Should genetic groups be fitted in BLUP evaluation? Practical answer for the French AI beef sire evaluation

Some analytical and simulated criteria were used to determine whether a priori genetic differences among groups, which are not accounted for by the relationship matrix, ought to be fitted in models for genetic evaluation, depending on the data structure and the accuracy of the evaluation. These criteria were the mean square error of some extreme contrasts between animals, the true genetic superiority of animals selected across groups, i.e. the selection response, and the magnitude of selection bias (difference between true and predicted selection responses). The different statistical models studied considered either fixed or random genetic groups (based on six different years of birth) versus ignoring the genetic group effects in a sire model. Including fixed genetic groups led to an overestimation of selection response under BLUP selection across groups despite the unbiasedness of the estimation, i.e. despite the correct estimation of differences between genetic groups. This overestimation was extremely important in numerical applications which considered two kinds of within-station progeny test designs for French purebred beef cattle AI sire evaluation across years: the reference sire design and the repeater sire design. When assuming a priori genetic differences due to the existence of a genetic trend of around 20% of genetic standard deviation for a trait with h² = 0.4, in a repeater sire design, the overestimation of the genetic superiority of bulls selected across groups varied from about 10% for an across-year selection rate p = 1/6 and an accurate selection index (100 progeny records per sire) to 75% for p = 1/2 and a less accurate selection index (20 progeny records per sire). This overestimation decreased when the genetic trend, the heritability of the trait, the accuracy of the evaluation or the connectedness of the design increased. Whatever the data design, a model of genetic evaluation without groups was preferred to a model with genetic groups when the genetic trend was in the range of likely values in cattle breeding programs (0 to 20% of genetic standard deviation). In such a case, including random groups was pointless and including fixed groups led to a large overestimation of selection response, smaller true selection response across groups and larger variance of estimation of the differences between groups. Although the genetic trend was correctly predicted by a model fitting fixed genetic groups, important errors in predicting individual breeding values led to incorrect ranking of animals across groups and, consequently, led to lower selection response.     

DGAT1 underlies large genetic variation in milk-fat composition of dairy cows

Dietary fat may play a role in the aetiology of many chronic diseases. Milk and milk-derived foods contribute substantially to dietary fat, but have a fat composition that is not optimal for human health. We measured the fat composition of milk samples in 1918 Dutch Holstein Friesian cows in their first lactation and estimated genetic parameters for fatty acids. Substantial genetic variation in milk-fat composition was found: heritabilities were high for short- and medium-chain fatty acids (C4:0-C16:0) and moderate for long-chain fatty acids (saturated and unsaturated C18). We genotyped 1762 cows for the DGAT1 K232A polymorphism, which is known to affect milk-fat percentage, to study the effect of the polymorphism on milk-fat composition. We found that the DGAT1 K232A polymorphism has a clear influence on milk-fat composition. The DGAT1 allele that encodes lysine (K) at position 232 (232K) is associated with more saturated fat; a larger fraction of C16:0; and smaller fractions of C14:0, unsaturated C18 and conjugated linoleic acid (P < 0.001). We conclude that selective breeding can make a significant contribution to change the fat composition of cow's milk.     

Genome-wide genetic diversity of Holstein Friesian cattle reveals new insights into Australian and global population variability, including impact of selection

Past breeding strategies for dairy cattle have been very effective in producing rapid genetic gain to achieve industry targets and raise profitability. Such gains have been largely facilitated by intense selection of sires combined with the use of artificial insemination. However, this practice can potentially limit the level of genetic diversity through inbreeding and selection plateaus. The rate of inbreeding in Australia is increasing, primarily as a result of semen importation from a small number of prominent bulls from the USA. The effect of this genetic influx in the Australian dairy cattle population is poorly understood both in terms of diversity and local adaptation/divergence. This study uses 845 genome-wide SNP genetic markers and 431 bulls to characterize the level of genetic diversity and genetic divergence within the Australian and international Holstein Friesian dairy population. No significant differences in genetic diversity (as measured by heterozygosity [H(o)] and allelic richness [A]) were observed over the 25-year time period (1975-1999) for bulls used in Australia. The importation of foreign semen into Australia has increased the effective population size until it was in effect a sub-sample of the global population. Our data indicate that most individuals are equally closely related to one another, regardless of country of origin and year of birth. In effect, the global population can be considered as one single population unit. These results indicate that inbreeding, genetic drift and selection has had little effect at reducing genetic diversity and differentiating the Australian Holstein Friesian population at a genome-wide level.     

奶牛微卫星基因座与产奶性能关系的研究

根据小鼠与牛的遗传比较图谱及相关报道选择了与weaver基因连锁的7个微卫星基因库,并在荷斯坦牛群体中对这些基因座进行群体遗传学特性分析。选择具有中度以上多态性的4个微卫星基因座（BM6438、BMS2321、BMS711和TGLA116）进行产奶性能的相关分析。最小二乘分析结果表明,4个微卫星基因座对产奶量影响不显著（P＞0．05）,BM6438生BMS711基因座对乳成分影响不显著（P＞0．05）,BMS2321基因座对乳蛋白量和乳蛋白率有极显著的影响（P＜0．01）,TGLA116对乳蛋白量和乳蛋白率的影响达到0．05的显著水平。     

Casein haplotypes and their association with milk production traits in the Finnish Ayrshire cattle

Polymorphism of casein genes was studied in half-sib families of artificial insemination bulls of the Finnish Ayrshire dairy breed. Ten grandsires and 300 of their sons were genotyped for the following polymorphisms: α_S1-casein (B, C), β-casein (A¹, A²), the microsatellite within the K-casein gene (ms⁵, ms⁴) and K-casein (A, B, E). Nine different combinations of these alleles, casein haplotypes, were found. Associations between casein haplotypes and milk production traits (milk and protein yield, fat and protein percentage and milking speed) were studied with ordinary least-squares analysis to find a direct effect of the haplotypes or an association within individual grandsire families using the granddaughter design. Estimated breeding values of sons were obtained from cow evaluation by animal model. No direct effect of the casein haplotypes on the traits was found. Within grandsire families, in one out of four families the chromosomal segment characterized by haplotype 3 (B-A²-ms⁴-A) was associated with an increase in milk yield ( P <0.01) and a decrease in fat percentage ( P < 0.01) when contrasted with haplotype 8 (B-A¹-ms⁴-E). The results provide evidence that in the Finnish Ayrshire breed at least one quantitative trait locus affecting the genetic variation in yields traits is segregating linked to either haplotype 3 (B-A²-ms⁴-A) or 8 (B-A¹-ms⁴-E).     

Associations between genetic merit for milk production and animal parameters and the fertility performance of dairy cows

Relationships between genetic merit for milk production and animal parameters and various parameters of reproductive performance were examined using multilevel binary response analysis in a study of 19 dairy herds for three successive years, representing approximately 2500 cows per year. The proportion of cows intended for rebreeding that were back in-calf again within 100 days of calving (ICR-100) and the proportion of cows that reappeared again with 365 (RR-365) and 400 days (RR-400) of a previous calving were considered in addition to the traditional measures of reproductive performance. Each 100-kg increase in genetic merit for milk yield was associated with an increased interval to first service (IFS) and calving index (CI) of 1.4 ( P < 0.001) and 1.8 days ( P < 0.001), respectively, a 0.5% increase ( P < 0.05) in calving rate to first insemination (CR-1) and 0.8% increase in RR-400. Each £10 increase in £PIN (the economically weighted yield selection index used in the UK that takes account of butterfat and protein yields) was associated with an increased IFS and CI of 1.5 ( P < 0.001) and 3.0 days ( P < 0.001), respectively. Cows with increased genetic merit for milk yield and £PIN were more likely to re-calve (RR-overall; P < 0.001). Each 1000-kg increase in 305-day milk yield was associated with an increased IFS and CI of 3.2 ( P < 0.001) and 7.8 days ( P < 0.001), respectively, and a 13.6 ( P < 0.001), 22.4 ( P < 0.001), 19.9 ( P < 0.001) and 19.0% ( P < 0.001) decrease in CR-1, ICR-100, RR-365 and RR-400, respectively. A 10-kg increase in maximum yield was associated with a 6.6-day increase in CI ( P < 0.001) and a 14.9 ( P < 0.001), 18.3 ( P < 0.001), 9.6 ( P < 0.05) and 14.2% ( P < 0.001) decrease in CR-1, ICR-100, RR-365 and RR-400, respectively. Fertility performance was also associated with season of calving, lactation number and dystocia score. Level of production had a larger effect on fertility performance than genetic merit for milk production suggesting that infertility at an individual cow level is more likely to be associated with increased production and an inability to meet the nutritional requirements of the cow.     

Seasonal variations in the composition of Holstein cow’s milk and temperature–humidity index relationship

A retrospective study on seasonal variations in the characteristics of cow’s milk and temperature–humidity index (THI) relationship was conducted on bulk milk data collected from 2003 to 2009. The THI relationship study was carried out on 508 613 bulk milk data items recorded in 3328 dairy farms form the Lombardy region, Italy. Temperature and relative humidity data from 40 weather stations were used to calculate THI. Milk characteristics data referred to somatic cell count (SCC), total bacterial count (TBC), fat percentage (FA%) and protein percentage (PR%). Annual, seasonal and monthly variations in milk composition were evaluated on 656 064 data items recorded in 3727 dairy farms. The model highlighted a significant association between the year, season and month, and the parameters analysed (SCC, TBC, FA%, PR%). The summer season emerged as the most critical season. Of the summer months, July presented the most critical conditions for TBC, FA% and PR%, (52 054±183 655, 3.73%±0.35% and 3.30%±0.15%, respectively), and August presented higher values of SCC (369 503±228 377). Each milk record was linked to THI data calculated at the nearest weather station. The analysis demonstrated a positive correlation between THI and SCC and TBC, and indicated a significant change in the slope at 57.3 and 72.8 maximum THI, respectively. The model demonstrated a negative correlation between THI and FA% and PR% and provided breakpoints in the pattern at 50.2 and 65.2 maximum THI, respectively. The results of this study indicate the presence of critical climatic thresholds for bulk tank milk composition in dairy cows. Such indications could facilitate the adoption of heat management strategies, which may ensure the health and production of dairy cows and limit related economic losses.     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状,随着平衡育种理念的提出和发展,繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展,全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。