Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values.

In across-country genomic predictions for dairy cattle, 2 kinds of bull information can be used as dependent variables. The first is estimated breeding value (EBV) from the national genetic evaluations, assuming genetic correlations between countries are less than 1. The second is EBV from multitrait across-countries evaluation (MACE), assuming genetic correlations between countries equal 1. In the present study, the level of bias and reliability of a cross-countries genomic prediction using national EBV or MACE EBV as the dependent variable were investigated. Data from Brown Swiss Organizations joining the InterGenomics Service by Interbull Centre (Uppsala, Sweden) were used. National and MACE EBV of 3 traits (protein yield, cow conception rate, and calving interval) from 7, 5, and 4 countries, respectively, were used, resulting in 16 trait-country combinations. Genotypes for 45,473 SNP markers and deregressed (national or MACE) EBV of 7,490; 5,833; and 5,177 bulls were used in analysis of protein yield, cow conception rate, and calving interval, respectively. For most of trait-country combinations, the use of MACE EBV via single-trait approach resulted in less biased and more reliable across-countries genomic predictions. In case some of the MACE EBV might have been inflated, the resulting single-trait genomic predictions were inflated as well. For these specific cases, the use of national EBV via multitrait approach provided less bias and more reliable across-countries genomic predictions.

Integument, mortality, and skeletal strength in extended production cycles for laying hens - effects of genotype and dietary zinc source.

1. This study on long-life layers, covering the period 20-100 weeks of age, investigated longitudinal effects on mortality, layer integument, and skeletal properties in Bovans White (BoW) and Lohmann Selected Leghorn Classic (LSL), with or without supplementation with dietary organic zinc (Zn).2. Two experiments, using 1440 layers in furnished small group cages (FC) and 1836 layers in a traditional floor housing system (Floor), were run in parallel. Each replicate consisted of five adjacent cages containing eight hens in each FC, or a pen with 102 layers in the Floor group.3. Mortality was recorded daily. Integument and keel bone condition were scored at 35, 55, 85, and 100 weeks of age on 20% of the layers. Tibial strength was recorded from 933 layers at 100 weeks. Statistical analyses were performed on replicate means, with four to five and nine replicates per combination of hybrid and diet in Floor and FC groups, respectively.4. Cumulative mortality was 9.6% and 16.3% in FC and Floor, respectively, and increased in the latter part of the production cycle, particularly in the Floor group.5. In FC, LSL had inferior feather cover, less keel bone deviation, and shorter claws than BoW. In Floor, LSL had superior feather cover, less severe vent wounds, more bumble foot, and cleaner plumage than BoW. In both production systems, claws grew longer and keel bone deviation became more severe with age.6. In FC, layers fed organic Zn had lower body weight and less keel bone deviation at 100 weeks of age.7. In conclusion, keel bone integrity, claw length, and mortality rate are potential threats to welfare in long-life layers. Feather pecking is a problem that needs addressing at an early stage in the production period. On the whole, organic Zn did not improve welfare conditions in long-life layers.

Genetic parameters for noncoagulating milk, milk coagulation properties, and detailed milk composition in Swedish Red Dairy Cattle.

The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level.

Effects of milk proteins and posttranslational modifications on noncoagulating milk from Swedish Red dairy cattle.

Milk that does not coagulate after rennet addition, also called noncoagulating (NC) milk, is unwanted in cheese production due to prolonged processing time. Amounts of whey and casein proteins, genetic variants, as well as posttranslational modifications (PTM) of proteins are all contributing factors in rennet-induced coagulation of milk. In this study, we conducted a wide-ranging investigation of milk proteins in milk samples from 616 Swedish Red dairy cattle using liquid chromatography-high resolution mass spectrometry. Relative concentration of proteins, genetic variants, and PTM were compared between NC milk and coagulating milk. The PTM investigated were phosphorylation of caseins and glycosylation of κ-casein. Several genetic variants and PTM were found, including rare phosphorylation variants of the αS-caseins. Genetic variants were found to effect the expressed amount of different proteins. Further, the effect of protein amounts and PTM on a binary NC milk trait was modeled using a generalized linear model. The model showed that NC milk significantly correlated with higher relative concentrations of α-lactalbumin and ß-casein and lower relative concentrations of ß-lactoglobulin and κ-casein. Regarding PTM of caseins, an effect on NC milk from a lower relative concentration of αS1-casein with 8 phosphate groups were found, even though an effect from total relative concentration of αS1-casein was not found. This study has provided insights into protein variants and PTM important for NC milk to improve this undesirable property.

Genome-wide association study of normal and atypical progesterone profiles in Holstein-Friesian dairy cows.

Female fertility has a major role in dairy production and affects the profitability of dairy cattle. The genetic progress obtained by traditional selection can be slow because of the low heritability of classical fertility traits. Endocrine fertility traits based on progesterone concentration in milk have higher heritability and more directly reflect the cow's own reproductive physiology. The aim of our study was to identify genomic regions for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 54,000 SNP. The next step was to fine-map targeted genomic regions with significant SNP using imputed sequences to identify potential candidate genes associated with the normal and atypical progesterone profiles. The association between a SNP and a phenotype was assessed by a single SNP analysis, using a linear mixed model that included a random polygenic effect. Phenotypes and genotypes were available for 1,126 primiparous and multiparous Holstein-Friesian cows from research herds in Ireland, the Netherlands, Sweden, and the United Kingdom. In total, 44 significant SNP associated with 7 endocrine fertility traits were identified on Bos taurus autosome (BTA) 1-4, 6, 8-9, 11-12, 14-17, 19, 21-24, and 29. Three chromosomes, BTA8, BTA17, and BTA23, were imputed from 54,000 SNP genotypes to the whole-genome sequence level with Beagle version 4.1. The fine-mapping identified several significant associations with delayed cyclicity, cessation of cyclicity, commencement of luteal activity, and inter-ovulatory interval. These associations may contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes reported to affect reproduction were also identified in the targeted genomic regions. However, due to high linkage disequilibrium, it was not possible to identify putative causal genes or polymorphisms for any of the regions.

Validated quantitative trait loci for eggshell quality in experimental and commercial laying hens.

Compromised eggshell quality causes considerable economic losses for the egg industry. Breeding for improved eggshell quality has been very challenging. Eggshell quality is a trait that would greatly benefit from marker-assisted selection, which would allow the selection of sires for their direct contribution to the trait and would also allow implementation of measurements integrating a number of shell parameters that are difficult to measure. In this study, we selected the most promising autosomal quantitative trait loci (QTL) affecting eggshell quality on chromosomes 2, 3, 6 and 14 from earlier experiments and we extended the F2 population to include 1599 F2 females. The study was repeated on two commercial populations: Lohmann Tierzucht Rhode Island Red line (n = 692 females) and a Hy-Line White Plymouth Rock line (n = 290 progeny tested males). We analyzed the selected autosomal QTL regions on the three populations with SNP markers at 4-13 SNPs/Mb density. QTL for eggshell quality were replicated on all studied regions in the F2 population. New QTL were detected for eggshell color on chromosomes 3 and 6. Marker associations with eggshell quality traits were validated in the tested commercial lines on chromosomes 2, 3 and 6, thus paving the way for marker-assisted selection for improved eggshell quality.

Improving accuracy of bulls' predicted genomic breeding values for fertility using daughters' milk progesterone profiles.

The main objective of this study was to investigate the benefit of accuracy of genomic prediction when combining records for an intermediate physiological phenotype in a training population with records for a traditional phenotype. Fertility was used as a case study, where commencement of luteal activity (C-LA) was the physiological phenotype, whereas the interval from calving to first service and calving interval were the traditional phenotypes. The potential accuracy of across-country genomic prediction and optimal recording strategies of C-LA were also investigated in terms of the number of farms and number of repeated records for C-LA. Predicted accuracy was obtained by estimating population parameters for the traits in a data set of 3,136 Holstein Friesian cows with 8,080 lactations and using a deterministic prediction equation. The effect of genetic correlation, heritability, and reliability of C-LA on the accuracy of genomic prediction were investigated. When the existing training population was 10,000 bulls with reliable estimated breeding value for the traditional trait, predicted accuracy for the physiological trait increased from 0.22 to 0.57 when 15,000 cows with C-LA records were added to the bull training population; but, when the interest was in predicting the traditional trait, we found no benefit from the additional recording. When the genetic correlation was higher between the physiological and traditional traits (0.7 instead of 0.3), accuracy increased less when adding the 15.000 cows with C-LA (from 0.51 to 0.63). In across-country predictions, we observed little to no increase in accuracy of the intermediate physiological phenotype when the training population from Sweden was large, but when accuracy increased the training population was small (200 cows), from 0.19 to 0.31 when 15,000 cows were added from the Netherlands (genetic correlation of 0.5 between countries), and from 0.19 to 0.48 for genetic correlation of 0.9. The predicted accuracy initially increased substantially when recording on the same farm was extended and multiple C-LA records per cow were used in prediction compared with single records; that is, accuracy increased from 0.33 with single records to 0.38 with multiple records (on average 1.6 records per cow) from 2 yr of recording C-LA. But, when the number C-LA per cow increased beyond 2 yr of recording, we noted no substantial benefit in accuracy from multiple records. For example, for 5 yr of recording (on average 2.5 records per cow), accuracy was 0.47; on doubling the recording period to 10 yr (on average 3.1 records per cow), accuracy increased by 0.07 units, whereas when C-LA was recorded for 15 yr (on average 3.3 records per cow) accuracy increased only by 0.05 units. Therefore, for genomic prediction using expensive equipment to record traits for training populations, it is important to optimize the recording strategy. The focus should be on recording more cows rather than continuous recording on the same cows.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows.

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle.

Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.

Fine mapping of a calving QTL on Bos taurus autosome 18 in Holstein cattle.

Decreased calving performance not only directly impacts the economic efficiency of dairy cattle farming but also influences public concern for animal welfare. Previous studies have revealed a QTL on Bos taurus autosome (BTA) 18 that has a large effect on calving traits in Holstein cattle. In this study, fine mapping of this QTL was performed using imputed high-density SNP chip (HD) genotypes followed by imputed next-generation sequencing (NGS) variants. BTA18 was scanned for seven direct calving traits in 6113 bulls with imputed HD genotypes. SNP rs136283363 (BTA18: 57 548 213) was consistently the most significantly associated SNP across all seven traits [e.g. p-value = 2.04 × 10(-59) for birth index (BI)]. To finely map the QTL region and to explore pleiotropic effects, we studied NGS variants within the targeted region (BTA18: 57 321 450-57 625 355) for associations with direct calving traits and with three conformation traits. Significant variants were prioritized, and their biological relevance to the traits was interpreted. Considering their functional relationships with direct calving traits, SIGLEC12, CD33 and CEACAM18 were proposed as candidate genes. In addition, pleiotropic effects of this QTL region on direct calving traits and conformation traits were observed. However, the extent of linkage disequilibrium combined with the lack of complete annotation and potential errors in the Bos taurus genome assembly hampered our efforts to pinpoint the causal mutation.

Accuracy of genomic prediction of purebreds for cross bred performance in pigs.

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 implemented in, for example dairy cattle breeding. A good strategy is to estimate 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 genomic 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 number 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.

Predicted optimum ambient temperatures for broiler chickens to dissipate metabolic heat do not affect performance or improve breast muscle quality.

An experiment was conducted to test the hypothesis that muscle damage in fast-growing broiler chickens is associated with an ambient temperature that does not permit the birds to lose metabolic heat resulting in physiological heat stress and a reduction in meat quality. The experiment was performed in 4 climate chambers and was repeated in 2 trials using a total of 200 male broiler chickens. Two treatments compared the recommended temperature profile and a cool regimen. The cool regimen was defined by a theoretical model that determined the environmental temperature that would enable heat generated by the bird to be lost to the environment. There were no differences in growth rate or feed intake between the two treatments. Breast muscles from birds on the recommended temperature regimen were lighter, less red and more yellow than those from the cool temperature regimen. There were no differences in moisture loss or shear strength but stiffness was greater in breast muscle from birds housed in the cool compared to the recommended regimen. Histopathological changes in the breast muscle were similar in both treatments and were characterised by mild to severe myofibre degeneration and necrosis with regeneration, fibrosis and adipocyte infiltration. There was no difference in plasma creatine kinase activity, a measure of muscle cell damage, between the two treatments consistent with the absence of differences in muscle pathology. It was concluded that breast muscle damage in fast-growing broiler chickens was not the result of an inability to lose metabolic heat at recommended ambient temperatures. The results suggest that muscle cell damage and breast meat quality concerns in modern broiler chickens are related to genetic selection for muscle yields and that genetic selection to address breast muscle integrity in a balanced breeding programme is imperative.

Efficiency of genomic prediction for boar taint reduction in Danish Landrace pigs.

Genetic selection against boar taint, which is caused by high skatole and androstenone concentrations in fat, is a more acceptable alternative than is the current practice of castration. Genomic predictors offer an opportunity to overcome the limitations of such selection caused by the phenotype being expressed only in males at slaughter, and this study evaluated different approaches to obtain such predictors. Samples from 1000 pigs were included in a design which was dominated by 421 sib pairs, each pair having one animal with high and one with low skatole concentration (≥0.3 µg/g). All samples were measured for both skatole and androstenone and genotyped using the Illumina SNP60 porcine BeadChip for 62 153 single nucleotide polymorphisms. The accuracy of predicting phenotypes was assessed by cross-validation using six different genomic evaluation methods: genomic best linear unbiased prediction (GBLUP) and five Bayesian regression methods. In addition, this was compared to the accuracy of predictions using only QTL that showed genome-wide significance. The range of accuracies obtained by different prediction methods was narrow for androstenone, between 0.29 (Bayes Lasso) and 0.31 (Bayes B), and wider for skatole, between 0.21 (GBLUP) and 0.26 (Bayes SSVS). Relative accuracies, corrected for h(2) , were 0.54-0.56 and 0.75-0.94 for androstenone and skatole respectively. The whole-genome evaluation methods gave greater accuracy than using only the QTL detected in the data. The results demonstrate that GBLUP for androstenone is the simplest genomic technology to implement and was also close to the most accurate method. More specialised models may be preferable for skatole.

Asian low-androstenone haplotype on pig chromosome 6 does not unfavorably affect production and reproduction traits.

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 1.94 Mbp would not unfavorably affect the other eight relevant traits.

Genetic analysis of atypical progesterone profiles in Holstein-Friesian cows from experimental research herds.

The objective of this study was to quantify the genetic variation in normal and atypical progesterone profiles and investigate if this information could be useful in an improved genetic evaluation for fertility for dairy cows. The phenotypes derived from normal profiles included cycle length traits, including commencement of luteal activity (C-LA), interluteal interval, luteal phase length. and interovulatory interval. In total, 44,977 progesterone test-day records were available from 1,612 lactations on 1,122 primiparous and multiparous Holstein-Friesian cows from Ireland, the Netherlands, Sweden, and the United Kingdom. The atypical progesterone profiles studied were delayed cyclicity, prolonged luteal phase, and cessation of cyclicity. Variance components for the atypical progesterone profiles were estimated using a sire linear mixed model, whereas an animal linear mixed model was used to estimate variance components for the cycle length traits. Heritability was moderate for delayed cyclicity (0.24 ± 0.05) and C-LA (0.18 ± 0.04) but low for prolonged luteal phase (0.02 ± 0.04), luteal phase length (0.08 ± 0.05), interluteal interval (0.08 ± 0.14), and interovulatory interval (0.03 ± 0.04). No genetic variation was detected for cessation of cyclicity. Commencement of luteal activity, luteal phase length, and interovulatory interval were moderately to strongly genetically correlated with days from calving to first service (0.35 ± 0.12, 0.25 ± 0.14, and 0.76 ± 0.24, respectively). Delayed cyclicity and C-LA are traits that can be important in both genetic evaluations and management of fertility to detect (earlier) cows at risk of compromised fertility. Delayed cyclicity and C-LA were both strongly genetically correlated with milk yield in early lactation (0.57 ± 0.14 and 0.45 ± 0.09, respectively), which may imply deterioration in these traits with selection for greater milk yield without cognizance of other traits.

Genome-wide associations for investigating time-dependent genetic effects for milk production traits in dairy cattle.

Phenotypic variation in milk production traits has been described over the course of a lactation as well as between different parities. The objective of this study was to investigate whether variation in production is affected by different loci across lactations. A genome-wide association study (GWAS) using a 50-k SNP chip was conducted in 152 divergent German Holstein Friesian cows to test for association with milk production traits over different lactations. The first four lactations were analysed regarding milk yield, fat, protein, lactose, milk urea nitrogen yield and content as well as somatic cell score. Two approaches were used: (i) Wilmink curve parameters were used to assess the genetic effects over the course of a lactation and (ii) test-day yield deviations (YD) were used as a normative approach for a GWAS. The significant effects were largest for markers affecting curve parameters for which there was a statistical power <0.8 of detection even in this small design. While significant markers for YDs were detected in this study, the power to detect effects of a similar magnitude was only 0.11, suggesting that many loci may have been missed with this approach in the present design. Furthermore, all significant effects were specific for a single lactation, leading to the conclusion that the variance explained by a certain locus changes from lactation to lactation. We confirm the common evidence that most production traits vary in the degree of persistency after the peak as a result of genetic influence.

Complex traits analysis of chicken growth using targeted genetical genomics.

Dissecting the genetic control of complex trait variation remains very challenging, despite many advances in technology. The aim of this study was to use a major growth quantitative trait locus (QTL) in chickens mapped to chromosome 4 as a model for a targeted approach to dissect the QTL. We applied a variant of the genetical genomics approach to investigate genome-wide gene expression differences between two contrasting genotypes of a marked QTL. This targeted approach allows the direct quantification of the link between the genotypes and the genetic responses, thus narrowing the QTL-phenotype gap using fewer samples (i.e. microarrays) compared with the genome-wide genetical genomics studies. Four differentially expressed genes were localized under the region of the QTL. One of these genes is a potential positional candidate gene (AADAT) that affects lysine and tryptophan metabolism and has alternative splicing variants between the two genotypes. In addition, the lysine and glycolysis metabolism pathways were significantly enriched for differentially expressed genes across the genome. The targeted approach provided a complementary route to fine mapping of QTL by characterizing the local and the global downstream effects of the QTL and thus generating further hypotheses about the action of that QTL.

Quantitative trait loci for resistance to fish pasteurellosis in gilthead sea bream (Sparus aurata).

Fish pasteurellosis is a bacterial disease causing important losses in farmed fish, including gilthead sea bream, a teleost fish of great relevance in marine aquaculture. We report in this study a QTL analysis for resistance to fish pasteurellosis in this species. An experimental population of 500 offspring originating from eight sires and six dams in a single mass-spawning event was subjected to a disease challenge with Photobacterium damselae subsp. piscicida (Phdp), the causative agent of fish pasteurellosis. A total of 151 microsatellite loci were genotyped in the experimental population, and half-sib regression QTL analysis was carried out on two continuous traits, body length at time of death and survival, and for two binary traits, survival at day 7 and survival at day 15, when the highest peaks of mortality were observed. Two significant QTLs were detected for disease resistance. The first one was located on linkage group LG3 affecting late survival (survival at day 15). The second one, for overall survival, was located on LG21, which allowed us to highlight a potential marker (Id13) linked to disease resistance. A significant QTL was also found for body length at death on LG6 explaining 5-8% of the phenotypic variation.

Quantitative trait loci affecting eggshell traits in an F(2) population.

Good eggshell quality is important for both table egg quality and chicken reproductive performance. Weak eggshells cause economic losses in all production steps. Poor eggshell quality also poses increased risk for Salmonella infections. Eggshell quality has been a difficult trait to improve by traditional breeding, as it can be measured only for females and it is difficult and expensive to measure. Breeding for improved shell quality may therefore benefit from the use of marker-assisted selection. In an effort to find markers linked to eggshell quality, we have used an F(2) population of 668 females to map quantitative trait loci (QTL) affecting eggshell traits (eggshell deformation, breaking force, weight). By using 160 microsatellite markers on 27 chromosomes, we found 11 genome-wide and 15 suggestive QTL for shell traits measured at different times during production. Loci affecting the deformation were found on chromosomes 1, 2, 6, 10, 14 and Z. Loci affecting the breaking force were detected on chromosomes 2, 3, 10, 12 and Z. Loci affecting the shell weight were detected on chromosomes 6, 12, 24 and Z. Each QTL explains between 1.5% and 4.6% of the phenotypic variance, adding up to 10-15% of total phenotypic variance explained for the different traits. No epistatic effects were observed between loci affecting eggshell traits. Because the effects for quality are mainly additive, these results provide a basis for further characterization of the loci to identify closely linked markers to be used in marker-assisted selection.

High throughput analyses of epistasis for swine body dimensions and organ weights.

High throughput analyses were performed to detect epistatic QTL in 17 body dimension and organ weight traits from a large F(2) pig population derived from a White Duroc and Erhualian intercross. The analyses used a nested test framework to handle multiple tests and a combined search algorithm to map epistatic QTL with empirical genome-wide thresholds derived via prior permutation. Alternative statistical models (e.g. including vs. excluding carcass weight as a covariate) were tested to develop an in-depth understanding of the role of epistasis in these kinds of traits. Epistasis signals were detected in only two or three traits under each statistical model studied. The interaction component of each pair of epistatic QTL explained a small proportion (0.7 to 2.1%) of the phenotypic variance in general. About half of the detected epistatic QTL pairs involved one of the two major QTL on porcine chromosomes 7 and 4. In those traits, the Erhualian allele consistently increased the phenotypes for the chromosome 7 QTL but decreased them for the chromosome 4 QTL. Models including carcass weight as covariate detected epistasis in body dimension traits whereas those excluding carcass weight found epistasis in organ weight traits. In addition, the epistasis results suggested that a QTL on chromosome 14 could be important for a number of organ weight traits. Using the high-throughput analysis tool to examine different statistical models was essential for the generation of a complete picture of epistasis in a whole category of traits.