Poor fertility has become a major reason for involuntary culling of dairy cows in the United Kingdom. Calving interval (CI) and body condition score (BCS) are recorded, heritable, genetically correlated with each other, and could be used to extend the scope of dairy indices to include fertility traits. The use of U.K. insemination information for the evaluation of fertility has not been examined previously. Fertility and correlated traits were examined using nationally recorded milk (MILK = daily milk yield at test nearest d 110), BSC, and fertility traits (CI and the insemination traits of nonreturn rate after 56 d, NR56; days to first service, DFS; and number of inseminations per conception, INS). Genetic parameters for the traits were estimated simultaneously with a multitrait sire maternal grandsire (MGS) model and a multitrait BLUP sire MGS model was used to predict sire predicted transmitting abilities for each trait. The relationship between the fertility traits and other predicted transmitting abilities calculated in the United Kingdom was then examined. Heritabilities for the fertility traits were CI = 0.033 +/- 0.01, DFS = 0.037 +/- 0.01, NR56 = 0.018 +/- 0.001, and INS = 0.020 +/- 0.001, with a genetic correlation of 0.671 +/- 0.063 between CI and DFS and -0.939 +/- 0.031 between NR56 and INS. There was an unfavorable genetic correlation between the fertility traits and milk yield and BCS. Predicted transmitting abilities produced are similar in size and range to those produced in other studies and genetic trends are as expected. Results to date are encouraging and suggest that the planned program of work will lead to a fertility index that, when used by breeding companies, will lead to improvements in national dairy cow fertility.
The impact of 9 single nucleotide polymorphisms (SNP) in the leptin (LEP), leptin receptor (LEPR), growth hormone receptor (GHR), and diacylglycerol acyltransferase (DGAT1) gene loci on daily milk production, feed intake, and feed conversion, and weekly measures of live weight, BCS, and body energy traits was evaluated using genetic and phenotypic data on 571 Holstein cows raised at the Langhill Dairy Cattle Research Center in Scotland. Six SNP were typed on the LEP gene and 1 on each of the other 3 loci. Of the 6 LEP SNP, 3 were in very high linkage disequilibrium, meaning there is little gain in typing all of them in the future. Seven LEP haplotypes were identified by parsimony-based analyses. Random-regression allelesubstitution models were used to assess the impact of each SNP allele or haplotype on the traits of interest. Diacylglycerol acyltransferase had a significant effect on milk yield, whereas GHR significantly affected feed intake, feed conversion, and body energy traits. There was also evidence of dominance in allelic effects on milk yield and BCS. The LEP haplotype CCGTTT (corresponding to leptin SNP C207T, C528T, A1457G, C963T, A252T, and C305T, respectively) significantly affected milk yield and feed and dry matter intake. Animals carrying this haplotype produced 3.13 kg more milk daily and consumed 4.64 kg more feed. Furthermore, they tended to preserve more energy than average. Such results may be used to facilitate genetic selection in animal breeding programs.
Energy balance, especially in early lactation, is known to be associated with subsequent health and fertility in dairy cows. However, its inclusion in routine management decisions or breeding programs is hindered by the lack of quick, easy, and inexpensive measures of energy balance. The objective of this study was to evaluate the potential of mid-infrared (MIR) analysis of milk, routinely available from all milk samples taken as part of large-scale milk recording and milk payment operations, to predict body energy status and related traits in lactating dairy cows. The body energy status traits investigated included energy balance and body energy content. The related traits of body condition score and energy intake were also considered. Measurements on these traits along with milk MIR spectral data were available on 17 different test days from 268 cows (418 lactations) and were used to develop the prediction equations using partial least squares regression. Predictions were externally validated on different independent subsets of the data and the results averaged. The average accuracy of predicting body energy status from MIR spectral data was as high as 75% when energy balance was measured across lactation. These predictions of body energy status were considerably more accurate than predictions obtained from the sometimes proposed fat-to-protein ratio in milk. It is not known whether the prediction generated from MIR data are a better reflection of the true (unknown) energy status than the actual energy status measures used in this study. However, results indicate that the approach described may be a viable method of predicting individual cow energy status for a large scale of application.
The effects of kappa-casein (kappa-CN) and beta-lactoglobulin (beta-LG) loci on milk production traits (milk, fat, protein, and lactose yield, fat, protein, and lactose content) and reproductive performance (gestation length, calving interval, age at first and second calving, number of services per conception) was estimated for 278 Holstein cows in the first 2 lactations. Genotypes of kappa-CN and beta-LG were determined by alkaline and acidic polyacrylamide gel electrophoresis. Milk production was recorded daily. Single-trait, mixed, linear models were used for the statistical analysis of the data. Results indicated that kappa-CN genotypes affected significantly protein yield and content (genotype AB > genotype AA). A tendency for increased milk and fat yield of animals having AB kappa-CN genotype was also found. Fat content and lactose yield and content were not affected. In the beta-LG system, significant differences were detected for milk yield (AB > AA), fat yield (BB and AB > AA), fat content (BB > AA and AB), and lactose yield (AB > AA). A tendency for higher protein yield was also observed (AB > AA). The beta-LG locus had no significant effect on protein and lactose content. No associations between polymorphisms at the kappa-CN locus and reproductive performance were found. There was a tendency, however, for cows with AB genotype to have older age at first and second calving. In the beta-LG system, cows with AA genotype had significantly shorter gestation length than did those with AB or BB genotype. No differences were detected between beta-LG polymorphisms for the other reproductive traits.
Over the recent years, next generation sequencing and microarray technologies have revolutionized scientific research with their applications to high-throughput analysis of biological systems. Isolation of high quantities of pure, intact, double stranded, highly concentrated, not contaminated genomic DNA is prerequisite for successful and reliable large scale genotyping analysis. High quantities of pure DNA are also required for the creation of DNA-banks. In the present study, eleven different DNA extraction procedures, including phenol-chloroform, silica and magnetic beads based extractions, were examined to ascertain their relative effectiveness for extracting DNA from ovine blood samples. The quality and quantity of the differentially extracted DNA was subsequently assessed by spectrophotometric measurements, Qubit measurements, real-time PCR amplifications and gel electrophoresis. Processing time, intensity of labor and cost for each method were also evaluated. Results revealed significant differences among the eleven procedures and only four of the methods yielded satisfactory outputs. These four methods, comprising three modified silica based commercial kits (Modified Blood, Modified Tissue, Modified Dx kits) and an in-house developed magnetic beads based protocol, were most appropriate for extracting high quality and quantity DNA suitable for large-scale microarray genotyping and also for long-term DNA storage as demonstrated by their successful application to 600 individuals.
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