125,344 research outputs found
Rafferty, N J, NX52435
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/412190Surname: RAFFERTY. Given Name(s) or Initials: N J. Military Service Number or Last Known Location: NX52435. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 18262.228685
Item: [2016.0049.44453] "Rafferty, N J, NX52435
Integrating three genetic dimensions relating to piglet birth weight: direct and maternal effects on the mean and genetic control of residual variance
No full textCredit authorship contribution statement
E. Sell-Kubiak: Writing – review & editing, Writing – original draft, Validation, Conceptualisation. C. Kasper: Writing – review & editing, Visualisation, Resources, Investigation, Data curation, Conceptualisation. A. Lepori: Writing – review & editing, Resources, Investigation, Data curation. J.P. Gutiérrez: Writing – review & editing, Writing – original draft, Visualisation, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualisation. N. Formoso-Rafferty: Writing – review & editing, Writing – original draft, Visualisation, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualisation. N. Khayatzadeh: Writing – review & editing, Resources, Data curation. I. Cervantes: Writing – review & editing, Writing – original draft, Visualisation, Validation, Supervision, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualisation.The uniformity of production traits is desired for different traits in livestock species, including the uniformity of within-litter birth weight (BW) in piglets. In pigs, BW is associated with increased vitality and survival until weaning. However, as the uniformity of the BW increases, the importance of the initial weight decreases as competition between piglets decreases. The aim of this study was to estimate the direct and maternal genetic components of BW, jointly with the maternal genetic component of the residual variance for within-litter BW, and their genetic correlations. We used two distinct datasets of Swiss Large White pigs: (1) an experimental farm dataset, and (2) a commercial farm dataset, comprising 43 135 and 23 313 records of individual piglet BW, respectively. A heteroscedastic model was used for the statistical analysis. This model assumes that both the mean BW and the residual variance are affected by systematic and random effects, with the residual variance being heterogeneous and partially under genetic control. In the most complex models, which included both genetic effects for the mean trait, the results indicated that direct genetic effects or correlations with such effects were negligible. The genetic component of the residual variance for BW ranged from 0.0712 to 0.1246 for the experimental farm and from 0.0371 to 0.0994 for the commercial farms. The genetic correlation between the mean BW and BW variability was always positive, ranging from 0.1492 to 0.3069 for the experimental farm and from 0.2197 to 0.5892 for the commercial farms. Thus, it is sufficient to model mean BW and BW variability by including only the maternal genetic effect for both traits. In addition, although moderate genetic correlations existed between the within-litter mean BW and BW variability, focusing on BW uniformity within litters would be preferable in simultaneously creating a selection index for both traits.University of Life Sciences, Poland.Ministerio de Innovación y Universidades (España()Depto. de Producción AnimalFac. de VeterinariaTRUEpu
N. D. Donnelly, Changing Lives of Refugee Hmong Women
No full textFormoso Bernard. N. D. Donnelly, Changing Lives of Refugee Hmong Women. In: L'Homme, 1996, tome 36 n°140. pp. 169-172
Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice
No full text[EN] Data from seven generations of a divergent selection experiment designed for environmental variability of birth weight were analysed to estimate genetic parameters and to explore signs of selection response. A total of 10 783 birth weight records from 638 females and 1127 litters in combination with 10 007 pedigree records were used. Each record of birth weight was assigned to the mother of the pup in a heteroscedastic model, and after seven generations of selection, evidence of success in the selection process was shown. A Bayesian analysis showed that success of the selection process started from the first generation for birth weight and from the second generation for its environmental variability. Genetic parameters were estimated across generations. However, only from the third generation onwards were the records useful to consider the results to be reliable. The results showed a consistent positive and low genetic correlation between the birth weight trait and its environmental variability, which could allow an independent selection process. This study has demonstrated that the genetic control of the birth weight environmental variability is possible in mice. Nevertheless, before the results are applied directly in farm animals, it would be worth confirming any other implications on other important traits, such as robustness, longevity and welfare.This manuscript was partially funded by a grant from the Spanish Government (AGL2008-00794). The experiment will be continued with partial funding of Feed-agene and a grant from MEC- INIA (RTA2014- 00015-C02-01)Formoso-Rafferty, N.; Cervantes, I.; Ibañez Escriche, N.; Gutiérrez, J. (2016). Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice. Journal of Animal Breeding and Genetics. 133(3):227-237. https://doi.org/10.1111/jbg.12174S227237133
Modulating birth weight heritability in mice
No full text[EN] Expected genetic response is proportional to the heritability of the trait, and this parameter is considered inherent of a specific trait in a particular population. However, models assuming heterogeneity in residual variance lead to different estimates of heritability across combinations of systematic (environmental) effects. Modifying the residual variance of the birth weight by artificial selection was shown to be feasible in a divergent selection experiment in mice. The objectives of this work were to 1) estimate the evolution of the heritability of birth weight in mice in the mentioned experiment, and 2) estimate different heritability regarding systematic effects. Data came from eleven generations of a divergent selection experiment to modify the residual variability of birth weight in mice. A total of 15,431 birth weight records from 959 females and 1,641 litters in combination with 14,786 pedigree records were used. The model used for analysis included generation, litter size, sex, and parity number as systematic effects. Each record of birth weight was assigned to the mother of the pup in the model which assumes that the residual variance is heterogeneous and partially under genetic control. Differences in heritability between lines reached values of 0.06 in the last generations. Choosing the most extreme values of systematic effects, the birth weight heritability ranged from 0.04 to 0.22. From these results, the possibility of modulating the heritability for this trait could be explored in 1 of 2 ways: selecting to decrease the residual variability, or choosing the specific levels of the systematic effects.This research has been conducted with a partial funding through a project MEC-INIA (RTA2014-00015-C02-02).This experiment was partially funded by a grant from the Spanish Government (AGL2008 00794).Formoso-Rafferty, N.; Cervantes, I.; Ibañez Escriche, N.; Gutiérrez, J. (2017). Modulating birth weight heritability in mice. Journal of Animal Science. 95(2):531-537. https://doi.org/10.2527/jas.2016.1169S531537952Bolet, G., Garreau, H., Joly, T., Theau-Clement, M., Falieres, J., Hurtaud, J., & Bodin, L. (2007). Genetic homogenisation of birth weight in rabbits: Indirect selection response for uterine horn characteristics. Livestock Science, 111(1-2), 28-32. doi:10.1016/j.livsci.2006.11.012Damgaard, 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:10.2527/2003.813604xFernandez, B. J., & Toro, M. A. (1999). The use of mathematical programming to control inbreeding in selection schemes. Journal of Animal Breeding and Genetics, 116(6), 447-466. doi:10.1046/j.1439-0388.1999.00196.xFormoso-Rafferty, N., Cervantes, I., Ibáñez-Escriche, N., & Gutiérrez, J. P. (2015). Genetic control of the environmental variance for birth weight in seven generations of a divergent selection experiment in mice. Journal of Animal Breeding and Genetics, 133(3), 227-237. doi:10.1111/jbg.12174Formoso-Rafferty, N., Cervantes, I., Ibáñez-Escriche, N., & Gutiérrez, J. P. (2016). Correlated genetic trends for production and welfare traits in a mouse population divergently selected for birth weight environmental variability. animal, 10(11), 1770-1777. doi:10.1017/s1751731116000860Garreau, H., Bolet, G., Larzul, C., Robert-Granié, C., Saleil, G., SanCristobal, M., & Bodin, L. (2008). Results of four generations of a canalising selection for rabbit birth weight. Livestock Science, 119(1-3), 55-62. doi:10.1016/j.livsci.2008.02.009Gutiérrez, J., Nieto, B., Piqueras, P., Ibáñez, N., & Salgado, C. (2006). Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics Selection Evolution, 38(5), 445. doi:10.1186/1297-9686-38-5-445Hill, W. G. (1984). On selection among groups with heterogeneous variance. Animal Science, 39(3), 473-477. doi:10.1017/s0003356100032220Ibáñez-Escriche, N., Sorensen, D., Waagepetersen, R., & Blasco, A. (2008). Selection for Environmental Variation: A Statistical Analysis and Power Calculations to Detect Response. Genetics, 180(4), 2209-2226. doi:10.1534/genetics.108.091678Ibáñez-Escriche, N., Garcia, M., & Sorensen, D. (2009). GSEVM v.2: MCMC software to analyze genetically structured environmental variance models. Journal of Animal Breeding and Genetics, 127(3), 249-251. doi:10.1111/j.1439-0388.2009.00846.xJohnson, 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:10.2527/1999.773541xLamberson, W. R., Johnson, R. K., Zimmerman, D. R., & Long, T. E. (1991). Direct responses to selection for increased litter size, decreased age at puberty, or random selection following selection for ovulation rate in swine. Journal of Animal Science, 69(8), 3129. doi:10.2527/1991.6983129xMoreno, A., Ibáñez-Escriche, N., García-Ballesteros, S., Salgado, C., Nieto, B., & Gutiérrez, J. P. (2012). Correlated genetic trend in the environmental variability of weight traits in mice. Livestock Science, 148(1-2), 189-195. doi:10.1016/j.livsci.2012.05.009Robert-Granié, C., Bonaı̈ti, B., Boichard, D., & Barbat, A. (1999). Accounting for variance heterogeneity in French dairy cattle genetic evaluation. Livestock Production Science, 60(2-3), 343-357. doi:10.1016/s0301-6226(99)00105-0Ros, M., Sorensen, D., Waagepetersen, R., Dupont-Nivet, M., SanCristobal, M., Bonnet, J.-C., & Mallard, J. (2004). Evidence for Genetic Control of Adult Weight Plasticity in the Snail Helix aspersa. Genetics, 168(4), 2089-2097. doi:10.1534/genetics.104.032672Ruíz-Flores, A., & Johnson, R. K. (2001). Direct and correlated responses to two-stage selection for ovulation rate and number of fully formed pigs at birth in swine. Journal of Animal Science, 79(9), 2286. doi:10.2527/2001.7992286xSanCristobal-Gaudy, M., Elsen, J.-M., Bodin, L., & Chevalet, C. (1998). Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genetics Selection Evolution, 30(5), 423. doi:10.1186/1297-9686-30-5-423SORENSEN, D., & WAAGEPETERSEN, R. (2003). Normal linear models with genetically structured residual variance heterogeneity: a case study. Genetical Research, 82(3), 207-222. doi:10.1017/s0016672303006426Ziadi, 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. 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Marie-Odile Géraud, Regards sur les Hmong de Guyane française. Les détours d'une tradition.
No full textFormoso Bernard. Marie-Odile Géraud, Regards sur les Hmong de Guyane française. Les détours d'une tradition.. In: Études rurales, n°143-144, 1996. Dieux du sol en Asie, sous la direction de Bernard Formoso . pp. 154-157
Les dieux du sol en Asie : de l'apprivoisement à l'inféodation
No full textFormoso Bernard. Les dieux du sol en Asie : de l'apprivoisement à l'inféodation . In: Études rurales, n°143-144, 1996. Dieux du sol en Asie, sous la direction de Bernard Formoso . pp. 15-26
Estimation of direct and maternal genetic correlation of Birth Weight with its environmental maternal variability in mice
No full textInternational audienceEstimation of direct and maternal genetic correlation of Birth Weight with its environmental maternal variability in mice N. Formoso-Rafferty1, I. Cervantes1, J.P. Gutiérrez1, L. Bodin2 1Universidad Complutense de Madrid, Facultad de Veterinaria, Departamento de Producción Animal, Spain 2 INRA, GenPhySE, Castanet-Tolosan, France [email protected] (Corresponding Author) In polytocous species like pig, rabbit and mice, environmental variability of birth weight (BW) is generally studied assigning each BW record of a litter to the dam and considering that all genetic effects are maternal. However a direct effect might exist and could induce bias in the parameter estimations. In this paper, analyses of genetic parameters for the mean (location) and the variability (dispersion) of BW has been made on mice data from a divergently selection experiment on BW considering maternal genetic effects on the location and on the dispersion of BW together with a direct genetic effect on its location. They were done through a DHGLM procedure implemented in the ASReml software which could deal with both direct and maternal effects and which provided their variances and covariances for the location and the dispersion. The correlation between maternal genetic effects for the BW location and the BW dispersion was positive and confirmed results previously obtained. The new genetic correlation between a direct genetic effect on the location and the maternal genetic effect on the dispersion of BW was also positive. Thus increasing the individual BW, whatever the direct or maternal component concerned by the selection, should be avoided if BW variability is ignor
Estimation of direct and maternal genetic correlation of Birth Weight with its environmental maternal variability in mice
No full textInternational audienceEstimation of direct and maternal genetic correlation of Birth Weight with its environmental maternal variability in mice N. Formoso-Rafferty1, I. Cervantes1, J.P. Gutiérrez1, L. Bodin2 1Universidad Complutense de Madrid, Facultad de Veterinaria, Departamento de Producción Animal, Spain 2 INRA, GenPhySE, Castanet-Tolosan, France [email protected] (Corresponding Author) In polytocous species like pig, rabbit and mice, environmental variability of birth weight (BW) is generally studied assigning each BW record of a litter to the dam and considering that all genetic effects are maternal. However a direct effect might exist and could induce bias in the parameter estimations. In this paper, analyses of genetic parameters for the mean (location) and the variability (dispersion) of BW has been made on mice data from a divergently selection experiment on BW considering maternal genetic effects on the location and on the dispersion of BW together with a direct genetic effect on its location. They were done through a DHGLM procedure implemented in the ASReml software which could deal with both direct and maternal effects and which provided their variances and covariances for the location and the dispersion. The correlation between maternal genetic effects for the BW location and the BW dispersion was positive and confirmed results previously obtained. The new genetic correlation between a direct genetic effect on the location and the maternal genetic effect on the dispersion of BW was also positive. Thus increasing the individual BW, whatever the direct or maternal component concerned by the selection, should be avoided if BW variability is ignor
J. Mckinnon & B. Vienne, eds., Hill Tribes Today
No full textFormoso Bernard. J. Mckinnon & B. Vienne, eds., Hill Tribes Today. In: L'Homme, 1991, tome 31 n°119. pp. 155-157
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