With the availability of high‐density SNP panels and the establishment of approaches for characterizing homozygosity and heterozygosity sites, it is possible to access fine‐scale information regarding genomes, providing more than just comparisons of different inbreeding coefficients. This is the first study that seeks to access such information for the Mangalarga Marchador (MM) horse breed on a genomic scale. To this end, we aimed to assess inbreeding levels using different coefficients, as well as to characterize homozygous and heterozygous runs in the population. Using Axiom ® Equine Genotyping Array—670k SNP (Thermo Fisher), 192 horses were genotyped. Our results showed different estimates: inbreeding from genomic coefficients (FROH) = 0.16; pedigree‐based (FPED) = 0.008; and a method based on excess homozygosity (FHOM) = 0.010. The correlations between the inbreeding coefficients were low to moderate, and some comparisons showed negative correlations, being practically null. In total, 85,295 runs of homozygosity (ROH) and 10,016 runs of heterozygosity (ROHet) were characterized for the 31 horse autosomal chromosomes. The class with the highest percentage of ROH was 0–2 Mbps, with 92.78% of the observations. In the ROHet results, only the 0–2 class presented observations, with chromosome 11 highlighted in a region with high genetic variability. Three regions from the ROHet analyses showed genes with known functions: tripartite motif‐containing 37 (TRIM37), protein phosphatase, Mg2+/Mn2+ dependent 1E (PPM1E) and carbonic anhydrase 10 (CA10). Therefore, our findings suggest moderate inbreeding, possibly attributed to breed formation, annulling possible recent inbreeding. Furthermore, regions with high variability in the MM genome were identified (ROHet), associated with the recent selection and important events in the development and performance of MM horses over generations.

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Subcutaneous fat deposition measured as backfat thickness (BFT) increases protection for the bovine carcass during cooling, conferring to BFT an important characteristic for the meat industry. To study the influence of BFT on meat quality traits of Nellore bulls (Bos indicus), data from 1652 animals aged 20–24 months in feedlot finishing were used. The principal component analysis (PCA) was performed to characterise meat quality variables in longissimus thoracis muscle. Measurements comprised the rib eye area, BFT, marbling, shear force, myofibril fragmentation index, cooking losses, intramuscular lipid content and colour (lightness, yellowness, redness, chromaticity and hue). Considering BFT as a separation criterion, the K-means cluster analysis was applied to classify beef samples. The first four PC explained roughly 66% of total variability and meat colour (yellowness and chromaticity) was more effective to define the first PC. Tenderness or toughness (shear force and cooking losses) and fatness (BFT and intramuscular lipid content) were more effective to define the second and third PC, respectively. Three BFT groups were formed and projected in the gradient defined by PC 2 and PC 3. BFT means in the clusters were 10.82 ± 3.19 (I), 5.03 ± 1.01 (II) and 2.54 ± 0.63 (III) mm with 185, 947 and 520 animals in each group, respectively. The projection of I, II and III in the gradient allowed to distinguish fatness between beef samples and tenderness between I and III. Additionally, 57.32% of animals (Group II) were placed between the two previous groups. Beef samples with higher values of shear force and cooking losses (tough meat) showed lower BFT and myofibril fragmentation index values, possibly due to fibre shortening. PCA and K-means cluster analysis presented as interesting multivariate techniques to identify Nellore bulls regarding meat quality as some of the traits used in the study are difficult to measure. The three-cluster solution represented the main biological type of Nellore bulls finished on feedlot in Brazil showing that only 11.2% of beef samples (Cluster I) can be considered tender. This information can be useful for breeding programs of Nellore bulls. In this study, Cluster I shows optimal beef quality (SF = 4.52 ± 1.17 kg) with better marbling level and less cooking losses. Nellore cattle producers should target BFT at least 5.00 mm to prevent fibre shortening. However, the only condition which provides optimal beef tenderness (i.e. shear force values lower than 4.9 kg) was found in Cluster I. The BFT does not seem to be a suitable characteristic for the selection of animals to improve tenderness due the weak relationship between BFT and shear force.

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