Whole-genome resequencing reveals candidate genes associated with milk production trait in Guanzhong dairy goats

Milk production is one of the most important economic utility of goats. Guanzhong dairy goat is a local dairy goat in Shaanxi Province of China and has high milk yield and quality. However, there are relatively few studies on molecular markers of milk production traits in Guanzhong dairy goats. In this study, we sequenced the whole genomes of 20 Guanzhong dairy goats, 10 of which had high milk yield (HM) and 10 of which had low milk yield (LM). We detected candidate signatures of selection in HM goats using Fst and π-ratio statistics and identified several candidate genes including ANPEP, ADRA1A and PRKG1 associated with milk production. Our results provide the basis for molecular breeding of milk production traits in Guanzhong dairy goats.

Single-step genomic evaluation of milk production traits in Canadian Alpine and Saanen dairy goats

Genomic evaluations are routine in most plant and livestock breeding programs but are used infrequently in dairy goat breeding schemes. In this context, the purpose of this study was to investigate the use of the single-step genomic BLUP method for predicting genomic breeding values for milk production traits (milk, protein, and fat yields; protein and fat percentages) in Canadian Alpine and Saanen dairy goats. There were 6,409 and 12,236 Alpine records and 3,434 and 5,008 Saanen records for each trait in first and later lactations, respectively, and a total of 1,707 genotyped animals (833 Alpine and 874 Saanen). Two validation approaches were used, forward validation (i.e., animals born after 2013 with an average estimated breeding value accuracy from the full data set ≥0.50) and forward cross-validation (i.e., subsets of all animals included in the forward validation were used in successive replications). The forward cross-validation approach resulted in similar validation accuracies (0.55 to 0.66 versus 0.54 to 0.61) and biases (-0.01 to -0.07 versus -0.03 to 0.11) to the forward validation when averaged across traits. Additionally, both single and multiple-breed analyses were compared, and similar average accuracies and biases were observed across traits. However, there was a small gain in accuracy from the use of multiple-breed models for the Saanen breed. A small gain in validation accuracy for genomically enhanced estimated breeding values (GEBV) relative to pedigree-based estimated breeding values (EBV) was observed across traits for the Alpine breed, but not for the Saanen breed, possibly due to limitations in the validation design, heritability of the traits evaluated, and size of the training populations. Trait-specific gains in theoretical accuracy of GEBV relative to EBV for the validation animals ranged from 17 to 31% in Alpine and 35 to 55% in Saanen, using the cross-validation approach. The GEBV predicted from the full data set were 12 to 16% more accurate than EBV for genotyped animals, but no gains were observed for nongenotyped animals. The largest gains were found for does without lactation records (35-41%) and bucks without daughter records (46-54%), and consequently, the implementation of genomic selection in the Canadian dairy goat population would be expected to increase selection accuracy for young breeding candidates. Overall, this study represents the first step toward implementation of genomic selection in Canadian dairy goat populations.

Climatic effects on milk production traits and somatic cell score in lactating Holstein-Friesian cows in different housing systems

The objective of this study was to compare the effect of the temperature-humidity index (THI) on milk production traits and somatic cell score (SCS) of dairy cows raised in 4 different housing systems: (1) warm loose housing with access to grazing (WG), (2) warm loose housing without access to grazing (WI), (3) cold loose housing with access to grazing (CG), and (4) cold loose housing without access to grazing (CI). For each of the 4 housing systems, 5 farms with a herd size of 70 to 200 lactating cows in Lower Saxony, Germany, were studied. Ambient temperature and relative humidity were recorded hourly in each barn to calculate THI. Milk production data included 21,546 test-day records for milk, fat, and protein yield, and SCS. These data were associated with the average THI of the 3 d preceding the respective measurement, which was divided into 6 classes (<45, ≥45 to <50, ≥50 to <55, ≥55 to <60, ≥60 to <65, and ≥65). Furthermore, bulk milk samples including the fat and protein percentage, and SCS taken 4 to 6 times per month were associated with the average and maximum THI of the 3 d before sampling. Data were recorded from April 2010 to March 2011. In each of the housing systems, monthly THI values above 60, indicating heat stress, were recorded between June and September, with higher values in WI and WG. In all systems, fat-corrected milk, fat, and protein yields of the test-day records decreased in tendency from 60 ≤ THI<65 to THI >65. In WI and CI, values for SCS were greater in the class THI > 65 than in 60 ≤ THI<65, whereas no difference between any of the THI classes was found in WG and CG. The fat and protein percentage of the bulk milk samples decreased with increasing 3-d maximum THI in all 4 systems, whereas the SCS increased with increasing 3-d average THI. In conclusion, negative effects of heat stress conditions under a temperate climate on milk production traits and SCS were found, although a housing system being superior to the other systems in altering heat stress effects was not identified.