Genome-Wide Signature of Positive Selection in Ethiopian Indigenous and European Beef Cattle Breeds

doi:10.21203/rs.3.rs-2226293/v1

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Genome-Wide Signature of Positive Selection in Ethiopian Indigenous and European Beef Cattle Breeds

https://doi.org/10.21203/rs.3.rs-2226293/v1

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published 31 Jul, 2023

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Background: Despite the availability of genomic methods for determining the origin and divergence of domestic cattle in East Africa, particularly Ethiopia, knowledge regarding their genetic adaptability and divergence remain limited. To investigate signatures of selection Ethiopian cattle populations were genotyped with an 80K SNP array and European beef cattle breeds were also used for comparison purposes.

Results: Across Ethiopian cattle populations, the mean observed and expected heterozygosity were 0.403 and 0.400, respectively. Similarly, for European cattle, observed and expected heterozygosity were 0.25 and 0.26 respectively. PCA and NJ-tree revealed a separation of Ethiopian cattle breeds from European beef breeds. NJ-tree grouped the study cattle according to their breed group with close clustering of Ethiopian cattle populations. The top 1% FST values were considered to delimit genomic regions under positive selection. Some of the candidate genes are involved in biological processes and pathways linked to meat quality attributes determined. Furthermore, some of the candidate genes are associated with tropical adaptation to heat tolerance and resistance to disease.

Conclusion: The levels of genetic variation for SNPs on the Bovines GGP-80K assays obtained in this study indicate that these assays have utility for genetic studies in Ethiopian indigenous cattle breeds. The genetic distance of the indigenous Ethiopian breeds from European beef breeds coincides with existing knowledge, that European beef breeds considered under this study are artificially selected and are taurine, while Ethiopian indigenous breeds are naturally selected.

Beef breeds

SNP array

Selection signature

In Africa, Ethiopia has the largest cattle population (70 million) annual livestock survey (2020/21). According to the Ethiopian Biodiversity Institute, 2016 report, there are more than 28 indigenous cattle breeds/ecotypes that have been recognized to exist in the country. These populations can be further classified into four groups: zebu (B. indicus), sanga (zebu × B. taurus), zenga (sanga × zebu), and humpless B. taurus. Many of them are named after the community maintaining the population or geographical location where they predominate, the true genetic relationship between the main populations has not yet been well defined or documented(1). The productivity of indigenous cattle populations is influenced by several factors such as poor genetics, shortage of feed, water, abundant health problems, and a poor housing system that result in low production and low reproductive performance (2).

The determination of the allelic distribution of markers associated with economically significant traits can be a powerful tool for acquiring immediate knowledge for the selection of superior animals and to make successful early decisions (3). Identification of functional variations such as missense variants and variants in indigenous cattle within downstream and upstream genomic regions would allow these variants to be identified for their effects on complex traits (4). In the absence of phenotypic data, comparisons of breeds that have been subjected to various selective pressures may aid in the identification of genomic areas and genes that regulate qualitative and complicated traits (5, 6).

Therefore, the investigation of differences between and within cattle breeds is an important initial guide for promoting the best use of genetic resources for farm animals and allows successful genetic enhancement to meet the needs of production strategies and to plan and integrate enhancement programs in the context of the unique efficiency of a population (7).

In indigenous cattle, mapping and identification of candidate genes associated with economically significant traits help to attain rapid genetic gain in the beef industry (8). Single nucleotide polymorphism (SNP) markers analysis has become the standard approach in recent years for genome-wide association studies and selection signatures analysis. The commercial availability of a large range of genome-wide SNP panels offers the opportunity to fine map genes impacting complex quantitative traits (9).

Therefore, this study was designed to investigate selection signatures likely associated with beef and ecological traits in three Ethiopian indigenous cattle populations (Boran, Fogera, Begiat) and for comparison purpose European beef cattle breeds (Angus, Herford, Charolais) were considered.

Study Breeds, Sample Collection, And Dna Extraction

DNA samples were collected from three Ethiopian indigenous cattle populations that were kept in government ranches: Begait (n = 40) from Humera ranch, Boran (n = 40) from Dida Tiyura ranch, and Fogera (n = 43) from Andassa ranch. Unrelated female and male animals were sampled based on available pedigree information. Nasal samples were collected using Performagene livestock’s nasal swab DNA collection kit and DNA was extracted from nasal samples according to the manufacturer’s recommendations (DNA Genotek Inc). Three European beef breeds (n = 114) (Angus, n = 42), Hereford (n = 35), and Charolais (n = 37) were used as reference breeds from online database.

Genotyping And Quality Control

Ethiopian cattle samples were genotyped with the 80K SNP bead chip (Gene Seek Genomic Profiler). The SNP markers were screened for a call rate of ≥ 90%, a minor allele frequency (MAF) of > 0.01, and a sample call rate of > 90%. After the above quality management parameters had been applied, the autosomal SNP markers obtained were used for downstream analysis. Two hundred thirty-one animals were kept after removing 6 animals with a genotype completion rate of less than 90%. From an initial set of 67,491 SNPs, a subset of 67252, 67271, 67260, 67392, 67400, 67410, 67310, 67299, and 67300 for Begait-Angus, Begait- Hereford, Begait- Charolais, Boran-Angus, Boran-Hereford, Boran-Charolais, Fogera-Angus, Fogera- Hereford, and Fogera- Charolais, respectively were used for selection signatures analyses.

Data analysis

To examine the basic indices of within-breed genetic variability, genetic diversity (observed and expected heterozygosity) was estimated using PLINK (10). Principal component analysis (PCA) was analyzed using the same software and plotted in R. Power marker software was used to construct phylogenetic trees (11). Pairwise genetic differentiation (FST) values were calculated using PLINK between the following breed pairs: Boran-Angus, Boran-Hereford, Boran-Charolais, Begait-Angus, Begait- Hereford, Begait- Charolais, Fogera-Angus, Fogera- Hereford and Fogera- Charolais according to (12). For all pairwise comparisons, the top 1% FST values were considered to define SNPs under positive. The Bovine UMD.3.1 genome assembly was used to annotate candidate SNPs within the top 1% FST values. Functional analysis was performed using the database for annotation, visualization, and integrated discovery (DAVID) resources (v. 6.8; https://david.ncifcrf.gov/). QTL regions that overlapped with the identified candidate regions were searched from the cattle QTL db (http://www.animalgenome.org/cgibin/QTLdb/BT/index).

Genetic diversity

Genetic variability analysis was carried out to determine the level of heterozygosity within the Ethiopian and European breeds, and the results are presented in Table 1. The overall mean of observed and expected heterozygosity for Ethiopian breeds were 0.40, and 0.40 respectively; while 0.25 and 0.26 values were for European beef breeds (Table 1).

Table 1

Observed (H_O) and expected heterozygosity (H_E) in Ethiopian indigenous cattle breeds and European beef cattle breeds
Breed	H_O	H_E
Begait	0.40	0.40
Boran	0.40	0.40
Fogera	0.41	0.40
Over all	0.40	0.40
Angus	0.25	0.25
Charolais	0.28	0.28
Hereford	0.23	0.26
Overall	0.25	0.26

Population Structure And Relationship

To assess the population structure among the six cattle breeds/populations, a PCA was performed. The SNP data sets clearly distinguished the cattle breeds based on their geographic distributions. Accordingly, the three Ethiopian cattle breeds were clustered separately (Fig. 1). As portrayed in Fig. 2, PC1 explained 70.63% of the total variation and unequivocally separated the Ethiopian indigenous breeds from European beef breeds. Similarly, the phylogenetic analysis reiterated the PCA results. The three Ethiopian cattle breeds shared the same clade, while the European cattle breeds were found in separate clades (Fig. 3). As depicted in Fig. 4 the two European cattle breeds (Hereford and Charolais) were closely clustered as did Boran and Fogera.

Phylogenetic tree analysis (Fig. 4) strongly supports the PCA result, and clustering analysis a clear divergence among breeds of the Ethiopian breeds and the European beef cattle breeds.

Genetic Differentiation And Selection Signatures

The highest genetic differentiation (FST = 0.315) was observed between Angus and Ethiopian cattle populations Boran and Begait. As expected, the lowest genetic differentiation was observed among Ethiopian cattle populations. Moderate genetic FST value was observed among the three European beef cattle breeds.

Table 2

Pairwise genetic differentiation among the six cattle breeds
Breed	Begait	Borana	Fogera	Angus	Charolais	Hereford
Begait	0
Borana	0.028	0
Fogera	0.025	0.019	0
Angus	0.315	0.314	0.297	0
Charolais	0.271	0.275	0.258	0.083	0
Hereford	0.296	0.300	0.284	0.115	0.074	0

Pairwise comparison genetic differentiation between Ethiopian indigenous population and European beef cattle breeds showed very high differentiation (FST value), especially Angus breed showed greater differentiation in all Ethiopian breeds as indicated in Fig. 5.

The solid dark lines indicate the top 1% FST values considered for downstream analysis.

Functional Analysis Of Commonly Differentiated Genes

Commonly differentiated SNPs were annotated and the corresponding genes were associated with biological processes and pathways relevant to meat traits and tropical adaptations.

Genes Related To Meat Quality Trait In European Beef Breeds

Based on Gene Ontology (GO) analysis, seven genes (CAPZB, KIF5A, DCTN2, RGS20, STIM1, KLHL3, and ITGB1BP1) were involved in actin cytoskeleton organization and ten genes (KLHL3, HERC3, NPEPPS, YME1L1, TNIK, KLHL3 PARK2, PPP2R5C, UBE2D3, and GLB1L3) were found to be involved in protein ubiquitination, which is an important stage in protein breakdown. Further pathway analysis revealed genes associated with actin cytoskeleton regulation (MYLK, PIP4K2C, PDGFRA) were associated with meat tenderness.

Genes involved in the hydrolysis of phospholipids into fatty acids and phosphatidylinositol, as well as phospholipid and carbohydrates metabolism (DGAT1, LPCAT1, PLCL2, CTNNA1, and B4GALNT1), were identified as associated with meat intramuscular fat. Five genes (ASAP3, ADAP1, APBB1IP, RTKN2, and STAP2) involved in the main protein responsible for the red color of beef were also identified.

According to enrichment analysis (Table 3) genes involved in meat tenderness (ANAPC4, GLI2, YME1L1, DCTN2, KDM1A, FAF1, PARP4, RGS20), meat color (ASAP3, ADAP1, APBB1IP, RTKN2, STAP2), and meat marbling (DGAT1, FAR1, B4GALNT1) were identified.

Table 3

Enrichment analysis of candidate genes
Genes	P-value	Count	Terms
ANAPC4, GLI2, YME1L1, DCTN2, KDM1A, FAF1, PARP4, RGS20	0.0099	8	Cell proliferation
ASAP3,ADAP1,APBB1IP,RTKN2,STAP2	0.048	5	pH
DGAT1,FAR1, B4GALNT1	0.013	3	Long-chain fatty-acyl-CoA metabolic process

Commonly Differentiated Candidate Genes Related To Tropical Adaptation In Ethiopian Cattle Populations

Tropical cattle are subjected to a variety of environmental stresses. Our BP analysis revealed that the SOD1 gene is involved in heat tolerance. MATR3 gene is associated with fat storage in cattle. IKBKE a non-classical IKK family member is involved in the control of inflammatory reactions, immune cell activation and proliferation, and metabolic disease.

Further Pathway analysis revealed that genes involved in vasopressin-regulated water reabsorption, notch signaling, and Rap1 signaling were identified (Table 4). DCTN2, GNAS, and CREB5 genes were identified as involved in vasopressin-regulated water reabsorption. CTBP2, DTX3, and RBPJ genes were involved in notch signaling regulation. Five genes (IGF1, TLN1, RRAS, GNAS, and KDR) were involved in the Rap1 signaling pathway. Four genes (ASAP3, RAB22A, SH3GLB1, and EPS15) were identified as involved in the endocytosis pathway. KIT and KDR genes were identified as involved in melanogenesis mechanisms that underlie the modulation of skin and hair pigmentation in animals.

Table 4

Pathway analysis of candidate genes related to adaptation to tropical conditions
KEGG pathway	P-value	Genes
Vasopressin-regulated water reabsorption	0.037	DCTN2, GNAS, CREB5
Notch signaling pathway	0.038	CTBP2, DTX3, RBPJ
Rap1 signaling pathway	0.049	IGF1, TLN1, RRAS, GNAS, KDR
Endocytosis	0.05	ASAP3, RAB22A, SH3GLB1, EPS15

The genotypic frequency of the detected genes associated with carcass quality and tropical climate adaptation, showed higher variability in Ethiopian indigenous breeds and lower variability in European beef breeds.

Table 5

Functionally analyzed candidate genes for carcass traits and tropical adaptation genotypic frequencies
BTA	Position	Genes	SNP IDs	Genotypes	Breeds
BTA	Position	Genes	SNP IDs	Genotypes	Begait	Boran	Fogera	Angus	Charolais	Hereford
1	3113041	SOD1	BovineHD0100001037	CC	0.92	0.69	0.85	0	0	0
				AA	0.03	0.30	0	1.00	0.97	1.00
				AC	0 .05	0	0.15	0	0.03	0
1	68601244	MYLK	BovineHD0100019385	AA	0	0	0	0.94	0.63	0.78
				GG	0.76	0.72	0.95	0	0.05	0.05
				AG	0.24	0.28	0.05	0.05	0.32	0.17
2	129996771	ASAP3	BovineHD0200037782	AA	0.82	0.85	0.73	0	0	0
				AG	0.18	0.15	0.27	0	0.03	0.03
				GG	0	0	0	1.00	0.97	0.97
2	130411462	KDM1A	BovineHD0200037886	AA	0.68	0.64	0.48	0	0	0
				AG	0.27	0.33	0.47	0	0	0
				GG	0.05	0.03	0.05	1.00	1.00	1.00
5	56197180	PIP4K2C	BovineHD0500015977	AA	0.76	0.65	0.73	0	0	0
				AG	0.24	0.33	0.25	0	0	0
				GG	0	0	0.03	1.00	1.00	1.00
5	56275158	DCTN2	BovineHD0500015996	AA	0.87	0.72	0.80	0	0	0
				AG	0.13	0.28	0.17	0	0	0
				GG	0	0	0.03	1.00	1.00	1.00
11	88105122	ITGB1BP1	BovineHD1100025411	AA	0.03	0	02	0.98	0.95	0.89
				AG	0.18	0.24	0.20	0.02	0.05	0.11
				GG	0.79	0.76	0.78	0	0	0
12	36667090	PARP4	BovineHD1200010699	AA	0.03	0	0.13	1.00	1.00	1.00
		PARP4		AC	0.18	0.15	0.33	0	0	0
				CC	0.79	0.85	0.55	0	0	0
13	18287520	APBB1IP	BovineHD1300005225	AA	0.03	0.05	0.05	1.00	1.00	1.00
				AG	0.21	0.28	0.45	0	0	0
				GG	0.76	0.67	0.50	0	0	0
13	58051946	GNAS	BovineHD1300016641	AA	0.63	0.77	0.85	0	0	0
				AG	0.32	0.20	0.15	0	0.05	0
				GG	0.05	0.03	0	1.00	0.95	1.00
14	1801116	DGAT1	ARS-BFGL-NGS-4939	AG	0.08	0.17	0.03	0.10	0.19	0.05
				AA	0	0	0	0.90	0.81	0.86
				GG	0.92	0.83	0.97	0	0	0.09
18	56499147	RRAS	BovineHD1800016473	AA	0	0.08	0.03	1.00	0.92	1.00
				AG	0.26	0.41	0.27	0	0.03	0
				GG	0.74	0.51	0.70	0	0.05	0
19	39519992	NPEPPS	BovineHD1900011366	AA	0	0	0	1.00	0.89	1.00
				AG	0.29	0.26	0.35	0	0.11	0
				GG	0.71	0.74	0.65	0	0	0
25	42332601	ADAP1	BovineHD2500011865	AA	0.71	0.54	0.52	0	0	0
				AC	0.29	0.44	0.40	0	0	0
				CC	0	0.03	0.08	1.00	1.00	1.00

Identification Of Candidate Genes Qtl

Table 6

QTLs of the candidate genes (SNPs)
Genes	Position	BTA	QTL	References
SOD1	3113041	1	Heat tolerance	13
IGF1	66654472	5	Carcass weight	14
ANAPC4	46492439	6	Carcass weight	15
EPS15L1	95505916	7	Carcass quality traits	16
PARP4	36667090	12	Carcass weight	17
GNAS	58051946	13	Carcass weight	18
DGAT1	1801116	14	Carcass weight	19

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 (20). The observed heterozygosity (H_o) is the proportion of heterozygous individuals in population samples and expected heterozygosity (H_e) 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 (21). 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 (H_O = 0.314; H_E = 0.313) obtained from the 50K Bead Chip analysis). However, it was also lower than the values recorded from microsatellite markers (22).

Principal Component Analysis

PC1 (Fig. 1) 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.

Figure 2 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.

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 (23).

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.

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 (24), and similar genes were found to be involved in protein ubiquitination. Ubiquitination is an important stage in protein breakdown (25). The ubiquitination pathway affects muscle qualities that are important for postmortem meat quality, such as softness (26). Negative regulation of actin filament depolymerization and negative regulation of protein complex assembly are GO keywords that describe how adipocytes are controlled (24).

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 (27). 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 (28). 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.

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 (29). 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 (29). 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 (29). Muscle glycogen (stored energy) live animal p^H =7.1 a conversion to lactic acid adequate levels will result in a p^H level lowered. The more glycogen there is, the more lactic acid will be produced the lower p^H the darker the color meat.

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 (30).

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 (29). The SOD1 gene is involved in heat tolerance (18). 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 (18). 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 (32). 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 (33).

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 (34). 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 (35). 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 (36).

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 (37).

The levels of genetic variation for SNPs on the Bovines GGP-80K assays obtained in this study indicate that these assays have utility for genetic studies in Ethiopian indigenous cattle breeds. The genetic distance of the indigenous Ethiopian breeds from European beef breeds coincides with existing knowledge, that European beef breeds considered under this study are artificially selected and are taurine, while Ethiopian indigenous breeds are naturally selected. The identification of selection signatures helps us to understand domestication, breed formation, population structure, adaptive evolution, and selection consequences better. The genetic differentiation between Ethiopian and European beef breeds coincides with existing knowledge, that European beef breeds considered in this study have been strongly artificially selected, while Ethiopian indigenous breeds are naturally selected. To prevent the false-positive result the identified candidate genes have to be confirmed through GWAS, sequencing, and omics studies to include them in cattle genetic improvement programs. Future developments of structured breeding programs and the use of genomic selection in the development sector will allow the livestock industry to breed more productive and resilient cattle populations, which will ultimately assist with alleviating poverty and reducing hunger.

BP: Biological Process, CSA: central Statistical Agency, DAVID: Database for Annotation, Visualization and Integrated Discovery, FST: fixation Index, GWAS: Genome-Wide Association Study, GO: Gene Ontology, GGP: Gene Seeks Genomic Profiling, HD: High density, KEGG: Kyoto Encyclopedia of Genes and Genomes, MAF: minor Allele Frequency, MAS: Marker-Assisted Selection, IMF: Meat Intramuscular Fat, NJ: Neighbor-Joining, QTL: quantitative Trait Locus, SNP: Single Nucleotide Polymorphism.

Acknowledgements: The authors express their gratitude to all of the participants who took part in the study.

Author’s contributions: DM, ZE, TST and HD conceptualized and designed the study. GD, JJ, TD, EA, KSK and BS, conceptualize this study.

Funding: This study was supported by International livestock research institute for data collection and Chungbuk National University of South Korea for genotyping.

Availability of data and materials: 'Not applicable'

Ethics approval and consent to participate

All authors declare that animal samples were obtained in compliance with local/national laws in force at the time of sampling. The animals used in this study were owned by governmental institutions (ranches) established for research. Data exchange was by national and international regulations and approved by the owners. The procedure involving sample collection followed the recommendation of directive 2010/63/EU. In addition, the Scientific Ethical Review Board of Addis Ababa University approved the experimental design and animal data collection for the present study (certificate reference number RECSoANS/BIO/05/2021). All methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication: All the authors consent to publish this manuscript.

Competing interests: The authors state that the publishing of this paper does not include any conflicts of interest.

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published 31 Jul, 2023

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Genome-Wide Signature of Positive Selection in Ethiopian Indigenous and European Beef Cattle Breeds

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Journal Publication

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Abstract

Figures

Background

Study Breeds, Sample Collection, And Dna Extraction

Genotyping And Quality Control

Data analysis

Results

Genetic diversity

Population Structure And Relationship

Genetic Differentiation And Selection Signatures

Functional Analysis Of Commonly Differentiated Genes

Genes Related To Meat Quality Trait In European Beef Breeds

Commonly Differentiated Candidate Genes Related To Tropical Adaptation In Ethiopian Cattle Populations

Identification Of Candidate Genes Qtl

Discussions

Principal Component Analysis

Genetic Distance And Signatures Of Selection

Biological Process And Pathway Analysis Of Candidate Genes Related To Carcass

Genes Related To Meat Tenderness

Genes Related To Meat Intramuscular Fat

Genes Related To Meat Color

Enrichment And Biological Process Analysis Using A Gene-to-gene Similarity Matrix

Candidate Genes Related To Tropical Adaptation

Pathway Analysis Candidate Gene Related To Adaptation To Tropical Conditions

Conclusion And Recommendation

Abbreviations

Declarations

References

Status:

Journal Publication

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