bluuebunny/crossref_metadata_2025 huggingface dataset:
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

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

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

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

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

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

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

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

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

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

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

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

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.
Parameter expansion for estimation of reduced rank covariance matrices (Open Access publication)
Authors: Meyer Karin
Published: June 2009

Parameter expanded and standard expectation maximisation algorithms are described for reduced rank estimation of covariance matrices by restricted maximum likelihood, fitting the leading principal components only. Convergence behaviour of these algorithms is examined for several examples and contrasted to that of the average information algorithm, and implications for practical analyses are discussed. It is shown that expectation maximisation type algorithms are readily adapted to reduced rank estimation and converge reliably. However, as is well known for the full rank case, the convergence is linear and thus slow. Hence, these algorithms are most useful in combination with the quadratically convergent average information algorithm, in particular in the initial stages of an iterative solution scheme.
Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance
Authors: Mulder Han A , Bijma Piter , Hill William G
Published: June 2009

In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, breeding goal, number of progeny per sire and breeding scheme on selection responses in mean and variance when applying index selection. Genetic parameters were obtained from the literature. Economic values for the mean and variance were derived for some standard non-linear profit equations, e.g. for traits with an intermediate optimum. The economic value of variance was in most situations negative, indicating that selection for reduced variance increases profit. Predicted responses in residual variance after one generation of selection were large, in some cases when the number of progeny per sire was at least 50, by more than 10% of the current residual variance. Progeny testing schemes were more efficient than sib-testing schemes in decreasing residual variance. With optimum traits, selection pressure shifts gradually from the mean to the variance when approaching the optimum. Genetic improvement of uniformity is particularly interesting for traits where the current population mean is near an intermediate optimum.
Genes influencing milk production traits predominantly affect one of four biological pathways
Authors: Chamberlain Amanda Jane , McPartlan Helen Clare , Goddard Michael Edward
Published: June 2009

In this study we introduce a method that accounts for false positive and false negative results in attempting to estimate the true proportion of quantitative trait loci that affect two different traits. This method was applied to data from a genome scan that was used to detect QTL for three independent milk production traits, Australian Selection Index (ASI), protein percentage (P%) and fat percentage corrected for protein percentage (F% – P%). These four different scenarios are attributed to four biological pathways: QTL that (1) increase or decrease total mammary gland production (affecting ASI only); (2) increase or decrease lactose synthesis resulting in the volume of milk being changed but without a change in protein or fat yield (affecting P% only); (3) increase or decrease protein synthesis while milk volume remains relatively constant (affecting ASI and P% in the same direction); (4) increase or decrease fat synthesis while the volume of milk remains relatively constant (affecting F% – P% only). The results indicate that of the positions that detected a gene, most affected one trait and not the others, though a small proportion (2.8%) affected ASI and P% in the same direction.
Estimation by simulation of the efficiency of the French marker-assisted selection program in dairy cattle (Open Access publication)
Authors: Guillaume François , Fritz Sébastien , Boichard Didier , Druet Tom
Published: June 2009

The efficiency of the French marker-assisted selection (MAS) was estimated by a simulation study. The data files of two different time periods were used: April 2004 and 2006. The simulation method used the structure of the existing French MAS: same pedigree, same marker genotypes and same animals with records. The program simulated breeding values and new records based on this existing structure and knowledge on the QTL used in MAS (variance and frequency). Reliabilities of genetic values of young animals (less than one year old) obtained with and without marker information were compared to assess the efficiency of MAS for evaluation of milk, fat and protein yields and fat and protein contents. Mean gains of reliability ranged from 0.015 to 0.094 and from 0.038 to 0.114 in 2004 and 2006, respectively. The larger number of animals genotyped and the use of a new set of genetic markers can explain the improvement of MAS reliability from 2004 to 2006. This improvement was also observed by analysis of information content for young candidates. The gain of MAS reliability with respect to classical selection was larger for sons of sires with genotyped progeny daughters with records. Finally, it was shown that when superiority of MAS over classical selection was estimated with daughter yield deviations obtained after progeny test instead of true breeding values, the gain was underestimated.
Detection and modelling of time-dependent QTL in animal populations
Authors: Lund Mogens S. , Sorensen Peter , Madsen Per , Jaffrézic Florence
Published: June 2009

A longitudinal approach is proposed to map QTL affecting function-valued traits and to estimate their effect over time. The method is based on fitting mixed random regression models. The QTL allelic effects are modelled with random coefficient parametric curves and using a gametic relationship matrix. A simulation study was conducted in order to assess the ability of the approach to fit different patterns of QTL over time. It was found that this longitudinal approach was able to adequately fit the simulated variance functions and considerably improved the power of detection of time-varying QTL effects compared to the traditional univariate model. This was confirmed by an analysis of protein yield data in dairy cattle, where the model was able to detect QTL with high effect either at the beginning or the end of the lactation, that were not detected with a simple 305 day model.
Cloning, chromosome mapping and expression pattern of porcine PLIN and M6PRBP1 genes
Authors: Tao Xia , Jihong Yuan , Li Gan , Bin Feng , Yi Zhu , Xiaodong Chen , Peichao Zhang , Yang Zaiqing
Published: June 2009

The PAT proteins, named after the three PLIN/ADRP/TIP47 (PAT) proteins, PLIN for perilipin, ADRP for adipose differentiation-related protein and TIP47 for tail-interacting protein of 47 kDa, now officially named M6PRBP1 for mannose-6-phosphate receptor binding protein 1, is a set of intracellular lipid droplet binding proteins. They are localized in the outer membrane monolayer enveloping lipid droplets and are involved in the metabolism of intracellular lipid. This work describes the cloning and sequencing of porcine PLIN and M6PRBP1 cDNAs, the chromosome mapping of these two genes, as well as the expression pattern of porcine PAT genes. Sequence analysis shows that the porcine PLIN cDNA contains an open reading frame of 1551 bp encoding 516 amino acids and that the porcine M6PRBP1 cDNA contains a coding region of 1320 bp encoding 439 amino acids. Comparison of PLIN and M6PRBP1 amino-acid sequences among various species reveals that porcine and bovine proteins are the most conserved. Porcine PLIN and M6PRBP1 genes have been mapped to pig chromosomes 7 and 2, respectively, by radiation hybrid analysis using the IMpRH panel. Expression analyses in pig showed a high expression of PLIN mRNA in adipose tissue, M6PRBP1 mRNA in small intestine, kidney and spleen and ADRP mRNA in adipose tissue, lung and spleen.
Exploring the assumptions underlying genetic variation in host nematode resistance (Open Access publication)
Authors: Doeschl-Wilson Andrea Beate , Vagenas Dimitrios , Kyriazakis Ilias , Bishop Stephen Christopher
Published: June 2009

The wide range of genetic parameter estimates for production traits and nematode resistance in sheep obtained from field studies gives rise to much speculation. Using a mathematical model describing host – parasite interactions in a genetically heterogeneous lamb population, we investigated the consequence of: (i) genetic relationships between underlying growth and immunological traits on estimated genetic parameters for performance and nematode resistance, and (ii) alterations in resource allocation on these parameter estimates. Altering genetic correlations between underlying growth and immunological traits had large impacts on estimated genetic parameters for production and resistance traits. Extreme parameter values observed from field studies could only be reproduced by assuming genetic relationships between the underlying input traits. Altering preferences in the resource allocation had less pronounced effects on the genetic parameters for the same traits. Effects were stronger when allocation shifted towards growth, in which case worm burden and faecal egg counts increased and genetic correlations between these resistance traits and body weight became stronger. Our study has implications for the biological interpretation of field data, and for the prediction of selection response from breeding for nematode resistance. It demonstrates the profound impact that moderate levels of pleiotropy and linkage may have on observed genetic parameters, and hence on outcomes of selection for nematode resistance.
Genetic differentiation between the Old and New types of Serbian Tsigai sheep
Authors: Ćinkulov Mirjana , Tapio Miika , Ozerov Mikhail , Kiselyova Tatyana , Marzanov Nurbiy , Pihler Ivan , Olsaker Ingrid , Vegara Mensur , Kantanen Juha
Published: June 2009

Two Tsigai sheep populations exist in Serbia: the Old type, called Čokan, and the New type. It is assumed that the New type results from upgrading Tsigai sheep with exotic genetic material. We investigated genetic diversity and differentiation of these types by analysing 23 autosomal microsatellites. Tests for Hardy-Weinberg proportions, linkage equilibrium between genotypes across loci and the calculation of inbreeding coefficients were performed and the deficiency in the number of alleles within the Tsigai types was examined using a Wilcoxon sign-rank test. The New type displayed a higher level of genetic variability than the Čokan in terms of allele numbers, but the New Tsigai showed a pattern of heterozygosity deficiency. The positive f value for the Čokan suggests the occurrence of inbreeding in this type. The proportion of linkage disequilibrium was below that expected by chance. Exclusion of two loci in Hardy-Weinberg disequilibrium did not alter our conclusions based on the entire data set i.e. the two Tsigai types are clearly differentiated and the New Tsigai type has been influenced by crossbreeding. Therefore, the Čokan Tsigai should be considered as a distinct endangered breed in the FAO classification.
Exploration of lagged relationships between mastitis and milk yield in dairy cows using a Bayesian structural equation Gaussian-threshold model
Authors: Wu Xiao-Lin , Heringstad Bjørg , Gianola Daniel
Published: June 2009

A Gaussian-threshold model is described under the general framework of structural equation models for inferring simultaneous and recursive relationships between binary and Gaussian characters, and estimating genetic parameters. Relationships between clinical mastitis (CM) and test-day milk yield (MY) in first-lactation Norwegian Red cows were examined using a recursive Gaussian-threshold model. For comparison, the data were also analyzed using a standard Gaussian-threshold, a multivariate linear model, and a recursive multivariate linear model. The first 180 days of lactation were arbitrarily divided into three periods of equal length, in order to investigate how these relationships evolve in the course of lactation. The recursive model showed negative within-period effects from (liability to) CM to test-day MY in all three lactation periods, and positive between-period effects from test-day MY to (liability to) CM in the following period. Estimates of recursive effects and of genetic parameters were time-dependent. The results suggested unfavorable effects of production on liability to mastitis, and dynamic relationships between mastitis and test-dayMYin the course of lactation. Fitting recursive effects had little influence on the estimation of genetic parameters. However, some differences were found in the estimates of heritability, genetic, and residual correlations, using different types of models (Gaussian-threshold vs. multivariate linear).
Individual increase in inbreeding allows estimating effective sizes from pedigrees
Authors: Gutiérrez Juan Pablo , Cervantes Isabel , Molina Antonio , Valera Mercedes , Goyache Félix
Published: June 2009

We present here a simple approach to obtain reliable estimates of the effective population size in real world populations via the computation of the increase in inbreeding for each individual (delta F

i
) in a given population. The values of delta F

i
are computed as t-root of 1 - (1 - F

i
) where F

i
is the inbreeding coefficient and t is the equivalent complete generations for each individual. The values of delta F computed for a pre-defined reference subset can be averaged and used to estimate effective size. A standard error of this estimate of N
e can be further computed from the standard deviation of the individual increase in inbreeding. The methodology is demonstrated by applying it to several simulated examples and to a real pedigree in which other methodologies fail when considering reference subpopulations. The main characteristics of the approach and its possible use are discussed both for predictive purposes and for analyzing genealogies.
A comparison between Poisson and zero-inflated Poisson regression models with an application to number of black spots in Corriedale sheep
Authors: Naya Hugo , Urioste Jorge I. , Chang Yu-Mei , Rodrigues-Motta Mariana , Kremer Roberto , Gianola Daniel
Published: June 2009

Dark spots in the fleece area are often associated with dark fibres in wool, which limits its competitiveness with other textile fibres. Field data from a sheep experiment in Uruguay revealed an excess number of zeros for dark spots. We compared the performance of four Poisson and zero-inflated Poisson (ZIP) models under four simulation scenarios. All models performed reasonably well under the same scenario for which the data were simulated. The deviance information criterion favoured a Poisson model with residual, while the ZIP model with a residual gave estimates closer to their true values under all simulation scenarios. Both Poisson and ZIP models with an error term at the regression level performed better than their counterparts without such an error. Field data from Corriedale sheep were analysed with Poisson and ZIP models with residuals. Parameter estimates were similar for both models. Although the posterior distribution of the sire variance was skewed due to a small number of rams in the dataset, the median of this variance suggested a scope for genetic selection. The main environmental factor was the age of the sheep at shearing. In summary, age related processes seem to drive the number of dark spots in this breed of sheep.
Bayes factor between Student t and Gaussian mixed models within an animal breeding context
Authors: Casellas Joaquim , Ibáñez-Escriche Noelia , García-Cortés Luis Alberto , Varona Luis
Published: June 2009

The implementation of Student t mixed models in animal breeding has been suggested as a useful statistical tool to effectively mute the impact of preferential treatment or other sources of outliers in field data. Nevertheless, these additional sources of variation are undeclared and we do not know whether a Student t mixed model is required or if a standard, and less parameterized, Gaussian mixed model would be sufficient to serve the intended purpose. Within this context, our aim was to develop the Bayes factor between two nested models that only differed in a bounded variable in order to easily compare a Student t and a Gaussian mixed model. It is important to highlight that the Student t density converges to a Gaussian process when degrees of freedom tend to infinity. The twomodels can then be viewed as nested models that differ in terms of degrees of freedom. The Bayes factor can be easily calculated from the output of a Markov chain Monte Carlo sampling of the complex model (Student t mixed model). The performance of this Bayes factor was tested under simulation and on a real dataset, using the deviation information criterion (DIC) as the standard reference criterion. The two statistical tools showed similar trends along the parameter space, although the Bayes factor appeared to be the more conservative. There was considerable evidence favoring the Student t mixed model for data sets simulated under Student t processes with limited degrees of freedom, and moderate advantages associated with using the Gaussian mixed model when working with datasets simulated with 50 or more degrees of freedom. For the analysis of real data (weight of Pietrain pigs at six months), both the Bayes factor and DIC slightly favored the Student t mixed model, with there being a reduced incidence of outlier individuals in this population.
The analysis of disease biomarker data using a mixed hidden Markov model (Open Access publication)
Authors: Detilleux Johann C
Published: June 2009

A mixed hidden Markov model (HMM) was developed for predicting breeding values of a biomarker (here, somatic cell score) and the individual probabilities of health and disease (here, mastitis) based upon the measurements of the biomarker. At a first level, the unobserved disease process (Markov model) was introduced and at a second level, the measurement process was modeled, making the link between the unobserved disease states and the observed biomarker values. This hierarchical formulation allows joint estimation of the parameters of both processes. The flexibility of this approach is illustrated on the simulated data. Firstly, lactation curves for the biomarker were generated based upon published parameters (mean, variance, and probabilities of infection) for cows with known clinical conditions (health or mastitis due to Escherichia coli or Staphylococcus aureus). Next, estimation of the parameters was performed via Gibbs sampling, assuming the health status was unknown. Results from the simulations and mathematics show that the mixed HMM is appropriate to estimate the quantities of interest although the accuracy of the estimates is moderate when the prevalence of the disease is low. The paper ends with some indications for further developments of the methodology.
Genome-wide identification of QTL for age at puberty in gilts using a large intercross F2 population between White Duroc × Erhualian
Authors: Yang Guangcheng , Ren Jun , Li Shijun , Mao Huirong , Guo Yuanmei , Zou Zhengzhi , Ren Dongren , Ma Junwu , Huang Lusheng
Published: June 2009

Puberty is a fundamental development process experienced by all reproductively competent adults, yet the specific factors regulating age at puberty remain elusive in pigs. In this study, we performed a genome scan to identify quantitative trait loci (QTL) affecting age at puberty in gilts using a White Duroc × Erhualian intercross. A total of 183 microsatellites covering 19 porcine chromosomes were genotyped in 454 F2 gilts and their parents and grandparents in the White Duroc × Erhualian intercross. A linear regression method was used to map QTL for age at puberty via QTLexpress. One 1% genome-wise significant QTL and one 0.1% genome-wise significant QTL were detected at 114 cM (centimorgan) on SSC1 and at 54 cM on SSC7, respectively. Moreover, two suggestive QTL were found on SSC8 and SSC17, respectively. This study confirmed the QTL for age at puberty previously identified on SSC1, 7 and 8, and reports for the first time a QTL for age at puberty in gilts on SSC17. Interestingly, the Chinese Erhualian alleles were not systematically favourable for younger age at puberty.
Characterization of porcine ENO3: genomic and cDNA structure, polymorphism and expression
Authors: Wu Jian , Zhou Donghai , Deng Changyan , Wu Xiaoxiong , Long Liangqi , Xiong Yuanzhu
Published: June 2009

In this study, a full-length cDNA of the porcine ENO3 gene encoding a 434 amino acid protein was isolated. It contains 12 exons over approximately 5.4 kb. Differential splicing in the 5'-untranslated sequence generates two forms of mRNA that differ from each other in the presence or absence of a 142-nucleotide fragment. Expression analysis showed that transcript 1 of ENO3 is highly expressed in liver and lung, while transcript 2 is highly expressed in skeletal muscle and heart. We provide the first evidence that in skeletal muscle expression of ENO3 is different between Yorkshire and Meishan pig breeds. Furthermore, real-time polymerase chain reaction revealed that, in Yorkshire pigs, skeletal muscle expression of transcript 1 is identical at postnatal day-1 and at other stages while that of transcript 2 is higher. Moreover, expression of transcript 1 is lower in skeletal muscle and all other tissue samples than that of transcript 2, with the exception of liver and kidney. Statistical analysis showed the existence of a polymorphism in the ENO3 gene between Chinese indigenous and introduced commercial western pig breeds and that it is associated with fat percentage, average backfat thickness, meat marbling and intramuscular fat in two different populations.
Evolution of the polymorphism at molecular markers in QTL and non-QTL regions in selected chicken lines (Open Access publication)
Authors: Loywyck Valérie , Bed'hom Bertrand , Pinard-van der Laan Marie-Hélène , Pitel Frédérique , Verrier Étienne , Bijma Piter
Published: June 2009

We investigated the joint evolution of neutral and selected genomic regions in three chicken lines selected for immune response and in one control line. We compared the evolution of polymorphism of 21 supposedly neutral microsatellite markers versus 30 microsatellite markers located in seven quantitative trait loci (QTL) regions. Divergence of lines was observed by factor analysis. Five supposedly neutral markers and 12 markers in theQTL regions showed F
st values greater than 0.15. However, the non-significant difference (P > 0.05) between matrices of genetic distances based on genotypes at supposedly neutral markers on the one hand, and at markers in QTL regions, on the other hand, showed that none of the markers in the QTL regions were influenced by selection. A supposedly neutral marker and a marker located in the QTL region on chromosome 14 showed temporal variations in allele frequencies that could not be explained by drift only. Finally, to confirm thatmarkers located inQTL regions on chromosomes 1, 7 and 14were under the influence of selection, simulations were performed using haplotype dropping along the existing pedigree. In the zone located on chromosome 14, the simulation results confirmed that selection had an effect on the evolution of polymorphism of markers within the zone.
Genetic variation in eight Chinese cattle breeds based on the analysis of microsatellite markers
Authors: Sun Weibin , chen Hong , Lei Chuzhao , Lei Xueqin , Zhang Yinghan
Published: June 2009

Genetic variability and genetic relationships were investigated among eight Chinese cattle breeds using 12 microsatellite markers. Three hundred and fifty-two alleles were detected and the average number of alleles per locus ranged from 8.33 ± 1.67 in the Jiaxian breed to 21.33 ± 5.60 in the Qinchuan breed with a mean value of 13.91. The total number of alleles per microsatellite ranged from 21 (INRA005, HEL1) to 40 (HEL13), with a mean of 29.33 per locus. The fixation indices at the 12 loci in the eight breeds were very low with a mean of 0.006. A principal components analysis and the construction of a neighborjoining tree showed that these eight Chinese cattle breeds cluster into three groups i.e. the Yanbian andChineseHolstein, theNanyang and Jiaxian, and the four remaining breeds.This clustering agrees with the origin and geographical distributions of these Chinese breeds.
Genomic selection of purebreds for crossbred performance
Authors: Ibánẽz-Escriche Noelia , Fernando Rohan L , Toosi Ali , Dekkers Jack CM
Published: June 2009

Background

One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.

Results

Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.

Conclusion

In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.
Large-scale association study for structural soundness and leg locomotion traits in the pig
Authors: Fan Bin , Onteru Suneel K , Mote Benny E , Serenius Timo , Stalder Kenneth J , Rothschild Max F
Published: June 2009

Background

Identification and culling of replacement gilts with poor skeletal conformation and feet and leg (FL) unsoundness is an approach used to reduce sow culling and mortality rates in breeding stock. Few candidate genes related to soundness traits have been identified in the pig.

Methods

In this study, 2066 commercial females were scored for 17 traits describing body conformation and FL structure, and were used for association analyses. Genotyping of 121 SNPs derived from 95 genes was implemented using Sequenom's MassARRAY system.

Results

Based on the association results from single trait and principal components using mixed linear model analyses and false discovery rate testing, it was observed that APOE, BMP8, CALCR, COL1A2, COL9A1, DKFZ, FBN1 and VDBP were very highly significantly (P < 0.001) associated with body conformation traits. The genes ALOX5, BMP8, CALCR, OPG, OXTR and WNT16 were very highly significantly (P < 0.001) associated with FL structures, and APOE, CALCR, COL1A2, GNRHR, IHH, MTHFR and WNT16 were highly significantly (P < 0.01) associated with overall leg action. Strong linkage disequilibrium between CALCR and COL1A2 on SSC9 was detected, and haplotype -ACGACC- was highly significantly (P < 0.01) associated with overall leg action and several important FL soundness traits.

Conclusion

The present findings provide a comprehensive list of candidate genes for further use in fine mapping and biological functional analyses.