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Selionova M.I., Trukhachev V.I., Aybazov A-M.M., Stolpovsky Yu.A., Zinovieva N.A. GENETIC MARKERS OF GOATS (review). Sel'skokhozyaistvennaya Biologiya [Agricultural Biology], 2021, Vol. 56, № 6, p.1031-1048.
(how to cite this article)

doi: 10.15389/agrobiology.2021.6.1031eng

UDC: 636.39:575.17

Acknowledgements:
Supported financially by Russian Science Foundation (project No. 19-76-20006, analysis of SNP-markers and search for loci under selection pressure in the Karachaev goat genome; No. 21-76-20008, analysis of microsatellite and DNA markers of goat productivity)

 

GENETIC MARKERS OF GOATS (review)

M.I. Selionova1 ✉, V.I. Trukhachev1, A-M.M. Aybazov1,
Yu.A. Stolpovsky2, N.A. Zinovieva3

1Russian State Agrarian University — Timiryazev Moscow Agricultural Academy, 49, ul. Timiryazevskaya, Moscow, 127550 Russia, e-mail m_selin@mail.ru (✉ corresponding author), rector@rgau-msha.ru, velikii-1@yandex.ru;
2Vavilov Institute of General Genetics RAS, 3, ul. Gubkina, Moscow, 119333 Russia, e-mail stolpovsky@mail.ru;
3Ernst Federal Science Center for Animal Husbandry, 60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail n_zinovieva@mail.ru

ORCID:
Selionova M.I. orcid.org/0000-0002-9501-8080
Stolpovsky Yu.A. orcid.org/0000-0003-2537-1900
Trukhachev V.I. orcid.org/0000-0002-4650-1893
Zinovieva N.A. orcid.org/0000-0002-6926-2055
Aybazov A-M.M. orcid.org/0000-0002-3704-3210

Received October 1, 2021

 

Goat biodiversity comprises 635 breeds from in 170 countries (https://www.fao.org/dad-is). Wide geographical distribution and positive dynamics of goat populations in recent decades are due to high adaptability to various climatic conditions and the uniqueness of goat products (I.N. Skidan et al., 2015; A.I. Erokhin et al., 2020). DNA microsatellite markers have been widely used to study genetic differentiation of goat breeds and populations in many countries (C. Wei et al., 2014; G. Mekuriaw et al., 2016). Insignificant genetic distances (FST 0.033-0.069) between goat breeds bred in Europe confirm the frequent exchange of the gene pool between them. A more significant genetic differentiation (FST 0.134-0.183) is characteristic of breeds from East and Southeast Asia due to the ecological and geographical features and the remoteness of their habitats (K. Nomura et al., 2012; G. Wang et al., 2017; P. Azhar et al., 2018). The CSN1S1, CSN1S2, CSN2, and BLG gene polymorphisms are of most interest in dairy goat breeding (N. Silanikove et al., 2010; Vorozhko I.V. et al., 2016). Eighteen allelic variants have been described in the CSN1S1 gene, eight in CSN2, and 16 in CSN3 (S. Ollier et al., 2008; T.G. Devold et al., 2010). The CSN1S1AA association with more protein in milk and less total lipids and medium chain fatty acids has been found (Y. Chilliard et al., 2006; D. Marletta et al., 2007). Goats with BLGAB genotype have longer lactation period, produce more milk with higher fat and protein contents (A.S. Shuvarikov et al., 2019). The sequencing of the goat genome (the AdaptMap project) and the development of the 52K SNP BeadChipGoat chip has expanded the search for genome regions involved in breeding (G. Tosser-Klopp et al., 2014; A. Stella et al., 2018). There is evidence that the RARA, STAT, PTX3, IL6, IL8, and DGAT1 genes are linked to dairy performance traits (P. Martin et al., 2018; D. Ilie et al., 2018). At the genomic level, the MC1R, ASIP and KIT are associated with wool fiber coloration, FGF5, EPAS1 and NOXA1 with wool productivity of goats and their high-altitude adaptation (X. Wang et al., 2016; S. Song et al., 2016; Guo J. et al., 2018). Thus, the evaluation of genetic relationships between breeds, the search for genes associated with economically important traits are promising for use in breeding programs and further development of goat breeding (L.F. Brito et al., 2016; S. Desire, 2016; A. Molina et al., 2018; T.E. Deniskova et al., 2020). However, despite certain achievements, until now, loci associated with economically important traits in goats, such as breeding characteristics, the level of down, wool and milk productivity, as well as determining resistance to diseases, remain largely unknown.

Keywords: goats, microsatellites, breeds, productivity, genetic differentiation, genetic markers, GWAS.

 

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