The objective of this study was to investigate the association of PKM2 gene with glycolytic potential and meat quality traits in three groups of fatteners – Landrace, Landrace×Yorkshire and (Landrace×Yorkshire)×Duroc. The present study was conducted on 243 fatteners, free of RYR1T gene, which 95 were of Landrace breed and the rest were the following crosses: 66 – Landrace×Yorkshire and 82 (Landrace×Yorkshire)×Duroc. It has been stated, that PKM2 gene (independently from the breed) was significantly associated with GP, lactate content, R1 indicator, pH and drip loss. The presence of TT genotype may lead to increase of GP and lactate content and results in low pH24 and pH144 and bigger drip loss measured 96 and 144h after the slaughter. Except for the landrace fatteners, the association of the PKM2 gene with the glycogen content has not been statistically confirmed. Statistically confirmed interaction shows, that the association of PKM2 gene with glycolytic potential and glycogen content concerns mainly the Landrace pigs. Moreover, a high (almost 89%) conformability of the genotype of PKM2 gene with the RN− phenotype, can serve as an additional argument in favour of the thesis.

Summary Low heritability of meat quality traits and the lack of their systematic registration in breeding programs have encouraged the search for single nucleotide polymorphisms (SNPs) located within genes coding the proteins involved in muscle and fat metabolism. In this report, a panel of 52 SNPs was used to find which alleles and genotypes are more/less frequent in groups of pigs differentiated by extreme value of glycolytic potential (GP) and drip loss (DL). The analysis was carried out in 52 fatteners (chosen from 246 pigs), of which 28 were Landrace and 27 Landrace x Yorkshire. Two designs were performed: I, fatteners were divided into two groups showing extreme value of GP (<125 versus >145), II, fatteners were divided into two groups showing extreme value of DL (<6.0 versus >6.0). Allele frequency differences between the phenotypic groups of extreme GL or DL were not influenced by the breed. The frequency of 52 SNPs alleles for each of group was calculated and a chi-squared test was used to estimate the significance of differences in allele frequencies between alternative groups in each experimental design. Three SNPs (DECR1, PPARGC1, MC4R) and another two (CYP21, SFRS1) showed significant differences between groups of extreme GP and DL, respectively. To exemplify and validate potential associations of candidate SNPs for GP and DL, 293 fatteners representing three commercial breeds/crosses (95 Landrace, 66 Landrace x Yorkshire and 132 Landrace x Yorkshire x Duroc were genotyped for DECR1 and CYP21 by PCR-RFLP assays. DECR1 showed significant associations with GP in Landrace and Landrace x Yorkshire x Duroc fatteners. CYP21 showed significant associations with DL in all breeds/crosses. Interestingly, the CYP21 polymorphism revealed adverse associations trend in Landrace x Yorkshire x Duroc pigs in comparison to Landrace and Landrace x Yorkshire fatteners.

Modern pig production needs new tools for fast, reliable, more effective breeding. In the present paper we present a chip containing 45 SNP (Single Nucleotide Polymorphisms) which enables the determining of 1 genetic disease (PSS-Porcine Stress Syndrome), 4 QTLs genes: PRKAG3, CAST, MC4R and ESR, which together with the remaining SNPs create a panel useful in marker-assisted selection and veterinary control. The SNPs were genotyped using the PCR-APEX (Arrayed Primer Extension) technique. Special attention is paid to evaluation of the 45 SNP chip as an alternative approach to parentage and identity control. Based on allele frequency estimations, for a sample of 88 individuals of commercial pig lines, the probabilities that a randomly chosen candidate parent would be excluded from paternity or maternity were estimated to be 99.9% when genotypes of both parents and a progeny were known, and 98% when the genotypes of only one parent and a piglet were available. The marker set presented here also reached a probability of identity in the order of 10(-16), which allows for unequivocal discrimination of animals or their products among billions of individuals. Further improvements for upcoming chip versions were also considered.

The V54L missense mutation within the DECR1 gene, which encodes a mitochondrial 2,4-dienoyl-CoA reductase, was investigated to determine whether this polymorphism is associated with growth rate (daily gains), meat content and selection index in Polish Landrace boars kept under uniform feeding and environmental conditions (one herd). The genotype of 334 boars was determined by PCR-RFLP, identifying 112, 162, and 60 boars hearing genotypes CC, CG and GG, respectively. Statistical analysis was carried out by the General Linear Model (GLM) procedure, including fixed effects of DECR1 genotype, sire, and birth season. Significant differences (P<0.01) between boars with CC and GG genotypes were found. Boars with genotype CC showed the highest daily gains (860.7 g +/- 46.3), in comparison with boars bearing the GG genotype (841.7 g +/- 53.6). The current findings support the hypothesis that DECR1 V54L polymorphism is a promising marker of growth rate in pigs.

MilkProtChip is oligonucleotide microarray allowing bovine genotyping based on single nucleotide polymorphisms (SNPs) in genes influencing milk protein biosynthesis. A total of 71 SNPs in 42 genes were selected as associated with milk protein biosynthesis. Genotyping of about 300 animals of Polish Black-and-White cattle showed that SNPs in acyl-CoA:1,2-diacylglycerol O-transferase (DGAT1), lactoferrin (LTF), casein kappa (CSN3) and growth hormone receptor (GHR) genes were associated with several milk performance traits. Analysis of correlations between SNPs and milk production traits showed that SNPs in single genes rarely affect the investigated traits. Only 4 of 42 investigated single SNPs had impact on milk production traits while 22 combinations of paired SNPs in these genes had impact. Positive effect SNP combinations in two genes can be a result of additive effect on these SNPs on the same traits or effect of genes interaction. The MilkBovExp chip representing 90 genes encoding transcription factors expressed in the bovine mammary gland and/or involved in mammary gland signaling pathways was designed for further investigation of impact of gene expression and/or its encoded products on milk traits performance.

A new single nucleotide polymorphism was revealed using PCR–SSCP and sequencing methods within the bovine prolactin distal promoter region described as a functional enhancer. The A→G transition at position −1043 abolishes the recognition site for Hsp92II restriction endonuclease, allowing for PCR–RFLP genotyping. The application of real-time PCR revealed that the prolactin gene expression level in the pituitary was higher in cattle with the AA genotype than in those with the GG genotype. EMSA analysis, however, showed increased nuclear protein binding to the sequence variant with G, suggesting a possible inhibition event, in which the transcription factors Pit1, Oct1, and YY1 could be involved.

An oligonucleotide microarray—which allows for parallel genotyping of many SNPs in genes involved in cow milk protein biosynthesis—was used to identify which of the 16 candidate SNPs are associated with milk performance traits in Holstein cows. Four hundred cows were genotyped by the developed and validated microarray. Significant associations were found between four single SNPs, namely DGAT1 (acyloCoA:diacylglycerol acyltransferase), LTF (lactoferrin), CSN3 (kappa-casein), and GHR (growth hormone receptor) and with fat and protein yield and percentage. Many significant associations between combined genotypes (two SNPs) and milk performance traits were found. The associations between the combined genotypes DGAT1/LTF and DGAT1/LEPTIN analyzed traits are presented as examples. The microarray based on APEX (Arrayed Primer Extension) is a fast and reliable method for multiple SNP analysis of potential application in marker-assisted selection. After further development, the chip may prospectively be used for dairy cattle paternity analysis and evolutionary studies.

In marker-assisted selection (MAS) of dairy cattle certain genes are proposed as potential candidates associated with dairy performance traits. Among different candidates, prolactin receptor gene (PRLR) seems to be promising because of its crucial role in transmitting signal from lactogenic hormones to milk protein gene promoters. In this study nine PCR fragments representing most important functional domains of PRLR were screened for polymorphism. Using SSCP method one SNP (A→C) was found in intron 9. The SNP was deposited in GenBank AY484400 and AY339393 at position of 205 nt, for Jersey and Polish Black-and-White cattle, respectively. Allele frequency was estimated in 186 Polish Black-and-White (0.981 and 0.019 for A and C, respectively) and 138 Jersey (0.812 and 0.188 for A and C, respectively) cows. Preliminary analysis showed no significant associations between PRLR genotypes and milk performance traits. However, Jersey cows of CC genotype produced more milk with higher protein content than those of AA and AC genotypes. Because of the low number of cows of CC genotype, it is necessary to investigate more numerous population of cattle in which all genotypes will be efficiently represented.

One hundred forty three proven Polish Black-and-White bulls were genotyped for 6 polymorphic sites located within 4 milk protein genes (LGB-R promoter, LGB exon IV, CASK-R promoter, CASK exon IV, LALBA 5' flanking region and CSNISI promoter). All bulls were divided into groups, including animals with the same genotypes, intragenic haplotypes and combinations of genotypes. For each group, the arithmetic mean and standard deviation for Type Production Index (TPI) and Predicted Transmitting Ability (PTA) (milk kg, protein kg, protein %, fat kg, fat %) were calculated. These data were then used for analysis of variance to find possible associations between identified polymorphic sites and TPI and PTA values. Significant differences (P<0.01) were found within different genotypes of CASK, LGB, LALBA, intragenic haplotypes CASK/CASK-R, combinations of genotypes CASK/LALBA, CASK/LGB, LGB/LALBA, CASK/LGB/LALBA and TPI. Within these groups, the highest TPI value was found for bulls carrying the following genotypes: CASK/LGB/LALBA AA/AA/PM, CASK/LGB AA/AA, CASK/CASK-R AA/MM, LGB/LALBA AA/MM, LGB AA, CASK/LALBA AA/MM and LALBA MM. Also, associations between genotypes and combinations of genotypes and PTA for protein kg, fat kg, fat %, protein % and milk kg were found.