A search for quantitative trait loci for milk production traits on chromosome 6 in Finnish Ayrshire cattle

Cattle chromosome 6 was scanned with 11 markers, ten microsatellites and the casein haplotype, to identify quantitative trait loci (QTLs) affecting the following milk production traits: milk yield, fat percentage, fat yield, protein percentage and protein yield. Twelve Finnish Ayrshire half-sib families with a total of 480 sons were genotyped and used in a grand-daughter design. Interval mapping was performed with a multiple-marker regression approach with a one-QTL and a two-QTL model, and the significance threshold values were determined empirically using a permutation test. Across-family analysis with the one-QTL model revealed an effect on protein percentage (P < 0.05) and on milk yield (P < 0.05). The analysis with the two-QTL model identified significant effects (P < 0.05) on protein percentage, milk yield, and fat yield. Comparing these two cases, the results suggest the existence of two QTLs on chromosome 6 with an effect on milk production traits. One of the QTLs was located around the casein genes. As the other QTL was similar in location and effect to a QTL found previously in Holstein-Friesians, an identity-by-descent approach could be applied to fine map this region.     

Fine mapping quantitative trait loci affecting milk production traits on bovine chromosome 6 in a Chinese Holstein population

To fine map the previously detected quantitative trait loci （QTLs） affecting milk production traits on bovine chromosome 6 （BTA6）, 15 microsatellite markers situated within an interval of 14.3 cM spanning from BMS690 to BM4528 were selected and 918 daughters of 8 sires were genotyped. Two mapping approaches, haplotype sharing based LD mapping and single marker regression mapping, were used to analyze the data. Both approaches revealed a quantitative trait locus （QTL） with significant effects on milk yield, fat yield and protein yield located in the segment flanked by markers BMS483 and MNB209, which spans a genetic distance of 0.6 cM and a physical distance of 1.5 Mb. In addition, the single marker regression mapping also revealed a QTL affecting fat percentage and protein percentage at marker DIK2291. Our fine mapping work will facilitate the cloning of candidate genes underlying the QTLs for milk production traits.     

Detection of QTL for milk production traits in cattle by application of a specifically developed marker map of BTA6

Interval mapping was carried out to identify quantitative trait loci (QTL) for milk production traits in five granddaughter design families of the German Holstein population. Fourteen randomly generated markers spanning the whole of BTA6 and six targeted microsatellite markers from BTA6q21-31 were included in the analysis. In one family a QTL with effects on milk fat yield and milk protein yield was mapped to the interval TGLA37-FBN13 (3 CM proximal to FBN13, lodscore 3.22) in the middle part of the chromosome. Although there are several reports about QTL with effects on milk production traits on BTA6 in the literature, a QTL with effects on milk fat and milk protein yield has not been previously described.     

Detection of QTL for milk production on Chromosomes 1 and 6 of Holstein cattle

Seventy to 75 sons of each of six Holstein sires were assayed for genotypes at a number of microsatellite loci spanning Chromosomes (Chrs) 1 and 6. The number of informative loci varied from three to eight on each chromosome in different sire families. Linkage order and map distance for microsatellite loci were estimated using CRI-MAP. Estimates of QTL effect and location were made by using a least squares interval mapping approach based on daughter yield deviations of sons for 305-d milk, fat, protein yield, and fat and protein percentage. Thresholds for statistical significance of QTL effects were determined from interval mapping of 10,000 random permutations of the data across the bull sire families and within each sire family separately. Across-sire analyses indicated a significant QTL for fat and protein yield, and fat percentage on Chr 1, and QTL effects on milk yield and protein percentage that might represent one or two QTL on Chr 6. Analyses within each sire family indicated significant QTL effects in five sire families, with one sire possibly being heterozygous for two QTLs. Statistically significant estimates of QTL effects on breeding value ranged from 340 to 640 kg of milk, from 15.6 to 28.4 kg of fat, and 14.4 to 17.6 kg of protein. Received: 19 November 1999 / Accepted: 31 August 2000     

A quantitative trait locus for live weight maps to bovine Chromosome 23

A multiple-marker mapping approach was used to search for quantitative trait loci (QTLs) affecting production, health, and fertility traits in Finnish Ayrshire dairy cattle. As part of a whole-genome scan, altogether 469 bulls were genotyped for six microsatellite loci in 12 families on Chromosome (Chr) 23. Both multiple-marker interval mapping with regression and maximum-likelihood methods were applied with a granddaughter design. Eighteen traits, belonging to 11 trait groups, were included in the analysis. One QTL exceeded experiment level and one QTL genome level significance thresholds. Across-families analysis provided strong evidence (P_experiment= 0.0314) for a QTL affecting live weight. The QTL for live weight maps between markers BM1258 and BoLA DRBP1. A QTL significant at genome level (P_genome= 0.0087) was mapped for veterinary treatment, and the putative QTL probably affects susceptibility to milk fever or ketosis. In addition, three traits exceeded the chromosome 5% significance threshold: protein percentage of milk, calf mortality (sire), and milking speed. In within-family analyses, protein percentage was associated with markers in one family (LOD score = 4.5). Received: 14 December 1998 / Accepted: 28 March 1998     

Quantitative trait loci mapping in dairy cattle: review and meta-analysis

From an extensive review of public domain information on dairy cattle quantitative trait loci (QTL), we have prepared a draft online QTL map for dairy production traits. Most publications (45 out of 55 reviewed) reported QTL for the major milk production traits (milk, fat and protein yield, and fat and protein concentration (%)) and somatic cell score. Relatively few QTL studies have been reported for more complex traits such as mastitis, fertility and health. The collated QTL map shows some chromosomal regions with a high density of QTL, as well as a substantial number of QTL at single chromosomal locations. To extract the most information from these published records, a meta-analysis was conducted to obtain consensus on QTL location and allelic substitution effect of these QTL. This required modification and development of statistical methodologies. The meta-analysis indicated a number of consensus regions, the most striking being two distinct regions affecting milk yield on chromosome 6 at 49 cM and 87 cM explaining 4.2 and 3.6 percent of the genetic variance of milk yield, respectively. The first of these regions (near marker BM143) affects five separate milk production traits (protein yield, protein percent, fat yield, fat percent, as well as milk yield).     

Confirmation and refinement of a QTL on BTA5 affecting milk production traits in the Fleckvieh dual purpose cattle breed

We analysed a QTL affecting milk yield (MY), milk protein yield (PY) and milk fat yield (FY) in the dual purpose cattle breed Fleckvieh on BTA5. Twenty-six microsatellite markers covering 135 cM were selected to analyse nine half-sib families containing 605 sons in a granddaughter design. We thereby assigned two new markers to the public linkage map using the CRI-MAP program. Phenotypic records were daughter yield deviations (DYD) originating from the routinely performed genetic evaluations of breeding animals. To determine the position of the QTL, three different approaches were applied: interval mapping (IM), linkage analysis by variance component analysis (LAVC), and combined linkage disequilibrium (LD) and linkage (LDL) analysis. All three methods mapped the QTL in the same marker interval ( BM2830-ETH152 ) with the greatest test-statistic value at 118, 119.33 and 119.33 cM respectively. The positive QTL allele simultaneously increases DYD in the first lactation by 272 kg milk, 7.1 kg milk protein and 7.0 kg milk fat. Although the mapping accuracy and the significance of a QTL effect increased from IM over LAVC to LDL, the confidence interval was large (13, 20 and 24 cM for FY, MY and PY respectively) for the positional cloning of the causal gene. The estimated averages of pair wise marker LD with a distance <5 cM were low (0.107) and reflect the large effective population size of the Fleckvieh subpopulation analysed. This low level of LD suggests a need for increase in marker density in following fine mapping steps.     

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.     

Mapping and Analysis of Dairy Cattle Quantitative Trait Loci by Maximum Likelihood Methodology Using Milk Protein Genes as Genetic Markers

Maximum likelihood methodology was used to estimate effects of both a marker gene and a linked quantitative trait locus (QTL) on quantitative traits in a segregating population. Two alleles were assumed for the QTL. In addition to the effects of genotypes at both loci on the mean of the quantitative trait, recombination frequency between the loci, frequency of the QTL alleles and the residual standard deviation were also estimated. Thus six parameters were estimated in addition to the marker genotype means. The statistical model was tested on simulated data, and used to estimate direct and linked effects of the milk protein genes, β-lactoglobulin, κcasein, and β-casein, on milk, fat, and protein production and fat and protein percent in the Dutch dairy cattle population. β-Lactoglobulin had significant direct effects on milk yield and fat percent. κ-Casein had significant direct effects on milk yield, protein percent and fat yield. β-Casein had significant direct effects on milk yield, fat and protein percent and fat and protein yield. Linked QTL with significant effects on fat percent were found for κ-casein and β-casein. Since the β-casein and κ-casein genes are closely linked, it is likely that the same QTL was detected for those two markers. Further, a QTL with a significant effect on fat yield was found to be linked to κ-casein and a QTL with a significant effect on protein yield was linked to β-lactoglobulin.     

Quantitative trait loci affecting lactose and total solids on chromosome 6 in Brazilian Gir dairy cattle

Fourteen Brazilian Gir sire families with 657 daughters were analyzed for quantitative trait loci (QTL) on chromosome 6 affecting lactose and total solids. Cows and sires were genotyped with 27 microsatellites with a mean spacing between markers of 4.9 cM. We used a 1% chromosome-wide threshold for QTL qualification. A QTL for lactose yield was found close to marker MNB66 in three families. A QTL for total solid yield was identified close to marker BMS2508 in three families. A QTL for lactose percentage, close to marker DIK1182, was identified in two families. A QTL for total solid percentage, close to marker MNB208, was identified in four families. These QTLs could be used for selection of animals in dairy production systems.     

The identification of QTL that affect the fatty acid composition of milk on sheep chromosome 11

In this work, we analysed 11 genetic markers localized on OAR11 in a commercial population of Spanish Churra sheep to detect QTL that underlie milk fatty acid (FA) composition traits. Following a daughter design, we analysed 799 ewes distributed in 15 half‐sib families. Eight microsatellite markers and three novel SNPs identified in two genes related to fatty acid metabolism, acetyl‐CoA carboxylase α (ACACA) and fatty acid synthase (FASN), were genotyped in the whole population under study. The phenotypic traits considered in the study included 22 measurements related to the FA composition of the milk and three other milk production traits (milk protein percentage, milk fat percentage and milk yield). Across‐family regression analysis revealed four significant QTL at the 5% chromosome‐wise level influencing contents of capric acid (C10:0), lauric acid (C12:0), linoleic conjugated acid (CLA) and polyunsaturated fatty acids (PUFA) respectively. The peaks of the QTL affecting C10:0 and PUFA contents in milk map close to the FASN gene, which has been evaluated as a putative positional candidate for these QTL. The QTL influencing C12:0 content reaches its maximum significance at 58 cM, close to the gene coding for the glucose‐dependent insulinotropic polypeptide. We were not able to find any candidate genes related to fat metabolism at the QTL influencing CLA content, which is located at the proximal end of the chromosome. Further research efforts will be needed to confirm and refine the QTL locations reported here.     

Fine mapping and physical characterization of two linked quantitative trait loci affecting milk fat yield in dairy cattle on BTA26

Previously, a highly significant QTL affecting fat yield and protein yield and mapped to the bovine BTA26 chromosome has been reported to segregate in the French Holstein cattle population. To confirm and refine the location of this QTL, the original detection experiment was extended by adding 12 new families and genotyping 25 additional microsatellite markers (including 11 newly developed markers). Data were then analyzed by an approach combining both linkage and linkage disequilibrium information, making it possible to identify two linked QTL separated by 20 cM corresponding to approximately 29 Mb. The presence of a QTL affecting protein yield was confirmed but its position was found to be more telomeric than the two QTLunderlying fat yield. Each identified QTL affecting milk fat yield was physically mapped within a segment estimated to be <500 kb. Two strong functional candidate genes involved, respectively, in fatty acid metabolism and membrane permeability were found to be localized within this segment while other functional candidate genes were discarded. A haplotype comprising the favorable allele at each QTL position appears to be overrepresented in the artificial insemination bull population.     

A QTL affecting milk yield and composition maps to bovine chromosome 20: a confirmation

As part of a whole genome scan undertaken to detect quantitative trait loci (QTL) affecting milk yield and composition, we have genotyped a granddaughter design comprising 1152 sons for six microsatellite markers spanning bovine chromosome 20. An analysis performed across families provided strong evidence (experiment-wise P -values < 0·01) for the presence of a QTL affecting primarily protein percentage towards the telomeric end of the chromosome. A founder sire, shown in a previous study to segregate for a similar QTL in the corresponding chromosome region, was characterized by 29 and 57 sons and maternal grandsons, respectively, in the present design. Sorting corresponding sons and grandsons by paternal or grandpaternal allele provided significant evidence for the segregation of a QTL on chromosome 20. Altogether these results confirm the location of a QTL affecting milk production on bovine chromosome 20.     

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.     

Quantitative Trait Loci Analysis for Five Milk Production Traits on Chromosome Six in the Dutch Holstein-Friesian Population

Twenty Dutch Holstein-Friesian families, with a total of 715 sires, were evaluated in a granddaughter experiment design for marker-QTL associations. Five traits--milk, fat and protein yield and fat and protein percent--were analyzed. Across-family analysis was undertaken using multimarker regression principles. One and two QTL models were fitted. Critical values for the test statistic were calculated empirically by permuting the data. Individual trait distributions of permuted test statistics differed and, thus distributions, had to be calculated for each trait. Experimentwise critical values, which account for evaluating marker-QTL associations on all 29 autosomal bovine chromosomes and for five traits, were calculated. A QTL for protein percent was identified in one and two QTL models and was significant at the 1 and 2% level, respectively. Extending the multimarker regression approach to an analysis including two QTL was limited by families not being informative at all markers, which resulted in singularity. Below average heterozygosity for the first and last marker lowered information content for the first and last marker bracket. Highly informative markers at the ends of the mapped chromosome would overcome the decrease in information content in the first and last marker bracket and singularity for the two QTL model.     

Genes influencing milk production traits predominantly affect one of four biological pathways

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.     

Association of the heart fatty acid-binding protein (FABP3) gene with milk traits in Manchega breed sheep

The ovine fatty acid-binding protein type 3 gene has been chosen as a functional candidate gene for milk traits. Two different single nucleotide polymorphisms (SNPs) of ovine FABP3 gene have been tested in a daughter design comprising 13 families. No association was found between estimated breeding values for milk yield, protein and fat contents (FC) and genotypes across families using anova and transmission disequilibrium test (TDT). In within-family analysis, one family showed a significant effect for FC. These results could indicate linkage disequilibrium between the FABP3 gene and a quantitative trait loci (QTL) for FC, with the heterozygous genotype associated with a positive effect in this trait.     

A whole genome scan for quantitative trait loci affecting milk protein percentage in Israeli-Holstein cattle, by means of selective milk DNA pooling in a daughter design, using an adjusted false discovery rate criterion

Selective DNA pooling was employed in a daughter design to screen all bovine autosomes for quantitative trait loci (QTL) affecting estimated breeding value for milk protein percentage (EBVP%). Milk pools prepared from high and low daughters of each of seven sires were genotyped for 138 dinucleotide microsatellites. Shadow-corrected estimates of sire allele frequencies were compared between high and low pools. An adjusted false discovery rate (FDR) method was employed to calculate experimentwise significance levels and empirical power. Significant associations with milk protein percentage were found for 61 of the markers (adjusted FDR = 0.10; estimated power, 0.68). The significant markers appear to be linked to 19--28 QTL. Mean allele substitution effects of the putative QTL averaged 0.016 (0.009--0.028) in units of the within-sire family standard deviation of EBVP% and summed to 0.460 EBVP%. Overall QTL heterozygosity was 0.40. The identified QTL appear to account for all of the variation in EBVP% in the population. Through use of selective DNA pooling, 4400 pool data points provided the statistical power of 600,000 individual data points.     

Fine-mapping QTL for mastitis resistance on BTA9 in three Nordic red cattle breeds

A QTL affecting clinical mastitis and/or somatic cell score (SCS) has been reported previously on chromosome 9 from studies in 16 families from the Swedish Red and White (SRB), Finnish Ayrshire (FA) and Danish Red (DR) breeds. In order to refine the QTL location, 67 markers were genotyped over the whole chromosome in the 16 original families and 18 additional half-sib families. This enabled linkage disequilibrium information to be used in the analysis. Data were analysed by an approach that combines information from linkage and linkage disequilibrium, which allowed the QTL affecting clinical mastitis to be mapped to a small interval (<1 cM) between the markers BM4208 and INRA084 . This QTL showed a pleiotropic effect on SCS in the DR and SRB breeds. Haplotypes associated with variations in mastitis resistance were identified. The haplotypes were predictive in the general population and can be used in marker-assisted selection. Pleiotropic effects of the mastitis QTL were studied for three milk production traits and eight udder conformation traits. This QTL was also associated with yield traits in DR but not in FA or SRB. No QTL were found for udder conformation traits on chromosome 9.