Modelos de regressão aleatória multicaracterísticos combinando diferentes funções para descrever produção de leite, gordura e proteína em caprinos via inferência bayesiana

The present study aimed to propose multiple-trait random regression models (multiple-trait RRM) combining different functions to describe milk yield, fat and protein percent in a dairy goats genetic evaluation by using MCMC (Markov Chain Monte Carlo) Bayesian inference. Were analyzed 3,856 milk yield (MY), fat (FP) and protein (PP) percent test-day records from 535 first lactation of Saanen and Alpine goats (including crosses). The initial analyses were performed using single- trait RRM, in which for all effects (average curve, additive genetic and permanent environmental) the following models were considered: third and fifth order Legendre polynomials, linear B-splines with three (at 1, 20 and 40 weeks) and five (at 1, 8, 15, 20 and 40 weeks) knots, Ali and Schaeffer function (Ali and Schaeffer, 1987) and Wilmink function (Wilmink, 1987). Residual variances were modeled by a step function with three classes: 1 to 3, 4 to 8, and 9 to 40 weeks of lactation. After definition of the best single-trait RRM to describe each trait (MY, FP, PP) based on the Deviance Information Criterion (DIC), the functions were combined to compose the multiple-trait RRM. The model based on Ali and Schaffer function fitted better for MY and PP, while the model based on fifth order Legendre polynomials (Leg5) was the best one for FP. All tested RRM considering the combinations of functions presented lower DIC values, showing the superiority of these models when compared to other multiple-trait RRM based only on one function. Among the combined RRM, those considering Ali and Schaeffer function to describe the MY and PP, and Leg5 to describe the FP, presented the best fit. Estimates of heritability for MY and FP were close until 20 weeks, ranging from 0.25 at 0.54. The estimates of heritability for PP were, in general, higher than the estimates for MY and FP, ranging from 0.35 until 0.51. The genetic correlation between MY and FP and between MY and PP throughout the lactation period were negative, except for the period immediately after lactation peak. The genetic correlation between FP and PP was positive and approximately constant throughout the lactation (about 0.54). We concluded that combining different functions in a unique multiple-trait RRM can be an plausible alternative for joint genetic evaluation of different longitudinal traits.O presente estudo objetivou propor modelos de regressão aleatória multicaracterísticos (MRAM) combinando diferentes funções para descrever a produção de leite e a porcentagem de gordura e proteína do leite, em uma avaliação genética de cabras leiteiras via inferência bayesiana. Foram analisados 3.856 registros de produção de leite (MY), porcentagem de gordura (FP) e proteína (PP) no dia do controle da primeira lactação de 535 cabras Alpina e Saanen (incluindo mestiças). As análises iniciais foram realizadas utilizando MRA unicaracterísticos (MRAU), nos quais para todos os efeitos (curva média, genética aditiva e de ambiente permanente), os seguintes modelos foram considerados: terceira e quinta ordem dos polinômios ortogonais de Legendre; B-splines lineares com três (na 1°, 20° e 40° semana) e cinco (na 1°, 8°, 15°, 20° e 40° semana) nós, função de Ali e Schaeffer (Ali e Schaeffer, 1897) e função de Wilmink (Wilmink, 1987). As variâncias residuais foram consideradas heterogêneas com três classes: 1 a 3, 4 a 8 e 9 a 40 semanas de lactação. Depois da definição dos melhores MRAU para descrever cada característica (MY, FP e PP), baseado no Critério de Informação da Deviance (DIC), as funções foram combinadas para compor o MRAM (MRAM combinado). O modelo baseado na função de Ali e Schaeffer apresentou melhor ajuste para as características MY e PP, enquanto o modelo baseado nos polinômios ortogonais de Legendre de quinta ordem (Leg5) foi o melhor para descrever FP. Todos os MRA testados considerando a combinação de funções apresentaram menores valores de DIC, demonstrando a superioridade destes modelos quando comparados a outros MRAM baseados somente em uma função. Entre os MRAM combinados, aquele que considerou a função de Ali e Schaeffer para descrever MY e PP e o Leg5 para descrever FP apresentou o melhor ajuste. As estimativas de herdabilidade para MY e FP foram próximas até 20 semanas, e variaram de 0,25 até 0,54. As estimativas de herdabilidade para PP foram, em geral, maiores que as estimativas para MY e FP, variando de 0,35 até 0,51. A correlação genética entre MY e FP e entre MY e PP ao decorrer do período de lactação foram negativas, exceto para o período imediatamente após o pico de lactação. A correlação genética entre FP e PP foi positiva e aproximadamente constante durante a lactação (aproximadamente 0,54). Conclui-se que a combinação de diferentes funções em um único MRAM pode ser uma alternativa plausível para a avaliação genética conjunta de diferentes características longitudinais.Conselho Nacional de Desenvolvimento Científico e Tecnológic

Análises genética e genômica de características longitudinais em gado de leite

Traits with multiple phenotypic values taking over time are termed longitudinal traits, e.g., milk production. Despite of the great importance of analyzing these traits taking into account their time- dependent nature, the majority of studies on longitudinal traits have converted the repeated records for each animal into a single measure (e.g., average over all time points or accumulated yield), which does not allow any inference about the trait over time. Therefore, the general objective of this thesis was to better understand the genetic and genomic aspects of longitudinal traits over time in dairy cattle. Simulated and real datasets (from Brazilian Gyr and Canadian Ayrshire, Holstein and Jersey dairy cattle breeds) were used in this research. First, breeding values were predicted (EBVs) using a multiple-trait random regression model (RRM) combining Legendre orthogonal polynomials and linear B-splines to simultaneously describe the first and second lactation of Gyr Dairy cattle. Subsequently, genomic predictions, genome-wide association analyses were performed for milk, fat and protein yields, and somatic cell score from the first three lactations of the Canadian dairy breeds using different methodologies, including two-step and single-step genomic best linear unbiased prediction (GBLUP). The performance of the most used deregression methods for non-longitudinal traits for the deregression of cows’ and bulls’ EBVs for using in genomic evaluation of longitudinal traits was also evaluated, using RRMs and the Canadian Jersey data. In addition, the impact of including information from bulls and their daughters in the training population of multiple-step genomic evaluations was investigated using a simulated population. Combining different functions to model the fixed and random effects in multiple-trait RRMs seems to be a good alternative (based on the goodness-of-fit of model, breeding values and variance component estimates) for genetic modeling of lactation curves in dairy cattle, as shown here for Gyr cattle. Deregressed longitudinal EBVs obtained using well established methods of deregression for non-longitudinal traits can be used for genomic prediction of longitudinal traits. Furthermore, removing the parent average and the genotyped daughters’ average from the deregressed EBVs can increase the reliability of genomic estimated breeding values (GEBVs). In Holstein, the reliability of GEBVs predicted using the RRM was in general lower than the reliability from the accumulated 305-d model when using the two-step GBLUP method, however, the RRM provided less biased GEBVs compared to the accumulated 305-d model. The use of single-step GBLUP to predict GEBVs for longitudinal traits based on RRMs increased the reliability and reduced bias of GEBVs compared to traditional parent average, in the Canadian Ayrshire, Holstein, and Jersey breeds. Different genomic regions associated with the analyzed traits were identified for different lactation stages, supporting differential gene control across lactation stages. For all Canadian breeds, the pattern of the effect of several single nucleotide polymorphisms associated with the analyzed longitudinal traits changed over time. In addition, prospective candidate genes with potential different patterns of expression over time were identified in putative chromosomal regions. The findings described in this thesis will contribute to advance the knowledge on the genomic expression and prediction of breeding values for longitudinal traits.Características com múltiplos valores fenotípicos registrados ao longo do tempo são denominadas características longitudinais, como por exemplo produção de leite. Apesar da grande importância de analisar essas características levando em conta o tempo, a maioria dos estudos sobre características longitudinais convertem os registros repetidos de cada animal em uma única estimativa (por exemplo, média de todos os tempos ou produção acumulada), o que não permite nenhuma inferência sobre a característica ao longo do tempo. Desta forma, o objetivo geral desta tese foi entender melhor os aspectos genéticos e genômicos de características longitudinais ao longo do tempo em bovinos leiteiros. Dados simulados e reais (do gado brasileiro Gir leiteiro e das raças leiteiras canadenses Ayrshire, Holandesa e Jersey) foram utilizados neste estudo. Primeiro, valores genéticos (EBVs) foram preditos usando um modelo multicaracterístico de regressão aleatória (RRM) combinando polinômios ortogonais de Legendre e B-splines lineares para descrever simultaneamente a primeira e segunda lactação do gado leiteiro Gir. Subsequentemente, predições genômicas e análises de associação genômica ampla e funcional foram realizadas para produção de leite, gordura e proteína, e escore de células somáticas nas três primeiras lactações das raças canadenses usando diferentes metodologias, como o melhor preditor linear não viesado genômico (GBLUP) em um único ou dois passos. O desempenho dos métodos de deregressão mais utilizados para características não longitudinais na deregressão dos EBVs de vacas e touros usados para avaliação genômica de características longitudinais também foram avaliados, usando RRMs e os dados da raça canadense Jersey. Além disso, o impacto da inclusão da informação de touros e suas filhas na população de treinamento em avaliações genômicas de múltiplos passos foi estudado usando uma população simulada. Combinar diferentes funções para modelar os efeitos fixos e aleatórios em RRMs multicaracteristicos parece ser uma alternativa viável (com base no ajuste do modelo, e nas estimativas de valores genéticos e componentes de variância) para modelagem genética das curvas de lactação em vacas leiteiras, como mostrado aqui para o gado Gir. A deregressão dos EBV longitudinais realizada utilizando métodos bem estabelecidos de deregressão para características não-longitudinais pode ser usada para predição genômica de características longitudinais. Além disso, remover a média dos pais e a média das filhas genotipadas do EBV deregredido pode aumentar a confiabilidade dos valores genômicos estimados (GEBVs). Na raça Holandesa, a confiabilidade dos GEBVs preditos usando o RRM foi em geral menor que a confiabilidade do modelo de produção acumulada, ao usar o método GBLUP em dois passos, no entanto, o RRM forneceu GEBVs menos viesados comparado ao modelo de produção acumulada. O uso do GBLUP em um único passo para predizer os GEBVs para características longitudinais baseado em RRMs aumentou a confiabilidade e reduziu o viés dos GEBVs comparado com a tradicional média dos pais, nas raças canadenses Ayrshire, Holandesa e Jersey. Diferentes regiões genômicas associadas às características analisadas foram identificadas para diferentes estágios da lactação, evidênciando o controle diferencial de genes ao longo dos estágios de lactação. Para todas as raças canadenses, o padrão do efeito de vários polimorfismos de nucleotídeo único associados com as características longitudinais analisadas mudou ao longo do tempo. Além disso, potenciais genes candidatos com diferentes padrões de expressão ao longo do tempo foram identificados em diferentes regiões cromossômicas. Os achados descritos nesta tese contribuirão para o avanço do conhecimento sobre a expressão genômica e predição de valores genéticos para características longitudinais

Estimation of Genetic Parameters for Pork Quality, Novel Carcass, Primal-Cut and Growth Traits in Duroc Pigs

More recently, swine breeding programs have aimed to include pork quality and novel carcass (e.g., specific primal cuts such as the Boston butt or belly that are not commonly used in selection indexes) and belly traits together with growth, feed efficiency and carcass leanness in the selection indexes of terminal-sire lines, in order to efficiently produce pork with improved quality at a low cost to consumers. In this context, the success of genetic selection for such traits relies on accurate estimates of heritabilities and genetic correlations between traits. The objective of this study was to estimate genetic parameters for 39 traits in Duroc pigs (three growth, eight conventional carcass (commonly measured production traits; e.g., backfat depth), 10 pork quality and 18 novel carcass traits). Phenotypic measurements were collected on 2583 purebred Duroc gilts, and the variance components were estimated using both univariate and bivariate models and REML procedures. Moderate to high heritability estimates were found for most traits, while genetic correlations tended to be low to moderate overall. Moderate to high genetic correlations were found between growth, primal-cuts and novel carcass traits, while low to moderate correlations were found between pork quality and growth and carcass traits. Some genetic antagonisms were observed, but they are of low to moderate magnitude. This indicates that genetic progress can be achieved for all traits when using an adequate selection index

Assessing genetic diversity of various Canadian sheep breeds through pedigree analyses

The loss of genetic variability in a population will drastically affect the success of a breeding program by reducing selection response and fitness and, consequently, affecting reproduction, resilience and production efficiency. The objective of this study was to perform in-depth pedigree analyses of the Canadian sheep breeds in order to assess the levels of inbreeding, effective population size and other metrics of genetic diversity, which included the five most important sheep breeds in Canada: Dorset (DR), Polypay (PO), Rideau-Arcott (RI), Romanov (RV), and Suffolk (SU), using a large dataset (1,336,926 animals). As measures of genetic diversity, effective population size, inbreeding coefficient, effective number of founders, effective number of founder genomes, effective number of non-founders, and effective number of ancestors were estimated. The completeness and depth of the Canadian sheep pedigree datasets were reasonably high, with less than 20% parental information missing. More attention should be given to PO breed, which was found to have the smallest effective population size (55), and RV breed, which had the highest average level of inbreeding (4.8%). Techniques such as optimum contribution selection and minimum co-ancestry mating could be used to minimize the inbreeding of future generations, while maintaining genetic progress at a desirable level.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Using publicly available weather station data to investigate the effects of heat stress on milk production traits in Canadian Holstein cattle

Heat stress imposes a challenge to the dairy industry, even in northern latitudes. In this study, publicly available weather station data was combined with test-day records for milk, fat, and protein yields to identify the temperature-humidity index (THI) thresholds at which heat load starts affecting milk production traits in Canadian Holstein cows. Production loss per THI unit above the threshold for each trait was estimated. Test-day records from 2010-2019 from 166,749 cows raised in Ontario and from 221,214 cows raised in Quebec were analyzed. Annual economic losses due to heat stress were estimated from the average losses of fat and protein yields based on the annual average of 156 days with THI exceeding the calculated thresholds. Average thresholds for the daily maximum (THI_max) and daily average (THI_avg) THI estimated across lactations in both provinces were THI_max (THI_avg) 68 (64), 57 (50), and 60 (58) for milk, fat, and protein yield, respectively, indicating that milk components are more sensitive to heat stress. An economic loss of about $34.5 million per year was estimated. Our findings contribute to an initial investigation into the impact of heat stress on the Canadian dairy industry and provides a basis for genetic studies on heat tolerance.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Strategies for within-litter selection of piglets using ultra-low density SNP panels

Genotyping costs and the large number of selection candidates are major factors that inhibit the application of genomic selection in the swine industry and other small-sized livestock species. In order to reduce genotyping costs and increase the uptake of genomic selection, a possible strategy is to genotype animals with an affordable low-density (LD) SNP panel and, then accurately impute the LD panel to a high-density (HD) SNP panel. For within-litter piglet selection, genotyping all piglets from all farrows using the commercially available SNP chips is still cost prohibitive. Consequently, genomic evaluation is limited in this stage and genotypic and phenotypic data from all piglets in a litter are rarely available. This study investigates the feasibility of implementing genomic selection for within-litter piglet selection, using a total of nine simulated LD panels: from the “ultra” low (300–3000 SNP markers) to moderately low (6000–10, 000 SNP markers). For each LD panel, the performance of the genomic predictions according to the accuracy of genotype imputation, the accuracy of the genomic estimated breeding values (GEBV) based on the imputed data, and distribution of the correctly selected animals within litter was evaluated and compared to using the simulated HD panel (60,000 SNP) and True Breeding Values (TBVs). In this simulation study, we considered three economically important traits: back fat thickness (BF), growth rate of age to 100 Kg (GR), and litter size (LS). For the LD panel sizes ranging from 300 to 10,000, the accuracy of imputation (measured as concordance rate) ranged from 73.20 to 99.81%; and the mean proportion of the correctly selected top rank animals within litter ranged from 55 to 98%. Based on the trade-off between panel size and genomic selection accuracy, the use of a LD panel containing 1500 SNPs might be recommended, as this panel yielded more than 85% correctly selected animals within-litter based on all three traits

Bayesian estimation of genetic parameters for individual feed conversion and body weight gain in meat quail

We estimated genetic correlations between partial and total body weight gain (BWG) and individual feed conversion (FC) aiming to identify possible partial traits as selection criteria in meat quail breeding programs. Data included 379 records from two different genetic lines (188 quails from UFV1 and 191 from UFV2). The following traits were evaluated:individual feed conversion from21to28(FC21–28)andfrom28to35daysofage (FC28–35); body weight gain from 1 to 21 (BWG1–21), 21–28 (BWG21–28), 28–35 (BWG28–35) and from 1 to 35 (BWG1–35, full period) days of age. Genetic parameters (heritabilities and genetic correlations) were estimated through multi-trait models via Bayesian inference. For UFV1 line, genetic correlations estimates (with respective credible intervals) between BWG1–21 and BWG1–35, BWG21–28 and BWG1–35, BWG28–35 and BWG1–35, FC21–28 and FC28–35, FC 21–28 and BWG1–35, and FC28–35 and BWG1–35 were 0.62 0.15–0.90), 0.81 0.60–0.94), 0.69 0.35–0.88), 0.06 (−050 to 0.60), −0.87 (−0.97 to −0.63) and −0.51 (−0.84 to −0.01), respectively; and for UFV2 line, these estimates were 0.33 (−0.05 to 0.63), 0.79 0.59–0.92), 0.88 0.73–0.96), 0.35 (−0.30 to 0.78), −0.56 (−0.85 to −0.09) and −0.76 (−0.93 to −0.41), respectively. Additionally, for the UFV1 line heritability estimates for BWG21–28 and FC21–28 were 0.69 0.40–0.86) and 0.55 0.31–0.74), respectively; while for UFV2 line the heritabilities for BWG28–35 and FC28–35 were 0.68 0.47–0.83) and 0.37 0.17–0.63). Based on these results, we recommend as target traits BWG21–28 and FC21–28 for UFV1 line; and BWG28–35 for UFV2 line. Selecting for these indicated traits, we expect to reduce breeding program costs related mainly to feeding of nonselected animals and labor with phenotyping

Genetic Connectedness Between Norwegian White Sheep and New Zealand Composite Sheep Populations With Similar Development History

publishedVersio

Across-country genomic predictions in Norwegian and New Zealand Composite sheep populations with similar development history

acceptedVersio

A note on transgenerational epigenetics affecting egg quality traits in meat-type quail

The aim of the following experiment was to estimate transgenerational epigenetic variance for egg quality traits using genealogical and phenotypic information in meat-type quail. Measured traits included egg length (EL) and width (EWD), albumen weight (AW), shell weight (SW), yolk weight (YW) and egg weight (EW).A total of 391 birds were evaluated for egg quality by collecting a sample of one egg per bird, during three consecutive days, starting on the 14th d of production. Analyses were performed using mixed models including the random epigenetic effect. Variance components were estimated by the restricted maximum likelihood method. A grid-search for values for the auto-recursive parameter (λ) was used in the variance components estimation. This parameter is directly related to the reset (v) and epigenetic transmissibility (1 − v) coefficients. The epigenetic effect was not significant for any of the egg quality traits evaluated. Direct heritability estimates for egg quality traits ranged in magnitude from 0.06 to 0.33, whereby the higher estimates were found for AW and SW. Epigenetic heritability estimates were low and close to zero (ranging from 0.00 to 0.07) for all evaluated traits. The current breeding strategies accounting for additive genetic effect seem to be suitable for egg quality traits in meat-type quai