Ecological geneticsEcological genetics1811-09322411-9202Eco-Vector4640510.17816/ecogen46405Research ArticleAssessment of variability of egg production traits based on analysis of SNP markers and search for traces of selection in the genome of Russian white chickensMitrofanovaOlga V.<p>candidate of biological sciences, scientific secretary</p>mo1969@mail.ruhttps://orcid.org/0000-0003-4702-2736DementievaNatalia V.<p>PhD, Main Researcher, Laboratory of Molecular Genetics</p>dementevan@mail.ruhttps://orcid.org/0000-0003-0210-9344FedorovaElena S.<p>PhD, Senior Researcher, Department of Genetics, Breeding and Conservation of Poultry Genetic Resources</p>Fedorova816@mail.ruhttps://orcid.org/0000-0002-1618-6271PozovnikovaMarina V.<p>PhD, Senior Researcher, Laboratory of Molecular Genetics</p>pozovnikova@gmail.comhttps://orcid.org/0000-0002-8658-2026TyshchenkoValentina I.<p>PhD, Senior Researcher, Laboratory of Molecular Genetics</p>tinatvi@mail.ruhttps://orcid.org/0000-0003-4964-9938ShcherbakovYuriy S.<p>Junior Researcher, Laboratory of Molecular Genetics</p>yura.10.08.94.94@mail.ruhttps://orcid.org/0000-0001-6434-6287PlemyashovKirill V.<p>Dr Sci., Main Researcher, Reproduction Department</p>kirill060674@mail.ruhttps://orcid.org/0000-0002-3658-5886Russian Research Institute of Farm Animal Genetics and Breeding – Branch of the L.K. Ernst Federal Science Center for Animal HusbandryRussian Research Institute of Farm Animal Genetics and Breeding - Branch of the L.K. Ernst Federal Science Center for Animal Husbandry121220201844234320510202017112020Copyright © 2021, Mitrofanova O., Dementieva N., Fedorova E.S., Pozovnikova M., Tyshchenko V., Scherbakov Y., Plemyashov K.2021<p><strong>Objective.</strong> To assess the variability of egg production traits for nine SNPs, to search for traces of selection in the genome of Russian white chickens based on ROH patterns.</p>
<p><strong>Methods.</strong> The material for the study was DNA isolated from the blood of Russian white chickens (<em>n</em> = 141). Nine SNPs associated with egg production at <em>p</em> 5.16 10<sup>5</sup> according to GWAS data were selected for analysis. The frequencies of alleles and genotypes, the relationship between genotypes and characteristics of egg production were calculated, and ROH patterns were identified.</p>
<p><strong>Results.</strong> Significant differences between genotypes were found in terms of age of laying the first egg (<em>p</em> 0.005) and egg weight (<em>p</em> 0.05). The genomic regions surrounding the target SNPs were analyzed according to the distribution of homozygous regions in them.</p>
<p><strong>Conclusions.</strong> The substitutions rs317565390 and rs16625488 located in the 4.810.2 Mb region on chromosome 8 showed polymorphism, despite the fact that homozygous loci in this region of the genome are found in 58% of animals. For most SNPs, the prevalence of the frequency of one of the alleles was observed. As a cluster of increased selection pressure, a chick genome region in the 4.810.2 Mb region on chromosome 8 was identified.</p>Gallus gallusage of first egg layingegg weightlocal breedsROH patternspolymorphic lociSNPGallus gallusвозраст снесения первого яйцамасса яйцалокальные породыROH-паттерныполиморфные локусыSNP[Wolc A, Arango J, Settar P, et al. Evaluation of egg production in layers using random regression models. Poult Sci. 2011;90(1):30-34. https://doi.org/10.3382/ps.2010-01118.][Meuwissen TH, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps. Genetics. 2001;157(4): 1819-1829.][Muir WM. Comparison of genomic and traditional BLUP-estimated breeding value accuracy and selection response under alternative trait and genomic parameters. J Anim Breed Genet. 2007;124(6):342-355. https://doi.org/10.1111/j.1439-0388.2007.00700.x.][Mohammadifar A, Mohammadabadi M. Melanocortin-3 receptor (MC3R) gene association with growth and egg production traits in Fars indigenous chicken. Malays Appl Biol. 2018;47(3):85-90.][Mohammadabadi MR, Nikbakhti M, Mirzaee HR, et al. Genetic variability in three native Iranian chicken populations of the Khorasan province based on microsatellite markers. Russ J Genet. 2010;46(4):505-509. https://doi.org/10.1134/S1022795410040198.][Atzmon G, Blum S, Feldman M, et al. QTLs detected in a multigenerational resource chicken population. J Hered. 2008;99(5):528-538. https://doi.org/10.1093/jhered/esn030.][Goto T, Ishikawa A, Onitsuka S, et al. Mapping quantitative trait loci for egg production traits in an F2 intercross of oh-Shamo and white Leghorn chickens. Anim Genet. 2011; 42(6):634-641. https://doi.org/10.1111/j.1365-2052.2011.02190.x.][Goraga ZS, Nassar MK, Brockmann GA. Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits. Anim Genet. 2012;43(2):183-189. https://doi.org/10.1111/j.1365-2052.2011.02233.x.][Ball AD, Stapley J, Dawson DA, et al. A comparison of SNPs and microsatellites as linkage mapping markers: lessons from the zebra finch (Taeniopygia guttata). BMC Genomics. 2010;11:218. https://doi.org/10.1186/1471-2164-11-218.][Liu W, Li D, Liu J, et al. A genome-wide SNP scan reveals novel loci for egg production and quality traits in white leghorn and brown-egg dwarf layers. PLoS One. 2011;6(12): e28600. https://doi.org/10.1371/journal.pone.0028600.][Yuan J, Sun C, Dou T, et al. Identification of promising mutants associated with egg production traits revealed by genome-wide association study. PLoS One. 2015;10(10):e0140615. https://doi.org/10.1371/journal.pone.0140615.][Zhang GX, Fan QC, Wang JY, et al. Genome-wide association study on reproductive traits in Jinghai yellow chicken. Anim Reprod Sci. 2015;163:30-34. https://doi.org/10.1016/j.anireprosci.2015.09.011.][Бакоев С.Ю., Гетманцева Л.В. Методы оценки инбридинга и подписей селекции сельскохозяйственных животных на основе протяженных гомозиготных областей // Достижения науки и техники АПК. – 2019. – Т. 33. – № 11. – С. 63–68. [Bakoev SYu, Getmantseva LV. Methods for assessing inbreeding and selection signatures of farm animals based on runs of homozygosity. Achievements of science and technology in agro-industrial complex. 2019;33(11):63-68. (In Russ.)]. https://doi.org/10.24411/0235-2451-2019-11114.][Mitrofanova OV, Dementeva NV, Krutikova AA, et al. Association of polymorphic variants in MSTN, PRL, and DRD2 genes with intensity of young animal growth in Pushkin breed chickens. Cytol Gen. 2017;51(3):179-184. https://doi.org/10.3103/S0095452717030082.][Kudinov AA, Dementieva NV, Mitrofanova OV, et al. Genome-wide association studies targeting the yield of extraembryonic fluid and production traits in Russian White chickens. BMC Genomics. 2019;20(1):270. https://doi.org/10.1186/s12864-019-5605-5.][Luo PT, Yang RQ, Yang N. Estimation of genetic parameters for cumulative egg numbers in a broiler dam line by using a random regression model. Poult Sci. 2007;86(1):30-36. https://doi.org/10.1093/ps/86.1.30.][Venturini GC, Savegnago RP, Nunes BN, et al. Genetic parameters and principal component analysis for egg production from White Leghorn hens. Poult Sci. 2013;92(9):2283-2289. https://doi.org/10.3382/ps.2013-03123.][Qin N, Liu Q, Zhang YY, et al. Association of novel polymorphisms of forkhead box L2 and growth differentiation factor-9 genes with egg production traits in local chinese Dagu hens. Poult Sci. 2015;94(1): 88-95. https://doi.org/10.3382/ps/peu023.][Xu H, Zeng H, Luo C, et al. Genetic effects of polymorphisms in candidate genes and the QTL region on chicken age at first egg. BMC Genetics. 2011;12(1):33. https://doi.org/10.1186/1471-2156-12-33.][Johnson PA, Stephens CS, Giles JR. The domestic chicken: causes and consequences of an egg a day. Poult Sci. 2015;94(4):816-820. https://doi.org/10.3382/ps/peu083.][Sieron L, Lesiak M, Schisler I, et al. Functional and structural studies of tolloid-like 1 mutants associated with atrial-septal defect 6. Biosci Rep. 2019;39(1): BSR20180270. https://doi.org/10.1042/BSR20180270.][Yuan J, Sun C, Dou T, et al. Identification of promising mutants associated with egg production traits revealed by genome-wide association study. PLoS ONE. 2015;10(10): e0140615. https://doi.org/10.1371/journal.pone.0140615.][Sermyagin AA, Bykova OA, Loretts OG, et al. Genomic variability assess for breeding traits in holsteinizated Russian Black-and-White cattle using GWAS analysis and ROH patterns. Agricultural Biology. 2020;55(2):257-274. https://doi.org/10.15389/agrobiology.2020.2. 257eng.]