0000000000040441

AUTHOR

Torfinn Nome

MOESM2 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 2: Table S2. Primer sequences used for the reverse transcription qPCR (RT-qPCR).

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Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Background Bovine milk is widely regarded as a nutritious food source for humans, although the effects of individual fatty acids on human health is a subject of debate. Based on the assumption that genomic selection offers potential to improve milk fat composition, there is strong interest to understand more about the genetic factors that influence the biosynthesis of bovine milk and the molecular mechanisms that regulate milk fat synthesis and secretion. For this reason, the work reported here aimed at identifying genetic variants that affect milk fatty acid composition in Norwegian Red cattle. Milk fatty acid composition was predicted from the nation-wide recording scheme using Fourier tr…

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Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Background Clinical mastitis is an inflammation of the mammary gland and causes significant costs to dairy production. It is unfavourably genetically correlated to milk production, and, thus, knowledge of the mechanisms that underlie these traits would be valuable to improve both of them simultaneously through breeding. A quantitative trait locus (QTL) that affects both clinical mastitis and milk production has recently been fine-mapped to around 89 Mb on bovine chromosome 6 (BTA6), but identification of the gene that underlies this QTL was not possible due to the strong linkage disequilibrium between single nucleotide polymorphisms (SNPs) within this region. Our aim was to identify the gen…

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MOESM3 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 3: Figure S1. Further description of the procedure for estimating DBP protein levels. Detailed description of the protocol for estimating the DBP levels in serum from 50 NR cows. Figure S1 gives a schematic explanation of vitamin D3 metabolism.

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MOESM1 of Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Additional file 1: Table S1. SNPs genotyped for the candidate gene map, with rs numbers, positions in base pairs and primer sequences.

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MOESM6 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 6: Table S5. Results for General Linear Model (GLM) analyses of effect of rs110675140 genotype on DBP, ALB, 25(OH)D2, 25(OH)D3 and total 25(OH)D; free 25(OH)D2, 25(OH)D3 and total 25(OH)D; bioavailable (i.e., free and ALB-bound) 25(OH)D2, 25(OH)D3 and total 25(OH)D; DBP-bound total 25(OH)D; and ALB-bound total 25(OH)D serum concentrations. Detailed results of GLM analyses of genotype effect on several serum protein levels in 50 NR cows.

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MOESM5 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 5: Table S4. Results for single marker association analyses of CM1, CM4, CM6, kg milk, kg protein and kg fat on imputed full sequence data. Positions in basepairs, rs numbers, â log10(p value), minor allele frequency, SNP effects, alleles, putative consequences of the variants on the protein sequence and nearest gene for the imputed full sequence SNPs. The file contains six sheets, one for each tested trait.

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MOESM1 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 1: Table S1. SNP genotype, pregnancy status, age, lactation number and lactation status for the cows used for analyses of protein concentrations and ligand binding.

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MOESM4 of Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Additional file 4: Table S4. Results from single-marker association analyses on BTA13 data from the BovineHD BeadChip.

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MOESM2 of Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Additional file 2: Table S2. Results for calibration of FTIR-spectra against GC-FID reference data, correlations between each FA and total fat percentage, and estimates of variance components with standard errors.

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MOESM3 of Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Additional file 3: Table S3. GWAS results.

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MOESM5 of Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13

Additional file 5: Table S5. Results from single-marker association analyses on SNPs in the candidate gene region.

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MOESM4 of Fine mapping of a QTL on bovine chromosome 6 using imputed full sequence data suggests a key role for the group-specific component (GC) gene in clinical mastitis and milk production

Additional file 4: Table S3. Results for single marker association analyses of seven mastitis traits and five milk traits on BTA6 markers from the Illumina BovineHD BeadChip. rs numbers, positions in basepairs, â log10(p value), SNP effects and alleles for all markers on BTA6 on the Illumina BovineHD BeadChip. The file contains twelve sheets, one for each trait.

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