Search Results (2)

Days open (DO) is a critical economic and reproductive trait that is commonly employed in genetic selection. Making improvements using conventional genetic techniques is exceedingly challenging. Therefore, new techniques are required to improve the accuracy of genetic selection using genomic data. This study examined the genetic approaches of traditional AIREML and single-step genomic AIREML (ssGAIREML) to assess genetic parameters and the accuracy of estimated breeding values while also investigating SNP regions associated with DO and identifying candidate genes through a genome-wide association study (GWAS). The dataset included 59415 DO records from 36368 Thai–Holstein crossbred cows and 882 genotyped animals. The cows were classified according to their Holstein genetic proportion (breed group, BG) as follows: BG1 (>93.7% Holstein genetics), BG2 (87.5% to 93.6% Holstein genetics), and BG3 (<87.5% Holstein genetics). AIREML was utilized to estimate genetic parameters and variance components. The results of this study reveal that the average DO values for BG1, BG2, and BG3 were 97.64, 97.25, and 96.23 days, respectively. The heritability values were estimated to be 0.02 and 0.03 for the traditional AIREML and ssGAIREML approaches, respectively. Depending on the dataset, the ssGAIREML method produced more accurate estimated breeding values than the traditional AIREML method, ranging from 40.5 to 45.6%. The highest values were found in the top 20% of the dam dataset. For the GWAS, we found 12 potential candidate genes (DYRK1A, CALCR, MIR489, MIR653, SLC36A1, GNA14, GNAQ, TRNAC-GCA, XYLB, ACVR2B, SLC22A14, and EXOC2) that are believed to have a significant influence on days open. In summary, the ssGAIREML method has the potential to enhance the accuracy and heritability of reproductive values compared to those obtained using conventional AIREML. Consequently, it is a viable alternative for transitioning from conventional methodologies to the ssGAIREML method in the breeding program for dairy cattle in Thailand. Moreover, the 12 identified potential candidate genes can be utilized in future studies to select markers for days open in regard to dairy cattle. Full article

Reproductive traits are important traits that directly affect a farmer’s income and are difficult to improve upon using traditional genetic methods. Therefore, there is a need to consider new options for increasing the accuracy of the genetic selection of dairy cows. The objective of this study was to compare the genetic methods of the traditional BLUP and ssGBLUP techniques in terms of the estimated genetic parameters and accuracy of the estimated breeding values. The data comprised 101,331 services per conception (NSPC) records from 54,027 Thai–Holstein crossbred cows, 109,233 pedigree data, and 770 genotyped animals. A Bayesian analysis via threshold Gibbs sampling was used to analyze the estimated variance components and genetic parameters. The results showed that the means of the NSPC data were 2.21, 2.31, and 2.42 for less than 87.5% for Holstein genetics (breed group; BG1), 87.5 to 93.6% for Holstein genetics (BG2), and greater than 93.7% for Holstein genetics (BG3), respectively. The estimated heritability values were 0.038 and 0.051, and the repeatability values were 0.149 and 0.157 for the traditional BLUP and ssGBLUP methods, respectively. The accuracy of the estimated breeding values from the ssGBLUP method was higher than that from the traditional BLUP method, ranging from 6.05 to 17.69%, depending on the dataset, especially in the top 20% of the bull dataset had the highest values. In conclusion, the ssGBLUP method could improve the heritability value and accuracy of the breeding values compared with the traditional BLUP method. Therefore, switching from traditional methods to the ssGBLUP method for the Thai dairy cattle breeding program is a viable option. Full article