Assessment of runs of homozygosity, heterozygosity-rich regions and genomic inbreeding estimates in a subpopulation of Guzerá (Bos indicus) dual-purpose cattle

For decades, inbreeding in cattle has been evaluated using pedigree information. Nowadays, inbreeding coefficients can be obtained using genomic information such as runs of homozygosity (ROH). The aims of this study were to quantify ROH and heterozygosity-rich regions (HRR) in a subpopulation of Guzerá dual-purpose cattle, to examine ROH and HRR islands, and to compare inbreeding coefficients obtained by ROH with alternative genomic inbreeding coefficients. A subpopulation of 1733 Guzerá animals genotyped for 50k SNPs was used to obtain the ROH and HRR segments. Inbreeding coefficients by ROH (FROH ), by genomic relationship matrix based on VanRaden's method 1 using reference allele frequency in the population (FGRM ), by genomic relationship matrix based on VanRaden's method 1 using allele frequency fixed in 0.5 (FGRM_0.5 ), and by the proportion of homozygous loci (FHOM ) were calculated. A total of 15,660 ROH were identified, and the chromosome with the highest number of ROH was BTA6. A total of 4843 HRRs were identified, and the chromosome with the highest number of HRRs was BTA23. No ROH and HRR islands were identified according to established criteria, but the regions closest to the definition of an island were examined from 64 to 67 Mb of BTA6, from 36 to 37 Mb of BTA2 and from 0.50 to 1.25 Mb of BTA23. The genes identified in ROH islands have previously been associated with dairy and beef traits, while genes identified on HRR islands have previously been associated with reproductive traits and disease resistance. FROH was equal to 0.095 ± 0.084, and its Spearman correlation with FGRM was low (0.44) and moderate-high with FHOM (0.79) and with FGRM_0.5 (0.80). The inbreeding coefficients determined by ROH were higher than other cattle breeds' and higher than pedigree-based inbreeding in the Guzerá breed obtained in previous studies. It is recommended that future studies investigate the effects of inbreeding determined by ROH on the traits under selection in the subpopulation studied.

Genetics of bovine abomasal displacement

Displacement of the abomasum (DA) is a common inherited condition in Holstein cows. This article reviews the genetics of DA including risk factors, genetic parameters and molecular genetic results. Breeds other than Holsteins affected by DA include Guernseys, Jerseys, Brown Swiss, Ayrshires and Simmental-Red Holsteins. In most DA cases, left displacements of the abomasum (LDA) are seen. Lactation incidence rates are higher for DA in first lactation Holsteins compared to later lactations. For Holstein cows, heritability estimates for DA are between 0.03 and 0.53. Genetic correlation estimates among DA and milk production traits range from positive to negative. Genome-wide significant genomic regions associated with LDA are located on bovine chromosomes (BTA) 1, 3, 11, 20 and 23. Motilin-associated single nucleotide polymorphisms on BTA23 exhibit a functional relationship with LDA. Pathways for deposition of calcium, insulin-dependent diabetes mellitus and synaptic transmission are significantly related to LDA in Holsteins. Deciphering the DA-associated genomic regions and genes may be an important step in the quest to understand the underlying disease-causing mechanisms and in unravelling mutations with a causal relationship to DA.

Quantitative trait loci affecting response to crowding stress in an F(2) generation of rainbow trout produced through phenotypic selection

Selective breeding programs for salmonids typically aim to improve traits associated with growth and disease resistance. It has been established that stressors common to production environments can adversely affect these and other traits which are important to producers and consumers. Previously, we employed phenotypic selection to create families that exhibit high or low plasma cortisol concentrations in response to crowding stress. Subsequent crosses of high × low phenotypes founded a multigenerational breeding scheme with the aim of dissecting the genetic basis for variation underlying stress response through the identification of quantitative trait loci (QTL). Multiple methods of QTL analyses differing in their assumptions of homozygosity of the causal alleles in the grandparental generation yielded similar results in the F1 generation, and the analysis of two stress response phenotype measurement indexes were highly correlated. In the current study, we conducted a genome scan with microsatellites to detect QTL in the F2 generation of two families created through phenotypic selection and having larger numbers of offspring than families screened in the previous generation. Seven suggestive and three significant QTL were detected, seven of which were not previously detected in the National Center for Cool and Cold Water Aquaculture germplasm, bringing the total number of chromosomes containing significant and suggestive stress response QTL to 4 and 15, respectively. One significant QTL which peaks at 7 cM on chromosome Omy12 spans 12 cM and explains 25 % of the phenotypic variance in family 2008052 particularly warrants further investigation. Five QTL with significant parent-of-origin effects were detected in family 2008052, including two QTL on Omy12. The 95 % confidence intervals for the remaining QTL we detected were broad, requiring validation and fine mapping with other genotyping approaches and mapping strategies. These results will facilitate identification of potential casual alleles that can be employed in strategies aimed at better understanding the genetic and physiological basis of stress responses to crowding in rainbow trout aquaculture production.

QTL affecting stress response to crowding in a rainbow trout broodstock population

Background

Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL.

Results

A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively.

Conclusions

The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.

QTL mapping in outbred half-sib families using Bayesian model selection

In this article, we propose a model selection method, the Bayesian composite model space approach, to map quantitative trait loci (QTL) in a half-sib population for continuous and binary traits. In our method, the identity-by-descent-based variance component model is used. To demonstrate the performance of this model, the method was applied to map QTL underlying production traits on BTA6 in a Chinese half-sib dairy cattle population. A total of four QTLs were detected, whereas only one QTL was identified using the traditional least square (LS) method. We also conducted two simulation experiments to validate the efficiency of our method. The results suggest that the proposed method based on a multiple-QTL model is efficient in mapping multiple QTL for an outbred half-sib population and is more powerful than the LS method based on a single-QTL model.

Bayesian shrinkage mapping for multiple QTL in half-sib families

Recently, an effective Bayesian shrinkage estimation method has been proposed for mapping QTL in inbred line crosses. However, with regard to outbred populations, such as half-sib populations with maternal information unavailable, it is not straightforward to utilize such a shrinkage estimation for QTL mapping. The reasons are: (1) the linkage phase of markers in the outbred population is usually unknown; and (2) only paternal genotypes can be used for inferring QTL genotypes of offspring. In this article, a novel Bayesian shrinkage method was proposed for mapping QTL under the half-sib design using a mixed model. A simulation study clearly demonstrated that the proposed method was powerful for detecting multiple QTL. In addition, we applied the proposed method to map QTL for economic traits in the Chinese dairy cattle population. Two or more novel QTL harbored in the chromosomal region were detected for each trait of interest, whereas only one QTL was found using traditional maximum likelihood analyses in our earlier studies. This further validated that our shrinkage estimation method could perform well in empirical data analyses and had practical significance in the field of linkage studies for outbred populations.

Quantitative trait locus-by-environment interaction for milk yield traits on Bos taurus autosome 6

Genotype-by-environment interactions for production traits in dairy cattle have often been observed, while QTL analyses have focused on detecting genes with general effects on production traits. In this study, a QTL search for genes with environmental interaction for the traits milk yield, protein yield, and fat yield were performed on Bos taurus autosome 6 (BTA6), also including information about the previously investigated candidate genes ABCG2 and OPN. The animals in the study were Norwegian Red. Eighteen grandsires and 716 sires were genotyped for 362 markers on BTA6. Every marker bracket was regarded as a putative QTL position. The effects of the candidate genes and the putative QTL were modeled as a regression on an environmental parameter (herd year), which is based on the predicted herd-year effect for the trait. Two QTL were found to have environmentally dependent effects on milk yield. These QTL were located 3.6 cM upstream and 9.1 cM downstream from ABCG2. No environmentally dependent QTL was found to significantly affect protein or fat yield.

Estimation of Genetic Parameters for Quantitative Trait Loci for Dairy Traits in the French Holstein Population

A marker-assisted selection program (MAS) has been implemented in dairy cattle in France. The efficiency of such a selection program depends on the use of correct genetic parameters for the marked quantitative trait loci (QTL). Therefore, the objective of this study was to estimate the proportion of genetic variance explained by 4 QTL described in previous studies (these QTL are segregating on chromosomes 6, 14, 20, and 26). Genotypes for 11 markers were available for 3,974 bulls grouped within 54 sire families of the French Holstein population undergoing MAS. The parameters were estimated for 4 QTL and 5 dairy traits: milk, fat and protein yields, and fat and protein percentages. The proportion of genetic variance explained by the QTL ranged from as low as 0.03 to 0.36%. Both lack of marker informativity and poor monitoring of QTL transmission might limit the accuracy of estimation. The QTL explained a larger proportion of genetic variance for milk composition traits. The QTL on chromosome 14 and chromosomes 6 and 20 have their largest influence on fat and protein percentages, respectively. The overall proportions of genetic variance explained by the QTL were 27.0, 30.7, 24.1, 48.2, and 33.6% for milk, fat and protein yields, and fat and protein percentages, respectively. These results clearly indicated that a large part of the genetic variance is explained by a small number of QTL and that their use in MAS might be beneficial for dairy cattle breeding programs.

Multitrait Quantitative Trait Loci Mapping for Milk Production Traits in Danish Holstein Cattle

The aims of this study were (1) to confirm previously identified quantitative trait loci (QTL) on bovine chromosomes 6, 11, 14, and 23 in the Danish Holstein cattle population, (2) to assess the pleiotropic nature of each QTL on milk production traits by building multitrait and multi-QTL models, and (3) to include pedigree information on nongenotyped individuals to improve the estimation of genetic parameters underlying the random QTL model. Nineteen grandsire families were analyzed by single-trait (ST) and multitrait (MT) QTL mapping methods. The variance component-based QTL mapping model was implemented via restricted maximum likelihood (REML) to estimate QTL position and parameters. Segregation of the previously identified QTL was confirmed on bovine chromosomes 6, 11, and 14, but not on 23. A highly significant (1% chromosome-wise level) QTL was found on chromosome 6, between 37 and 73 cM. This QTL had a strong effect on protein percentage (PP) and fat percentage (FP) according to ST analyses, and effects on PP, FP, milk yield (MY), fat yield (FY), and protein yield (PY) in MT analyses. A QTL affecting PP was detected on chromosome 11 (at 70 cM) using ST analysis. The MT analysis revealed a second QTL (at 67 cM) approaching significance with an effect on MY. The ST analysis identified a QTL for MY and FP on chromosome 14, between 10 and 24 cM. The extended pedigree (nongenotyped animals) was included to estimate genetic parameters underlying the random QTL model; that is, additive polygenic and QTL variances. In general, the estimates of the QTL variance components were smaller but more precise when the extended pedigree was considered in the analysis.

Fine-mapping milk production quantitative trait loci on BTA6: analysis of the bovine osteopontin gene

Bovine chromosome six (BTA6) harbors up to six quantitative trait loci (QTL) influencing the milk production of dairy cattle. In stark contrast to human, there is long-range linkage disequilibrium in dairy cattle, which has previously made it difficult to identify the mutations underlying these QTL. Using 38 microsatellite markers in a pedigree of 3,147 Holstein bulls, we fine mapped regions of BTA6 that had previously been shown to harbor QTL. Next, we sequenced a 12.3-kb region harboring Osteopontin, a positional candidate for the statistically most significant of the identified QTL. Nine mutations were identified, and only genotypes for the OPN3907 indel were concordant with the QTL genotypes of eight bulls that were established by segregation analysis. Four of these mutations were genotyped, and a joint linkage/linkage disequilibrium mapping analysis was used to demonstrate the existence of only two functionally distinct clusters of haplotypes within the QTL region, which were uniquely defined by OPN3907 alleles. We estimate a probability of 0.40 that no other mutation within this region is concordant with the QTL genotypes of these eight bulls. Finally, we demonstrate that the motif harboring OPN3907, which is upstream of the promoter and within a region known to harbor tissue-specific osteopontin regulatory elements, is moderately conserved among mammals. The motif was not retrieved from database queries and may be a novel regulatory element.

Whole genome scan to detect chromosomal regions affecting multiple traits in dairy cattle

Chromosomal regions affecting multiple traits (multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait regression analysis was computed. A chromosomal region was considered an MQR when the observed covariance between contrasts deviated from the expected covariance under the null hypothesis of no pleiotropy or close linkage. The expected covariance and the confidence interval for the expected covariance were determined by permutation of the data. Four categories of traits were analyzed: production (5 traits), udder conformation (6 traits), udder health (2 traits), and fertility (2 traits). The analysis of a granddaughter design involving 833 sons of 20 grandsires resulted in 59 MQR (alpha = 0.01, chromosomewise). Fifteen MQR were found on Bos taurus autosome (BTA) 14. Four or more MQR were found on BTA 6, 13, 19, 22, 23, and 25. Eight MQR involving udder conformation and udder health and 4 MQR involving production traits and udder health were found. Five MQR were identified for combinations of fertility and udder conformation traits, and another 5 MQR were identified for combinations of fertility and production traits. For 22 MQR, the difference between the correlation attributable to the MQR and the overall genetic correlation was >0.60. Although the false discovery rate was relatively high (0.52), it was considered important to present these results to assess potential consequences of using these MQR for marker-assisted selection.

Estimation of Quantitative Trait Loci Parameters for Milk Production Traits in German Holstein Dairy Cattle Population

The main objective of this study was to estimate the proportion of total genetic variance attributed to a quantitative trait locus (QTL) on Bos taurus autosome 6 (BTA6) for milk production traits in the German Holstein dairy cattle population. The analyzed chromosomal region on BTA6 spanned approximately 70 cM, and contained 6 microsatellite markers. Milk production data were obtained from routine genetic evaluation for 4500 genotyped German Holstein bulls. Technical aspects related to the estimation of model parameters for a large data set from routine genotype recording were outlined. A fixed QTL model and a random QTL model were introduced to incorporate marker information into parameter estimation and genetic evaluation. Estimated QTL variances, expressed as the ratio of QTL to polygenic variances, were 0.04, 0.03, and 0.07 for milk yield; 0.06, 0.08, and 0.14 for fat yield; and 0.04, 0.04, and 0.11 for protein yield, in the first 3 parities, respectively. The estimated QTL positions, expressed as distances from the leftmost marker DIK82, were 18, 31, and 17 cM for milk yield; 25, 17, and 9 cM for fat yield; and 16, 30, and 17 cM for protein yield in the 3 respective parities. Because the data for the parameter estimation well represented the current population of active German Holstein bulls, the QTL parameter estimates have been used in routine marker-assisted genetic evaluation for German Holsteins.

Quantitative trait loci mapping for dairy cattle production traits using a maximum likelihood method

A maximum likelihood method was developed for QTL mapping in half-sib designs and compared to the regression method in analyses of both field and simulated data. The field data consisted of milk production evaluations of 433 progeny tested sons of 6 sires and 64 microsatellite markers distributed over 12 chromosomes. Based on permutation tests, 5 significant QTL were detected in the field data by the regression method compared with 10 by the maximum likelihood method (P < 0.05). In field data analysis, the maximum likelihood method detected more significant QTL and had a smaller residual variance than the regression method. The simulation included 9 scenarios differing in number of families, family size, QTL variance, and marker density, each replicated 100 times. The simulation results suggested that, as for the regression method, the precision of estimating QTL from the maximum likelihood method improves with increasing number of sons per sire, increasing the ratio of QTL to phenotypic variance, and decreasing marker interval. The maximum likelihood method had a smaller dispersion of estimated QTL positions than the regression method in 6 of 9 scenarios simulated. Overall, the maximum likelihood method shows potential advantage in QTL detection over the regression method, especially in the situations with less favorable conditions for QTL detection.

Polymorphism of the bovine CSN1S1 promoter: linkage mapping, intragenic haplotypes, and effects on milk production traits

The bovine CSN1S1 5' flanking region (CSN1S1-5') was screened for polymorphisms in different cattle breeds. Single-strand conformation polymorphisms (SSCP) and sequence analyses revealed four alleles (1-4), two of them being new allelic forms (3 and 4). Sequences were deposited in GenBank with accession numbers AF549499-502. In alleles 1 and 4, potential transcription factor binding sites are altered by the mutations. Using SSCP analysis, all four alleles were identified in German Holsteins. Six intragenic haplo-types comprising CSN1S1-5' (alleles 1, 2, 3, 4) and exon 17 (CSN1S1*B and C) genotypes were found. Linkage mapping using half-sib families from the German QTL project positioned CSN1S1 between the markers FBN14 and CSN3, with 5.6 cM distance between CSN1S1 and CSN3. Variance analysis, using family and CSN1S1 promoter genotypes as fixed effects, of breeding values and deregressed proofs for milk production traits (milk, fat, and protein yield and also fat and protein percentage) revealed significant effects on protein percentage when all families and genotypes were considered. Contrast calculations assigned a highly significant effect to genotype 24, which was associated with highest LS-means for protein percentage breeding values. As CSN1S1 is one of the main caseins in milk, this could be an effect of mutations in regulatory elements in the promoter region. An effect on milk yield breeding values was indicated for genotype 12, but is probably caused by a linked locus.

Search for pleiotropic QTL on chromosome BTA6 affecting yield traits of milk production

The primary aim of this study was to investigate whether previous findings of similar quantitative trait loci (QTL) positions for correlated yield traits are due to a pleiotropic QTL. We applied a multitrait variance component based QTL mapping method to a dataset involving five granddaughter families from the German Holstein dairy cattle population. The marker map contained 16 microsatellite markers, distributed across chromosome BTA6. A chromosomewise significance threshold was used, because BTA6 is known to harbor QTL for several milk traits. To evaluate the results from the multivariate, across-family analysis, we also conducted single-family analyses using the least squares method of QTL estimation. The results provided two significant QTL findings at 49 and 64 cM for milk yield in different families and putative QTL at 68 cM for fat yield and at 71 cM for protein yield in another family. The results for fat and protein yield were confirmed by a univariate, across-family variance components analysis. The multivariate analysis of three bivariate trait combinations resulted in a significant pleiotropic QTL finding at 68 cM for fat yield and protein yield, bracketed by markers TGLA37 and FBN13. The estimates of variance contribution due to this QTL were 23% and 25%, respectively.