Article Details: Received: 2021-03-25 | Accepted: 2021-04-16 | Available online: 2021-06-30

https://doi.org/10.15414/afz.2021.24.02.161-166

The use of single nucleotide polymorphism (SNP) data had become commonplace in animal breeding activities and management of livestock populations. The cost-effective genotyping allowed us to assess entire populations and learn about their history on the genomic level. This paper reviews several approaches that are commonly used in the context of genomic diversity in livestock, such as the linkage disequilibrium (LD) and assessment of autozygosity via runs of homozygosity (ROH). Both methods, however, are being used to assess the impact of natural or artificial selection on the livestock genome. Apart from these selection signatures, both the LD and ROH are used to assess the effective population size (Ne), which likewise, serves as a diversity management tool and describes the historical events in populations.

Keywords: livestock, genomics, SNP, selection signatures, diversity

References

Ablondi, M. et al. (2020). Genetic Diversity and Signatures of Selection in a Native Italian Horse Breed Based on SNP Data. Animals, 10(6), 1005. https://doi.org/10.3390/ani10061005

Almeida, O.A.C. et al. (2019). Identification of selection signatures involved in performance traits in a paternal broiler line. BMC Genomics, 20(1), 449. https://doi.org/10.1186/s12864-019-5811-1

Ardlie, K.G., Kruglyak, L. & Seielstad, M. (2002). Patterns of linkage disequilibrium in the human genome. Nature Reviews Genetics, 3(4), 299–309. https://doi.org/10.1038/nrg777

Baes, C. F. et al. (2019). Symposium review: The genomic architecture of inbreeding: How homozygosity affects health and performance. Journal of Dairy Science, 102(3), 2807–2817. https://doi.org/10.3168/jds.2018-15520

Barbato, M. et al. (2015). SNeP: A tool to estimate trends in recent effective population size trajectories using genomewide SNP data. Frontiers in Genetics, 6. https://doi.org/10.3389/fgene.2015.00109

Bradley, D. et al. (2004). Secondary guidelines for development of national farm animal genetic resources management plans. Food and Agricultural Organization of United Nations (FAO), Roma.

Brüniche-Olsen, A. et al. (2018). Runs of homozygosity have utility in mammalian conservation and evolutionary studies. Conservation Genetics, 19(6), 1295–1307. https://doi.org/10.1007/s10592-018-1099-y

Ceballos, F. C. et al. (2018). Runs of homozygosity: Windows into population history and trait architecture. Nature Reviews Genetics, 19(4), 220–234. https://doi.org/10.1038/nrg.2017.109

Curik, I., Ferenčaković, M. & Sölkner, J. (2017). Genomic dissection of inbreeding depression: A gate to new opportunities. Revista Brasileira de Zootecnia, 46(9), 773–782. https://doi.org/10.1590/s1806-92902017000900010

Deng, T. et al. (2019). Genome-Wide SNP Data Revealed the Extent of Linkage Disequilibrium, Persistence of Phase and Effective Population Size in Purebred and Crossbred Buffalo Populations. Frontiers in Genetics, 9. https://doi.org/10.3389/fgene.2018.00688

Fariello, M.I. et al. (2017). Accounting for linkage disequilibrium in genome scans for selection without individual genotypes: The local score approach. Molecular Ecology, 26(14), 3700–3714. https://doi.org/10.1111/mec.14141

Ferenčaković, M., Sölkner, J. & Curik, I. (2013). Estimating autozygosity from high-throughput information: Effects of SNP density and genotyping errors. Genetics Selection Evolution, 45(1), 42. https://doi.org/10.1186/1297-9686-45-42

Frankham, R., Bradshaw, C.J.A. & Brook, B.W. (2014). Genetics in conservation management: Revised recommendations for the 50/500 rules, Red List criteria and population viability analyses. Biological Conservation, 170, 56–63. https://doi.org/10.1016/j.biocon.2013.12.036

Gazal, S. (2017). Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nature Genetics, 49(10), 14.

Georges, M., Charlier, C. & Hayes, B. (2019). Harnessing genomic information for livestock improvement. Nature Reviews Genetics, 20(3), 135–156. https://doi.org/10.1038/s41576-018-0082-2

Granado-Tajada, I. et al. (2020). Inbreeding, effective population size, and coancestry in the Latxa dairy sheep breed. Journal of Dairy Science, 103(6), 5215–5226. https://doi.org/10.3168/jds.2019-17743

Grilz‐Seger, G. et al. (2019). Analysis of ROH patterns in the Noriker horse breed reveals signatures of selection for coat color and body size. Animal Genetics, 50(4), 334–346. https://doi.org/10.1111/age.12797

Hayes, B. J. et al. (2003). Novel Multilocus Measure of Linkage Disequilibrium to Estimate Past Effective Population Size. Genome Research, 13(4), 635–643. https://doi.org/10.1101/gr.387103

Hickey, J. M. et al. (2017). Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery. Nature Genetics, 49(9), 1297–1303. https://doi.org/10.1038/ng.3920

Hill, W.G. & Robertson, A. (1968). Linkage disequilibrium in finite populations. TAG. Theoretical and Applied Genetics. Theoretische Und Angewandte Genetik, 38(6), 226–231. https://doi.org/10.1007/BF01245622

Jasielczuk, I. et al. (2020). Comparison of linkage disequilibrium, effective population size and haplotype blocks in Polish Landrace and Polish native pig populations. Livestock Science, 231, 103887. https://doi.org/10.1016/j.livsci.2019.103887

Karimi, K., Esmailizadeh Koshkoiyeh, A. & Gondro, C. (2015). Comparison of linkage disequilibrium levels in Iranian indigenous cattle using whole genome SNPs data. Journal of Animal Science and Technology, 57. https://doi.org/10.1186/s40781-015-0080-2

Kasarda, R. et al. (2015). Genome-wide selection signatures in Pinzgau cattle. Potravinarstvo Slovak Journal of Food Sciences, 9(1), 268–274. https://doi.org/10.5219/478

Kasarda, R., Jamborová, Ľ. & Moravčíková N. (2020). Genetic diversity and production potential of animal food resources. Acta fytotechnica et zootechnica, 23(2), 102–108. https://doi.org/10.15414/afz.2020.23.02.102-108

Khatkar, M. S. et al. (2008). Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC Genomics, 9(1), 187. https://doi.org/10.1186/1471-2164-9-187

Kijas, J. W. et al. (2014). Linkage disequilibrium over short physical distances measured in sheep using a high-density SNP chip. Animal Genetics, 45(5), 754–757. https://doi.org/10.1111/age.12197

Kim, E.-S. et al. (2013). Effect of Artificial Selection on Runs of Homozygosity in U.S. Holstein Cattle. PLoS ONE, 8(11), e80813. https://doi.org/10.1371/journal.pone.0080813

Lu, D. et al. (2012). Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle. Frontiers in Genetics, 3. https://doi.org/10.3389/fgene.2012.00152

Makanjuola, B.O. et al. (2020). Effect of genomic selection on rate of inbreeding and coancestry and effective population size of Holstein and Jersey cattle populations. Journal of Dairy Science, 103(6), 5183–5199. https://doi.org/10.3168/jds.2019-18013

Mastrangelo, S. et al. (2014). Genome wide linkage disequilibrium and genetic structure in Sicilian dairy sheep breeds. BMC Genetics, 15(1), 108. https://doi.org/10.1186/s12863-014-0108-5

McHugo, G.P. et al. (2019). A Population Genomics Analysis of the Native Irish Galway Sheep Breed. Frontiers in Genetics, 10. https://doi.org/10.3389/fgene.2019.00927

McKay, S.D. et al. (2007). Whole genome linkage disequilibrium maps in cattle. BMC Genetics, 8(1), 74. https://doi.org/10.1186/1471-2156-8-74

McQuillan, R. et al. (2008). Runs of Homozygosity in European Populations. The American Journal of Human Genetics, 83(3), 359–372. https://doi.org/10.1016/j.ajhg.2008.08.007 

Meuwissen, T.H.E., Hayes, B.J. & Goddard, M.E. (2001). Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps. Genetics, 157(4), 1819–1829.

Mills, M.C. & Rahal, C. (2019). A scientometric review of genome-wide association studies. Communications Biology, 2(1), 1–11. https://doi.org/10.1038/s42003-018-0261-x

Moravčíková, N. et al. (2019). Analysis of selection signatures in the beef cattle genome. Czech Journal of Animal Science, 64(12), 491–503. https://doi.org/10.17221/226/2019-CJAS

Moravčíková, N. & Kasarda, R. (2020). Use of High-density SNP analyses to develop a long-term strategy for conventional populations to prevent loss of diversity – review. Acta fytotechnica et zootechnica, 23(4), 236–240. https://doi.org/10.15414/afz.2020.23.04.236-240

Otto, S.P. (2000). Detecting the form of selection from DNA sequence data. Trends in Genetics, 16(12), 526–529. https://doi.org/10.1016/S0168-9525(00)02141-7

Pérez O’Brien, A.M. et al. (2014). Linkage disequilibrium levels in Bos indicus and Bos taurus cattle using medium and high density SNP chip data and different minor allele frequency distributions. Livestock Science, 166, 121–132. https://doi.org/10.1016/j.livsci.2014.05.007

Peripolli, E. et al. (2016). Runs of homozygosity: Current knowledge and applications in livestock. Animal Genetics. https://doi.org/10.1111/age.12526

Porto-Neto, L.R., Kijas, J.W. & Reverter, A. (2014). The extent of linkage disequilibrium in beef cattle breeds using highdensity SNP genotypes. Genetics, Selection, Evolution: GSE, 46, 22. https://doi.org/10.1186/1297-9686-46-22

Qanbari, S. (2020). On the Extent of Linkage Disequilibrium in the Genome of Farm Animals. Frontiers in Genetics, 10. https://doi.org/10.3389/fgene.2019.01304

Rebelato, A.B. & Caetano, A.R. (2018). Runs of homozygosity for autozygosity estimation and genomic analysis in production animals. Pesquisa Agropecuária Brasileira, 53(9), 975–984. https://doi.org/10.1590/s0100-204x2018000900001

Reich, D.E. et al. (2001). Linkage disequilibrium in the human genome. Nature, 411(6834), 199–204. https://doi.org/10.1038/35075590

Rodríguez-Ramilo, S.T., Elsen, J.M. & Legarra, A. (2019). Inbreeding and effective population size in French dairy sheep: Comparison between genomic and pedigree estimates. Journal of Dairy Science, 102(5), 4227–4237. https://doi.org/10.3168/jds.2018-15405

Sabeti, P.C. et al. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature, 419(6909), 832–837. https://doi.org/10.1038/nature01140

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

Schiavo, G. et al. (2020). Runs of homozygosity islands in Italian cosmopolitan and autochthonous pig breeds identify selection signatures in the porcine genome. Livestock Science, 240, 104219. https://doi.org/10.1016/j.livsci.2020.104219

Schmid, M. & Bennewitz, J. (2017). Invited review: Genomewide association analysis for quantitative traits in livestock  – a  selective review of statistical models and experimental designs. Archives Animal Breeding, 60(3), 335–346. https://doi.org/10.5194/aab-60-335-2017

Signer‐Hasler, H. et al. (2019). Runs of homozygosity and signatures of selection: A comparison among eight local Swiss sheep breeds. Animal Genetics, 50(5), 512–525. https://doi.org/10.1111/age.12828

Sved, J.A. & Hill, W.G. (2018). One Hundred Years of Linkage Disequilibrium. Genetics, 209(3), 629–636. https://doi.org/10.1534/genetics.118.300642

Tam, V. et al. (2019). Benefits and limitations of genomewide association studies. Nature Reviews Genetics, 20(8), 467– 484. https://doi.org/10.1038/s41576-019-0127-1

Tenesa, A. et al. (2007). Recent human effective population size estimated from linkage disequilibrium. Genome Research, 17(4), 520–526. https://doi.org/10.1101/gr.6023607

Uimari, P. & Tapio, M. (2011). Extent of linkage disequilibrium and effective population size in Finnish Landrace and Finnish Yorkshire pig breeds. Journal of Animal Science, 89(3), 609–614. https://doi.org/10.2527/jas.2010-3249

Utsunomiya, Y.T. et al. (2013). Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods. PLOS ONE, 8(5), e64280. https://doi.org/10.1371/journal.pone.0064280

Voight, B.F. et al. (2006). A Map of Recent Positive Selection in the Human Genome. PLOS Biology, 4(3), e72. https://doi.org/10.1371/journal.pbio.0040072

Waples, R.S. (2016). Making sense of genetic estimates of effective population size. Molecular Ecology, 25(19), 4689–4691. https://doi.org/10.1111/mec.13814

Wright, S. (1931). Evolution in Mendelian Populations. Genetics, 16(2), 97–159.