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Correlated response to selection for litter size environmental variability in rabbits’ resilience

Published online by Cambridge University Press:  26 February 2019

M. J. Argente Open the ORCID record for M. J. Argente [Opens in a new window] ,
M. L. García ,
K. Zbyňovská ,
P. Petruška ,
M. Capcarová  and
A. Blasco
M. J. Argente*
Affiliation:
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, Ctra de Beniel Km 3.2, 03312 Orihuela, Spain
M. L. García
Affiliation:
Departamento de Tecnología Agroalimentaria, Universidad Miguel Hernández de Elche, Ctra de Beniel Km 3.2, 03312 Orihuela, Spain
K. Zbyňovská
Affiliation:
Slovak University of Agriculture in Nitra, Tr. A. Hlinku 2, 949 76 Nitra, Slovak Republic
P. Petruška
Affiliation:
Slovak University of Agriculture in Nitra, Tr. A. Hlinku 2, 949 76 Nitra, Slovak Republic
M. Capcarová
Affiliation:
Slovak University of Agriculture in Nitra, Tr. A. Hlinku 2, 949 76 Nitra, Slovak Republic
A. Blasco
Affiliation:
Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 22012, 46022 Valencia, Spain
*
†E-mail: mj.argente@umh.es
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Abstract

Resilience is the ability of an animal to return soon to its initial productivity after facing diverse environmental challenges. This trait is directly related to animal welfare and it plays a key role in fluctuations of livestock productivity. A divergent selection experiment for environmental variance of litter size has been performed successfully in rabbits over ten generations. The objective of this study was to analyse resilience indicators of stress and disease in the divergent lines of this experiment. The high line showed a lower survival rate at birth than the low line (−4.1%). After correcting by litter size, the difference was −3.2%. Involuntary culling rate was higher in the high than in the low line (+12.4%). Before vaccination against viral haemorrhagic disease or myxomatosis, concentration of lymphocytes, C-reactive protein (CRP), complement C3, serum bilirubin, triglycerides and cholesterol were higher in the high line than in the low line (difference between lines +4.5%, +5.6 µg/ml, +4.6 mg/ml, +7.9 mmol/l, +0.3 mmol/l and +0.4 mmol/l). Immunological and biochemical responses to the two vaccines were similar. After vaccination, the percentage of lymphocytes and CRP concentration were higher in the low line than in the high one (difference between lines +4.0% and +13.1 µg/ml). The low line also showed a higher increment in bilirubin and triglycerides than the high line (+14.2 v. +8.7 mmol/l for bilirubin and +0.11 v. +0.01 mmol/l for triglycerides); these results would agree with the protective role of bilirubin and triglycerides against the larger inflammatory response found in this line. In relation to stress, the high line had higher basal concentration of cortisol than the low line (+0.2ng/ml); the difference between lines increased more than threefold after the injection of ACTH 1 to 24, the increase being greater in the high line (+0.9 ng/ml) than in the low line (+0.4 ng/ml). Selection for divergent environmental variability of litter size leads to dams with different culling rate for reproductive causes and different kits’ neonatal survival. These associations suggest that the observed fitness differences are related to differences in the inflammatory response and the corticotrope response to stress, which are two important components of physiological adaptation to environmental aggressions.

Keywords

cortisolC-reactive proteininflammatory responseinvoluntary culling ratevaccination
Type
Research Article
Information
animal , Volume 13 , Issue 10 , October 2019 , pp. 2348 - 2355
Copyright
© The Animal Consortium 2019 

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References

Argente, MJ, Calle, EW, García, ML and Blasco, A 2017. Correlated response in litter size components in rabbits selected for litter size variability. Journal Animal Breeding and Genetics 134, 505–511.CrossRefGoogle ScholarPubMed
Argente, MJ, Santacreu, MA, Climen, A and Blasco, A 2000. Genetic correlations between litter size and uterine capacity. In Proceeding of the 8th World Rabbit Congress, 4–7 July 2000, Valencia, Spain, pp. 333–338.Google Scholar
Barcia, AM and Harris, HW 2005. Triglyceride-rich lipoproteins as agents of innate immunity. Clinical Infectious Diseases 41, S498–S503.CrossRefGoogle ScholarPubMed
Blasco, A 2017. Bayesian data analysis for animal scientists. Springer, New York, NY, USA.CrossRefGoogle Scholar
Blasco, A, Martínez-Álvaro, M, García, ML, Ibáñez-Escriche, N and Argente, MJ 2017. Selection for genetic environmental sensitivity of litter size in rabbits. Genetics Selection Evolution 49, 48–55.CrossRefGoogle Scholar
Burkuš, J, Kačmarová, M, Kubandová, J, Kokošová, N, Fabianová, K, Fabian, D, Koppel, J and Čikoš, Š 2015. Stress exposure during the preimplantation period affects blastocyst lineages and offspring development. Journal of Reproduction and Development 61, 325–331.CrossRefGoogle ScholarPubMed
Cabezas, S, Blas, J, Marchant, TA and Moreno, S 2007. Physiological stress levels predict survival probabilities in wild rabbits. Hormones and Behavior 51, 313–320.CrossRefGoogle ScholarPubMed
Castellini, C, Dal Bosco, A, Arias-Álvarez, M, Lorenzo, PL, Cardinalli, R and Rebollar, PG 2010. The main factors affecting the reproductive performance of rabbit does: a review. Animal Reproduction Science 122, 174–182.CrossRefGoogle ScholarPubMed
Colditz, IG and Hine, BC 2016. Resilience in farm animals: biology, management, breeding and implications for animal welfare. Animal Production Science 56, 1961–1983.CrossRefGoogle Scholar
De Nardo, D, Labzin, LI, Kono, H, Seki, R, Schmidt, SV, Beyer, M, Xu, D, Zimmer, S, Lahrmann, C, Schildberg, FA, Vogelhuber, J, Kraut, M, Ulas, T, Kerksiek, A, Krebs, W, Bode, N, Grebe, A, Fitzgerald, ML, Hernández, NJ, Williams, BRG, Knolle, P, Kneilling, M, Röcken, M, Lütjohann, D, Wright, SD, Schultze, JL and Latz, E 2014. High-density lipoprotein mediates anti-inflammatory reprogramming of macrophages via the transcriptional regulator ATF3. Nature Immunology 15, 152–160.CrossRefGoogle ScholarPubMed
Eckersall, PD 2000. Recent advances and future prospects for the use of acute phase proteins as markers of disease in animals. Revue de Médecine Vétérinaire 151, 577–584.Google Scholar
Feingold, KR and Grunfeld, C 2015. The effect of inflammation and infection on lipids and lipoproteins. In: De Groot LJ, Chrousos G, Dungan K, Feingold KR, Grossman A, Hershman JM, Koch C, Korbonits M, McLachlan R, New M, Purnell J, Rebar R, Singer F and Vinik A. Endotext, South Dartmouth, MA, USA. Retrieved on 7 June 2018 from https://www.ncbi.nlm.nih.gov/books/NBK326741/.Google Scholar
Fortun-Lamothe, L 2006. Energy balance and reproductive performance in rabbit does. Animal Reproduction Science 93, 1–15.CrossRefGoogle ScholarPubMed
Furze, RC and Rankin, SM 2008. Neutrophil mobilization and clearance in the bone marrow. Immunology 125, 281–288.CrossRefGoogle ScholarPubMed
García, ML, Blasco, A and Argente, MJ 2016. Embryologic changes in rabbit lines selected for litter size variability. Theriogenology 86, 1247–1250.CrossRefGoogle ScholarPubMed
García, ML, Blasco, A, García, ME and Argente, MJ 2018. Body condition and energy mobilisation in rabbits selected for litter size variability. Animal, 1–6, https://doi.org/10.1017/S1751731118002203, Published online by Cambridge University Press 28 August 2018.Google Scholar
Glaser, R and Kiecolt-Glaser, JK 2005. Stress-induced immune dysfunction: implications for health. Nature Reviews Immunology 5, 243–251.CrossRefGoogle Scholar
Guelfi, G, Zerani, M, Brecchia, G, Parillo, F, Dall’Aglio, C, Maranesi, M and Boiti, C 2011. Direct actions of ACTH on ovarian function of pseudopregnant rabbits. Molecular and Cellular Endocrinology 339, 63–71.CrossRefGoogle ScholarPubMed
Ibáñez-Escriche, N, Sorensen, D, Waagepetersen, R and Blasco, A 2008. Selection for environmental variation: a statistical analysis and power calculations to detect response. Genetics 180, 2209–2226.CrossRefGoogle ScholarPubMed
Janeway, CA, Travers, P, Walport, M and Shlomchik, MJ 2001. Immunobiology: the immune system in health and disease, 5th edition. Garland Science, New York, NY, USA.Google Scholar
Janssens, CJ, Helmond, FA and Wiegant, VM 1995. Chronic stress and pituitary-adrenocortical responses to corticotropin-releasing hormone and vasopressin in female pigs. European Journal of Endocrinology 132, 479–486.CrossRefGoogle ScholarPubMed
Madjid, M and Fatemi, O 2013. Components of the complete blood count as risk predictors for coronary heart disease: in-depth review and update. Texas Heart Institute Journal 40, 17–29.Google ScholarPubMed
Markanday, A 2015. Acute phase reactants in infections: evidence-based review and a guide for clinicians. Open Forum Infectious Diseases 2, 1–7.CrossRefGoogle Scholar
McDade, TW, Borja, JB, Kuzawa, CW, Perez, TL and Adair, LS 2005. C-reactive protein response to influenza vaccination as model of mild inflammatory stimulation in the Philippines. Vaccine 33, 2004–2008.CrossRefGoogle Scholar
Minemura, M, Tajiri, K and Shimizu, Y 2014. Liver involvement in systemic infection. World Journal of Hepatology 6, 632–642.CrossRefGoogle ScholarPubMed
Mirkena, T, Duguma, G, Haile, A, Tibbo, M, Okeyo, AM, Wurzinger, M and Sölkner, J 2011. Genetics of adaptation in domestic farm animals: a review. Livestock Science 132, 1–12.CrossRefGoogle Scholar
Mulder, HA and Rashidi, H 2017. Selection on resilience improves disease resistance and tolerance to infections. Journal of Animal Science 95, 3346–3358.Google ScholarPubMed
Otero, RW, Velasco, H and Sandoval, H 2009. The protective role of bilirubin in human beings. Revista Colombiana de Gastroenterologia 24, 293–301.Google Scholar
Piles, M, Garcia, ML, Rafel, O, Ramon, J and Baselga, M 2006. Genetics of litter size in three maternal lines of rabbits: repeatability versus multiple-trait models. Journal of Animal Science 84, 2309–1315.CrossRefGoogle ScholarPubMed
Posthouwer, D, Voorbij, HA, Grobbee, DE, Numans, ME and van der Bom, JG 2004. Influenza and pneumococcal vaccination as a model to assess C-reactive protein response to mild inflammation. Vaccine 23, 362–365.CrossRefGoogle ScholarPubMed
Knap, PW 2005. Breeding robust pigs. Australian Journal of Experimental Agriculture 45, 763–773.CrossRefGoogle Scholar
Rauw, WM, Kanis, N, Noordhuizen-Stassen, EN and Grommers, FG 1998. Undesirable side effects of selection for high production efficiency in farm animals: a review. Livestock Production Science 56, 15–33.CrossRefGoogle Scholar
Rosa Neto, NS and Carvalho, JF 2009. The use of inflammatory laboratory tests in rheumatology. Revista Brasileira de Reumatologia 49, 413–430.CrossRefGoogle Scholar
Volanakis, JE 1990. Participation of C3 and its ligands in complement activation. Current Topics in Microbiology and Immunology 153, 1–21.Google ScholarPubMed
Webster, JL, Tonelli, L and Sternberg, EM 2002. Neuroendocrine regulation of immunity. Annual Review of Immunology 20, 125–163.CrossRefGoogle Scholar
Yaşar, NF, Uylas, MU, Baspinar, M, Sarsilmaz, H, Ates, E, Erkasap, S and Sahin, A 2016. Evaluating the use of hematological parameters in staging hidradenitis suppurativa. Wounds 28, 87–91.Google ScholarPubMed