Agricultural Reviews

  • Chief EditorPradeep K. Sharma

  • Print ISSN 0253-1496

  • Online ISSN 0976-0741

  • NAAS Rating 4.84

Frequency :
Quarterly (March, June, September & December)
Indexing Services :
AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus

Genetic Diversity and Selection Signatures in Economically Important Traits of Ethiopian Indigenous Cattle Breed as a Base for Dairy Cattle Genetic Improvement: A Review

Assemu Tesfa1,2,*, Kefyalew Alemayehu1, Wossenie Shibabaw1, Bizuayehu Kerisew3, Mengistie Taye1,4
1College of Agriculture and Environmental Science, Bahir dar University, Bahir Dar, Ethiopia.
2Andassa Livestock Research Center, Bahir Dar, Ethiopia.
3Department of Molecular Biology and Genetics, Bahir Dar University, Bahir Dar, Ethiopia.
4Institute of Biotechnology, Bahir Dar University, Bahir Dar, Ethiopia.

The aim of this paper was to review the genetic diversities and selection signatures in economical important traits of Ethiopian indigenous cattle. This allows obtaining rapid genetic gain, predicting genomic potential and developing conservation strategies. A genetic variation among Ethiopian breeds ranging from 0.1 to 4.55% and a within variation of 95.45 to 99.9% was reported by various scholars. About 3.51% differentiation between Boran and Fogera from Begait and 2.82% differentiation of Boran from Fogera and Begait was reported. Even though the observed and expected heterozygosity values among Ethiopian cattle population was lower, research reports shown considerably higher values ranging from 0.638±0.015 in Boran and 0.714±0.022 in Raya-Azebo to 0.700± 0.014 in Ambo and 0.735±0.017 in Sheko. Genes responsible for heat tolerance, control of metabolic disease, immunity genes, high altitude and low altitude adaptation were reported in Ethiopian cattle breeds. In African indicus and European taurian cattle different genes responsible for milk production, milk fat yield and synthesis and milk composition, were reported. Genes associated with milk traits; fertility and reproduction genes were also reported in Ethiopian cattle. The presence of high within breed variation in Ethiopian cattle creates favorable conditions for further improvement through selection. Beyond identifying candidate potential genes, a detailed study targeting genomic prediction of milk yield and genomic inbreeding had better be done, which allows getting information to optimize and speed up the breeding programs and genetic improvement.

Growth of the world population is projected to increase from 7.8 billion in 2020 to 9.7 billion by 2050 (Smith et al., 2020) and it is predicted that demand for animal products will increase by 50% (Singh et al., 2014). And according to the Food and Agriculture Organization (FAO, 2013), beyond the population increment, the global food production is experiencing challenges due to climate change, which requests doubling of the food production so as to meet the increasing demand (Eggen, 2012; Strandén et al.,  2022). Cattle are central to the African economy (Kim et al., 2020; Saravanan et al., 2021) that plays a pivotal role in the economy through the provision of meat, dairy, leather, labor; acting as walking larder, traction power and manure and have societal importance and they are considered as a primary sources of wealth (Zerabruk et al., 2007; IBC, 2012; Xu et al., 2019; Kim et al., 2020). The genetic makeup of these cattle originated from the humpless B. taurus and the humped B. indicus subspecies (Taye et al., 2018) and they have diverse phenotypes with diverse adaptations. These breeds are classified as African Sanga (crossbred between Taurine and Zebu cattle), African Zenga (crossbred between Sanga and Zebu) and African Zebu (Edea et al., 2014a; Kim et al., 2020). These classifications (genetic differentiations) are arising due to domestication and selection pressures done naturally or artificially with human interference (Saravanan et al., 2021).

Several recent developments have strengthened the interest in local breeds (FAO, 2021). The reasons behind are these breeds are the source of vast environmental adaptations for diverse disease and parasite resistance,  tropical climate conditions (including dry, hot, humid), excessive heat tolerance, suitable for extensive management system and are the only options for ecosystem restoration (Kim et al., 2017; Taye et al., 2018; FAO 2021; Vaidya et al., 2023) and even if there productivity compared to exotic breeds is lower, they are the only option available for millions of farmers in the African agro-pastoral systems, where exotic improved breeds under-perform in the traditional management systems (Kim et al., 2020).

Understanding the current genetic diversity and beneficial traits of adaptation and production in indigenous cattle breeds had an important role in order to meet the growing worldwide demands for animal source proteins and develop a breeding strategy for increased meat and milk production (Taye et al., 2018; Cole et al., 2020). Currently, to support the agricultural breeding including livestock breeding viz., nanotechnology (Nikita et al., 2023), artificial intelligence (Vinod, 2023). About 64% (estimated of 20 breeds out of 31 registered breeds) of the Ethiopian local cattle breeds had studied for their genetic diversity within and among breeds; and their ancestral origin, adaptation and introgression with Asian and European cattle breeds with varying genomic characterization approaches (Zerabruk et al., 2007; Hassen et al., 2007; Edea et al., 2014a; Taye et al., 2018; Tarekegn et al., 2018; Kim et al., 2020; Yirsaw, 2021). Genetic diversity studies showed degree of differentiation among and within the livestock breeds or populations, but the selection signature study find the actual reason for that diversification (Saravanan et al., 2020).

This review article is not intended to be comprehensive one covering all the diversity studies and selection signatures; because molecular based researches had alarmingly increased and new findings had published within a finger count days. Given these characters, this paper aims to review the genetic diversities and selection signatures on economically important production and fitness traits of Ethiopian indigenous cattle to be a base for dairy cattle genetic improvement programs. Selection signature analyses can help to identify numerous candidate genes associated with production and fitness traits in domesticated animals (Xu et al., 2019). This selection signature can be analyzed through the identification of the fingerprints of natural and artificial selection pressures in the genomes of cattle (Yirsaw, 2021). Mapping and identification of candidate genes with economic significance allows obtaining rapid genetic gain, predicting genomic potential and developing conservation strategies for indigenous cattle, irrespective of the changing climate (Terefe et al., 2022). Numerous genes coding for production and fitness potential of the indigenous cattle had been identified with varying demographic and adaptation histories.
Methodologies used in genetic diversity and selection signature
Genomic characterization is a precise way of characterizing breeds and helps to identify the breeds or groups of breeds that have retained their uniqueness (FAO, 2021). The genomic evolution and ancestral history can be computed with maternal lineages (mtDNA), paternal lineages (Y chromosome) and autosomal groups (Utsunomiya et al., 2019). Genetic diversity could be described through level of expected and observed heterozygosity, level of allelic polymorphism within and among populations / breeds (Hunde and Tadese, 2020; Yirsaw, 2021); and it can be calculated and presented with population differentiation (FST), Reynold’s distance estimates (Tarekegn et al., 2018), principal component analysis (PCA)-based Clustering (Yirsaw, 2021) and Nei (1978) genetic distance (Hassen et al., 2007).

Various statistical methods and approaches have been used to detect selection signatures in African cattle breeds using DNA sequence or SNP genotype data (Edea et al., 2014a; Taye et al., 2018). The general workflow for the detection of selection signatures starts from the generation of genotype data, either using SNP microarray or high-throughput sequencing technologies (Saravanan et al., 2020). These methods are broadly classified into intra-population statistics (search for footprints within populations) and inter-populations statistics (the degree of differentiation due to locus-specific allele frequencies between the populations) (Saravanan et al., 2020). Intra population statistics includes methods based on site frequency spectrum, linkage disequilibrium and reduced local variability (Taye et al., 2018; Saravanan et al., 2020) while the inter-populations statistics had two groups, single site and haplotype-based differentiation (Tarekegn et al., 2018; Saravanan et al., 2020). Under the umbrella of the above two broad classification methods, different statistical approaches like integrated haplotype score (iHS) (Qanbari et al., 2011), run of homozygosity (ROH) (Ceballos et al., 2018), population differentiation (FST) (Wright, 1978), increased haplotype homozygosity (XP-EHH), cross population composite likelihood ratio (XP-CLR) (Kim et al., 2017), fixation index (F), nucleotide diversity (Pi) (Nanaei et al., 2020; FAO, 2023) and Tajima’s D (Taye et al., 2017) were also used to found selection signatures footprints. The selection of the methods can depend on the data type, software and bioinformatics tools used and knowledge and interests of the researchers.

It is indicated that different methods had brought different results on genetic distance and selection sweeps (Saravanan et al., 2020; Nanaei et al., 2020); and this had an implication to use two and more complementary methods for a single study. Even though different software programs are available in SNP data quality control and analysis, many scholars had used the popular PLINK and R statistical software packages which is due to their open access, speed and reliability. Analysis of gene ontology (GO) had been also used to identify biological pathways that were targeted by selection (Edea et al., 2014b). Because various methods have different strengths and weaknesses and have brought different results, it is recommended to use combinations of more than two methods for the analyses of selection signatures (Saravanan et al., 2020; Nanaei et al., 2020). Use of combined methods had also contributed to reduce and avoid false selection signals that mimic signatures of selection raised due to demographic events such as population expansions, genetic bottlenecks and population subdivision (de Simoni Gouveia et al., 2014). Besides the presence of difference in final result between the methods and software’s, the selection of the methods can also be dependent on the data type, knowledge and interests of the researchers.
Genetic diversity of Ethiopian indigenous cattle

The evolutionary history of Ethiopian cattle

Approximately 8000-10,000 years BC, the Taurine (Bos taurus taurus) and Indicine (Bos taurus indicus) cattle were domesticated from wild aurochs (Bos primigenius) in the Middle East and Indian subcontinent, respectively (Saravanan et al., 2021). In Africa, the earliest group of cattle known to have migrated into the continent were the Bos taurus taurus circa 7,000-4,000 years before present (YBP) and later the Bos taurus indicus circa 4,000-2,000 YBP from their domestication centers (Kim et al., 2020; Mauki et al., 2022). The autosomal DNA indicated that the Bos indicus and Bos taurus breeds are separated <330,000 YBP and the Bos indicus cattle of Chinese was separated <40,000 YBP from Indian and African sisters (Fig 1A) (Utsunomiya et al., 2019).

Ethiopia, as one of the East Africa countries, is considered the cradle of the Near-East B. taurus as well as the Arabian and Indian B. indicus cattle migration corridors (Fig 1B). According to Yirsaw (2021) and Terefe et al., (2022), the main reasons are the country is endowed with diverse indigenous cattle resources, diverse agro-ecology (ranging from extreme lowlands to Afro-alpine zones), located near the Horn and the East Coast and the cattle population is hybrid. With these facts Ethiopia is considered as a secondary hybridization zone for African indigenous cattle (Edea et al., 2014a; Yirsaw, 2021); which is evidently acknowledged with mtDNA analysis as the Ethiopian cattle had taurine ancestor (Kim et al., 2017; Tarekegn et al., 2018) on which the observed zebu influence on the country was a process of introgression. It is indicated that cattle may have penetrated to Ethiopia in the middle of the second millennium B.C (Mekuriaw and Kebede, 2015; Hagos, 2016).

Fig 1: A) Schematic of the phylogenetic trees of autosomal genome lineages in cattle (Utsunomiya et al., 2019); B) Approximate migration route and the origin of Africa domestic cattle (Mwai et al., 2015).

The African content is rich in cattle diversity and had about 150 cattle breeds or populations which are phenotypically grouped in to taurine, zebu and the ancient stabilized taurine × zebu crossbreed known as Sanga (Kim et al., 2017; FAO, 2021). With similar phenotypically grouping, Ethiopia had also a range of 28 (IBC, 2012) to 31 recognized cattle breeds (DAGRIS, 2007); and this number will in near future increased due emergency of uncharacterized breeds which probably due to admixture and breed substitution and decreased due to the facing climate change and lower effective population size observed in some breeds (Edea et al., 2013).
Genetic diversity and distance of Ethiopian cattle
Genetic diversity is the total genomic information in a certain species, including all breeds, subpopulations and varieties that fall within that particular species (Demir et al., 2022). Before domestication, the major sources of genetic variation were natural selection, mutation, migration, gene flow and genetic drift; while artificial selection based on the breeders preference (Bahbahani et al., 2018a; Yirsaw, 2021; Demir et al., 2022) is the currently sources of genetic variation.

Pairwise population differentiation (FST) and Reynolds’ genetic distance (Reynolds et al., 1983) in Ethiopian cattle estimates close relationships among breeds and higher variation within breeds (Edea et al., 2013; Tarekegn et al., 2018; Dadi et al., 2008). This situation coupled with the transformation of the agricultural systems leads to a rapid loss of indigenous livestock resources. A genetic variation among breeds of 4.55% (Tarekegn et al., 2018); 0.56% (Edea et al., 2013); 2% (Edea et al., 2014a); 0.1 -4% (Dadi et al., 2008) was reported between Ethiopian breeds. Even grouping of Ethiopian cattle into highland and lowland had contributed low (0.42%) group variation (Edea et al., 2013). Principal component analysis (Yirsaw, 2021) indicated a 3.51% differentiation between Boran and Fogera from Begait and 2.82% differentiation of Boran from Fogera and Begait. However higher genetic distance between Arsi, Sheko, Horro, Guraghe Highland and Abigar cattle was reported (Hassen et al., 2007). The main reasons for low genetic differentiation could be a result of a recent common ancestral origin, multiple introgressions, short domestication history and admixture of the population and lack of selection pressure (Edea et al., 2013; Tarekegn et al., 2018; Hunde and Tadese, 2020). Besides, varying reports could also be a result of differences in molecular markers used, type of laboratory procedures, sample size and area coverage of each sample collected (Hunde and Tadese, 2020). 

The phylogenetic analysis reported by Dadi et al., (2008) and PCA analysis (Edea et al., 2013) indicated that the Ethiopian cattle breed had two clusters (Fig 2A and B). These are Sheko in one cluster and other cattle in another cluster. Other studies also indicated that there is higher variability in Sheko breed (Hassen et al., 2007; Tarekegn et al., 2018). The authors reasoned that the breed, Sheko cattle, is originally short horn taurine cattle of East Africa; and believed that it had a different and longer evolutionary history. Edea et al., (2014a) also indicated that 76% (on average with exception of Sheko) of the genome of Ethiopian cattle populations shared an Asian zebu background, whereas approximately 41% and 59% of Sheko samples appeared to share taurine and indicine ancestry, respectively. But currently the breed has miniature humps due to interbreeding with zebu cattle (Dadi et al., 2008).

Fig 2: A) Genetic relationships among Ethiopian cattle based on microsatellite loci (Dadi et al., 2008); B) Principal component analysis (PCA) based on autosomal SNPs of 10 cattle breeds (Edea et al., 2014a).

It was also reported that the observed and expected heterozygosity values among the Ethiopian cattle population was lower (Dadi et al., 2008; Edea et al., 2013). The overall mean observed and expected heterozygosity for Boran, Begayit and Fogera breeds were 0.40, 0.40, respectively (Yirsaw, 2021). Besides, a considerably higher respective observed and expected heterozygosity per population ranging from 0.638±0.015 in Boran and 0.714±0.022 in Raya-Azebo to 0.700± 0.014 in Ambo and 0.735±0.017 in Sheko was reported (Dadi et al., 2008); while lower observed heterozygosity of Danakil (0.363), Horro (0.387), Borana (0.374), Arsi (0.376) and Ambo (0.385) was reported (Edea et al., 2013).
Selection signatures in economically important traits
African indigenous cattle breeds have unique morphological features that distinguish them from other cattle that are largely the result of natural and human selection (Mwai et al., 2015). They have evolved to adapt to the harsh environmental conditions like livestock diseases, high solar radiation and temperature, drought and poor nutritional condition (href="#mbole-kariuki_2014">Mbole-Kariuki et al., 2014; Kim et al., 2017). In addition, African zebu cattle are still a reliable source of draught power (Rege et al., 2001). Likewise, Ethiopian breeds had immense adaptation; example Sheko breed is tolerant to trypanosomosis, Barka has active disposition, Jem-Jem is well adapted to the wet and cold climate, Ogaden breed has good dairy and beef characteristics, Raya-Azebo has good draught power, Arado is a docile, good working animal, Fogera had docile temperament and good milk yield and Horro breed is known for its calm disposition with variable milk production (DAGRIS, 2007; Mwai et al., 2015). These environmental conditions and various adaptations of the Africa indigenous cattle provide a signal of positive selection (Kim et al., 2017). In the classical view, selection acts upon newly arising beneficial mutations, but under some circumstances, standing genetic variation that was previously neutral or slightly deleterious may become the source for adaptive substitutions (Burke, 2012).

The unique genetic patterns or footprints left behind in the genome of individuals under selection are called ‘selection signatures’. Knowledge of selection signatures may help in understanding the basis of heat tolerance and disease resistance (adaptable traits of indigenous cattle breeds) (Saravanan et al., 2021); enable a better understanding of the evolutionary forces that shape the genetic constitution of populations (Edea et al., 2014a); acts a successful tool for the long-term improvement of livestock populations; allows to speed up the rate of genetic improvements  (Cole et al., 2020; Saravanan et al., 2020); and used to identify genomic regions affected by natural and artificial selection that are associated with the phenotypes of specific populations (Taye et al., 2018).

Selection interest had varied between the production participating components like producers, processor, breeders and the scientists. Scientists, as indicated by Cole et al., (2020), required the selection of specific gene of interest to be expressed in the animals while, production participants, even the cost of manufacturing is higher, need to manufacture those traits with technological approaches. However, currently genomic selection provides an answer to both parties and avoids the problems of the past. Selection signatures for production (Singh et al., 2014; Bahbahani et al., 2018a; 2018b; Nanaei et al., 2020; Yirsaw, 2021; Saravanan et al., 2021), fitness (Kim et al., 2017; Saravanan et al., 2021; Yirsaw, 2021), environmental adaptation (Kim et al., 2017; Taye et al., 2018; Saravanan et al., 2021; Yirsaw, 2021; Demir et al., 2022) and adaptation to higher and lower altitudes (Terefe et al., 2022) was reported in Ethiopian and other Bos indicus cattle breeds.

Candidate genes related to immunity and tropical adaptation
Climate is the single most important ecological factor that determines the growth, development and productivity of domestic animals (Demir et al., 2022). The continuing steady ambient temperature increment is becoming a big challenge that lowers the productivity, even death of animals and causes a significant reduction in biodiversity (Alemayehu and Molla, 2018; Taye et al., 2018). Animals adapt these climatic conditions through physiological, metabolic and other inherent conditions. Presence of disease deteriorates the productivity of cattle through depressing potential traits and lower farm profitability (Cole et al., 2020). It was reported that more genes related to disease resistance are available in Bos indicus cattle than Bos taurus breeds (Alemayehu and Molla, 2018; Saravanan et al., 2021) which is due to natural selection for survival in the former and artificial selection targeting economical production traits in the later species. Advances in biotechnology allows the identification of disease causing agents though molecular markers and enables a method of reduction in pathogens or parasite abundances (Singh et al., 2014).

A thermo tolerance in cattle was identified based on expression or activation of biological markers (Taye et al., 2018; Saravanan et al., 2021; Yirsaw, 2021). Heat shock transcription factor (HSF), heat shock proteins (HSP70, HSP90 and HSP27) (Saravanan et al., 2021), cellular response to heat [Gene Ontology (GO): 0034605] and regulation of pH (GO: 0006885) (Yirsaw, 2021) and genes involved in calcium signaling (ATP2A2, TGM3 and TGM1) (Taye et al., 2018) were reported as a contributor for thermo tolerance in different breeds of cattle. According to Terefe et al., (2022), a total of 144 and 20 candidate selected regions for respective high and low altitude adaptation were found in Ethiopian zebu populations. The candidate genes have different biological processes, cellular and molecular functions and pathways responsible for immune response for disease resistance and adaptation for environmental stress. For example the function of MZB1 gene is related to the endoplasmic reticulum calcium ion homeostasis, cellular signal transduction, B cell activation and T cell proliferation; and STING1 gene is responsible to the innate immune signaling response to protect the host against viral and bacterial infections (Terefe et al., 2023). According to reports, these genes responsible for environmental adaptation, disease resistance and immunity were continuously detected in the genome of the African livestock population due to the retained synonymous and missense mutations creating polymorphism in a single gene and gene segment’s (Taye et al., 2017; Terefe et al., 2023; Getinet, 2016; Adebabay, 2018; Edea et al., 2018). Table 1 presents a summary of genes responsible for different tropical adaptation and immunity functions in Ethiopian and other Bos indicus cattle.

Table 1: Genes responsible for different tropical adaptation and immunity functions in Bos indicus cattle.

Candidate genes related to milk yield and its constituents
Since most of the indicine breeds were used for the dairy purpose, it is expected to have several genes associated with milk production traits. According to Singh et al., (2014), animal databases show around 344 and 71 quantitative trait loci (QTL) associated with milk yield and mastitis related traits, respectively. Table 2 summarizes those genes related to milk production in European and African cattle breeds.

Table 2: Candidate genes responsible for milk production and milk related functions.

In a work done on African indicus (Ankole, Kenana, N’Dama) and European taurus cattle (Hereford and Holstein) reported genes related to milk production (IGFBP2, RORA, B4GALT1, CD44, MACF1, IL15), milk fat yield and synthesis (LPIN1, ACACA, PDE3A, ABCC9), milk composition (NF2, KCNIP4, CSN3) and milk traits (GHR, NME1,  ATP2B) (Nanaei et al., 2020). Genes associated with milk traits (prolactin, leptin, DGAT1 and ABCG2), milk protein expression [CSN1S1 (casein Q s1)], milk protein concentration [LGB b-lactoglobulin)] and milk protein synthesis and fat metabolism (STAT1 (signal transducer and activator of transcription 1) were reported (Singh et al., 2014). The Diacylglycerol acyl-CoA acyltransferase 1 (DGAT1) genes had reported to have high diversity, heterozygosity and polymorphic information content under Ethiopian cattle breeds (Fogera, Boran, Begait and Horro cattle) (Samuel et al., 2022). Besides the presence of leptin gene in Ethiopian cattle breed (Mandefro et al., 2021), fertility and reproduction genes (RXFP2, CLGN, MEA1) in Sheko cattle (Bahbahani et al., 2018b) was also reported. The distribution of different milk related genes in the autosomal chromosome were indicted (Fig 3I) and clustering and molecular phylogenetic analysis for comparison of the haplotypes of the cattle breeds with other species for SNPs of Leptin gene in Ethiopian cattle breeds (Fig 3II) was indicated.

Fig 3: I) Genomic landscape of positive selection signatures for milk associated traits using the FST (A) and XP-CLR (B) values (Nanaei et al., 2020). II) UPGMA tree of the six cattle breeds based on SNP data with linked software, MEGA X (a) and Molecular phylogenetic analysis for comparison of the haplotypes of the cattle breeds with other species (b) for Leptin gene SNPs (Mandefro et al., 2021).

Significance connotations for the ethiopian dairy development
Genetic improvement provides a significant technique to improve the performance of herds through selection of superior animals to be a parent for the next generation based on their performance in target traits under the breeding program (Nwogwugwu et al., 2020). And the use of genomic selection in the dairy cattle is a useful tool for selecting traits with low heritability and difficult and expensive to measure, with accuracy level range of 0.8 for production traits and 0.7 for fertility (Meuwissen et al., 2016), increases genetic gain and reduce the generation interval (Nwogwugwu et al., 2020; Saravanan et al., 2020).

Economically important traits in farm animals largely consist of complex and continuously distributed phenotypes and understanding of their structure and function in the genome had bought international interest in the use animal genetic resources (Alemayehu and Molla, 2018). The presence of genes responsible for climatic resistance with a varying diversity in the Ethiopian cattle benefits the country in potential use of them for future generation under the continuously changed climatic condition. Demir et al., (2022) indicated that the conservation of genomic variants in adaptation will allow animals to adapt to future challenges, benefit farms for sustainable use of local breeds and these animals will be the only answers in the ongoing global warming.

The continuous admixture between different Ethiopian breeds due to in search of feed and water (Boran cattle), escaping of flood of Lake Tana (Fogera cattle), indiscriminate crossbreeding (Sheko cattle) and increased urbanization and crop intensification (lowering grazing lands), will create a gene flow and population bottleneck and become a big factor in threatening unique cattle breeds. Even though these cases had lowered the genetic diversity among breeds, still there is a wider within breed diversity that allows selection and preservation of unique genetic variants in these breeds. Understanding the presence of genetic diversity and selection signatures in milk production, disease resistance and other productivity traits in Ethiopian cattle benefits the actors in dairy sector; allows designing effective improvement and conservation strategies that targets the production and management conditions of producers and farmers; and will provide a basis for future genome-wide association studies and investigations into genomic targets of selection in dairy cattle. But, realization of these genetic potentials will require placing those animals in the right environment and management conditions. 
The genetic diversity and population structure studies indicated that the Ethiopian cattle breeds are closely related and are at risk of becoming genetically homozygous. However, the presence of high within breed variation creates favorable conditions for further improvement through selection. The molecular studies in the Ethiopian cattle breeds had been limited to the well-known breeds thus even though the cost of genomic study is expensive, unaddressed breeds with wider adaptations and production performances had better be considered to print out the full picture of breed diversity and differentiation among Ethiopian cattle’s. Besides, genomic prediction of milk yield, prediction of inbreeding and other production traits need to be considered to get information to optimize and speed up the breeding performances and genetic improvement.
All authors declared that there is no conflict of interest.

  1. Adebabay, K.B. (2018). Whole Genome Based Characterization of Indigenous Chicken Populations in Ethiopia. PhD dissertation, Addis Ababa University. Addis Adaba Ethiopia. 

  2. Alemayehu, K. and Molla, E. (2018). The role of economically important traits for genetic improvement and climate change adaptation in livestock production: A review. Ethiop. J. Sci. and Technol. 11(2): 145-163.  

  3. Bahbahani, H., Afana, A. and Wragg, D. (2018b). Genomic signatures of adaptive introgression and environmental adaptation in the Sheko cattle of southwest Ethiopia. Plos One. 13(8): e0202479.

  4. Bahbahani, H., Salim, B., Almathen, F., Al Enezi, F., Mwacharo, J.M. and Hanotte, O. (2018a). Signatures of positive selection in African Butana and Kenana dairy zebu cattle. Plos One. 13(1): e0190446. journal.pone.0190446.

  5. Burke, M.K. (2012). How does adaptation sweep through the genome? Insights from long-term selection experiments. Proc. R. Soc. 279: 5029-5038. 

  6. Ceballos, F.C.,  Joshi, P.K., Clark, D.W., Ramsay, M. and Wilson, J.F. (2018). Runs of homozygosity: Windows into population history and trait architecture. Nature Reviews Genetics. 19: 220-234.

  7. Cole, J.B., Eaglen, S.A.E., Maltecca, C., Mulder, H.A. and Pryce, J.E. (2020). The future of phenomics in dairy cattle breeding. Animal Frontiers. 10(2): 37-44.

  8. Dadi, H., Tibbo, M., Takahashi, Y., Nomura, K., Hanada, H. and Amano, T. (2008). Microsatellite analysis reveals high genetic diversity but low genetic structure in Ethiopian indigenous cattle populations. Animal Genetics. 39: 425- 431. 

  9. DAGRIS, (2007). Domestic Animal Genetic Resources Information System (DAGRIS). [(eds.) Kemp, S., Mamo, Y., Asrat, B. and Dessie, T.]. International Livestock Research Institute, Addis Ababa, Ethiopia.

  10. de Simoni Gouveia J.J., da Silva M.V., Paiva S.R., de Oliveira S.M. (2014). Identification of selection signatures in livestock species. Genetics and Molecular Biology. 37(2): 330-342.

  11. Demir, E., Ceccobelli, S., Bilginer, U., Pasquini, M., Attard, G. and Karsli, T. (2022). Conservation and selection of genes related to environmental adaptation in native small ruminant  breeds: A review. Ruminants. 2: 255-270. 

  12. Edea, Z., Bhuiyan, M., Dessie, T., Rothschild, M.F., Dadi, H. and Kim, K.S. (2014a). Genome wide genetic diversity, population structure and admixture analysis in African and Asian cattle breeds. Animal. 9(2): 218-226. doi:10.1017/S1751 731114002560.

  13. Edea, Z., Dadi, H., Kim, S.W., Park, J.H., Shin, G.H., Dessie, T. and Kim, K.S. (2014b). Linkage disequilibrium and genomic scan to detect selective loci in cattle populations adapted to different ecological conditions in Ethiopia. J. Anim. Breed. Genet. 1-9. doi:10.1111/jbg.12083.

  14. Edea, Z., Dadi, H., Dessie, T., Uzzaman, M.R., Rothschild, M.F., Kim, E.S., Sonstegard, T.S. and Kim, K.S. (2018). Genome- wide scan reveals divergent selection among taurine and zebu cattle populations from different regions. Stichting International Foundation for Animal Genetics. 49(6): 550- 563. doi: 10.1111/age.12724.

  15. Edea, Z., Dadi, H., Kim, S.W., Dessie, T., Lee, T., Kim, H., Kim, J.J. and Kim, K.S. (2013). Genetic diversity, population structure and relationships in indigenous cattle populations of Ethiopia and Korean Hanwoo breeds using SNP markers.  Frontiers in Genetics: Livestock Genomics. 4: 35. doi: 10.3389/fgene.2013.00035.

  16. Eggen, A. (2012). The development and application of genomic selection as a new breeding paradigm. Animal Frontiers. 2(1). doi:10.2527/af.2011-0027.

  17. FAO, (2013). Tackling climate change through livestock. A global assessment of emissions and mitigation opportunities. Food and Agricultural Organization of the United Nations. Rome, Italy. Retrieved on 14 Oct 2021 from https://

  18. FAO, (2021). Draft Practical Guide on Genomic Characterization of Animal Genetic Resources. Eighteenth Regular Session: 27 September-1 October 2021. CGRFA-18/21/10.2/Inf.2.

  19. FAO, (2023). Genomic Characterization of Animal Genetic Resources: Practical Guide. [Ajmone-Marsan, P., Boettcher, P.J., Colli, L., Ginja, C, Kantanen J. and Lenstra, J.A., (eds.)]. FAO Animal Production and Health Guidelines No. 32. Rome. 

  20. Getinet, M.T. (2016). Molecular Characterization of Ethiopian Indigenous Goat Populations: Genetic Diversity and Structure, Demographic Dynamics and Assessment of the Kisspeptin Gene Polymorphism. PhD dissertation, Addis Ababa University. Addis Adaba Ethiopia. https://

  21. Hagos, B. (2016). Ethiopian cattle genetic resource and unique characteristics under a rapidly changing production environment- A review. International Journal of Science and Research. 6(12). doi: 10.21275/ART20179194.

  22. Hassen, F., Bekele, E., Ayalew, W. and Dessie, T. (2007). Genetic variability of five indigenous Ethiopian cattle breeds using RAPD markers. African Journal of Biotechnology. 6(19): 2274-2279.  

  23. Hunde, D. and Tadese, Y. (2020). Genetic distance and differentiation among cattle breeds in Ethiopia: A review. Eth. J. Anim. Prod. 20(1): 80-88.

  24. IBC, (2012). Ethiopian National Strategy and Plan of Action for Conservation, Sustainable Use and Development of Animal Genetic Resources: Draft Document. 

  25. Kim, J., Hanotte, O., Mwai, O.A., Dessie, T., Bashir, S., Diallo, B., Kim, K., Kwak, W., et al. (2017). The genome landscape of indigenous African cattle. Genome Biology. 18(34). doi: 10.1186/s13059-017-1153-y. 

  26. Kim, K., Kwon, T., Dessie, T., Yoo, D., Mwai, O. A., Jang, J., Sung, S., Lee, S., Salim, B. et al. (2020). The mosaic genome of indigenous African cattle as a unique genetic resource for African pastoralism. Nature Genetics. 52: 1099-1110.

  27. Mandefro, A., Sisay, T., Kim, K.S., Edea, Z., Konwarh, R. and Dadi, H. (2021). Single nucleotide polymorphisms of leptin gene in five Ethiopian indigenous cattle breeds and the Korean Hanwoo breed. Tropical Animal Health and Production. 53(2): 202.  doi: 10.1007/s11250-021-02642-1.

  28. Mauki, D.H., Tijjani, A., Ma, C., Ng’ang’a, S.I., Mark, A.I., Abdussamad, A.M., Olaogun, S.C., et al. (2022). Genome-wide investigations reveal the population structure and selection signatures of Nigerian cattle adaptation in the sub-Saharan tropics. BMC Genomics. 23(1): 306.  doi: 10.1186/s12864-022- 08512-w.

  29. Mbole-Kariuki, M.N., Sonstegard, T., Orth, A., Thumbi, S.M., Bronsvoort, B.M.D.C., Kiara, H., Toye, P., Conradie, I., Jennings, A., Coetzer, K., Woolhouse, M.E.J., Hanotte, O., Tapio, M. (2014). Genome-wide analysis reveals the ancient and recent admixture history of East African Shorthorn Zebu from Western Kenya. Heredity. 113: 297-305. 

  30. Mekuriaw, G. and Kebede, A. (2015). A review on indigenous cattle genetic resources in Ethiopia: Adaptation, status and survival. Online J. Anim. Feed Res. 5(5): 125-137.

  31. Meuwissen, T.H., Hayes, B.J. and Goddard, M.E. (2016). Genomic selection: A paradigm shift in animal breeding. Anim Front. 6: 6-14.

  32. Mwai, O., Hanotte, O., Kwon, Y.J. and Cho, S. (2015). African indigenous cattle: Unique genetic resources in a rapidly changing world. Asian Australas. J. Anim. Sci. 28(7): 911-921.

  33. Nanaei, H.A., Qanatqestani, M.D. and Esmailizadeh, A. (2020). Whole-genome resequencing reveals selection signatures associated with milk production traits in African Kenana dairy zebu cattle. Genomics. 112: 880-885.

  34. Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics. 89: 583-590.

  35. Nikita, S., Naresh, G. and Abha, K. (2023). Latest developments and applications of nanotechnology in agriculture sector: A review. Agricultural Reviews. 44(3): 275-288. doi: 10.18805/ag.R-2175.

  36. Nwogwugwu, C.P., Kim, Y., Ugbo, E.H., Lee J.H. and Lee, S.H. (2020).  Review on the genetic improvement and application of genomic selection in Korean Hanwoo cattle. Journal of Animal Breeding and Genomics. 4(2): 19-31.

  37. Qanbari, S., Gianola, D., Hayes, B., Schenkel, F., Miller, S., Moore, S., Thaller, G. and Simianer, H. (2011). Application of site and haplotypefrequency based approaches for detecting selection signatures in cattle. BMC Genomics.  12: 318.

  38. Rege, J.E.O., Kahi, A., Okomo-Adhiambo, M., Mwacharo, J. and Hanotte, O. (2001). Zebu cattle of Kenya: Uses, performance, farmers preference, measures of genetic diversity and options for improved use. Animal Genetic Resources Research 1. ILRI (International Livestock Research Institute), Nairobi, Kenya. 103 pp.

  39. Reynolds, J., Weir, B.S. and Cockerham, C.C. (1983). Estimation of the coancestry coefficient: Basis for a short-term genetic distance. Genetics. 105: 767-779.

  40. Samuel, B., Mengistie, D., Assefa, E., Kang, M., Park, C. and Dinka, H. (2022). Genetic diversity of DGAT1 gene linked to milk production in cattle populations of Ethiopia. BMC Genomic Data. 23: 64.

  41. Saravanan, K.A., Panigrahi, M., Kumar, H., Bhushan, B. and Mishra, B.P. (2020). Selection signatures in livestock genome: A review of concepts, approaches and applications. Livestock Science. 241(2020): 104257. doi: 10.1016/j.livsci.2020. 104257.

  42. Saravanan, K.A., Panigrahi, M., Kumar, H., Parida, S., Bhushan, B., Gaur, G.K., Dutt, T., Mishra, B.P. and Singh R.K. (2021). Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds. Genomics. 113(2021): 955-963. 

  43. Singh, U., Deb, R., Alyethodi, R.R., Alex, R., Kumar, S., Chakraborty, S., Dhama, K. and Sharma, A. (2014). Molecular markers and their applications in cattle genetic research: A review. Biomarkers and Genomic Medicine. 6: 49-58. 

  44. Smith, J., Wright, I., Grace, D. and Perry, B. (2020).  Conclusion: The Future of Research at ILRI.  The Impact of the International Livestock Research Institute. 2020. Edited by John McIntire and Delia Grace. Nairobi, Kenya: ILRI and Wallingford, UK: CABI.

  45. Strandén, I., Kantanen, J., Lidauer, M.H., Mehtiö, T. and Negussie, E. (2022). Animal board invited review: Genomic-based improvement of cattle in response to climate change. Animal. 16: 100673. 2022.100673.  

  46. Tarekegn, G.M., Ji, X., Bai, X., Liu, B., Zhang, W., Birungi, J., Djikeng, A. and Tesfaye, K. (2018). Variations in mitochondrial cytochrome b region among Ethiopian indigenous cattle populations assert Bos taurus maternal origin and historical dynamics. Asian-Australas J. Anim Sci. 31(9): 1393-1400. Taye, M., Lee, W., Caetano-Anolles, K., Dessie, T., Cho, S., Oh, S.J., Lee, H.K. and Kim, H. (2018). Exploring the genomes of East African Indicine cattle breeds reveals signature of selection for tropical environmental adaptation traits. Cogent Food and Agriculture. 4(1): 1552552. doi: 10.10 80/23311932.2018.1552552.  

  47. Terefe, E., Belay, G., Han, J., Hanotte, O. and Tijjani, A. (2022). Genomic adaptation of Ethiopian indigenous cattle to high altitude. Front. Genet. 13: 960234. 10.3389/fgene.2022.960234.

  48. Terefe, E. Belay, G. Tijjani, A. Han, J. Hanotte, O. (2023). Whole genome resequencing reveals genetic diversity and selection signatures of ethiopian indigenous cattle adapted to local environments. Diversity. 15: 540. https:/ /

  49. Utsunomiya, Y.T., Milanesi, M., Fortes, M.R.S., Porto-Neto, L.R., Utsunomiya, A.T.H., Silva, M.V.G.B., Garcia, J.F. and Ajmone-Marsan, P. (2019). Genomic clues of the evolutionary history of Bos indicus cattle. Animal Genetics. 50: 557- 568. doi: 10.1111/age.12836.

  50. Vaidya, M.M., Dhenge, S.A., Dongre, V.B. and Singh, S.V. (2023). Role of HSP and leptin in dairy animals during thermal stress: A review. Agricultural Reviews. 44(3): 370-374. doi: 10.18805/ag.R-2547.

  51. Vinod, S.S.C. (2023). Role of artificial intelligence in Indian agriculture: A review. Agricultural Reviews. 44(4): 558-562. doi: 10.18805/ag.R-2296.

  52. Wright, S. (1978). Evolution and the Genetics of Populations, Vol. 4. University of Chicago Press, Chicago.

  53. Xu, L., Yang, L., Zhu, B., Zhang, W., Wang, Z., Chen, Y., Zhang, L., Huijiang Gao, Liu, G.E. and Li, J. (2019). Genome- wide scan reveals genetic divergence and diverse adaptive selection in Chinese local cattle. BMC Genomics. 20: 494. 

  54. Yirsaw, D.M. (2021). Genome-Wide Signature of Positive Selection, Breed-specific SNPs and Linkage Disequilibrium in Ethiopian Indigenous and European Beef Cattle Breeds. M.Sc Thesis; Addis Ababa University, Addis Ababa, Ethiopia. Pp 111.   

  55. Zerabruk, M., Bennewitz, J., Kantanen, J., Olsaker, I. and Vangen, O. (2007). Analysis of genetic diversity and conservation priorities for six north Ethiopian cattle breeds. J. Anim. Breed. Genet. 124(2007): 236-241.

Editorial Board

View all (0)