Many of the world's agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two subspecies, Bos taurus indicus (Bos indicus) and Bos taurus taurus (Bos taurus). Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations.
View Article and Find Full Text PDFCopy number variants (CNVs) are a type of genetic polymorphism which contribute to phenotypic variation in several species, including livestock. In this study, we used genomic data of 192 animals from 3 Iranian sheep breeds including 96 Baluchi sheep and 47 Lori-Bakhtiari sheep as fat-tailed breeds and 47 Zel sheep as thin-tailed sheep breed genotyped with Illumina OvineSNP50K Beadchip arrays. Also, for association test, 70 samples of Valle del Belice sheep were added to the association test as thin-tailed sheep breed.
View Article and Find Full Text PDFPregnancy in cattle is the outcome of the complex process of initiation of cycling, fertilization, maternal recognition of pregnancy and foeto-placental development. Though much is known about initiation of cycling and associated risk factors, there are virtually no data on pregnancy rate per cycle for naturally mated cattle, especially for extensively managed, tropically adapted genotypes, which this study aimed to determine. Tropical composite (Bos indicus and African Sanga crosses with Bos taurus) and Brahman cattle (n = 2,181) of known pedigree in four-year groups at four sites were mated annually for 84 days.
View Article and Find Full Text PDFBackground: A cost-effective strategy to explore the complete DNA sequence in animals for genetic evaluation purposes is to sequence key ancestors of a population, followed by imputation mechanisms to infer marker genotypes that were not originally reported in a target population of animals genotyped with single nucleotide polymorphism (SNP) panels. The feasibility of this process relies on the accuracy of the genotype imputation in that population, particularly for potential causal mutations which may be at low frequency and either within genes or regulatory regions. The objective of the present study was to investigate the imputation accuracy to the sequence level in a Nellore beef cattle population, including that for variants in annotation classes which are more likely to be functional.
View Article and Find Full Text PDFGenome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively.
View Article and Find Full Text PDFBackground: Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance.
View Article and Find Full Text PDFBackground: In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies; including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved.
Methods: Genotypes and phenotypes were obtained from two research herds.
Deciding on the best statistical method to apply when the response variable is ordinal is essential because the way the categories are ordered in the data is relevant as it could change the results of the analysis. Although the models for continuous variables have similarities to those for ordinal variables, this paper presents the advantages of the use of the ordering information on the outcomes with methods developed for modeling ordinal data such as the ordered stereotype model. The novelty of this article lies in showing the dangers of assigning equally spaced scores to ordered response categories in statistical analysis, which are illustrated with a simulation study and a case study.
View Article and Find Full Text PDFInt J Methods Psychiatr Res
December 2019
Objective: The collection and use of ordinal variables are common in many psychological and psychiatric studies. Although the models for continuous variables have similarities to those for ordinal variables, there are advantages when a model developed for modeling ordinal data is used such as avoiding "floor" and "ceiling" effects and avoiding to assign scores, as it happens in continuous models, which can produce results sensitive to the score assigned. This paper introduces and focuses on the application of the ordered stereotype model, which was developed for modeling ordinal outcomes and is not so popular as other models such as linear regression and proportional odds models.
View Article and Find Full Text PDFBackground: Selection of cattle that are less sensitive to environmental variation in unfavorable environments and more adapted to harsh conditions is of primary importance for tropical beef cattle production systems. Understanding the genetic background of sensitivity to environmental variation is necessary for developing strategies and tools to increase efficiency and sustainability of beef production. We evaluated the degree of sensitivity of beef cattle performance to environmental variation, at the animal and molecular marker levels (412 K single nucleotide polymorphisms), by fitting and comparing the results of different reaction norm models (RNM), using a comprehensive dataset of Nellore cattle raised under diverse environmental conditions.
View Article and Find Full Text PDFAim: Cancer burden measured in disability adjusted life years (DALYs) captures survival and disability impacts of incident cancers. In this paper, we estimate the prospective burden of disease arising from 27 cancer sites diagnosed in 2006, by sex and ethnicity; and determine how its distribution differs from that for incidence rates alone.
Methods: Using a prospective approach, Markov and cancer disease models were used to estimate DALYs with inputs of population counts, incidence and excess mortality rates, disability weights, and background mortality.
Relative survival and excess mortality approaches are commonly used to estimate and compare net survival from cancer. These approaches are based on the assumption that the underlying (non-cancer) mortality rate of cancer patients is the same as that of the general population. This assumption is likely to be violated particularly in the context of smoking-related cancers.
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