Dissertations / Theses on the topic 'Dairy cattle Genetic engineering'

I sistemi di valutazione genetica nel mondo sono in rapido sviluppo. Attualmente, i programmi di selezione “tradizionale” basati su fenotipi e rapporti di parentela tra gli animali vengono integrati, e nel futuro potrebbero essere sostituiti, dalle informazioni molecolari. In questo periodo di transizione, questa tesi riguarda ricerche su entrambi i tipi di valutazioni: dall’accertamento sull’accuratezza degli indici genetici internazionali (tradizionali), allo studio di metodi statistici utilizzati per integrare informazioni genomiche nella selezione (selezione genomica). Tre capitoli valutano gli approcci per stimare i valori genetici dai dati genomici riducendo il numero di variabili indipendenti. In modo particolare, la correzione di Bonferroni e il test di permutazioni con regressione a marcatori singoli (Capitolo III), analisi delle componenti principali con BLUP (Capitolo IV) e indice Fst tra razze con BayesA (Capitolo VI). Inoltre, il Capitolo V analizza l’accuratezza dei valori genomici con BLUP, BayesA e Bayesian LASSO includendo tutte le variabili disponibili. I risultati di questa tesi indicano che il progresso genetico atteso dall’analisi dei dati simulati può effettivamente essere ottenuto, anche se ulteriori ricerche sono necessarie per ottimizzare l’utilizzo delle informazioni molecolari in modo da ottimizzare i risultati per tutti i caratteri sotto selezione.
Genetic evaluation systems are in rapid development worldwide. In most countries, “traditional” breeding programs based on phenotypes and relationships between animals are currently being integrated and in the future might be replaced by the introduction of molecular information. This thesis stands in this transition period, therefore it covers research on both types of genetic evaluations: from the assessment of the accuracy of (traditional) international genetic evaluations to the study of statistical methods used to integrate genomic information into breeding (genomic selection). Three chapters investigate and evaluate approaches for the estimation of genetic values from genomic data reducing the number of independent variables. In particular, Bonferroni correction and Permutation test combined with single marker regression (Chapter III), principal component analysis combined with BLUP (Chapter IV) and Fst across breeds combined with BayesA (Chapter VI). In addition, Chapter V analyzes the accuracy of direct genomic values with BLUP, BayesA and Bayesian LASSO including all available variables. The results of this thesis indicate that the genetic gains expected from the analysis of simulated data can be obtained on real data. Still, further research is needed to optimize the use of genome-wide information and obtain the best possible estimates for all traits under selection.

A genetic approach to lowering protease (plasmin) levels in milk, requires the presence of polymorphism of bovine plasminogen. This study was conducted to determine to what extent genetic polymorphism exists in dairy cattle. Bovine plasminogen was first purified from Holstein cow plasma by affinity chromatography on Lysine-Sepharose and antibodies to bovine plasminogen were raised by monthly intramuscular injection of the isolated bovine plasminogen into rabbits. For plasminogen phenotyping, blood samples were collected at random from 50 Holstein and Ayrshire cattle, and plasminogen was isolated from the plasma using lysine-Sepharose and then treated with neuraminidase. After separation by isoelectric focusing (pH 3.5-9.5) in polyacrylamide gels, Plasminogen polymorphs were detected immunologically using rabbit anti-bovine plasminogen antibodies. Additionally, the plasminogen isoforms were evaluated with a functional assay (caseinolytic overlay technique) after activation of the plasminogen with urokinase. Six plasminogen phenotypes were identified which represent products of 5 variant alleles. The 5 plasminogen variants were characterized based on their isoelectric points and designated PLG A$ sb2$ (pI 6.5 and 7.0), B$ sb2$ (pI 7.6 and 7.8), C$ sb1$ (pI 6.8), D$ sb2$ (pI 7.8 and 8.0), and E$ sb2$ (pI 6.8 and 7.0). PLG A$ sb2$ and PLG B$ sb2$ were the most common variants in these cattle. The 6 phenotypes were $ rm A sb2A sb2, B sb2B sb2, A sb2B sb2, B sb2C sb1, A sb2D sb2 and D sb2E sb2$. The phenotypic frequencies in Holstein and Ayrshire were very different, $ rm A sb2A sb2 and B sb2B sb2$ being respectively the most frequent phenotype. In addition, DNA polymorphism at bovine plasminogen gene was detected when genomic DNA was digested with the restriction enzyme Msp I and hybridized with mouse plasminogen cDNA. This is the first description of plasminogen polymorphism reported in dairy cattle. If different variants have altered activity, the detrimental effect

The aims in this thesis were to investigate more comprehensive breeding goals in dairy cattle, to investigate the possible importance of genotype by environment interaction and to identify possible sources of genetic variation in feed utilisation. On the basis of a literature review, longevity was examined as component of the breeding goal, and four linear type traits (foot angle, udder depth, teat length and angularity) with the closest genetic association with longevity were used as index measurements. Economic values were derived for protein, fat and milk yield and for longevity using dynamic programming. The derived values were in genetic standard deviations relative to protein yield 1.0, 0.2, -0.2 and 0.8, respectively. Three completely additive indices were derived, assuming that the breeding goal was for: (i) yield only (YIN), (ii) longevity only (LIN) or (iii) yield and longevity, hence profit (PIN). Selection on PIN was expected to give a 5% higher annual rate of genetic progress in economic merit compared with selection on YIN, and PIN was robust to most assumptions made in the calculation. Genotype by environment interaction was investigated for a range of traits. Selection (S) and Control line (C) cows, housed and managed at the Langhill Dairy Cattle Research Centre, have been offered ad libitum complete mixed diets, with proportions (in total DM) of concentrates, silage, brewers' gains of either 20:5:75 (LC; 1.0 ton concentrate per annum) or 45:5:50 (HC; 2.5 ton concentrate), over a full lactation. No diet x genetic line interactions were observed for a number of traits, describing milk production, feed intake, efficiency and body tissue mobilisation. However, regression coefficients of milk yield and condition score on pedigree index for fat plus protein yield were significantly different between LC and HC. Phenotypic and genetic variances were generally larger on HC than on LC, but difficulties in separating the permanent environmental variance from the additive genetic variance might have obscured some of the comparisons.

The objective of this study was to evaluate the variability of growth curves of dairy heifers and estimate genetic parameters. 15066 records taken from birth until 26 months (808 days) on 2754 heifers of Quebec were considered. The pedigree file comprised 10123 animals. The Mixed procedure of SAS with ordinary polynomials was used for simple phenotypic analyses, fitting fixed linear, quadratic and cubic regressions of body weight (in kilograms) on age (in months) as well as random intercept, and random linear and quadratic regressions for each animal. The Wombat program (Meyer, 2007), with Legendre polynomials was used to estimate the genetic parameters by fitting fixed herd-year-season of birth and quartic regression of body weight on age in days, as well as random regressions for quadratic additive genetic and cubic permanent environmental effects. Heritability estimates of body weight ranged from 0.22 at around 70 days to 0.45 at around 210 days. Heritabilities of body weight at birth and 808 days were 0.35 and 0.32, respectively. The additive genetic correlations between body weights at different ages ranged from -0.37 to 1.00. In general, the genetic correlations were higher than the permanent environmental and phenotypic correlations.

The main aim of this study was to estimate the genetic parameters of test day records of British Holstein-Friesian heifers and to determine how best to use these parameters for generic prediction of lactation performance from test day records. The possibility of reducing the frequency of recording to less often than monthly and procedures for the inclusion of part records in genetic evaluations were also investigated. Estimates of genetic parameters of test day and lactation records were obtained from data on 47736 heifers in 7973 herds, progeny of 40 proven and 707 young sires, using multivariate restricted maximum likelihood methods with a sire model. Average values of heritability estimates for test day records of milk, fat and protein yields and fat and protein contents were 0.36, 0.23, 0.29, 0.36 and 0.36, respectively. Generally, heritability estimates for test day records were lowest at the start and highest in mid and late lactation. Heritability estimates for lactation records of these traits wre 0.49, 0.39, 0.43, 0.63 and 0.47, respectively. Average values of genetic correlations between adjacent TD records of these traits were high (0.92 to 0.97), and the correlations decreased as the interval between tests increased. Genetic correlations of lactation milk yield with fat and protein yields and contents were 0.72, 0.94, -0.56 and -0.53, respectively. Estimates of genetic correlation of test day records with corresponding lactation traits were also high (0.76 to 0.99), being highest in mid lactation.

For the modern dairy cow, advances in genetics and breeding for productivity has resulted in an increasing incidence of health disorders and reduced longevity. One of the most important health problems is lameness, which has led to significant economic, production and welfare consequences. A reduction in lameness will improve the economic future of the dairy industry through increased profitability and decreased welfare-related problems. Although positive attempts have been made by researchers and the industry towards improving lameness, it has remained a persistent ailment for dairy farmers. Further analysis of the genetic and environmental factors influencing lameness is warranted so that selection indices and management practices can be modified leading to improved health and welfare of the dairy cow. Several factors that cause dairy cow lameness have been implicated. I reviewed previous studies on these causative factors as well as the association between lameness, longevity and fertility. It has also been suggested that lameness affects milk production of dairy cows, but reports on the association between lameness and daily milk yield of cows have varied among researchers. Using locomotion score data on 248 cows from the Langhill herd, I investigated the relationship between locomotion score which has a high genetic correlation with lameness and various explanatory variables and also the association between daily milk yield and lameness. The study revealed that the most significant factors affecting locomotion are management regime (high concentrate feed and all year indoor housing; low concentrate feed and outdoors in summer) and time of year when cows are locomotion scored. It also showed that lameness adversely affects the milk yield of later lactation cows, and that high yielding cows are more susceptible to lameness. Housing environment plays a significant role in the health and welfare of dairy cows. With national type evaluation records, I estimated the association between housing systems and lameness-related type traits as well as genetic parameters for the locomotion traits. The analysis indicated that cows kept at pasture had favourable linear and composite type trait scores compared with cows in cubicles, straw yards and slatted floors or loafing yards. Locomotion score had strong genetic and phenotypic correlations with the leg and feet composite. Bone quality, which is a new trait in the UK type classification scheme, was moderately heritable (0.23) and had a moderate and positive genetic association with locomotion and leg and feet composite. This suggests that breeding for flatter, more refined bones could reduce locomotion disorders and help improve the longevity of the dairy cow. Analysis of national data again showed reduced incidence of digital dermatitis (DD) for cows at pasture and those with flatter, more refined bones, higher locomotion score and better leg and feet composite. Estimates of genetic parameters indicated heritable variation of DD among cows and moderate genetic associations between DD and production traits and longevity. Incorporating DD in future selection indices will be useful for increased productive life. Using random regression, I analysed changes in type traits associated with lameness (locomotion, rear legs, side view, foot angle and leg and feet composite) in relation to time (months) that cows had spent in cubicles before being classified. The general trend supported the fact that cubicle housing is unfavourable to these traits. There was significant evidence of a genotype x environment interaction, suggesting variation between bulls in the sensitivity of their daughters to cubicle housing with time.

The aim of this study was to determine how daily yield records might be used to improve the genetic evaluation of dairy cattle, which is currently based on 305-day yield predicted from monthly test day records. Daily milk yield records of 488 first lactation Holstein Friesian cows were obtained from one UK herd and summarised into weekly averages. Weekly fat, protein and lactose content records, from the same herd, were also obtained and each multiplied by test day yield to estimate fat, protein and lactose yields. Analysis of variance indicated that residual standard deviation (RSD) for each trait was lower when season of production was included in the model instead of the season of calving. The difference in RSD was more for fat and protein yields than the other traits. Lactation stage and season were the most important environmental factors affecting daily milk yield and composition while calving age had a small but significant (P<0.05) effect. Pregnancy accounted for 1.4 to 1.7% of the variation in yield traits but less than 0.4% of the variation in content traits. Its effects varied with gestation stage causing daily milk yield to decline by 3kg in the 8^th month of gestation. A significant interaction between lactation and gestation stage was observed which suggested that the negative effect of pregnancy was higher in mid than late stages of lactation. Standard models of the lactation curve studied accounted for a substantial proportion of the variation in daily milk yields of typical lactations, which made up about half of the lactations studied. The other half was made up of atypical lactations such as highly persistent animals with almost flat curves whose lactation could not be adequately modelled with the standard curve functions. A regression spline model was derived which was as good as the best 3 parameter model and more flexible. These results indicate that models which make rigid assumptions about the shape of the lactation curve may not be very effective in accounting for the effect of lactation stage on daily yields. Yields of the same trait at different stages of lactation were positively correlated throughout but the correlation between yield and content traits was negative. Average correlation between milk yield and adjacent weeks was 0.93 declining to 0.61 between yields 41 weeks apart. Daily milk yields in mid and late stages of lactation were more highly correlated with 305-day yield than yields in early lactation. Covariance functions, using orthogonal polynomials up to the order of 4, were used to model genetic and permanent environmental covariances in a restricted maximum likelihood (REML) random regression (RR) model. Genetic parameters and breeding values were estimated for yield in every week of lactation. There were compared with estimates from a multivariate model, which considered yield at different stages as different traits, and a repeatability model without random regressions.

Kyoto University (京都大学)
0048
新制・課程博士
博士(農学)
甲第8568号
農博第1151号
新制||農||810(附属図書館)
学位論文||H12||N3447(農学部図書室)
UT51-2000-M32
京都大学大学院農学研究科応用生物科学専攻
(主査)教授 佐々木 義之, 教授 守屋 和幸, 教授 矢野 秀雄
学位規則第4条第1項該当

Crossbreeding parameters (additive (a), dominance (d) and additive x additive (aa) epistatic effects for individual $ sp{ rm (I)}$ and for maternal $ sp{ rm (M)}$ performance) on body weight growth and first lactation performance traits of females from a crossbreeding experiment between Holstein (H) and Ayrshire (A) based lines were estimated by individual animal models, incorporating all known additive genetic relationships amongst animals, through restricted maximum likelihood and mixed-model methodologies.
The growth traits (asymptotic weight (A), rate parameter (k), inflection parameter (m), average lifetime absolute growth rate (AGR), average lifetime absolute maturing rate (AMR) and average lifetime relative growth rate (RGR)) were estimated by fitting the nonlinear equation, W$ sb1$ = A(1 $ pm$ be$ sp{ rm -kt}) sp{ rm M}$, to the observed weight-age data of 3076 individual females.
Results from the analyses of growth traits indicated that the H line exceeded the A line in addition genetic effects for individual performance (a$ sp{ rm I}$) for both A and AGR. The H line also exceeded the A line in additive effects for maternal performance (a$ sp{ rm M}$) in trait A. Both dominance (d) and additive x additive (aa) epistatic effects were statistically important in most cases. Individual heterosis (h$ sp{ rm I}$ = d$ sp{ rm I}$ $-$ 0.5aa$ sp{ rm I}$) was positive for traits A and AGR, whereas maternal heterosis (h$ sp{ rm M}$ = d$ sp{ rm M}$ $-$ 0.5aa$ sp{ rm M}$) was negative for A and positive for AMR. Total heterosis (TH = h$ sp{ rm I}$ + h$ sp{ rm M}$) had positive effects on AGR and AMR. For all growth traits, heterosis retained in advanced crossbred generations was statistically irrelevant. The overall conclusion was that crossbreeding systems designed to capitalize on TH would produce faster growing and earlier maturing animals.
The analyses of production traits found the additive effect of the H line for individual performance to be a major factor to increase yields of milk, protein and fat. On the other hand, line maternal and cytoplasmic source tended to favour the A line, but none reached statistical significance in any of the traits. Results indicate that two-line specific crosses or synthetic development would be sound breeding strategies for taking advantage of first cross heterosis or of line additive differences, respectively.
Estimates of crossbreeding parameters from mixed-model analyses, were found to be more reliable than those from ordinary least squares analyses. (Abstract shortened by UMI.)

The aim of this study was to estimate genetic parameters in the U.K. pedigree Holstein-Friesian (HF) population using an animal model (AM), and to investigate some implications of the results for genetic improvement. In a theoretical study it was shown that little bias in estimating variances components is introduced by grouping herds according to their mean (milk) production, a common practice for investigating heterogeneity of variance in dairy populations. For each of 26 large pedigree herds, comprising a total of 7720 HF cows, variances and h² for first lactation fat yield were estimated with residual maximum likelihood (REML) using an AM. The mean fat yield was 212 kg. The mean and range of individual herd h² estimates were 0.38 and 0.03-0.80 respectively, and the average standard error of the h² estimates was 0.19. Using likelihood ratio (LR) tests it was found that individual herd h² were not significantly different from each other (P> 0.05), but that phenotypic variances differed substantially among herds (P< 0.01). An investigation into the statistical power of a LR test for small samples showed that it is difficult to detect real differences in individual h² if the standard errors of the estimates are relatively large. Using production records in lactations 1-3 from 100 large Holstein-Friesian pedigree herds, parameters for milk, fat and protein yield in lactations 1-3 were estimated with REML using an AM. The number of records for each lactation was approximately 39000, 26000 and 17000 for lactation 1, 2 and 3 respectively. Heritabilities for the three yield traits were similar: approximately 0.36 in lactation 1 and 0.30 in lactations 2 and 3. Genetic correlations between yield traits in lactations 1 and 2, for example between milk production in first and second lactations, were approximately 0.86. Genetic correlations between yield traits in lactations 2 and 3 were nearly unity. Genetic correlations between yield traits within lactations ranged from 0.58, for milk and fat yield in lactation 3, to 0.91, for milk and protein yield in lactation 1. Genetic correlations between yield traits between lactations ranged from 0.55, for milk yield in lactation 1 and fat yield in lactation 2, to 0.85, for milk yield in lactation 2 and protein yield in lactation 3. Environmental correlations between traits within lactations were approximately 0.95, and approximately 0.40 across lactations. The effect of simplifying covariance structures for milk, fat and protein yield in lactations 1-3 on accuracy of selection for lifetime yield was investigated using selection index theory. It was found that applying a transformation to make the traits in lactation 1 independent at the phenoptypic and genetic level to the yield traits in later lactations, and assuming that three new uncorrelated variates were formed, was highly efficient in terms of accuracy of selection when compared to the accuracy of a general multivariate model. This transformation was recommended for a national BLUP evaluation, since it may take account of selection to a larger extent than when performing separate analyses for milk, fat and protein yield.

This study has compared the effect of milk pricing systems on the selection goals of dairy producers in two provinces of Canada, British Columbia (BC), and Quebec. These provinces were chosen for comparison as BC produces milk largely for a fluid market, while Quebec produces milk for a manufacturing market. Within BC, due to a higher utilization and higher milk price, the value/kg of skim on Vancouver Island was higher than that of the Vancouver Lower Mainland over the study period 1963-1982. Between the two provinces, the value/kg of skim in BC was found to be consistently higher than in Quebec over the 20 year period, while the value of fat was higher in Quebec than BC. In BC in 1980, the value of a kilogram of skim was approximately $0.30, whereas its value in Quebec was only $0.20. During the 1960s in BC, the value of skim represented one half the value of milk, and in 1982 it comprised two thirds of the value of milk, as compared to Quebec, where fat represented 43% of the value of milk. Net economic values were calculated by subtracting the dollar cost of production associated with the components of milk (carrier, fat and protein), from the gross value/kg of skim and fat. These values showed that the value/kg of protein was negative and decreasing in both BC and Quebec. The economic value/kg of butterfat has been consistently positive and increasing over the study period in BC and Quebec to $3.27 and $3.34/kg respectively in 1982. The relative economic values of carrier, fat and protein in BC and Quebec in 1982 were 0.08:1.00:-0.10 and 0.06:1.00:-0.12 respectively, which puts moderate selection on carrier and fat, and negative selection on protein. Selection index weights for carrier, fat and protein revealed that the BC dairy industry has always applied positive selection to the carrier and fat portion, and negative selection to the protein portion of milk. In 1982 the selection weights were 0.087:1.253:-1.189. The Quebec index has shown more fluctuation that BC, with less selection against solids compared to BC; (0.050:1.280:-0.657). Theoretical genetic goals of the BC dairy industry have been consistent at approximately 3.0% butterfat, 2.0% protein and 95.0% carrier. The genetic goals in Quebec have undergone wide fluctuations, but generally have signalled the dairy producer to increase both butterfat and protein. The goals of the two industries are now very similar, with the exception that Quebec continues to place higher value on solids than BC.
Land and Food Systems, Faculty of
Graduate

Data for this study were 79,997 evaluations for 12 individual body and udder traits of Holstein cows. Type scores were subjectively assigned by trained personnel of Select Sires, Inc., Plain City, OH, through their corrective mating and young sire evaluation programs. After editing data to remove incomplete, erroneous and duplicate records, 56,642 records were used to calculate overall and regional age adjustment factors. Genetic parameters were estimated. Heritabilities ranged from .40 for stature to .14 for fore udder. Standard errors ranged from .039 for stature to .018 for fore udder. Genetic correlations ranged from +.75 between teats and udder support to -.61 between feet and legs. Phenotypic correlations were generally smaller than genetic correlations, ranging from .56 between udder support and teats to -.23 for dairyness and strength. These findings were in general agreement with previous research. Genetic evaluations for the 12 individual linear traits were made using Herdmate Comparison (HC) and Best Linear Unbiased Prediction (BLUP) methods. Mean evaluations by HC were near zero, and ranged from .026 for stature to -.027 for teats. Mean repeatability also showed very little variation, ranging from .404 for stature to .241 for teats. BLUP evaluations were similar to HC evaluations, with mean evaluation ranging from .121 for feet to -.183 for dairyness. Direct correlations between BLUP and HC evaluations ranged from .90 for stature to .74 for dairyness. Forty-eight different combinations of minimum daughter numbers and model variables were tested to predict sires' overall evaluations for type from linear trait evaluations using regression analysis. Results indicate that with 5 or more daughters per sire, all predictions tested were similar in accuracy for Predicted Difference for Type.
M.S.

Bovine mammary glands respond to infection by foreign pathogens such as Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) through changes in gene expression. Monitoring the gene expression profiles will contribute to better understanding of the pathology of mastitis, and provide important selective markers for future animal breeding programs. Using cultured bovine mammary duct epithelial cells and somatic cells from infected bovine mammary glands, this study first examined the existence of Toll Like Receptors in these two systems. In cultured duct epithelial cells stimulated with E. coli LPS, both TLR 4 and 2 mRNA up regulation was detected at 2h-72h and 12h-48h respectively. For S. aureus LTA TLR 2 mRNA was up regulated at 48 and 72h whereas for TLR 4 mRNA expression up regulation was detected at 24, 48, and 72h in comparison to the Oh (p<0.05). In the case of PGN, an abundant structural component of S. aureus, the expression of TLR 2 mRNA was significant (p<0.05) at 72h whereas TLR 4 mRNA expression increased at 24, 48, and 72h. The expression of these receptors was also monitored in milk cells from cows infected with either E. coli or S. aureus. However, results obtained from the milk cells were inconclusive due to the high individual variability. Afterwards, differential gene expression profiles were monitored by the Differential Display Polymerase Chain Reaction technique in the cultured duct epithelial cells in response to E. coli and S. aureus structural components. A total of 6 candidate fragments were identified for E. coli LPS induction, whereas only one fragment was identified for S. aureus LTA induction. After LTA induction, a specific band was found to be up regulated and confirmed to be GCP-2, a chemokine involved in neutrophil recruitment. In contrast, PGN induction resulted in no change in GCP-2 levels. In different preparations of cultured duct epithelial cells both GCP-2 and IL-8 were confirmed by real time PCR to be up regulated by LTA with a significance of (p<0.01) when compared to the control cells. In the case of the E. coli identified bands, a different approach is necessary to potentially confirm the origin of these fragments. Further large scale screening of the GCP-2 and IL-8 genes in dairy cattle is necessary to test for their potential use as targets to differentiate the mastitis resistant from the mastitis prone cows.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico
O presente trabalho teve como objetivo avaliar a estrutura populacional de um rebanho bovino da raca Pardo-Suica no Estado do Ceara. Os dados foram provenientes do fichario de controle zootecnico da Fazenda Experimental Vale do Curu (FEVC), da Universidade Federal do Ceara, no periodo de 1988 a 2009, referentes a registros de 431 animais (149 machos e 282 femeas). Foram estimados o tamanho efetivo (Ne), o coeficiente de consanguinidade (F) parentesco medio (AR) dos individuos, o tamanho efetivo de fundadores e de ancestrais (fa e fe), o intervalo de geracoes (IG), a integridade dos pedigrees e as estatisticas F de Wright. Os coeficientes de F e AR medios da populacao foram de 0,0037 e 0,0139 respectivamente. Ja o intervalo de geracoes (IG) total foi de 5,40 anos, sendo maior para mae-filha. O numero efetivo de animais fundadores (fe) e de ancestrais (fa) foi 50 e 39 respectivamente, sendo que de todos os ancestrais apenas, metade foi responsavel pela variabilidade genetica da populacao, o que indica perda de genes de origem. Observa-se baixa contribuicao dos animais fundadores ao longo das geracoes. Quanto a integridade dos pedigrees foram identificados 53,13% animais como pais (reprodutores) e 50,81% como maes. Para subdivisao da populacao os valores obtidos para FIS, FST e FIT foram -1,00, 0,498 e -0,003 respectivamente, indicando perda de heterozigosidade causada pela divisao da populacao.
This study aimed to evaluate the population structu re of a cattle herd of Brown Swiss cattle in the state of CearÃ. Data were from Binder Animal Co ntrol Experimental Farm Valley Curu (FEVC), Federal University of CearÃ, from 1988 to 2 009, relating to records of 431 animals (149 males and 282 females). We estimated the effec tive size (Ne), the inbreeding coefficient (F) average kinship (AR) of individuals, the effective size of founders and ancestors (fa and fe), the generation interval (GI), the integrity of the pedigrees and Wright's F statistics. The coefficients of F and AR average population were 0.0037 and 0.0139 respecti vely. Since the generation interval (GI) total was 5.40 years, higher for motherdaughter. T he actual number of animals founders (fe) and ancestors ( fa) was 50 and 39 respectively, and all the ancestors only, was responsible for half the population genet ic variability, indicating loss of genes of origin. Found to be low contribution of founding an imals over generations. The integrity of the pedigrees were identified 53.13% animals as par ents (breeders) and 50.81% as mothers. For subdivision of the values obtained for F IS , F ST , and F IT were 1.00, 0.003 and 0.498 respectively, indicating loss of heterozygosi ty caused by the division of the population.

Milk production, feed intake, and liveweight records were available on individual animals from a high yielding Holstein-Friesian herd in which selection had been practised on fat plus protein yield using nationally available AI sires. Unlike most other studies, animals were fed ad libitum thus making this data ideal for investigating genetic relationships. In total, the data comprised 475 26-week and 293 38-week (a subset of the 26-week data) lactation records. The relationship between sires and maternal grandsire's transmitting ability (ICC), expressed as a pedigree index (sire ICC + 0.5 maternal grandsire ICC), and offspring performance for milk production traits, feed intake, and gross efficiency (milk energy (MJ)/total intake (MJ)) was investigated. Regressions of fat plus protein yield, fat yield, protein yield, and milk yield, of heifers, on their corresponding pedigree index were not far from the theoretical expectation (for a full lactation) of 1. A genetic increase of 10% in fat plus protein yield of daughters of sires of high genetic merit for fat plus protein yield was accompanied by a genetic increase of 2.0% in feed intake and a 7.9% genetic increase in efficiency. The genetic relationships among milk production, feed intake, feed efficiency and liveweight traits were investigated. Restricted Maximum Likelihood analyses were carried out, fitting an Animal Model, with repeat lactations as an additional random effect. Univariate analyses were done after approximate canonical transformation of the traits. Heritability estimates for fat plus protein yield, feed efficiency and feed intake ranged from 0.45±0.22 to 0.15±0.12, 0.48±0.21 to 0.13±0.09, and 0.52±0.14 to 0.30±0.15, respectively. Genetic correlations between milk production traits and efficiency were generally less than 0.65. Genetic correlations between liveweight traits and efficiency were very high and negative. The results indicate that when selection is on yield, the correlated responses in efficiency may be smaller under ad libitum feeding, compared with published values where cows were fed according to yield. Including liveweight in the selection criterion may give higher responses in efficiency compared to selection on yield alone. In nucleus schemes (based on Multiple Ovulation and Embryo Transfer) it may be worthwhile to include feed intake or efficiency directly in the selection criteria.

The quality of early milk produced by dams is affected by various factors (i.e. breed, age, parity, environment, nutrition, management). The impact of these factors on the quality of milk then have subsequent effects on calf health and development. Producers are responsible for following guidelines in order to ensure that they feed calves optimal quality milk in order to produce a healthy animal. They can also regulate factors such as environment and nutrition of the dam in order to produce better quality early milk. However, even after maximizing these factors there is still high mortality rate among pre-weaned calves, therefore, other factors such as mode of birth and genetics need to be studied to determine impacts on early milk quality and make further improvements to calf health and decrease mortality. Two experiments were conducted in order to study the effects of maternal and genetic factors on early milk production and to determine relationships that exist with calf health. The objective of the first study was to determine the effects that the mode of delivery had on early milk composition, and on the rumen microbiome of calves. We hypothesized that mode of birth would impact early milk composition, and, in turn, influence the microbial phyla in the calf gut. The second study had three objectives: 1) establish phenotypic relationships between colostrum composition traits, milk production traits, and calf health, 2) determine impact of breed and season on colostrum production and 3) ) elucidate the genetic parameters (i.e. heritability, genotypic, and phenotypic correlations) among colostrum production and milk production We hypothesized that colostrum composition and production differ among breeds and by season and that individual components influence calf health. Additionally, we hypothesized that colostrum quality traits (i.e. Brix score and volume) are heritable. For the first study Charolaise (CHAR; n = 23) and Angus (ANG; n = 15) dams were divided into two experimental groups; dams underwent vaginal (VD; n= 25) or cesarean (CD; n= 13) deliveries. Early milk samples were collected and quantified for protein, lactose, somatic cell count, and fatty acid concentrations. After parturition calves were separated based on dams experimental group. Rumen fluid was collected from calves on d 1, 3, and 28 post-partum. Extracted DNA from fluid were used for metagenomic sequencing (ANG calves, n=11; CHAR calves, n=13). Samples were run on the HiSeq 2500 platform as paired end reads according to Ilumina's standard sequencing protocol. A regression analysis was done in SAS using PROC GLM and regressing mode of birth on milk components for d 1,3, and 28. After, milk components found to be significantly impacted by mode of birth were regressed against microbial counts. Results showed that VD dams were more likely to have increased (P  0.05) protein, solids non-fat, and lactose on d 1 and 3, but decreased (P < 0.05) urea concentrations. Similarly, short, medium, and long-chain fatty acids were increased (P  0.05) in VD d 3 milk. Changes in true protein elicited a decrease (P  0.05) in rumen fluid Actinobacteria and Proteobacteria; whereas, both solids non-fat and lactose were associated with an increased (P  0.05) response in d 1 transition milk. No significant results for d 28 of sampling were observed. Based on our results we suggest that mode of birth influences protein concentrations in early milk. However, only a slight impact on the overall dynamics of the calf rumen was observed with the microbiome remaining relatively stable on the phyla level in response to changes in protein concentration. The second study looked into relationships between colostrum composition traits, management practices, and calf health, as well as determined heritability and genetic correlations for colostrum quality traits. Values for test-day milk, protein, fat, and somatic cell count (SCS) for Holstein (HO, n= 250) and Jersey (JE, n=289) cows were obtained from the Animal Genomic and Improvement laboratory server at the USDA. Brix score, colostrum weight, dam age, parity, and 3-month season of calving were also recorded. After, colostrum samples from JE cows were sent to DHIA where compositional measurements were obtained (i.e. true protein, fat, lactose, SCS, solid non-fats). Lactoferrin concentration for JE colostrum samples was also determined via ELISA. Calf blood samples were collected within 72 h post-partum and total serum protein (TSP) quantified to determine success of passive immunity transfer. Additionally, farm staff were instructed to record colostrum source for 1st feeding (i.e. dam, mix, other), freshness for 1st feeding (frozen vs fresh), Brix score of colostrum fed, volume of colostrum fed, and birth weight. A PROC Mixed with LSMEANS was performed in SAS to determine relationships between colostrum components, test day components, and quality traits for season, breed, and the interaction between season and breed. Also, PROC Mixed with LSMEANS was used to determine relationships of calf health with environment, management, and colostrum components. Additionally, a Pearson correlation was used to determine relationships between colostrum components and quality traits. Results for Holstein and Jersey showed that both colostrum Brix and volume (P < 0.001) differed by breed. Colostrum volume (P < 0.001), lactose (P < 0.001), and lactoferrin (P = 0.002) varied significantly by season. Additionally, test day milk (P = 0.046), fat (P = 0.012), and protein (P = 0.003) varied significantly by season. Moreover, a significant season and breed interaction (P = 0.028) was observed solely for colostrum volume. Calf health models indicated that TSP, colostrum total protein and solid non-fats impacted incidence of respiratory illness, but no factor significantly impacted incidence of scours. Results for Pearson correlation indicated strong correlations between true protein and solid non-fats and Brix (r = 0.99; 0.86). Lactoferrin also had moderate negative correlations with volume and lactose (r = -0.35; -0.33). Heritability and repeatability's were calculated using BLUPF90 family of programs. A single-trait repeatability animal model was used and included a 1-vector phenotype (Brix or Colostrum weight), fixed effects (i.e. calving year, parity, 3-month season of calving, and age at calving), additive genetic variance, random permanent environment effects, and random residual effects. A series of bivariate models were used to calculate genetic correlations of Brix score and colostrum weight with test-day compositional traits. Heritability estimates results for Holstein cow Brix and colostrum weight, were 0.25 and 0.15. Jersey cow heritability estimates were 0.36 and 0.47 respectively. We also observed some significant genetic correlations with Holstein Brix score and test-day milk (-0.23), fat (0.54), and SCS (0.29) having moderate correlations. Holstein colostrum weight had a strong correlation with test-day milk (0.96). Jerseys had strong genetic correlation of Brix score with colostrum weight (-0.98). Low to moderately heritability was observed for Brix score and colostrum weight in both breeds making them receptive to genetic selection in order to improve breeding programs. In conclusion, mode of birth significantly impacted colostrum composition which had subsequent effects on abundance of rumen microbiota. Colostrum Brix and volume were impacted by breed, season, and interaction, and calf incidence of disease was impacted by colostrum composition and environment. Additionally, two factors influencing colostrum quality (Brix score and colostrum weight) were found to be low to moderately heritable and have moderate to strong genetic correlations to compositional traits. Strong significant relationships were also found between colostrum compositional traits and colostrum quality traits. Therefore, incorporating quality traits into breeding programs has the potential to influence compositional traits which, in turn, can impact calf health and development by the interactions that exist between composition and microbial abundance in the rumen.
Master of Science in Life Sciences
Factors like breed, age, parity, nutrition, environment, and management can affect the quality of early milk produced. Many of these factors have been studied and guidelines developed in order to ensure producers feed the best quality milk to their calves which will allow for calves to develop properly. However, there is still a high mortality rate in pre-weaned calves and factors like mode of birth and genetics have not been readily studied. The purpose of our studies were to determine mode of birth impacts on composition of early milk and establish relationships between composition and rumen microbial phyla abundance. Additionally, establish relationships between colostrum composition traits, management practices, and calf health, and determine heritability and genetic correlations of colostrum quality traits to test-day composition traits. Our hypothesis was that colostrum quality traits such as Brix score and colostrum weight are heritable. We also hypothesized that mode of birth influences early milk composition and changes to composition has secondary effects to calf rumen microbial abundance. Charolaise (CHAR; n = 23) and Angus (ANG; n = 15) dams were divided into two experimental groups; dams underwent vaginal (VD; n= 25) or cesarean (CD; n= 13) delivery. Early milk samples were collected and sent to DHIA to quantify components. After parturition calves were separated based on dam's experimental group. Rumen fluid was collected from calves on d 1, 3, 28 post-partum and DNA extracted from fluid (ANG calves, n=11; CHAR calves, n=13). Results showed that VD significant differences in composition of VD and CD cows. Dams in VD group were more likely to have increased (P  0.05) protein, solids non-fat, and lactose but decreased (P < 0.05) urea concentrations. Similarly, short, medium, and long-chain fatty acids were increased (P  0.05) in VD. Changes in true protein elicited a decrease (P  0.05) in rumen fluid Actinobacteria and Proteobacteria. Results suggest that mode of birth influences protein concentrations in early milk and induces a slight impact on the overall dynamics of the calf rumen microbiome. A second study was conducted to establish relationships between colostrum components, management and calf health as well as determine genetic parameters of colostrum quality traits. Holstein (HO, n= 250) and Jersey (JE, n=289) cow test-day data was obtained from the Animal Genomic and Improvement laboratory server at the USDA. Brix score, colostrum weight, dam age, parity, and 3-month season of calving were also recorded. Colostrum samples from JE cows were sent to DHIA where compositional measurements were obtained (i.e. true protein, fat, lactose, SCS, solid non-fats). Lactoferrin concentration for JE cow colostrum samples was also determined via ELISA. Calf blood samples were collected within 72 h post-partum and TSP quantified. Farm staff recorded colostrum source for 1st feeding and colostrum freshness for 1st and feeding. A PROC Mixed was performed to determine impact of test-day milk composition traits on colostrum quality traits by breed, PROC Mixed with LSMEANS was used to determine relationships of environment, colostrum management, and colostrum components with incidence of scours and respiratory disease in calves. A Pearson correlation was used to determine relationships between colostrum components and quality traits Heritability and repeatability's were calculated using BLUPF90 family of programs. A series of bivariate models were used to calculate genetic correlations of Brix score and colostrum weight with test-day compositional traits. Results indicated that colostrum Brix and volume were impacted by season, breed, and the interaction of breed and season. Calf incidence of disease was impacted by colostrum components and total serum protein levels. Results for Pearson correlation indicated strong correlations between true protein and solid non-fats and Brix (r = 0.99; 0.86). Lactoferrin also had moderate negative correlations with volume and lactose (r = -0.35; -0.33). Heritability estimates results for Holstein Brix and colostrum weight were 0.25 and 0.15. Jersey cow heritability estimates were 0.36 and 0.47, respectively. We also observed some significant genetic correlations with Holstein Brix score and test-day milk (-0.23), fat (0.54), and SCS (0.29) having moderate correlations. Holstein colostrum weight had a strong correlation with test-day milk (0.96). Jerseys had strong genetic correlation of Brix score with colostrum weight (-0.98). Results indicated a low to moderately heritability for Brix score and colostrum weight in both breeds making them receptive to genetic selection in order to improve breeding programs. Strong significant relationships were also found between colostrum compositional traits and colostrum quality traits.

Master of Science
Department of Biological and Agricultural Engineering
Zifei Liu
This study reviewed state-of-the-art cattle enteric methane (CH4) emissions with three reported measuring units: g/head/d, g/kg DMI (dry matter intake), and %GEI (gross energy intake). Cattle emissions studies included in this meta-analysis were reported from 1995 to 2013. Fifty-five published studies were analyzed with specific objectives: (1) to gain basic information regarding magnitudes and distributions of enteric CH4 emission rates with various units, regions, cattle types and feed situations; (2) to identify and evaluate effects of influence factors or diet mitigation techniques on enteric CH4 emissions; and (3) to evaluate Intergovernmental Panel on Climate Change (IPCC) approaches to estimate enteric CH4 emissions. Emissions data (n=165) with the unit of g/head/d had large variances and non-normal distribution, and were not homogeneous across the studies. Emissions data (n=134) with the unit of g/kg DMI were not homogeneous across the studies, while emissions data (n=76) with the unit of %GEI had small variances and normal distribution, and were homogeneous across the studies. Therefore, data with the unit of %GEI may be better for meta-analysis compared to data with the units of g/head/d and g/kg DMI; however, the number of data with the unit of %GEI was small relative to the number of data with the units of g/head/d and g/kg DMI. Enteric CH4 emissions with the unit of g/head/d are significantly influenced by geographic region, cattle classification, sub-classification, humidity, temperature, body weight, and feed intake. Emissions and feed intake had a strong positive linear relationship with R2 of 0.75 (n=148). Emissions with the unit of g/kg DMI are significantly affected by humidity, body weight, and feed intake. The relationship between emissions and feed intake is positive. Emissions with the unit of %GEI are significantly associated with humidity, production stage, and body weight. IPCC Tier 1 and Tier 2 estimated emissions were approximate to most of the measured enteric CH4 emissions; however, the residuals were not normally distributed. Based on results from PRD method and paired t-tests, IPCC Tier 1 overestimated emissions in Asian studies, underestimated emissions in European studies for beef cattle, and underestimated emissions in Oceanian studies for dairy cattle. IPCC Tier 2 underestimated emissions in Asian studies for beef cattle. The underestimated emissions of IPCC Tier 2 in Asian studies might result from no consideration of effects from production stage and body weight.

The objective of this thesis was to determine the viability of alternative genetic improvement strategies (GIS). Each alternative GIS combined the use of whole genome selection (WGS) with common reproductive methods (non-sexed semen artificial insemination (AI), sexed semen AI, embryo transfer utilizing non-sexed semen AI) that can be found on a commercial dairy operation. The viability of each GIS was determined using a discounted gene flow model, designed with parameters of a typical western dairy operation, to evaluate the following variables: reproductive method, selection intensity, accuracy of prediction and female age-class. Of the GIS investigated, a heifer-based strategy that used embryo transfer with 11% selection intensity and 85% accuracy was viable. This GIS generated 2.7 million dollars in present value of cumulative gross marginal returns. Despite such encouraging results, at the current prices for genotyping, reproductive methods and achievable prediction accuracy levels, all other GIS resulted in negative returns. Whole genome selection could be a powerful genetic improvement tool for the commercial dairy industry if high accuracy genotyping solutions and reproductive methods that allowed for high selection intensity were combined and priced less than $379.07 per individual.

The significant social and economic losses as a result of bovine tuberculosis (bTB) present a continuous challenge to cattle industries in the United Kingdom (UK) and worldwide. Furthermore, as a zoonotic disease, bTB may pose a threat to humans. The potential transmission of bTB in cattle, estimated by the basic reproductive ratio (R0) was found to range between 1.0 and 1.9 in previous studies. In the UK, there has been an overall increase in bTB incidence in the last two decades despite national control and eradication programmes spanning over five decades. Such programmes mainly consist of surveillance based on the administration of skin tests and culling of animals reacting positive to these tests. Animal mobility restrictions are implemented in this case. At the same time, several studies have demonstrated that there is significant host genetic variation in individual cattle susceptibility to bTB, making the disease amenable to improvement with genetic or genomic selection. In addition, genomic analyses enhance the understanding of genetic mechanisms underlying the disease and its dynamics. The overall aim of this PhD thesis was to address existing scientific research gaps on the genetics of bTB resistance in dairy cattle. The following specific objectives were set: 1) to identify genomic regions underlying susceptibility to bTB using novel trait definitions, 2) to quantify the impact of long-term genetic selection for increased resistance to bTB on disease prevalence and dynamics and 3) to determine the consequences of genetically selecting for increased resistance to bTB on other economically important traits in dairy cattle. Genome-wide association studies (GWAS), regional heritability mapping (RHM) and chromosomal association analyses were applied in order to identify genomic regions associated with bTB (objective 1). Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires obtain from the UK national genetic evaluation for bTB. Phenotypes pertained to three bTB trait definitions: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin test with positive post-mortem examination results (phenotype 3). In all cases, non-reactors without a subsequent positive post-mortem were considered to be healthy animals with regards to bTB. Genotypes based on a 50K SNP DNA array were available and a total of 34,874 SNPs remained after quality control. The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWAS identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB. A stochastic genetic epidemiological model based on four main disease states, namely susceptible (S), exposed (E), infectious (I) and test-sensitive (T), was developed to address objective 2. Effects of selection for increased resistance to bTB were investigated in a closed, genetically heterogeneous simulated population whose structure reflected the UK national dairy herd. Disease dynamics reflected real bTB data from the UK national genetic evaluation. The proposed genetic epidemiological model was implemented to simulate breakdowns under both absence and presence of selection. Genetic selection was simulated over 20 generations in 50 replicates, while exploring various selection intensities reflecting selection of the 10, 25, 50, 70 and 100% (no selection scenario) most resistant sires. Results indicated that selection significantly reduced the average underlying susceptibility across generations. The risk of breakdown was reduced by half after 4 and 6 generations for high selection intensities (10 or 25% of sires selected) and after 9 and 15 generations for low selection intensities (50 or 70% of sires selected). The average percentage of secondary cases was reduced to less than 1% in 4 and 5 generations for high selection intensities, and in 7 and 11 generations for low selection intensities. The reduction in the number of secondary cases across generations could also be indicative of the possible impact of genetic selection on the basic reproductive ratio (R0) which is defined as the number of secondary cases that results from an infectious individual in a naive population. Genetic selection also reduced severity and duration of breakdowns across generations. Finally, with regards to objective 3, a stochastic simulation was used to investigate the long-term effects of selection for resistance to bTB on other economically important traits in the UK dairy selection programme. Selection was simulated in a genetically heterogeneous population across 10 generations in 50 replicates. Animal genetic values for bTB and other traits were simulated based on variance and genetic correlation estimates obtained from literature. Independent culling levels selection of sires was applied in every generation whereby selection was first based on increasing resistance to bTB, then improving either an overall index, milk fat yield (FY) or milk protein yield (PY). This mimics real life practices regarding the newly released national genetic evaluations for bTB resistance. The overall index comprised several traits of interest such as milk yield (MY), FY, PY, feet and legs (FL), mammary (MAM), milk somatic cell count (SCC), calving interval (CI), non-return to service at 56 days (NR56) and lifespan (LS). A fertility index (FI) consisting of CI and NR56 was also considered in the analyses. Regarding bTB, different levels of selection intensities were explored corresponding to selection of the 10, 25, 50, 70 and 100% (no selection) most resistant sires. Two levels of selection intensity on the overall index, FY or PY were considered corresponding to selecting the best 5 and 10% of sires that were left after first selecting for bTB resistance. Results indicated that selection for increased bTB resistance would generally not have far-reaching consequences on other important traits. As expected, susceptibility to bTB declined with time and increasing selection intensity. Trends for all production traits (MY, FY and PY) in the present study were affected by selection for increased bTB resistance because of their significant genetic correlations with bTB. However, body conformation traits (FL and MAM) were not affected by selection for increased bTB resistance due to zero correlation assumed between these traits and bTB in the present study. Selection on bTB hampered improvement of SCC but enhanced LS because it was correlated unfavourably with SCC but favourably with LS. In all selection scenarios, the overall index improved and was generally not affected by selection for bTB resistance. Similarly, the FI was not affected by selection on bTB in all cases. However, secondary selection on production traits only (FY or PY) led to a decline in FI. Results presented in this thesis add insight into the genetic architecture of bTB and offer a prediction of potential effects of genetic selection for increased resistance to bTB in dairy cattle. The genomic regions and candidate genes identified to be associated with susceptibility to bTB will assist to further elucidate pathways critical to cattle susceptibility to bTB.
Consistent with previous studies of other populations and trait definitions, results from genomic association analyses suggest that susceptibility of cattle to bTB is heritable and likely a polygenic trait, amenable to improvement by genetic and/or genomic selection. Embarking on routine selection for resistance to bTB will reduce future bTB prevalence and severity of breakdowns across selection generations, as manifested by results of this thesis. The results also highlight the importance of considering selection as a complementary strategy to existing interventions. This has the potential to accelerate control and ultimate eradication of bTB. This strategy could assist the UK to achieve the national goal of being officially bTB free by 2038. Furthermore, as indicated by results of this thesis, selection against bTB in the national breeding programme will not adversely affect other economically important traits. Assimilation of bTB into the overall index will better manage possible antagonistic correlations between bTB susceptibility and some of the other traits.

A study to examine factors that influence dairy cattle fertility was conducted in the United Kingdom (UK) and Malawi. Productivity data from the UK comprising 56,014 records from 574 Holstein cows were retrieved from a database at Scotland’s Rural College Dairy Research Centre in Dumfries. The cows were of either high (select) or average (control) genetic merit and fed total mixed rations with high or low forage. These formed four production systems - high forage select (HFS), low forage select (LFS), high forage control (HFC) and low forage control (LFC). Data from Malawi were obtained through a baseline survey in 67 smallholder farms and monitoring of 28 and 62 dairy cows from smallholder farms and a commercial farm, respectively. The breeds were Holstein-Friesians and Holstein-Friesian x Malawi Zebu crosses predominantly fed forages supplemented with concentrates. Some cows were fitted with accelerometers to enable monitoring of cow activity which was then related to cow fertility and energy balance. The data were analysed using descriptive statistics, mixed models and logistic regression models using SAS 9.3. The UK data showed that production system significantly (p<0.05) influenced milk yield, body energy content (BEC) and fertility. BEC is a trait that indicates absolute level of energy in the body per day regardless of energy use and intake the previous day. Daily milk yield of LFS cows was 35±0.1 (mean±SEM) litres which was significantly (p<0.05) higher than that of LFC (30.4±0.1 litres), HFS (27.5±0.1 litres) and HFC (24.3±0.1 litres) cows. LFS cows also had the highest milk yield acceleration to peak milk yield (0.51 litres/day/day) than (LFC 0.47±0.02 litres/day/day), HFC (0.47±0.03 litres/day/day) and HFS (0.46±0.03 litres/day/day) cows. The interval from calving to nadir BEC was 68±5, 83±6, 88±5 and 106±6 days for LFC, LFS, HFC and HFS cows, respectively. Days to first high luteal activity (DFHLA) and days to successful service (DSS) were significantly different with production system and genetic merit, respectively. LFC cows had DFHLA of 27±2 days (mean±SEM) which were significantly lower (p<0.05) than those of HFC (30±3 days), HFS (30±2 days) and LFS (35±3 days) cows. Average genetic merit cows had significantly lower (p<0.05) DSS (119±5 days, mean±SEM) than high genetic merit cows (132±5 days). Results from data collected in Malawi showed variations that reflected differences in management and other environmental factors. Average daily milk yield per lactation in Malawi was 13.3±4.9 (mean±SD) litres. Fertility traits in the UK herd were better than those in Malawi herds. The average DFHLA in Malawi was 79±29 days while in the UK it was 31±18 days. Cow activity in both the UK and Malawi farms varied with the feeding system, genetic merit and BEC. Select cows on home grown feeding system were more active (motion index =6250±40), stood longer (13.4±0.04 hours/day) and spent more time eating (5.6±0.32 hours/day, mean±SEM) than select cows on by products feeding system that had motion index, standing and eating time of 5166±37, 11.9±0.04 hours/day and 4.6±0.16 hours/day, respectively. Genetic merit, lactation number, days to first observed oestrus, calving BEC, service BEC and service milk yield were significant predictors of pregnancy to first insemination (p<0.05) while genetic merit, milk yield, percentage BEC between calving and service, service milk yield and service BEC were significant predictors (p<0.05) of pregnancy to the first three inseminations. Validation of models derived showed C-statistics of the receiver operating characteristic (ROC) curve of 0.66 (95% confidence interval (CI): 0.57 to 0.75) and 0.65 (CI: 0.55-0.75), respectively. It is concluded that genetic merit, feeding system, parity, energy status and stage of lactation are the major factors that determine the likelihood of achieving pregnancy following insemination. Models developed have a potential to predict the probability of pregnancy to an insemination at an acceptable level of accuracy.

A series of studies were conducted to evaluate genetic and phenotypic aspects of culling, herd life and survival in Quebec Holstein herds. Data consisted of lactation records obtained from the Programme d'Analyse des Troupeaux Laitiers du Quebec (PATLQ) files, which included 2.2 Million records before the editing procedures. The average productive herd life in Quebec herds was approximately 33 months, corresponding to an average replacement rate of MIND, for both milk recording options. Herds enrolled in the PATLQ official option had cows with longer calving intervals and culled their heifers earlier than herds in the owner sampler option. The probability of being culled for each major reason for disposal was assessed by logistic regression models, and it was shown that culling for low production (voluntary) had a clearly descending trend from 1981 to 1994, while involuntary culling (assumed to include all the reasons other than production) increased in importance mainly because of the ascending trends observed for cuffing due to reproductive problems, mastitis and feet and legs problems. Proportion of cows culled for involuntary reasons increased with parity number, but the opposite occurred for culling due to low production. Herds in the official option culled less for mastitis and sold more cows for dairy purposes than owner sampler herds. After these preliminary studies, a sequence of Weibull models were fitted to analyze different aspects of the data. The genetic study of herd life traits focused on differences between sires regarding true and functional herd life, but also described the effect of different explanatory variables on the failure time variable. Heritability for true and functional herd life was, respectively, 0.09 and 0.08 in the log scale and 0.19 and 0.15 in the original scale. The difference in the median survival time of daughters of bulls with extreme proofs for functional herd life was 1.7 lactations. Quebec dairymen use classification fo

Laboratory scale Cheddar type cheese were made from 411 milk samples originating from Ayrshire, Brown Swiss, Canadienne and Jersey with different phenotypes of kappa-casein (kappa-CN) and beta-lactoglobulin (beta-LG). From the milk input, cheese and whey outputs, the cheese yield, cheese composition and cheesemaking efficiency and other parameters were determined. The overall 37% moisture adjusted cheese yield and cheese yield efficiency were 11.19g, 10.19g, 11.97g, 11.46g and 98.91%, 90.10%, 90.76% and 90.92% for Ayrshire, Brown Swiss, Canadienne and Jersey respectively. The milk of the four respective breeds contained 12.91, 12.69, 13.50, 14.57% total solids; 3.97, 3.58, 4.40, 4.61% fat; 3.61, 3.73, 3.81, 4.00% protein. In Ayrshire, the combination BB/BB and BB/AA (kappa-CN/beta-LG) were associated with higher 37% moisture adjusted cheese yield with the values of 12.51 and 12.83 g/100 g milk respectively. The cheese composition for these two types of milk were 62.28 and 63.96% total solids, 24.22 and 20.40% protein; 32.75 and 37.92% fat. For Brown Swiss, type AA/BB was associated with higher cheese yield (11.18g) with composition of 62.15% total solids, 22.54% protein, 33.23% fat. The phenotype with the highest cheese yield for Canadienne is BB/AB (12.45g) with cheese composition of 63.61% total solids, 23.27% protein and 63.61% fat. In Jersey, the phenotype combination with higher cheese yield (14.59g) is BB/BB. The cheese composition corresponding to this phenotype was 58.64% total solids, 22.96% protein and 29.59% fat. Phenotypes associated with better coagulating properties for Ayrshire, Brown Swiss, Canadienne and Jersey were BB/AB, BB/BB, BB/BB and BB/BB for kappa-CN/beta-LG respectively.

DNA methylation has been shown to be involved in switching a number of genes on or off in particular cells. The relationship between DNA methylation and $ beta$-casein gene expression in the mammary tissue of lactating cows and mammary epithelial cells was examined. A positive correlation existed between hypomethylation of two MspI/HpaII sites in the body and one MspI/HpaII site in the 3$ sp prime$ end of the $ beta$-casein gene and its expression. In addition to these sites, hypomethylation of a distal MspI/HpaII site and HindIII sensitivity at a HindIII site also correlated with gene expression. Five DNase I hypersensitive sites were located within a 8 kb fragment. These sites designated as H1 to H5 were mapped approximately $-5, -1.3, -0.2,$ 1.7 and 2.5 kb with respect to the start site of transcription, respectively. The H2 and H3 sites were within a 1790 bp sequence that has been reported to contain a responsive element for prolactin and extracellular matrix dependent regulation and the binding site for mammary gland specific factor.
To study the dynamic changes in hypomenthylation at the MspI/HpaII sites and HindIII sensitivity, mammary tissues from pregnant heifers were evaluated. Site specific demethylation was observed depending on the stage of gestation. Demethylation of two MspI/HpaII sites (denoted M2 and M4) occurred during the early gestation, progressed slowly until mid-pregnancy, and rapidly during the last part of pregnancy. During the early stages of gestation, changes in the HindIII sensitivity in the coding domain of the $ beta$-casein gene also took place. Despite changes in HindIII sensitivity, the second HindIII site remained resistant to HindIII. By the fifth stage of gestation, the third MspI/HpaII site (M3) became less methylated and during this time the H2 site became more sensitive to HindIII. Northern analysis confirmed that demethylation of the M3 site and the acquisition of HindIII sensitivity at the H2 site was correlated with $ beta$-casein transcription.
Although $ alpha$-lactalbumin and $ beta$-casein genes are structurally and evolutionarily unrelated, they likely share common regulatory features, since both are expressed in the mammary gland during lactation. To investigate this possibility, methylation of the $ alpha$-lactalbumin gene was examined. In vivo studies revealed hypomethylation of the bovine $ alpha$-lactalbumin gene at two MspI sites and a cluster of two HhaI sites during the first and second stage of gestation, respectively. Furthermore, hypomethylation events occured only in the functional gene and not in pseudogenes, and the hypomethylation pattern was established prior to gene expression.
Taken together, the present finding suggest that DNA hypomethylation is necessary for the expression of two mammary-specific milk protein genes, $ beta$-casein and $ alpha$-lactalbumin. Hypermethylation within the body of these genes may silence these genes in non-expressing tissues and in non-epithelial cells within the mammary gland during lactation.

Tesis por compendio
[ES] El análisis del control genético del hospedador sobre su microbiota ha sido señalado recientemente como un tema prometedor en diferentes campos de estudio. La relación entre el holobionte hospedador-microbioma y los fenotipos en el ganado lechero podría conducir a nuevos conocimientos en los programas de selección genética. Dentro de esta tesis doctoral, se realizó la estimación y análisis a través de diferentes enfoques estadísticos con el objetivo de desentrañar el control genético del hospedador sobre la microbiota en ganado lechero. Además, se analizó el rasgo de concentración de metano como un fenotipo potencial para ser incluido en el programa de mejora de ganado lechero español. Mayor abundancia relativa de la mayoría de los eucariotas (principalmente protozoos ciliados y hongos) y algunas arqueas (Methanobrevibacter spp. Methanothermus spp. y Methanosphaera spp.) fueron factores de riesgo para ser clasificadas en la categoría alta. Se propuso un conjunto de modelos de ecuaciones estructurales (SEM) de tipo recursivo dentro de un marco de Cadenas de Markov Monte Carlo (MCMC) para analizar conjuntamente la relación hospedador-metagenoma-fenotipo. Se estableció un modelo bivariado no-recursivo como punto de referencia. La heredabilidad de CH4 se estimó en 0,12 ± 0,01 en ambos modelos, recursivo y no recursivo. Asimismo, las estimaciones de heredabilidad para la abundancia relativa de los taxones se superpusieron entre los modelos y variaron entre 0.08 y 0.48. Las correlaciones genéticas entre la composición microbiana y el CH4 variaron de -0,76 a 0,65 en el modelo bivariado no recursivo y de -0,68 a 0,69 en el modelo recursivo. Doce matrices de relación de microbiota (K) fueron construidas a partir de diferentes métricas de distancia del microbioma, con el objetivo de comparar su desempeño dentro de un marco de estimación de componentes de varianza para CH4 y toda la microbiota. Análisis de simulación (n = 1000) y datos reales fueron desarrollados considerando cuatro modelos posibles: un modelo genómico aditivo (GBLUP), un modelo de microbioma (MBLUP), un modelo de efectos genéticos y microbioma (HBLUP) y un modelo de efectos de interacción genético, microbioma y genético × microbioma (HiBLUP). Un nuevo término "Holobiabilidad" fue definido para referirse a la proporción de la varianza atribuible a los efectos del holobionte hospedador-microbioma. Las estimaciones a partir de datos reales usando HiBLUP variaron dependiendo de la K utilizada y estuvieron entre 0.15-0.17, 0.15-0.21 y 0.42-0.59 para heredabilidad, microbiabilidad y holobiabilidad, respectivamente. El conjunto de datos de microbioma fue agregado a través de análisis de componentes principales (PCA), en pocos componentes principales (PCs) que fueron utilizados como aproximaciones del metagenoma central. Parte de la variabilidad condensada en estos PC está controlada por el genoma de la vaca, con estimaciones de heredabilidad para el primer PC (PC1) de ~ 0,30 en todos los niveles taxonómicos, con una gran probabilidad (> 83%) de que la distribución posterior sea > 0,20 y con un intervalo de mayor densidad posterior al 95% (95% HPD) no conteniendo cero. La mayoría de las estimaciones de correlación genética entre PC1 y metano fueron grandes (>0,70) en todos los niveles taxonómicos, con la mayor parte de la distribución posterior (> 82%) siendo > 0,50 y con su 95% HPD no conteniendo cero. Estos resultados sugieren que todo el metagenoma del rumen regula recursivamente las emisiones de metano en las vacas lecheras, y que tanto el CH4 como las composiciones de la microbiota están parcialmente controladas por el genotipo del hospedador. Las variables agregadas (PC) propuestas podrían ser usadas en programas de mejora de animales para reducir las emisiones de metano en las generaciones futuras.
[CA] L'anàlisi del control genètic de l'hoste sobre la seva microbiota s'ha assenyalat recentment com un tema prometedor en diferents camps d'estudi. La relació entre el holobiont hoste-microbioma i els fenotips en bovins de llet podria conduir a nous coneixements en els programes de cria. Dins d'aquest doctorat es van realitzar tesis, estimacions i anàlisis mitjançant diferents enfocaments estadístics amb l'objectiu de desentranyar el control genètic de l'hoste sobre la microbiota en bestiar lleter. A més, es va analitzar el tret de concentració de metà com a fenotip potencial a incloure en el programa espanyol de cria de bestiar lleter. La major abundància relativa de la majoria dels eucariotes (principalment protozous i fongs ciliats) i algunes arquees (Methanobrevibacter spp. Methanothermus spp i Methanosphera spp.) Van ser factors de risc per classificar-se en les categories altes. Es va proposar un conjunt de models d'equacions estructurals (SEM) de tipus recursiu dins d'un marc de cadena Markov Monte Carlo (MCMC) per analitzar conjuntament la relació hoste-metagenoma-fenotip. Es van establir models no recursius com a referència. L'heretabilitat del CH4 es va estimar en 0,12 ± 0,01 en ambdós models, recursius i no recursius. De la mateixa manera, les estimacions d'heretabilitat de l'abundància relativa dels tàxons es van superposar entre models i van oscil·lar entre 0,08 i 0,48. Les correlacions genètiques entre la composició microbiana i el CH4 van oscil·lar entre -0,76 i 0,65 en els models bivariables no recursius i de -0,68 a 0,69 en els models recursius. Dotze matrius de relació de microbiota (K) de diferents mètriques de distància de microbiomes, amb l'objectiu de comparar el seu rendiment dins d'un marc d'estimació de components de variància per CH4 i anàlisi de microbiomes sencers en simulació (n = 1000, 25 rèpliques) i es van realitzar dades reals , considerant quatre possibles models: un model genòmic additiu (GBLUP), un model de microbioma (MBLUP), un model d'efectes genètics i microbiomes (HBLUP) i un model d'efectes d'interacció genètics, microbiomes i genètics × microbiomes (HiBLUP). Es va definir un nou terme "Holobiabilitat" per referir-se a la proporció de la variància fenotípica atribuïble als efectes holobiont del microbioma host. Les estimacions de dades reals mitjançant HiBLUP van variar en funció de la K utilitzada i van oscil·lar entre 0,15-0,17, 0,15-0,21 i 0,42-0,59 per heretabilitat, microbiabilitat i holobiabilitat, respectivament. El conjunt de dades de microbiomes es va agregar mitjançant l'anàlisi de components principals (PCA) en pocs components principals (PC) que es van utilitzar com a proxies del metagenoma principal. Part de la variabilitat condensada en aquestes PC està controlada pel genoma de la vaca, amb estimacions d'heretabilitat per a la primera PC (PC1) de ~ 0,30 a tots els nivells taxonòmics, amb una gran probabilitat (> 83%) de la distribució posterior> 0,20 i amb un 95% més alt interval de densitat posterior (95% HPD) que no conté zero. La majoria de les estimacions de correlació genètica entre PC1 i metà eren grans (>0,70) en tots els nivells taxonòmics, amb una gran part de la distribució posterior (> 82%)> 0,50 i amb un 95% de HPD que no contenia zero. Aquests resultats suggereixen que tot el metagenoma del rumen regula recursivament les emissions de metà en vaques lleteres i que tant el CH4 com les composicions de microbiota estan parcialment controlades pel genotip de l'hoste. Les variables agregades proposades (PC) es podrien utilitzar en programes de cria d'animals per reduir les emissions de metà en les generacions futures.
[EN] The analysis of the host genetic control over its microbiota has recently been pointed out as a promising theme in different fields of study. The relationship between the host-microbiome holobiont and phenotypes in dairy cattle could lead to new insights in breeding programs. Within this Ph.D. thesis, estimation and analysis through different statistical approaches were performed aiming to unravel the host genetic control over the microbiota in dairy cattle. Besides, methane concentration trait was analyzed as a potential phenotype to be included in the Spanish dairy cattle breeding program. Higher relative abundance of most eukaryotes (mainly ciliate protozoa and fungi) and some archaea (Methanobrevibacter spp. Methanothermus spp and Methanosphera spp.) were risk factors for being classified in the high categories. a set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed to jointly analyze the host-metagenome-phenotype relationship. Non-recursive models were set as benchmark. Heritability of CH4 was estimated at 0.12 ± 0.01 in both, the recursive and non-recursive, models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH4 ranged from -0.76 to 0.65 in the non-recursive bivariate models and from -0.68 to 0.69 in the recursive models. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the 7 genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. Twelve microbiota relationship matrices (K) from different microbiome distance metrics were built, aiming to compare its performance within a variance component estimation framework for CH4 and whole microbiome analysis on simulation (n = 1000, 25 replicates) and real data were performed, considering four possible models: an additive genomic model (GBLUP), a microbiome model (MBLUP), a genetic and microbiome effects model (HBLUP) and a genetic, microbiome and genetic × microbiome interaction effects model (HiBLUP). A new term "Holobiability" was defined to refer to the proportion of the phenotypic variance attributable to the host-microbiome holobiont effects. Estimates from real data using HiBLUP varied depending on the K used and ranged between 0.15-0.17, 0.15-0.21 and 0.42-0.59 for heritability, microbiability and holobiability, respectively. The microbiome dataset was aggregated through Principal Component Analysis (PCA) into few principal components (PCs) that were used as proxies of the core metagenome. Part of the variability condensed in these PCs is controlled by the cow genome, with heritability estimates for the first PC (PC1) of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being > 0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (>0.70) at all taxonomic levels, with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. These results suggest that rumen's whole metagenome recursively regulate methane emissions in dairy cows, and that both CH4 and the microbiota compositions are partially controlled by the host genotype. The purposed aggregated variables (PCs) could be used in animal breeding programs to reduce methane emissions in future generations.
This research was financed by RTA2015-00022-C03-02 (METALGEN) project from the national plan of research, development and innovation 2013-2020 and the Department of Economic Development and Competitiveness (Madrid, Spain). We thank the regional Holstein Associations and farmers collaborating in the project. Computational support from the High-Performance Computing Centre in Galicia (Spain) is acknowledged. Alejandro Saborío-Montero acknowledges the scholarship from Universidad de Costa Rica for his doctorate studies which partially conducted to the progress of this study.
Saborío Montero, A. (2021). Study of the Host Genetic Control over the Ruminal Microbiota and their Relationships with Methane Emissions in Dairy Cattle [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172633
TESIS
Compendio

It is well known that DNA methylation in gene promoter regions inhibits gene transcription and that tissue-specific gene expression is partially under the control of this transcription regulatory mechanism. In this study, bovine mammary gland tissues were collected from individual animals in lactating and non-lactating stages to investigate the DNA methylation patterns in the kappa-casein gene and alpha-lactalbumin gene core promoter regions using the bisulphite treatment in combination with polymerase chain reaction (PCR) sequencing. Different methylation status of each sample was classified into three categories, namely methylation at known transcription factor binding domains, methylation at core promoter non-binding domains and the absence of cytosine methylation. Real-time quantitative PCR was used to quantify the transcription levels of the kappa-casein and alpha-lactalbumin genes from the collected samples. A comparative method was used and fold-change values were calculated based on the comparison of the normalized threshold values of samples from different physiological stages as well as on various methylation patterns observed in their core promoter regions. Statistical analyses showed that the expressions of the kappa-casein and alpha-lactalbumin genes were significantly different in lactating and non-lactating mammary gland tissues. The methylation observed in the core promoter region of bovine alpha-lactalbumin gene was found to be associated with its gene expression. On the other hand, the methylation found in the core promoter region of bovine kappa-casein gene did not have any effect on its gene transcript levels.

Bovine mastitis adversely affects the dairy industry around the world. This disease is caused by a diverse range of bacteria, broadly categorised as minor and major pathogens. In-line tools that help identify these bacterial groupings in the early stages of the disease are advantageous as timely decisions could be made before the cow develops any clinical symptoms. The first objective of this research was to identify the most informative milk parameters for the detection of minor and major bacterial pathogens. The second objective of this research was to evaluate the potential of supervised and unsupervised neural network learning paradigms for the detection of minor infected and major infected quarters in the early stages of the disease. The third objective was to evaluate the effects of different proportions of infected to non-infected cases in the training data set on the correct classification rate of the supervised neural network models as there are proportionately more non-infected cases in a herd than infected cases. A database developed at Lincoln University was used to achieve the research objectives. Starting at calving, quarter milk samples were collected weekly from 112 cows for a period of fourteen weeks, resulting in 4852 samples with complete records for somatic cell count (SCC), electrical resistance, protein percentage, fat percentage, and bacteriological status. To account for the effects of the stage of lactation on milk parameters with respect to days in milking, data was divided into three days in milk ranges. In addition, cow variation was accounted for by the sire family from which the cow originated and the lactation number of each cow. Data was pre-processed before the application of advanced analytical techniques. Somatic cell score (SCS) and electrical resistance index were derived from somatic cell count and electrical resistance, respectively. After pre-processing, the data was divided into training and validation sets for the unsupervised neural network modelling experiment and, for the supervised neural network modelling experiments, the data was divided into training, calibration and validation sets. Prior to any modelling experiments, the data was analysed using statistical and multivariate visualisation techniques. Correlations (p<0.05) were found between the infection status of a quarter and its somatic cell score (SCS, 0.86), electrical resistance index (ERI, -0.59) and protein percentage (PP, 0.33). The multivariate parallel visualisation analysis validated the correlation analysis. Due to significant multicolinearity [Correlations: SCS and ERI (-0.65: p<0.05); SCS and PP (0.32: p<0.05); ERI and PP (-0.35: p<0.05)], the original variables were decorrelated using principle component analysis. SCS and ERI were found to be the most informative variables for discriminating between non-infected, minor infected and major infected cases. Unsupervised neural network (USNN) model was trained using the training data set which was extracted from the database, containing approximately equal number of randomly selected records for each bacteriological status [not infected (NI), infected with a major pathogen (MJI) and infected with a minor pathogen (MNI)]. The USNN model was validated with the remaining data using the four principle components, days in milk (DIM), lactation number (LN), sire number, and bacteriological status (BS). The specificity of the USNN model in correctly identifying non infected cases was 97%. Sensitivities for correctly detecting minor and major infections were 89% and 80%, respectively. The supervised neural network (SNN) models were trained, calibrated and validated with several sets of training, calibration and validation data, which were randomly extracted from the database in such a way that each set has a different proportion of infected to non-infected cases ranging from 1:1 to 1:10. The overall accuracy of these models based on validation data sets gradually increased with increase in the number of non-infected cases in the data sets (80% for the 1:1, 84% for 1:2, 86% for 1:4 and 93% for 1:10). Specificities of the best models for correctly recognising non-infected cases for the four data sets were 82% for 1:1, 91% for 1:2, 94% for 1:4 and 98% for 1:10. Sensitivities for correctly recognising minor infected cases for the four data sets were 86% for 1:1, 76% for 1:2, 71% for 1:4 and 44% for 1:10. Sensitivities for correctly recognising major infected cases for the four data sets were 20% for 1:1, 20% for 1:2, 30% for 1:4 and 40% for 1:10. Overall, sensitivity for the minor infected cases decreased while that of major infected cases increased with increase in the number non-infected cases in the training data set. Due to the very low prevalence of MJI category in this particular herd, results for this category may be inconclusive. This research suggests that somatic cell score and electrical resistance index of milk were the most effective variables for detecting the infection status of a quarter followed by milk protein and fat percentage. The neural network models were able to differentiate milk containing minor and major bacterial pathogens based on milk parameters associated with mastitis. It is concluded that the neural network models can be developed and incorporated into milking machines to provide an efficient and effective method for the diagnosis of mastitis.

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A realização do presente estudo teve como objetivo estimar as associações genéticas entre produção de leite acumulada até os 305 dias (P305), escore de células somáticas (ECS), habilidade de permanência aos 60 meses de idade (Stay60) e características lineares de úbere e pernas e pés. Foram utilizadas 14.864 avaliações de Stay60, 17.200 classificações lineares, 24.147 registros de P305 e 14.307 de ECS da primeira lactação de fêmeas que pariram entre 19 e 36 meses de idade. Foram realizadas três análises multicaracterísticas contendo as características P305, ECS, Stay60, além das características de classificação linear. Os componentes de (co)variância foram estimados por meio de abordagem Bayesiana, empregando o programa THRGIBBS2F90. Para todas as características foram considerados como efeitos aleatórios no modelo, o genético aditivo e o residual. Como efeitos fixos, o grupo de contemporâneas foi incluído para todas as características, a idade da vaca ao parto como covariável (efeito linear) para P305 e ECS, e idade da vaca na classificação (efeito linear) para as de tipo. Para a Stay60 não foi incluída a covariável idade. As estimativas de herdabilidade obtidas nas análises foram de 0,24±0,02, 0,08±0,02 e 0,09±0,03 para P305, ECS e Stay60, respectivamente. As herdabilidades para as características lineares de úbere variaram de 0,16 a 0,39, e as de pernas e pés, de 0,13 a 0,21. As correlações genéticas estimadas foram de 0,08±0,09 entre P305 e ECS, -0,25±0,12 entre P305 e Stay60 e 0,11±0,20 entre ECS e Stay60. As correlações de maiores magnitudes com as características de tipo foram entre a P305 e a largura do úbere posterior e a profundidade de úbere (0,34 e -0,40), entre a ECS e a profundidade de úbere e pernas traseiras vista posterior (-0,39 e 0,39), e entre a Stay60 e a colocação dos tetos posteriores e as pernas traseiras vista lateral (0,33 e -0,47). A correlação negativa entre P305 e a Stay60 sugere que vacas com produção de leite muito elevada tendem a permanecerem menos tempo no rebanho. A característica pernas traseiras-vista lateral apresentou elevada resposta correlacionada na Stay60, podendo ser usada como um preditor precoce da longevidade dos animais.
The aim of this study was to estimate genetic associations between milk production truncated to 305 days (P305), somatic cell score (ECS), stayability at 60 months of age (Stay60) and type traits of udder and feet and legs.Were used 14,864 evaluations for Stay60, 17,200 type classifications, 24,147 records of P305 and 14,307 of ECS of first lactation belonging to Holstein females that calved between 19 and 36 months old. Three standard multi-trait analyses were carried out, containing P305, ECS, Stay60 and the type traits. The (co)variance components were estimated using Bayesian approach, using the THRGIBBS2F90 program. For all traits were considered as random effects the genetic additive and residual. As fixed effects, the contemporary group was included for all traits, the covariate age of cow at calving (linear effect) for P305 and ECS, and age of cow at classification (linear effect) for type traits. For Stay60 the covariate age of cow was not included in the model. Posterior means of heritability estimates were 0.24±0.02, 0.08±0.02 and 0.09±0.03 for P305, ECS and Stay60, respectively. The udder traits heritabilities ranged from 0.16 to 0.39, and feet and legs, from 0.13 to 0.21 The genetic correlations estimates were 0.08±0.09 between P305 and ECS, 0.25±0.12 between P305 and Stay60, and -0.11±0.20 between ECS and Stay60. The higher correlations magnitudes with the type traits were between P305 and rear udder width, and udder depth (0.34 and -0.40), and between ECS and udder depth and rear legs-rear view (- 0.39 and 0.39), and between Stay60 and fore teat placement and rear legs-side view (-0.33 and 0.47). The negative correlation between P305 and Stay60 suggests that cows with very high milk production tend to remain less time in the herd. The trait rear legs-side view presented a high correlated response in Stay60 (75% of selection efficiency), and can be used as an early predictor of animal longevity.

Dissertation (PhD(Agric))--University of Stellenbosch, 2007.
ENGLISH ABSTRACT: This study is a search for a quantifiable measure which estimates the genetic merit of female animals’ breeding efficiency. For practical reasons, such a measure must be both simple and inexpensive to record, irrespective of the herd management strategy. A literature investigation was undertaken to summarize breeding objectives for reproduction efficiency and to review different ways of expressing genetic reproduction efficiency. Traits to assess these in terms of the breeding objective, merits and requirements in terms of data collection are discussed. During the lifetime of a cow events occur which influence her fertility. A distinction is made between component traits and aggregate traits: a component trait points to one event, while aggregate traits are composites of more than one event. Although all the traits discussed seem relevant for breeding value estimation, the practical application depends on the herd management system in use. Age at first calving and days to calving are component traits that are easily and inexpensively measurable. Heritability estimates for the age at first calving were moderate. The heritability estimated for days to calving was 0.09. Calving rate comes close to the overall breeding objective. The estimated heritability of calving rate is low (0.04), resulting in slow genetic improvement. Calving success was defined and investigated even though some constraints exist. A sire model proved that genetic variation exists for calving success on the underlying scale. The corresponding heritability estimate was 0.27. Three categorical traits were defined. For stayability a sire variance of 0.41 was estimated with a heritabitity on the underlying scale of 0.27. The sire variances and heritabilities estimated for retention and calf tempo were high. Of the three traits, calf tempo is the one that reflects the true fertility of the bull’s female progeny. Calf tempo was redefined as net breeding merit, a trait describing the retention of male animals and the reproductive performance of their female offspring. The obtained sire variances show that the trait is heritable and can be improved by selection. Net breeding merit gives an indication of the ‘success’ of sires in a given population. A heritability estimate of 0.20 was estimated on a data set comprising offspring of bulls older than nine years, but when offspring of all sires were included, heritability estimates of 0.08 and 0.11 for the Afrikaner and Bonsmara, respectively, were found. Adjusting for young females was investigated by using the best linear unbiased estimate (BLUE) deviations to derive adjustment factors for herd level in order to predict performance for net breeding merit. Variation in the BLUE deviations occurred between all age class groups for the Afrikaner, whereas for the Bonsmara the variation between the BLUE deviations for the 3 year olds seems greater than the variation in the other age groups. It is suggested that the standardized curve for herd performance level derived from the BLUE deviations be used to adjust the phenotypic values of younger animals. This way the comparison between older and younger animals should be more valid. In conclusion, reproductive traits are heritable and genetic improvement can be achieved through selection. Any economical viable beef enterprise should include at least one trait in their selection criteria that will improve the reproductive efficiency.
AFRIKAANSE OPSOMMING: Hierdie studie is ‘n ondersoek na ‘n kwantifiseerbare maatstaf wat die genetiese meriete van vroulike diere se teeldoeltreffendheid beraam. Om praktiese redes moet so ‘n beraming sowel eenvoudig as goedkoop wees om te bepaal, onafhanklik van die kudde bestuurstrategie. ‘n Literatuurstudie is onderneem om die teeldoeleindes vir reproduktiewe doeltreffendheid op te som, sowel as om die verskillende wyses van genetiese reproduksiedoeltreffendheid beskrywing onder oë te neem. Verskeie eienskappe om hierdie beskrywings in terme van teeldoeleindes, meriete en dataversamelings-vereistes te raam, word bespreek. Gedurende ‘n koei se leeftyd kom gebeurtenisse voor wat haar vrugbaarheid beïnvloed. Daar word onderskei tussen komponenteienskappe en aggregaateienskappe: ‘n komponenteienskap verwys na een gebeurtenis, terwyl aggregaateienskappe na samestellings van meer as een gebeurtenis verwys. Hoewel al die eienskappe wat bespreek word relevant voorkom, sal die praktiese toepassing afhang van die kuddebestuurstelsel in gebruik. Ouderdom by eerste kalwing en dae tot kalwing is komponenteienskappe wat maklik en goedkoop bepaal kan word. Oorerflikheidsramings vir die ouderdom van eerste kalwing was matig. Die oorerflikheidsraming vir dae tot kalwing was 0.09. Kalffrekwensie is baie na aan die oorkoepelende teeldoelwit. Die geraamde oorerflikheid vir kalffrekwensie is laag (0.04), wat stadige genetiese verbetering tot gevolg het. Kalfsukses is gedefinieer en ondersoek, hoewel enkele beperkings bestaan het. ‘n Vaar-model het aangetoon dat genetiese variasie ten opsigte van kalfsukses op die onderliggende skaal bestaan. Die ooreenkomstige oorerflikheidsraming was 0.27. Drie kategoriese eienskappe is gedefinieer. Vir blyvermoë in die kudde is ‘n vaar-variansie van 0.41 geraam, met ‘n oorerflikheid van 0.27 op die onderliggende skaal. Die vaar-variansies en oorerflikhede wat vir retensie en kalftempo bereken is, was hoog. Van die drie eienskappe is kalftempo die een wat die ware vrugbaarheid van die bul se vroulike nageslag reflekteer. Kalftempo is herdefinieer as netto teelmeriete, ‘n eienskap wat die retensie van manlike diere en die reproduktiewe prestasie van hulle vroulike nasate beskryf. Die verkreë vaar-variasies wys dat die eienskap oorerflik is en verbeter kan word met seleksie. Netto teelmeriete gee ‘n aanduiding van die “sukses” van ‘n vaar in ‘n gegewe populasie. ‘n Oorerflikheidsraming van 0.30 is verkry op ‘n datastel bestaande uit die nageslag van bulle ouer as nege jaar, maar as die nageslag van alle vaars ingesluit is, was die oorerflikheidsraming onderskeidelik 0.08 en 0.11 vir die Afrikaner en Bonsmara. Aanpassing vir jong vroulike diere is ondersoek deur gebruik te maak van die beste lineêre onpartydige beramings (BLUE) om korreksiefaktore vir die kuddevlak te verkry, ten einde die prestasie ten opsigte van netto teelmeriete te voorspel. Variasies in die BLUE afwykings het voorgekom tussen alle ouderdomsgroepe vir die Afrikaner, terwyl vir die Bonsmara die variasie tussen BLUE afwykings vir die 3-jaar oud diere groter was as vir die ander ouderdomsgroepe. Dit word voorgestel dat die gestandardiseerde kurwe vir kuddeprestasievlak wat afgelei word van BLUE afwykings gebruik word om die fenotipiesewaardes van jonger diere aan te pas. Op hierdie wyse behoort die vergelyking tussen ouer en jonger diere meer geldig te wees. Ten slotte, reproduktiewe eienskappe is oorerfbaar en genetiese vordering is moontlik deur seleksie. Enige ekonomies lewensvatbare vleisbees-onderneming behoort ten minste een eienskap wat die reproduktiewe doeltreffendhied sal verbeter, in te sluit in seleksie kriteria.

Este estudo foi realizado para detectar quantitative trait loci (QTL) afetando características e curva de crescimento numa população F2 Holandês x Gir. As características estudadas foram peso ao nascer (BW), peso à desmama (WW), peso aos 205 dias (W205), peso ao sobreano (YW), peso aos 720 dias (W720), ganho de peso diário do nascimento ao desmama (ADG0_60), ganho de peso diário da desmama ao peso aos 205 dias (ADG60_205), ganho de peso diário de peso ao 205 dias ao peso ao sobreano (ADG205_365), ganho de peso diário do sobreano ao peso aos 720 dias (ADG365_720), ganho de peso diário total (ADG), curva de crescimento de peso ao nascer ao peso aos 720 dias (GC). 180 marcadores microssatélites, abrangendo os 29 autossomos bovino e cobrindo 3,322 cM foram selecionados a partir do mapa genético bovino. A média de intervalo de marcador foi 22 cM. Vinte e oito QTLs foram detectados em dez cromossomos, quinze QTLs tem modo aditivo, dois QTLs tem modo de dominância e onze QTLs têm sobredominância como modo de ação. Um QTL sugestivo foi detectado para BW no cromossomo BTA 17 em 1 cM. Um QTL sugestivo foi detectado para W205 no BTA 3 a 20 cM. Quatro QTLs sugestivos foram encontrados para YW no BTA 3 a 7 cM, no BTA 6 a 134,9 cM, no BTA 12 a 1 cM, e no BTA 22 a 1 cM. Para W720, seis QTLs sugestivos foram identificados, no BTA 2 a 30 cM, no BTA 3 a 1 cM, no BTA 6 a 44 cM, no BTA 10 a 20 cM, no BTA 12 a 1cM e no BTA 22 a 1 cM. Um QTL sugestivo foi identificado para ADG0_60 no BTA 8 a 143 cM. Dois QTLs sugestivos foram relatados para ADG60_205 no BTA 3 a 19 cM e no BTA 23 19 cM. Um QTL sugestivo foi observado para ADG205_365 no BTA 12 a 7 cM. Para ADG365_720, três QTLs foram detectados. Dois QTLs têm efeitos sugestivos no BTA 1 a 12 cM e no BTA 10 a 22 cM, um QTL significativo no BTA 6 a 43 cM. Seis QTLs sugestivos para ADG foram encontrados no BTA 2 a 32 cM, no BTA 3 a 1 cM, no BTA 6 a 43 cM, no BTA 10 a 20 cM, no BTA 12 a 1 cM e no BTA 22 a 1 cM. Três QTLs sugestivos foram identificados por GC no BTA 2 a 34 cM, no BTA 12 a 2 cM e no BTA 22 a 3 cM. Nenhum QTL foi detectado para WW em todos os cromossomos. Existem vários efeitos pleiotrópcos nos cromossomos BTA 2, 3, 6, 10, 12 e 22, os quais influenciam as características de crescimento. Foram detectados 22 efeitos epistáticos complexos para as cinco características YW, W720, GC, ADG365_720 e ADG.
This study was conducted to detect quantitative trait loci (QTL) affecting growth traits and growth curve using F2 Holstein x Gyr population. Traits analyzed were birth weight (BW), weaning weights (WW), weight at 205 day (W205), yearling weight (YW), weight at 720 day (W720), average daily gain from birth to weaning weight (ADG0_60), average daily gain from weaning weight to weight at 205 days (ADG60_205), average daily gain from weight at 205 days to yearling weight (ADG205_365), average daily gain from yearling weight to weight at 720 days (ADG365_720), total average daily gain (ADG), and growth curve from birth weight to weight at 720 days (GC). 180 microsatellite markers covering the 29 bovine autosomes and covered 3322 cM were chosen from bovine genetic map. The average marker interval was 22 cM. Twenty eight QTLs detected span ten chromosomes, fifteen QTLs had additive mode, two QTLs had dominance mode and eleven QTLs had overdominance mode of gene action. Suggestive QTL was found for BW on BTA 17 at 1 cM. Also, Suggestive QTL was detected for W205 on BTA 3 at 20 cM. Four suggestive QTLs were found for YW on BTA 3 at 7 cM, on BTA 6 at 134.9 cM, on BTA 12 at 1 cM, and on BTA 22 at 1 cM. For W720, six suggestive QTLs were identified, on BTA 2 at 30 cM, on BTA 3 at 1 cM, on BTA 6 at 44 cM, on BTA 10 at 20 cM, on BTA 12 at 1cM and on BTA 22 at 1 cM. Suggestive QTL was observed for ADG0_60 on BTA 8 at 143 cM. Two suggestive QTLs were reported for ADG60_205 on BTA 3 at 19 cM and on BTA 23 at 19 cM. Suggestive QTL was observed for ADG205_365 on BTA 12 at 7 cM. For ADG365_720, three QTLs were detected. Two QTLs had suggestive effect on BTA 1 at 12 cM and BTA 10 at 22 cM, one significant QTL on BTA 6 at 43 cM. Six suggestive QTLs were found for ADG on BTA 2 at 32 cM, BTA 3 at 1 cM, BTA 6 at 43 cM, BTA 10 at 20 cM, BTA 12 at 1 cM and BTA 22 at 1 cM. Three suggestive QTLs were identified for GC on BTA 2 at 34 cM, BTA 12 at 2 cM and BTA 22 at 3 cM. No QTLs were detected for WW in all chromosomes. There were many pleiotropy effects on BTA 2, 3, 6, 10, 12 and 22 influencing growth traits. There were 22 complexes epistatic effects were detected for five traits YW, W720, GC, ADG365_720 and ADG.