Genome-wide association analysis of heifer livability and early first calving in Holstein cattle.

BACKGROUND: The survival and fertility of heifers are critical factors for the success of dairy farms. The mortality of heifers poses a significant challenge to the management and profitability of the dairy industry. In dairy farming, achieving early first calving of heifers is also essential for optimal productivity and sustainability. Recently, Council on Dairy Cattle Breeding (CDCB) and USDA have developed new evaluations of heifer health and fertility traits. However, the genetic basis of these traits has yet to be thoroughly studied. RESULTS: Leveraging the extensive U.S dairy genomic database maintained at CDCB, we conducted large-scale GWAS analyses of two heifer traits, livability and early first calving. Despite the large sample size, we found no major QTL for heifer livability. However, we identified a major QTL in the bovine MHC region associated with early first calving. Our GO analysis based on nearby genes detected 91 significant GO terms with a large proportion related to the immune system. This QTL in the MHC region was also confirmed in the analysis of 27 K bull with imputed sequence variants. Since these traits have few major QTL, we evaluated the genome-wide distribution of GWAS signals across different functional genomics categories. For heifer livability, we observed significant enrichment in promotor and enhancer-related regions. For early calving, we found more associations in active TSS, active Elements, and Insulator. We also identified significant enrichment of CDS and conserved variants in the GWAS results of both traits. By linking GWAS results and transcriptome data from the CattleGTEx project via TWAS, we detected four and 23 significant gene-trait association pairs for heifer livability and early calving, respectively. Interestingly, we discovered six genes for early calving in the Bovine MHC region, including two genes in lymph node tissue and one gene each in blood, adipose, hypothalamus, and leukocyte. CONCLUSION: Our large-scale GWAS analyses of two heifer traits identified a major QTL in the bovine MHC region for early first calving. Additional functional enrichment and TWAS analyses confirmed the MHC QTL with relevant biological evidence. Our results revealed the complex genetic basis of heifer health and fertility traits and indicated a potential connection between the immune system and reproduction in cattle.

Longitudinal analysis of body weight and average daily feed intake during the feedlot test period in Angus cattle.

The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd-year-observation_date-age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%-3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.

Genetic and phenotypic associations of feed efficiency with growth and carcass traits in Australian Angus cattle.

Genetic and phenotypic parameters for feed efficiency, growth, and carcass traits for Australian Angus beef cattle were estimated. Growth traits included birth weight (BWT), 200-d weight (200dWT), 400-d weight (400dWT), and 600-d weight (600dWT). Traits associated with feed efficiency were average daily weight gain (ADG), metabolic midweight, average of daily feed intake (FI), feed conversion ratio (FCR), residual feed intake (RFI), and residual gain (RG). Carcass traits involved were carcass eye muscle area (CEMA), carcass intramuscular fat (IMF), subcutaneous fat depths at the 12th/13th rib (CRIB), rump P8 fat depth (P8FAT), and carcass weight (CWT). For growth traits, heritability estimates ranged from 0.14 ± 0.03 for 200dWT to 0.48 ± 0.06 for 600dWT. For feed efficiency traits, direct heritability estimates for FI, FCR, RFI, and RG were 0.55 ± 0.08, 0.20 ± 0.06, 0.40 ± 0.07, and 0.19 ± 0.06, respectively. High heritability estimates were observed for CEMA, IMF, P8FAT, and CWT of 0.52 ± 0.09, 0.61 ± 0.09, 0.55 ± 0.09, and 0.66 ± 0.09, respectively. Strong positive genetic correlations were found for FI with 200dWT, 400dWT, and 600dWT of 0.68 ± 0.09, 0.42 ± 0.11, and 0.61 ± 0.07, respectively. Weak genetic correlations were observed between RFI and growth traits. For carcass traits, genetic correlations between RFI and CEMA, IMF, CRIB, P8FAT, CWT were -0.19 ± 0.14, 0.31 ± 0.14, 0.18 ± 0.16, 0.24 ± 0.13, and 0.40 ± 0.12, respectively. There was a tendency for low to moderate unfavorable genetic associations between feed efficiency traits, evaluated as RFI and RG, with growth and carcass traits. This implies that selection for RFI would have slight negative impacts on growth and reduce carcass quality. To avoid this, it would be necessary to build selection indices to select feed efficient animals without compromising growth and meat quality.

Genetic polymorphism of the alpha s1-casein locus in five populations of goats from Mexico

With the objective of estimating allele frequencies, and testing for population divergence for the CSN1S1 locus, genotypes of animals from five goat populations; Saanen (n = 97), Alpine (n = 81) Toggenburg (n = 92), local goats with external appearance similar to the Murciana-Granadina breed from Central Mexico (n = 26) and heterogeneous local animals denominated Mosaico Lagunero (n = 30), from Northern Mexico, were identified using PCR and Xmn1 PCR-RFLP methodology. For Saanen, Alpine and Toggenburg, the sum of E and F alleles had the largest frequencies (from 0.468 to 0.789), while for the groups local Murciana-Granadina and Mosaico Lagunero the sum of the most frequent allelic groups (A and B), were 0.385 and 0.533 respectively. Both local Murciana-Granadina and Mosaico Lagunero populations showed heterozygote excess (P < 0.08). The percentage of the total genetic variation (F ST) explained by population differences was 5.16. There was genetic differentiation for most pair comparisons between populations (P < 0.05), excepting for Alpine versus Toggenburg, and Toggenburg versus Mosaico Lagunero (P > 0.05). For Saanen and Alpine the frequencies of alleles E and F were similar to the same breeds previously analyzed in Europe. Therefore there are opportunities of increasing the frequency of the strong alleles for protein content Gene Assisted Selection (GAS) in these two breeds. For Toggenburg the most frequent allelic groups were F (0.32) and B (0.21). Results indicate differentiation between most populations for this locus. Moreover, heterozygote excess in local populations indicated breed admixture.