Open Access. Powered by Scholars. Published by Universities.®

Animal Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 7 of 7

Full-Text Articles in Animal Sciences

Estimation Of Breeding Values Using Different Densities Of Snp To Inform Kinship In Broiler Chickens, Mayara Salvian, Gabriel Costa Monteiro Moreira, Ândrea Plotzki Reis, Brayan Dias Dauria, Fabrício Pilonetto, Izally Carvalho Gervásio, Mônica Corrêa Ledur, Luiz Lehmann Coutinho, Matthew L. Spangler, Gerson Barreto Mourao Jan 2023

Estimation Of Breeding Values Using Different Densities Of Snp To Inform Kinship In Broiler Chickens, Mayara Salvian, Gabriel Costa Monteiro Moreira, Ândrea Plotzki Reis, Brayan Dias Dauria, Fabrício Pilonetto, Izally Carvalho Gervásio, Mônica Corrêa Ledur, Luiz Lehmann Coutinho, Matthew L. Spangler, Gerson Barreto Mourao

Department of Animal Science: Faculty Publications

Background: Traditionally, breeding values are estimated based on phenotypic and pedigree information using the numerator relationship (A) matrix. With the availability of genomic information, genome-wide markers can be included in the estimation of breeding values through genomic kinship. However, the density of genomic information used can impact the cost of implementation. The aim of this study was to compare the rank, accuracy, and bias of estimated breeding values (EBV) for organs [heart (HRT), liver (LIV), gizzard (GIZ), lungs (LUN)] and carcass [breast (BRST), drumstick (DRM) and thigh (THG)] weight traits in a broiler population using pedigree-based BLUP (PBLUP) and …


Using Pooled Data For Genomic Prediction In A Bivariate Framework With Missing Data, Johnna L. Baller, Stephen D. Kachman, Larry A. Kuehn, Matthew L. Spangler May 2022

Using Pooled Data For Genomic Prediction In A Bivariate Framework With Missing Data, Johnna L. Baller, Stephen D. Kachman, Larry A. Kuehn, Matthew L. Spangler

Department of Animal Science: Faculty Publications

Pooling samples to derive group genotypes can enable the economically efficient use of commercial animals within genetic evaluations. To test a multivariate framework for genetic evaluations using pooled data, simulation was used to mimic a beef cattle population including two moderately heritable traits with varying genetic correlations, genotypes and pedigree data. There were 15 generations (n = 32,000; random selection and mating), and the last generation was subjected to genotyping through pooling. Missing records were induced in two ways: (a) sequential culling and (b) random missing records. Gaps in genotyping were also explored whereby genotyping occurred through generation 13 …


Accuracy Of Gebv Of Sires Based On Pooled Allele Frequency Of Their Progeny, Napoleón Vargas Jurado, Larry A. Kuehn, John W. Keele, Ronald M. Lewis Jan 2021

Accuracy Of Gebv Of Sires Based On Pooled Allele Frequency Of Their Progeny, Napoleón Vargas Jurado, Larry A. Kuehn, John W. Keele, Ronald M. Lewis

Roman L. Hruska U.S. Meat Animal Research Center: Reports

Despite decreasing genotyping costs, in some cases individually genotyping animals is not economically feasible (e.g., in small ruminants). An alternative is to pool DNA, using the pooled allele frequency (PAF) to garner information on performance. Still, the use of PAF for prediction (estimation of genomic breeding values; GEBVs) has been limited. Two potential sources of error on accuracy of GEBV of sires, obtained from PAF of their progeny themselves lacking pedigree information, were tested: (i) pool construction error (unequal contribution of DNA from animals in pools), and (ii) technical error (variability when reading the array). Pooling design (random, extremes, K-means), …


Do Stronger Measures Of Genomic Connectedness Enhance Prediction Accuracies Across Management Units?, Haipeng Yu, Matthew L. Spangler, Ronald M. Lewis, Gota Morota Jan 2018

Do Stronger Measures Of Genomic Connectedness Enhance Prediction Accuracies Across Management Units?, Haipeng Yu, Matthew L. Spangler, Ronald M. Lewis, Gota Morota

Department of Animal Science: Faculty Publications

Genetic connectedness assesses the extent to which estimated breeding values can be fairly compared across management units. Ranking of individuals across units based on best linear unbiased prediction (BLUP) is reliable when there is a sufficient level of connectedness due to a better disentangling of genetic signal from noise. Connectedness arises from genetic relationships among individuals. Although a recent study showed that genomic relatedness strengthens the estimates of connectedness across management units compared with that of pedigree, the relationship between connectedness measures and prediction accuracies only has been explored to a limited extent. In this study, we examined whether increased …


The Impact Of Training Strategies On The Accuracy Of Genomic Predictors In United States Red Angus Cattle, J. Lee, Stephen D. Kachman, Matthew L. Spangler Jan 2017

The Impact Of Training Strategies On The Accuracy Of Genomic Predictors In United States Red Angus Cattle, J. Lee, Stephen D. Kachman, Matthew L. Spangler

Department of Animal Science: Faculty Publications

Genomic selection (GS) has become an integral part of genetic evaluation methodology and has been applied to all major livestock species, including beef and dairy cattle, pigs, and chickens. Significant contributions in increased accuracy of selection decisions have been clearly illustrated in dairy cattle after practical application of GS. In the majority of U.S. beef cattle breeds, similar efforts have also been made to increase the accuracy of genetic merit estimates through the inclusion of genomic information into routine genetic evaluations using a variety of methods. However, prediction accuracies can vary relative to panel density, the number of folds used …


Genetic And Genomic Basis Of Antibody Response To Porcine Reproductive And Respiratory Syndrome (Prrs) In Gilts And Sows, Nick V. Serão, Robert A. Kemp, Benny Mote, Philip Willson, John C.S. Harding, Stephen C. Bishop, Graham S. Plastow, Jack C.M. Dekkers Jan 2016

Genetic And Genomic Basis Of Antibody Response To Porcine Reproductive And Respiratory Syndrome (Prrs) In Gilts And Sows, Nick V. Serão, Robert A. Kemp, Benny Mote, Philip Willson, John C.S. Harding, Stephen C. Bishop, Graham S. Plastow, Jack C.M. Dekkers

Department of Animal Science: Faculty Publications

Background: Our recent research showed that antibody response to porcine reproductive and respiratory syndrome (PRRS), measured as sample-to-positive (S/P) ratio, is highly heritable and has a high genetic correlation with reproductive performance during a PRRS outbreak. Two major quantitative trait loci (QTL) on Sus scrofa chromosome 7 (SSC7; QTLMHC and QTL130) accounted for ~40 % of the genetic variance for S/P. Objectives of this study were to estimate genetic parameters for PRRS S/P in gilts during acclimation, identify regions associated with S/P, and evaluate the accuracy of genomic prediction of S/P across populations with different prevalences of …


Evaluation Of Reduced Subsets Of Single Nucleotide Polymorphisms For The Prediction Of Age At Puberty In Sows, Katherine L. Lucot, Matthew L. Spangler, Melanie D. Trenhaile, Stephen D. Kachman, Daniel C. Ciobanu Aug 2015

Evaluation Of Reduced Subsets Of Single Nucleotide Polymorphisms For The Prediction Of Age At Puberty In Sows, Katherine L. Lucot, Matthew L. Spangler, Melanie D. Trenhaile, Stephen D. Kachman, Daniel C. Ciobanu

Department of Animal Science: Faculty Publications

Genomic information could be used efficiently to improve traits that are expensive to measure, sex limited or expressed late in life. This study analyzed the phenotypic variation explained by major SNPs and windows for age at puberty in gilts, an indicator of reproductive longevity. A genome-wide association study using 56,424 SNPs explained 25.2% of the phenotypic variation in age at puberty in a training set (n = 820). All SNPs from the top 10% of 1-Mb windows explained 33.5% of the phenotypic variance compared to 47.1% explained by the most informative markers (n = 261). In an evaluation population, consisting …