Heterozygosity can be considered as a measure of the amount of genetic variation within a population. This parameter indicates how much the variation exists in the population and how the variation is distributed across the alleles of analyzed markers (Nietlisbach et al., 2016). The observed heterozygosity (Ho) is the proportion of heterozygous individuals in population samples and expected heterozygosity (He) is the probability of an individual being heterozygous in any locus.
The lower observed heterozygosity in most studied genotypes reflects a low level of diversity within each breed or low levels of outcrossing. The observed and expected average heterozygosity results for the European beef breeds were 0.25, and 0.26, respectively. The expected heterozygosity value was greater than the observed heterozygosity, which shows a high level of genetic homozygosity or heterozygosity deficiency. The three European beef breeds showed lower heterozygosity than the reported value based on 777 K SNP data analysis (Kelleher et al., 2017).
The mean observed and expected heterozygosity of the Ethiopian indigenous cattle breeds were 0.403 and 0.400, respectively. These values were higher than the previous results (HO = 0.314; HE = 0.313) obtained from the 50K Bead Chip analysis (Edea et al. 2012). However, it was also lower than the values recorded from microsatellite markers (Dadi et al. 2008).
4.1. Principal component analysis
PC1 explains 3.51% of the variance and differentiates Ethiopian Zebu (B. indicus) and Zenga (Sanga x Zebu) (represented here by Boran and Fogera respectively) from Begait cattle. PC2 explains 2.82% of the variance and differentiates Boran from Fogera and Begait. The three Ethiopian indigenous cattle breeds were grouped according to their geographical distribution, insighting that these breeds have not experienced recent admixture and might have been exposed to different selective pressures and demographic effects. Such breeds could be used directly for genetic conservation and pure-bred genetic improvement programs.
The next Plot explains the variance and differentiation of the three reference European B. taurus from East African breeds, Boran, Begait, and Fogera. PC1 explains 70.63% of the variance and differentiates European B. taurus from East African breed. PC2 explains 7.27% differentiates the three European B. taurus (i.e., Angus, Herford, and Charolais). The Angus cattle breed was genetically distinct from Hereford and Charolais. Gene flow was observed between Charolais and Herford breeds Ethiopia's indigenous breeds showed closely cluster this may have shared a common ancestor.
4.2. Genetic distance and signatures of selection
Pairwise comparison of genetic distance among the six populations ranged from 0.019 to 0.315. Great differentiation (0.315) was observed between Angus (Taurus) and Begait (Zebu) populations, which is expected. This could be because of parental history and low genetic material exchange between the populations. Relatively low genetic distances were also observed between Ethiopian cattle populations (0.019) between Fogera (Zenga) and Boran(zebu).
These low values of genetic distance indicate may be due to gene flow and shared ancestry. Generally, the level of genetic differentiation between populations increases with increasing geographic distance (Deng et al., 2020).
4.3. Biological process and pathway analysis of candidate genes related to carcass
Following domestication, cattle have been subjected to different selective pressures and distributed throughout the world covering various agro-ecologies and production environments. The European cattle breeds included in this study have been highly selected and improved for beef traits, while Ethiopian cattle breeds have been less selected artificially for production traits. Genome-wide analysis of these breeds can aid in better understanding the impacts of selection and differences in genomic structure.
Results from the whole genome scan revealed several positively selected genes involved in different biological and cellular functions including those affecting meat quality characteristics. Meat quality is a multifactorial and complex character that is determined by several factors at different levels, from molecular to mechanical.
4.4. Genes related to meat tenderness
At the molecular level, several cellular pathways have been involved in meat quality characteristics, including muscle growth, glycolysis, muscle contraction, stress reaction, cell cycle, proteolysis, protein ubiquitination, and apoptosis. According to GO keywords, genes involved in actin cytoskeleton organization were determined as meat tenderness (Guillemin et al., 2011, Gao et al., 2011), and similar genes were found to be involved in protein ubiquitination. Ubiquitination is an important stage in protein breakdown (Jiang et al.,2010). The ubiquitination pathway affects muscle qualities that are important for postmortem meat quality, such as softness (Hamill et al., 2012). Negative regulation of actin filament depolymerization and negative regulation of protein complex disassembly are GO keywords that describe how adipocytes are controlled (Gao et al., 2011).
4.5. Genes related to meat intramuscular fat
Intramuscular fat (IMF), a heritable meat quality trait, has an impact on taste, juiciness, appearance, and meat tenderness. Genes involved in the hydrolysis of phospholipids into fatty acids and phosphatidylinositol, as well as phospholipid and carbohydrates metabolism intramuscular fat, according to the pathway analysis (Roux et al., 2015). The metabolism of lipids has been linked to carbohydrates. Glucose levels influence the formation of fatty acids in the liver as well as the quantity of cholesterol or lipid in the blood. The CTNNA1 gene has been linked to the degree of myostatin expression in the skeletal muscle of Holstein-Friesian bulls (Sadkowski et al., 2008). Myostatin is a critical protein that regulates skeletal muscle growth and is thought to be one of the most critical elements in cattle meat productivity.
4.6. Genes related to meat color
The color of the meat and its ability to hold water are two consistency measures that are considered indicators of freshness and wholesomeness (Joo et al., 2013). These traits are linked to variations in glycolysis rate and muscle temperature drop after death. The main protein responsible for the red color of beef is a globular single-chain protein found in the sarcoplasm and represented by candidate genes association. Myoglobin serves as a secondary source of oxygen and assists in the delivery of oxygen within muscles (Joo et al., 2013). Meat pigmentation is associated with Myoglobin.
The darker the meat, the higher the concentration of myoglobin. Exercise, the animal's nutrition, genetics, and environmental conditions all have an impact on myoglobin content. The brilliant red hue of red meat, which is related to a high level of oxymyoglobin, is a positive indicator of quality, whereas the myoglobin concentration in brown meat is a negative indicator (Joo et al., 2013). Muscle glycogen (stored energy) live animal pH =7.1 a conversion to lactic acid adequate levels will result in a pH level lowered. The more glycogen there is, the more lactic acid will be produced the lower pH the darker the color meat.
4.7. Enrichment and biological process analysis using a gene-to-gene similarity matrix
Based on mutual functional annotation, the DAVID 6.8 functional clustering annotation method classifies closely related genes into functionally related groupings. Each functional gene cluster should include a list of shared 'consensus words, a display of enriched terms. Meat tenderness is linked to actin cytoskeleton organization, actin filament-based processes, and protein ubiquitination, whereas adipocyte regulation is linked to the cellular component organization, negative regulation of actin filament depolymerization, and negative control of protein complex disassembly. Meat tenderness is improved by the GO term biological process involved in cell growth (Chang K. 2007).
4.8. Candidate genes related to tropical adaptation
Tropical cattle are subjected to a variety of environmental stresses, including hot and humid weather, limited feed and water supplies, diseases, and parasites (Porto et al., 2014).
The SOD1 gene is involved in heat tolerance (Zeng et al., 2018). Heat stress is the most common cause of oxidative stress, as it causes mitochondrial oxidative stress and cell malfunction, which leads to cell death and damage.
Cell survival in stressful situations necessitates rapid response mechanisms and, as a result, effective resumption of cell functioning when stress has been alleviated. When cells are exposed to heat stress, molecules are produced that are ready to mediate cell death and survival signals, as well as assist the cell's tolerance and/or recovery from damage (Zeng et al., 2018). The SOD1 gene is identified as involved in heat tolerance in tropical breeds and the genotypic frequency result shows AA genotype fixed in European beef breeds, whereas the CC genotype was the most frequent in Ethiopian cattle populations. It was determined that the MATR3 gene is associated with fat storage in cattle. This gene regulates insulin sensitivity and obesity susceptibility (Akakabe et al., 2013). Furthermore, the protein encoded by this gene is primarily found in endothelial cells and blood vessels. Angiogenesis is a physiological process in which pre-existing vessels give rise to new blood vessels. Endothelial cells play an important role in this process. Vasodilation is the dilation of blood vessels to dissipate heat to the environment.
IKBKE is involved in several signaling pathways, including the activation of pro-inflammatory signaling pathways by Toll-like receptor (TLR) at the beginning of immune responses against pathogens. Tri-acyl lipopeptides from bacteria or mycobacteria are ligands for TLR 1, and Di-acyl lipopeptides from mycoplasma are ligands for TLR 6, but the ligand for TLR10 is unknown (Yin et al., 2020).
4.8.1. Pathway analysis candidate gene related to adaptation to tropical conditions
Pathway analysis identified genes as involved in Vasopressin-regulated water reabsorption. Terrestrial animals have evolved a delicate and diverse system to maintain their water homeostasis, thanks to vasopressin-regulated water reabsorption. The antidiuretic hormone vasopressin is released from the pituitary in situations of hypernatremia or hypovolemia and binds to its type-2 receptor in renal main cells (Fukuoka et al., 2020).
Through the regulation of a range of cell fate determination of vascular endothelial cells, regulation of arterial differentiation, and angiogenesis, involvement in Notch signaling induced by classical Notch ligands is important for tissue homeostasis. Angiogenesis is the physiological process by which pre-existing blood vessels give rise to new blood vessels (Akil et al., 2021). These pathways are involved in a variety of key cellular functions, including cell adhesion and cell junction information and regulation, cell migration, polarization, and cell proliferation and survival (Van Hooren et al., 2012).
Endocytosis is the mechanism by which cells transport items into the cell that are too big to pass through the cell membrane's lipid bilayer. Multiple kinds of plasma membrane invaginations regulate this pathway in mammalian cells, each with a different biological function, composition, and cargo recruitment. A variety of stressful situations, such as changes in osmolality, oxygen, or food delivery, pose a threat to cellular viability. As a result, cells have evolved sophisticated stress mechanisms to deal with these difficulties. Some of these stress responses, such as the heat shock response, are well understood (Lopez et al., 2020).
4.9. Linkage disequilibrium
D' and r2 are two alternative LD measures. D' represents historical recombination via allelic association, whereas r2 measures the squared correlation coefficient between locus allele frequencies (Bohmanova et al., 2010). These measurements have a range of 0 to 1. D' = 1 denotes the absence of recombination between the two loci due to the presence of one of the polymorphisms, whereas D' < 1 denotes the presence of historical recombination between the loci. As a result, rather than being a true estimate of LD, D' is a signal of missing haplotypes.
For association studies, dealing with the r2 value is recommended since there is a simple inverse relationship between r2 and the sample size required to detect the association between QTL and SNP (Bohmanova et al., 2010). The r2 value indicates the degree of correlation between the two loci; it equals 1 only if two haplotypes are present. A recent study found that in all populations, the amount of LD available for association analysis does not exceed 960 kb.
The overall average of r2 estimates of LD in Ethiopian cattle populations was lower than the previous SNP-based studies. The overall r2 values obtained for European beef breeds were far lower than those obtained for Angus cattle r2 = 0.25 (Porto-Neto et al., 2014). However, the average r2 values for Ethiopian cattle were higher than those reported for the Nellore cattle breed (r2 = 0.17; D’ = 0.52) (Espigolan et al., 2013). The LD value in Ethiopian indigenous cattle populations is higher than in European breeds, this is due to the chips designed from B. indicus and it is biased to Ethiopian breeds, since Ethiopian cattle populations (i.e., Boran, Begait, Fogera) are Zebu, while European breeds (i.e., Angus, Herford, Charolais) are B. taurus. According to Meuwissen et al. (2016), genomic selection requires an r2 of 0.20 to reach an accuracy of 0.85 for genomic breeding values. The most practical value of r2 for association studies is 0.25. Brien et al., (2014) showed that in genome-wide association analyses, r2 values greater than 0.3 were necessary to provide appropriate power (GWAS). Hence, the 80K chip is more informative for GWAS and genomic selection in Ethiopian cattle populations.