Tag Archives: polymorphisms

1001-1015 I. Trapina, S. Plavina, N. Krasņevska, J. Paramonovs, D. Kairisa and N. Paramonova
IGF1 and IGF2 gene polymorphisms are associated with the feed efficiency of fattened lambs in Latvian sheep breads
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IGF1 and IGF2 gene polymorphisms are associated with the feed efficiency of fattened lambs in Latvian sheep breads

I. Trapina¹*, S. Plavina¹, N. Krasņevska¹, J. Paramonovs¹, D. Kairisa² and N. Paramonova¹

¹Genomics and Bioinformatics, Institute of Biology of the University of Latvia, Jelgava str. 3, LV-1004, Riga, Latvia
²Institute of Agrobiotechnology, Faculty of Agriculture, Latvian University of Life Sciences and Technologies, Liela Street 2, LV-3001, Jelgava, Latvia
*Correspondence: ilva.trapina@lu.lv

Abstract:

Feed efficiency is an economically important indicator in sheep farming. The most effective technology for selecting the best feed-efficient lambs for breeding is marker association selection of genetic variations in the sheep genome as potential biomarkers. In tissue growth and differentiation, insulin-like growth factors (IGFs) play a major role: IGF1 mediates the effects of growth hormone, and IGF2 is a growth regulator, regulating skeletal muscle growth. The study aims to find possible molecular markers for feed efficiency indicators in IGF1 and IGF2 genes for Latvian sheep breeds. The exonic regions of the IGF1 and IGF2 genes were sequenced for the first time in the genomic DNA of 76 controlled, intensively fattened lambs, to search for possible genetic biomarkers. Seven polymorphic loci in the IGF1 gene and sixteen in the IGF2 gene were detected. Statistically significant associations of the IGF1 SNP rs600896367 were found with residual indicators: Residual feed intake, Residual weight gain (RWG), and Residual intake and body weight gain (RIG), and with feed efficiency and feed conversion ratio in the overall group of samples. Additionally, IGF2 SNPs New_7 and rs429576107 exhibited associations with RWG and RIG specifically in the Latvian dark-head sheep group. On average, effect of the IGF1 SNP on associated feed efficiency residuals is 3.9%, with the most pronounced impact observed in RFI. In contrast, the influence of IGF2 SNPs is comparatively lower. Our results indicate that rs600896367 and New7/rs429576107 are potential molecular markers for marker-assisted selection in sheep breeding for residual feed efficiency indicators.

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900-909 D. Smiltina and Z. Grislis
Molecular genetics analysis of milk protein gene polymorphism of dairy cows and breeding bulls in Latvia
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Molecular genetics analysis of milk protein gene polymorphism of dairy cows and breeding bulls in Latvia

D. Smiltina* and Z. Grislis

Latvia University of Life Sciences and Technologies, Faculty of Agriculture, Institute of Agrobiotechnology, Liela street 2, LV-3001 Jelgava, Latvia
*Correspondence: dace.smiltina@llu.lv

Abstract:

Milk protein is the most valuable component of milk from a dietary point of view. More than 95% of ruminants’ milk proteins are coded by six structural genes: two whey proteins (α – lactalbumin and β – lactoglobulin) and four caseins (αS1 – and αS2 – caseins, β – casein, κ – casein). The object of the research was the genetic polymorphisms of milk protein genes in populations of cows and breeding bulls of milk producing breeds in Latvia. The aim was to promote cow breeding in Latvia by developing and testing molecular genetics analyses for future quantity and quality analysis of the dairy cows’ population in Latvia, based on the research of genes encoding milk protein polymorphism. In methodology the molecular markers were chosen which would be suitable for characterization of polymorphism of five milk protein genes in the population of dairy cows reared in Latvia. As a genetic method chosen the Restriction Fragment Length Polymorphism (RFLP) method and most analysed alleles of milk proteins. Using data of 719 DNA samples of dairy cows, the analysis of Latvian cows’ population was carried out through six SNP of five milk protein genes: CSN1S1 c.–175A > G, CSN2 – c.4451A > C, CSN3 c.11625C > T and c.11661A > C, LAA c.15A > G and LGB c.3106T > C. The results of PCR-RFLP analysis showed, as it was expected, that all genotypes were found in the populations.

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