Novel SNPs in the Ankyrin 1 gene and their association with beef quality traits

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.

Allelic and genotypic frequencies for loci associated with meat quality in Mexican Braunvieh cattle

The objective was to estimate allelic and genotypic frequencies for loci associated with meat quality in a Mexican population of Braunvieh cattle. Information was obtained from 300 animals genotyped with the Genomic Profile Bovine LD chip of 30K and 50K SNPs. After the final edition, including quality control, the data contained information for 12 loci of the CAPN1, CAPN3, CAPN5, CAPN14, DGAT1, DGAT2, TG, ANK1, and MADH3 genes. Allelic and genotypic frequencies and Hardy-Weinberg equilibrium were estimated with the Cervus 3.0.7 software. The studied population markers were in Hardy-Weinberg equilibrium, except for those associated with CAPN1, DGAT1, and MADH3. Frequencies higher than those reported for other breeds were found for genotypes associated with meat softness, higher marbling score, lower quantity of saturated fatty acids, and lower shear force (CAPN1 and DGAT2). There were similarities with frequencies reported for Bos taurus breeds for the CAPN3 and TG genes. For the DGAT1 and ANK1 genes, the frequencies of the desired genotypes were low. A marker for DGAT1 and another for MADH3 were monomorphic. The results of this study are encouraging in terms of the potential of the Braunvieh population studied for breeding programs aiming to increase meat quality. The breed has strengths that could be used either by crossbreeding to generate heterozygous animals or by selection to increase frequencies of valuable alleles.

Sequence and haplotypes of ankyrin 1 gene (ANK1) and their association with carcass and meat quality traits in yak

Ankyrin 1 (ANK1) gene has been demonstrated to be a functional candidate gene for meat quality that helps to constitute and maintain the structure of the cell skeleton. In this study, three contiguous ANK1 regions from yak were analyzed using polymerase chain reaction-single-stranded conformational polymorphism (PCR-SSCP). As a result, nine single-nucleotide polymorphisms (SNPs) were identified, four of them in the coding region and three (c.179 C/A, c.250 G/C, and c.313 C/T) putatively resulting in amino acid changes (p. Ala 60 Glu, p. Asp 84 His, and p. Pro 105 Ser). Some SNPs in promoter region were located within or nearby the putative transcription factor binding sites, such as Sp1 and GATA, which might have an impact on the expression of the yak ANK1 gene. The presence of C₁-D₃ and C₁-A₃ were associated with an increased hot carcass weight (p = 0.0045) and a decreased drip loss rate (p = 0.0046). The presence of B₁-B₃, C₁-A₃ and C₁-D₃ had decreased Warner-Bratzler shear force (p = 0.0066, p = 0.0343 and p = 0.0004). The presence of one and two copies of B₁-B₃ and C₁-A₃ had decreased Warner-Bratzler shear force (p = 0.0005 and p = 0.0443), and C₁-A₃ had also decreased drip loss rate (p = 0.0164). These findings indicated that genetic variations of the ANK1 gene would be a preferable biomarker for the improvement of yak meat quality.

Genome-wide association study and pathway analysis for fat deposition traits in nellore cattle raised in pasture-based systems

Genome-wide association study (GWAS) is a powerful tool to identify candidate genes and genomic regions underlying key biological mechanisms associated with economically important traits. In this context, the aim of this study was to identify genomic regions and metabolic pathways associated with backfat thickness (BFT) and rump fat thickness (RFT) in Nellore cattle, raised in pasture-based systems. Ultrasound-based measurements of BFT and RFT (adjusted to 18 months of age) were collected in 11,750 animals, with 39,903 animals in the pedigree file. Additionally, 1,440 animals were genotyped using the GGP-indicus 35K SNP chip, containing 33,623 SNPs after the quality control. The single-step GWAS analyses were performed using the BLUPF90 family programs. Candidate genes were identified through the Ensembl database incorporated in the BioMart tool, while PANTHER and REVIGO were used to identify the key metabolic pathways and gene networks. A total of 18 genomic regions located on 10 different chromosomes and harbouring 23 candidate genes were identified for BFT. For RFT, 22 genomic regions were found on 14 chromosomes, with a total of 29 candidate genes identified. The results of the pathway analyses showed important genes for BFT, including TBL1XR1, AHCYL2, SLC4A7, AADAT, VPS53, IDH2 and ETS1, which are involved in lipid metabolism, synthesis of cellular amino acids, transport of solutes, transport between Golgi Complex membranes, cell differentiation and cellular development. The main genes identified for RFT were GSK3β, LRP1B, EXT1, GRB2, SORCS1 and SLMAP, which are involved in metabolic pathways such as glycogen synthesis, lipid transport and homeostasis, polysaccharide and carbohydrate metabolism. Polymorphisms located in these candidate genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for carcass fatness. In addition to uncovering biological mechanisms associated with carcass quality, the key gene pathways identified can also be incorporated in biology-driven genomic prediction methods.

Genome-wide association for metabolic clusters in early-lactation Holstein dairy cows

The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows.