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Sermyagin A.A., Ignatieva L.P., Lashneva I.A., Kositsin A.A., Kositsina O.V., Abdelmanova A.S., Zinovieva N.A. Using of infrared high-performance spectrometry data for genome-wide associations study of fatty acid composition and milk components in dairy cattle (Bos taurus). Sel'skokhozyaistvennaya Biologiya [Agricultural Biology], 2022, Vol. 57, № 6, p. 1083-1100.
(how to cite this article)

doi: 10.15389/agrobiology.2022.6.1083eng

UDC: 636.2:637.043:577.21

Acknowledgements:
Supported financially by Russian Science Foundation, project No. 21-76-20046

 

USING OF INFRARED HIGH-PERFORMANCE SPECTROMETRY DATA FOR GENOME-WIDE ASSOCIATIONS STUDY OF FATTY ACID COMPOSITION AND MILK COMPONENTS IN DAIRY CATTLE (Bos taurus)

A.A. Sermyagin✉, L.P. Ignatieva, I.A. Lashneva, A.A. Kositsin,
O.V. Kositsina, A.S. Abdelmanova, N.A. Zinovieva

Ernst Federal Research Center for Animal Husbandry, 60, pos. Dubrovitsy, Podolsk District, Moscow Province, 142132 Russia, e-mail alex_sermyagin85@mail.ru (✉ corresponding author), ignatieva-lp@mail.ru, lashnevaira@gmail.com, ksicins@gmail.com, ok.kositsina@mail.ru, preevetic@mail.ru, n_zinovieva@mail.ru

ORCID:
Sermyagin A.A. orcid.org/0000-0002-1799-6014
Kositsina O.V. orcid.org/0000-0002-3637-4202
Ignatieva L.P. orcid.org/0000-0003-2625-6912
Abdelmanova A.S. orcid.org/0000-0003-4752-0727
Lashneva I.A. orcid.org/0000-0009-4276-8782
Zinovieva N.A. orcid.org/0000-0003-4017-6863
Kositsin A.A. orcid.org/0000-0001-8484-4902

Received September 30, 2022

Milk fat percentage is highly variabile and depends on environmental conditions which include feeding and farm technology, and on genetic factors such as breed and genotype features. The content of fatty acids (FA) is a biomarker for the physiological state of animals and a parameter of raw milk suitability for processing (yield of cheese, butter and cream). FA profile of mild in terms of C number, the chain length and saturation degree differs between individuals and at the population level. Therefore, the study of genetic and genomic variability of milk production traits to improve the efficiency of animal selection remains relevant. This study aimed at searching for genome-wide associations and polymorphisms in genes involved in milk fatty acid production. In the study, infrared spectrometry was used as an accurate and rapid method to analyze milk composition. Population variability of milk fatty acid profiles was studied using 36982 milk samples from Holsteinized Black-and-White and Holstein cows of 14 breeding herds from the Moscow region in 2017-2018. The heritability (h2) and correlation (rg) coefficients for cows’ milk components were calculated using REML (residual maximum likelihood) method with BLUPF90 family software. SNPs were detected for a dataset of Holsteinized Black-and-White cows from an experimental herd (the breeding farm Ladozhsky, branch of Ernst Federal Research Center for Animal Husbandry, Krasnodar Territory, 2020-2021). Milk composition was determined using an infrared spectroscopy-based automatic MilkoScan 7 DC analyzer (FOSS, Denmark). A group of 144 cows subjected to phenotyping for fatty acids and milk components were individually genotyped (Bovine GGP 150K biochip, Neogen, USA). Plink 1.9 software was applied to control genotyping quality (110884 SNPs) and to perform GWAS (genome-wide association study) analysis and multidimensional scaling (MDS). Searching genes by identified significant polymorphisms was performed using the bovine genome assembly Bos taurus UMD 3.1.1 (https://www.ncbi.nlm.nih.gov/assembly/) and the Ensembl genome browser. QTL annotation was carried out using the Animal QTLdb database. In general, milk fatty acids showed a heritability level that ranged from low to moderate, varying from h2 = 0.018 for polyunsaturated fatty acids to h2 = 0.125 for medium-chain FAs, h2 = 0.155 for long-chain FAs, h2 = 0.155 for myristic acid, h2 = 0.176 for monounsaturated FAs, and h2 = 0.196 for oleic acid. Visualizing experimental cows’ population structure by multidimensional scaling showed a moderate range of variability (PC1 = 7.82 %, PC2 = 4.65 %). For myristic and palmitic acids, common QTL clusters are identified on BTA5, BTA10, BTA14, BTA18, and BTA27. For stearic and oleic acids (as members of the long-chain FA family), similar location of QTLs is found on BTA9, BTA10, BTA11, BTA14, BTA17, BTA18, BTA19, BTA20, and BTA29. For short- and medium-chain FAs, there are associations revealed on BTA1, BTA5, BTA10, BTA11, BTA14, BTA18, BTA19, and BTA24. For long-chain FAs, QTLs are detected on BTA6, BTA7, BTA9, BTA10, BTA11, BTA17, BTA18, and BTA29. For short- and medium-chain FAs, saturated FAs, C14:0, C16:0, C18:0 and C18:1, the genes CACNA1C, GCH1, ATG14, KCNH5, PRKCE, CTNNA2, CYHR1, VPS28, DGAT1, ZC3H3, RHPN1, TSNARE1 are identified which form QTLs on BTA10, BTA11 and BTA14. Short- and medium-chain FAs, myristic and palmitic acids and saturated FAs show associations with polymorphisms in the MED12L, EPHB1, GRIN2B, PRMT8, ERC1, PELI2,ARHGAP39, MROH1, MAF1, GSDMD, and LY6D genes. For long-chain, monounsaturated fatty acids, stearic and oleic acids, there are significant associations with genesRPS6KA2, CPQ, CPE, FTO, FAT3, and LUZP2 which may be valuable for genetic improvement of dairy cattle. Continued study of the inheritance of cows’ milk fatty acids and other components is necessary to develop a strategy for breeding dairy cattle with a better fatty acid profile and milk composition.

Keywords: cow, fatty acids, milk components, heritability, GWAS, SNP, QTL, genes.

 

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