Interval and composite interval mapping of somatic cell score,yield, and components of milk in dairy cattle

Single-marker, interval-mapping (IM) and composite interval mapping (CIM) were used to detect quantitative trait loci (QTL) controlling milk, fat and protein yields, and somatic cell score (SCS). A granddaughter design was used to combine molecular genetic information with predicted transmitting abilities (PTA) and estimated daughter yield deviations (DYD) from eight Dairy Bull DNA Repository Holstein families. Models that included and excluded weights accounting for the uncertainty of the response variable were evaluated in each trait, family and phenotype (DYD and PTA) combination. The genotypic information consisted of 174 microsatellite markers along 29 Bos taurus autosomes. The average number of informative markers per autosome was three and the number of informative sons per family and marker varied between 21 and 173. Within-family results from the least squares single-marker analyses were used in expectation-maximization likelihood IM and CIM implemented with QTL Cartographer. Different CIM model specifications, offering complementary control on the background QTL outside the interval under study, were evaluated. Permutation techniques were used to calculate the genome-wide threshold test statistic values based on 1,000 samples. Results from the DYD and PTA analyses were highly consistent across traits and families. The minor differences in the estimates from the models that accounted for or ignored the uncertainty of the DYD (variance) and PTA (inverse of reliability) may be associated to the elevated and consistent precision of the DYD and PTA among sons. The CIM model best supported by the data had 10 markers controlling for background effects. On autosome (BTA) three, a QTL at 32 cM influencing protein yield was located in family five and a QTL at 74 cM for fat yield was located in family eight. Two map positions associated with SCS were detected on BTA 21, one at 33 cM in family one and the other at 84 cM in family three. A QTL for protein yield was detected between 26 and 36 cM on BTA six, family six, and a QTL for milk yield was detected at 116 cM on BTA seven in family three. The IM and CIM approaches detected a QTL at 3 cM on BTA 14 influencing fat yield in family four. Two map positions on BTA 29 were associated with significant variation of milk (0 cM) and fat yield (14 cM) in family seven. These results suggest the presence of one QTL with pleiotropic effects on multiple traits or multiple QTL within the marker interval. Findings from this study could be used in subsequent fine-mapping work and applied to marker-assisted selection of dairy production and health traits.     

Genome-wide scan to detect quantitative trait loci for milk urea nitrogen in Dutch Holstein-Friesian cows

Studies have reported genetic variation in milk urea nitrogen (MUN) between cows, suggesting genetic differences in nitrogen efficiency between cows. In this paper, the results of a genome-wide scan to identify quantitative trait loci (QTL) that contribute to genetic variation in MUN and MUN yield are presented. Two to 3 morning milk samples were taken from 1,926 cows, resulting in 5,502 test-day records. Test-day records were corrected for systematic environmental effects using a repeatability animal model. Averages of corrected phenotypes of 849 cows, belonging to 7 sire families, were used in an across-family multimarker regression approach to detect QTL. Animals were successfully genotyped for 1,341 single nucleotide polymorphisms. The QTL analysis resulted in 4 chromosomal regions with suggestive QTL: Bos taurus autosomes (BTA) 1, 6, 21, and 23. On BTA 1, 2 suggestive QTL affecting MUN were detected at 60 and 140 cM. On BTA 6, 1 suggestive QTL affecting both MUN and MUN yield was detected at 103 cM. On BTA 21, 1 suggestive QTL affecting MUN yield was detected at 83 cM. On BTA 23, 1 suggestive QTL affecting MUN was detected at 54 cM. Quantitative trait loci for MUN and MUN yield were suggestive and each explained between 2 and 3% of the phenotypic variance.     

Detection of quantitative trait loci influencing dairy traits using a model for longitudinal data

A longitudinal-linkage analysis approach was developed and applied to an outbred population. Nonlinear mixed-effects models were used to describe the lactation patterns and were extended to include marker information following single-marker and interval mapping models. Quantitative trait loci (QTL) affecting the shape and scale of lactation curves for production and health traits in dairy cattle were mapped in three U.S. Holstein families (Dairy Bull DNA Repository families one, four, and five) using the granddaughter design. Information on 81 informative markers on six Bos taurus autosomes (BTA) was combined with milk yield, fat, and protein percentage and somatic cell score (SCS) test-day records. Six percent of the single-marker tests surpassed the experiment-wise significance threshold. Marker BL41 on BTA3 was associated with decrease in milk yield during mid-lactation in family one. The scale and shape of the protein percentage lactation curve in family four varied with BMC4203 (BTA6) allele that the son received from the grandsire. Some map locations were associated with variation in the lactation pattern of multiple traits. In family four, the marker HUJI177 (BTA3) was associated with changes in the milk yield and protein percentage curves suggesting a QTL with pleiotropic effects or multiple QTL in the region. The interval mapping model uncovered a QTL on BTA7 associated with variation in milk-yield pattern in family four and a QTL on BTA21 affecting SCS in family five. The developed approach can be extended to random regressions, covariance functions, spline, gametic and variance component models. The results from the longitudinal-QTL approach will help to understand the genetic factors acting at different stages of lactation and will assist in positional candidate gene research. Identified positions can be incorporated into marker-assisted selection decisions to alter the persistency and peak production or the fluctuation of SCS during a lactation.     

Detection of quantitative trait loci in Danish Holstein cattle affecting clinical mastitis, somatic cell score, udder conformation traits, and assessment of associated effects on milk yield

The aim of this study was to 1) detect QTL across the cattle genome that influence the incidence of clinical mastitis and somatic cell score (SCS) in Danish Holsteins, and 2) characterize these QTL for pleiotropy versus multiple linked quantitative trait loci (QTL) when chromosomal regions affecting clinical mastitis were also affecting other traits in the Danish udder health index or milk production traits. The chromosomes were scanned using a granddaughter design where markers were typed for 19 to 34 grandsire families and 1,373 to 2,042 sons. A total of 356 microsatellites covering all 29 autosomes were used in the scan. Among the across-family regression analyses, 16 showed chromosome-wide significance for the primary traits incidence of clinical mastitis in first (CM1), second (CM2), and third (CM3) lactations, and SCS. Regions of chromosomes 5, 6, 9, 11, 15, and 26 were found to affect CM and regions of chromosomes 5, 6, 8, 13, 22, 23, 24, and 25 affected SCS. Markers on chromosomes 6, 11, 15, and 26 can be used to perform marker-assisted selection on CM without a direct negative selection on milk yield, because no effects were detected on the milk traits. Comparing multi-trait models assuming either a pleiotropic QTL affecting 2 traits or 2 QTL each affecting 1 trait gave some evidence to distinguish between these models. For Bos taurus autosome 5, the most likely models were a pleiotropic QTL affecting CM2, CM3, and SCS, and a linked QTL affecting fat yield index. For Bos taurus autosome 9, the most likely model is a pleiotropic QTL affecting CM1 and CM2 at approximately 8 cM.     

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 affecting milk production traits on bovine chromosome 6 in zebuine Gyr breed

Fourteen Brazilian dairy Gyr sire families with 657 daughters were analyzed for quantitative trait loci (QTL) on chromosome 6 by using a daughter design for 5 economic traits: milk, fat, and protein production, fat and protein percentage. The cows and sires were genotyped for 27 microsatellites with average spacing between markers of 4.9 cM. In the analyses across 14 families, for the largest significant families, and within family, a QTL was located for milk yield and fat yield close to marker BMS2508 at the 5% chromosome-wide significance level across families and 1% chromosome-wide within families. For fat percentage, a QTL near DIK4482 was identified at the 5% chromosome-wide significance level when all families were analyzed together and at the 1% chromosome-wide significance level within the largest significant families. The different analyses yielded results that were generally consistent for milk yield, fat yield, and fat percentage. The order of the markers in the derived map was consistent with that in the consensus map. Some QTL and candidate genes in dairy cattle for milk production traits are probably preserved in Bos taurus and Bos indicus.     

Detection of quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population by the daughter design

Fourteen microsatellite markers with a coverage of 63.5 cM on bovine chromosome 6 were selected, and 26 sire families with 2,260 daughters were analyzed for mapping quantitative trait loci (QTL) affecting 5 milk production traits in a Chinese Holstein population. In the analyses across 26 families and within the largest significant families with a one-QTL model fitted, a QTL near BMS470 was detected that affected fat yield at the 5% experiment-wide significance level. When a 2-QTL model was fitted in the across-family analysis, it was found that there might exist 2 QTL affecting the 3 yield traits, although the exact or empirical thresholds for the significance testing were unknown. In all analyses, the results for milk yield and protein yield were generally consistent, which might have resulted from the same genetic background for milk and protein yield.     

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.     

Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle

We report putative quantitative trait loci affecting female fertility and milk production traits using the merged data from two research groups that conducted independent genome scans in Dairy Bull DNA Repository grandsire families to identify quantitative trait loci (QTL) affecting economically important traits. Six families used by both groups had been genotyped for 367 microsatellite markers covering 2713.5 cM of the cattle genome (90%), with an average spacing of 7.4 cM. Phenotypic traits included PTA for pregnancy rate and daughter deviations for milk, protein and fat yields, protein and fat percentages, somatic cell score, and productive life. Analysis of the merged dataset identified putative quantitative trait loci that were not detected in the separate studies, and the pregnancy rate PTA estimates that recently became available allowed detection of pregnancy rate QTL for the first time. Sixty-one putative significant marker effects were identified within families, and 13 were identified across families. Highly significant effects were found on chromosome 3 affecting fat percentage and protein yield, on chromosome 6 affecting protein and fat percentages, on chromosome 14 affecting fat percentage, on chromosome 18 affecting pregnancy rate, and on chromosome 20 affecting protein percentage. Within-family analysis detected putative QTL associated with pregnancy rate on six chromosomes, with the effect on chromosome 18 being the most significant statistically. These findings may help identify the most useful markers available for QTL detection and, eventually, for marker-assisted selection for improvement of these economically important traits.     

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle

A whole genome scan of Finnish Ayrshire was conducted to map quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.