Polymorphisms in genes in the SREBP1 signalling pathway and SCD are associated with milk fatty acid composition in Holstein cattle

Department of Animal Science, University of California, Davis, CA 95616, USA.
Journal of Dairy Research (Impact Factor: 1.6). 11/2011; 79(1):1-10. DOI: 10.1017/S002202991100080X
Source: PubMed


Genes in the sterol regulatory element-binding protein-1 (SREBP1) pathway play a central role in regulation of milk fat synthesis, especially the de-novo synthesis of saturated fatty acids. SCD, a SREBP-responsive gene, is the key enzyme in the synthesis of monounsaturated fatty acids in the mammary gland. In the present study, we discovered SNP in candidate genes associated with this signalling pathway and SCD to identify genetic markers that can be used for genetic and metabolically directed selection in cattle. We resequenced six candidate genes in the SREBP1 pathway (SREBP1, SCAP, INSIG1, INSIG2, MBTPS1, MBTPS2) and two genes for SCD (SCD1 and SCD5) and discovered 47 Tag SNP that were used in a marker-trait association study. Milk and blood samples were collected from Holstein cows in their 1st or 2nd parity at 100-150 days of lactation. Individual fatty acids from C4 to C20, saturated fatty acid (SFA) content, monounsaturated fatty acid content, polyunsaturated fatty acid content and desaturase indexes were measured and used to perform the asociation analysis. Polymorphisms in the SCD5 and INSIG2 genes were the most representative markers associated with SFA/unsaturated fatty acid (UFA) ratio in milk. The analysis of desaturation activity determined that markers in the SCD1 and SCD5 genes showed the most significant effects. DGAT1 K232A marker was included in the study to examine the effect of this marker on the variation of milk fatty acids in our Holstein population. The percentage of variance explained by DGAT1 in the analysis was only 6% of SFA/UFA ratio. Milk fat depression was observed in one of the dairy herds and in this particular dairy one SNP in the SREBP1 gene (rs41912290) accounted for 40% of the phenotypic variance. Our results provide detailed SNP information for key genes in the SREBP1 signalling pathway and SCD that can be used to change milk fat composition by marker-assisted breeding to meet consumer demands regarding human health, as well as furthering understanding of technological aspects of cows' milk.

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Available from: Gonzalo Rincon, Jul 07, 2015
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    • "Marker-trait association analysis was performed under an additive model (Rincon et al. 2012), using the genotype association and regression modules from SNP Variation Suite (SVS) Version 7 (Golden Helix Inc., Bozeman MT, USA) (Rincon et al. 2009a, b). An F test was performed to find significant associations, and a p value threshold of 0.05 was established. "
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    ABSTRACT: The objectives of this study were to measure gene expression in zebrafish and then identify SNP to be used as potential markers in a growth association study. We developed an approach where muscle samples collected from low- and high-growth fish were analyzed using RNA-Sequencing (RNA-seq), and SNP were chosen from the genes that were differentially expressed between the low and high groups. A population of 24 families was fed a plant protein-based diet from the larval to adult stages. From a total of 440 males, 5 % of the fish from both tails of the weight gain distribution were selected. Total RNA was extracted from individual muscle of 8 low-growth and 8 high-growth fish. Two pooled RNA-Seq libraries were prepared for each phenotype using 4 fish per library. Libraries were sequenced using the Illumina GAII Sequencer and analyzed using the CLCBio genomic workbench software. One hundred and twenty-four genes were differentially expressed between phenotypes (p value < 0.05 and FDR < 0.2). From these genes, 164 SNP were selected and genotyped in 240 fish samples. Marker-trait analysis revealed 5 SNP associated with growth in key genes (Nars, Lmod2b, Cuzd1, Acta1b, and Plac8l1). These genes are good candidates for further growth studies in fish and to consider for identification of potential SNPs associated with different growth rates in response to a plant protein-based diet.
    Marine Biotechnology 02/2015; 17(3). DOI:10.1007/s10126-015-9624-1 · 3.27 Impact Factor
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    • "Percentages of genetic variance explained by dinucleotide allele substitution of DGAT1:g.10433–10434AA N GC determined in our study did not exceed 18.5%, which agrees with earlier reports of relatively low phenotypic variance explained by this mutation [38], whereas other reports [41] [42] claimed up to 50% of genetic variance was explained by the substitution for some traits. For the first time we report results of association analysis between DGAT1:g.10433–10434AA "
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    ABSTRACT: Changing bovine milk fatty acid (FA) composition through selection can decrease saturated FA (SFA) consumption, improve human health and provide a means for manipulating processing properties of milk. Our study determined associations between milk FA composition and genes from triacylglycerol (TAG) biosynthesis pathway. The GC dinucleotide allele of diacylglycerol O-acyltransferase 1:g.10433-10434AA>GC was associated with lower palmitic acid (16:0) concentration but higher oleic (18:1 cis-9), linoleic (18:2 cis-9, cis-12) acid concentrations, and elongation index. Accordingly, the GC dinucleotide allele was associated with lower milk fat percentage and SFA concentrations but higher monounsaturated FA and polyunsaturated FA (PUFA) concentrations. The glycerol-3-phosphate acyltransferase, mitochondrial haplotypes were associated with higher myristoleic acid (14:1 cis-9) concentration and C14 desaturation index. The 1-acylglycerol-3-phosphate acyltransferase 1 haplotypes were associated with higher PUFA and linoleic acid concentrations. The results of this study provide information for developing genetic tools to modify milk FA composition in dairy cattle.
    Genomics 10/2014; 104(6). DOI:10.1016/j.ygeno.2014.10.001 · 2.28 Impact Factor
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    • "The gene families MAP kinase, P13K and frizzled were not included in the pathways since specific genes were not suggested in the reviews and these gene families have a wide range of signalling functions. The genomic location of these genes were determined using UMD3.1 in the NCBI database [26]. The SNPs within the genes of a pathway, or within 100 kb to each side of those genes, were then tested for association with each trait using the model above. "
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    ABSTRACT: The maintenance of lactation in mammals is the result of a balance between competing signals from mammary development, prolactin signalling and involution pathways. Dairy cattle are an interesting case study to investigate the effect of polymorphisms that affect the function of genes in these pathways. In dairy cattle, lactation yields and milk composition (for example protein percentage and fat percentage) are routinely recorded, and these vary greatly between individuals. In this study, we test 8058 single nucleotide polymorphisms in or close to genes in these pathways for association with milk production traits and determine the proportion of variance explained by each pathway, using data on 16 812 dairy cattle, including Holstein-Friesian and Jersey bulls and cows. Single nucleotide polymorphisms close to genes in the mammary development, prolactin signalling and involution pathways were significantly associated with milk production traits. The involution pathway explained the largest proportion of genetic variation for production traits. The mammary development pathway also explained additional genetic variation for milk volume, fat percentage and protein percentage. Genetic variants in the involution pathway explained considerably more genetic variation in milk production traits than expected by chance. Many of the associations for single nucleotide polymorphisms in genes in this pathway have not been detected in conventional genome-wide association studies. The pathway approach used here allowed us to identify some novel candidates for further studies that will be aimed at refining the location of associated genomic regions and identifying polymorphisms contributing to variation in lactation volume and milk composition.
    Genetics Selection Evolution 04/2014; 46(1):29. DOI:10.1186/1297-9686-46-29 · 3.82 Impact Factor
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