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Genetics, Selection, Evolution: GSE

Kay Boulton, Matthew J Nolan, Zhiguang Wu, Androniki Psifidi, Valentina Riggio, Kimberley Harman, Stephen C Bishop, Pete Kaiser, Mitchell S Abrahamsen, Rachel Hawken, Kellie A Watson, Fiona M Tomley, Damer P Blake, David A Hume
BACKGROUND: Coccidiosis is a major contributor to losses in poultry production. With emerging constraints on the use of in-feed prophylactic anticoccidial drugs and the relatively high costs of effective vaccines, there are commercial incentives to breed chickens with greater resistance to this important production disease. To identify phenotypic biomarkers that are associated with the production impacts of coccidiosis, and to assess their covariance and heritability, 942 Cobb500 commercial broilers were subjected to a defined challenge with Eimeria tenella (Houghton)...
November 21, 2018: Genetics, Selection, Evolution: GSE
Qianqian Zhang, Goutam Sahana, Guosheng Su, Bernt Guldbrandtsen, Mogens Sandø Lund, Mario P L Calus
BACKGROUND: Availability of whole-genome sequence data for a large number of cattle and efficient imputation methodologies open a new opportunity to include rare and low-frequency variants (RLFV) in genomic prediction in dairy cattle. The objective of this study was to examine the impact of including RLFV that are within genes and selected from whole-genome sequence variants, on the reliability of genomic prediction for fertility, health and longevity in dairy cattle. RESULTS: All genic RLFV with a minor allele frequency lower than 0...
November 20, 2018: Genetics, Selection, Evolution: GSE
Alessandra Stella, Ezequiel Luis Nicolazzi, Curtis P Van Tassell, Max F Rothschild, Licia Colli, Benjamin D Rosen, Tad S Sonstegard, Paola Crepaldi, Gwenola Tosser-Klopp, Stephane Joost
No abstract text is available yet for this article.
November 19, 2018: Genetics, Selection, Evolution: GSE
Licia Colli, Marco Milanesi, Andrea Talenti, Francesca Bertolini, Minhui Chen, Alessandra Crisà, Kevin Gerard Daly, Marcello Del Corvo, Bernt Guldbrandtsen, Johannes A Lenstra, Benjamin D Rosen, Elia Vajana, Gennaro Catillo, Stéphane Joost, Ezequiel Luis Nicolazzi, Estelle Rochat, Max F Rothschild, Bertrand Servin, Tad S Sonstegard, Roberto Steri, Curtis P Van Tassell, Paolo Ajmone-Marsan, Paola Crepaldi, Alessandra Stella
BACKGROUND: Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats...
November 19, 2018: Genetics, Selection, Evolution: GSE
Andrea Talenti, Isabelle Palhière, Flavie Tortereau, Giulio Pagnacco, Alessandra Stella, Ezequiel L Nicolazzi, Paola Crepaldi, Gwenola Tosser-Klopp
BACKGROUND: International standard panels of single nucleotide polymorphisms (SNPs) have replaced microsatellites in several species for parentage assessment and assignment (PA) purposes. However, such a resource is still lacking in goats. The application of a cheap tool for PA would help the management of goat populations by improving the reliability of pedigree registration and, consequently, allow a better implementation of breeding schemes or conservation programs. RESULTS: Using data from the current GoatSNP50 chip, starting from a worldwide dataset of more than 4000 animals belonging to more than 140 breeds and populations from the AdaptMap initiative, we selected a panel of 195 SNPs...
November 19, 2018: Genetics, Selection, Evolution: GSE
Francesca Bertolini, Tainã Figueiredo Cardoso, Gabriele Marras, Ezequiel L Nicolazzi, Max F Rothschild, Marcel Amills
BACKGROUND: Patterns of homozygosity can be influenced by several factors, such as demography, recombination, and selection. Using the goat SNP50 BeadChip, we genotyped 3171 goats belonging to 117 populations with a worldwide distribution. Our objectives were to characterize the number and length of runs of homozygosity (ROH) and to detect ROH hotspots in order to gain new insights into the consequences of neutral and selection processes on the genome-wide homozygosity patterns of goats...
November 19, 2018: Genetics, Selection, Evolution: GSE
Taina F Cardoso, Marcel Amills, Francesca Bertolini, Max Rothschild, Gabriele Marras, Geert Boink, Jordi Jordana, Juan Capote, Sean Carolan, Jón H Hallsson, Juha Kantanen, Agueda Pons, Johannes A Lenstra
BACKGROUND: Genetic isolation of breeds may result in a significant loss of diversity and have consequences on health and performance. In this study, we examined the effect of geographic isolation on caprine genetic diversity patterns by genotyping 480 individuals from 25 European and African breeds with the Goat SNP50 BeadChip and comparing patterns of homozygosity of insular and nearby continental breeds. RESULTS: Among the breeds analysed, number and total length of ROH varied considerably and depending on breeds, ROH could cover a substantial fraction of the genome (up to 1...
November 19, 2018: Genetics, Selection, Evolution: GSE
Francesca Bertolini, Bertrand Servin, Andrea Talenti, Estelle Rochat, Eui Soo Kim, Claire Oget, Isabelle Palhière, Alessandra Crisà, Gennaro Catillo, Roberto Steri, Marcel Amills, Licia Colli, Gabriele Marras, Marco Milanesi, Ezequiel Nicolazzi, Benjamin D Rosen, Curtis P Van Tassell, Bernt Guldbrandtsen, Tad S Sonstegard, Gwenola Tosser-Klopp, Alessandra Stella, Max F Rothschild, Stéphane Joost, Paola Crepaldi
BACKGROUND: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip...
November 19, 2018: Genetics, Selection, Evolution: GSE
Clémence Fraslin, Nicolas Dechamp, Maria Bernard, Francine Krieg, Caroline Hervet, René Guyomard, Diane Esquerré, Johanna Barbieri, Claire Kuchly, Eric Duchaud, Pierre Boudinot, Tatiana Rochat, Jean-François Bernardet, Edwige Quillet
BACKGROUND: Bacterial cold-water disease, which is caused by Flavobacterium psychrophilum, is one of the major diseases that affect rainbow trout (Oncorhynchus mykiss) and a primary concern for trout farming. Better knowledge of the genetic basis of resistance to F. psychrophilum would help to implement this trait in selection schemes and to investigate the immune mechanisms associated with resistance. Various studies have revealed that skin and mucus may contribute to response to infection...
November 16, 2018: Genetics, Selection, Evolution: GSE
Wioleta Drobik-Czwarno, Anna Wolc, Janet E Fulton, Jack C M Dekkers
BACKGROUND: Copy number variations (CNV) are an important source of genetic variation that has gained increasing attention over the last couple of years. In this study, we performed CNV detection and functional analysis for 18,719 individuals from four pure lines and one commercial cross of layer chickens. Samples were genotyped on four single nucleotide polymorphism (SNP) genotyping platforms, i.e. the Illumina 42K, Affymetrix 600K, and two different customized Affymetrix 50K chips. CNV recovered from the Affymetrix chips were identified by using the Axiom® CNV Summary Tools and PennCNV software and those from the Illumina chip were identified by using the cnvPartition in the Genome Studio software...
November 6, 2018: Genetics, Selection, Evolution: GSE
Andres Legarra, Antonio Reverter
BACKGROUND: Cross-validation tools are used increasingly to validate and compare genetic evaluation methods but analytical properties of cross-validation methods are rarely described. There is also a lack of cross-validation tools for complex problems such as prediction of indirect effects (e.g. maternal effects) or for breeding schemes with small progeny group sizes. RESULTS: We derive the expected value of several quadratic forms by comparing genetic evaluations including "partial" and "whole" data...
November 6, 2018: Genetics, Selection, Evolution: GSE
Jérémie Vandenplas, Herwin Eding, Mario P L Calus, Cornelis Vuik
BACKGROUND: The single-step single nucleotide polymorphism best linear unbiased prediction (ssSNPBLUP) method, such as single-step genomic BLUP (ssGBLUP), simultaneously analyses phenotypic, pedigree, and genomic information of genotyped and non-genotyped animals. In contrast to ssGBLUP, SNP effects are fitted explicitly as random effects in the ssSNPBLUP model. Similarly, principal components associated with the genomic information can be fitted explicitly as random effects in a single-step principal component BLUP (ssPCBLUP) model to remove noise in genomic information...
November 3, 2018: Genetics, Selection, Evolution: GSE
Thinh T Chu, Setegn W Alemu, Elise Norberg, Anders C Sørensen, John Henshall, Rachel Hawken, Just Jensen
BACKGROUND: A breeding program for commercial broiler chicken that is carried out under strict biosecure conditions can show reduced genetic gain due to genotype by environment interactions (G × E) between bio-secure (B) and commercial production (C) environments. Accuracy of phenotype-based best linear unbiased prediction of breeding values of selection candidates using sib-testing in C is low. Genomic prediction based on dense genetic markers may improve accuracy of selection. Stochastic simulation was used to explore the benefits of genomic selection in breeding schemes for broiler chicken that include birds in both B and C for assessment of phenotype...
November 3, 2018: Genetics, Selection, Evolution: GSE
Graham Lough, Andrew Hess, Melanie Hess, Hamed Rashidi, Oswald Matika, Joan K Lunney, Raymond R R Rowland, Ilias Kyriazakis, Han A Mulder, Jack C M Dekkers, Andrea Doeschl-Wilson
BACKGROUND: High resistance (the ability of the host to reduce pathogen load) and tolerance (the ability to maintain high performance at a given pathogen load) are two desirable host traits for producing animals that are resilient to infections. For Porcine Reproductive and Respiratory Syndrome (PRRS), one of the most devastating swine diseases worldwide, studies have identified substantial genetic variation in resistance of pigs, but evidence for genetic variation in tolerance has so far been inconclusive...
October 24, 2018: Genetics, Selection, Evolution: GSE
Biaty Raymond, Aniek C Bouwman, Yvonne C J Wientjes, Chris Schrooten, Jeanine Houwing-Duistermaat, Roel F Veerkamp
BACKGROUND: Genomic prediction (GP) accuracy in numerically small breeds is limited by the small size of the reference population. Our objective was to test a multi-breed multiple genomic relationship matrices (GRM) GP model (MBMG) that weighs pre-selected markers separately, uses the remaining markers to explain the remaining genetic variance that can be explained by markers, and weighs information of breeds in the reference population by their genetic correlation with the validation breed...
October 10, 2018: Genetics, Selection, Evolution: GSE
Everestus C Akanno, Liuhong Chen, Mohammed K Abo-Ismail, John J Crowley, Zhiquan Wang, Changxi Li, John A Basarab, Michael D MacNeil, Graham S Plastow
BACKGROUND: Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations. METHODS: Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle...
October 5, 2018: Genetics, Selection, Evolution: GSE
Kasper Janssen, Hans Komen, Helmut W Saatkamp, Mart C M de Jong, Piter Bijma
BACKGROUND: Macroparasites, such as ticks, lice, and helminths, are a concern in livestock and aquaculture production, and can be controlled by genetic improvement of the host population. Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. [Formula: see text], which is the appropriate breeding goal trait. This study aims at providing a method to derive the economic value of [Formula: see text]...
October 3, 2018: Genetics, Selection, Evolution: GSE
Stephanie M Matheson, Grant A Walling, Sandra A Edwards
BACKGROUND: In polytocous livestock species, litter size and offspring weight act antagonistically; in modern pig breeds, selection for increased litter size has resulted in lower mean birth weights, an increased number of small piglets and an increased number of those affected by varying degrees of intrauterine growth retardation (IUGR). IUGR poses life-long challenges, both mental, with morphological brain changes and altered cognition, and physical, such as immaturity of organs, reduced colostrum intake and weight gain...
September 18, 2018: Genetics, Selection, Evolution: GSE
Andrew Whalen, Gregor Gorjanc, Roger Ros-Freixedes, John M Hickey
BACKGROUND: In this paper, we review the performance of various hidden Markov model-based imputation methods in animal breeding populations. Traditionally, pedigree and heuristic-based imputation methods have been used for imputation in large animal populations due to their computational efficiency, scalability, and accuracy. Recent advances in the area of human genetics have increased the ability of probabilistic hidden Markov model methods to perform accurate phasing and imputation in large populations...
September 17, 2018: Genetics, Selection, Evolution: GSE
Mehdi Momen, Gota Morota
BACKGROUND: Genetic connectedness is classically used as an indication of the risk associated with breeding value comparisons across management units because genetic evaluations based on best linear unbiased prediction rely for their success on sufficient linkage among different units. In the whole-genome prediction era, the concept of genetic connectedness can be extended to measure a connectedness level between reference and validation sets. However, little is known regarding (1) the impact of non-additive gene action on genomic connectedness measures and (2) the relationship between the estimated level of connectedness and prediction accuracy in the presence of non-additive genetic variation...
September 17, 2018: Genetics, Selection, Evolution: GSE
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