bluuebunny/crossref_metadata_2025_split huggingface dataset:
A periodic analysis of longitudinal binary responses: a case study of clinical mastitis in Norwegian Red cows
Authors: Chang Yu-mei , Gianola Daniel , Heringstad Bjørg , Klemetsdal Gunnar 
Published: June 2009

Abstract
A Bayesian procedure for analyzing longitudinal binary responses using a periodic cosine function was developed. It was assumed that, after adjustment for "seasonal" effects, the oscillation of the underlying latent variables for longitudinal binary responses was a stationary series. Based on this assumption, a single dimension sinusoidal analysis of longitudinal binary responses using the Gibbs sampling and Metropolis algorithms was implemented in a study of clinical mastitis records of Norwegian Red cows taken over five lactations.
Within-family marker-assisted selection for aquaculture species
Authors: Sonesson Anna K. 
Published: June 2009

Abstract
A within-family marker-assisted selection scheme was designed for typical aquaculture breeding schemes, where most traits are recorded on sibs of the candidates. Here, sibs of candidates were tested for the trait and genotyped to establish genetic marker effects on the trait. BLUP breeding values were calculated, including information of the markers (MAS) or not (NONMAS). These breeding values were identical for all family members in the NONMAS schemes, but differed between family members in the MAS schemes, making within-family selection possible. MAS had up to twice the total genetic gain of the corresponding NONMAS scheme. MAS was somewhat less effective when heritability increased from 0.06 to 0.12 or when the frequency of the positive allele was < 0.5. The relative efficiency of MAS was higher for schemes with more candidates, because of larger fullsib family sizes. MAS was also more efficient when male:female mating ratio changed from 1:1 to 1:5 or when the QTL explained more of the total genetic variation. Four instead of two markers linked to the QTL increased genetic gain somewhat. There was no significant difference in polygenic genetic gain between MAS and NONMAS for most schemes. The rates of inbreeding were lower for MAS than NON-MAS schemes, because fewer full-sibs were selected by MAS.
An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication)
Authors: Lassen Jan , Sørensen Morten Kargo , Madsen Per , Ducrocq Vincent 
Published: June 2009

Abstract
In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.
Quantitative trait loci linked to PRNP gene controlling health and production traits in INRA 401 sheep
Authors: Vitezica Zulma G. , Moreno Carole R. , Lantier Frederic , Lantier Isabelle , Schibler Laurent , Roig Anne , François Dominique , Bouix Jacques , Allain Daniel , Brunel Jean-Claude , Barillet Francis , Elsen Jean-Michel 
Published: June 2009

Abstract
In this study, the potential association of PrP genotypes with health and productive traits was investigated. Data were recorded on animals of the INRA 401 breed from the Bourges-La Sapinière INRA experimental farm. The population consisted of 30 rams and 852 ewes, which produced 1310 lambs. The animals were categorized into three PrP genotype classes: ARR homozygous, ARR heterozygous, and animals without any ARR allele. Two analyses differing in the approach considered were carried out. Firstly, the potential association of the PrP genotype with disease (Salmonella resistance) and production (wool and carcass) traits was studied. The data used included 1042, 1043 and 1013 genotyped animals for the Salmonella resistance, wool and carcass traits, respectively. The different traits were analyzed using an animal model, where the PrP genotype effect was included as a fixed effect. Association analyses do not indicate any evidence of an effect of PrP genotypes on traits studied in this breed. Secondly, a quantitative trait loci (QTL) detection approach using the PRNP gene as a marker was applied on ovine chromosome 13. Interval mapping was used. Evidence for one QTL affecting mean fiber diameter was found at 25 cM from the PRNP gene. However, a linkage between PRNP and this QTL does not imply unfavorable linkage disequilibrium for PRNP selection purposes.
The costs of breed reconstruction from cryopreserved material in mammalian livestock species
Authors: Gandini Gustavo , Pizzi Flavia , Stella Alessandra , Boettcher Paul J 
Published: June 2009

Abstract
The aim of this work was to compare costs, in the horse, cattle, sheep, swine, and rabbit species, for the creation of gene banks for reconstruction of an extinct breed, using different strategies: embryos-only, embryos in combination with semen, and semen-only. Three cost measures were used: time required for population reconstruction, cost for creation of the gene bank, number of years-keeping-female to reach reconstruction. Semen costs were estimated across four scenarios: the presence or absence of a commercial market for semen, purchase of semen donors, and semen extracted from the epididymus. The number of cells were doubled to take into account the creation of two storage sites. The strategy embryos-only required the shortest time to reach reconstruction. With the strategy embryos + semen, time increased with decreasing proportions of embryos. With semen-only, reconstruction time varied from 2 to 21 years. A high variation of costs was observed across species and strategies, from 360 Euros in the rabbit to 1 092 300 in the horse. In all species, the embryos-only strategy was about 10% more expensive than using 90% embryos + semen. Decreasing the percentage of embryos further diminished costs. The number of years-keeping-female ranged across strategies, from 2 in the rabbit, to a maximum of 12 878 in the horse.
Factor analysis models for structuring covariance matrices of additive genetic effects: a Bayesian implementation
Authors: de los Campos Gustavo , Gianola Daniel 
Published: June 2009

Abstract
Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA) may provide an avenue for structuring (co)variance matrices, thus reducing the number of parameters needed for describing (co)dispersion. We describe how FA can be used to model genetic effects in the context of a multivariate linear mixed model. An orthogonal common factor structure is used to model genetic effects under Gaussian assumption, so that the marginal likelihood is multivariate normal with a structured genetic (co)variance matrix. Under standard prior assumptions, all fully conditional distributions have closed form, and samples from the joint posterior distribution can be obtained via Gibbs sampling. The model and the algorithm developed for its Bayesian implementation were used to describe five repeated records of milk yield in dairy cattle, and a one common FA model was compared with a standard multiple trait model. The Bayesian Information Criterion favored the FA model.
Factors influencing the efficiency of a marker-assisted introgression programme in Merino sheep
Authors: Dominik Sonja , Henshall John , O'Grady Julian , Marshall Karen 
Published: June 2009

Abstract
This study investigated a marker-assisted introgression programme in Australian Merino sheep. The goal was to introgress an allele with a large negative effect on fibre diameter into a Merino flock possessing medium average fibre diameter. The influence of two factors was explored: the strategy used to select animals from the purebred and backcross line for backcrossing purposes and the use of selection on background markers to accelerate the return to the purebred line's genome. The results were compared to introgression based on EBVs only. Introgression using EBVs only produced almost the same response in the dollar index as marker-based introgression methods. However, this study did not account for some of the costs associated with implementing the programmes, including the costs of phenotyping and genotyping. Given that the cost of measuring fibre diameter is low, it was concluded that introgression on EBVs only would be the preferred method since the marginal profit of marker-assisted introgression would not be large enough to cover the additional cost of genotyping. In marker-assisted introgression, reciprocal crossing of male and female selection candidates from the backcross and the purebred line was the most advantageous strategy from a practical and profit point of view. Selection for background markers was less profitable in this study than recovering the donor genome by selection on phenotype.
Genotype by environment interactions in relation to growth traits in slow growing chickens
Authors: N'Dri Aya Lydie , Sellier Nadine , Tixier-Boichard Michèle , Beaumont Catherine , Mignon-Grasteau Sandrine 
Published: June 2009

Abstract
Since feed conversion ratio (FCR) is higher in slow-growing "Label Rouge" chickens than in broiler chickens, it is important to work on its improvement in this breed. However, this involves rearing animals in cages (C), an environment very different from that used for selection (in floor pens, S) and production (outdoor, E). The aim of this study was to evaluate the importance of genotype by environment (G × E) interactions between S, C, and E environments, to find the best way to select for FCR, using 2002 related animals. Growth curve parameters were estimated and body composition measured. Individual feed conversion ratios (FCR) were recorded between 8 and 10 weeks in C. The presence of G × E interactions was assessed by the genetic correlations between the same trait recorded in different environments. Moderate but significant G × E interactions were detected for carcass traits, a significant one was observed between E and S or C for growth curve parameters but none between C and S. If G × E interactions are set aside, i.e. selecting on traits recorded in C, abdominal fatness is the best indirect selection criterion for FCR but if they are taken in account then leg yield or growth curve parameters in S and growth curve parameters in E are better.
Changes in the expression of genetic characteristics across cohorts in skeletal deformations of farmed salmonids
Authors: Kause Antti , Ritola Ossi , Paananen Tuija 
Published: June 2009

Abstract
Genetic analysis of disorder incidence in farmed animals is challenged by two factors. Disorders in different cohorts and environments could be caused by different factors, leading to changes in heritability and to less than unity genetic correlations across cohorts. Moreover, due to computational limitations, liability scale heritabilities at very low incidence may differ from those estimated at higher incidence. We tested whether these two dilemmas occur in skeletal deformations of farmed salmonids using multigeneration data from the Finnish rainbow trout breeding programme and previous salmonid studies. The results showed that heritability was close to zero in cohorts in which management practices maintained incidence at a low level. When there was a management failure and incidence was unusually high, heritability was elevated. This may be due to computational limitations at very low incidence and/or because deformations are induced by different factors in different cohorts. Most genetic correlations between deformations recorded in different generations were weakly to strongly positive. However, also negative correlations between generations were present, showing that high liability at one time can be genetically connected to low liability at another time. The results emphasise that genetic architecture of binary traits can be influenced by trait expression.
SNP mapping of QTL affecting growth and fatness on chicken GGA1
Authors: Rao Yousheng , Shen Xu , Xia Mengna , Luo Chenglong , Nie Qinghua , Zhang Dexiang , Zhang Xiquan 
Published: June 2009

Abstract
An F2 chicken population was established from a crossbreeding between a Xinghua line and a White Recessive Rock line. A total of 502 F2 chickens in 17 full-sib families from six hatches was obtained, and phenotypic data of 488 individuals were available for analysis. A total of 46 SNP on GGA1 was initially selected based on the average physical distance using the dbSNP database of NCBI. After the polymorphism levels in all F0 individuals (26 individuals) and part of the F1 individuals (22 individuals) were verified, 30 informative SNP were potentially available to genotype all F2 individuals. The linkage map was constructed using Cri-Map. Interval mapping QTL analyses were carried out. QTL for body weight (BW) of 35 d and 42 d, 49 d and 70 d were identified on GGA1 at 351–353 cM and 360 cM, respectively. QTL for abdominal fat weight was on GGA1 at 205 cM, and for abdominal fat rate at 221 cM. Two novel QTL for fat thickness under skin and fat width were detected at 265 cM and 72 cM, respectively.
Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)
Authors: Jaffrézic Florence , de Koning Dirk-Jan , Boettcher Paul J , Bonnet Agnès , Buitenhuis Bart , Closset Rodrigue , Déjean Sébastien , Delmas Céline , Detilleux Johanne C , Dovč Peter , Duval Mylène , Foulley Jean-Louis , Hedegaard Jakob , Hornshøj Henrik , Hulsegge Ina , Janss Luc , Jensen Kirsty , Jiang Li , Lavrič Miha , Cao Kim-Anh Lê , Lund Mogens Sandø , Malinverni Roberto , Marot Guillemette , Nie Haisheng , Petzl Wolfram , Pool Marco H , Robert-Granié Christèle , San Cristobal Magali , van Schothorst Evert M , Schuberth Hans-Joachim , Sørensen Peter , Stella Alessandra , Tosser-Klopp Gwenola , Waddington David , Watson Michael , Yang Wei , Zerbe Holm , Seyfert Hans-Martin 
Published: June 2009

Abstract
A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.
Analysis of the real EADGENE data set: Multivariate approaches and post analysis (Open Access publication)
Authors: Sørensen Peter , Bonnet Agnès , Buitenhuis Bart , Closset Rodrigue , Déjean Sébastien , Delmas Céline , Duval Mylène , Glass Liz , Hedegaard Jakob , Hornshøj Henrik , Hulsegge Ina , Jaffrézic Florence , Jensen Kirsty , Jiang Li , de Koning Dirk-Jan , Cao Kim-Anh Lê , Nie Haisheng , Petzl Wolfram , Pool Marco H , Robert-Granié Christèle , San Cristobal Magali , Lund Mogens Sandø , van Schothorst Evert M , Schuberth Hans-Joachim , Seyfert Hans-Martin , Tosser-Klopp Gwenola , Waddington David , Watson Michael , Yang Wei , Zerbe Holm 
Published: June 2009

Abstract
The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.
Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differential expression (Open Access publication)
Authors: Watson Michael , Pérez-Alegre Mónica , Baron Michael Denis , Delmas Céline , Dovč Peter , Duval Mylène , Foulley Jean-Louis , Garrido-Pavón Juan José , Hulsegge Ina , Jaffrézic Florence , Jiménez-Marín Ángeles , Lavrič Miha , Lê Cao Kim-Anh , Marot Guillemette , Mouzaki Daphné , Pool Marco H , Robert-Granié Christèle , San Cristobal Magali , Tosser-Klopp Gwenola , Waddington David , de Koning Dirk-Jan 
Published: June 2009

Abstract
Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.
Interval mapping of quantitative trait loci with selective DNA pooling data
Authors: Wang Jing , Koehler Kenneth J , Dekkers Jack CM 
Published: June 2009

Abstract
Selective DNA pooling is an efficient method to identify chromosomal regions that harbor quantitative trait loci (QTL) by comparing marker allele frequencies in pooled DNA from phenotypically extreme individuals. Currently used single marker analysis methods can detect linkage of markers to a QTL but do not provide separate estimates of QTL position and effect, nor do they utilize the joint information from multiple markers. In this study, two interval mapping methods for analysis of selective DNA pooling data were developed and evaluated. One was based on least squares regression (LS-pool) and the other on approximate maximum likelihood (ML-pool). Both methods simultaneously utilize information from multiple markers and multiple families and can be applied to different family structures (half-sib, F2 cross and backcross). The results from these two interval mapping methods were compared with results from single marker analysis by simulation. The results indicate that both LS-pool and ML-pool provided greater power to detect the QTL than single marker analysis. They also provide separate estimates of QTL location and effect. With large family sizes, both LS-pool and ML-pool provided similar power and estimates of QTL location and effect as selective genotyping. With small family sizes, however, the LS-pool method resulted in severely biased estimates of QTL location for distal QTL but this bias was reduced with the ML-pool.
Biodiversity of pig breeds from China and Europe estimated from pooled DNA samples: differences in microsatellite variation between two areas of domestication
Authors: Megens Hendrik-Jan , Crooijmans Richard PMA , Cristobal Magali San , Hui Xiao , Li Ning , Groenen Martien AM 
Published: June 2009

Abstract
Microsatellite diversity in European and Chinese pigs was assessed using a pooled sampling method on 52 European and 46 Chinese pig populations. A Neighbor Joining analysis on genetic distances revealed that European breeds were grouped together and showed little evidence for geographic structure, although a southern European and English group could tentatively be assigned. Populations from international breeds formed breed specific clusters. The Chinese breeds formed a second major group, with the Sino-European synthetic Tia Meslan in-between the two large clusters. Within Chinese breeds, in contrast to the European pigs, a large degree of geographic structure was noted, in line with previous classification schemes for Chinese pigs that were based on morphology and geography. The Northern Chinese breeds were most similar to the European breeds. Although some overlap exists, Chinese breeds showed a higher average degree of heterozygosity and genetic distance compared to European ones. Between breed diversity was even more pronounced and was the highest in the Central Chinese pigs, reflecting the geographically central position in China. Comparing correlations between genetic distance and heterozygosity revealed that China and Europe represent different domestication or breed formation processes. A likely cause is a more diverse wild boar population in Asia, but various other possible contributing factors are discussed.