Identification of biological pathways and putative candidate genes for residual feed intake in a tropically adapted beef cattle breed by plasma proteome analysis.

This study identified potential biomarkers for feed efficiency by blood plasma proteome analysis of a tropically adapted beef cattle breed. Two experimental groups were selected based on residual feed intake (RFI). The proteome was investigated by LC-MS/MS in a data-dependent acquisition mode.

Combining large broiler populations into a single genomic evaluation: dealing with genetic divergence.

Combining breeding populations that have diverged at some point is a conventional practice, particularly in the poultry industry, where generation intervals are short and genetic evaluations should be frequently available. This study aimed to assess the feasibility of combining large, distantly genetically connected broiler populations into a single genomic evaluation within the single-step GBLUP framework. The pedigree data for broiler lines 1 and 2 consisted of 428,790 and 477,488 animals, being 156,088 and 186,387 genotyped, respectively.

Proteomic identification of potential biomarkers for heat tolerance in Caracu beef cattle using high and low thermotolerant groups.

Background: Heat stress has deleterious effects on physiological and performance traits in livestock. Within this context, using tropically adapted cattle breeds in pure herds or terminal crossbreeding schemes to explore heterosis is attractive for increasing animal production in warmer climate regions. This study aimed to identify biological processes, pathways, and potential biomarkers related to thermotolerance in Caracu, a tropically adapted beef cattle breed, by proteomic analysis of blood plasma.

Transforming estimated breeding values from observed to probability scale: how to make categorical data analyses more efficient.

Threshold models are often used in genetic analysis of categorical data, such as calving ease. Solutions in the liability scale are easily transformed into probabilities; therefore, estimated breeding values are published as the probability of expressing the category of main interest and are the industry's gold standard because they are easy to interpret and use for selection. However, because threshold models involve nonlinear equations and probability functions, implementing such a method is complex.

Marker effect p-values for single-step GWAS with the algorithm for proven and young in large genotyped populations.

Background: Single-nucleotide polymorphism (SNP) effects can be backsolved from ssGBLUP genomic estimated breeding values (GEBV) and used for genome-wide association studies (ssGWAS). However, obtaining p-values for those SNP effects relies on the inversion of dense matrices, which poses computational limitations in large genotyped populations. In this study, we present a method to approximate SNP p-values for ssGWAS with many genotyped animals.

Reviewing the definition of mortality in broiler chickens and its implications in genomic evaluations.

Mortality is an economically important trait usually handled as a discrete outcome from hatch time until selection in most broiler breeder programs. However, in other species, it has been shown that not only does the genetic component change over time, but also there are maternal genetic effects to be considered when mortality is recorded early in life. This study aimed to investigate alternative trait definitions of mortality with varying models and effects.

Comparing algorithms to approximate accuracies for single-step genomic best linear unbiased predictor.

The exact accuracy of estimated breeding values can be calculated based on the prediction error variances obtained from the diagonal of the inverse of the left-hand side (LHS) of the mixed model equations (MME). However, inverting the LHS is not computationally feasible for large datasets, especially if genomic information is available. Thus, different algorithms have been proposed to approximate accuracies.

Converting estimated breeding values from the observed to probability scale for health traits.

Dairy cattle health traits are paramount from a welfare and economic viewpoint, and modern breeding programs therefore prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.

Single nucleotide polymorphism profile for quantitative trait nucleotide in populations with small effective size and its impact on mapping and genomic predictions.

Increasing SNP density by incorporating sequence information only marginally increases prediction accuracies of breeding values in livestock. To find out why, we used statistical models and simulations to investigate the shape of distribution of estimated SNP effects (a profile) around quantitative trait nucleotides (QTNs) in populations with a small effective population size (Ne). A QTN profile created by averaging SNP effects around each QTN was similar to the shape of expected pairwise linkage disequilibrium (PLD) based on Ne and genetic distance between SNP, with a distinct peak for the QTN.

Genome-wide association study considering genotype-by-environment interaction for productive and reproductive traits using whole-genome sequencing in Nellore cattle.

Background: The genotype-by-environment interaction (GxE) in beef cattle can be investigated using reaction norm models to assess environmental sensitivity and, combined with genome-wide association studies (GWAS), to map genomic regions related to animal adaptation. Including genetic markers from whole-genome sequencing in reaction norm (RN) models allows us to identify high-resolution candidate genes across environmental gradients through GWAS. Hence, we performed a GWAS via the RN approach using whole-genome sequencing data, focusing on mapping candidate genes associated with the expression of reproductive and growth traits in Nellore cattle.

Potential negative effects of genomic selection.

Initial findings on genomic selection (GS) indicated substantial improvement for major traits, such as performance, and even successful selection for antagonistic traits. However, recent unofficial reports indicate an increased frequency of deterioration of secondary traits. This phenomenon may arise due to the mismatch between the accelerated selection process and resource allocation.

Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP.

Brazilian livestock breeding programmes strive to enhance the genetics of beef cattle, with a strong emphasis on the Nellore breed, which has an extensive database and has achieved significant genetic progress in the last years. There are other indicine breeds that are economically important in Brazil; however, these breeds have more modest sets of phenotypes, pedigree and genotypes, slowing down their genetic progress as their predictions are less accurate. Combining several breeds in a multi-breed evaluation could help enhance predictions for those breeds with less information available.

Estimating genetic parameters of digital behavior traits and their relationship with production traits in purebred pigs.

Background: With the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and rate of genetic gain in animal production. It is of interest to assess how behavioral traits are indirectly related to the production traits during the performance testing period. The aim of this study was to assess the quality of behavior data extracted from day-wise video recordings and estimate the genetic parameters of behavior traits and their phenotypic and genetic correlations with production traits in pigs.

Estimation of heritability with genomic information by method R.

Estimating heritabilities with large genomic models by established methods such as restricted maximum likelihood (REML) or Bayesian via Gibbs sampling is computationally expensive. Alternatively, heritability can be estimated indirectly by method R and by maximum predictivity, referred to as MaxPred here, at a much lower computing cost. By method R, the heritability used for predictions with whole and partial data is considered the best estimate when the predictions based on partial data are unbiased relative to those with the complete data.

Confidence intervals for validation statistics with data truncation in genomic prediction.

Background: Validation by data truncation is a common practice in genetic evaluations because of the interest in predicting the genetic merit of a set of young selection candidates. Two of the most used validation methods in genetic evaluations use a single data partition: predictivity or predictive ability (correlation between pre-adjusted phenotypes and estimated breeding values (EBV) divided by the square root of the heritability) and the linear regression (LR) method (comparison of "early" and "late" EBV). Both methods compare predictions with the whole dataset and a partial dataset that is obtained by removing the information related to a set of validation individuals.

Caregivers' concerns through health professionals' eyes.

Objectives: Advancements in medicine and science have enabled more and more people to live longer with a chronic medical condition, namely cancer. Nevertheless, the palliative care (PC) approach continues to be introduced and incorporated later in the lives of patients and families dealing with such conditions. Thus, the need for individuals to care for this population in our society is increasing, giving rise to the so-called "informal caregivers.

Genomic analysis of feed efficiency traits in beef cattle using random regression models.

Feed efficiency plays a major role in the overall profitability and sustainability of the beef cattle industry, as it is directly related to the reduction of the animal demand for input and methane emissions. Traditionally, the average daily feed intake and weight gain are used to calculate feed efficiency traits. However, feed efficiency traits can be analysed longitudinally using random regression models (RRMs), which allow fitting random genetic and environmental effects over time by considering the covariance pattern between the daily records.

Derivation of indirect predictions using genomic recursions across generations in a broiler population.

Genomic estimated breeding values (GEBV) of animals without phenotypes can be indirectly predicted using recursions on GEBV of a subset. To maximize predictive ability of indirect predictions (IP), the subset must represent the independent chromosome segments segregating in the population. We aimed to 1) determine the number of animals needed in recursions to maximize predictive ability, 2) evaluate equivalency IP-GEBV, and 3) investigate trends in predictive ability of IP derived from recent vs.

Boundaries for genotype, phenotype, and pedigree truncation in genomic evaluations in pigs.

Historical data collection for genetic evaluation purposes is a common practice in animal populations; however, the larger the dataset, the higher the computing power needed to perform the analyses. Also, fitting the same model to historical and recent data may be inappropriate. Data truncation can reduce the number of equations to solve, consequently decreasing computing costs; however, the large volume of genotypes is responsible for most of the increase in computations.

The importance of historically popular sires on the accuracy of genomic predictions of young animals in the US Holstein population.

The dairy industry is known for its extensive use of artificial insemination, which has resulted in a population where most animals can be traced back to only a few sires. Due to their relatedness to the population, old influential sires could still contribute to the accuracy of genomic predictions. The objective of the study was to identify the impact of historically influential sires on the recent population.

Using social interaction models for genetic analysis of skin damage in gilts.

Background: Skin damage is a trait of economic and welfare importance that results from social interactions between animals. These interactions may produce wound signs on the gilt's skin as a result of damage behavior (i.e.