Enhancing the sustainability of rabbit production from the perspective of animal genetics
Submitted: 2024-10-21
|Accepted: 2025-03-07
|Published: 2025-03-31
Copyright (c) 2025 Juan Pablo Sánchez
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Keywords:
feed efficiency, genetic selection, animal breeding, new phenotypes, omic tools, rabbit
Supporting agencies:
These research activities were funded by research projects from the Spanish research plan (PID2021- 128173OR-C21, RTI2018-097610-R-I00, RTA2014-00015-C02-00, RTA2011-A0064-00-00) as well as from the H2020 Feeda- Gene programme (grant nº633531)
Abstract:
The concept of sustainability, originating from the late 1980s, emphasises the ability to maintain processes over time without compromising future generations’ needs. It encompasses social, environmental and economic dimensions, although controversies persist regarding the latter’s inclusion. In the case of rabbit production, the economic dimension is paramount to ensure the future sustainability of the sector, given the large number of threats, mainly economic, it is facing. The major challenge when considering social and environmental sustainability plans in breeding programmes is how to properly include these dimensions in the functions defining the relevance of the different traits to be considered during the development of specialised lines. Note however that the key drivers of the current economic sustainability of the sector: prolificacy, feed efficiency and some functional traits such as resilience and survivability, are also the most likely levers of the environmental and social components of sustainability. In this context, the development of specialised lines is the most valuable contribution to sustainability by animal geneticists, the maternal lines specialised in producing large amounts of healthy weaned kits and the terminal sire lines specialised in efficiently transforming feed into meat. Regarding feed efficiency, important milestones have been achieved in recent years, many of them related to the fact that kits are raised in collective cages, and under these rearing conditions, tools have been developed to measure feed intake at the individual level, as well as to explore the role that one individual imposes on their cage-mates. Despite the fact that genomic tools have been developed and used to explore the role of genomic regions of different traits of interest, this information is still far from being used in applied breeding programmes. In the near future, we could predict that breeding programmes for enhanced sustainability will still mainly rely on pedigree records and phenotypic information for prolificacy and feed efficiency; but enriching the list of available phenotypes with additional traits, most likely obtained under automatic recording systems, to explicitly account for the social and environmental sustainability plans. In this framework, omic tools will perform a valuable role for further investigation of the biological basis controlling the major drivers of rabbit production sustainability, and hopefully in the future this information could be directly incorporated into breeding programmes.
References:
Alfonso L. 2019. Impact of incorporating greenhouse gas emission intensities in selection indexes for sow productivity traits. Livest. Sci., 219: 57-61. https://doi.org/10.1016/j.livsci.2018.11.016
Ali B.M., de Mey Y., Bastiaansen J.W.M., Oude Lansink A.G.J.M. 2018. Effects of incorporating environmental cost and risk aversion on economic values of pig breeding goal traits. J. Anim. Breed. Genet., 35: 194-207. https://doi.org/10.1111/jbg.12331
Amer P.R., Hely F.S., Quinton C.D., Cromie A.R. 2018. A methodology framework for weighting genetic traits that impact greenhouse gas emission intensities in selection indexes. Animal, 12: 5-11. https://doi.org/10.1017/S1751731117001549
Argente M.J., Merchán M., Peiró R., García M.L., Santacreu M.A., Folch J.M., Blasco A. 2010. Candidate gene analysis for reproductive traits in two lines of rabbits divergently selected for uterine capacity. J. Anim. Sci., 88: 828-836. https://doi.org/10.2527/jas.2009-2324
Argente M.J., García M.L., Zbyňovská K., Petruška P., Capcarová M., Blasco A. 2019 Correlated response to selection for litter size environmental variability in rabbits’ resilience. Animal, 13: 2348-2355. https://doi.org/10.1017/S1751731119000302
Ballester M., Castelló A., Peiró R., Argente M.J., Santacreu M.A., Folch J.M. 2013. Identification of differentially expressed genes in the oviduct of two rabbit lines divergently selected for uterine capacity using suppression subtractive hybridization. Anim. Genet., 44: 296-304. https://doi.org/10.1111/age.12005
Baselga M., Nagy I., Piles M., Garreau H., Buttazzoni L., Szendrő Z., García M.L. 2021. Genetic improvement in the meat rabbit. In: Fontanesi L. (Eds) The Genetics and Genomics of the rabbit. CABI Publishing. CAB International, Wallingford Oxon, UK, 234-249. https://doi.org/10.1079/9781780643342.0013
Biada I., Ibáñez-Escriche N., Blasco A., Santacreu M.A. 2022. The gut microbiome profile varies between two maternal rabbit lines with different longevity, In Proc.: XX Reunión Nacional de Mejora Genética Animal, June, Madrid, Spain, Available at https://acteon.webs.upv.es/CONGRESOS/Z-XX_Reunion_MG_MADRID_2020/COMUNICACIONES%20MADRID/BiadaIliyass_rnmga2022.pdf. Accessed March 2025.
Blasco A., Ortega J.A., Climent A., Santacreu M.A. 2005. Divergent selection for uterine capacity in rabbits. I. Genetic parameters and response to selection. J. Anim. Sci., 83: 2297-2302. https://doi.org/10.2527/2005.83102297x
Blasco A., Martínez-Álvaro M., García M.L., Ibáñez-Escriche N., Argente M.J. 2017. Selection for environmental variance of litter size in rabbit. Genet. Sel. Evol., 49: 48. https://doi.org/10.1186/s12711-017-0323-4
Blasco A., Nagy I., Hernández P. 2021. Genetics and Genomics of Growth, Carcass and Meat Production traits in rabbits. In: Fontanesi L. (Eds) The Genetics and Genomics of the rabbit. CABI Publishing. CAB International, Wallingford Oxon, UK, 179-196. https://doi.org/10.1079/9781780643342.0010
Brascamp E.W., Smith C., Guy D.R. 1985. Derivation of economic weights from profit equations. Anim. Prod., 40: 175-180. https://doi.org/10.1017/S0003356100031986
Bijma P. 2011. Socially Affected Traits, Inheritance and Genetic Improvement. In: Meyers R.A. (Eds) Encyclopedia of Sustainable Science and Technology. Springer, New York, NY, USA, 1477-1512. https://doi.org/10.1007/978-1-4614-5797-8_346
Carneiro M., Rubin C.J., Di Palma F., Albert F.W., Alföldi J., Martinez Barrio A., Pielberg G., Rafati N., Sayyab S., Turner-Maier J., Younis S., Afonso S., Aken B., Alves J.M., Barrell D., Bolet G., Boucher S., Burbano H.A., Campos R., Chang J.L., Duranthon V., Fontanesi L., Garreau H., Heiman D., Johnson J., Mage R.G., Peng Z., Queney G., Rogel-Gaillard C., Ruffier M., Searle S., Villafuerte R., Xiong A., Young S., Forsberg-Nilsson K., Good J.M., Lander E.S., Ferrand N., Lindblad-Toh K., Andersson L. 2014. Rabbit genome analysis reveals a polygenic basis for phenotypic change during domestication. Science, 345: 1074-1079. https://doi.org/10.1126/science.1253714
Cartuche L., Pascual M., Gómez E.A., Blasco A. 2014. Economic weights in rabbit meat production. World Rabbit Sci., 22: 165-177. https://doi.org/10.4995/wrs.2014.1747
Casto-Rebollo C., Argente M.J., García M.L., Pena R., Ibáñez-Escriche N. 2020. Identification of functional mutations associated with environmental variance of litter size in rabbits. Genet. Sel. Evol., 52: 22. https://doi.org/10.1186/s12711-020-00542-w
Casto-Rebollo C., Argente M.J., García M.L., Pena R. Blasco A., Ibáñez-Escriche N. 2023. Selection for environmental variance shifted the gut microbiome composition driving animal resilience. Microbiome, 11: 147. https://doi.org/10.1186/s40168-023-01580-4
Cesari V., Zucali M., Bava L., Gislon G., Tamburini A., Toschi I. 2018. Environmental impact of rabbit meat: The effect of production efficiency. Meat Sci.,145: 447-454. https://doi.org/10.1016/j.meatsci.2018.07.011
Chen L.J., Xing L., Han L.J. 2009. Quantitative determination of nutrient content in poultry manure by near infrared spectroscopy based on artificial neural networks. Poult. Sci., 88: 2496-503. https://doi.org/10.3382/ps.2009-00210
Déru V., Bouquet A., Labussière E., Ganier P., Blanchet B., Carillier-Jacquin C., Gilbert H. 2021. Genetics of digestive efficiency in growing pigs fed a conventional or a high-fibre diet. J. Anim. Breed. Genet., 138: 246-258. https://doi.org/10.1111/jbg.12506
Drouilhet L., Gilbert H., Balmisse E., Ruesche J., Tircazes A., Larzul C., Garreau H. 2013. Genetic parameters for two selection criteria for feed efficiency in rabbits. J. Anim. Sci., 91: 3121-3128. https://doi.org/10.2527/jas.2012-6176
Drouilhet L., Achard C.S., Zemb O., Molette C., Gidenne T., Larzul C., Ruesche J., Tircazes A., Segura M., Bouchez T., Theau-Clément M., Joly T., Balmisse E., Garreau H., Gilbert H. 2016. Direct and correlated responses to selection in two lines of rabbits selected for feed efficiency under ad libitum and restricted feeding: I. Production traits and gut microbiota characteristics. J. Anim. Sci., 94: 38-48. https://doi.org/10.2527/jas.2015-9402
Fang S., Chen X., Pan J., Chen Q., Zhou L., Wang C., Xiao T., Gan Q.F. 2020. Dynamic distribution of gut microbiota in meat rabbits at different growth stages and relationship with average daily gain (ADG). BMC Microbiol., 20: 116. https://doi.org/10.1186/s12866-020-01797-5
Fortun-Lamothe L., Combes S., Gidenne T. 2010. Contribution of intensive rabbit breeding to sustainable development. A semiquantitative analysis of the production in France. World Rabbit Sci., 17: 79-85. https://doi.org/10.4995/wrs.2009.661
Gidenne T., Garreau H., Drouilhet L.,Aubert C., Martens L. 2017. Improving feed efficiency in rabbit production, a review on nutritional, technico-economical, genetic and environmental aspects. Anim. Feed Sci. Technol., 225: 109-112. https://doi.org/10.1016/j.anifeedsci.2017.01.016
García M.L., Gunia M., Argente M.J., 2021. Genetic factors of functional traits (invited paper). In Proc.: 12th World Rabbit Congress, November, Nantes, France, BG-00.
Garreau H., Bolet G., Larzul C., Robery-Granié C., Saleil G., San Cristobal M., Bodin L. 2008. Results of four generations of a canalising selection for rabbit birth weight. Livest. Sci., 119: 55-62. https://doi.org/10.1016/j.livsci.2008.02.009
Garreau H., Bosze Z., Curik I., Piles M., Rogel-Gaillard C., Thulin C.G., Fontanesi L., the RGB-Net consortium. 2012. A collaborative European network on rabbit genome biology: RGB-net. In Proc.: 10th World Rabbit Congress, September, Sharm El- Sheikh, Egypt, 147-151.
Garreau H., Ruesche J., Gilbert H., Balmisse E., Benitez F., Richard F., David I., Drouilhet L., Zemb O. 2019. Estimating direct genetic and maternal effects affecting rabbit growth and feed efficiency with a factorial design. J. Anim. Breed. Genet., 136: 168-173. https://doi.org/10.1111/jbg.12380
Garreau H., Gunia M., Lemos de Matos A., Abrantes J., Esteves P.J. 2021. Genetics of Disease Resistance in the European Rabbit. In: Fontanesi L. (Eds) The Genetics and Genomics of the rabbit. CABI Publishing. CAB International, Wallingford Oxon, UK, 163-178. https://doi.org/10.1079/9781780643342.0009
Garreau H., Labrune Y., Chapuis H., Ruesche J., Riquet J., Demars J., Benitez F., Richard F., Drouilhet L., Zemb O., Gilbert H., 2023. fon. World Rabbit Sci., 31: 163-169. https://doi.org/10.4995/wrs.2023.18215
Gilbert H. 2023. A framework to leverage comparative genomics sequence-based data in experimental populations to improve livestock sustainability – FeedSeq. Available at https://anr.fr/Project-ANR-22-CE20-0040. Accessed March 2025.
Jaén-Téllez J.A., Sánchez-Guerrero M.J., López-Campos J.I., Valera M., González-Redondo P. 2020. Acute stress assessment using infrared thermography in fattening rabbits reacting to handling under winter and summer conditions. Span. J. Agric. Res., 18: e0502. https://doi.org/10.5424/sjar/2020182-15706
Larzul C., De Rochambeau H. 2004. Comparison of ten rabbit lines of terminal bucks for growth, feed efficiency and carcass traits. Anim. Res., 53: 535-545. https://doi.org/10.1051/animres:2004032
Larzul C., Ducrocq V., Tudela F., Juin H., Garreau H. 2014. The length of productive life can be modified through selection: an experimental demonstration in the rabbit. J. Anim. Sci., 92: 2395-2401. https://doi.org/10.2527/jas.2013-7216
Lebas F., Coudert P., Rouvier R., De Rochambeau H. 1986. The rabbit, breeding and pathology. F.A.O., Rome, Italy. Mancin E., Sosa-Madrid B.S., Blasco A., Ibáñez-Escriche N. 2021. Genotype Imputation to Improve the Cost-Efficiency of Genomic Selection in Rabbits. Animals, 11: 803. https://doi.org/10.3390/ani11030803
Martínez-Álvaro M., Zubiri-Gaitán A., Hernández P., Greenacre M., Ferrer A., Blasco A. 2021. Comprehensive functional core microbiome comparison in genetically obese and lean hosts under the same environment. Commun. Biol., 4, 1: 1246. https://doi.org/10.1038/s42003-021-02784-w
Merchán M., Peiró R., Argente M.J., Santacreu M.A., García M.L., Blasco A., Folch J.M. 2009. Analysis of the oviductal glycoprotein 1 polymorphisms and their effects on components of litter size in rabbits. Anim. Genet., 40: 756-758. https://doi.org/10.1111/j.1365-2052.2009.01898.x
Mora M., Velasco-Galilea M., Sánchez J. P., Ramayo-Caldas Y., Piles M. 2022. Disentangling the causal relationship between rabbit growth and cecal microbiota through structural equation models. Genet. Sel. Evol., 54: 81. https://doi.org/10.1186/s12711-022-00770-2
Muir W.M., Bijma P., Schinckel A., 2013. Multilevel selection with kin and non-kin groups, experimental results with Japanese quail (Coturnix japonica). Evolution, 67, 6: 1598-1606. https://doi.org/10.1111/evo.12062
Nicodemus N., Pereda N., Romero C., Rebollar P.G. 2009. Evaluation de la technique d´impédance bioélectrique (IBE) pour estimer la composition corporelle de lapines reproductrices. In Proc.: 13émes Jornées de la Recherche Cunicole (INRA/ITAVI), November, Le Mans, France, 109-112.
Peiró R., Merchán M., Santacreu M.A., Argente M.J., García M.L., Folch J.M., Blasco A. 2008. Identification of single‐nucleotide polymorphism in the progesterone receptor gene and its association with reproductive traits in rabbits. Genetics, 180: 1699-1705. https://doi.org/10.1534/genetics.108.090779
Piles, M., Sánchez J.P. 2019. Use of group records of feed intake to select for feed efficiency in rabbit. J Anim Breed Genet., 136: 474-483. https://doi.org/10.1111/jbg.12395
Piles M., David I., Ramón J., Canario L., Rafel O., Pascual M., Ragab M., Sánchez J.P. 2017. Interaction of direct and social genetic effects with feeding regime in growing rabbits. Genet. Sel. Evol., 49: 58. https://doi.org/10.1186/s12711-017-0333-2
Piles M., Sánchez J.P., Riaboff L., David I., Mora M. 2023. Use of accelerometers to predict the behaviour of growing rabbits. In Proc.: 74th Annual Meeting of the European Association for Animal Production (EAAP), August, Lyon, France, 973.
Piles M., Mora M., Kyriazakis I., Tusell L., Pascual M., Sánchez J.P. 2024. Novel phenotypes of feeding and social behaviour and their relationship with individual rabbit growth and feed efficiency. Animal, 18: 101090. https://doi.org/10.1016/j.animal.2024.101090
Purvis B., Mao Y., Robinson D. 2019. Three pillars of sustainability: in search of conceptual origins. Sustain. Sci., 14:681-695. https://doi.org/10.1007/s11625-018-0627-5
Ramón J., Perucho O., Rafel O., Sánchez J.P, Piles M. 2015. ¿Es la aplicación de una restricción alimentaria en el cebo una estrategia recomendable para las granjas productoras de carne de conejo cuando hay riesgo de enteropatía?. In Proc.: XL Symposium de Cunicultura, May, Santiago de Compostela, Spain, 75-81
Saeys W., Mouazen A.M., Ramon H. 2005. Potential for Onsite and Online Analysis of Pig Manure using Visible and Near Infrared Reflectance Spectroscopy. Biosyst. Eng., 91: 393-402. https://doi.org/10.1016/j.biosystemseng.2005.05.001
Sánchez J.P., Theilgaard P., Mínguez C., Baselga M. 2008. Constitution and evolution of a long-lived productive rabbit line. J. Anim. Sci., 86: 515-525. https://doi.org/10.2527/jas.2007-0217
Sánchez J.P., Legarra A., Velasco-Galilea M., Piles M., Sánchez A., Rafel O., González-Rodríguez O., Ballester M. 2020. Genomewide association study for feed efficiency in collective cageraised rabbits under full and restricted feeding. Anim. Genet., 51: 799-810. https://doi.org/10.1111/age.12988
Sánchez J.P., Muñoz I., González O., Pascual M., Perucho O., Alsina P., Piles M. 2022. A Computer Vision System for Individual Tracking of Group Housed Rabbits. In Proc.: 12th World Congress on Genetics Applied to Livestock Production, July, Rotterdam, The Netherland, 610-613. https://doi.org/10.3920/978-90-8686-940-4_140
Sánchez J.P., Muñoz J., Chetrit R., Pascual M., Ragab M., Piles M. 2024. eFeederRab: An electronic feeder to measure feed intake related traits on growing rabbits raised in collective cages. Animal-Open Space, 3, 100074. https://doi.org/10.1016/j.anopes.2024.100074
Santacreu M.A., Mocé M.L., Climent A., Blasco A. 2005. Divergent selection for uterine capacity in rabbits. II. Correlated response in litter size and its components estimated with a cryopreserved control population. J. Anim. Sci., 83, 2303-2307. https://doi.org/10.2527/2005.83102303x
Sosa-Madrid B.S., Hernández P., Blasco A., Haley C.S., Fontanesi L., Santacreu M.A., Pena R.N., Navarro P., Ibáñez-Escriche N. 2020a. Genomic regions influencing intramuscular fat in divergently selected rabbit lines. Anim Genet., 51: 58-69. https://doi.org/10.1111/age.12873
Sosa‐Madrid B.S., Santacreu M.A., Blasco A., Fontanesi L., Pena R.N., Ibáñez‐Escriche N. 2020b. A genome-wide association study in divergently selected lines in rabbits reveals novel genomic regions associated with litter size traits. J. Anim. Breed. Genet.,137: 123-138. https://doi.org/10.1111/jbg.12451
Sosa-Madrid B.S., Varona L., Blasco A., Hernández P., Casto-Rebollo C., Ibáñez-Escriche N. 2020c. The effect of divergent selection for intramuscular fat on the domestic rabbit genome. Animal, 14: 2225-2235. https://doi.org/10.1017/S1751731120001263
Velasco-Galilea M., Piles M., Ramayo-Caldas Y., Sánchez J.P. 2021. The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes. Sci. Rep., 11: 19495. https://doi.org/10.1038/s41598-021-99028-y
World Commission on Environment and Development. 1987. Our Common Future. Oxford University Press.
Xu X., Sharma P., Shu S., Lin T.S., Ciais P., Tubiello F.N., Smith P., Campbell N., Jain A.K. 2021. Global greenhouse gas emissions from animal-based foods are twice those of plantbased foods. Nat. Food, 2: 724-732. https://doi.org/10.1038/s43016-021-00358-x
Zeng B., Han S., Wang P., Wen B., Jian W., Guo W., Yu Z., Du D., Fu X., Kong F., Yang M., Si X., Zhao J., Li Y. 2015. The bacterial communities associated with fecal types and body weight of rex rabbits. Sci. Rep., 5: 9342. https://doi.org/10.1038/srep09342
Zomeño C., Hernández P., Blasco A. 2011. Use of NIRS in selection for intramuscular fat. World Rabbit Sci., 19: 203-208. https://doi.org/10.4995/wrs.2011.939
