Non-lactational traits of importance in dairy cows and applications for emerging biotechnologies

Dairy cattle have traditionally been selected for their ability to produce milk and milk components. The traditional single-minded approach to selection of dairy cattle has now changed and secondary traits are being included in selection indices by decreasing the emphasis on production. Greater emphasis on non-production traits reflects the industry's desire for functional dairy cattle. Six broad categories of non-lactational traits are discussed in this review. They are: type; growth, body size and composition; efficiency of feed utilisation; disease resistance, e.g. udder health as measured by somatic cell score; reproduction; and management. Most of these traits can be found within selection indices worldwide, although relative emphasis varies. The non-lactational traits mentioned above are quantitative, meaning that the phenotype in the whole animal represents the sum of lesser traits that cannot be easily measured. The physiological mechanisms that underlie quantitative traits are extremely complex. Genetic selection can be applied to quantitative traits but it is difficult to link successful genetic selection with the underlying physiological mechanisms. The importance that the bovine genome sequence will play in the future of the genetics of dairy cattle cannot be understated. Completing the bovine genome sequence is the first step towards modernising our approach to the genetics of dairy cattle. Finding genes in the genome is difficult and scanning billions of base pairs of DNA is an imperfect task. The function of most genes is either unknown or incompletely understood. Combining all of the information into a useable format is known as bioinformatics. At the present time, our capacity to generate information is great but our capacity to understand the information is small. The important information resides within subtle changes in gene expression and within the cumulative effect that these have. Traditional methods of genetic selection in dairy cattle will be used for the foreseeable future. Most non-lactational traits are heritable and will be included in selection indices if the traits have value. The long-term prognosis for genome science is good but advances will take time. Genetic selection in the genome era will be different because DNA sequence analysis may replace traditional methods of genetic selection.     

Lactational traits of importance in dairy cows and applications for emerging biotechnologies

New molecular and quantitative genetic technologies are the latest in a long list of technologies that have been introduced to dairy industries over many decades to improve the performance of cows. The catalysts for future advances will be sequencing of the bovine genome and development of high-throughput technologies to identify and exploit relevant variation in DNA sequences. The new technologies will allow the selection of animals based on specific genotypes that suit specific applications such as once-daily (OAD) milking or extended lactation.

These technologies will also allow exploitation of between-cow variation in milk composition, which is currently hidden by bulking of milk on and between farms. Thus, there are opportunities to produce milk from herds of cows selected for specific milk composition that might be, for example, more suitable for cheese-making or have milkfat with specific properties to enhance human health. Identification of genes and gene polymorphisms associated with improved resistance to specific diseases in cows and other farm species also represents a real opportunity to improve animal health over the coming decade.

New levels of genetic regulation have been identified, e.g. microRNA and epigenetics, the impacts of which on the performance of cows and humans are only just beginning to be understood.

There is a potential role for veterinarians to provide or be the interface for provision of genetic advice to farmers in much the same way that nutritional advice is currently given.     

Lactational traits of importance in dairy cows and applications for emerging biotechnologies

New molecular and quantitative genetic technologies are the latest in a long list of technologies that have been introduced to dairy industries over many decades to improve the performance of cows. The catalysts for future advances will be sequencing of the bovine genome and development of high-throughput technologies to identify and exploit relevant variation in DNA sequences. The new technologies will allow the selection of animals based on specific genotypes that suit specific applications such as once-daily (OAD) milking or extended lactation. These technologies will also allow exploitation of between-cow variation in milk composition, which is currently hidden by bulking of milk on and between farms. Thus, there are opportunities to produce milk from herds of cows selected for specific milk composition that might be, for example, more suitable for cheese-making or have milkfat with specific properties to enhance human health. Identification of genes and gene polymorphisms associated with improved resistance to specific diseases in cows and other farm species also represents a real opportunity to improve animal health over the coming decade. New levels of genetic regulation have been identified, e.g. microRNA and epigenetics, the impacts of which on the performance of cows and humans are only just beginning to be understood. There is a potential role for veterinarians to provide or be the interface for provision of genetic advice to farmers in much the same way that nutritional advice is currently given.     

Quantitative trait loci for milk production and functional traits in two Danish Cattle breeds

Quantitative trait loci (QTL) in Danish Jersey and Danish Red cattle were independently mapped by least squares regression analysis. For Jersey breed, five grandsire families were genotyped for 186 markers on 16 chromosomes (BTAs). Eight traits analysed were milk yield (MY), fat percentage (FP), protein percentage (PP), clinical mastitis (CM), somatic cell score (SCS), maternal stillbirth, maternal calf size (MCS) and maternal calving difficulty. For Red breed, nine grandsire families were genotyped for 166 markers on 18 BTAs. Six traits analysed were MY, FP, PP, CM, SCS and female fertility. Nine and five QTL were detected in Jersey and Red breed, respectively, in across family tests. In Jersey breed, the results indicate QTL for CM and MCS on BTA 3. Additionally, there is an indication of QTL for MCS and FP on BTA 1 and a tentative evidence for a QTL for MY on BTA 26. There is a high risk of detected QTL being false positives. The detected QTL in Jersey breed indicate interesting results from a breeding perspective, but a practical application should await genome-wide association studies.     

Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle

Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences. Estimated proportion of TD records originated from cows infected with mastitis was 0.66 in DIM from 5 to 15 and averaged 0.2 in the remaining part of lactation. Data from healthy and mastitic cows exhibited markedly different distributions, with respect to both average value and the variance, across all parts of lactation. Heterogeneity of distributions for infected cows was also apparent in different DIM intervals. Cows with mastitis were characterized by smaller milk yield (down to -5 kg) and larger F:P (up to 0.13) and SCS (up to 1.3) compared with healthy contemporaries. Differences in averages between healthy and infected cows for F:P were the most profound at the beginning of lactation, when a dairy cow suffers the strongest energy deficit and is therefore more prone to mammary infection. Residual variances for data from infected cows were substantially larger than for the other mixture components. Fat-to-protein ratio had a significant genetic component, with estimates of heritability that were larger or comparable with milk yield, and was not strongly correlated with milk and SCS on both genetic and environmental scales. Daily milk, F:P and SCS are easily available from milk-recording data for most breeding schemes in dairy cattle. Fat-to-protein ratio can potentially be a valuable addition to SCS and milk yield as an indicator trait for selection against mastitis.     

籽鹅卵巢组织中铁蛋白重链基因和8个新ESTs的定量研究

采用实时定量PCR技术定量检测产蛋前期和产蛋期籽鹅卵巢组织中铁蛋白重链基因(FTH)和8个新ESTs(ODEUG01~ODEUG08)的mRNA表达水平。结果表明:产蛋期籽鹅卵巢组织中FTH和8个新ESTs的相对表达量分别比产蛋前期卵巢组织高13.25、7.68、11.82、14.23、8.25、15.14、9.78、6.48、14.21倍。本研究进一步证实,FTH和8个新ESTs在产蛋期籽鹅卵巢组织中高效表达,FTH和8个新ESTs可能参与籽鹅卵巢功能的调节,并影响籽鹅的产蛋性能。     

几种基因差异表达筛选技术在动物发育与繁殖中的最新进展

抑制性消减杂交(SSH)、DNA芯片和基因表达系列分析(SAGE)技术都是高效鉴别不同细胞群之间差异表达基因的方法。作者对这3种方法在动物发育与繁殖领域中的最新应用进展作了简要阐述。     

Whole-genome QTL scan for ultrasound and carcass merit traits in beef cattle using Bayesian shrinkage method

Fine mapping of quantitative trait loci (QTL) for 16 ultrasound measurements and carcass merit traits that were collected from 418 hybrid steers was conducted using 1207 SNP markers covering the entire genome. These SNP markers were evaluated using a Bayesian shrinkage estimation method and the empirical critical significant thresholds (α = 0.05 and α = 0.01) were determined by permutation based on 3500 permuted datasets for each trait to control the genome-wide type I error rates. The analyses identified a total of 105 QTLs (p < 0.05) for seven ultrasound measure traits including ultrasound backfat, ultrasound marbling and ultrasound ribeye area and 113 QTLs for seven carcass merit traits of carcass weight, grade fat, average backfat, ribeye area, lean meat yield, marbling and yield grade. Proportion of phenotypic variance accounted for by a single QTL ranged from 0.06% for mean ultrasound backfat to 4.83% for carcass marbling (CMAR) score, while proportion of the phenotypic variance accounted for by all significant (p < 0.05) QTL identified for a single trait ranged from 4.54% for carcass weight to 23.87% for CMAR.     

Evaluation of association between polymorphism within the thyroglobulin gene and milk production traits in dairy cattle

In dairy cattle, many studies have reported quantitative trait loci (QTL) on the centromeric end of chromosome 14 that affect milk production traits. One of the candidate genes in this QTL region – thyroglobulin (TG) – was previously found to be significantly associated with marbling in beef cattle. Thus, based on QTL studies in dairy cattle and because of possible effects of this gene on fat metabolism, we investigated the association of TG with milk yield and composition in Holstein dairy cattle. A total of 1279 bulls from the Cooperative Dairy DNA Repository Holstein population were genotyped for a single nucleotide polymorphism in TG used previously in beef cattle studies. Analysis of 29 sire families showed no significant association between TG variants and milk production traits. Within‐sire family analysis suggests that TG is neither the responsible gene nor a genetic marker in association with milk production traits.     

Cervix–rectum temperature differential at the time of insemination is correlated with the potential for pregnancy in dairy cows

This study sought to establish whether temperature gradients between the cervix, vagina, and rectum at and 7 days post-artificial insemination (AI) were associated with the incidence of pregnancy in lactating dairy cows (Experiment I; n = 90 ovulating cows) and to evaluate temperature gradient dynamics from the time of insemination to 7 days post-AI under heat stress conditions (Experiment II; n = 16 ovulating and 4 non-ovulating cows). In Experiment I, 39 cows (43.3%) became pregnant. The odds ratio for pregnancy was 2.5 for each one-tenth of a degree drop in cervical temperature with reference to the control rectal temperature at the time of AI (P = 0.01), whereas the same decrease in the cervix–rectum temperature differential 7 days post-AI resulted in an odds ratio of 0.44 (P = 0.02). In Experiment II, 5 of the ovulating cows (31.3%) became pregnant. The mean values of the vagina–rectum, vagina–cervix, and cervix–rectum temperature differentials at AI (day 0), 8 h, 24 h, and 7 days post-AI changed significantly from day 0 to day 7 (within-subject effect; P < 0.02) in ovulating cows but not in non-ovulating cows. Temperature differentials on days 0 and 7 were similar between ovulating cows and cows of Experiment I. Overall, our findings support the notion that a temperature differential between the caudal cervical canal and rectum at AI may be an indicator of the likelihood of pregnancy. Possible prospects of confirming estrus at the herd-level are also suggested.     

Quantifying characteristics of information-technology applications based on expert knowledge for detection of oestrus and mastitis in dairy cows

Expert opinions were elicited about the characteristics at the commercial-farm level of on-line information technology (IT) applications that are able to detect oestrus and mastitis in dairy cows. Since actual data of these characteristics are not available, judgmental data provided an alternative means to interpret the implications of research results for commercial farms. Applications included were activity measurement, milk-production measurement, electrical conductivity of quarter milk, automated concentrate feeders and milk-temperature measurement. Sensitivity and specificity of detection of oestrus (OD), clinical-mastitis (CMD) and subclinical-mastitis (SCMD) were ascertained. Conjoint-analysis was used to assess the effect of each application indirectly by decomposing the evaluated overall detection characteristics of a predefined number of IT combinations.

The individual experts were consistent in evaluating the alternatives, but there was variation in estimates among experts. Estimations of the main effects of the applications and important first-order interactions were incorporated into the detection models. Implementation of all applications under study resulted in overall sensitivities and specificities of 82% and 90%, 73% and 87%, 58% and 82% for OD, CMD and SCMD, respectively. Further research is necessary that should take into account costs and benefits of the different detection systems based on the current status of farm performance (e.g. OD and mastitis incidence) and farm structure (e.g. farm size, years in operation of the milking parlour and parlour layout). Research to do this is currently in progress.     

Interval mapping of growth quantitative trait loci in Japanese Black beef cattle using microsatellite DNA markers and half-sib regression analysis

A confirmatory scan for the regions of bovine chromosome 1 segregating the quantitative trait loci (QTL) influencing birthweight, weaning weight, yearling weight, and preweaning and postweaning average daily gains was performed by genotyping half‐sib progeny of four Japanese Black sires using microsatellite DNA markers. Data were analyzed by generating an F‐statistic every 1 cM on a linkage map by the regression of phenotype on the probabilities of inheriting an allele from the sire after adjusting for the fixed effects of sire, sex, parity and season of birth as well as age as a covariate. Permutation tests at chromosome‐wide significance thresholds were carried out over 10 000 iterations. A significant QTL for birthweight at 114 cM was detected in the sire 2 family. This identification of a birthweight QTL in Japanese Black cattle may be useful for the implementation of marker‐assisted selection.     

拷贝数变异全基因组关联分析及数量性状基因座定位联合鉴定猪体高性状候选基因

旨在利用全基因组拷贝数变异区域（copy number variation regions,CNVRs）关联分析以及全基因组数量性状基因座（quantitative trait locus,QTLs）定位联合筛选出影响猪体高性状的候选基因。本研究利用快速检测基因组拷贝数变异软件CNVcaller对本实验室构建的大白×民猪F2代资源群体的重测序数据进行拷贝数变异检测。利用混合线性模型（mixed-linear model,MLM）将性别和胎次作为固定效应对体高性状进行拷贝数变异全基因组关联分析（CNVR-GWAS）。采用软件R/qtl进行QTL分析,并使用置换检验（permutation test,PT）进行检验。将CNVR-GWAS与QTL结果进行联合注释,结合GO富集和KEGG通路分析,对影响猪体高的位点和基因进行挖掘。利用实时荧光定量PCR（qPCR）方法验证候选基因。结果表明,本群体在全基因组范围内共有3 099个CNVRs,其中有两个CNVRs与体高性状在全基因组范围内显著相关,分别位于7号染色体的25 358 001~26 696 400 bp处（CNVR1）和54 087 201~54 090 000 bp处（CNVR2）。在混合线性模型分析的结果中发现,CNVR1拷贝数增加（P<0.01）和CNVR2拷贝数缺失（P<0.01）对猪的体高性状具有显著影响。基因组显著水平可找到2个显著影响猪体高的QTLs,分别为BH-1和BH-2,其中BH-2对体高性状的影响较大。CNVR1和BH-2重叠区存在1个嗅觉受体基因OR12D3和18个未被注释的基因。qPCR验证OR12D3的拷贝数变异与利用混合线性模型统计推断出的结果一致。初步推测,OR12D3基因的拷贝数变异可能与猪体高性状相关。