Genetic evaluation of Holstein-Friesian and Jersey sires using records from pure- and cross-bred progeny in New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Master of Agricultural Science in animal science at Massey University

Milk Yield, Milk Fat Yield, Milk Protein Yield and Days in Milk of 72,480 dairy cows of Holstein-Friesian, Jersey and their reciprocal crossbred were analysed. The main objective of this study was to investigate possible use of crossbred progeny records to genetically evaluate sires. Bulls of each breed were evaluated separately using their purebred, crossbred or both purebred and crossbred progeny. First, crossbred progeny were used without including genetic groups. Secondly, crossbred progeny were used with genetic groups included. Rank correlations for different types of evaluations were calculated. In total, 10 different comparisons, 5 for each breed, were performed. The expected correlation of ranks of sires obtained using different data sets were estimated where applicable. Reliability and Prediction Error Variance of sire proofs were estimated both by an approximate method and direct calculation. Over-estimation of reliability and under-estimation of Prediction Error Variance by the approximate method was given. High correlations between ranks of Holstein-Friesian sires evaluated using different data sets were observed, while, the correlation between ranks of Jersey sires evaluated using purebred progeny with ranks of the same sires evaluated using only crossbred progeny was less than expected. Correlations of ranks of Jersey sires evaluated using all progeny with ranks of the same sires evaluated using only crossbred progeny were also low. After plotting EBVs of sires of each breed obtained using only purebred against EBVs of the same sires obtained using both purebred and crossbred progeny, two lines with slightly different slopes were observed. The reasons for the formation of these two lines were investigated. It was found that the number of effective crossbred progeny of sires was affecting the regression of EBVs of sires obtained using all progeny on EBVs of same sires obtained using only purebred progeny. It was concluded that crossbred progeny of Holstein-Friesian sires may be used to assist in their evaluation under New Zealand conditions, but, further research is recommended before using crossbred progeny of Jersey sires in sire evaluation

Single nucleotide polymorphisms in BMPR-IB and STAT5B genes and their association with growth and reproductive traits in chicken

The aim of the current study was to investigate the association of G4533815A SNP in STAT5B and A287G SNP in BMPR-IB genes with growth and reproduction related traits in chicken. A sample of 205 individuals from breeding station of Mazandaran native chicken population was selected randomly. All of the individuals were genotyped for both SNPs using PCR-RFLP technique. Marker-trait association analyses were performed using estimated breeding value of the traits as dependent variable in GLM procedure of SAS 9.1. Results suggested that breeding value least square means for genotypes of G4533815A SNP is significantly differed from each other for traits of body weight at 8 and 12 weeks (P<0.01). In the case of BMPR-IB gene, no significant difference was found. In conclusion, STAT5B gene may be associated with body growth in chicken and may be considered in Marker Assisted Selection program to improve chicken growth performance

Whole genome amplification: Use of advanced isothermal method

Laboratory method for amplifying genomic deoxyribonucleic acid (DNA) samples aiming to generate more amounts and sufficient quantity DNA for subsequent specific analysis is named whole genome amplification (WGA). This method is only way to increase input material from few cells and limited DNA contents. While PCR-based WGA methods have been under continuous development for over a decade, shortcomings of these methods enforced many researchers to switch to the use of non-PCR-based linear amplification techniques. Moreover, application of high fidelity and high possessive DNA polymerases enabled development of an isothermal WGA technique named multiple displacement amplification (MDA). MDA is not based on PCR and doses not require thermal cycling. It should be noted that, while MDA-based techniques proposed aiming to overcome the drawbacks of PCR-based methods however, MDA is still facing some challenges. It seems that PCR-based WGA methods alsohave some merits. One of the problems which encountered both MDA and PCR-based methods is in the amplification of degraded DNA templates. WGA methods such as T7-based linear amplification of DNA(TLAD), balanced-PCR amplification and restriction and circularization-aided rolling circle amplification (RCA-RCA) have been suggested to aim at amplification of such DNA templates.Keywords: Whole genome amplification, multiple displacement amplification (MDA), non PCR-based method

Selection in Fat-tailed Sheep Based on Two Traits of Fat-tail and Body Weight versus Single-trait Total Body Weight

ABSTRACT The objective of the present study was to compare several selection strategies and to find a method of selection permitting improvement in body weight with possible decrease or, if possible, slight increase in fat tail weight. Stochastic simulation was used to produce a flock of 10 breeding rams and 250 breeding ewes with four lambs per ewe. A total of 1000 lambs were produced for five consecutive non-overlapping generations. Data were simulated using a two trait model. Both single trait and two trait models were used under phenotypic and genetic selection. In two trait selection, economic weights were used to construct the selection indices. A range of covariance components were used for generating data and different sets of economic weights were applied to test the sensitivity of different selection strategies to these parameters. With low heritability for both traits, the least genetic trend was achieved for tail weight with phenotypic selection index. Highest aggregate genotype was obtained with two trait genetic method. With increased heritability for tail weight and under single trait selection, an increase in total body weight fully coincided with increased genetic trend in fat tail weight. The highest aggregate genotype and the lowest genetic trend in fat tail weight was obtained when negative economic weight was applied to fat tail weight. When high heritability was used for simulation, the two trait genetic selection model performed the best. However, when two trait genetic evaluation is not practical, the best alternative would be to use two trait phenotypic selection based on economic weights for the two traits

Imputation of Missing Genotypes from Sparse to High Density Using Long-Range Phasing

Related individuals share potentially long chromosome segments that trace to a common ancestor. We describe a phasing algorithm (ChromoPhase) that utilizes this characteristic of finite populations to phase large sections of a chromosome. In addition to phasing, our method imputes missing genotypes in individuals genotyped at lower marker density when more densely genotyped relatives are available. ChromoPhase uses a pedigree to collect an individual's (the proband) surrogate parents and offspring and uses genotypic similarity to identify its genomic surrogates. The algorithm then cycles through the relatives and genomic surrogates one at a time to find shared chromosome segments. Once a segment has been identified, any missing information in the proband is filled in with information from the relative. We tested ChromoPhase in a simulated population consisting of 400 individuals at a marker density of 1500/M, which is approximately equivalent to a 50K bovine single nucleotide polymorphism chip. In simulated data, 99.9% loci were correctly phased and, when imputing from 100 to 1500 markers, more than 87% of missing genotypes were correctly imputed. Performance increased when the number of generations available in the pedigree increased, but was reduced when the sparse genotype contained fewer loci. However, in simulated data, ChromoPhase correctly imputed at least 12% more genotypes than fastPHASE, depending on sparse marker density. We also tested the algorithm in a real Holstein cattle data set to impute 50K genotypes in animals with a sparse 3K genotype. In these data 92% of genotypes were correctly imputed in animals with a genotyped sire. We evaluated the accuracy of genomic predictions with the dense, sparse, and imputed simulated data sets and show that the reduction in genomic evaluation accuracy is modest even with imperfectly imputed genotype data. Our results demonstrate that imputation of missing genotypes, and potentially full genome sequence, using long-range phasing is feasible

International genomic evaluation methods for dairy cattle

<p>Abstract</p> <p>Background</p> <p>Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Higher reliabilities from larger genotype files promote cooperation across country borders. Genomic information can be exchanged across countries using simple conversion equations, by modifying multi-trait across-country evaluation (MACE) to account for correlated residuals originating from the use of foreign evaluations, or by multi-trait analysis of genotypes for countries that use the same reference animals.</p> <p>Methods</p> <p>Traditional MACE assumes independent residuals because each daughter is measured in only one country. Genomic MACE could account for residual correlations using daughter equivalents from genomic data as a fraction of the total in each country and proportions of bulls shared. MACE methods developed to combine separate within-country genomic evaluations were compared to direct, multi-country analysis of combined genotypes using simulated genomic and phenotypic data for 8,193 bulls in nine countries.</p> <p>Results</p> <p>Reliabilities for young bulls were much higher for across-country than within-country genomic evaluations as measured by squared correlations of estimated with true breeding values. Gains in reliability from genomic MACE were similar to those of multi-trait evaluation of genotypes but required less computation. Sharing of reference genotypes among countries created large residual correlations, especially for young bulls, that are accounted for in genomic MACE.</p> <p>Conclusions</p> <p>International genomic evaluations can be computed either by modifying MACE to account for residual correlations across countries or by multi-trait evaluation of combined genotype files. The gains in reliability justify the increased computation but require more cooperation than in previous breeding programs.</p