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.     

Revisiting the quantitative trait loci for milk production traits on BTA6

A parallel association study was performed in two independent cattle populations based on 41 validated, targeted single nucleotide polymorphisms (SNPs) and four microsatellite markers to re-evaluate the multiple quantitative trait loci (QTL) architecture for milk performance on bovine chromosome 6 (BTA6). Two distinct QTL located in the vicinity of the middle region of BTA6, but differing unambiguously regarding their effects on milk composition and yield traits were validated in the German Holstein population. A highly significant association of the protein variant ABCG2 p.Tyr581Ser with milk composition traits reconfirmed the causative molecular relevance of the ABCG2 gene in QTL region 1, whereas in QTL region 2, significant and tentative associations between gene variants RW070 and RW023 (located in the promoter region and exon 9 of the PPARGC1A gene for milk yield traits) were detected. For the German Fleckvieh population, only RW023 showed a tentative association with milk yield traits, whereas those loci with significant effects in German Holsteins (ABCG2 p.Tyr581Ser, RW070) showed fixed alleles. Even though our new data highlight two variants in the PPARGC1A gene (RW023, RW070) in QTL region 2, based on the results of our study, currently no unequivocal conclusion about the causal background of this QTL affecting milk yield traits can be drawn. Notably, the German Holstein and Fleckvieh populations, known for their divergent degree of dairy type, differ substantially in their allele frequencies for the growth-associated NCAPG p.Ile442Met locus.     

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.     

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.     

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.     

Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers

Quantitative trait loci (QTL) affecting health and milk production traits were studied in seven large half-sib US Holstein families by using the granddaughter design. Genotyping for 16 markers was completed and marker allele differences within and pooled-across families were analysed. Potential QTL were identified for somatic cell score (SCS), fat yield, fat percentage, protein yield and protein percentage. Three markers (BM203, BM4505 and BM2078) were associated with significant effects for different traits and, after further analysis, may be useful in marker-assisted selection in specific families. Comparisons between these data and previously identified QTL support the location of a QTL for milk yield and protein yield on chromosome 21.     

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).     

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 for fertility traits in Finnish Ayrshire cattle

A whole genome scan was carried out to detect quantitative trait loci (QTL) for fertility traits in Finnish Ayrshire cattle. The mapping population consisted of 12 bulls and 493 sons. Estimated breeding values for days open, fertility treatments, maternal calf mortality and paternal non-return rate were used as phenotypic data. In a granddaughter design, 171 markers were typed on all 29 bovine autosomes. Associations between markers and traits were analysed by multiple marker regression. Multi-trait analyses were carried out with a variance component based approach for the chromosomes and trait combinations, which were observed significant in the regression method. Twenty-two chromosome-wise significant QTL were detected. Several of the detected QTL areas were overlapping with milk production QTL previously identified in the same population. Multi-trait QTL analyses were carried out to test if these effects were due to a pleiotropic QTL affecting fertility and milk yield traits or to linked QTL causing the effects. This distinction could only be made with confidence on BTA1 where a QTL affecting milk yield is linked to a pleiotropic QTL affecting days open and fertility treatments.     

Modelling QTL effect on BTA06 using random regression test day models

In statistical models, a quantitative trait locus (QTL) effect has been incorporated either as a fixed or as a random term, but, up to now, it has been mainly considered as a time-independent variable. However, for traits recorded repeatedly, it is very interesting to investigate the variation of QTL over time. The major goal of this study was to estimate the position and effect of QTL for milk, fat, protein yields and for somatic cell score based on test day records, while testing whether the effects are constant or variable throughout lactation. The analysed data consisted of 23 paternal half-sib families (716 daughters of 23 sires) of Chinese Holstein-Friesian cattle genotyped at 14 microsatellites located in the area of the casein loci on BTA6. A sequence of three models was used: (i) a lactation model, (ii) a random regression model with a QTL constant in time and (iii) a random regression model with a QTL variable in time. The results showed that, for each production trait, at least one significant QTL exists. For milk and protein yields, the QTL effect was variable in time, while for fat yield, each of the three models resulted in a significant QTL effect. When a QTL is incorporated into a model as a constant over time, its effect is averaged over lactation stages and may, thereby, be difficult or even impossible to be detected. Our results showed that, in such a situation, only a longitudinal model is able to identify loci significantly influencing trait variation.     

Mapping of quantitative trait loci for carcass traits in a Japanese Black (Wagyu) cattle population

To detect quantitative trait loci (QTL) that influence economically important traits in a purebred Japanese Black cattle population, we performed a preliminary genome-wide scan using 187 microsatellite markers across a paternal half-sib family composed of 258 offspring. We located six QTL at the 1% chromosome-wise level on bovine chromosomes (BTA) 4, 6, 13, 14 and 21. A second screen of these six QTL regions using 138 additional paternal offspring half-sib from the same sire, provided further support for five QTL: carcass weight on BTA14 (22-39 cM), one for rib thickness on BTA6 (27-58 cM) and three for beef marbling score (BMS) on BTA4 (59-67 cM), BTA6 (68-89 cM) and BTA21 (75-84 cM). The location of QTL for subcutaneous fat thickness on BTA13 was not supported by the second screen (P > 0.05). We determined that the combined contribution of the three QTLs for BMS was 10.1% of the total variance. The combined phenotypic average of these three Q was significantly different (P < 0.001) from those of other allele combinations. Analysis of additional half-sib families will be necessary to confirm these QTL.     

Characterization and RH mapping of bovine microsatellites generated from a microdissected BTA20-specific DNA library

Bovine chromosome 20 (BTA20) is associated with several quantitative trait loci (QTL) for meat tenderness, birth weight, milk yield and composition. Fine mapping of these QTL requires the development of additional informative markers to increase the resolution of the BTA20 genetic and physical maps. A BTA20-specific library was constructed by means of microdissection and microcloning, and screened for dinucleotide repeats with (CA)16 and (GT)16 oligos. A total of 60 new microsatellites (MS) were developed and characterized for polymorphism using the U.S. Department of Agriculture (USDA)/Meat Animal Research Center (MARC) bovine reference family, of which 53 markers were informative in this family. The number of alleles for these loci varied from 1 to 14, with an average of 6.5. Thirty-three of these MSs, together with 105 markers previously mapped to BTA20, were scored on a 7000-rad cattle-hamster whole-genome radiation hybrid panel (SUNbRH), resulting in a high-resolution RH7000 rad map for BTA20.     

Testing for the presence of previously identified QTL for milk production traits in new populations

Five chromosomal regions previously associated with milk production traits were tested in 16 families of Black and White cattle from the UK. The traits were also linearly transformed into genetically and phenotypically independent variables normalized by phenotypic variances ('canonical traits'). Significant associations with the untransformed and canonical traits were found for bovine chromosome 6. There was also evidence that chromosome 9 influenced these traits. The linear transformation clarified the effects of chromosomal regions; regions with effects on all three untransformed traits (milk, fat and protein yields) were generally condensed into an effect on a single canonical trait. Comparison of our results with those reported previously for American Holstein cattle suggested that the QTL may not be the same.     

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.     

Genome-wide association and biological pathway analysis for milk-fat composition in Danish Holstein and Danish Jersey cattle

Background

The milk fat profile of the Danish Holstein (DH) and Danish Jersey (DJ) show clear differences. Identification of the genomic regions, genes and biological pathways underlying the milk fat biosynthesis will improve the understanding of the biology underlying bovine milk fat production and may provide new possibilities to change the milk fat composition by selective breeding. In this study a genome wide association scan (GWAS) in the DH and DJ was performed for a detailed milk fatty acid (FA) profile using the HD bovine SNP array and subsequently a biological pathway analysis based on the SNP data was performed.

Results

The GWAS identified in total 1,233 SNPs (FDR < 0.10) spread over 18 chromosomes for nine different FA traits for the DH breed and 1,122 SNPs (FDR < 0.10) spread over 26 chromosomes for 13 different FA traits were detected for the DJ breed. Of these significant SNPs, 108 SNP markers were significant in both DH and DJ (C14-index, BTA26; C16, BTA14; fat percentage (FP), BTA14). This was supported by an enrichment test. The QTL on BTA14 and BTA26 represented the known candidate genes DGAT and SCD. In addition we suggest ACSS3 to be a good candidate gene for the QTL on BTA5 for C10:0 and C15:0. In addition, genetic correlations between the FA traits within breed showed large similarity across breeds. Furthermore, the biological pathway analysis revealed that fat digestion and absorption (KEGG04975) plays a role for the traits FP, C14:1, C16 index and C16:1.

Conclusion

There was a clear similarity between the underlying genetics of FA in the milk between DH and DJ. This was supported by the fact that there was substantial overlap between SNPs for FP, C14 index, C14:1, C16 index and C16:1. In addition genetic correlations between FA showed a similar pattern across DH and DJ. Furthermore the biological pathway analysis suggested that fat digestion and absorption KEGG04975 is important for the traits FP, C14:1, C16 index and C16:1.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1112) contains supplementary material, which is available to authorized users.     

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.     

Radiation hybrid and genetic linkage mapping of two genes related to fat metabolism in cattle: fatty acid synthase (FASN) and glycerol-3-phosphate acyltransferase mitochondrial (GPAM)

Fatness traits, such as fat deposition, carcass composition, fat content, and the percentage of fat in milk, are economically relevant to cattle production. Fatty acid synthase (FASN) and glycerol-3-phosphate acyltransferase mitochondrial (GPAM) are two enzymes that play a central role in de novo lipogenesis. Both could be putative candidate genes for quantitative trait loci (QTL). Several clones containing the fatty acid synthase (FASN) and glycerol-3-phosphate acyltransferase mitochondrial (GPAM) genes were isolated after screening the INRA bovine bacterial artificial chromosome (BAC) library using PCR. Five microsatellite loci were derived from the BAC clones containing the genes of interest with heterozygosity values ranging from 27 to 78%, using DNA samples from the International Bovine Reference Panel (IBRP). The newly developed markers were genotyped on the IBRP animals and on a radiation hybrid panel to compare the obtained linkage and RH maps. Radiation hybrid maps were developed for chromosome BTA19 and BTA26 regions containing FASN and GPAM genes, respectively. The two genes and their associated microsatellite markers were located on the genetic or RH maps or on both. These microsatellite markers could be useful to study the QTL effect on fat synthesis in reference population.     

Verification of selective DNA pooling methodology through identification and estimation of the DGAT1 effect

The discovery of markers linked to genes that are responsible for traits of interest to the dairy industry might prove useful because they could aid in selection and breeding decisions. We have developed a selective DNA pooling methodology to allow us to efficiently screen the bovine genome in order to find genes responsible for production traits. Using markers on chromosome 14 as a test case, we identified a gene (DGAT1) previously known to affect three traits (fat yield, protein yield and total milk yield). Furthermore, we predicted similar effects to those previously shown for DGAT1 in a New Zealand Holstein-Friesian herd. Additionally, we showed a low error rate (1.6%) for the pooling procedure. Hence we are confident that we can apply this procedure to an entire genome scan in the search for quantitative trait loci (QTL).     

Whole genome scan to detect quantitative trait loci for bovine milk protein composition

The objective of this study was to perform a whole genome scan to detect quantitative trait loci (QTL) for milk protein composition in 849 Holstein–Friesian cows originating from seven sires. One morning milk sample was analysed for the major milk proteins using capillary zone electrophoresis. A genetic map was constructed with 1341 single nucleotide polymorphisms, covering 2829 centimorgans (cM) and 95% of the cattle genome. The chromosomal regions most significantly related to milk protein composition ( P _genome < 0.05) were found on Bos taurus autosomes (BTA) 6, 11 and 14. The QTL on BTA6 was found at about 80 cM, and affected α_S1-casein, α_S2-casein, β-casein and κ-casein. The QTL on BTA11 was found at 124 cM, and affected β-lactoglobulin, and the QTL on BTA14 was found at 0 cM, and affected protein percentage. The proportion of phenotypic variance explained by the QTL was 3.6% for β-casein and 7.9% for κ-casein on BTA6, 28.3% for β-lactoglobulin on BTA11, and 8.6% for protein percentage on BTA14. The QTL affecting α_S2-casein on BTA6 and 17 showed a significant interaction. We investigated the extent to which the detected QTL affecting milk protein composition could be explained by known polymorphisms in β-casein , κ -casein , β-lactoglobulin and DGAT1 genes. Correction for these polymorphisms decreased the proportion of phenotypic variance explained by the QTL previously found on BTA6, 11 and 14. Thus, several significant QTL affecting milk protein composition were found, of which some QTL could partially be explained by polymorphisms in milk protein genes.     

Multiple quantitative trait locus analysis of bovine chromosome 6 in the Israeli Holstein population by a daughter design

Nine Israeli Holstein sire families with 2978 daughters were analyzed for quantitative trait loci effects on chromosome 6 for five milk production traits by a daughter design. All animals were genotyped for 2 markers. The three families with significant effects were genotyped for up to 10 additional markers spanning positions 0-122 cM of BTA6. Two sires were segregating for a locus affecting protein and fat percentage near position 55 cM with an estimated substitution effect of 0.18% protein, which is equivalent to one phenotypic standard deviation. This locus was localized to a confidence interval of 4 cM. One of these sires was also heterozygous for a locus affecting milk, fat, and protein production near the centromere. The hypothesis of two segregating loci was verified by multiple regression analysis. A third sire was heterozygous for a locus affecting milk and protein percentage near the telomeric end of the chromosome. Possible candidates for the major quantitative gene near position 55 cM were determined by comparative mapping. IBSP and SSP1 were used as anchors for the orthologous region on human chromosome 4. Twelve genes were detected within a 2-Mbp sequence. None of these genes have been previously associated with lactogenesis.