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Apeldoorn, Netherlands

Siwek M.,University of Technology and Life Sciences in Bydgoszcz | Slawinska A.,University of Technology and Life Sciences in Bydgoszcz | Nieuwland M.,Wageningen University | Witkowski A.,Lublin University of Life Sciences | And 4 more authors.
Poultry Science | Year: 2010

A QTL involved in the primary antibody response toward keyhole limpet hemocyanin (KLH) was detected on chicken chromosome 14 in the experimental population, which was created by crossing commercial White Leghorn and a Polish native chicken breed (green-legged partridgelike). The current QTL location is a validation of previous experiments pointing to the same genomic location for the QTL linked to a primary antibody response to KLH. An experimental population was typed with microsatellite markers distributed over the chicken chromosome 14. Titers of antibodies binding KLH were measured for all individuals by ELISA. Statistical models applied in the Grid QTL Web-based software were used to analyze the data: a half-sib model, a line-cross model, and combined analysis in a linkage disequilibrium and linkage analysis model. Candidate genes that have been proposed were genotyped with SNP located in genes exons. Statistical analyses of single SNP associations were performed pointing out 2 SNP of an axis inhibitor protein (AXIN1) gene as significantly associated with the trait of an interest. © 2010 Poultry Science Association Inc. Source


De Oliveira Junior G.M.,Federal University of Vicosa | Ferreira A.S.,Federal University of Vicosa | Oliveira R.F.M.,Federal University of Vicosa | Silva B.A.N.,Institute for Pig Genetics bv IPG | And 2 more authors.
Livestock Science | Year: 2011

Thirty mixed-parity Landrace × Large White sows were used to evaluate the effects of the type of farrowing room on 28-day lactation behaviour under tropical conditions during summer. The sows were allocated in a completely randomised design with three treatments with 10 replicates according to parity number and body weight, with each animal being considered an experimental unit. The treatments consisted of a conventional farrowing room (T1); a conventional farrowing room with floor cooling under the sow (T2); and a semi-outdoor farrowing room without a cage and with access to a fenced field (T3). The sows from T1 and T2 groups were exposed to mean maximum and minimum environmental temperatures of 25.7 and 21.0. °C, respectively, and the sows from the T3 group to average maximum and minimum environmental temperatures of 26.5 and 20.7. °C, respectively. The feed consumption of T3 sows was numerically higher than the T1 and T2 sows (+. 9.5% on average). The body-weight loss was influenced at 28 days (P<. 0.10) by treatment, being that the T3 sows gained weight (+. 4.7. kg) while the T1 and T2 sows lost weight (- 11.9 and - 3.7. kg, respectively for T1 and T2). The T3 sows showed a higher percentual litter mortality than the T1 and T2 sows (3.2% vs. 0% vs. 7.8%, respectively for T1, T2 and T3 sows). From farrowing until day 28 of lactation, the T2 and T3 sows showed higher lactation efficiency when compared with the T1 sows (72% vs. 87% vs. 88%, respectively for T1, T2 and T3 sows). The T1 sows showed higher (P<. 0.01) frequencies of visits to the feeder and drinker (+. 38% on average). The T3 sows spent more time (P<. 0.01) at the drinker than T1 and T2 sows (23 vs. 23 vs. 32 min, respectively for T1, T2 and T3 sows). The T3 sows showed a higher (P<. 0.10) frequency of nursing than the other treatments (+. 15% on average). T1 and T2 sows were found to spend more time (P<. 0.01) performing other postures during 24 h than sows maintained in T3 (50 vs. 51 vs. 22 min/d, respectively for T1, T2 and T3). It is concluded that cooling of the floor under the sow in the conventional farrowing room or the use of semi-outdoor farrowing rooms improves the thermal environment and the lactation efficiency of the sows housed in hot ambient temperatures at 28-day lactation in the summer period, indicating an improved welfare. © 2011 Elsevier B.V. Source


Silva K.M.,Federal University of Vicosa | Bastiaansen J.W.M.,Wageningen University | Knol E.F.,Institute for Pig Genetics bv IPG | Merks J.W.M.,Institute for Pig Genetics bv IPG | And 5 more authors.
Animal Genetics | Year: 2011

Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this study, we performed a meta-analysis of QTL on chromosome 4 in pig, using data from 25 separate experiments. First, a meta-analysis was performed for individual traits: average daily gain and backfat thickness. Second, a meta-analysis was performed for the QTL of three traits affecting loin yield: loin eye area, carcass length and loin meat weight. Third, 78 QTL were selected from 20 traits that could be assigned to one of three broad categories: carcass, fatness or growth traits. For each analysis, the number of identified meta-QTL was smaller than the number of initial QTL. The reduction in the number of QTL ranged from 71% to 86% compared to the total number before the meta-analysis. In addition, the meta-analysis reduced the QTL confidence intervals by as much as 85% compared to individual QTL estimates. The reduction in the confidence interval was greater when a large number of independent QTL was included in the meta-analysis. Meta-QTL related to growth and fatness were found in the same region as the FAT1 region. Results indicate that the meta-analysis is an efficient strategy to estimate the number and refine the positions of QTL when QTL estimates are available from multiple populations and experiments. This strategy can be used to better target further studies such as the selection of candidate genes related to trait variation. © 2010 Stichting International Foundation for Animal Genetics. Source


Harlizius B.,Institute for Pig Genetics bv IPG | Lopes M.S.,Federal University of Vicosa | Duijvesteijn N.,Institute for Pig Genetics bv IPG | van de Goor L.H.P.,Dr. Van Haeringen Laboratorium B.V. | And 5 more authors.
Journal of Animal Science | Year: 2011

In animal breeding, recording of correct pedigrees is essential to achieve genetic progress. Markers on DNA are useful to verify the on-farm pedigree records (parental verification) but can also be used to assign parents retrospectively (parental identification). This approach could reduce the costs of recording for traits with low incidence, such as those related to diseases or mortality. In this study, SNP were used to assign the true sires of 368 purebred animals from a Duroc-based sire line and 140 crossbred offspring from a commercial pig population. Some of the sires were closely related. There were 3 full sibs and 17 half sibs among the true fathers and 4 full sibs and 35 half sibs among all putative fathers. To define the number of SNP necessary, 5 SNP panels (40, 60, 80, 100, and 120 SNP) were assembled from the Illumina PorcineSNP60 Beadchip (Illumina, San Diego, CA) based on minor allele frequency (>0.3), high genotyping call rate (≥90%), and equal spacing across the genome. For paternal identification considering only the 66 true sires in the data set, 60 SNP resulted in 100% correct assignment of the sire. By including additional putative sires (n = 304), 80 SNP were sufficient for 100% correct assignment of the sire. The following criteria were derived to identify the correct sire for the current data set: the logarithm of odds (LOD) score for assigning the correct sire was ≥5, the number of mismatches was ≥1, and the difference in the LOD score between the first and the second most likely sire was >5. If the correct sire was not present among all putative sires, the mean LOD for the most likely sire was close to zero or negative when using 100 SNP. More SNP would be needed for paternal identification if the number of putative sires increased and the degree of relatedness was greater than in the data set used here. The threshold for the number of mismatches can be adjusted according to the practical situation to account for the tradeoff between false negatives and false positives. The latter can be avoided efficiently, ensuring that the correct father is being sampled. Nevertheless, a restriction on the number of putative sires is advisable to reduce the risk of assigning close relatives. © 2011 American Society of Animal Science. All rights reserved. Source


Broekhuijse M.L.W.J.,University Utrecht | Sostaric E.,University Utrecht | Feitsma H.,Institute for Pig Genetics bv IPG | Gadella B.M.,University Utrecht
Journal of Animal Science | Year: 2012

Sperm quality is often evaluated through computer-assisted semen analysis (CASA) and is an indicator of boar fertility. The aim of this research was to study the relationship between CASA motility parameters and fertility results in pigs. Insemination records and semen parameters from a total of 45,532 ejaculates collected over a 3-yr period were used. The statistical model for analysis of fertility data from these inseminations included factors related to sow productivity. The boar-and semen-related variance (direct boar effect) were corrected for the effects of individual boar, genetic line of the boar, age of the boar, days between ejaculations, number of sperm cells in an ejaculate, number of sperm cells in an insemination dose, and AI station. The remaining variance was analyzed if semen motility parameters had a significant effect. This analysis revealed significant (P < 0.05) effects of progressive motility, velocity curvilinear, and beat cross frequency on farrowing rate (FR). Total motility, velocity average path, velocity straight line, and amplitude of lateral head displacement affected (P < 0.05) total number of piglets born (TNB). Boar-and semen-related parameters explained 5.3% of the variation in FR and 5.9% of the variation in TNB. Motility parameters, measured by CASA, explained 9% of the boar-and semen-related variation in FR and 10% of the boar-and semen-related variation in TNB. Individual boar and genetic line of the boar affected (P < 0.0001) the variation in FR and TNB. No differences (P > 0.05) were observed between effects of AI stations on fertility outcome, underscoring the objectivity of the CASA system used. Motility parameters can be measured with CASA to assess sperm motility in an objective manner. On the basis of the motility pattern, CASA enables one to discriminate between the fertilizing capacity of ejaculates, although this depends on the genetic line of the boar used in AI stations. © 2012 American Society of Animal Science. All rights reserved. Source

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