Future Perspective of NGS Data for Evaluation of Population Genetic Structure in Turkish Cattle


  • Eymen Demir Department of Animal Science, Faculty of Agriculture, Akdeniz University
  • Nina Moravčíková Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources, Institute of Nutrition and Genomics, Slovak Republic
  • Taki Karsli Akdeniz University, Faculty of Agriculture, Department of Animal Science, Republic of Turkey
  • Radovan Kasarda Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources, Institute of Nutrition and Genomics, Slovak Republic


bioinformatics, local cattle, NGS, whole-genome sequencing


Developments in sequencing and SNP chip technologies have enabled scientists to obtain high-density genomic data from different livestock species, including cattle. Moreover, many bioinformatics tools are available to analyse high-density genomic data. Via these tools, several statistical approaches such as Principal Component Analysis and clusterin-based analyses could be conducted to reveal the genetic structure of cattle populations. However, revealing the genetic structure and selection signatures of Turkish cattle breeds is a new area of research, since the previous studies are limited with a few microsatellite data. On the other hand, rearing in different geographical and environmental conditions for a long period could possibly lead to more genetic variation in native Turkish cattle breeds compared to high-yielding culture breeds. These variations obviously cannot be detected by limited number of microsatellite markers, while Next Generation Sequencing is promising for further population structure studies. Hence this review aims to summarise previous studies and give a perspective of Next Generation Sequencing possibilities to reveal the population structure of Turkish cattle for further studies.


Alarslan, E. et al. (2021) Genetic identification and characterisation of some Turkish sheep. Small Ruminant Research, 202, 106455. https://doi.org/10.1016/j.smallrumres.2021.106455

Bai, Y. et al. (2012) Current status and future perspectives for sequencing livestock genomes. Journal of Animal Science and Biotechnology, 3(1), 1-6. https://doi.org/10.1186/2049-1891-3-8

Brøndum, R.F. et al. (2014) Strategies for imputation to whole genome sequence using a single or multi-breed reference population in cattle. BMC genomics, 15(1), 1-8. https://doi.org/10.1186/1471-2164-15-728

Decker, J.E. et al. (2014) Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genetics, 10(3), e1004254. https://doi.org/10.1371/journal.pgen.1004254

Demir, E. and Balcioğlu, M.S. (2019) Genetic diversity and population structure of four cattle breeds raised in Turkey using microsatellite markers. Czech Journal of Animal Science, 64(10), 411-419. https://doi.org/10.17221/62/2019-CJAS

Demir, E. et al. (2021) A comprehensive review on genetic diversity and phylogenetic relationships among native Turkish cattle breeds based on microsatellite markers. Turkish Journal of Veterinary and Animal Sciences, 45(1), 1-10. https: //doi:10.3906/vet-2006-107

Di Lorenzo, P. et al. (2018) Mitochondrial DNA variants of Podolian cattle breeds testify for a dual maternal origin. PLoS One, 13(2), e0192567. https://doi.org/10.1371/journal.pone.0192567

Edea, Z. et al. (2015) Genome-wide genetic diversity, population structure and admixture analysis in African and Asian cattle breeds. Animal, 9(2), 218-226. https://doi.org/10.1017/S1751731114002560

Elsik, C.G. et al. (2009) The genome sequence of taurine cattle: a window to ruminant biology and evolution. Science, 324(5926), 522-528. https://doi.org/10.1126/science.1169588

Excoffier, L. et al. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131(2), 479-491. https://doi.org/10.1093/genetics/131.2.479

Fraga, A.B. et al. (2016) Multivariate analysis to evaluate genetic groups and production traits of crossbred Holstein× Zebu cows. Tropical Animal Health and Production, 48(3), 533-538. https://doi.org/10.1007/s11250-015-0985-2

Ghafar, A. et al. (2021). Targeted next-generation sequencing and informatics as an effective tool to establish the composition of bovine piroplasm populations in endemic regions. Microorganisms, 9(1), 21. https://doi.org/10.3390/microorganisms9010021

Ghosh, M. et al. (2018). Transformation of animal genomics by next-generation sequencing technologies: a decade of challenges and their impact on genetic architecture. Critical Reviews in Biotechnology, 38(8), 1157-1175. https://doi.org/10.1080/07388551.2018.1451819

Jiang, L. et al. (2014). Targeted resequencing of GWAS loci reveals novel genetic variants for milk production traits. BMC Genomics, 15(1), 1-9. https://doi.org/10.1186/1471-2164-15-1105

Jombart, T. et al. (2010). Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics, 11, 1-15. https://doi.org/10.1186/1471-2156-11-94

Jost, L. (2009). D vs. GST: response to Heller and Siegismund (2009) and Ryman and Leimar (2009). Molecular Ecology, 18, 2088-2091. https://doi.org/10.1111/j.1365-294X.2009.04186.x

Kanduma, E.G. et al. (2016). Multi-locus genotyping reveals absence of genetic structure in field populations of the brown ear tick (Rhipicephalus appendiculatus) in Kenya. Ticks and Tick-borne Diseases, 7, 26-35. https://doi.org/10.1016/j.ttbdis.2015.08.001

Kõks, S. et al. (2013). Sequencing and annotated analysis of the Holstein cow genome. Mammalian Genome, 24(7), 309-321. https://doi.org/10.1007/s00335-013-9464-0

Kukučková, V. et al. (2017). Genomic characterisation of Pinzgau cattle: genetic conservation and breeding perspectives. Conservation Genetics, 18(4), 893-910. https://doi.org/10.1007/s10592-017-0935-9

Kukučková, V., Moravčíková, N., & Kasarda, R. (2016). Evaluating signatures of selection through variation in linkage disequilibrium among different cattle breeds. Acta Fytotechnica et Zootechnica, 19(5).


Leroy, G. et al. (2016). Rare phenotypes in domestic animals: unique resources for multiple applications. Animal Genetics, 47(2), 141-153. https://doi.org/10.1111/age.12393

Ma, L. et al. (2015). Statistical measures of genetic differentiation of populations: Rationales, history and current states. Current Zoology, 61, 886-897. https://doi.org/10.1093/czoolo/61.5.886Makina, S.O. et al. (2014) Genetic diversity and population structure among six cattle breeds in South Africa using a whole genome SNP panel. Frontiers in Genetics, 5, 333. https://doi.org/10.3389/fgene.2014.00333

Maudet, C. et al. (2002) Genetic diversity and assignment tests among seven French cattle breeds based on microsatellite DNA analysis. Journal of Animal Science, 80(4), 942-950. https://doi.org/10.2527/2002.804942x

Mrode, R. et al. (2019). Genomic selection and use of molecular tools in breeding programs for indigenous and crossbred cattle in developing countries: Current status and future prospects. Frontiers in Genetics, 9, 694. https://doi.org/10.3389/fgene.2018.00694

Nei, M. (1972) Genetic distance between populations. The American Naturalist, 106(949), 283-292. https://doi.org/10.1086/282771

Nei, M. (1973). Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences, 70, 3321-3323. https://doi.org/10.1073/pnas.70.12.3321

Nguluma, A.S. et al. (2018) Assessment of genetic variation among four populations of Small East African goats using microsatellite markers. South African Journal of Animal Science, 48(1), 117-127. https://doi.org/10.4314/sajas.v48i1.14

Olšanská, B., et al. (2020) Genome-wide characterisation of regions under intense selection based on runs of homozygosity in Charolais cattle. Acta Fytotechnica et Zootechnica, 23(5), 350-355. https://doi.org/10.15414/afz.2020.23.mi-fpap.350-355

Öner, Y. et al. (2019) Genetic diversity and population structure of Turkish native cattle breeds. South African Journal of Animal Science, 49(4), 628-635. https://doi.org/10.4314/sajas.v49i4.4

Orozco-terWengel, P. et al. (2015) Revisiting demographic processes in cattle with genome-wide population genetic analysis. Frontiers in genetics, 6(1), 191. https://doi.org/10.3389/fgene.2015.00191

Özşensoy, Y. et al. (2019) Phylogenetic relationships of native Turkish cattle breeds using microsatellite markers. Turkish Journal of Veterinary and Animal Sciences, 43(1), 23-29. https://doi.org/10.3906/vet-1805-10.

Peterson, B.K. et al. (2012) Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PloS one, 7(5), e37135. https://doi.org/10.1371/journal.pone.0037135

Pitt, D. et al. (2019) Domestication of cattle: Two or three events? Evolutionary applications, 12(1), 123-136. https://doi.org/10.1111/eva.12674

Pritchard, J.K. (2000) Inference of population structure using multilocus genotype data. Genetics, 155(2), 945-959. https://doi.org/10.1534/genetics.116.195164

Qanbari, S. (2020) On the extent of linkage disequilibrium in the genome of farm animals. Frontiers in Genetics, 10, 1304. https://doi.org/10.3389/fgene.2019.01304

Roh, H.J. et al. (2020). Estimating genetic diversity and population structure of 22 chicken breeds in Asia using microsatellite markers. Asian-Australasian Journal of Animal Sciences, 33(12), 1896. https://doi.org/10.5713/ajas.19.0958

Saravanan, K.A. et al. (2020) Selection signatures in livestock genome: A review of concepts, approaches and applications. Livestock Science, 241, 104257. https://doi.org/10.1016/j.livsci.2020.104257

Sharma, R. et al. (2015) Genetic diversity and relationship of Indian cattle inferred from microsatellite and mitochondrial DNA markers. BMC genetics, 16(1), 1-12. https://doi.org/10.1186/s12863-015-0221-0

Slatkin, M. (1995). A measure of population subdivision based on microsatellite allele frequencies. Genetics, 139, 457-462. https://doi.org/10.1093/genetics/139.1.457

van der Westhuizen, L. et al. (2020) Genetic variability and relationships in nine South African cattle breeds using microsatellite markers. Tropical Animal Health and Production, 52(1), 177-184. https://doi.org/10.1007/s11250-019-02003-z

van Marle-Köster, E. et al. (2013). A review of genomic selection-Implications for the South African beef and dairy cattle industries. South African Journal of Animal Science, 43(1), 1-17. https://doi.org/10.4314/sajas.v43i1.1

Wang, J. (2012). On the measurements of genetic differentiation among populations. Genetics Research, 94, 275-289. https://doi.org/10.1017/S0016672312000481

Weldenegodguad, M. et al. (2019). Whole-genome sequencing of three native cattle breeds originating from the northernmost cattle farming regions. Frontiers in Genetics, 9, 728. https://doi.org/10.3389/fgene.2018.00728

Yilmaz, O., et al. (2012) The domestic livestock resources of Turkey: cattle local breeds and types and their conservation status. Animal Genetic Resources, 50, 65-73. https://doi.org/10.1017/S2078633612000033

Zhang, Y. (2020) Population structure, and selection signatures underlying high-altitude adaptation inferred from genome-wide copy number variations in Chinese indigenous cattle. Frontiers in genetics, 10, 1404. https://doi.org/10.3389/fgene.2019.01404






Animal Science