Detection and mapping of QTL on bovine chromosomes 2 and 5 segregating for live weight, average daily gain and body measurements in Japanese Black Cattle

Bovine chromosomes 2 (BTA2) and 5 (BTA5) of purebred, half-sib progeny sired by five Japanese black bulls were genotyped using microsatellite DNA markers. The data were subjected to linkage analysis for the detection and mapping of segregating quantitative trait loci (QTL) influencing live weight, average daily gain and body measurements at weaning. Probability coefficients of inheriting allele 1 or 2 from the sire at specific chromosomal intervals were computed. The phenotypic data on progeny were regressed on these probability coefficients in a within-common-parent regression analysis. Fixed effects of sex, parity and season of birth as well as age as a covariate, were fitted in a linear model to the phenotypic data and subsequently analysed using QTL Express by generating an F-statistic through permutation tests at chromosome-wide significance thresholds over 10, 000 iterations at 1 cM intervals. Highly significant (P<0.01) segregating QTL for body measurements were detected on BTA2 for hip width (1 cM) and chest depth (8 cM) in Sire Family 1 and pin bone width (16 cM) in Sire Family 3. Other significant QTL (P<0.05) detected were withers height (3 cM), hip height (4 cM), body length (4 cM), shoulder width (6 cM), lumbar width (3 cM), thurl width (3 cM) and canon circumference (2 cM) in Sire Family 1, shoulder width (16 cM) in Sire Family 3 and thurl width (24 cM), pin bone width (19 cM), heart girth (26 cM) and abdominal width (69 cM) in Sire Family 4. Significant (P<0.05) QTL for live weight and average daily gain were detected on BTA2 for birth weight (5 cM) and weaning weight (3 cM) in Sire Family 1 and post-weaning average daily gain (68 cM) in Sire Family 4. BTA 5 contained QTL for birth weight, pin bone width and heart girth in Sire Family 3 that were only suggestive and not significant. Such localization of economically important QTL as demonstrated in this study, will expedite genetic improvement via marker-assisted selection, gene introgression and positional cloning in Japanese black cattle

Improving the Accuracy of Genomic Predictions: Investigation of Training Methods and Data Pooling

One of the primary factors in the response to selection is the accuracy of selection. This study focused on methodologies to predict breeding values (BV) accurately within multi- and single-step genomic evaluations. Factors including cross-validation methods, dependent variables, and genotyping strategies were assessed on the accuracy of genomic BV while using multi-step prediction in real and simulated data. In both cases, random clustering led to largest estimated accuracies compared to clusters based on k-means, k-medoids, and principle component analysis, but differences in bias were not detected. Using deregressed estimated BV (EBV) to estimate SNP effects led to larger accuracies and smaller standard errors than adjusted phenotypes. Randomly genotyping animals instead of selectively genotyping the top 25% was associated with highest accuracies and least amount of bias. Genetic improvement of economically relevant traits (ERT) should be the goal of breeding programs. Although generally absent in seedstock herds, ERT are routinely collected within commercial sectors; therefore, pooling data was proposed to include commercial information in a cost-effective manner. Pooling involves collecting tissue samples from a group of animals and then combining the DNA to be genotyped as one. The accuracy of EBV when pooled data were used within single-step analysis was investigated through simulation. For a single trait, pool sizes of 2, 10, 20 or 50 did not generally lead to differences in EBV accuracy compared to using individual data when pools were constructed to minimize phenotypic variation. Low accuracy sires benefited the most from pooling, while EBV for the pools could be used for management purposes. For a bivariate analysis, pool sizes of at least 20 were recommended in combination with minimizing phenotypic variation. Additionally, if pools were constructed to minimize phenotypic variation, pooling could be used across a range of genetic correlations (0.1, 0.4, and 0.7) and ways in which missing values arise (randomly missing records or sequential culling). Collectively, these results suggest pooling can be used to include commercial data within genetic evaluations. Advisor: Matthew L. Spangle

Improving the Accuracy of Genomic Predictions: Investigation of Training Methods and Data Pooling

One of the primary factors in the response to selection is the accuracy of selection. This study focused on methodologies to predict breeding values (BV) accurately within multi- and single-step genomic evaluations. Factors including cross-validation methods, dependent variables, and genotyping strategies were assessed on the accuracy of genomic BV while using multi-step prediction in real and simulated data. In both cases, random clustering led to largest estimated accuracies compared to clusters based on k-means, k-medoids, and principle component analysis, but differences in bias were not detected. Using deregressed estimated BV (EBV) to estimate SNP effects led to larger accuracies and smaller standard errors than adjusted phenotypes. Randomly genotyping animals instead of selectively genotyping the top 25% was associated with highest accuracies and least amount of bias. Genetic improvement of economically relevant traits (ERT) should be the goal of breeding programs. Although generally absent in seedstock herds, ERT are routinely collected within commercial sectors; therefore, pooling data was proposed to include commercial information in a cost-effective manner. Pooling involves collecting tissue samples from a group of animals and then combining the DNA to be genotyped as one. The accuracy of EBV when pooled data were used within single-step analysis was investigated through simulation. For a single trait, pool sizes of 2, 10, 20 or 50 did not generally lead to differences in EBV accuracy compared to using individual data when pools were constructed to minimize phenotypic variation. Low accuracy sires benefited the most from pooling, while EBV for the pools could be used for management purposes. For a bivariate analysis, pool sizes of at least 20 were recommended in combination with minimizing phenotypic variation. Additionally, if pools were constructed to minimize phenotypic variation, pooling could be used across a range of genetic correlations (0.1, 0.4, and 0.7) and ways in which missing values arise (randomly missing records or sequential culling). Collectively, these results suggest pooling can be used to include commercial data within genetic evaluations. Advisor: Matthew L. Spangle

Evaluation of the ingestive behaviour of the dairy cow under two systems of rotation with slope

The ingestive behaviour of grazing animals is modulated by the vegetation characteristics, topography and the type of stocking method. This research was carried out in 2019, at the Rumipamba CADER-UCE. It aimed to evaluate the impact of two contrasting stocking methods of dairy cows grazing a pasture with an average of slope >8.5%. Four dairy cows were set to graze a 0.4 ha paddock for 5 days for continuous stocking methods, while for the electric fence methods the dairy cows were restricted to 0.2 ha and the fence was moved uphill every 3 hours, repeating this process four times a day. Cow were equipped with activity sensors for 12 h per day. The whole procedure was repeated 2 times after realizing an equalization cuts and both paddocks, a rest time of 30 days and a random reassignment of paddocks to one of the treatments. The cows showed a difference in terms of the percentage of grazing P=0.0072, being higher with the electric fence (55% of the measurement time). From rising-plate-meter estimates of available biomass along the grazing periods, we calculated despite similar forage allowances (electric fence = 48.06 kg DM/cow/d and continuous = 48.21 DM/cow/d) a higher forage intake was obtained in the electric fence treatment (17.5 kg DM/cow/d) compared the continuous stocking (15.7 kg DM/cow/d) (P=0.006). In terms of milk production animals grazing under the differences electrical fence stocking method tended (P=0.0985) to produce more milk (17.39 kg/d) than those grazing in the continuous system (15.16 kg/d) due to the influence of the slope (P=0.05), while for milk quality the protein content was higher for the electric fence (33.7 g/l) than the continuous method (30.5 g/l) (P=0.039). None of the other milk properties differed between methods (P>0.05)

Exploitation of microsatellites as genetic markers of beef-performance traits in Piemontese x Chianina crossbred cattle

The majority of traits selected in livestock production are quantitative, and the observed phenotype is the result of the effect of many quantitative trait loci (QTL) and environmental factors (RON et al. 1994). QTLs account for only a small fraction of total variance, and can be located by genetic linkage to a genetic marker (SOLLER1990; WELLER1992). Therefore, by using many genetic markers associated with the same trait, it is possible to explain a good part of the genetic variance. Microsatellites, a new class of genetic markers that are highly variable and polymorphic (LITTand LUTY1989;WEBERand MAY1989), are DNA regions composed of few repeated short-sequence motifs, which are present in the genome of different species (HAMADAet al. 1984), including bovine species (FRIESet al. 1990). Microsatellite loci occur frequently, randomly and uniformly distributed throughout the genome (DIETRICHet al. 1992;HEARNeEt al. 1992;WEBER1990).They exhibit considerable polymorphism, due to variation in the number of repeat units, and there are often multiple alleles, probably because of past slippage mutation (TAUTZand RENZ1984; SCHLOTTERER and TAUTZ1992). One of the advantages of microsatellites is that the banding patterns are extremely simple, showing one or two strong bands, and alleles differ in size by integer multiples of the repeat unit. They can be easily detected through simple polymerase chain reaction amplification if the two flanking regions are known, and registered in open access gene banks (i.e. EMBL). Pedigree studies have shown that microsatellites are inherited in typical Mendelian co- dominant fashion (LITT and LUTY1989). As microsatellites are so abundant in the genome of a species, they can be used as markers, exploiting their association with QLTs and including them in marker-assisted selection programmes to increase the rate of genetic progress (GEORGESet al. 1993). The purpose of this research was to associate three identified microsatellites with beef-performance traits. Because a crossbred population was studied in which marker and QTL are in linkage disequilibrium, the aim of the analysis was to evaluate the mere substitution effect of the marker on the trait