Ovarian transcriptomic analysis reveals differential expression genes associated with cell death process after selection for ovulation rate in rabbits

[EN] Transcriptomic analysis showed nineteen potential biomarkers in ovarian tissue from females belonged to a rabbit line selected for ovulation rate for 10 generations and the control line. These females differed not only in ovulation rate but also in prenatal survival since similar litter size were observed. Litter size is an essential trait in rabbit meat production but with low heritability. A selection experiment for ovulation rate has been performed for 10 generations to improve litter size in rabbits. The selected line increased two ova more than the control line but nevertheless a negative correlation was observed with prenatal survival. A transcriptomic study was performed, using microarrays, in ovarian tissue from females belonging to the selected line and the control line. Our results showed 1357 differential expressed genes and nineteen potential biomarkers associated with prenatal mortality, which could explain differences between litter size in rabbits. Cell death was the most relevant process.This research was supported by MEC (AGL2014-55921-C2-1-P) and Generalitat Valenciana (Prometeo 2009/125).Serna-García, M.; Peiró Barber, RM.; Serna, E.; Santacreu Jerez, MA. (2020). Ovarian transcriptomic analysis reveals differential expression genes associated with cell death process after selection for ovulation rate in rabbits. Animals. 10(10):1-11. https://doi.org/10.3390/ani10101924S1111010Laborda, P., Mocé, M. L., Blasco, A., & Santacreu, M. A. (2012). Selection for ovulation rate in rabbits: Genetic parameters and correlated responses on survival rates1. Journal of Animal Science, 90(2), 439-446. doi:10.2527/jas.2011-4219Laborda, P., Mocé, M. L., Santacreu, M. A., & Blasco, A. (2011). Selection for ovulation rate in rabbits: Genetic parameters, direct response, and correlated response on litter size1. Journal of Animal Science, 89(10), 2981-2987. doi:10.2527/jas.2011-3906Laborda, P., Santacreu, M. A., Blasco, A., & Mocé, M. L. (2012). Selection for ovulation rate in rabbits: Direct and correlated responses estimated with a cryopreserved control population1. Journal of Animal Science, 90(10), 3392-3397. doi:10.2527/jas.2011-4837Cunningham, P. J., England, M. E., Young, L. D., & Zimmerman, D. R. (1979). Selection for Ovulation Rate in Swine: Correlated Response in Litter Size and Weight. Journal of Animal Science, 48(3), 509-516. doi:10.2527/jas1979.483509xRosendo, A., Druet, T., Gogué, J., & Bidanel, J. P. (2007). Direct responses to six generations of selection for ovulation rate or prenatal survival in Large White pigs. Journal of Animal Science, 85(2), 356-364. doi:10.2527/jas.2006-507Johnson, R. K., Zimmerman, D. R., & Kittok, R. J. (1984). Selection for components of reproduction in swine. Livestock Production Science, 11(6), 541-558. doi:10.1016/0301-6226(84)90070-8Rodrigues, P., Limback, D., McGinnis, L. K., Plancha, C. E., & Albertini, D. F. (2008). Oogenesis: Prospects and challenges for the future. 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Correlated responses on litter size traits and survival traits after two-stage selection for ovulation rate and litter size in rabbits

[EN] Farmer profit depends on the number of slaughter rabbits. The improvement of litter size (LS) at birth by two-stage selection for ovulation rate (OR) and LS could modify survival rate from birth to slaughter. This study was aiming to estimate direct and correlated response on LS traits and peri- and postnatal survival traits in the OR_LS rabbit line selected first only for OR (first period) and then for OR and LS using independent culling levels (second period). The studied traits were OR, LS measured as number of total born, number of kits born alive (NBA) and dead (NBD), and number of kits at weaning (NW) and young rabbits at slaughter (NS). Prenatal survival (LS/OR) and survival at birth (NBA/LS), at weaning (NW/NBA) and at slaughter (NS/NW) were also studied. Data were analysed using Bayesian inference methods. Heritability for LS traits were low, 0.07 for NBA, NW and NS. Survival traits had low values of heritability 0.07, 0.03 and 0.03 for NBA/LS, NW/NBA and NS/NW, respectively. After six generations of selection by OR (first period), a small increase in NBD and a slight decrease in NBA/LS were found. However, no correlated responses on NW/NBA and NS/NW were observed. After 11 generations of two-stage selection for OR and LS (second period), correlated responses on NBA, NW and NS were 0.12, 0.12 and 0.11 kits per generation, respectively, whereas no substantial modifications on NBA/LS, NW/NBA and NS/NW were found. In conclusion, two-stage selection improves the number of young rabbits at slaughter without modifying survival from birth to slaughter.This study was supported by the Ministerio de Economia y Competitividad (AGL2014-55921-C2-1-P) and by funds from Generalitat Valenciana research programme (Prometeo 2009/125). A.Y.B. was supported by a grant of the Egyptian Ministry of Higher Education.Badawy Elmoghazy, AY.; Peiró Barber, RM.; Blasco Mateu, A.; Santacreu Jerez, MA. (2019). Correlated responses on litter size traits and survival traits after two-stage selection for ovulation rate and litter size in rabbits. Animal. 13(3):453-459. https://doi.org/10.1017/S1751731118002033S453459133Ziadi, C., Mocé, M. L., Laborda, P., Blasco, A., & Santacreu, M. A. (2013). Genetic selection for ovulation rate and litter size in rabbits: Estimation of genetic parameters and direct and correlated responses1. Journal of Animal Science, 91(7), 3113-3120. doi:10.2527/jas.2012-6043Su, G., Lund, M. S., & Sorensen, D. (2007). Selection for litter size at day five to improve litter size at weaning and piglet survival rate1. Journal of Animal Science, 85(6), 1385-1392. doi:10.2527/jas.2006-631Ruíz-Flores, A., & Johnson, R. K. (2001). 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Genetic parameters for piglet survival, litter size and birth weight or its variation within litter in sire and dam lines using Bayesian analysis. Livestock Science, 135(2-3), 215-224. doi:10.1016/j.livsci.2010.07.005Johnson, R. K., Nielsen, M. K., & Casey, D. S. (1999). Responses in ovulation rate, embryonal survival, and litter traits in swine to 14 generations of selection to increase litter size. Journal of Animal Science, 77(3), 541. doi:10.2527/1999.773541xBlasco, A. (2017). Bayesian Data Analysis for Animal Scientists. doi:10.1007/978-3-319-54274-4Argente, M. J., Santacreu, M. A., Climent, A., & Blasco, A. (2006). Influence of available uterine space per fetus on fetal development and prenatal survival in rabbits selected for uterine capacity. Livestock Science, 102(1-2), 83-91. doi:10.1016/j.livprodsci.2005.11.022Laborda, P., Santacreu, M. A., Blasco, A., & Mocé, M. L. (2012). Selection for ovulation rate in rabbits: Direct and correlated responses estimated with a cryopreserved control population1. Journal of Animal Science, 90(10), 3392-3397. doi:10.2527/jas.2011-4837Arango, J., Misztal, I., Tsuruta, S., Culbertson, M., & Herring, W. (2005). Threshold-linear estimation of genetic parameters for farrowing mortality, litter size, and test performance of Large White sows. Journal of Animal Science, 83(3), 499-506. doi:10.2527/2005.833499xPeiró, R., Herrler, A., Santacreu, M. A., Merchán, M., Argente, M. J., García, M. L., … Blasco, A. (2010). Expression of progesterone receptor related to the polymorphism in the PGR gene in the rabbit reproductive tract1. Journal of Animal Science, 88(2), 421-427. doi:10.2527/jas.2009-1955Cartuche, L., Pascual, M., Gómez, E. A., & Blasco, A. (2014). Economic weights in rabbit meat production. World Rabbit Science, 22(3), 165. doi:10.4995/wrs.2014.1747Putz, A. M., Tiezzi, F., Maltecca, C., Gray, K. A., & Knauer, M. T. (2015). Variance component estimates for alternative litter size traits in swine. Journal of Animal Science, 93(11), 5153-5163. doi:10.2527/jas.2015-9416Cunningham, P. J., England, M. E., Young, L. D., & Zimmerman, D. R. (1979). Selection for Ovulation Rate in Swine: Correlated Response in Litter Size and Weight. Journal of Animal Science, 48(3), 509-516. doi:10.2527/jas1979.483509xGarcı́a, M. L., & Baselga, M. (2002). Estimation of genetic response to selection in litter size of rabbits using a cryopreserved control population. Livestock Production Science, 74(1), 45-53. doi:10.1016/s0301-6226(01)00280-9Damgaard, L. H., Rydhmer, L., Løvendahl, P., & Grandinson, K. (2003). Genetic parameters for within-litter variation in piglet birth weight and change in within-litter variation during suckling1. Journal of Animal Science, 81(3), 604-610. doi:10.2527/2003.813604xSantacreu, 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 population1. Journal of Animal Science, 83(10), 2303-2307. doi:10.2527/2005.83102303xBennett, G. L., & Leymaster, K. A. (1989). Integration of Ovulation Rate, Potential Embryonic Viability and Uterine Capacity into a Model of Litter Size in Swine. Journal of Animal Science, 67(5), 1230. doi:10.2527/jas1989.6751230

Effect of increased ovulation rate on embryo and foetal survival as a model for selection by ovulation rate in rabbits

[EN] Selection for ovulation rate in prolific species has not improved litter size, due to an increase in prenatal mortality, with most mortality observed in the foetal period. The aim of this study was to investigate the magnitude and timing of embryo and early foetal survival in females with high ovulation rate using hormonal treatment as a model for selection by ovulation rate. Two groups of females (treated and untreated) were used. Treated females were injected with 50 IU equine chorionic gonadotropin 48 h before mating. Females were slaughtered at 18 d of gestation. Ovulation rate (OR), number of implanted embryos (IE), number of live foetuses at 12 and 18 d (LF12 and LF18, respectively) were recorded. In addition, embryo survival (ES=IE/OR), foetal survival at 18 d of gestation (FSLF18=LF18/IE), foetal survival between 12 and 18 d of gestation (FSLF18/LF12=LF18/LF12) and prenatal survival (PSLF18=LF18/OR) were estimated. For each female, the mean and variability of the weight for live foetuses (LFWm and LFWv, respectively) and their placentas (LFPWm and LFPWv, respectively) were calculated. Treated females had a higher ovulation rate (+3.02 ova) than untreated females, with a probability of 0.99. An increase in the differences (D) between treated and untreated females was observed from implantation to 18 d of gestation (D=–0.33, –0.70 and –1.28 for IE, LF12 and LF18, respectively). These differences had a low accuracy and the probability that treated females would have a lower number of foetuses also increased throughout gestation (0.60, 0.70 and 0.86 for IE, LF12 and LF18, respectively). According to the previous results for OR and LF18, treated females showed a lower survival rate from ovulation to 18 d of gestation (D=–0.12, P=0.98 for PSLF18). Treated females also had lower embryo and foetal survival (D=–0.10 and P=0.94 for ES and D=–0.08 and P=0.93 for FSLF18). Main differences in foetal survival appeared from 12 to 18 d of gestation (D=–0.09 and P=0.98 for FSLF18/LF12). Unexpectedly, treated females showed similar foetus weight and higher foetal placenta weight than untreated females (D=0.25 g, P=0.98) and lower variability for these traits (D=–0.02 g, P=0.72 for LFWv and D=–0.05 g, P=0.83 for LFPWv). These results are not related to a lower number of IE or LF18. Thus, the effect of increasing by three ova in rabbits leads to a lower embryo and early foetal survival. There seems to be no relationship between foetal mortality and foetus weight.This study was supported by the Comision Interministerial de Ciencia y Tecnologia CICYT- AGL2011-29831-C03-01 and by funds from Generalitat Valenciana research programme (Prometeo 2009/125). A.Y. Badawy was supported by a grant of the Egyptian Ministry of Higher Education.Badawy, A.; Peiro, R.; Blasco Mateu, A.; Santacreu Jerez, MA. (2016). Effect of increased ovulation rate on embryo and foetal survival as a model for selection by ovulation rate in rabbits. World Rabbit Science. 24(2):87-94. https://doi.org/10.4995/wrs.2016.3992879424

Inflammatory correlated response in two lines of rabbit selected divergently for litter size environmental variability

[EN] Animal welfare is a priority objective for the livestock industry. Litter size environmental variability has been related to environmental sensitivity. A divergent selection experiment for environmental variance of litter size variance was carried out successfully in rabbits over thirteen generations. The low line showed a lower inflammatory response and susceptibility to infectious disorders than the high line. In conclusion, the decrease of environmental sensitivity seems to increase the adaptation of the animal to the environment, and thus, its welfare.This research was supported by Projects AGL2017-86083, C2-1-P and C2-2-P, funded by Ministerio de Ciencia e Innovacion (MIC)-Agencia Estatal de Investigacion (AEI) and el Fondo Europeo de Desarrollo Regional (FEDER) "Una manera de hacer Europa" and Project AICO/2019/169 funded by Valencia Regional Government.Beloumi, D.; Blasco Mateu, A.; Muelas, R.; Santacreu Jerez, MA.; García, MDLL.; Argente, M. (2020). 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Autoimmunity Reviews, 10(7), 369-374. doi:10.1016/j.autrev.2010.12.006Del Giudice, M., & Gangestad, S. W. (2018). Rethinking IL-6 and CRP: Why they are more than inflammatory biomarkers, and why it matters. Brain, Behavior, and Immunity, 70, 61-75. doi:10.1016/j.bbi.2018.02.013Lockwood, K. G., Marsland, A. L., Cohen, S., & Gianaros, P. J. (2016). Sex differences in the association between stressor-evoked interleukin-6 reactivity and C-reactive protein. Brain, Behavior, and Immunity, 58, 173-180. doi:10.1016/j.bbi.2016.07.001Haran, J., Gardiner, F., & Suner, S. (2012). Correlation of C-reactive protein to severity of symptoms in acute influenza A infection. Journal of Emergencies, Trauma, and Shock, 5(2), 149. doi:10.4103/0974-2700.96484Shrotriya, S., Walsh, D., Nowacki, A. S., Lorton, C., Aktas, A., Hullihen, B., … Estfan, B. (2018). Serum C-reactive protein is an important and powerful prognostic biomarker in most adult solid tumors. PLOS ONE, 13(8), e0202555. doi:10.1371/journal.pone.0202555Chen, W., Zheng, K. I., Liu, S., Yan, Z., Xu, C., & Qiao, Z. (2020). Plasma CRP level is positively associated with the severity of COVID-19. Annals of Clinical Microbiology and Antimicrobials, 19(1). doi:10.1186/s12941-020-00362-2Stoner, L., Lucero, A. A., Palmer, B. R., Jones, L. M., Young, J. M., & Faulkner, J. (2013). Inflammatory biomarkers for predicting cardiovascular disease. Clinical Biochemistry, 46(15), 1353-1371. doi:10.1016/j.clinbiochem.2013.05.070Iung, L. H. de S., Carvalheiro, R., Neves, H. H. de R., & Mulder, H. A. (2019). Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review. Journal of Animal Breeding and Genetics, 137(3), 263-280. doi:10.1111/jbg.12454Blasco, A., Martínez-Álvaro, M., García, M.-L., Ibáñez-Escriche, N., & Argente, M.-J. (2017). Selection for environmental variance of litter size in rabbits. Genetics Selection Evolution, 49(1). doi:10.1186/s12711-017-0323-4Argente, 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(10), 2348-2355. doi:10.1017/s1751731119000302Leineweber, C., Müller, E., & Marschang, R. E. (2018). Blood reference intervals for rabbits (Oryctolagus cuniculus) from routine diagnostic samples. Tierärztliche Praxis Ausgabe K: Kleintiere / Heimtiere, 46(06), 393-398. doi:10.1055/s-0038-1677403Mbanasor, U. U., Anene, B. M., Chime, A. B., Nnaji, T. O., Eze, J. I., & Ezekwe, A. G. (2003). Haematology of normal and trypanosome infected Muturu cattle in southeastern Nigeria. Nigerian Journal of Animal Production, 30(2). doi:10.4314/njap.v30i2.3300Moore, D. M., Zimmerman, K., & Smith, S. A. (2015). Hematological Assessment in Pet Rabbits. 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Oxidative Stress and NLRP3-Inflammasome Activity as Significant Drivers of Diabetic Cardiovascular Complications: Therapeutic Implications. Frontiers in Physiology, 9. doi:10.3389/fphys.2018.00114Fan, J., Kitajima, S., Watanabe, T., Xu, J., Zhang, J., Liu, E., & Chen, Y. E. (2015). Rabbit models for the study of human atherosclerosis: From pathophysiological mechanisms to translational medicine. Pharmacology & Therapeutics, 146, 104-119. doi:10.1016/j.pharmthera.2014.09.009Zhao, X., Li, L., Li, X., Li, J., Wang, D., & Zhang, H. (2019). The Relationship between Serum Bilirubin and Inflammatory Bowel Disease. Mediators of Inflammation, 2019, 1-7. doi:10.1155/2019/5256460Inoguchi, T., Sonoda, N., & Maeda, Y. (2016). Bilirubin as an important physiological modulator of oxidative stress and chronic inflammation in metabolic syndrome and diabetes: a new aspect on old molecule. Diabetology International, 7(4), 338-341. doi:10.1007/s13340-016-0288-5Koenig, G., & Seneff, S. (2015). Gamma-Glutamyltransferase: A Predictive Biomarker of Cellular Antioxidant Inadequacy and Disease Risk. Disease Markers, 2015, 1-18. doi:10.1155/2015/818570Kim, W. R., Flamm, S. L., Di Bisceglie, A. M., & Bodenheimer, H. C. (2008). Serum activity of alanine aminotransferase (ALT) as an indicator of health and disease. Hepatology, 47(4), 1363-1370. doi:10.1002/hep.22109Dirksen, K., Verzijl, T., van den Ingh, T. S. G. A. M., Vernooij, J. C. M., van der Laan, L. J. W., Burgener, I. A., … Fieten, H. (2016). Hepatocyte-derived microRNAs as sensitive serum biomarkers of hepatocellular injury in Labrador retrievers. The Veterinary Journal, 211, 75-81. doi:10.1016/j.tvjl.2016.01.010Casto-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. Genetics Selection Evolution, 52(1). doi:10.1186/s12711-020-00542-

Identification of differentially expressed genes in the oviduct of two rabbit lines divergently selected for uterine capacity using suppression subtractive hybridization

This is the accepted version of the following article: Ballester, M.; Castelló, A.; Peiró Barber, RM.; Argente, M. J.;Santacreu Jerez, MA.; 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. Animal Genetics. 44:296-304. doi:10.1111/AGE.12005. , which has been published in final form at http://dx.doi.org/10.1111/age.12005.[EN] Suppressive subtractive hybridization libraries from oviduct at 62h post-mating of two lines of rabbits divergently selected for uterine capacity were generated to identify differentially expressed genes. A total of 438 singletons and 126 contigs were obtained by cluster assembly and sequence alignment of 704 expressed sequence tags (ESTs), of which 54% showed homology to known proteins of the non-redundant NCBI databases. Differential screening by dot blot validated 71 ESTs, of which 47 showed similarity to known genes. Transcripts of genes were functionally annotated in the molecular function and the biological process gene ontology categories using the blast2go software and were assigned to reproductive developmental process, immune response, amino acid metabolism and degradation, response to stress and apoptosis terms. Finally, three interesting genes, PGR, HSD17B4 and ERO1L, were identified as overexpressed in the low line using RT-qPCR. Our study provides a list of candidate genes that can be useful to understanding the molecular mechanisms underlying the phenotypic differences observed in early embryo survival and development traits.We would like to thank Henry Cardona Cadavid for help in the sequencing. This study was funded with project AGL2005-07624-C03.Ballester Devis, M.; Castelló Farre, A.; Peiró Barber, RM.; Argente, MJ.; Santacreu Jerez, MA.; Folch, JM. (2013). Identification of differentially expressed genes in the oviduct of two rabbit lines divergently selected for uterine capacity using suppression subtractive hybridization. Animal Genetics. 44:296-304. https://doi.org/10.1111/AGE.12005S2963044

The effect of unilateral ovariectomy on early embryonic survival and embryo development in rabbits

[EN] Unilateral ovariectomy can be used to study uterine capacity in rabbits because an overcrowding of the functional uterine horn is produced. Due to the uterus duplex, the rabbit is the ideal model for such studies. However, this technique may affect embryo survival. The aim of this work is to study the effect of unilateral ovariectomy on early embryo survival and development in rabbit. A total of 101 unilateral ovariectomised females and 52 intact females were compared after slaughter at 30 h post-mating. Early embryo survival was estimated as the ratio between number of embryo recovered and ovulation rate. No differences were found between intact and unilaterally ovariectomised females in this trait. Unilateral ovariectomy did not change embryo development, measured as the number of embryo cells. Variability of embryo development was not affected either. At 30 h post-mating, the majority of embryos (86.2%) were 4-cell stage. Embryo quality was evaluated according to morphological criteria. No difference in embryo quality between intact and unilaterally ovariectomised females was found. Therefore, unilateral ovariectomy performed before puberty in rabbit does not modify early embryo survival and development.This experiment was supported by the Interministerial Commission for Science and Technology (AGL2005-07624-C03-01 and AGL2008-05514-C02-01).Peiró Barber, RM.; Gallego, M.; Blasco Mateu, A.; Santacreu Jerez, MA. (2014). The effect of unilateral ovariectomy on early embryonic survival and embryo development in rabbits. World Rabbit Science. 22(2):123-127. https://doi.org/10.4995/wrs.2014.2105SWORD12312722

Effect of divergent selection for uterine capacity on embryonic survival and development at 30 h post-mating in unilaterally ovariectomized rabbit females

[EN] Uterine capacity has been proposed as an indirect way to increase litter size. The aim of this work is to study the effect of a divergent selection for uterine capacity (UC) on reproductive traits at 30 h post mating in unilaterally ovariectomized (ULO) females. A total of 62 ULO females from the high line (selected to increase UC) and 39 ULO females from the low line (selected to decrease UC) were used. Ovulation rate was estimated as the number of corpora haemorrhagica and early embryonic survival was estimated as the ratio between number of embryos and ovulation rate. No differences in ovulation rate and early embryonic survival at 30 h post mating were found between high and low lines. Selection for UC did not change the embryonic stage of development either, the majority of embryos being at 4-cell stage. Additionally, the embryos were evaluated according to morphological criteria and more than 95% of the embryos were evaluated as good or fair quality. No differences in embryonic morphological criteria between high and low lines were found either. Thus, selection for UC did not modify the early embryonic survival and development in ULO females at 30 h post mating.This experiment was supported by the Comision Interministerial de Ciencia y Tecnologia (AGL2005-07624-C03-01 and AGL2008-05514-C02-01).Peiró Barber, RM.; Gallego, M.; Blasco Mateu, A.; Santacreu Jerez, MA. (2015). Effect of divergent selection for uterine capacity on embryonic survival and development at 30 h post-mating in unilaterally ovariectomized rabbit females. World Rabbit Science. 23(4):241-215. https://doi.org/10.4995/wrs.2015.3592SWORD24121523

Genomic regions influencing intramuscular fat in divergently selected rabbit lines

[EN] Intramuscular fat (IMF) is one of the main meat quality traits for breeding programs in livestock species. The main objective of this study was to identify genomic regions associated with IMF content comparing two rabbit populations divergently selected for this trait, and to generate a list of putative candidate genes. Animals were genotyped using the Affymetrix Axiom OrcunSNP Array (200k). After quality control, the data involved 477 animals and 93,540 single nucleotide polymorphisms (SNPs). Two methods were used in this research: single marker regressions with the data adjusted by genomic relatedness, and a Bayesian multi-marker regression. Associated genomic regions were located on the rabbit chromosomes (OCU) OCU1, OCU8 and OCU13. The highest value for the percentage of the genomic variance explained by a genomic region was found in two consecutive genomic windows on OCU8 (7.34%). Genes in the associated regions of OCU1 and OCU8 presented biological functions related to the control of adipose cell function, lipid binding, transportation and localization (APOLD1, PLBD1, PDE6H, GPRC5D, and GPRC5A) and lipid metabolic processes (MTMR2). The EWSR1 gene, underlying the OCU13 region, is linked to the development of brown adipocytes. The findings suggest that there is a large component of polygenic effect behind the differences in IMF content in these two lines, as the variance explained by most of the windows was low. The genomic regions of OCU1, OCU8 and OCU13 revealed novel candidate genes. Further studies would be needed to validate the associations and explore their possible application in selection programs.The work was funded by project AGL2014-55921-C2-1-P from National Programme for Fostering Excellence in Scientific and Technical Research -Project I+D. BSS was supported by a FPI grant from the Ministry of Economy and Competitiveness of Spain+ (BES-2015-074194). NIB was supported with a "Ramon y Cajal" grant provided by Ministerio de Ciencia e Innovacion (RYC-2016-19764). CSH and PN were supported by the Medical Research Council (United kingdom, grants MC_PC_U127592696 and MC_PC_U127561128). CSH was supported by Biotechnology and Biological Sciences Research Council (United Kingdom, Grant/Award Number: BBS/E/D/30002276).Sosa-Madrid, BS.; Hernández, P.; Blasco Mateu, A.; Haley, CS.; Fontanesi, L.; Santacreu Jerez, MA.; Pena, RN.... (2020). Genomic regions influencing intramuscular fat in divergently selected rabbit lines. Animal Genetics. 51:58-69. https://doi.org/10.1111/age.12873586951Aken, B. L., Ayling, S., Barrell, D., Clarke, L., Curwen, V., Fairley, S., … Searle, S. M. J. (2016). The Ensembl gene annotation system. Database, 2016, baw093. doi:10.1093/database/baw093Aloulou, A., Ali, Y. B., Bezzine, S., Gargouri, Y., & Gelb, M. 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