Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds

Genomic prediction based on a joint reference population for the Xinjiang Brown cattle

Introduction: Xinjiang Brown cattle constitute the largest breed of cattle in Xinjiang. Therefore, it is crucial to establish a genomic evaluation system, especially for those with low levels of breed improvement. Methods: This study aimed to establish a cross breed joint reference population by analyzing the genetic structure of 485 Xinjiang Brown cattle and 2,633 Chinese Holstein cattle (Illumina GeneSeek GGP bovine 150 K chip). The Bayes method single-step genome-wide best linear unbiased prediction was used to conduct a genomic evaluation of the joint reference population for the milk traits of Xinjiang Brown cattle. The reference population of Chinese Holstein cattle was randomly divided into groups to construct the joint reference population. By comparing the prediction accuracy, estimation bias, and inflation coefficient of the validation population, the optimal number of joint reference populations was determined. Results and Discussion: The results indicated a distinct genetic structure difference between the two breeds of adult cows, and both breeds should be considered when constructing multi-breed joint reference and validation populations. The reliability range of genome prediction of milk traits in the joint reference population was 0.142-0.465. Initially, it was determined that the inclusion of 600 and 900 Chinese Holstein cattle in the joint reference population positively impacted the genomic prediction of Xinjiang Brown cattle to certain extent. It was feasible to incorporate the Chinese Holstein into Xinjiang Brown cattle population to form a joint reference population for multi-breed genomic evaluation. However, for different Xinjiang Brown cattle populations, a fixed number of Chinese Holstein cattle cannot be directly added during multi-breed genomic selection. Pre-evaluation analysis based on the genetic structure, kinship, and other factors of the current population is required to ensure the authenticity and reliability of genomic predictions and improve estimation accuracy.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.

Associations among Farm, Breed, Lactation Stage and Parity, Gene Polymorphisms and the Fatty Acid Profile of Milk from Holstein, Simmental and Their Crosses

This study aimed to analyze the factors affecting the fatty acid (FA) profile in cow's milk. The effects of a farm, lactation parity and stage, breed and polymorphisms in the AGPAT6, DGAT1, LEP, FASN and SCD1 genes were evaluated. A total of 196 Holstein cows, 226 Simmental cows and seven crosses were sampled 751 times. The cows were kept at five farms and were in the first up to the sixth lactation, and 49 individual FAs and 11 groups were analyzed. The farm significantly affected the proportion of all FAs except for C16:1n-7c and isoC14:0. Additionally, the lactation stage was significant for most FAs, and the opposite was true for lactation parity. The effect of the breed was negligible. For the gene polymorphisms, the SCD1&nbsp;TT genotype exceeded the CC in C10:0, C12:0, C14:0, C16:1n-7c and C18:2, and the opposite was true for C10:1, C12:1, C14:1n-5c, isoC17:0, C16:1 and C18:1, i.e., the TT genotype was higher for saturated FAs, and the CT genotype was higher for monounsaturated FAs. The results hint at the intermediary heredity of the SCD1 gene. The FASN gene was strongly associated with four FAs and branched-chain FAs, and genotype AG was better than GG. LEP was significant for five individual FAs and branched-chain FAs. The differences in FA composition among genotypes were rather small, which could lead to overestimation of the effect and needs to be considered in the next research.