Bias in heritability estimates from genomic restricted maximum likelihood methods under different genotyping strategies

We investigated the effects of different strategies for genotyping populations on variance components and heritabilities estimated with an animal model under restricted maximum likelihood (REML), genomic REML (GREML), and single‐step GREML (ssGREML). A population with 10 generations was simulated. Animals from the last one, two or three generations were genotyped with 45,116 SNP evenly distributed on 27 chromosomes. Animals to be genotyped were chosen randomly or based on EBV. Each scenario was replicated five times. A single trait was simulated with three heritability levels (low, moderate, high). Phenotypes were simulated for only females to mimic dairy sheep and also for both sexes to mimic meat sheep. Variance component estimates from genomic data and phenotypes for one or two generations were more biased than from three generations. Estimates in the scenario without selection were the most accurate across heritability levels and methods. When selection was present in the simulations, the best option was to use genotypes of randomly selected animals. For selective genotyping, heritabilities from GREML were more biased compared to those estimated by ssGREML, because ssGREML was less affected by selective or limited genotyping.     

Plasma and cerebrospinal fluid interleukin-1β during lipopolysaccharide-induced systemic inflammation in ewes implanted or not with slow-release melatonin

Background: Interleukin-1β(IL-1β) is important mediator of inflammatory-induced suppression of reproductive axis at the hypothalamic level. At the beginning of inflammation, the main source of cytokines in the cerebrospinal fluid(CSF) is peripheral circulation, while over time, cytokines produced in the brain are more important. Melatonin has been shown to decrease pro-inflammatory cytokines concentration in the brain. In ewes, melatonin is used to advance the onset of a breading season. Little is known about CSF concentration of IL-1β in ewes and its correlation with plasma during inflammation as well as melatonin action on the concentration of IL-1β in blood plasma and the CSF, and brain barriers permeability in early stage of lipopolysaccharide(LPS)-induced inflammation.Methods: Systemic inflammation was induced through LPS administration in melatonin-and sham-implanted ewes. Blood and CSF samples were collected before and after LPS administration and IL-1β and albumin concentration were measured. To assess the functions of brain barriers albumin quotient(QAlb) was used.Expression of IL-1β(Il1B) and its receptor type Ⅰ(Il1r1) and type Ⅱ(Il1r2) and matrix metalloproteinase(Mmp) 3 and 9 was evaluated in the choroid plexus(CP).Results: Before LPS administration, IL-1β was on the level of 62.0 ± 29.7 pg/mL and 66.4 ± 32.1 pg/mL in plasma and 26.2 ± 5.4 pg/mL and 21.3 ± 8.7 pg/mL in the CSF in sham-and melatonin-implanted group, respectively.Following LPS it increased to 159.3 ± 53.1 pg/mL and 197.8 ± 42.8 pg/mL in plasma and 129.8 ± 54.2 pg/mL and139.6 ± 51.5 pg/mL in the CSF. No correlations was found between plasma and CSF IL-1β concentration after LPS in both groups. The QAlb calculated before LPS and 6 h after was similar in all groups. Melatonin did not affected m RNA expression of Il1B, Il1r1 and Il1r2 in the CP. The m RNA expression of Mmp3 and Mmp9 was not detected.Conclusions: The lack of correlation between plasma and CSF IL-1β concentration indicates that at the beginning of inflammation the local synthesis of IL-1β in the CP is an important source of IL-1β in the CSF. Melatonin from slow-release implants does not affect IL-1β concentration in plasma and CSF in early stage of systemic inflammation.     

Modeling final scores in US Holsteins as a function of year of classification using a random regression model

Conformation final scores in Holsteins were used to assess genetic changes over the years due to various factors such as selection and changes in trait definition. The model included management group, age group, and stage of lactation as fixed effects; additive genetic effects with random regressions on year of classification using Legendre polynomials with order from linear to cubic; and residual effects assuming heterogeneous variances. Two sets of simulated data were used to test the feasibility of variance component estimation in situations where the definition of the trait of interest changes continuously over time. Estimated variances from the simulated data sets were unbiased. Empirical tests involved 30,041 records of cows with single records scored in 1981-1999. Heritability estimates and additive genetic variances from field data decreased while residual variances increased over time. Differences among estimates of variance components from linear, quadratic and cubic random-regression models were small. Genetic correlations among final scores at years of classification estimated with the multiple-trait model that treated different groups of years as separate traits and with linear, quadratic and cubic random-regression models decreased from 1.0 to a minimum of 0.91, as the distance between the years increased. Although there were no significant differences among estimates of variance components from random-regression models, genetic correlations between different years estimated with higher order random-regression models were closer to those with the multiple trait model that treated different group of years as separate traits. Genetic changes in a trait over time can be studied with a random-regression model.     

Joint evaluation of purebreds and crossbreds in swine

Data from two purebred swine lines A (n = 6,022) and B (n = 24,170), and their reciprocal, cross C (n = 6,135), were used to examine gains in reliability of combined purebred and crossbred evaluation over conventional within-line evaluations using crossbred and pureline models. Random effects in the pureline model included additive, parental dominance, and litter. In the crossbred model, effects were as in the pureline model except traits of each line were treated as separate traits and two additive effects were present. The approximate model was the same as the pureline except it was used for all lines disregarding breed differences. The traits in the evaluation were lifetime daily gain (LDG) and backfat. When separate line evaluations were replaced by evaluations with crossbreds, mean reliabilities of predicted breeding values increased by 2 to 9% for purebreds and by 21 to 72% for crossbreds. Rank correlations between these breeding values were > 0.99 for purebreds but 0.85 to 0.87 for crossbreds. Rank correlations between predicted breeding values obtained from crossbred and approximate models were 0.98 to 0.99 for purebreds and 0.96 to 0.98 for crossbreds. When the number of crossbreds was small in comparison to purebreds, the increase in reliability by using the crossbred data and the crossbred model as opposed to purebred models was small for purebreds but large for crossbreds. The approximate model provided very similar rankings to the crossbred model for purebreds but rankings were less consistent for crossbreds.     

Use of a test day model for dairy goat milk yield across lactations in Germany.

Breeding value prediction for dairy goats in Germany is still based on herd mate comparison within breeding society. The objective of this study was to estimate genetic parameters for milk yield based on a test day model. For the analysis 35,308, 30,551 and 23,640 test day records from lactations 1, 2 and 3 from 5079, 4118 and 3132 animals, respectively, were used. The data between 1987 and 2003 were obtained from six German breeding societies. The multiple trait (lactations 1, 2 and 3) repeatability model (RPT) included the fixed effects of breeding society-breed-herd-year, litter size, lambing season, and days in milk of third-order Legendre polynomials nested within herd-year, and the random effects of animal additive and permanent environment. The three-trait random regression model (RR) also included the random regressions based on second-order Legendre polynomials for animal additive and permanent environmental effects. Heritability estimates in RPT were 0.27 +/- 0.02, 0.20 +/- 0.02 and 0.37 +/- 0.02 for the first, second and third lactation, respectively. The genetic correlation between the first and second lactation was 0.69, between the second and third lactation 0.79, and between the first and third lactation 0.45. Heritability estimates from the RR in the first and second lactations decreased from the beginning to the end of the lactation, with average values of 0.28 and 0.27, respectively. Estimates in the third lactation showed a maximum in the middle of lactation, averaging 0.37. Genetic correlations between the first and second lactation averaged 0.64, between the second and third lactation 0.72, and between the first and third lactation 0.46. Despite the small data set and restricted relationship structure the estimates were reasonable with the exception of estimates from the third lactation, which seemed inflated. RR could be used for genetic evaluation of dairy goats in Germany.     

Nutritional value and physiological effects of soya-free diets fed to rats during growth and reproduction

The objective of the study was to assess the effects of substitution milk and egg for soya products in breeding diets for rats, with concomitant decrease of the dietary protein level and supplementation with amino acids. Soya-containing (S) and two soya-free (NS and NSA) diets were evaluated as protein and energy sources, and their effects on reproductive performance during two cycles, and on the quality of the offspring were assessed. Organ weights were registered in females and blood parameters were determined in males. In the offspring males from S and NS groups, plasma LH, testosterone and prolactin levels were measured on the 22nd and the 60th day of life. The S diet contained more protein of smaller concentration of methionine and cystine and lower biological value than both NS and NSA diets and promoted similar post-weaning growth rate, similar body weight changes of dams during gestation and lactation and slightly lower mating efficiency. Within each reproductive cycle, the number and individual and total body weight of newborn and weanling pups did not differ but in two cycles mean number of neonates per litter and mean litter weight were significantly lower on S than on NSA diet. Plasma concentration of hormones did not differ in 22-day-old offspring males while in the older ones LH and prolactin levels were higher in animals fed on S than on NS diet. It is concluded that replacing soya protein by milk and egg protein with concomitant lowering dietary protein level and amino acid supplementation does not impair the growth rate and tends to improve reproductive performance. Feeding soya-free vs. soya-containing diets differentiates hormonal status of young males.     

Dependence of the lactation duration and efficiency on the season of lambing in relation to the prolactin and melatonin secretion in ewes

Changes in day length and the related secretion of melatonin and prolactin are of particular significance in sheep, as they determine reproductive processes, the last stage of which is lactation. The aim of the present study was to examine the dependence of the lactation duration and efficiency on the season of lambing (January—Group I/June—Group II) in relation to the hormonal status of milking ewes (Polish Longwool). The possibility of artificial extension of the milking period in late-lambing ewes by application of prolonged day length, 16 h of light–8 h of darkness (16L:8D), was introduced additionally (Group III). Measurements of plasma levels of prolactin and melatonin were used as parameters of season-dependent hormonal regulation of milk production in this seasonally breeding species. Although during the first 28 days of lactation sheep of all groups produced similar amounts of milk (based on the weight gains of the lambs), our results clearly showed that during the period of machine milking (from weaning at 56 day to the dry period) the level of milk production in Group I was almost twice that noted in Group II. Thus, the highest milk yield was obtained from sheep during the period when the days became longer, i.e. from March to May, which was accompanied by an increase in prolactin secretion. In both groups, melatonin secretion was found to increase while milk performance parameters and prolactin secretion decreased during the shortening photoperiod. The sustained decreases in milk production and prolactin secretion were also observed during the autumn months in sheep from Group III, despite the low level of melatonin. The present study showed that time of lambing and related photoperiod length could significantly affect the milk production of sheep that have a clear season of sexual activity. Maintenance of June-lambing sheep under the 16L:8D regime failed to extend the high prolactin level and lactation considerably into the autumn months. The spontaneous decrease in prolactin secretion observed under the long artificial photoperiod indicated for a development of refractoriness, which could also limit the lactation period.     

Properties of random regression models using linear splines

Properties of random regression models using linear splines (RRMS) were evaluated with respect to scale of parameters, numerical properties, changes in variances and strategies to select the number and positions of knots. Parameters in RRMS are similar to those in multiple trait models with traits corresponding to points at knots. RRMS have good numerical properties because of generally superior numerical properties of splines compared with polynomials and sparser system of equations. These models also contain artefacts in terms of depression of variances and predictions in the middle of intervals between the knots, and inflation of predictions close to knots; the artefacts become smaller as correlations corresponding to adjacent knots increase. The artefacts can be greatly reduced by a simple modification to covariables. With the modification, the accuracy of RRMS increases only marginally if the correlations between the adjacent knots are ≥0.6. In practical analyses the knots for each effect in RRMS can be selected so that: (i) they cover the entire trajectory; (ii) changes in variances in intervals between the knots are approximately linear; and (iii) the correlations between the adjacent knots are at least 0.6. RRMS allow for simple and numerically stable implementations of genetic evaluations with artefacts present but transparent and easily controlled.     

Genetic parameter estimates from joint evaluation of purebreds and crossbreds in swine using the crossbred model.

Records on lifetime daily gain and backfat from two purebred lines A (n = 6,022), B (n = 24,170), and their reciprocal crosses C (n = 6,135) were used to estimate genetic parameters using within-line and terminal-cross models. The models that were fitted included fixed (contemporary group and sex), random additive A and(or) random additive B, random dominance, and random litter effects. Model for purebreds included only one additive effect, whereas the model for crossbreds included two additive effects. End weight was included as a covariable for backfat. Heritability estimates for lifetime daily gain were 0.26, 0.28, and 0.23 with within-line models for lines A, B, and C, respectively, and 0.26, 0.30, and 0.27 with the crossbred model, respectively. Heritability estimates for backfat were 0.52, 0.35, and 0.29 with within-line models for lines A, B, and C, respectively, and 0.51, 0.38, and 0.29 with the crossbred model, respectively. The genetic correlations between purebreds and crossbreds (r(pc)) for lifetime daily gain were 0.99 (A-C) and 0.62 (B-C); for backfat the correlations were 0.32 (A-C) and 0.70 (B-C). The amount of dominance variance from the crossbred model expressed as a proportion of phenotypic variance for lifetime daily gain was 0.39, 0.16, and 0.29 for lines A, B, and C respectively. Dominance variance for backfat was estimated as 0. A joint evaluation of purebreds and crossbreds would be most efficient with the crossbred model. The dominance variation should be accounted for lifetime daily gain.