| 319491. |
- Hidal, Sten
(författare)
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Bibeltolkning i den tidiga kyrkan
- 2012
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Ingår i: Svensk Exegetisk Årsbok. - 1100-2298. ; 77, s. 47-54
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 319492. |
- Hidal, Sten
(författare)
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Helmer Ringgren in memoriam
- 2012
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Ingår i: Svensk Exegetisk Årsbok. - 1100-2298. ; 77, s. 255-258
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 319493. |
- Hidalgo, André
(författare)
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Accounting for genetic architecture in single - and multipopulation genomic prediction using weights from genomewide association studies in pigs
- 2016
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Ingår i: Journal of Animal Breeding and Genetics. - : Wiley. - 0931-2668 .- 1439-0388. ; 133, s. 187-196
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Tidskriftsartikel (refereegranskat)abstract
- We studied the effect of including GWAS results on the accuracy of single- and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines (SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accura- cies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accu- racies were higher (0.36 for SL1 and 0.32 for SL3) than in single-popula- tion prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopu- lation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions.
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| 319494. |
- Hidalgo, André
(författare)
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Accuracy of genome-enabled prediction exploring purebred and crossbred pig populations
- 2015
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Ingår i: Journal of Animal Science. - : Oxford University Press (OUP). - 0021-8812 .- 1525-3163. ; 93, s. 4684-4691
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Tidskriftsartikel (refereegranskat)abstract
- Pig breeding companies keep relatively small populations of pure sire and dam lines that are selected to improve the performance of crossbred animals. This design of the pig breeding industry presents challenges to the implementation of genomic selection, which requires large data sets to obtain highly accurate genomic breeding values. The objective of this study was to evaluate the impact of different reference sets (across population and multipopulation) on the accuracy of genomic breeding values in 3 purebred pig populations and to assess the potential of using crossbreed performance in genomic prediction. Data consisted of phenotypes and genotypes on animals from 3 purebred populations (sire line [SL] 1, n = 1,146; SL2, n = 682; and SL3, n = 1,264) and 3 crossbred pig populations (Terminal cross [TER] 1, n = 183; TER2, n = 106; and TER3, n = 177). Animals were genotyped using the Illumina Porcine SNP60 Beadchip. For each purebred population, within-, across-, and multipopulation predictions were considered. In addition, data from the paternal purebred populations were used as a reference set to predict the performance of crossbred animals. Backfat thickness phenotypes were precorrected for fixed effects and subsequently included in the genomic BLUP model. A genomic relationship matrix that accounted for the differences in allele frequencies between lines was implemented. Accuracies of genomic EBV obtained within the 3 different sire lines varied considerably. For within-population prediction, SL1 showed higher values (0.80) than SL2 (0.61) and SL3 (0.67). Multipopulation predictions had accuracies similar to within-population accuracies for the validation in SL1. For SL2 and SL3, the accuracies of multipopulation prediction were similar to the within-population prediction when the reference set was composed by 900 animals (600 of the target line plus 300 of another line). For across-population predictions, the accuracy was mostly close to zero. The accuracies of predicting crossbreed performance were similar for the 3 different crossbred populations (ranging from 0.25 to 0.29). In summary, the differences in accuracy of the within-population scenarios may be due to line divergences in heritability and genetic architecture of the trait. Within- and multipopulation predictions yield similar accuracies. Across-population prediction accuracy was negligible. The moderate accuracy of prediction of crossbreed performance appears to be a result of the relationship between the crossbreed and its parental lines.
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| 319495. |
- Hidalgo, André, et al.
(författare)
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Accuracy of genomic prediction of purebreds for cross bred performance in pigs
- 2016
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Ingår i: Journal of Animal Breeding and Genetics. - : Wiley. - 0931-2668 .- 1439-0388. ; 133, s. 443-451
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Tidskriftsartikel (refereegranskat)abstract
- In pig breeding, as the final product is a cross bred (CB) animal, the goal is to increase the CB performance. This goal requires different strategies for the implementation of genomic selection from what is currently imple- mented in, for example dairy cattle breeding. A good strategy is to esti- mate marker effects on the basis of CB performance and subsequently use them to select pure bred (PB) breeding animals. The objective of our study was to assess empirically the predictive ability (accuracy) of direct geno- mic values of PB for CB performance across two traits using CB and PB genomic and phenotypic data. We studied three scenarios in which genetic merit was predicted within each population, and four scenarios where PB genetic merit for CB performance was predicted based on either CB or a PB training data. Accuracy of prediction of PB genetic merit for CB performance based on CB training data ranged from 0.23 to 0.27 for gestation length (GLE), whereas it ranged from 0.11 to 0.22 for total num- ber of piglets born (TNB). When based on PB training data, it ranged from 0.35 to 0.55 for GLE and from 0.30 to 0.40 for TNB. Our results showed that it is possible to predict PB genetic merit for CB performance using CB training data, but predictive ability was lower than training using PB training data. This result is mainly due to the structure of our data, which had small-to-moderate size of the CB training data set, low relationship between the CB training and the PB validation populations, and a high genetic correlation (0.94 for GLE and 0.90 for TNB) between the studied traits in PB and CB individuals, thus favouring selection on the basis of PB data.
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| 319496. |
- Hidalgo, André, et al.
(författare)
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Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs
- 2015
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Ingår i: Journal of Animal Science. - : Oxford University Press (OUP). - 0021-8812 .- 1525-3163. ; 93, s. 3313-3321
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Tidskriftsartikel (refereegranskat)abstract
- Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.
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| 319497. |
- Hidalgo, André, et al.
(författare)
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Accuracy of predicted genomic breeding values in purebred and crossbred pigs
- 2015
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Ingår i: G3. - : Oxford University Press (OUP). - 2160-1836. ; 5, s. 1575-1583
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Tidskriftsartikel (refereegranskat)abstract
- Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Withinpopulation predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than withinpopulation prediction for the purebred validation set. Accuracy of prediction was very trait-dependent.
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| 319498. |
- Hidalgo, André, et al.
(författare)
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Asian low-androstenone haplotype on pig chromosome 6 does not unfavorably affect production and reproduction traits
- 2014
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Ingår i: Animal Genetics. - : Wiley. - 0268-9146 .- 1365-2052. ; 45, s. 874-877
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Tidskriftsartikel (refereegranskat)abstract
- European pigs that carry Asian haplotypes of a 1.94-Mbp region on pig chromosome 6 have lower levels of androstenone, one of the two main compounds causing boar taint. The objective of our study was to examine potential pleiotropic effects of the Asian low-androstenone haplotypes. A single nucleotide polymorphism marker, rs81308021, distinguishes the Asian from European haplotypes and was used to investigate possible associations of androstenone with production and reproduction traits. Eight traits were available from three European commercial breeds. For the two sow lines studied, a favorable effect on number of teats was detected for the low-androstenone haplotype. In one of these sow lines, a favorable effect on number of spermatozoa per ejaculation was detected for the low-androstenone haplotype. No unfavorable pleiotropic effects were found, which suggests that selection for low-androstenone haplotypes within the 1.94Mbp would not unfavorably affect the other eight relevant traits.
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| 319499. |
- Hidalgo, André
(författare)
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Canonical-correlation analysis applied to selection-index methodology in quails
- 2014
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Ingår i: Livestock Science. - : Elsevier BV. - 1871-1413 .- 1878-0490. ; 169, s. 35-41
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Tidskriftsartikel (refereegranskat)abstract
- Genetic evaluations in dual-purpose quails (Coturnix coturnix) have demonstrated that overall genetic gains in a breeding program are achieved not only based on a specific trait, but on several. The most common technique to use all this information is the selection index. Another alternative may be the canonical-correlation analysis applied to selection index. There is, however, a lack of studies using canonical correlation in quails. Hence, the objectives of this study were to apply canonical-correlation analysis to estimate the relationship of nine traits and to compare genetic gains obtained by this methodology to desired-gain selection index in three lines of quails. Data for three lines of layer quails consisted of body weight at 28 days (W28), egg weight (EW), age at first egg (APE) and egg production at 30, 60, 90, 120, 150 and 180 days after onset of lay. Two sets of traits were established: the first one contained predictor variables (W28, EW and APE) and the second one contained variables related to egg production. A selection index was constructed using the standardized coefficients of canonical covariates as weighting factors when a given canonical correlation was significant. We constructed two desired-gain selection indices: DG-SI1 and DG-S12. The difference between them is that DG-S12 had a desired gain for body weight set to 0. The estimated canonical correlations were as follows: 0.811, 0.058 and 0.003 for the yellow, 0.821, 0.181 and 0.076 for the red, and 0.825, 0.117 and 0.038 for the blue line. Only the first pair of canonical variates was significant (P < 0.05). AFE and early stages of egg production were very influent and showed great importance in defining the canonical variates and, consequently, the estimated canonical correlations. All lines had, in general, similar results for the canonical analysis indicating that traits that drive management decisions in these lines would be the same. The indices under study showed differences in response to selection; however, they generally resulted in consistent favorable genetic gains. For all lines, the canonical selection index resulted in the lowest AFE and highest egg production at 30 days. The DG-SI1 showed the highest genetic gains for W28 in all lines. There was a general lower genetic gain of other traits for DG-SI1 at the expense of the desired genetic gain for W28. Selection for AFE, according to the canonical-correlation analysis, would have a great impact on the number of eggs produced. Canonical selection index is a good alternative for a desired-gain selection index. (C) 2014 Elsevier B.V. All rights reserved.
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| 319500. |
- Hidalgo, André
(författare)
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Genome-wide association study reveals regions associated with gestation length in two pig populations
- 2016
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Ingår i: Animal Genetics. - : Wiley. - 0268-9146 .- 1365-2052. ; 47, s. 223-226
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Tidskriftsartikel (refereegranskat)abstract
- Reproduction traits, such as gestation length (GLE), play an important role in dam line breeding in pigs. The objective of our study was to identify single nucleotide polymorphisms (SNPs) that are associated with GLE in two pig populations. Genotypes and deregressed breeding values were available for 2081 Dutch Landrace-based (DL) and 2301 Large White- based (LW) pigs. We identified two QTL regions for GLE, one in each population. For DL, three associated SNPs were detected in one QTL region spanning 0.52 Mbp on Sus scrofa chromosome (SSC) 2. For LW, four associated SNPs were detected in one region of 0.14 Mbp on SSC5. The region on SSC2 contains the heparin-binding EGF-like growth factor (HBEGF) gene, which promotes embryo implantation and has been described to be involved in embryo survival throughout gestation. The associated SNP can be used for marker-assisted selection in the studied populations, and further studies of the HBEGF gene are warranted to investigate its role in GLE.
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