Table 1 shows the allelic and genotypic frequencies of CAPN316, CAPN4751, CAST282, CAST2959, E2FB and E2JW SNPs genotyped by PCR-RFLP and PCR-HRM. Table 2 shows the least squares means of the studied Brahman population regarding the characteristics evaluated. The study evidenced an effect of the livestock and contemporary group upon most of the studied variables, Table 3 presents the markers that had significant effects (p < 0,05) upon the characteristics, the minimum square means for genotypes, the regression coefficients (β1) of the allelic substitution effects of CAPN316, CAPN4751, CAST282, CAST2959, E2FB, and E2JW SNPs when they were significant (p < 0,05) upon the production and meat quality variables.
Table 2
Findings on productivity and quality in cattle meat production.
Variable | Day | Mean | SD | Min | Max | CV |
Age | D0 | 31,55 | 6,0 | 19,5 | 47,8 | 19,06 |
LW | D0 | 435,41 | 40,0 | 357 | 652 | 9,18 |
HCW | D0 | 246,23 | 27,3 | 196 | 365 | 11,10 |
HCY | D0 | 56,41 | 1,91 | 52,26 | 60,50 | 3,39 |
MY | D0 | 38,42 | 1,40 | 35,14 | 41,99 | 3,65 |
LP | D0 | 79,52 | 6,50 | 72,87 | 101,90 | 8,17 |
ICTA | D0 | 4,08 | 0,72 | 2,00 | 5,00 | 17,66 |
LEA | D0 | 72,03 | 9,54 | 51,58 | 96,01 | 13,25 |
IMF | D0 | 3,02 | 1,71 | 0,60 | 8,55 | 56,68 |
IMM | D0 | 72,07 | 1,61 | 67,00 | 77,20 | 2,23 |
IMP | D0 | 22,41 | 0,76 | 20,40 | 25,40 | 3,39 |
pH | D1 | 5,81 | 0,13 | 5,52 | 6,12 | 2,18 |
D7 | 5,93 | 0,10 | 5,68 | 6,18 | 1,70 |
D14 | 5,86 | 0,11 | 5,64 | 6,14 | 1,80 |
WHC | D1 | 26,87 | 3,03 | 20,49 | 35,86 | 11,28 |
D7 | 25,58 | 2,83 | 19,77 | 33,71 | 11,08 |
D14 | 25,17 | 2,87 | 19,07 | 33,60 | 11,42 |
HAR | D1 | 5,71 | 1,21 | 2,57 | 8,98 | 21,13 |
D7 | 5,02 | 1,26 | 2,03 | 9,54 | 25,17 |
D14 | 4,83 | 1,28 | 2,20 | 8,77 | 26,50 |
ADH | D1 | -1,62 | 0,85 | -3,00 | -0,17 | -52,54 |
D7 | -1,95 | 0,96 | -3,49 | -0,20 | -49,06 |
D14 | -2,19 | 1,04 | -3,96 | -0,26 | -47,58 |
ELA | D1 | 0,62 | 0,07 | 0,46 | 0,76 | 10,74 |
D7 | 0,64 | 0,05 | 0,40 | 0,77 | 8,54 |
D14 | 0,65 | 0,05 | 0,51 | 0,85 | 7,55 |
COH | D1 | 0,54 | 0,05 | 0,44 | 0,76 | 8,67 |
D7 | 0,53 | 0,04 | 0,34 | 0,75 | 7,97 |
D14 | 0,52 | 0,03 | 0,44 | 0,62 | 5,29 |
GUM | D1 | 2,98 | 2,32 | 0,13 | 9,81 | 78,05 |
D7 | 1,89 | 1,62 | 0,00 | 8,25 | 85,72 |
D14 | 2,51 | 1,81 | 0,03 | 8,58 | 72,20 |
CHE | D1 | 1,91 | 1,50 | 0,08 | 8,93 | 78,40 |
D7 | 1,18 | 0,98 | 0,00 | 5,35 | 82,94 |
D14 | 1,56 | 1,07 | 0,00 | 6,59 | 68,48 |
RES | D1 | 0,29 | 0,02 | 0,23 | 0,35 | 7,94 |
D7 | 0,28 | 0,02 | 0,22 | 0,33 | 7,51 |
D14 | 0,29 | 0,02 | 0,24 | 0,34 | 6,48 |
WBSF | D1 | 6,82 | 1,42 | 2,13 | 9,56 | 20,81 |
D7 | 6,44 | 1,47 | 2,21 | 10,81 | 22,91 |
D14 | 5,63 | 0,65 | 3,34 | 7,53 | 11,59 |
Adhesivity (ADH, kg x s), area of the loin eye (LEA, cm2), water holding capability (WHC, %), carcass classification (ICTA), cohesiviness (COH), intramuscular humidity content (IMH, %), intramuscular fat (IMF, %) and intramuscular protein (IMP, %), age (age, months), after dressing (D0), days 1 (D1), 7 (D7) and 14 (D14) of maturation, hardness (HAR, kg), elasticity (ELA), Warner-Bratzler's shear force (WBSF, KgF), gumminess (GUM), chewiness (MAS, kg), leg perimeter (LP, cm), hot carcass weight (HCW, kg), live weight (LW, kg), hot carcass yielding (HCY, %), meat yielding (MY,%), resilience (RES). |
Table 3
Genotypes with association upon the carcass and meat quality in brahman livestock
SNPs | Variable | Day | P-value* | Adjusted means by genotype ± Standard deviation | Allelic substitution |
CAPN316 | | | | CC (n = 5) | CG (n = 25) | GG (n = 380) | β1 | P value** |
| Capn1 | D0 | 0,003 | 1,47 ± 0,11a | 1,76 ± 0,03b | 1,66 ± 0,01a | 0,04 | 0,12 |
| HAR | D1 | 0,010 | 5,42 ± 0,57ab | 5,24 ± 0,18a | 5,78 ± 0,05b | -0,44 | 0,00 |
| CHE | D7 | 0,036 | 1,82 ± 0,39a | 0,94 ± 0,14a | 0,84 ± 0,04a | 0,24 | 0,04 |
| WBSF | D14 | < 0,001 | 5,57 ± 0,27a | 5,16 ± 0,11a | 5,61 ± 0,03a | -0,28 | 0,00 |
CAPN4751 | | | | CC (n = 82) | CT (n = 57) | TT (n = 271) | | |
| LW | D0 | 0,028 | 431,5 ± 2,62ab | 432,1 ± 2,70b | 425,8 ± 1,36a | 3,25 | 0,01 |
| CY | D0 | 0,001 | 55,94 ± 0,15a | 56,75 ± 0,16b | 56,34 ± 0,08b | -0,16 | 0,03 |
| LEA | D0 | 0,005 | 72,30 ± 0,98a | 75,80 ± 1,04b | 72,00 ± 0,53a | 0,50 | 0,31 |
| Capn1 | D0 | < 0,01 | 1,85 ± 0,02c | 1,80 ± 0,02b | 1,61 ± 0,01a | 0,13 | < 0,01 |
| HAR | D1 | 0,001 | 5,45 ± 0,10a | 5,82 ± 0,11b | 5,86 ± 0,06b | -0,15 | 0,01 |
| ELA | D1 | 0,028 | 0,62 ± 0,01b | 0,60 ± 0,01a | 0,61 ± 0,00a | 0,01 | 0,03 |
| GUM | D1 | 0,000 | 2,52 ± 0,20a | 3,71 ± 0,20b | 2,48 ± 0,11a | 0,16 | 0,11 |
| WBSF | D7 | 0,001 | 6,28 ± 0,14a | 6,85 ± 0,15b | 6,84 ± 0,07b | -0,16 | 0,04 |
| HAR | D7 | 0,001 | 4,47 ± 0,12a | 4,88 ± 0,13b | 4,92 ± 0,07b | -0,22 | 0,00 |
| pH | D14 | 0,048 | 5,85 ± 0,01ab | 5,84 ± 0,01a | 5,87 ± 0,01b | 0,04 | 0,78 |
| WBSF | D14 | < 0,001 | 5,38 ± 0,06a | 5,49 ± 0,06a | 5,67 ± 0,03b | -0,13 | 0,00 |
| HAR | D14 | < 0,001 | 4,18 ± 0,12a | 4,82 ± 0,13b | 4,76 ± 0,07b | -0,25 | 0,00 |
CAST282 | | | | CC (n = 82) | CG (n = 123) | GG (n = 205) | | |
| CY | D0 | 0,023 | 56,08 ± 0,14a | 56,22 ± 0,12a | 56,59 ± 0,10b | -0,19 | 0,02 |
| IMF | D0 | 0,000 | 2,10 ± 0,13a | 2,69 ± 0,10b | 2,62 ± 0,08b | -0,21 | 0,01 |
| IMM | D0 | 0,004 | 72,57 ± 0,15b | 72,10 ± 0,12a | 72,02 ± 0,10a | 0,25 | 0,00 |
| Cast | D0 | < 0,01 | 0,34 ± 0,01a | 0,45 ± 0,01b | 0,55 ± 0,00c | -0,10 | < 0,01 |
| pH | D1 | 0,000 | 5,84 ± 0,01b | 5,79 ± 0,01a | 5,81 ± 0,01a | 0,01 | 0,04 |
| WBSF | D1 | 0,021 | 6,82 ± 0,13a | 7,16 ± 0,11ab | 7,24 ± 0,09b | -0,20 | 0,01 |
| HAR | D1 | 0,006 | 5,47 ± 0,10a | 5,76 ± 0,08b | 5,85 ± 0,07b | -0,18 | 0,00 |
| WHC | D7 | 0,013 | 25,20 ± 0,23a | 25,80 ± 0,24b | 25,20 ± 0,12a | 0,07 | 0,58 |
| HAR | D7 | < 0,001 | 4,53 ± 0,11a | 4,66 ± 0,09b | 5,09 ± 0,07b | -0,31 | 0,00 |
| WBSF | D14 | < 0,001 | 5,40 ± 0,06a | 5,54 ± 0,05a | 5,70 ± 0,04b | -0,15 | 0,00 |
| HAR | D14 | 0,035 | 4,47 ± 0,12a | 4,56 ± 0,09ab | 4,80 ± 0,08b | -0,18 | 0,02 |
| ADH | D14 | > 0,05 | -2,26 ± 0,12a | -2,34 ± 0,10a | -2,10 ± 0,08a | -0,10 | 0,01 |
CAST2959 | | | | AA (n = 213) | AG (n = 115) | GG (n = 82) | | |
| MY | D0 | 0,028 | 38,33 ± 0,06a | 38,57 ± 0,07b | 38,41 ± 0,09ab | 0,00 | 0,94 |
| LEA | D0 | 0,020 | 73,80 ± 0,59b | 72,20 ± 0,77ab | 71,00 ± 0,91a | -1,10 | 0,03 |
| Cast | D0 | < 0,01 | 0,46 ± 0,01a | 0,48 ± 0,01a | 0,56 ± 0,01b | 0,05 | < 0,01 |
| pH | D1 | > 0,05 | 5,80 ± 0,01a | 5,82 ± 0,01a | 5,83 ± 0,01a | 0,01 | 0,03 |
| WHC | D1 | 0,017 | 26,70 ± 0,14a | 27,00 ± 0,20ab | 27,40 ± 0,22b | 0,28 | 0,03 |
| WBSF | D1 | 0,008 | 7,02 ± 0,08a | 7,17 ± 0,10ab | 7,45 ± 0,12b | 0,21 | 0,00 |
| HAR | D1 | < 0,001 | 5,60 ± 0,06a | 5,82 ± 0,09ab | 6,05 ± 0,10b | 0,23 | 0,00 |
| ADH | D1 | 0,038 | -1,60 ± 0,06a | -1,55 ± 0,08ab | -1,32 ± 0,10b | 0,13 | 0,02 |
| ELA | D1 | 0,036 | 0,61 ± 0,00ab | 0,62 ± 0,01b | 0,60 ± 0,01a | 0,00 | 0,16 |
| HAR | D7 | < 0,001 | 4,77 ± 0,07a | 4,72 ± 0,09a | 5,30 ± 0,11b | 0,16 | 0,02 |
| WBSF | D14 | < 0,001 | 5,50 ± 0,04a | 5,64 ± 0,05b | 5,84 ± 0,06c | 0,20 | 0,00 |
E2FB | | | | CC (n = 254) | CT (n = 127) | TT (n = 29) | | |
| HCW | D0 | 0,012 | 239,9 ± 0,99a | 238,8 ± 1,42a | 248,5 ± 2,91b | 1,80 | 0,14 |
| CY | D0 | 0,031 | 56,39 ± 0,08ab | 56,18 ± 0,11a | 56,83 ± 0,24b | 0,02 | 0,88 |
| MY | D0 | 0,010 | 38,49 ± 0,05a | 38,24 ± 0,07a | 38,45 ± 0,16ab | -0,14 | 0,03 |
| IMF | D0 | < 0,01 | 2,48 ± 0,07a | 2,53 ± 0,10ab | 3,00 ± 0,22b | 0,16 | 0,07 |
| Cast | D0 | 0,011 | 0,49 ± 0,01ab | 0,47 ± 0,01a | 0,53 ± 0,01b | 0,00 | 0,95 |
| HAR | D1 | 0,073 | 5,82 ± 0,06b | 5,69 ± 0,08ab | 5,44 ± 0,17a | -0,16 | 0,03 |
| pH | D7 | 0,028 | 5,94 ± 0,01b | 5,92 ± 0,01a | 5,92 ± 0,01ab | -0,01 | 0,05 |
| HAR | D7 | > 0,05 | 4,94 ± 0,07a | 4,73 ± 0,09a | 4,63 ± 0,19a | -0,17 | 0,04 |
| WHC | D14 | 0,017 | 25,10 ± 0,16a | 25,70 ± 0,21b | 24,50 ± 0,46a | 0,08 | 0,67 |
| WBSF | D14 | < 0,001 | 5,35 ± 0,03a | 5,50 ± 0,05a | 5,67 ± 0,10b | -0,16 | 0,00 |
| COH | D14 | 0,036 | 0,52 ± 0,00a | 0,52 ± 0,00a | 0,53 ± 0.00a | 0,00 | 0,02 |
| CHE | D14 | 0,011 | 1,36 ± 0,06a | 1,60 ± 0,08b | 1,65 ± 0,16ab | 0,19 | 0,00 |
Adhesivity (ADH, kg x s), loin eye area (LEA, cm2), water holding capacity (WHC, %), classification o the carcass (ICTA), regression coefficient (β1), cohesiveness (COH), moisture content (IMM, %), intramuscular fat (IMF, %) and intramuscular protein (IMP, %), age (age, months), after slaughtering (D0) days 1 (D1), 7 (D7) and 14 (D14) of maturation, Hardness (HAR, kg), elasticity (ELA), Warner-Bratzler’s shear force (WBSF, KgF), gumminess (GUM), chewiness (CHE, kg), muscle µ-calpain (Capn1) and calpastatin content (Cast), leg perimeter (LP, cm), weight of the hot carcass (HCW, kg), live weight (LW, kg), carcass yielding (CY, %), meat yielding (MY,%), resilience (RES), the letters mean statistic difference (a < b < c). P-value of the association model (*), P-value of the substitution model (**). |
Effects Upon The Productive Characteristics Of The Meat
The effects of the CAPN4751 (LW, CY, and LEA), CAST282 (CY), CAST2959 (CY, LEA), and E2FB (HCW, CY, MY) SNPs were observed upon the assessed production characteristics. These results might have a relevant impact upon the meat productivity of the brahman breed livestock raised and grazed in the lower Colombian tropic conditions. Perhaps this is due to the high frequency of the alleles that favor these characteristics in the population studied (Table 1). The aforementioned is founded in the fact that these alleles have been related to a greater calpastatin expression, an inhibitor of the action of the µ-calpain (Goll et al., 2003). The µ-calpain participates in the renovation of the muscular tissue (Gerken et al., 1995) through a process with high energy requirements (Herd, Oddy, and Richardson, 2004) and, thus, the inhibition of the µ-calpain would favor the growth and deposition of fats in the animal (Motter et al., 2013). Given all of this, some authors have suggested that this enzymatic complex might be related with: i) the growth rate and the living weight of the animal (Howard, 2013, Motter et al., 2013); ii) the weight and yielding of the carcass (Cafe et al., 2010a; Howard, 2013); iii) the loin eye area (Casas et al., 2006; Motter et al., 2013; Allais et al., 2014; Calvo et al., 2014; Lee et al., 2014); the fat yielding (Schenkel et al., 2006; Motter et al., 2013); iv) dorsal fat thickness (Howard, 2013; Motter et al., 2013); and v) might be related to the adaptation capability of the Bos indicus specimens to adverse conditions (Cafe et al., 2010a).
It is important to highlight that even though there was not an observed association between the CAPN316 SNP upon the production characteristics of the animal alive and in carcass, it is known that the brahman breed specimens that are carriers of the CG and GG genotypes have better parameters in some of the values such as hump height (Casas et al., 2005), weight gains and hip fat (Cafe et al., 2010a). Besides, the Holstein (Ardicli et al., 2019), Simental (Ardicli et al., 2017) and Friesian (Ardicli et al., 2019) livestock breeds with these genotypes have a higher rate of food conversion and weight gain. Continuing, their LW, HCW, cold canal weight, LEA, and dorsal fat thickness are higher. In contrast, the carriers of the CC genotype had higher fat yielding, a smaller food conversion rate, and required longer times for achieving 400 kg. Added to this, there have been reports that claim that the low frequency of the C allele in the brahman livestock might be related to the adaptability to the tropic conditions (Cafe et al., 2010b).
Opposite to this is the LEP or obese gene, which codifies leptin. This proteic hormone participates in the regulation of food consumption and energetic equilibrium in the animal. Its exon number 2 have the E2FB and E2JW SNPs (Buchanan et al., 2002), which alleles are associated with fat deposition differences among bovines (Buchanan et al., 2002; Kononoff et al., 2005; Nkrumah et al., 2005; Schenkel et al., 2005). This defends the hypothesis that these markers might be useful for improving meat production in cattle. Thus, the low frequency of the favorable allele (T) in E2FB (0,22), and its practical absence in E2JW (0,001) (Table 1), might explain, partially, the reason why brahman breed animals present deficient carcass characteristics in comparison with those observed in taurine breeds. In these last, the T alleles are present in bigger proportions (Smith et al., 2009).
Moreover, even though there were no reports of the association of these markers with the LW —CY and MY—, there is evidence that supports that the T alleles in E2JW improve the food consumption (Lagonigro et al., 2003), and in E2FB favors the weight gain (da Silva et al., 2012). Both markers are related to the thickness of the dorsal fat (Buchanan et al., 2002; de Carvalho et al., 2012; da Silva et al., 2012; de Oliveira et al., 2013), fatty content, lean content (Schenkel et al., 2005) and LEA (da Silva et al., 2012), both in taurine and indicine breeds.
Effects Upon The Quality Attributes Of The Meat
Chemical composition of the meat. Characterizing the proximal composition of the meat is a powerful tool for decision making that allows productivity improvement, as well as knowing, underlive, and highlighting the attributes better valued by consumers (Mamani and Gallo, 2011; Faucitano et al., 2008). The chemical composition of the meat, represented mainly by the IMP, IMM, and IMF contents, has different functions in determining the meat quality, i.e., as a source of nutrients for human nutrition (McAfee et al., 2010; Lobato et al., 2014), which determines its acceptability (Mamani and Gallo, 2011, Lobato et al., 2014) and acts as a productivity indicator. This is made taking into account the efficiency and yielding achieved, both in the live animal as in its final products after slaughtering and butchering (Faucitano et al., 2008). Given the aforementioned, the effect of the CAPN, CAST, and LEP genes over the IMF, IMM, and IMP contents were assessed; the findings are compatible with what is stated in this study.
The animals that carry the CC genotype of the CAST282 marker had the highest IMM content and the lowest IMF (marbling). Even though there are no reports of this effect in brahman breeds, the study found a contrary relationship between these parameters (Cheng et al., 2015). Nonetheless, the water quantity in the muscle is not as relevant as its water holding capacity (WHC), given that this characteristic, alongside marbling, participate in the juiciness and tenderness sensation of the meat (Zhang et al., 2005; Pearce et al., 2011; Warner, 2014).
However, it is important to highlight that the animals that carry the GG genotype of CAST282 (Table 3) had the highest values in the WBSF (less tenderness). The aforesaid might be explained with a raise in the calpastatin levels in the animals with this genotype (Table 3). Under this circumstance, the proteolytic activity of the µ-calpain decreases. Consequently, the protein replacement processes of the muscle become slower. Thus, the energy requirements decrease (Herd, Oddy, and Richardson, 2004), and animal growth and muscle fact deposition are favored. This might explain the higher values in thickness and dorsal fat percentage in the Brangus breed specimens that are carriers of the GG genotype (Motter et al., 2013).
It must be highlighted that the IMF disposition (marbling) is a highly important attribute of meat quality, given how much it influences its texture, smell, and flavor. There is a direct correlation between the marbling grade and the tenderness sensitivity, while with the WBSF this relationship is inversely proportional. This last fact happens due to the fact that the IMF, located between the fibers, modifies its structure, which reduces its mechanical force and favors the tenderness of the bovine flesh (Nishimura, 2010).
The carriers of the TT genotype of E2FB have the highest IMF values. Something similar was found in animals from different taurine breeds with this genotype (Buchanan et al., 2002) and in animals of the Nellore breed that carry the CTAT haplotype of E2FB/E2JW. The results did not make evident an effect of the CAPN4751 SNP. Nevertheless, the bovine animals, carriers of the CC genotype, have the highest values (Chung, Shin, and Chung, 2014).
Among the population of the brahman breed from this study, there was no association between the studied markers with the protein contents in the muscle (IMP). This is a consistent result because bovine meat is considered an excellent source of protein. In general, its content is stable. Although there are reports of values that oscillate between 16 and 31% (Ferreira, 1999; Serra et al., 2004), the consensus is around 22% (Mamani and Gallo, 2011, Montoya, 2014; Wood, 2017). This has made that this content stopped becoming a preoccupation in the meat industry, which is made evident in the absence of works for raising its values. The interest has focused on characterizing the type of proteins and the efficiency of the biochemical context of the muscle for degrading them during maturation, cooking process, and mastication for obtaining quality products and providing the consumer with a better organoleptic perception at consumption (Bowker and Zhuang, 2013; Bowker, Eastridge, and Solomon, 2014).
pH. There is a pH descent in the postmortem period, from 7,0 to a value between 5,4 and 5,8 in ideal conditions (Lomiwes et al., 2014). If this does not happen, the meat develops deficient organoleptic and production characteristics (Grayson et al., 2016; Zhang et al., 2018) that affect color, smell, WHC (Muchenje et al., 2009), among others. Taking the aforementioned into account, both calpastatin as leptin participate in the regulation of the muscle’s metabolism. Leptin stimulates glucose uptake and glycogen synthesis (Ceddia et al., 1998), while calpastatin participates in glycolysis regulation (Reardon et al., 2010). Consequently, they might affect the establishment of the pHu and the WHC.
Even though the CAST282 (D1), E2FB (D7), and CAPN4751 (D14) SNPs had an effect upon the meat’s pH in different maturation times, there was a variation in the genotypes and the effect of the allelic substitution. Even so, among the studied population, the pH values were within the ranges considered ideal or intermediate (Córdoba et al., 2017). Hence, these effects might not have any practical utility over the organoleptic quality of the meat. There have been reports of the effect of the CAST282 SNP over the pHu. The highest pHu values were found in carriers of the GG genotype and not in CC carriers, as this study found. Even if there are no reports of association of the E2FB upon the pH, it was found that the carriers of the AT genotype of E2JW have the highest values (de Oliveira et al., 2013), which may be due to overdominance where the heterozygous present higher values on a given characteristic (Falconer and Mackay, 1996).
Water holding capability. The CAST2959 (D1), CAST282 (D7) and E2FB (D14) markers affected the WHC, which was assessed through the measurement of water loss during cooking in different meat maturation times (Table 3). Similar to the results obtained by Leal et al (2015) in brahman breed animals and its crossings with different breeds and in Bos taurus animals (Chung, Shin, and Chung, 2014, Kök S and Atalay, 2018), there were no effects of the CAPN316 and CAPN4751 SNPs. These results can be contrasted with the findings by Cafe et al. (2010b) in which the CG genotypes of CAPN316 and CC of CAPN4751 had the highest WHC values.
It is important to highlight that there has been documentation on the association of the CAST2959 SNP with the WHC in raw meat, which is assessed through the measurement of water loss by dripping. Even so, this technique assesses the meat yielding (Warner, 2014) and not its organoleptic characteristics, as is the case of the WHC in cooked meat (Yu et al., 2005).
Texture profile analysis and Warner-Bratzler’s shear force. The texture is considered as the main attribute of meat. This attribute refers to the sensations perceived during mastication and its analysis focuses on characterizing the structure of the meat through sensitive perception (Cáceres, 2010). The study of texture is done through a sensory panel or with instrumental methods (Szczesniak, 1963), as the texture profile analysis (TPA) and the WBSF. TPA offers the possibility of assessing several characteristics of the meat with one single sample (Ruiz de Huidobro et al., 2001).
Because the TPA is not used regularly in the meat texture characterization (Ruiz de Huidobro et al., 2005), There is not enough available literature about the effect of molecular markers (Pinilla, 2014). Moreover, even though the WBSF only offers the possibility of characterizing the parameters of shear resistance, this is the most widespread methodology in academic and commercial contexts (Ruiz de Huidobro et al., 2005). There seems to be an adequate correlation between the hardness assessed through TPA and the WBSF (Onega, 2003). Nonetheless, these methodologies are focused on different components of the muscle. The WBSF defines the hardness due to the myofibrillar component (Möller, 1980), while the TPA focuses on the hardness related to the connective tissue (Lepetit and Culioli, 1994; Harper, 1999). Another aspect to bear in mind is that the texture in cooked meat is made of two main components: tenderness, which explains the 64%; and juiciness, which represents 19%. Thus, the least juicy meats are considered less tender (Pinilla, 2014).
The hardness, adhesivity, elasticity, gumminess, and chewiness are the most used TPA parameters in the characterization of the meat quality (Ruiz de Huidobro et al., 2001); they have a significant correlation with the results obtained through a sensory panel (Ruiz de Huidobro et al., 2005). The studied molecular markers had a significant effect upon these characteristics as follows: CAPN4751 had an effect upon hardness (D1, D7, D14), elasticity (D1) and gumminess (D1); CAST282, upon Hardness (D1, D7, D14); CAST2959 upon hardness (D1, D7, D14), adhesivity (D1, D7) and elasticity (D1); and E2FB upon hardness (D1 and D7) and chewiness (D14). This contrasts with the findings of Pinilla (2014), where the CAST2959 SNP was found to have effects only in elasticity and extensibility, while CAST282 presented an effect upon hardness and extensibility. The CAPN4751 SNP did not have any effect upon any of the variables assessed by them. Thus, as observed in this study, the CAPN316 SNP had a very low frequency in the C allele, the reason why this marker was not included in the association analysis.
Despite the low frequencies of the CC genotype (0,04) and the C allele (0,01) of the CAPN316 SNP, the study found an effect of this marker upon the WBSF (D14). In this case, the lowest values were found among animals with the CG genotype. This result is similar to what is reported by different authors in brahman animals (Smith et al., 2009; Chung, Shin, and Chung, 2014; Rubio et al., 2016), Brangus (Corva et al., 2007), and among different taurine breeds (Page et al., 2002; Casas et al., 2006; Kök and Atalay, 2018), where the lowest values are found in animals carrying the C allele. The above contrasts with other findings in which the most tender meat, assessed with a sensory panel (Casas et al., 2005) and through WBSF (Cafe et al., 2010b), was found in brahman animals carrying the GG genotype.
Similarly, there was a significant effect of the CAPN4751 SNP. The best results were found in CC (D7) animals and carriers of the CC and CT (D14). This result coincides with the finding on animals of the brahman breeds (White et al., 2005; Smith et al., 2009; Cafe et al., 2010b; Rubio et al., 2016), Nellore (Pinto et al., 2010), in different taurine breeds (Casas et al., 2006, Alfaro et al., 2012, Chung, Shin and Chung, 2014) and its crossings with Nellore and Brahman (Corva et al., 2007, Curi et al., 2009), where the carriers of the C allele (CC, CT) present the lowest WBSF values.
The animals with a CC genotype in D1 and CG of the CAST282 SNP had the lowest WBSF values in D14, which is similar to the findings reported in the Nellore breed (Pinto et al., 2010) and in different breeds (Schenkel et al., 2006; Avilés et al., 2015; Kök and Atalay, 2018). An analogous result was found in the carriers of the AA genotype of the CAST2959 SNP in D1 and D14, which coincides with which was found in animals from different taurine breeds (Morris et al., 2006) and its crossings with brahman (Casas et al., 2006) and nellore (Curi et al., 2009) breeds.
The E2FB SNP was associated with this characteristic in D14. The lowest values were found among animals with the CC and CT genotypes, which are comparable to the findings reported in taurine livestock (Schenkel et al., 2005) and its crossings with indicine specimens (de Carvalho et al., 2012). Although these authors also reported an association between the E2JW SNP with this characteristic (Lagonigro et al., 2003), this study did not find the said association due to the absence of the T allele, which has been reported as favorable.
The findings of this study and other authors adhere to the observation that these markers have an effect upon the WBSF in the brahman livestock meat (Smith et al., 2009; Casas et al., 2005, Cafe et al., 2010b; White et al., 2005). Nevertheless, other authors suggest that this association does not exist. For example, Pinilla (2014) did not evidence any association among the CAPN316, CAPN4751, CAST282, and CAST2929 SNPs and this variant of brahman animals and neither with its crossing with animals from other breeds.
Regardless of the aforementioned, these results must be analyzed bearing in mind the acceptability context of the meat by its degree of tenderness. Although an association is observed between these SNP with the WBSF (Table 3), the values of this characteristic are in the intermediate levels of tenderness (4,36 < WBSF > 5,37 kgF), tough (5,38 < WBSF > 6,38 KgF) and very tough (> 6,38), according to the scale proposed by Destefanis et al (2008). It must also be taken into account that the observed differences are smaller than 0,5 kgF, whence they are not perceptible by consumers untrained in sensory analysis (Miller et al., 1995; Huffman et al., 1996). Nonetheless, from a meat quality point of view, the existence of this difference is important, which when added to the effect of other genes might lead to important differences in the organoleptic qualities of the meat.
Effects upon the amount of calpastatin and µ-calpain in the muscle.
There was a significant effect of the CAST282, CAST2959, and E2FB SNPs upon the amount of calpastatin and by CAPN4751 upon the amount of µ-calpain. The carriers of the GG genotype of CAST282 had the highest values in the Cast. Something similar happened to the animals with GG genotype of CAST2959, where the change of an A allele for a G increased it by 0,04. Finally, higher values in the TT genotype in comparison with the CT were found in the E2FB marker, there was no difference between CT and CC. The change of a C for a T allele increased in 0,0004216 the amount of the Cast protein.
Upon the µ-calpain, there is a significant effect by CAPN4751. In this case, the CC genotype had the highest values; besides the change of a T allele for a C one increases the amount of this protein by 0,013. Equally, there were differences between GG and CG by CAPN316. Nonetheless, this result is not conclusive due to the unbalance of the samples that generate the low frequency of the C allele in this marker.
The µ-calpain enzyme content found were 3,6 times greater than those of the Cast one, which coincides with the findings of Saccà et al (2015) about the expression of the mRNAs of these genes. The effect of CAPN4751 upon the expression of the µ-calpain; as well as the effect of the CAST282 and CAST2959 SNPs upon the expression of calpastatin, is predictable. This happens due to the fact that these SNPs are located in CANP1 (intron 17) and CAST (intron 5 and region 3´UTR) regions, where there are sequences that regulate their expression. The results are consistent with the findings of Niciura et al. (2012), where the animals carrying the GG genotype of CAST2959 had twice the amount of mRNAs of this gene as the carriers of the heterozygous genotype, both in taurine and indicine livestock. Besides, the CAPN316 SNP does not influence the CAPN1 expression, while the C allele of the CAPN4751 SNP does it in animals of the brahman and Angus breeds (Nattrass et al., 2014). Regarding the effect of the E2FB upon the expression of this protein, there are no relations reported about it in the available literature. The above is coherent with the effect of these markers upon some production and quality characteristics related to the levels of expression of these enzymes (Howard, 2013; Motter et al., 2013; Allais et al., 2014; Calvo et al., 2014; Lee et al., 2014). Nonetheless, these differences are small. For making them clearly evident, animals with more extreme tenderness-quality parameters must be used (Barendse, 2002).