Association of single nucleotide polymorphisms in the bovine leptin and leptin receptor genes with growth and ultrasound carcass traits in Nellore cattle

Given the important role of leptin in metabolism, we looked for a possible association of leptin and leptin receptor polymorphisms with carcass and growth traits in Nellore cattle. We examined associations of leptin and leptin receptor SNPs with ultrasound carcass (longissimus dorsi muscle area (ribeye area), backfat thickness and rump fat thickness and growth traits (weaning weight adjusted to 210 days of age, yearling weight adjusted to 550 days of age, weight gain of weaning to yearling and scrotal circumference adjusted to 550 days of age) of 2162 Bos primigenius indicus (Nellore) animals. Allele and genotypic frequencies were calculated for each marker. Allele substitution, additive and dominance effects of the polymorphisms were also evaluated. Some alleles of the molecular markers had low frequencies, lower than 1%, in the sample analyzed, although the same polymorphisms described for B. p. taurus cattle were found. Due to very low allelic frequencies, the E2JW, A59V and UASMS2 markers were not included in the analysis, because they were almost fixed. E2FB was found to be significantly associated with weight gain, ribeye area and backfat thickness. The promoter region markers, C963T and UASMS1, were also found to be significantly associated with ribeye area. T945M was significantly associated with weight gain. We conclude that the leptin and receptor gene markers would be useful for marker-assisted selection.

MUC1 gene polymorphism in three Nelore lines selected for growth and its association with growth and carcass traits

The objective of this study was to describe the VNTR polymorphism of the mucin 1 gene (MUC1) in three Nelore lines selected for yearling weight to determine whether allele and genotype frequencies of this polymorphism were affected by selection for growth. In addition, the effects of the polymorphism on growth and carcass traits were evaluated. Birth, weaning and yearling weights, rump height, Longissimus muscle area, backfat thickness, and rump fat thickness, were analyzed. A total of 295 Nelore heifers from the Beef Cattle Research Center, Instituto de Zootecnia de Sertozinho, were used, including 41 of the control line, 102 of the selection line and 152 of the traditional. The selection and traditional lines comprise animals selected for higher yearling weight, whereas control line animals are selected for yearling weight close to the average. Five alleles were identified, with allele 1 being the most frequent in the three lines, especially in the lines selected for higher means for yearling weight. Heterozygosity was significantly higher in the control line. Association analyses showed significant effects of allele 1 on birth weight and weaning weight while the allele 3 exert significant effects on yearling weight and back fat thickness. Despite these findings, application of this marker to marker-assisted selection requires more consistent results based on the genotyping of a larger number of animals in order to increase the accuracy of the statistical analyses.

Degree of multicollinearity and variables involved in linear dependence in additive-dominant models

The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.