Evaluation of Breeding Value and Selection of Bull Dams in the Danish Dairy Breeds: II. Model Calculations of the Effect of Bias on the Efficiency of Selection

Abstract

Alternative selection strategies in the bull dam path were investigated to reduce the magnitude of bias. The study's objective was to examine the effect of alternative strategies under the assumption of particular biases. Bias in the evaluation of bull dam estimated breeding values (EBVs) causes an estimated reduction of 32% in their genetic superiority, compared with the theoretical potential. Biased evaluations caused selection of too many bull dams from later lactations. Two alternative strategies were developed to account for existing bias. Results suggested that the influence of bias could be reduced. The estimated improvement in selection response was 11–13% higher than current practice. Problems with biased EBVs in conventional breeding schemes are discussed and a method to counteract bias from future breeding schemes is presented.     

Genetic Correlations Between Beef Traits Measured on Young Performance Test Bulls and Daughter Milk Yield

In a breeding programme where young potential breeding bulls are reared on performance test stations, selection based on own results can be carried out before test inseminations. Both beef and milk production traits are included in the total merit index used for selection, and estimates of genetic and phenotypic parameters of these traits are therefore of interest for an optimal construction of such indices. Data on first lactation milk records from the field and beef records of potential dairy breeding bulls from the Danish performance test stations were analysed in bivariate animal-sire models using the AI-REML algorithm. Genetic correlations of 0.16, 0.25 and 0.43 between feed intake capacity and protein yield were obtained for Red Danish (RD), Danish Black and White (DBW) and Danish Jersey (DJ), respectively. These correlations were significantly different from zero for the two populations (DBW and DJ). Genetic correlations around zero between feed efficiency and protein yield were obtained for all three populations. Genetic correlations of 0.44, 0.19 and 0.47 between average daily gain and protein yield were obtained for RD, DBW and DJ, respectively. The genetic correlations between protein yield and muscle area was close to zero for DBW, while it was -0.31 for RD. Selection index calculations indicate that indices composed of different beef performance traits can be used as early predictors for milk yield. Selection on such an index could increase the breeding value of the young bulls for milk production traits by 0.8-2.0% of the population mean.     

公牛家系泌乳曲线的研究

本文根据北京黑白花奶牛２２个公牛家系的女儿泌期资料，利用Ｗｏｏｄ模型估计了各公牛家系的泌乳曲线参数，并且按照家系内女儿的不同胎次，所在牧场和产犊年份分组作了更加深入的研究。所考虑的曲线参数为规模因子ａ。产奶量上升率ｂ和下降率ｃ；次级参数包括３０５天实际产奶量，３０５天估计产奶量，高峰月份，高峰月产奶量和泌乳持久力。结果表明，与低产公牛家系相比，高产公牛家系的泌乳曲线通常具有较高的初始产奶量，参数ａ     

Genetic trends production and somatic cell count for Jersey cattle in Zimbabwe born from 1994 to 2005

Genetic trends for Jersey dairy cattle in Zimbabwe were estimated. A total of 10,986 lactation records were obtained from Zimbabwe Livestock Identification Trust, with cows calving in the period 1996 to 2008. An ASReml program fitting an animal model was used for the analyses. The animal model that was used included overall mean, herd-year-season, previous calving interval, and days dry as fixed effects while linear and quadratic regression coefficients of age at calving as covariates. Random effects were cow, permanent environmental effects, and residual error. The pedigree file included 1,228 animals born from 1994 to 2005. The traits studied were milk yield, fat yield, protein yield, fat percent, protein percent, and Log₁₀SCC. Results indicated that milk yield, fat yield, and protein yield increased genetically (P?<?0.0001) on average by 1.420, 0.160, and 0.164?kg per year, respectively. Fat percent, protein percent, and Log₁₀SCC declined over the past 12?years (P?<?0.0001) at the rate of ?0.021, ?0.015, and ?0.0002 per year, respectively. This was due to the negative correlation between milk composition and milk yield. The results implies that the selection applied in the last decade has achieved genetic progress and that there is genetic variance for continued improvement and for setting up an effective dairy breeding program in Zimbabwean Jersey herds for milk, fat, and protein production.     

Analysis of genotype by environment interaction for milk yield traits in first lactation of Simmental cattle

The breeding goal for Simmental cattle is derived for intensively managed dairy farms. Its suitability for extensive farms was addressed by analysing possible genotype by environment interaction (G × E) between the management levels for first lactation milk yield traits. A first analysis was performed with the data collected from 300 000 purebred daughters of 278 second crop bulls born in Bavaria in 1993 and 1994. The farms were classified by herd‐year‐effect, using the sum of fat and protein yields into two levels of management, either with 33 or 10% quantiles, corresponding to approximately 100 000 cows and 30 000 cows, respectively. The comparison was based on ‘daughter yield’ deviations (DYD). Correlations between DYD of extensive and intensive environments were 0.90, 0.91 and 0.87 for milk, fat and protein yield (kg) for 33% quantiles, respectively. Corresponding correlations for 10% quantiles were 0.85, 0.83 and 0.77. Despite high correlations, 50 out of 149 sires showed significant differences between DYD in different environments. Bulls with higher DYD for milk yield on intensive farms were superior in all environments. For the second analysis extensive and intensive farms in northern and southern Bavaria were chosen at random. Approximately 20 000 cows in each management class were used for the estimation of genetic parameters. In both regions phenotypic and additive‐genetic variances were higher in the intensively managed herds. Likewise heritabilities were higher for fat and protein yield, but not for milk where higher heritabilities were observed in 33% quantiles. Genetic correlations between extensive and intensive environments were 0.97 and above (33% quantiles). Ten per cent quantiles led to lower genetic correlations (0.90–0.95). Although no serious re‐ranking effects of sires were evident, the scale effect and the differences in genetic parameters should be taken into consideration in practical breeding.     

Estimation of genetic parameters for milk and fertility traits within and between low,medium and high dairy production systems in Kenya to account for genotype-by-environment interaction

Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305-day milk yield using the K-means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype-by-environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305-day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305-day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.     

Genetic parameters and predicted selection results for maternal traits related to lactation efficiency in sows

The increased productivity of sows increases the risk of a more pronounced negative energy balance during lactation. One possibility to prevent this is to increase the lactation efficiency (LE) genetically and thereby increase milk output for a given feed intake and mobilization of body tissue. The benefits of selection for LE depend on its heritability and the relationships with other traits of interest. The objectives of this study were to estimate genetic parameters for LE, its underlying traits, and to predict the consequences of current selection strategies in dam lines. Data from 4 farms were available to estimate genetic parameters. Heritabilities were estimated by using a univariate repeatability model, and genetic correlations were estimated bivariately. Selection index theory was used to predict the genetic progress by 3 alternative breeding programs: 1) a breeding program that aimed at balanced progress in the total number of piglets born, piglet mortality, and percent prolonged interval from weaning to estrus; 2) extension of this breeding goal with LE; and 3) a breeding goal that included only one selection criterion, litter weight gain, to demonstrate the effect of indirect selection for milk production. The heritability for LE was low (0.12). Body fat mass (0.52) and BW (0.45) of sows at the beginning of lactation showed the greatest heritabilities. Protein mass at the beginning of lactation, protein loss, weight loss, and ad libitum feed intake during lactation showed moderate heritabilities (0.39, 0.21, 0.20, and 0.30, respectively). Low to moderate heritabilities were found for litter weight at birth, within-litter SD in the birth weight of piglets, litter weight gain, fat loss, and restricted feed intake during lactation (0.19, 0.09, 0.18, 0.05, and 0.14, respectively). Within-litter SD in the weaning weight of piglets showed no genetic variability. It was predicted that a breeding goal for dam lines with an emphasis on the total number of piglets born, piglet mortality, and percent prolonged interval from weaning to estrus would not dramatically change BW or body composition at the beginning of lactation, or mobilization of body tissue and feed intake during lactation. Inclusion of LE in the breeding goal will improve stayability, as defined by the first-litter survival of sows and LE itself, without negative consequences for other economically important traits. Nevertheless, it might be worthwhile to design a breeding goal in which LE increases and feed intake remains unchanged.     

Lactation curves of dairy camels in an intensive system

Weekly milk records of 47 she-camels in a multibreed dairy camel herd were collected for over a period of 5 years. A total of 72 lactation curves were defined, and relationships with parity, calving season, lactation length, milk production level, following lactations, and dam weight were analyzed. Overall mean values were milk yield up to 12 months, 1,970?±?790 l; lactation length, 12.5 months; persistency, 94.7 %; weekly peak yield, 50.7 l; monthly peak yield, 220?±?90 l; and the number of weeks to reach peak yield, 28. The highest productivity was recorded in summer with a weekly mean of 48.2?±?19.4 l, compared with 34.1?±?16.3 l in winter. The highest average yield recorded was for camels at sixth parity, whereas the highest weekly peak was at eighth parity, and highest persistency at fifth parity. Camels that calved during the cold months (November to February) were most productives, with the highest persistency, peak yield, and longest lactation length. Four types of curves were identified corresponding to different parities and milk yield levels. Based on these data, specific models for camels are proposed.     

Application of multiple‐trait finite mixture model to test‐day records of milk yield and somatic cell score of Canadian Holsteins

Multiple‐trait (MT) finite mixture random regression (MIX) model was applied using Bayesian methods to first lactation test‐day (TD) milk yield and somatic cell score (SCS) of Canadian Holsteins, allowing for heterogeneity of distributions with respect to days in milk (DIM) in lactation. The assumption was that the associations between patterns of variation in these traits and mastitis would allow revealing the hidden structure in the data distribution because of unknown health status of cows. The MIX model assumed separate means and residual co‐variance structures for two components in four intervals of lactation, in addition to fitting the fixed effect of herd‐test‐day, and fixed and random regressions with Legendre polynomials. Results indicated that the mixture model was superior to standard MT model, as supported by the Bayes factor. Approximately 20% of TD records were classified as originated from cows with a putative, sub‐clinical form of mastitis. The proportion of records from mastitic cows was the largest at the beginning of lactation. The MIX model exhibited different distributions of data from healthy and infected cows in different parts of lactation. Records from sick cows were characterized by larger (smaller) means for SCS (milk) and larger variances. Residual, and daily genetic and environmental correlations between milk and SCS were smaller from the MIX model when compared with MT estimates. Heritabilities of both traits differed significantly among records from healthy, sick and MT model estimates. Both models fitted milk records from healthy cows relatively well. The ability of the MT model in handling SCS records, measured by model residuals, was low, but improved substantially, however, where the data were allowed to be separated into two components in the MIX parameterization. Correlations between estimated breeding values (EBV) for sires from both models were very high for cumulative milk yield (>0.99) and slightly lower (0.95 in the interval from 5 to 45 DIM) for daily SCS. EBV for SCS from MT and MIX models were weakly correlated with posterior probability of sub‐clinical mastitis on the phenotypic scale.     

Relationships among growth hormone and prolactin secretory parameter estimates in Holstein bulls and their predicted differences for lactational traits

Selection of dairy sires is based on the production records of their female ancestors, half-sibs and daughters. No trait expressed by the sire is used. Concentrations of growth hormone (GH) and prolactin (PRL), hormones produced in both males and females that are fundamental in lactation, may be correlated with production. A study was conducted to determine whether measures of these hormones in the sire would be useful predictors of lactational ability of daughters. Blood samples were collected at 15-min intervals for 8 h from 26 Holstein bulls (5.5 yr of age) that had one progeny summary available. Plasma concentrations of GH and PRL were quantified and the mean and baseline concentrations and the frequency and mean amplitude of the secretory peaks were determined for each bull. Concentrations among these values and bulls' predicted differences (PD) were determined. Significant negative correlations were detected for frequency of GH peaks and PD for yield of milk, fat and protein; correlations were positive for PRL baseline concentrations and PD for fat and protein (P less than .10), and correlations were negative for frequency of PRL peaks and PD for milk, fat and protein (P less than .10). Addition of estimates of bull hormone secretory parameters to breeding values based on performance of relatives considerably improved the accuracy (R2) for predicting progeny performance from sire information. Certain characteristics of the patterns of GH and PRL secretion may be heritable and aid in identification of superior dairy animals.     

Genomic and single-step evaluations of carcass traits of young bulls in dual-purpose cattle

Genetic evaluations for carcass traits of young bulls in Normande and Montbeliarde breeds are currently being developed in France. In order to determine a suitable genomic evaluation for three carcass traits of young bulls, genomic breeding values were estimated for young candidates to selection using different approaches. Records of 111,789 Normande and 118,183 Montbeliarde were used. Average progeny pre-adjusted performances (DYD) were calculated for sires. Evaluation approaches were compared based on an assessment of their accuracy (correlation between DYD and estimated breeding values [EBVs]) and bias (regression coefficient of DYD on EBVs) on the 20% youngest AI sires. All genomic approaches were generally more accurate than BLUP (+.045 to +.116 correlation points), except for age at slaughter where single-step GBLUP (SSGBLUP) was the only genomic method leading to a greater accuracy (+.038 to +.126 points). The best setting of the SSGBLUP relationship matrix was characterized by a weight of 30% for pedigree information in the genomic relationship matrix. SSGBLUP was the most valuable evaluation approach for the evaluation of carcass traits of Normande and Montbeliarde young bulls.     

Milk production and composition in captive Iberian red deer (Cervus elaphus hispanicus): effect of birth date

This study describes milk production and milk composition of Iberian red deer (Cervus elaphus hispanicus) females (hinds) and the effect of calving date and BW change of hinds by milking over 34 wk. All hinds produced milk throughout the 34-wk study period, well over the standard lactation period. Total milk yield was 224.1 +/- 21.1 L, and daily production was 0.91 +/- 0.06 L. Milk yield decreased with lactation stage (P = 0.01) and the later a calf was born (P = 0.008), and it was greater in posterior quarters (P < 0.05). Milk yield was unaffected (P > 0.10) by side position or milking order of the udder. Milk production did not correlate with hind BW (P > 0.1). Hinds lost 4.4% BW during lactation (P < 0.001); losses increased the later a calf was born (P = 0.012). Iberian red deer milk had 11.5% fat, 7.6% protein, 5.9% lactose, and 26.7% DM. Stage of lactation affected fat (P < 0.001), protein (P = 0.002), DM (P < 0.001), and protein:fat ratio (P < 0.001), but not lactose (P > 0.1). These constituents became concentrated as lactation proceeded, and protein was substituted by fat. Calving date had a similar concentrating effect on fat (P < 0.001) and DM (P < 0.001), whereas it decreased lactose (P = 0.015) and protein (P = 0.002), thus producing a substitution of protein by fat (ratio of protein to fat, P < 0.001). Milking order of quarters or their position had no effect on milk composition (P > 0.10). Results suggest that milk production and milk energetic quality might increase by advancing calving date in red deer hinds.     

Comparison of estimated breeding values, daughter yield deviations and de-regressed proofs within a whole genome scan for QTL

An important issue in quantitative trait loci (QTL) detection is the use of phenotypic measurement as a dependent variable. Daughter yield deviations (DYDs) as the unit of choice are not available for all traits of interest. The use of de-regressed proofs (DRPFs) of estimated breeding values (EBVs) is an alternative to using daughter yield deviations. The objective of this study was to examine possible differences between DYDs and DRPFs within the use of QTL detection. The pedigree used was part of the granddaughter design of the German QTL effort. Consisting marker maps for livestock species were derived from all available data of 16 German Holstein paternal half-sib families with a total of 872 sires. The number of progeny ranged from 19 to 127. A whole genome scan was performed using weighted and unweighted multimarker regression with DYDs, DRPFs and EBVs as dependent variables for the traits milk, fat and protein yields. Results were compared with respect to the number of QTL detected. A similar number of QTL was detected with DRPFs and DYDs. Also, when dependent variables were weighted according to the variance of the trait, a higher number of QTL was detected at the desired level of significance as compared to using unweighted variables.     

Milk yield and lactation length of Ghana Sanga and its crosses with the Friesian Raised under agropastoral system

Milk yield traits and lactation length of two breeds of cattle raised on natural pasture with little or no supplementation were assessed. A total of 42 573 daily milk records on 98 Friesian-Sanga cows collected over a period of 10 years and 17 790 daily milk records on 72 Sanga cows spanning a 6-year period were used in the study. Traits examined for each breed were daily milk yield, total milk yield, 305-day milk yield, 305-day milk yield/day and lactation length. Friesian-Sanga cows outperformed their Sanga counterparts in all traits studied. Friesian-Sanga cows had an average daily milk yield of 1.35?±?0.00 kg; average total milk yield of 266?±?12 kg; average 305-day milk yield of 339?±?10 kg; average 305-day milk yield/ day of 1.11?±?0.03 kg and mean lactation length of 201.1?±?6.9 days. Average values for Sanga cows were 1.01?±?0.00 kg as daily milk yield; 162?±?12 kg as total milk yield; 244?±?10 kg as 305-day milk yield; 0.80?±?0.03 kg as 305-day milk yield/day. Mean lactation length for Sanga cows was 164.1?±?9.4 days. Season of calving significantly (P?<?0.05) influenced daily milk yield of Friesian-Sanga cows and all traits of Sanga cows with animals calving in the major rainy season surpassing those that calved in the minor and dry seasons. Daily milk yield for both Friesian-Sanga and Sanga cows was significantly (P?<?0.05) influenced by season of lactation. Daily milk yield gradually declined from second parity towards the sixth parity for Friesian-Sanga cows. A gradual increase in daily milk yield from first to third parity was observed in Sanga cows. Year of calving significantly influenced all traits for both breeds. Genetic improvement in milk yield traits and lactation length is achievable for both breeds of cattle as co-efficient of variation of traits were moderate to high.     

Influence of genotype and yield and composition of milk on interval to first postpartum ovulation in milked beef and dairy cows.

Our objectives were to investigate the effects of genotype, yield and composition of milk, and changes in BW and body condition on the initiation of cyclic ovarian activity in nonsuckled beef and dairy cows milked twice daily. Nulliparous heifers were selected from three breeds, 12 Angus, 13 Simmentals, and 26 Holsteins, based on their EBV for milk yield. Cows were machine-milked twice daily, and daily milk yield was recorded; composite samples of milk were collected twice weekly for analyses of milk components. Blood was collected from all cows thrice weekly for 75 d postpartum, and concentrations of progesterone in serum measured by RIA were used to estimate day of first postpartum ovulation. Holstein cows produced more (P less than .05) milk (unadjusted or 3.5% fat-corrected) than Angus or Simmental cows during the first 30 d of lactation. Holstein cows had higher (P less than .01) peak yield of milk than Simmental and Angus cows. Days to peak milk yield were similar for Simmental and Holstein cows, and both were more (P less than .05) than those for Angus cows. Percentages of fat, protein, and total solids in milk were highest (P less than .05) for Simmental cows, whereas milk of Holstein cows had the highest (P less than .05) percentage of lactose and lowest (P less than .05) concentration of somatic cells. Average BW at ovulation differed (P less than .05) among breeds. Estimated daily changes in BW from calving to first ovulation were different (P less than .05) for Holstein and Simmental cows but were similar to those of Angus cows.(ABSTRACT TRUNCATED AT 250 WORDS)     

Comparison between genomic predictions using daughter yield deviation and conventional estimated breeding value as response variables

This study compared genomic predictions using conventional estimated breeding values (EBV) and daughter yield deviations (DYD) as response variables based on simulated data. Eight scenarios were simulated in regard to heritability (0.05 and 0.30), number of daughters per sire (30, 100, and unequal numbers with an average of 100 per sire) and numbers of genotyped sires (all or half of sires were genotyped). The simulated genome had a length of 1200 cM with 15,000 equally spaced Single-nucleotide polymorphism (SNP) markers and 500 randomly distributed Quantitative trait locus (QTL). In the simulated scenarios, the EBV approach was as effective as or slightly better than the DYD approach at predicting breeding value, dependent on simulated scenarios and statistical models. Applying a Bayesian common prior model (the same prior distribution of marker effect variance) and a linear mixed model (GBLUP), the EBV and DYD approaches provided similar genomic estimated breeding value (GEBV) reliabilities, except for scenarios with unequal numbers of daughters and half of sires without genotype, for which the EBV approach was superior to the DYD approach (by 1.2 and 2.4%). Using a Bayesian mixture prior model (mixture prior distribution of marker effect variance), the EBV approach resulted in slightly higher reliabilities of GEBV than the DYD approach (by 0.3-3.6% with an average of 1.9%), and more obvious in scenarios with low heritability, small or unequal numbers of daughters, and half of sires without genotype. Moreover, the results showed that the correlation between GEBV and conventional parent average (PA) was lower (corresponding to a relatively larger gain by including PA) when using the DYD approach than when using the EBV approach. Consequently, the two approaches led to similar reliability of an index combining GEBV and PA in most scenarios. These results indicate that EBV can be used as an alternative response variable for genomic prediction.     

Stochastic simulation of dairy cattle nucleus breeding schemes: Influence of breeding strategy and biased breeding values in the population

SUMMARY: A stochastic simulation model of an open nucleus scheme was used to study the consequences of the breeding strategy and biased lactation records for population cows. Selection was for a single sex-limited trait with a heritability of 0.25 and based on animal model breeding value estimates. Selection of dams was across age classes while sires were required to have a progeny test before they could be selected as proven bull or bull sire. Dams to breed nucleus replacements and young bulls could be selected from the nucleus and the top population which contained 240 and 1600 replacement heifers annually. The first 15 years of the simulated period was used to reach a population with an equilibrium genetic progress for a progeny testing scheme. Comparisons were based on the 25 year period after an alternative breeding scheme was adopted. The annual genetic gain was calculated from the last 10 years of that period. The annual genetic gain in an open nucleus breeding scheme was .247 σ(a) . The annual genetic gain increased 5.4% when MOET was also used on cows selected to breed replacements for the top population. When, in addition the number of sires used on top population cows was reduced from 8 to 4, that being the number used in the nucleus, the annual genetic gain increased by another 2.8%. The reduction in annual genetic gain due to biased lactation records of top population cows ranged from 4.6 to 15.4%. The average bias in estimated breeding values of the top population dams selected to breed nucleus replacements ranged from 0.53 to 2,52 σ(a) . The regression coefficient of the EBV of the bull after progeny testing on the EBV of the dam at the time of selection was 0.55 without biased lactations and ranged from 0.10 to 0.27 with biased lactations. The reduction in genetic gain was especially related to the regression coefficient and to a lesser extent to the average bias. In practice, the expected reduction in annual genetic gain from biased lactation records of population cows is expected to be between 5 and 10 %. ZUSAMMENFASSUNG: Stochastische Simulation von Milchvieh-Nukleussystemen: Einflu? der Zuchtstrategie und verzerrter Zuchtwerte in der Population Eine stochastische Simulation eines offenen Nukleussystems wurde zur Untersuchung der Konsequenzen der Zuchtstrategie und verzerrter Laktationsabschlüsse für Populationskühe untersucht. Selektion bezog sich auf ein einzelnes weibliches Merkmal mit Heritabilit?t von 1/4 und gründete auf Tiermodell Zuchtwertsch?tzungen, Selektion von Muttertieren über Altersklassen, w?hrend Stiere vor der Selektion einen Nachkommenschaftstest haben mu?ten. Muttertiere für Nukleus- und Jungstiere kommen vom Nukleus und Spitzen der Population, die 240 und 1600 nachgestellte Kalbinnen umfa?ten. Die ersten 15 Jahre der simulierten Periode wurden zum Erreichen einer Population mit Gleichgewichtsfortschritt für ein Nachkommenschaftsprüfsystem verwendet. Vergleiche beruhten auf einer 25-Jahre-Periode nach Einrichtung des alternativen Zuchtsystems, und der j?hrliche Zuchtfortschritt wurde für die letzten 10 Jahre berechnet. Der j?hrliche Zuchtfortschritt im offenen Nukleussystem war 0,247 σ(a) und nahm um 5,4% zu, wenn MOETauch für Kühe zum Ersatz der Spitzenpopulation verwendet wurde. Wenn darüber hinaus die Zahl der Vatertiere in der Spitzenpopulation von 8 auf 4 reduziert wurde, die Zahl der im Nukleus verwendeten, konnte der j?hrliche genetische Fortschritt um weitere 2, 8% gesteigert werden. Die Verminderung des Zuchtfortschrittes auf Grund von verzerrten Laktationsabschlüssen der Spitzenkühe der Population variierte von 4,6 bis 15,4%. Die durchschnittliche Verzerrung der gesch?tzten Zuchtwerte der Populationsspitzenkühe für die Nukleusremonte bewegte sich von 0,53 bis 2,52 σ(a) . Der Regressionskoeffizient von EBV der Stiere auf Grund von Nachkommenschaftsprüfung auf EBV der Muttertiere beim Zeitpunkt der Selektion war 0,55 ohne verzerrte Laktationen und schwankte zwischen 0,10 und 0,27 bei verzerrten Laktationen. Die Verminderung des genetischen Fortschritts hing deutlich mit dem Regressionskoeffizient zusammen und weniger mit der durchschnittlichen Verzerrung. In der Praxis ist zu erwarten, da? die Reduktion des Zuchtfortschrittes durch verzerrte Laktationsabschlüsse der Population zwischen 5 und 10% liegt.     

中国荷斯坦牛RPL23A和ACACB基因对产奶性状的遗传效应分析

作者所在团队前期通过奶牛乳腺上皮组织转录组测序及荷斯坦公牛全基因组重测序研究发现RPL23A和ACACB基因是奶牛乳蛋白和乳脂性状的候选功能基因,本研究旨在探究这两个基因是否对奶牛产奶性状具有显著遗传效应。以北京地区7个牧场的1059头中国荷斯坦母牛为试验群体,采集尾根静脉血并提取基因组DNA,通过飞行时间质谱方法检测SNP位点基因型,利用SAS9.4软件的MIXED过程进行关联分析。结果表明,RPL23A基因的SNP位点g.20146771C>T与第1泌乳期5个产奶性状达到显著或极显著关联(P=0.0001~0.0416),其优势等位基因为T;ACACB基因的g.63878254T>C位点与第1泌乳期产奶量、乳脂量和乳蛋白量呈极显著关联(P<0.01),其优势等位基因为C;g.63962768G>A位点与第1泌乳期产奶量、乳脂量、乳脂率和乳蛋白率关联显著或极显著(P=0.0001~0.0391),其优势等位基因为A。综上,RPL23A基因主要影响中国荷斯坦牛产奶量和乳蛋白,ACACB基因对产奶量和乳脂具有显著遗传效应,3个SNP位点可考虑作为遗传标记用于标记辅助选择培育奶牛高乳蛋白乳脂新品系和选育提高。     

Estimation of Variances and Covariances of Milk Traits by REML with an Individual Animal Model

Abstract

Records form Finnish Ayrshire cattle were used to estimate variances and covariances of milk traits by the restricted maximum likelihood (REML) method using the individual animal model (IAM). Two data sets were analyzed. The first data set consisted of 1423 sires and 16363 cows, of which 11911 had records on first lactation. The heritabilities estimated from this data set for milk yield, protein yield, protein content and fat content were 0.40, 0.31, 0.63 and 0.68, respectively. The second data set was a subset of first data set with herds with less than ten observations excluded and consisted of 1335 sires and 11262 cows with 8140 first, 5688 second and 3717 third lactation records. The heritability estimates from the second data set under a repeatability model for milk yield, protein yield, protein content and fat content were 0.30, 0.26, 0.59 and 0.66, respectively. The repeatability estimates for the same traits were 0.53, 0.51, 0.67 and 0.76, respectively. The second data set was also used to estimate genetic and phenotypic correlations among milk traits in first lactation. Both genetic and phenotypic correlations among protein yield and protein and fat content traits were small. The genetic correlation between milk yield and protein content was -0.61, between milk yield and fat content -0.50 and between protein content and fat content 0.67. Absolute values of phenotypic correlations for the same pairs of traits were somewhat smaller than respective genetic correlations.     

Estimates of genetic parameters for Boran, Friesian, and crosses of Friesian and Jersey with the Boran cattle in the tropical highlands of Ethiopia: milk production traits and cow weight

Breed additive and non‐additive effects plus heritabilities and repeatabilities for milk yield per lactation (LMY), milk yield per day (DMY), lactation length (LL), annual milk yield (AMY), annual milk yield per metabolic body weight (AMYBW) and cow weight at calving (BW) were estimated for 5464 lactation records collected from purebred Boran (B), Friesian (F), and crosses of Friesian and Jersey (J) breeds with the Boran breed raised in the tropical highlands of Ethiopia. Single trait analysis was carried out by using two equivalent repeatability animal models. In the first model the genotype was fitted as a fixed group effect, while in the second model the genotype was substituted by breed additive, heterotic and recombination effects fitted as fixed covariates. Both the F and J breed additive effects, measured as a deviation from the B breed were significant (p < 0.01) for all traits, except for BW of the J. The F and J additive contributions were 2774 ± 81 and 1473 ± 362 kg for LMY, 7.1 ± 0.2 and 4.8 ± 0.8 kg for DMY, 152 ± 7 and 146 ± 31 days for LL, 2345 ± 71 and 1238 ± 319 kg for AMY, 20.6 ± 0.9 and 18.9 ± 4.3 kg for AMYBW, and 140 ± 4 and ?21 ± 22 kg (p > 0.05) for BW. The heterotic contributions to the crossbred performance were also positive and significant (p < 0.01) for all traits. The F₁ heterosis expressed as a deviation from the mid‐parent values were 22 and 66% for LMY, 11 and 20% for DMY, 29 and 29% for LL, 21 and 64% for AMY, 42 and 42% for AMYBW, and 2% (p < 0.05) and 11% for BW for the F × B and J × B crosses, respectively. The recombination effect estimated for the F × B crosses was negative and significant for LMY (?526 ± 192 kg, p < 0.01), DMY (?3.0 ± 0.4 kg, p < 0.001), AMY (?349 ± 174 kg, p < 0.05) and BW (?68 ± 11 kg, p < 0.001). For the J × B crosses the recombination loss was significant and negative only for DMY (?2.2 ± 0.7 kg, p < 0.05) and BW (?33 ± 17 kg, p < 0.05). The direct heritabilities (h²) estimated for LMY, DMY, LL, AMY and AMYBW were 0.24 ± 0.04, 0.19 ± 0.03, 0.13 ± 0.03, 0.23 ± 0.04 and 0.17 ± 0.05, respectively. Based on the genetic parameters estimated, the best breeding strategy to increased milk production under highland Ethiopian conditions is to apply selection on purebred base populations (Boran and Friesian) and then crossing them to produce F₁ dairy cows. However, for breeding decision based on total dairy merit, further investigations are needed for traits such as milk quality, reproduction, longevity and survival.