Background: Genomic selection using single nucleotide polymorphism (SNP) markers has been widely used for genetic improvement of livestock, but most current methods of genomic selection are based on SNP models. In this study, we investigated the prediction accuracies of haplotype models based on fixed chromosome distances and gene boundaries compared to those of SNP models for genomic prediction of phenotypic values. We also examined the reasons for the successes and failures of haplotype genomic prediction. Methods: We analyzed a swine population of 3195 Duroc boars with records on eight traits: body judging score (BJS), teat number (TN), age (AGW), loin muscle area (LMA), loin muscle depth (LMD) and back fat thickness (BF) at 100 kg live weight, and average daily gain (ADG) and feed conversion rate (FCR) from 30 to100 kg live weight. Ten-fold validation was used to evaluate the prediction accuracy of each SNP model and each multi-allelic haplotype model based on 488,124 autosomal SNPs from low-coverage sequencing. Haplotype blocks were defined using fixed chromosome distances or gene boundaries. Results: Compared to the best SNP model, the accuracy of predicting phenotypic values using a haplotype model was greater by 7.4% for BJS, 7.1% for AGW, 6.6% for ADG, 4.9% for FCR, 2.7% for LMA, 1.9% for LMD, 1.4% for BF, and 0.3% for TN. The use of gene-based haplotype blocks resulted in the best prediction accuracy for LMA, LMD, and TN. Compared to estimates of SNP additive heritability, estimates of haplotype epistasis heritability were strongly correlated with the increase in prediction accuracy by haplotype models. The increase in prediction accuracy was largest for BJS, AGW, ADG, and FCR, which also had the largest estimates of haplotype epistasis heritability, 24.4% for BJS, 14.3% for AGW, 14.5% for ADG, and 17.7% for FCR. SNP and haplotype heritability profiles across the genome identified several genes with large genetic contributions to phenotypes: NUDT3 for LMA, LMD and BF, VRTN for TN, COL5A2 for BJS, BSND for ADG, and CARTPT for FCR. Conclusions: Haplotype prediction models improved the accuracy for genomic prediction of phenotypes in Duroc pigs. For some traits, the best prediction accuracy was obtained with haplotypes defined using gene regions, which provides evidence that functional genomic information can improve the accuracy of haplotype genomic prediction for certain traits.

A genome-wide association study (GWAS) of the daughter pregnancy rate (DPR), cow conception rate (CCR), and heifer conception rate (HCR) using 1,001,374–1,194,736 first-lactation Holstein cows and 75,140–75,295 SNPs identified 7567, 3798, and 726 additive effects, as well as 22, 27, and 25 dominance effects for DPR, CCR, and HCR, respectively, with log₁₀(1/p) > 8. Most of these effects were new effects, and some new effects were in or near genes known to affect reproduction including GNRHR, SHBG, and ESR1, and a gene cluster of pregnancy-associated glycoproteins. The confirmed effects included those in or near the SLC4A4-GC-NPFFR2 and AFF1 regions of Chr06 and the KALRN region of Chr01. Eleven SNPs in the CEBPG-PEPD-CHST8 region of Chr18, the AFF1-KLHL8 region of Chr06, and the CCDC14-KALRN region of Chr01 with sharply negative allelic effects and dominance values for the recessive homozygous genotypes were recommended for heifer culling. Two SNPs in and near the AGMO region of Chr04 that were sharply negative for HCR and age at first calving, but slightly positive for the yield traits could also be considered for heifer culling. The results from this study provided new evidence and understanding about the genetic variants and genome regions affecting the three fertility traits in U.S. Holstein cows.

Epistasis is widely considered important, but epistasis studies lag those of SNP effects. Genome-wide association study (GWAS) using 76,109 SNPs and 294,079 first-lactation Holstein cows was conducted for testing pairwise epistasis effects of five production traits and three fertility traits: milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FPC), protein percentage (PPC), and daughter pregnancy rate (DPR). Among the top 50,000 pairwise epistasis effects of each trait, the five production traits had large chromosome regions with intra-chromosome epistasis. The percentage of inter-chromosome epistasis effects was 1.9% for FPC, 1.6% for PPC, 10.6% for MY, 29.9% for FY, 39.3% for PY, and 84.2% for DPR. Of the 50,000 epistasis effects, the number of significant effects with log10(1/p) ≥ 12 was 50,000 for FPC and PPC, and 10,508, 4763, 4637 and 1 for MY, FY, PY and DPR, respectively, and A × A effects were the most frequent epistasis effects for all traits. Majority of the inter-chromosome epistasis effects of FPC across all chromosomes involved a Chr14 region containing DGAT1, indicating a potential regulatory role of this Chr14 region affecting all chromosomes for FPC. The epistasis results provided new understanding about the genetic mechanism underlying quantitative traits in Holstein cattle.

A genome-wide association study (GWAS) of age at first calving (AFC) using 813,114 first lactation Holstein cows and 75,524 SNPs identified 2063 additive effects and 29 dominance effects with p-values < 10⁻⁸. Three chromosomes had highly significant additive effects in the regions of 7.86–8.12 Mb of Chr15, 27.07–27.48 Mb and 31.25–32.11 Mb of Chr19, and 26.92–32.60 Mb of Chr23. Two of the genes in those regions were reproductive hormone genes with known biological functions that should be relevant to AFC, the sex hormone binding globulin (SHBG) gene, and the progesterone receptor (PGR) gene. The most significant dominance effects were near or in EIF4B and AAAS of Chr05 and AFF1 and KLHL8 of Chr06. All dominance effects were positive overdominance effects where the heterozygous genotype had an advantage, and the homozygous recessive genotype of each SNP had a very negative dominance value. Results from this study provided new evidence and understanding about the genetic variants and genome regions affecting AFC in U.S. Holstein cows.

Substantial proteolysis occurs and free amino acids can be degraded to biogenic amines by decarboxylation during stylo (Stylosanthes guianensis) ensiling. High biogenic amine concentrations in silage are harmful to the health of ruminant animals. The purposes of this work were to (1) analyze the biogenic amines and amino acids concentrations, bacterial composition, and fermentation profile of spontaneously fermented stylo silage, (2) explore the effect of formic acid or sugar additive on these silage parameters, and (3) further reveal the correlations between silage amines and fermentation parameters, amino acids, and bacteria. Freshly chopped stylo was treated with distilled water (control), formic acid (4 mL/kg), and sugar (20 g/kg) and fermented for 28 days. The results indicated that putrescine (321 mg/kg dry matter), cadaverine (384 mg/kg dry matter), and tyramine (127 mg/kg dry matter) rapidly increased in concentration and become predominant in the control silage after 28 days of fermentation. Applying formic acid and sugar at ensiling, especially the acidifier, significantly decreased putrescine, cadaverine, tyramine, and total biogenic amine concentrations compared with the control treatment (p < 0.0001). Clostridium pabulibutyricum, Weissella cibaria and W. paramesenteroides were the predominant bacteria in the control silage, and the application of both additives remarkably lowered their relative abundance in comparison with the control treatment (p < 0.001). Correlation analysis showed that putrescine, cadaverine, and tyramine were positively related to pH, butyric acid, non-protein nitrogen, and ammonia nitrogen (p < 0.01). These amines also had significant correlations with C. pabulibutyricum, W. cibaria and W. paramesenteroides (p < 0.001). Putrescine, cadaverine, and tyramine were the main biogenic amines and C. pabulibutyricum was the predominant undesirable bacterium in naturally fermented stylo silage. C. pabulibutyricum, W. cibaria and W. paramesenteroides were positively related to putrescine, cadaverine, and tyramine formation. The application of formic acid or sugar significantly reduced the undesirable bacterial population and improved the fermentation and hygienic quality of the stylo silage. These findings lay the foundation for further elucidating the microbial mechanism underlying the main biogenic amine formation during fermentation of stylo silage.

A genome-wide association study (GWAS) of fat percentage (FPC) using 1,231,898 first lactation cows and 75,198 SNPs confirmed a previous result that a Chr14 region about 9.38 Mb in size (0.14–9.52 Mb) had significant inter-chromosome additive × additive (A×A) effects with all chromosomes and revealed many new such effects. This study divides this 9.38 Mb region into two sub-regions, Chr14a at 0.14–0.88 Mb (0.74 Mb in size) with 78% and Chr14b at 2.21–9.52 Mb (7.31 Mb in size) with 22% of the 2761 significant A×A effects. These two sub-regions were separated by a 1.3 Mb gap at 0.9–2.2 Mb without significant inter-chromosome A×A effects. The PPP1R16A-FOXH1-CYHR1-TONSL (PFCT) region of Chr14a (29 Kb in size) with four SNPs had the largest number of inter-chromosome A×A effects (1141 pairs) with all chromosomes, including the most significant inter-chromosome A×A effects. The SLC4A4-GC-NPFFR2 (SGN) region of Chr06, known to have highly significant additive effects for some production, fertility and health traits, specifically interacted with the PFCT region and a Chr14a region with CPSF1, ADCK5, SLC52A2, DGAT1, SMPD5 and PARP10 (CASDSP) known to have highly significant additive effects for milk production traits. The most significant effects were between an SNP in SGN and four SNPs in PFCT. The CASDSP region mostly interacted with the SGN region. In the Chr14b region, the 2.28–2.42 Mb region (138.46 Kb in size) lacking coding genes had the largest cluster of A×A effects, interacting with seventeen chromosomes. The results from this study provide high-confidence evidence towards the understanding of the genetic mechanism of FPC in Holstein cows.