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Genetics, Selection, Evolution: GSE

Sunduimijid Bolormaa, Andrew A Swan, Daniel J Brown, Sue Hatcher, Nasir Moghaddar, Julius H van der Werf, Michael E Goddard, Hans D Daetwyler
BACKGROUND: The application of genomic selection to sheep breeding could lead to substantial increases in profitability of wool production due to the availability of accurate breeding values from single nucleotide polymorphism (SNP) data. Several key traits determine the value of wool and influence a sheep's susceptibility to fleece rot and fly strike. Our aim was to predict genomic estimated breeding values (GEBV) and to compare three methods of combining information across traits to map polymorphisms that affect these traits...
August 15, 2017: Genetics, Selection, Evolution: GSE
Qianqian Zhang, Mario P L Calus, Bernt Guldbrandtsen, Mogens Sandø Lund, Goutam Sahana
BACKGROUND: Whole-genome sequencing and imputation methodologies have enabled the study of the effects of genomic variants with low to very low minor allele frequency (MAF) on variation in complex traits. Our objective was to estimate the proportion of variance explained by imputed sequence variants classified according to their MAF compared with the variance explained by the pedigree-based additive genetic relationship matrix for 17 traits in Nordic Holstein dairy cattle. RESULTS: Imputed sequence variants were grouped into seven classes according to their MAF (0...
August 1, 2017: Genetics, Selection, Evolution: GSE
Breno O Fragomeni, Daniela A L Lourenco, Yukata Masuda, Andres Legarra, Ignacy Misztal
BACKGROUND: Much effort is put into identifying causative quantitative trait nucleotides (QTN) in animal breeding, empowered by the availability of dense single nucleotide polymorphism (SNP) information. Genomic selection using traditional SNP information is easily implemented for any number of genotyped individuals using single-step genomic best linear unbiased predictor (ssGBLUP) with the algorithm for proven and young (APY). Our aim was to investigate whether ssGBLUP is useful for genomic prediction when some or all QTN are known...
July 26, 2017: Genetics, Selection, Evolution: GSE
Miriam Piles, Ingrid David, Josep Ramon, Laurianne Canario, Oriol Rafel, Mariam Pascual, Mohamed Ragab, Juan P Sánchez
BACKGROUND: Most rabbit production farms apply feed restriction at fattening because of its protective effect against digestive diseases that affect growing rabbits. However, it leads to competitive behaviour between cage mates, which is not observed when animals are fed ad libitum. Our aim was to estimate the contribution of direct ([Formula: see text]) and social ([Formula: see text]) genetic effects (also known as indirect genetic effects) to total heritable variance of average daily gain ([Formula: see text]) in rabbits on different feeding regimens (FR), and the magnitude of the interaction between genotype and FR (G × FR)...
July 20, 2017: Genetics, Selection, Evolution: GSE
David M Howard, Ricardo Pong-Wong, Pieter W Knap, John A Woolliams
BACKGROUND: Lethal recessive genetic variants are maintained at relatively low frequencies in a population in the heterozygous state, but by definition are fatal and therefore unobserved in the homozygous state. Since haplotypes allow the tagging of rare and untyped genetic variants, they have potential for studying lethal recessive variants. In this study, we used a large commercial population to identify putative lethal recessive haplotypes that impact either the total number born (TNB) or the number born alive (NBA) as a proportion of the total number born (NBA/TNB)...
July 14, 2017: Genetics, Selection, Evolution: GSE
Min Wang, Timothy P Hancock, Iona M MacLeod, Jennie E Pryce, Benjamin G Cocks, Benjamin J Hayes
BACKGROUND: Enhancers are non-coding DNA sequences, which when they are bound by specific proteins increase the level of gene transcription. Enhancers activate unique gene expression patterns within cells of different types or under different conditions. Enhancers are key contributors to gene regulation, and causative variants that affect quantitative traits in humans and mice have been located in enhancer regions. However, in the bovine genome, enhancers as well as other regulatory elements are not yet well defined...
July 6, 2017: Genetics, Selection, Evolution: GSE
Serap Gonen, Mara Battagin, Susan E Johnston, Gregor Gorjanc, John M Hickey
BACKGROUND: This study uses simulation to explore and quantify the potential effect of shifting recombination hotspots on genetic gain in livestock breeding programs. METHODS: We simulated three scenarios that differed in the locations of quantitative trait nucleotides (QTN) and recombination hotspots in the genome. In scenario 1, QTN were randomly distributed along the chromosomes and recombination was restricted to occur within specific genomic regions (i.e. recombination hotspots)...
July 4, 2017: Genetics, Selection, Evolution: GSE
Melanie Hess, Tom Druet, Andrew Hess, Dorian Garrick
BACKGROUND: Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle...
July 3, 2017: Genetics, Selection, Evolution: GSE
Floor Biemans, Mart C M de Jong, Piter Bijma
BACKGROUND: Infectious diseases in farm animals affect animal health, decrease animal welfare and can affect human health. Selection and breeding of host individuals with desirable traits regarding infectious diseases can help to fight disease transmission, which is affected by two types of (genetic) traits: host susceptibility and host infectivity. Quantitative genetic studies on infectious diseases generally connect an individual's disease status to its own genotype, and therefore capture genetic effects on susceptibility only...
June 30, 2017: Genetics, Selection, Evolution: GSE
Marcos S Lopes, Henk Bovenhuis, André M Hidalgo, Johan A M van Arendonk, Egbert F Knol, John W M Bastiaansen
BACKGROUND: Breed-specific effects are observed when the same allele of a given genetic marker has a different effect depending on its breed origin, which results in different allele substitution effects across breeds. In such a case, single-breed breeding values may not be the most accurate predictors of crossbred performance. Our aim was to estimate the contribution of alleles from each parental breed to the genetic variance of traits that are measured in crossbred offspring, and to compare the prediction accuracies of estimated direct genomic values (DGV) from a traditional genomic selection model (GS) that are trained on purebred or crossbred data, with accuracies of DGV from a model that accounts for breed-specific effects (BS), trained on purebred or crossbred data...
June 26, 2017: Genetics, Selection, Evolution: GSE
Adeniyi C Adeola, Olufunke O Oluwole, Bukola M Oladele, Temilola O Olorungbounmi, Bamidele Boladuro, Sunday C Olaogun, Lotanna M Nneji, Oscar J Sanke, Philip M Dawuda, Ofelia G Omitogun, Laurent Frantz, Robert W Murphy, Hai-Bing Xie, Min-Sheng Peng, Ya-Ping Zhang
BACKGROUND: The history of pig populations in Africa remains controversial due to insufficient evidence from archaeological and genetic data. Previously, a Western ancestry for West African pigs was reported based on loci that are involved in the determination of coat color. We investigated the genetic diversity of Nigerian indigenous pigs (NIP) by simultaneously analyzing variation in mitochondrial DNA (mtDNA), Y-chromosome sequence and the melanocortin receptor 1 (MC1R) gene. RESULTS: Median-joining network analysis of mtDNA D-loop sequences from 201 NIP and previously characterized loci clustered NIP with populations from the West (Europe/North Africa) and East/Southeast Asia...
June 26, 2017: Genetics, Selection, Evolution: GSE
Vinzent Boerner
BACKGROUND: Parentage verification by molecular markers is mainly based on short tandem repeat markers. Single nucleotide polymorphisms (SNPs) as bi-allelic markers have become the markers of choice for genotyping projects. Thus, the subsequent step is to use SNP genotypes for parentage verification as well. Recent developments of algorithms such as evaluating opposing homozygous SNP genotypes have drawbacks, for example the inability of rejecting all animals of a sample of potential parents...
June 15, 2017: Genetics, Selection, Evolution: GSE
Bruna P Sollero, Vinícius S Junqueira, Cláudia C G Gomes, Alexandre R Caetano, Fernando F Cardoso
BACKGROUND: Cattle resistance to ticks is known to be under genetic control with a complex biological mechanism within and among breeds. Our aim was to identify genomic segments and tag single nucleotide polymorphisms (SNPs) associated with tick-resistance in Hereford and Braford cattle. The predictive performance of a very low-density tag SNP panel was estimated and compared with results obtained with a 50 K SNP dataset. RESULTS: BayesB (π = 0.99) was initially applied in a genome-wide association study (GWAS) for this complex trait by using deregressed estimated breeding values for tick counts and 41,045 SNP genotypes from 3455 animals raised in southern Brazil...
June 15, 2017: Genetics, Selection, Evolution: GSE
Agustín Blasco, Marina Martínez-Álvaro, Maria-Luz García, Noelia Ibáñez-Escriche, María-José Argente
BACKGROUND: In recent years, there has been an increasing interest in the genetic determination of environmental variance. In the case of litter size, environmental variance can be related to the capacity of animals to adapt to new environmental conditions, which can improve animal welfare. RESULTS: We developed a ten-generation divergent selection experiment on environmental variance. We selected one line of rabbits for litter size homogeneity and one line for litter size heterogeneity by measuring intra-doe phenotypic variance...
May 22, 2017: Genetics, Selection, Evolution: GSE
Serap Gonen, Roger Ros-Freixedes, Mara Battagin, Gregor Gorjanc, John M Hickey
BACKGROUND: This paper describes a method, called AlphaSeqOpt, for the allocation of sequencing resources in livestock populations with existing phased genomic data to maximise the ability to phase and impute sequenced haplotypes into the whole population. METHODS: We present two algorithms. The first selects focal individuals that collectively represent the maximum possible portion of the haplotype diversity in the population. The second allocates a fixed sequencing budget among the families of focal individuals to enable phasing of their haplotypes at the sequence level...
May 18, 2017: Genetics, Selection, Evolution: GSE
Pierre Faux, Tom Druet
BACKGROUND: Haplotype reconstruction (phasing) is an essential step in many applications, including imputation and genomic selection. The best phasing methods rely on both familial and linkage disequilibrium (LD) information. With whole-genome sequence (WGS) data, relatively small samples of reference individuals are generally sequenced due to prohibitive sequencing costs, thus only a limited amount of familial information is available. However, reference individuals have many relatives that have been genotyped (at lower density)...
May 16, 2017: Genetics, Selection, Evolution: GSE
Yu Wang, Jörn Bennewitz, Robin Wellmann
BACKGROUND: Optimum contribution selection (OCS) is effective for increasing genetic gain, controlling the rate of inbreeding and enables maintenance of genetic diversity. However, this diversity may be caused by high migrant contributions (MC) in the population due to introgression of genetic material from other breeds, which can threaten the conservation of small local populations. Therefore, breeding objectives should not only focus on increasing genetic gains but also on maintaining genetic originality and diversity of native alleles...
May 12, 2017: Genetics, Selection, Evolution: GSE
Jérémie Vandenplas, Jack J Windig, Mario P L Calus
BACKGROUND: In crossbreeding programs, various genomic prediction models have been proposed for using phenotypic records of crossbred animals to increase the selection response for crossbred performance in purebred animals. A possible model is a model that assumes identical single nucleotide polymorphism (SNP) effects for the crossbred performance trait across breeds (ASGM). Another model is a genomic model that assumes breed-specific effects of SNP alleles (BSAM) for crossbred performance...
May 12, 2017: Genetics, Selection, Evolution: GSE
Lingzhao Fang, Goutam Sahana, Peipei Ma, Guosheng Su, Ying Yu, Shengli Zhang, Mogens Sandø Lund, Peter Sørensen
BACKGROUND: A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. RESULTS: We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features...
May 12, 2017: Genetics, Selection, Evolution: GSE
Brendan M Duggan, Anne M Rae, Dylan N Clements, Paul M Hocking
BACKGROUND: Genetic progress in selection for greater body mass and meat yield in poultry has been associated with an increase in gait problems which are detrimental to productivity and welfare. The incidence of suboptimal gait in breeding flocks is controlled through the use of a visual gait score, which is a subjective assessment of walking ability of each bird. The subjective nature of the visual gait score has led to concerns over its effectiveness in reducing the incidence of suboptimal gait in poultry through breeding...
May 2, 2017: Genetics, Selection, Evolution: GSE
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