Genetic polymorphisms of leptin and leptin receptor genes in relation with production and reproduction traits in cattle.
Author(s) -
Anna Trakovická,
Nina Moravčíková,
Radovan Kasarda
Publication year - 1970
Publication title -
acta biochimica polonica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.452
H-Index - 78
eISSN - 1734-154X
pISSN - 0001-527X
DOI - 10.18388/abp.2013_2058
Subject(s) - leptin , biology , reproduction , leptin receptor , ice calving , single nucleotide polymorphism , population , candidate gene , zoology , genetics , genotype , gene , endocrinology , lactation , obesity , pregnancy , medicine , environmental health
Leptin and leptin receptor genes are considered as production traits markers in dairy or beef cattle. The aim of this study was to verify the associations of polymorphisms in bovine LEP and LEPR genes with production and reproduction traits in Slovak Spotted and Pinzgau cows. Long-life production was evaluated: milk, protein, and fat yield and reproduction traits: age at first calving, calving interval, days open, and insemination interval. In total, 296 blood samples of Slovak Spotted and 85 hair roots samples of Pinzgau cows were analyzed. In order to detect LEP/Sau3AI (BTA 4, inron 2) and LEPR/T945M (BTA 3, exon 20) genotypes PCR-RFLP method was used. In Slovak Spotted and Pinzgau cows allele frequencies were 0.838/0.162 and 0.694/0.306 for A and B LEP variants, and 0.954/0.046 and 0.912/0.088 for C and T LEPR variants, respectively. For testing the associations between SNPs LEP/Sau3AI and LEPR/T945M and evaluated traits, the General Linear Model procedure in SAS Software was used. Statistical analysis showed that SNP LEP/Sau3AI significantly affected milk, protein and fat yield (P<0.05), and age at first calving (P<0.01) in analyzed population of cows. Statistically, SNP LEPR/T945M affected significantly calving interval (P<0.01) only. Results of our study suggest that especially leptin is a candidate gene, which influences mainly milk production traits and might be implemented in breeding strategies to improve the production performance of both analyzed cattle breeds.
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