS ONE, 7(3), e33763. doi:10.1371/journal.pone.0033763 | es_ES |
dc.description.references | Gandolfi, G., Mazzoni, M., Zambonelli, P., Lalatta-Costerbosa, G., Tronca, A., Russo, V., & Davoli, R. (2011). Perilipin 1 and perilipin 2 protein localization and gene expression study in skeletal muscles of European cross-breed pigs with different intramuscular fat contents. Meat Science, 88(4), 631-637. doi:10.1016/j.meatsci.2011.02.020 | es_ES |
dc.description.references | Gol, S., Ros-Freixedes, R., Zambonelli, P., Tor, M., Pena, R. N., Braglia, S., … Davoli, R. (2015). Relationship between perilipin genes polymorphisms and growth, carcass and meat quality traits in pigs. Journal of Animal Breeding and Genetics, 133(1), 24-30. doi:10.1111/jbg.12159 | es_ES |
dc.description.references | González-Rodríguez, A., Munilla, S., Mouresan, E. F., Cañas-Álvarez, J. J., Díaz, C., Piedrafita, J., … Varona, L. (2016). On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations. Genetics Selection Evolution, 48(1). doi:10.1186/s12711-016-0258-1 | es_ES |
dc.description.references | Grams, V., Wellmann, R., Preuß, S., Grashorn, M. A., Kjaer, J. B., Bessei, W., & Bennewitz, J. (2015). Genetic parameters and signatures of selection in two divergent laying hen lines selected for feather pecking behaviour. Genetics Selection Evolution, 47(1). doi:10.1186/s12711-015-0154-0 | es_ES |
dc.description.references | Gurgul, A., Jasielczuk, I., Ropka-Molik, K., Semik-Gurgul, E., Pawlina-Tyszko, K., Szmatoła, T., … Krupiński, J. (2018). A genome-wide detection of selection signatures in conserved and commercial pig breeds maintained in Poland. BMC Genetics, 19(1). doi:10.1186/s12863-018-0681-0 | es_ES |
dc.description.references | Johansson, A. M., Pettersson, M. E., Siegel, P. B., & Carlborg, Ö. (2010). Genome-Wide Effects of Long-Term Divergent Selection. PLoS Genetics, 6(11), e1001188. doi:10.1371/journal.pgen.1001188 | es_ES |
dc.description.references | Kim, E.-S., Ros-Freixedes, R., Pena, R. N., Baas, T. J., Estany, J., & Rothschild, M. F. (2015). Identification of signatures of selection for intramuscular fat and backfat thickness in two Duroc populations1. Journal of Animal Science, 93(7), 3292-3302. doi:10.2527/jas.2015-8879 | es_ES |
dc.description.references | Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., … Ma’ayan, A. (2016). Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research, 44(W1), W90-W97. doi:10.1093/nar/gkw377 | es_ES |
dc.description.references | Li, X., Lee, C.-K., Choi, B.-H., Kim, T.-H., Kim, J.-J., & Kim, K.-S. (2010). Quantitative gene expression analysis on chromosome 6 between Korean native pigs and Yorkshire breeds for fat deposition. Genes & Genomics, 32(4), 385-393. doi:10.1007/s13258-010-0009-6 | es_ES |
dc.description.references | Lillie, M., Sheng, Z., Honaker, C. F., Dorshorst, B. J., Ashwell, C. M., Siegel, P. B., & Carlborg, Ö. (2017). Genome-wide standing variation facilitates long-term response to bidirectional selection for antibody response in chickens. BMC Genomics, 18(1). doi:10.1186/s12864-016-3414-7 | es_ES |
dc.description.references | Ma, H., Zhang, S., Zhang, K., Zhan, H., Peng, X., Xie, S., … Ma, Y. (2019). Identifying Selection Signatures for Backfat Thickness in Yorkshire Pigs Highlights New Regions Affecting Fat Metabolism. Genes, 10(4), 254. doi:10.3390/genes10040254 | es_ES |
dc.description.references | Mallick, S., Gnerre, S., Muller, P., & Reich, D. (2009). The difficulty of avoiding false positives in genome scans for natural selection. Genome Research, 19(5), 922-933. doi:10.1101/gr.086512.108 | es_ES |
dc.description.references | Martínez-Álvaro, M., Hernández, P., & Blasco, A. (2016). Divergent selection on intramuscular fat in rabbits: Responses to selection and genetic parameters1. Journal of Animal Science, 94(12), 4993-5003. doi:10.2527/jas.2016-0590 | es_ES |
dc.description.references | Mauch E, Servin B, Gilbert H and Dekkers J 2018. Signatures of selection in two independent populations of pigs divergently selected for feed efficiency. Animal Industry Report AS 664, ASL R3274. | es_ES |
dc.description.references | Oleksyk, T. K., Smith, M. W., & O’Brien, S. J. (2010). Genome-wide scans for footprints of natural selection. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1537), 185-205. doi:10.1098/rstb.2009.0219 | es_ES |
dc.description.references | Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., … Sham, P. C. (2007). PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses. The American Journal of Human Genetics, 81(3), 559-575. doi:10.1086/519795 | es_ES |
dc.description.references | Qanbari, S., & Simianer, H. (2014). Mapping signatures of positive selection in the genome of livestock. Livestock Science, 166, 133-143. doi:10.1016/j.livsci.2014.05.003 | es_ES |
dc.description.references | Sabeti, P. C., Varilly, P., Fry, B., Lohmueller, J., Hostetter, E., … Lander, E. S. (2007). Genome-wide detection and characterization of positive selection in human populations. Nature, 449(7164), 913-918. doi:10.1038/nature06250 | es_ES |
dc.description.references | Sargolzaei, M., Chesnais, J. P., & Schenkel, F. S. (2014). A new approach for efficient genotype imputation using information from relatives. BMC Genomics, 15(1), 478. doi:10.1186/1471-2164-15-478 | es_ES |
dc.description.references | Sosa-Madrid BS, Hernández P, Blasco A, Haley CS, Fontanesi L, Santacreu MA, Pena RN, Navarro P and Ibáñez-Escriche N 2020. Genomic regions influencing intramuscular fat in divergently selected rabbit lines. Animal Genetics 51, 58–69. | es_ES |
dc.description.references | Sosa-Madrid BS, Ibañez-Escriche N, Santacreu MA, Varona L and Blasco A 2017. Huellas de selección en un experimento de seleccion divergente para capacidad uterina en conejo. In Proceedings of the XVII Jornadas sobre Producción Animal, 30–31 May 2017, Zaragoza, Spain, pp. 558–560. | es_ES |
dc.description.references | Szpiech ZA and Hernandez RD 2014. selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Molecular Biology and Evolution 31, 2824–2827. | es_ES |
dc.description.references | Utsunomiya, Y. T., Pérez O’Brien, A. M., Sonstegard, T. S., Van Tassell, C. P., do Carmo, A. S., Mészáros, G., … Garcia, J. F. (2013). Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods. PLoS ONE, 8(5), e64280. doi:10.1371/journal.pone.0064280 | es_ES |
dc.description.references | Walter, M., Chen, F. W., Tamari, F., Wang, R., & Ioannou, Y. A. (2009). Endosomal lipid accumulation in NPC1 leads to inhibition of PKC, hypophosphorylation of vimentin and Rab9 entrapment. Biology of the Cell, 101(3), 141-153. doi:10.1042/bc20070171 | es_ES |
dc.description.references | Wang, Z., Ma, H., Xu, L., Zhu, B., Liu, Y., Bordbar, F., … Li, J. (2019). Genome-Wide Scan Identifies Selection Signatures in Chinese Wagyu Cattle Using a High-Density SNP Array. Animals, 9(6), 296. doi:10.3390/ani9060296 | es_ES |
dc.description.references | Wipperman, M. F., Montrose, D. C., Gotto, A. M., & Hajjar, D. P. (2019). Mammalian Target of Rapamycin. The American Journal of Pathology, 189(3), 492-501. doi:10.1016/j.ajpath.2018.11.013 | es_ES |
dc.description.references | Zomeño, C., Hernández, P., & Blasco, A. (2013). Divergent selection for intramuscular fat content in rabbits. I. Direct response to selection1. Journal of Animal Science, 91(9), 4526-4531. doi:10.2527/jas.2013-6361 | es_ES |