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Genetics, Selection, Evolution: GSE

Rohan L Fernando, Hao Cheng, Bruce L Golden, Dorian J Garrick
BACKGROUND: Two types of models have been used for single-step genomic prediction and genome-wide association studies that include phenotypes from both genotyped animals and their non-genotyped relatives. The two types are breeding value models (BVM) that fit breeding values explicitly and marker effects models (MEM) that express the breeding values in terms of the effects of observed or imputed genotypes. MEM can accommodate a wider class of analyses, including variable selection or mixture model analyses...
December 8, 2016: Genetics, Selection, Evolution: GSE
Roel F Veerkamp, Aniek C Bouwman, Chris Schrooten, Mario P L Calus
BACKGROUND: Whole-genome sequence data is expected to capture genetic variation more completely than common genotyping panels. Our objective was to compare the proportion of variance explained and the accuracy of genomic prediction by using imputed sequence data or preselected SNPs from a genome-wide association study (GWAS) with imputed whole-genome sequence data. METHODS: Phenotypes were available for 5503 Holstein-Friesian bulls. Genotypes were imputed up to whole-genome sequence (13,789,029 segregating DNA variants) by using run 4 of the 1000 bull genomes project...
December 1, 2016: Genetics, Selection, Evolution: GSE
Matti Janhunen, Juha Koskela, Nguyễn Hữu Ninh, Harri Vehviläinen, Heikki Koskinen, Antti Nousiainen, Ngô Phú Thỏa
BACKGROUND: Rainbow trout is an important aquaculture species, which has a worldwide distribution across various production environments. The diverse locations of trout farms involve remarkable variation in environmental factors such as water temperature, which is of major importance for the performance of fish. Thus, robust fish that could thrive under different and suboptimal thermal conditions is a desirable goal for trout breeding. Using a split-family experimental design (40 full-/half-sib groups) for a rainbow trout population derived from the Finnish national breeding program, we studied how two different rearing temperatures (14 and 20 °C) affect feed intake, growth rate and feed conversion ratio in 1-year-old fish...
November 29, 2016: Genetics, Selection, Evolution: GSE
Jinmei Ding, Lele Zhao, Lifeng Wang, Wenjing Zhao, Zhengxiao Zhai, Li Leng, Yuxiang Wang, Chuan He, Yan Zhang, Heping Zhang, Hui Li, He Meng
BACKGROUND: The gastrointestinal tract is populated by a complex and vast microbial network, with a composition that reflects the relationships of the symbiosis, co-metabolism, and co-evolution of these microorganisms with their host. The mechanism that underlies such interactions between the genetics of the host and gut microbiota remains elusive. RESULTS: To understand how genetic variation of the host shapes the gut microbiota and interacts with it to affect the metabolic phenotype of the host, we compared the abundance of microbial taxa and their functional performance between two lines of chickens (fat and lean) that had undergone long-term divergent selection for abdominal fat pad weight, which resulted in a 4...
November 28, 2016: Genetics, Selection, Evolution: GSE
Tao Xiang, Ole Fredslund Christensen, Zulma Gladis Vitezica, Andres Legarra
BACKGROUND: Improved performance of crossbred animals is partly due to heterosis. One of the major genetic bases of heterosis is dominance, but it is seldom used in pedigree-based genetic evaluation of livestock. Recently, a trivariate genomic best linear unbiased prediction (GBLUP) model including dominance was developed, which can distinguish purebreds from crossbred animals explicitly. The objectives of this study were: (1) methodological, to show that inclusion of marker-based inbreeding accounts for directional dominance and inbreeding depression in purebred and crossbred animals, to revisit variance components of additive and dominance genetic effects using this model, and to develop marker-based estimators of genetic correlations between purebred and crossbred animals and of correlations of allele substitution effects between breeds; (2) to evaluate the impact of accounting for dominance effects and inbreeding depression on predictive ability for total number of piglets born (TNB) in a pig dataset composed of two purebred populations and their crossbreds...
November 25, 2016: Genetics, Selection, Evolution: GSE
Smaragda Tsairidou, Susan Brotherstone, Mike Coffey, Stephen C Bishop, John A Woolliams
BACKGROUND: Bovine tuberculosis (bTB) is a disease of significant economic importance and is a persistent animal health problem with implications for public health worldwide. Control of bTB in the UK has relied on diagnosis through the single intradermal comparative cervical test (SICCT). However, limitations in the sensitivity of this test hinder successful eradication and the control of bTB remains a major challenge. Genetic selection for cattle that are more resistant to bTB infection can assist in bTB control...
November 24, 2016: Genetics, Selection, Evolution: GSE
Jeremy T Howard, Francesco Tiezzi, Yijian Huang, Kent A Gray, Christian Maltecca
BACKGROUND: In nucleus populations, regions of the genome that have a high frequency of runs of homozygosity (ROH) occur and are associated with a reduction in genetic diversity, as well as adverse effects on fitness. It is currently unclear whether, and to what extent, ROH stretches persist in the crossbred genome and how genomic management in the nucleus population might impact low diversity regions and its implications on the crossbred genome. METHODS: We calculated a ROH statistic based on lengths of 5 (ROH5) or 10 (ROH10) Mb across the genome for genotyped Landrace (LA), Large White (LW) and Duroc (DU) dams...
November 24, 2016: Genetics, Selection, Evolution: GSE
Matteo Bergamaschi, Alessio Cecchinato, Franco Biasioli, Flavia Gasperi, Bruno Martin, Giovanni Bittante
BACKGROUND: Volatile organic compounds determine important quality traits in cheese. The aim of this work was to infer genetic parameters of the profile of volatile compounds in cheese as revealed by direct-injection mass spectrometry of the headspace gas from model cheeses that were produced from milk samples from individual cows. METHODS: A total of 1075 model cheeses were produced using raw whole-milk samples that were collected from individual Brown Swiss cows...
November 16, 2016: Genetics, Selection, Evolution: GSE
Mekki Boussaha, Pauline Michot, Rabia Letaief, Chris Hozé, Sébastien Fritz, Cécile Grohs, Diane Esquerré, Amandine Duchesne, Romain Philippe, Véronique Blanquet, Florence Phocas, Sandrine Floriot, Dominique Rocha, Christophe Klopp, Aurélien Capitan, Didier Boichard
BACKGROUND: In recent years, several bovine genome sequencing projects were carried out with the aim of developing genomic tools to improve dairy and beef production efficiency and sustainability. RESULTS: In this study, we describe the first French cattle genome variation dataset obtained by sequencing 274 whole genomes representing several major dairy and beef breeds. This dataset contains over 28 million single nucleotide polymorphisms (SNPs) and small insertions and deletions...
November 15, 2016: Genetics, Selection, Evolution: GSE
Sithembile O Makina, Lindsey K Whitacre, Jared E Decker, Jeremy F Taylor, Michael D MacNeil, Michiel M Scholtz, Este van Marle-Köster, Farai C Muchadeyi, Mahlako L Makgahlela, Azwihangwisi Maiwashe
BACKGROUND: Understanding the history of cattle breeds is important because it provides the basis for developing appropriate selection and breed improvement programs. In this study, patterns of ancestry and admixture in Afrikaner, Nguni, Drakensberger and Bonsmara cattle of South Africa were investigated. We used 50 K single nucleotide polymorphism genotypes that were previously generated for the Afrikaner (n = 36), Nguni (n = 50), Drakensberger (n = 47) and Bonsmara (n = 44) breeds, and for 394 reference animals representing European taurine, African taurine, African zebu and Bos indicus...
November 15, 2016: Genetics, Selection, Evolution: GSE
Donagh P Berry, Aine O'Brien, Eamonn Wall, Kevin McDermott, Shane Randles, Paul Flynn, Stephen Park, Jenny Grose, Rebecca Weld, Noirin McHugh
BACKGROUND: Accurate genomic analyses are predicated upon access to accurate genotype input data. The objective of this study was to quantify the reproducibility of genotype data that are generated from the same genotype platform and from different genotyping platforms. METHODS: Genotypes based on 51,121 single nucleotide polymorphisms (SNPs) for 84 animals that were each genotyped on Illumina and Affymetrix platforms and for another 25 animals that were each genotyped twice on the same Illumina platform were compared...
November 10, 2016: Genetics, Selection, Evolution: GSE
Fernanda S S Raidan, Dalinne C C Santos, Mariana M Moraes, Andresa E M Araújo, Henrique T Ventura, José A G Bergmann, Eduardo M Turra, Fabio L B Toral
BACKGROUND: Central testing is used to select young bulls which are likely to contribute to increased net income of the commercial beef cattle herd. We present genetic parameters for growth and reproductive traits on performance-tested young bulls and commercial animals that are raised on pasture and in feedlots. METHODS: Records on young bulls and heifers in performance tests or commercial herds were used. Genetic parameters for growth and reproductive traits were estimated...
November 9, 2016: Genetics, Selection, Evolution: GSE
Chen Yao, Xiaojin Zhu, Kent A Weigel
BACKGROUND: Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a semi-supervised learning strategy known as the self-training model, and applied this method to genomic prediction of residual feed intake (RFI) in dairy cattle. METHODS: We describe a self-training model that is wrapped around a support vector machine (SVM) algorithm, which enables it to use data from animals with and without measured phenotypes...
November 7, 2016: Genetics, Selection, Evolution: GSE
Irene van den Berg, Didier Boichard, Mogens S Lund
BACKGROUND: Sequence data can potentially increase the reliability of genomic predictions, because such data include causative mutations instead of relying on linkage disequilibrium (LD) between causative mutations and prediction variants. However, the location of the causative mutations is not known, and the presence of many variants that are in low LD with the causative mutations may reduce prediction reliability. Our objective was to investigate whether the use of variants at quantitative trait loci (QTL) that are identified in a multi-breed genome-wide association study (GWAS) for milk, fat and protein yield would increase the reliability of within- and multi-breed genomic predictions in Holstein, Jersey and Danish Red cattle...
November 4, 2016: Genetics, Selection, Evolution: GSE
Ivan Pocrnic, Daniela A L Lourenco, Yutaka Masuda, Ignacy Misztal
BACKGROUND: A genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and Young (APY) through recursion on a small number of core animals. The number of core animals is theoretically linked to effective population size (N e ). In a simulation study, the optimal number of core animals was equal to the number of largest eigenvalues of GRM that explained 98% of its variation. The purpose of this study was to find the optimal number of core animals and estimate N e for different species...
October 31, 2016: Genetics, Selection, Evolution: GSE
Aldemar González-Rodríguez, Sebastián Munilla, Elena F Mouresan, Jhon J Cañas-Álvarez, Clara Díaz, Jesús Piedrafita, Juan Altarriba, Jesús Á Baro, Antonio Molina, Luis Varona
BACKGROUND: Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations...
October 28, 2016: Genetics, Selection, Evolution: GSE
Rohan L Fernando, Hao Cheng, Dorian J Garrick
BACKGROUND: The mixed linear model employed for genomic best linear unbiased prediction (GBLUP) includes the breeding value for each animal as a random effect that has a mean of zero and a covariance matrix proportional to the genomic relationship matrix ([Formula: see text]), where the inverse of [Formula: see text] is required to set up the usual mixed model equations (MME). When only some animals have genomic information, genomic predictions can be obtained by an extension known as single-step GBLUP, where the covariance matrix of breeding values is constructed by combining the pedigree-based additive relationship matrix with [Formula: see text]...
October 27, 2016: Genetics, Selection, Evolution: GSE
Hanne Gro Olsen, Tim Martin Knutsen, Anna M Lewandowska-Sabat, Harald Grove, Torfinn Nome, Morten Svendsen, Mariann Arnyasi, Marte Sodeland, Kristil K Sundsaasen, Sandra Rinne Dahl, Bjørg Heringstad, Hanne H Hansen, Ingrid Olsaker, Matthew Peter Kent, Sigbjørn Lien
BACKGROUND: Clinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region...
October 19, 2016: Genetics, Selection, Evolution: GSE
Gesine Lühken, Stefan Krebs, Sophie Rothammer, Julia Küpper, Boro Mioč, Ingolf Russ, Ivica Medugorac
BACKGROUND: The mode of inheritance of horn status in sheep is far more complex than a superficial analysis might suggest. Observations, which were mostly based on crossbreeding experiments, indicated that the allele that results in horns is dominant in males and recessive in females, and some authors even speculated about the involvement of more than two alleles. However, all recent genome-wide association analyses point towards a very strong effect of a single autosomal locus on ovine chromosome 10, which was narrowed down to a putatively causal insertion polymorphism in the 3'-untranslated region of the relaxin/insulin-like family peptide receptor 2 gene (RXFP2)...
October 19, 2016: Genetics, Selection, Evolution: GSE
Xiaochen Sun, Rohan Fernando, Jack Dekkers
BACKGROUND: Traditional genomic prediction models using multiple regression on single nucleotide polymorphisms (SNPs) genotypes exploit associations between genotypes of quantitative trait loci (QTL) and SNPs, which can be created by historical linkage disequilibrium (LD), recent co-segregation (CS) and pedigree relationships. Results from field data analyses show that prediction accuracy is usually much higher for individuals that are close relatives of the training population than for distantly related individuals...
October 11, 2016: Genetics, Selection, Evolution: GSE
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