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Genótipos de 25 touros usados em inseminação artificial foram utilizados para estudar a extensão do desequilíbrio de ligação (LD) e a correspondência entre estimadores de endogamia baseados na informação de pedigree e de SNP da raça Gir no Brasil. No total, 24.020 SNPs tiveram frequências do alelo menor (MAF) maiores que 5 % e foram usados para calcular duas medidas de LD (r² and D’) para todos os pares de marcadores em cada autossomo. LD também foi utilizado para estimar o tamanho efetivo populacional (Ne) da população ancestral em diferentes gerações passadas. Coeficientes de endogamia individuais (F) foram estimados usando informação genealógica (Fped, pedigree de 9 gerações) ou informação de marcadores. As estimativas de F baseadas em marcadores foram obtidas com base no excesso de homozigose (Fhet) em marcadores SNP e a proporção estimada do genoma localizada em trilhas de homozigose (runs of homozigosity, Froh). O LD médio entre marcadores adjacentes de todos os autossomos foi de aproximadamente 0,20 e 0,75, estimado de acordo com as estatísticas r2 e D’. Nesta amostra analisada da raça Gir, verificou-se a existência de LD potencialmente útil para seleção genômica (r²>0,30) no caso de pares de marcadores separados por até 100kb. O tamanho efetivo populacional apresentou uma tendência consistente de queda ao longo do tempo, chegando abaixo de 56 nas últimas três gerações. Uma fraca correspondência entre as estimativas de endogamia individuais baseadas nas trilhas de homozigose e pedigree foi verificada neste estudo (correlações estimadas entre Fped e Froh variaram de 0,32 a 0,42). Os presentes resultados sugerem a possibilidade de aplicação da seleção genômica na raça Gir no Brasil, mas são necessários mais estudos sobre a extensão do desequilíbrio de ligação usando uma maior amostra desta população.

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.

Summary Selection is known to influence the linkage disequilibrium (LD) pattern in livestock populations. Spurious LD may lead to a higher number of false-positive signals in whole genome association mapping experiments. We compared three approaches for whole genome association mapping in a simulation study: single marker regression (SMR), a two-step approach, which analyses residuals corrected for family effects with an SMR (GRAMMAR), and a combined linkage and LD approach, which applies the quantitative transmission disequilibrium test to the Mendelian sampling term (MTDT). Three different scenarios were simulated: idealized random mating, limited number of parents and directional selection. The number of false-positive associations increased when the number of parents was limited. Mapping accuracy was the worst in the scenario with directional selection for all approaches. As SMR produced a high number of false-positive signals in small populations, results of whole genome scans in livestock analysed with SMR should be considered with caution. GRAMMAR was the most accurate approach, but also the least powerful one. The Bonferroni-corrected significance threshold seemed to be too stringent for this approach. Results obtained with MTDT changed only slightly with selected populations. MTDT combined sufficient power with a manageable number of false-positive associations in all scenarios.

Made available in DSpace on 2013-08-12T19:03:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-01-01 Made available in DSpace on 2013-09-30T18:01:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:36Z No. of bitstreams: 0 Made available in DSpace on 2014-05-20T13:18:36Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-01-01 Bundesministerium für Bildung und Forschung (BMBF) Forderverein Biotechnologieforschung e.V. Bonn Lohmann Tierzucht GmbH, Cuxhaven Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The aim of this study was to compare iterative and direct solvers for estimation of marker effects in genomic selection. One iterative and two direct methods were used: Gauss-Seidel with Residual Update, Cholesky Decomposition and Gentleman-Givens rotations. For resembling different scenarios with respect to number of markers and of genotyped animals, a simulated data set divided into 25 subsets was used. Number of markers ranged from 1,200 to 5,925 and number of animals ranged from 1,200 to 5,865. Methods were also applied to real data comprising 3081 individuals genotyped for 45181 SNPs. Results from simulated data showed that the iterative solver was substantially faster than direct methods for larger numbers of markers. Use of a direct solver may allow for computing (co)variances of SNP effects. When applied to real data, performance of the iterative method varied substantially, depending on the level of ill-conditioning of the coefficient matrix. From results with real data, Gentleman-Givens rotations would be the method of choice in this particular application as it provided an exact solution within a fairly reasonable time frame (less than two hours). It would indeed be the preferred method whenever computer resources allow its use. Univ Gottingen, Dept Anim Sci, Anim Breeding & Genet Grp, D-37075 Gottingen, Germany Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Jaboticabal, SP, Brazil Univ Guelph, Dept Anim & Poultry Sci, Ctr Genet Improvement Livestock, Guelph, on N1G 2W1, Canada Vereinigte Informat Syst Tierhaltung wV, Verden, Germany GenSys Consultores Assoc SS Ltda, Porto Alegre, RS, Brazil Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Zootecnia, Jaboticabal, SP, Brazil

Summary In many farm animal populations, high-density single nucleotide polymorphism (SNP) genotypes are becoming available on a large scale, and routine estimation of breeding values is implemented for a multiplicity of traits. We propose to apply the basic principle of the quantitative transmission disequilibrium test (QTDT) to estimated Mendelian sampling terms. A two-step procedure is suggested, where in the first step additive breeding values are estimated with a mixed linear model and the Mendelian sampling terms are calculated from the estimated breeding values. In the second step, the QTDT is applied to these estimated Mendelian sampling terms. The resulting test is expected to yield significant results if the SNP is in sufficient linkage disequilibrium and linkage with quantitative trait loci (QTL). This principle is illustrated with a simulated data set comprising 4665 individuals genotyped for 6000 SNP and 15 true QTL. Thirteen of the fifteen QTL were significant on a genome-wide 0.1% error level. Results for the empirical power are derived from repeated samples of 1000 and 3000 genotyped individuals, respectively. General properties and potential extensions of the methodology are indicated. Owing to its computational simplicity and speed, the suggested procedure is well suited to scan whole genomes with high-density SNP coverage in samples of substantial size and for a multiplicity of different traits.

Additive and nonadditive genetic ef- fects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different ge- netic models and estimation methods. The data set con- sisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epis- tasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed vari

In cattle, at least 39 variants of the 4 casein proteins (α(S1)-, β-, α(S2)- and κ-casein) have been described to date. Many of these variants are known to affect milk-production traits, cheese-processing properties, and the nutritive value of milk. They also provide valuable information for phylogenetic studies. So far, the majority of studies exploring the genetic variability of bovine caseins considered European taurine cattle breeds and were carried out at the protein level by electrophoretic techniques. This only allows the identification of variants that, due to amino acid exchanges, differ in their electric charge, molecular weight, or isoelectric point. In this study, the open reading frames of the casein genes CSN1S1, CSN2, CSN1S2, and CSN3 of 356 animals belonging to 14 taurine and 3 indicine cattle breeds were sequenced. With this approach, we identified 23 alleles, including 5 new DNA sequence variants, with a predicted effect on the protein sequence. The new variants were only found in indicine breeds and in one local Iranian breed, which has been phenotypically classified as a taurine breed. A multidimensional scaling approach based on available SNP chip data, however, revealed an admixture of taurine and indicine populations in this breed as well as in the local Iranian breed Golpayegani. Specific indicine casein alleles were also identified in a few European taurine breeds, indicating the introgression of indicine breeds into these populations. This study shows the existence of substantial undiscovered genetic variability of bovine casein loci, especially in indicine cattle breeds. The identification of new variants is a valuable tool for phylogenetic studies and investigations into the evolution of the milk protein genes.

Selection index theory was used to compare different selection strategies aiming at the improvement of meat quality in beef cattle. Alternative strategies were compared with a reference scenario with three basic traits in the selection index: BW at 200 d (W200) and 400 d (W400) and muscling score (MUSC). These traits resemble the combination currently used in the German national beef genetic evaluation system. Traits in the breeding goal were defined as the 3 basic traits plus marbling score (MARB), to depict a situation where an established breeding program currently selecting for growth and carcass yield intends to incorporate meat quality in its selection program. Economic weights were either the same for all 4 traits, or doubled or tripled for MARB. Two additional selection criteria for improving MARB were considered: Live animal intramuscular fat content measured by ultrasound (UIMF) as an indicator trait and a genomic breeding value (GEBV) for the target trait directly (gMARB). Results were used to estimate the required number of genotyped animals in an own calibration set for implementing genomic selection focusing on meat quality. Adding UIMF to the basic index increased the overall genetic gain per generation by 15% when the economic weight on MARB was doubled and by 44% when it was tripled. When a genomic breeding value for marbling could be estimated with an accuracy of 0.5, adding gMARB to the index provided larger genetic gain than adding UIMF. Greatest genetic gain per generation was obtained with the scenario containing GEBV for 4 traits (gW200, gW400, gMUSC, and gMARB) when the accuracies of these GEBV were ≥0.7. Adding UIMF to the index substantially improved response to selection for MARB, which switched from negative to positive when the economic weight on MARB was doubled or tripled. For all scenarios that contained gMARB in the selection index, the response to selection in MARB was positive for all relative economic weights on MARB, when the accuracy of GEBV was >0.7. Results indicated that setting up a calibration set of ∼500 genotyped animals with carcass phenotypes for MARB could suffice to obtain a larger response to selection than measuring UIMF. If the size of the calibration set is ∼2,500, adding the ultrasound trait to an index containing already the GEBV would bring little benefit, unless the relative economic weight for marbling is much larger than for the other traits.

The objective of this study was to estimate the contribution of each autosome to genetic variation of milk yield, fat, and protein percentage and somatic cell score in Holstein cattle. Data on 2294 Holstein bulls genotyped for 39,557 autosomal markers were used. Three approaches were applied to estimate the proportion of genetic variance attributed to each chromosome. In two of them, marker-derived kinship coefficients were computed, using either marker genotypes observed on the whole genome or on subsets relative to each chromosome. Variance components were then estimated using residual maximum likelihood in method 1 or a regression-based approach in method 2. In method 3, genetic variances associated to each marker were estimated in a linear multiple regression approach, and then were summed up chromosome-wise. Generally, all chromosomes contributed to genetic variation. For most of the chromosomes, the amount of variance attributed to a chromosome was found to be proportional to its physical length. Nevertheless, for traits influenced by genes with very large effects a larger proportion of the genetic variance is expected to be associated with the chromosomes where these genes are. This is illustrated with the DGAT1 gene on BTA14 which is known to have a large effect on fat percentage in milk. The proportion of genetic variance for fat percentage associated with chromosome 14 was two to sevenfold (depending on the method) larger than would be predicted from chromosome size alone. Based on method 3 an approach is suggested to estimate the effective number of genes underlying the inheritance of the studied traits, yielding numbers between N ≈ 400 (for fat percentage) to N ≈ 900 (for milk yield). It is argued that these numbers are conservative lower bound estimates, but are in line with recent findings suggesting a highly polygenic background of production traits in dairy cattle. peerReviewed

Selection is known to influence the linkage disequilibrium (LD) pattern in livestock populations. Spurious LD may lead to a higher number of false-positive signals in whole genome association mapping experiments. We compared three approaches for whole genome association mapping in a simulation study: single marker regression (SMR), a two-step approach, which analyses residuals corrected for family effects with an SMR (GRAMMAR), and a combined linkage and LD approach, which applies the quantitative transmission disequilibrium test to the Mendelian sampling term (MTDT). Three different scenarios were simulated: idealized random mating, limited number of parents and directional selection. The number of false-positive associations increased when the number of parents was limited. Mapping accuracy was the worst in the scenario with directional selection for all approaches. As SMR produced a high number of false-positive signals in small populations, results of whole genome scans in livestock analysed with SMR should be considered with caution. GRAMMAR was the most accurate approach, but also the least powerful one. The Bonferroni-corrected significance threshold seemed to be too stringent for this approach. Results obtained with MTDT changed only slightly with selected populations. MTDT combined sufficient power with a manageable number of false-positive associations in all scenarios.

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.

This study presents a second generation of linkage disequilibrium (LD) map statistics for the whole genome of the Holstein-Friesian population, which has a four times higher resolution compared with that of the maps available so far. We used DNA samples of 810 German Holstein-Friesian cattle genotyped by the Illumina Bovine SNP50K BeadChip to analyse LD structure. A panel of 40 854 (75.6%) markers was included in the final analysis. The pairwise r(2) statistic of SNPs up to 5 Mb apart across the genome was estimated. A mean value of r(2) = 0.30 +/- 0.32 was observed in pairwise distances of25 kb and it dropped to 0.20 +/- 0.24 at 50-75 kb, which is nearly the average inter-marker space in this study. The proportion of SNPs in useful LD (r(2)or = 0.25) was 26% for the distance of 50 and 75 kb between SNPs. We found a lower level of LD for SNP pairs at the distanceor =100 kb than previously thought. Analysis revealed 712 haplo-blocks spanning 4.7% of the genome and containing 8.0% of all SNPs. Mean and median block length were estimated as 164 +/- 117 kb and 144 kb respectively. Allele frequencies of the SNPs have a considerable and systematic impact on the estimate of r(2). It is shown that minimizing the allele frequency difference between SNPs reduces the influence of frequency on r(2) estimates. Analysis of past effective population size based on the direct estimates of recombination rates from SNP data showed a decline in effective population size to N(e) = 103 up to approximately 4 generations ago. Systematic effects of marker density and effective population size on observed LD and haplotype structure are discussed.

Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2013-08-22T19:04:58Z No. of bitstreams: 1 S1415-47572007000400006.pdf: 350450 bytes, checksum: 33f410f68c408518de4c2c3047d90d48 (MD5) Made available in DSpace on 2013-08-22T19:04:58Z (GMT). No. of bitstreams: 1 S1415-47572007000400006.pdf: 350450 bytes, checksum: 33f410f68c408518de4c2c3047d90d48 (MD5) Previous issue date: 2007-01-01 Made available in DSpace on 2013-09-30T18:02:53Z (GMT). No. of bitstreams: 2 S1415-47572007000400006.pdf: 350450 bytes, checksum: 33f410f68c408518de4c2c3047d90d48 (MD5) S1415-47572007000400006.pdf.txt: 39939 bytes, checksum: 15a5ddec4d1d716e4fe0af9f7734a040 (MD5) Previous issue date: 2007-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T13:18:58Z No. of bitstreams: 2 S1415-47572007000400006.pdf: 350450 bytes, checksum: 33f410f68c408518de4c2c3047d90d48 (MD5) S1415-47572007000400006.pdf.txt: 39939 bytes, checksum: 15a5ddec4d1d716e4fe0af9f7734a040 (MD5) Made available in DSpace on 2014-05-20T13:18:58Z (GMT). No. of bitstreams: 2 S1415-47572007000400006.pdf: 350450 bytes, checksum: 33f410f68c408518de4c2c3047d90d48 (MD5) S1415-47572007000400006.pdf.txt: 39939 bytes, checksum: 15a5ddec4d1d716e4fe0af9f7734a040 (MD5) Previous issue date: 2007-01-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The problem of multicollinearity in regression analysis was studied. Ridge regression (RR) techniques were used to estimate parameters affecting the performance of crossbred calves raised in tropical and subtropical regions by a model including additive, dominance, joint additive or profit heterosis and epistatic effects and their interactions with latitude in an attempt to model genotype by environment interactions. A software was developed in Fortran 77 to perform five variant types of RR: the originally proposed method; the method implemented by SAS; and three methods of weighting the RR parameter lambda. Three mathematical criteria were tested with the aim of choosing a value for the lambda coefficient: the sum and the harmonic mean of the absolute Student t-values and the value of lambda at which all variance inflation factors (VIF) became lower than 300. Prediction surfaces obtained from estimated coefficients were used to compare the five methods and three criteria. It was concluded that RR could be a good alternative to overcome multicollinearity problems. For all the methods tested, acceptable prediction surfaces could be obtained when the VIF criterion was employed. This mathematical criterion is thus recommended as an auxiliary tool for choosing lambda. Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia GenSys Consultores Associados S/S Ltda. Lagoa da Serra Ltda (Holland Genetics) Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore.

In this study we compared different statistical procedures for estimating SNP effects using the simulated data set from the XII QTL-MAS workshop. Five procedures were considered and tested in a reference population, i.e., the first four generations, from which phenotypes and genotypes were available. The procedures can be interpreted as variants of ridge regression, with different ways for defining the shrinkage parameter. Comparisons were made with respect to the correlation between genomic and conventional estimated breeding values. Moderate correlations were obtained from all methods. Two of them were used to predict genomic breeding values in the last three generations. Correlations between these and the true breeding values were also moderate. We concluded that the ridge regression procedures applied in this study did not outperform the simple use of a ratio of variances in a mixed model method, both providing moderate accuracies of predicted genomic breeding values.