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 reveals novel loci for litter size and its variability in a Large White pig population.

BACKGROUND: In many traits, not only individual trait levels are under genetic control, but also the variation around that level. In other words, genotypes do not only differ in mean, but also in (residual) variation around the genotypic mean. New statistical methods facilitate gaining knowledge on the genetic architecture of complex traits such as phenotypic variability. Here we study litter size (total number born) and its variation in a Large White pig population using a Double Hierarchical Generalized Linear model, and perform a genome-wide association study using a Bayesian method. RESULTS: In total, 10 significant single nucleotide polymorphisms (SNPs) were detected for total number born (TNB) and 9 SNPs for variability of TNB (varTNB). Those SNPs explained 0.83 % of genetic variance in TNB and 1.44 % in varTNB. The most significant SNP for TNB was detected on Sus scrofa chromosome (SSC) 11. A possible candidate gene for TNB is ENOX1, which is involved in cell growth and survival. On SSC7, two possible candidate genes for varTNB are located. The first gene is coding a swine heat shock protein 90 (HSPCB = Hsp90), which is a well-studied gene stabilizing morphological traits in Drosophila and Arabidopsis. The second gene is VEGFA, which is activated in angiogenesis and vasculogenesis in the fetus. Furthermore, the genetic correlation between additive genetic effects on TNB and on its variation was 0.49. This indicates that the current selection to increase TNB will also increase the varTNB. CONCLUSIONS: To the best of our knowledge, this is the first study reporting SNPs associated with variation of a trait in pigs. Detected genomic regions associated with varTNB can be used in genomic selection to decrease varTNB, which is highly desirable to avoid very small or very large litters in pigs. However, the percentage of variance explained by those regions was small. The SNPs detected in this study can be used as indication for regions in the Sus scrofa genome involved in maintaining low variability of litter size, but further studies are needed to identify the causative loci.

SNP annotation-based whole genomic prediction and selection: an application to feed efficiency and its component traits in pigs.

The study investigated genetic architecture and predictive ability using genomic annotation of residual feed intake (RFI) and its component traits (daily feed intake [DFI], ADG, and back fat [BF]). A total of 1,272 Duroc pigs had both genotypic and phenotypic records, and the records were split into a training (968 pigs) and a validation dataset (304 pigs) by assigning records as before and after January 1, 2012, respectively. SNP were annotated by 14 different classes using Ensembl variant effect prediction. Predictive accuracy and prediction bias were calculated using Bayesian Power LASSO, Bayesian A, B, and Cπ, and genomic BLUP (GBLUP) methods. Predictive accuracy ranged from 0.508 to 0.531, 0.506 to 0.532, 0.276 to 0.357, and 0.308 to 0.362 for DFI, RFI, ADG, and BF, respectively. BayesCπ100.1 increased accuracy slightly compared to the GBLUP model and other methods. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP groups. Genomic prediction has accuracy comparable to observed phenotype, and use of genomic prediction can be cost effective by replacing feed intake measurement. Genomic annotation had less impact on predictive accuracy traits considered here but may be different for other traits. It is the first study to provide useful insights into biological classes of SNP driving the whole genomic prediction for complex traits in pigs.

Evidence of major genes affecting resistance to bacterial cold water disease in rainbow trout using Bayesian methods of segregation analysis.

Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation for BCWD resistance in our rainbow trout population, and a family-based selection program to improve resistance was initiated at the National Center for Cool and Cold Water Aquaculture (NCCCWA). This study investigated evidence of major trait loci affecting BCWD resistance using only phenotypic data (without using genetic markers) and Bayesian methods of segregation analysis (BMSA). A total of 10,603 juvenile fish from 101 full-sib families corresponding to 3 generations (2005, 2007, and 2009 hatch years) of the NCCCWA population were challenged by intraperitoneal injection with Flavobacterium psychrophilum, the bacterium that causes BCWD. The results from single- and multiple-QTL models of BMSA suggest that 6 to 10 QTL explaining 83 to 89% of phenotypic variance with either codominant or dominant disease-resistant alleles plus polygenic effects may underlie the genetic architecture of BCWD resistance. This study also highlights the importance of polygenic background effects in the genetic variation of BCWD resistance. The polygenic heritability on the observed scale of survival status is slightly larger than that previously reported for rainbow trout BCWD resistance. These findings provide the basis for designing informative crosses for QTL mapping and carrying out genome scans for QTL affecting BCWD resistance in rainbow trout.

Evidence of major genes affecting stress response in rainbow trout using Bayesian methods of complex segregation analysis.

As a first step toward the genetic mapping of QTL affecting stress response variation in rainbow trout, we performed complex segregation analyses (CSA) fitting mixed inheritance models of plasma cortisol by using Bayesian methods in large full-sib families of rainbow trout. To date, no studies have been conducted to determine the mode of inheritance of stress response as measured by plasma cortisol response when using a crowding stress paradigm and CSA in rainbow trout. The main objective of this study was to determine the mode of inheritance of plasma cortisol after a crowding stress. The results from fitting mixed inheritance models with Bayesian CSA suggest that 1 or more major genes with dominant cortisol-decreasing alleles and small additive genetic effects of a large number of independent genes likely underlie the genetic variation of plasma cortisol in the rainbow trout families evaluated. Plasma cortisol is genetically determined, with heritabilities of 0.22 to 0.39. Furthermore, a major gene with an additive effect of -42 ng/mL (approximately 1.0 genetic SD) is segregating in this rainbow trout broodstock population. These findings provide a basis for designing and executing genome-wide linkage studies to identify QTL for stress response in rainbow trout broodstock and markers for selective breeding.

Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

Genetic and phenotypic parameters for conformation and yield traits in three Swiss dairy cattle breeds.

This study presents genetic parameters for conformation traits and their genetic and phenotypic correlations with milk production traits and somatic cell score (SCS) in three Swiss dairy cattle breeds. Data on first lactations from Holstein (67,839), Brown Swiss (173,372) and Red & White breeds (53,784) were available. Analysed conformation traits were stature and heart girth (both in cm), and linear scores of body depth, rump width, dairy character or muscularity, and body condition score (only in Holstein). A sire model, with relationships among sires, was used for all breeds and traits and variance components were estimated using AS-REML. Heritabilities for stature were high (0.6-0.8), and for the linear type traits ranged from 0.3 to 0.5, for all breeds. Genetic correlations with production traits (milk, fat and protein yield) and SCS differed between the dairy breeds. Most markedly, stronger correlations were found between SCS and some conformation traits in Brown Swiss and Red & White, indicating that a focus on a larger and more 'dairy' type in these breeds would lead to increased SCS. Another marked difference was that rump width correlated positively with milk yield traits in Holstein and Red & White, but negative in Brown Swiss. Results indicate that conformation traits generally can be used as predictors for various purposes in dairy cattle breeding, but may require specific adaptation for each breed.

Genotype by environment interaction for somatic cell score across bulk milk somatic cell count and days in milk.

The objective of this paper was to investigate the importance of a genotype x environment interaction (G x E) for somatic cell score (SCS) across levels of bulk milk somatic cell count (BMSCC), number of days in milk (DIM), and their interaction. Variance components were estimated with a model including random regressions for each sire on herd test-day BMSCC, DIM, and the interaction of BMSCC and DIM. The analyzed data set contained 344,029 test-day records of 24,125 cows, sired by 182 bulls, in 461 herds comprising 13,563 herd test-days. In early lactation, considerable G x E effects were detected for SCS, indicated by 3-fold higher genetic variance for SCS at high BMSCC compared with SCS at low BMSCC, and a genetic correlation of 0.72 between SCS at low and at high BMSCC. Estimated G x E effects were smaller during late lactation. Genetic correlations between SCS at the same level of BMSCC, across DIM, were between 0.43 and 0.89. The lowest genetic correlation between SCS measures on any 2 possible combinations of BMSCC and DIM was 0.42. Correlated responses in SCS across BMSCC and DIM were, on some occasions, less than half the direct response to selection in the response environment. Responses to selection were reasonably high among environments in the second half of the lactation, whereas responses to selection between environments early and late in lactation tended to be low. Selection for reduced SCS yielded the highest direct response early in lactation at high BMSCC.

Bayesian inference on major loci in related multigeneration selection lines of laying hens.

A mixed inheritance model, postulating a polygenic effect and differences between the 3 genotypes of a biallelic locus, was fitted separately to the data of 2 multigeneration selection lines and a control evolving from a common base population. Inferences about the model were drawn from the application of the Gibbs sampler. Body weight at 20 and 40 wk (BW20, BW40) and average egg weight to 40 wk (EW40) were included in the analyses. Significance of differences between posterior means of parameters was established by comparing their 95% highest probability density regions. Significant (P < 0.05) additive and dominance effects due to the genotypes at the major locus were found for all traits. The allele causing a lower trait value was the (partial) dominant one in all traits, leading to a negative dominance effect. The additive variance due to the major locus was also significant, i.e., greater than zero (P < 0.05) in all traits, whereas the dominance variance was only important for EW40. With the exception of the residual variances of one selection and the control line, no (P > 0.05) differences of posterior means of any parameter could be observed between lines. No significant genotypic or polygenic selection response was found for BW40. On the contrary, both genetic responses were found significant for EW40 in the selected lines, but not in the control. No differences (P > 0.05) between lines could be observed for the derived frequencies of the allele causing the higher trait value and the frequencies of one homozygote and the heterozygote genotypes at the major locus. The detection of a major locus with relatively modest effect confirmed that this type of analysis with data from selected lines was indeed powerful.

An indication of major genes affecting hip and elbow dysplasia in four Finnish dog populations.

The aim of the study was to assess the possible existence of major genes influencing hip and elbow dysplasia in four dog populations. A Bayesian segregation analysis was performed separately on each population. In total, 34 140 dogs were included in the data set. Data were analysed with both a polygenic and a mixed inheritance model. Polygenic models included fixed and random environmental effects and additive genetic effects. To apply mixed inheritance models, the effect of a major gene was added to the polygenic models. The major gene was modelled as an autosomal biallelic locus with Mendelian transmission probabilities. Gibbs sampling and a Monte Carlo Markov Chain algorithm were used. The goodness-of-fit of the different models were compared using the residual sum-of-squares. The existence of a major gene was considered likely for hip dysplasia in all the breeds and for elbow dysplasia in one breed. Several procedures were followed to exclude the possible false detection of major genes based on non-normality of data: permuted datasets were analysed, data-transformations were applied, and residuals were judged for normality. Allelic effects at the major gene locus showed nearly to complete dominance, with a recessive, unfavourable allele in both traits. Relatively high estimates of the frequencies of unfavourable alleles in each breed suggest that considerable genetic progress would be possible by selection against major genes. However, the major genes that are possibly affecting hip and elbow dysplasia in these populations will require further study.

Disease incidence and immunological traits for the selection of healthy pigs. A review.

Disease is a major issue in animal production systems and society demands that the use of medicines and vaccines be reduced. This review describes the breeding approaches that could be used to improve disease resistance and focuses especially on their application to pigs. Disease reduction by genetic means has certain advantages through cumulative and permanent effects, and direct and indirect selection methods are available. Direct selection for disease incidence requires, besides a unique pig identification and disease registration system, challenge routines that are inconvenient in intensive pig production. Indirect selection for the expression of immune capacity may be an alternative but requires detailed knowledge of the different components of the immune system. There is ample opportunity for genetic improvement of the immune capacity because immune traits show substantial genetic variation between pigs. We therefore conclude that indirect selection via immune traits is very interesting, also for practical implementation, and that there is an urgent need for knowledge, within lines, about the genetic relationships between immune capacity traits and resistance to specific diseases or to disease incidence in general. Furthermore, knowledge about the relationship between immune system traits and production traits is needed as well as knowledge about the effect of selection on the epidemiology of disease at a farm/population level and on the host-pathogen interaction and coevolution.

Resistance of broiler outbred lines to infection with Salmonella enteritidis.

Salmonella infections originating from poultry are one of the major causes of food-borne disease. For the control of salmonella in poultry a multifactorial approach is more likely to be effective, and the genetic resistance of poultry breeds to salmonella infections may be a valuable contribution. Experimental Salmonella enteritidis infections were examined in three different broiler outbred lines: the FC line, which had been selected for feed conversion efficiency; the R line, which had been selected for growth rate; and the C line, a commercially available line. The FC line had the highest mortality rate after intramuscular inoculation with 5 x 10(6) colony forming units (CFU) of S. enteritidis at 2 weeks of age (40% versus 21 and 20% in the other lines). However, at slaughter age, the number of birds carrying salmonella in caecal contents, and the concentration of salmonella in the caecal contents, was lowest in the FC line. The FC and R lines were compared by inoculation with doses ranging from 10(2) to 10(7) CFU S. enteritidis. At sublethal doses (10(5) CFU or less), the FC line carried significantly less salmonella in caecal contents and the rate of systemic infection was lower. The start of shedding was also delayed compared with the R line. At doses of 10(6) CFU S. enteritidis or higher, there were no differences in salmonella carriage between the lines, and the FC line showed higher mortality. In conclusion, resistance to mortality and resistance to the carriage of S. enteritidis do not necessarily coincide within lines, as the FC line showed high mortality but low carriage, both in survivors of high infection doses and in all birds at lower infection doses.