The Heparan and Heparin Metabolism Pathway Is Involved in Regulation of Fatty Acid Composition

The Heparan and Heparin Metabolism Pathway Is Involved in Regulation of Fatty Acid Composition

Int. J. Biol. Sci. 2011, 7 659 Ivyspring International Publisher International Journal of Biological Sciences 2011; 7(5):659-663 Letter The Heparan and Heparin Metabolism Pathway is Involved in Regulation of Fatty Acid Composition Zhihua Jiang1,, Jennifer J. Michal1, Xiao-Lin Wu2, Zengxiang Pan1 and Michael D. MacNeil3 1. Department of Animal Sciences, Washington State University, Pullman, WA 99164-6351, USA; 2. Department of Dairy Science, University of Wisconsin-Madison, Madison, WI 53706-1284, USA; 3. USDA-ARS, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT 59301, USA Corresponding author: Dr. Zhihua Jiang, Phone: 509-335-8761; Fax: 509-335-4246; Email: [email protected] © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons License (http://creativecommons.org/ licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited. Received: 2011.03.04; Accepted: 2011.05.16; Published: 2011.05.21 Abstract Six genes involved in the heparan sulfate and heparin metabolism pathway, DSEL (dermatan sulfate epimerase-like), EXTL1 (exostoses (multiple)-like 1), HS6ST1 (heparan sulfate 6-O-sulfotransferase 1), HS6ST3 (heparan sulfate 6-O-sulfotransferase 3), NDST3 (N-deacetylase/N-sulfotransferase (heparan glucosaminyl) 3), and SULT1A1 (sul- fotransferase family, cytosolic, 1A, phenol-preferring, member 1), were investigated for their associations with muscle lipid composition using cattle as a model organism. Nineteen single nucleotide polymorphisms (SNPs)/multiple nucleotide length poly- morphisms (MNLPs) were identified in five of these six genes. Six of these mutations were then genotyped on 246 Wagyu x Limousin F2 animals, which were measured for 5 carcass, 6 eating quality and 8 fatty acid composition traits. Association analysis revealed that DSEL, EXTL1 and HS6ST1 significantly affected two stearoyl-CoA desaturase activ- ity indices, the amount of conjugated linoleic acid (CLA), and the relative amount of saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) in skeletal muscle (P<0.05). In particular, HS6ST1 joined our previously reported SCD1 and UQCRC1 genes to form a three gene network for one of the stearoyl-CoA desaturase activity indices. These results provide evidence that genes involved in heparan sulfate and heparin me- tabolism are also involved in regulation of lipid metabolism in bovine muscle. Whether the SNPs affected heparan sulfate proteoglycan structure is unknown and warrants fur- ther investigation. Key words: Heparan sulfate and heparin metabolism pathway, muscle fatty acid composition, as- sociations, genetic networks. Research has shown that the enzymes and pro- lism [1]. Both heparan sulfate and heparin are mem- teins encoded by DSEL (dermatan sulfate epi- bers of the glycosaminoglycan family of carbohy- merase-like), EXTL1 (exostoses (multiple)-like 1), drates that are very closely related in structure. As HS6ST1 (heparan sulfate 6-O-sulfotransferase 1), reviewed by Kolset and Salmivirta [2], cell surface HS6ST3 (heparan sulfate 6-O-sulfotransferase 3), heparan sulfate proteoglycans play biological roles in NDST3 (N-deacetylase/N-sulfotransferase (heparan several aspects of lipoprotein metabolism. For exam- glucosaminyl) 3), and SULT1A1 (sulfotransferase ple, the binding of lipoproteins to heparan sulfate family, cytosolic, 1A, phenol-preferring, member 1), presents an important process for the cellular uptake are involved in heparan sulfate and heparin metabo- and turnover of lipoproteins. Heparan sulfate also http://www.biolsci.org Int. J. Biol. Sci. 2011, 7 660 serves as a primary interaction site for lipoprotein Table 1. Primers designed for mutation detection in six lipase and hepatic lipase on cell surfaces and trans- bovine genes ports lipoprotein lipase from extravascular cells to the Region Primer sequences (5’-3’) Size Tm luminal surface of the endothelia. Furthermore, Wilsie DSEL and colleagues [3] found that heparan sulfate proteo- Promoter F-GGAAGCAAGACGCTCTTCATTTGT 551 bp 60°C glycans facilitate fatty acid transport across the plas- ma membrane of adipocytes, thus contributing to in- R-AAAGAGGAGCCCAGATGCAAAGAT tracellular lipid accumulation in the cell. On the other 3’UTR (I) F-CAGCACAGTTTTTGGTGATTTGGT 553 bp 60°C hand, heparin has been reported to decrease the deg- R-TTTTCTGCCAACATGAAGGGAAAT radation rate of lipoprotein lipase in adipocytes [4] 3’UTR (II) F-TTCCAAACCTTAGCCGGGTATCTT 572 bp 60°C and promote adipocyte differentiation [5]. In the pre- R-AGCTGAAATCATGGGACTGCATTT sent study, we tested the hypothesis that genes in- EXTL1 volved in heparan sulfate and heparin metabolism are Exon 1 F- CTCACAGACAGGAGCCAATCAGAG 584 bp 60°C also involved in regulation of lipid metabolism in R- CCTGACCTTAGCCTTGAGGGAGAG bovine muscle. Cattle were used as a model organism in the 3’UTR (I) F- CGTAAGAAGTATCGCAGCCTGGAG 571 bp 60°C present study. The bovine DSEL, EXTL1, HS6ST1, R- CCAGGCACGTAGCTGATGTCTATC HS6ST3, NDST3 and SULT1A1 genes were annotated 3’UTR (II) F- GCCTAATGAACTCCACGCCTACAC 589 bp 60°C using a protocol described previously [6]. In brief, a R- GCTACCACTCAGCCCACCTAGAAA cDNA sequence for each of these genes was retrieved HS6ST1 from the GenBank database and then extended to a 3’UTR F- AGTCCCTAGACTGAGGGGAGCTGT 588 bp 60°C full length cDNA sequence using electronic rapid R- AGCGTTTGCAATGGACTGAACAT amplification of cDNA ends (e-RACE) [7]. Next, the HS6ST3 full-length cDNA sequence was used to search for 3’UTR (I) F- GCTTGGATGTTCTGCTGAAACTGA 571 bp 60°C genomic DNA contigs against the 7.15X bovine ge- nome sequence database (see the Bovine Genome R- AAGAGGCCTGCTCCAAATAGGAAA Resources at NCBI). A total of 15 primer pairs were 3’UTR (II) F- AAGGAGCTGAAGGCAAAATGAGTG 537 bp 60°C designed to amplify various targets located in 6 genes R- TCTGGACAATAACGGGTGGTTTCT (Table 1). Approximately 50 ng of genomic DNA from 3’UTR F- TCTCCCTTCCTGATGATTTGTTCC 550 bp 60°C (III) each of six Wagyu x Limousin F1 bulls were amplified in a final volume of 10 μl that contained 12.5 ng of R- GGAGAGGACAAGTGTGTTGCTTCA NDST3 each primer, 150 μM dNTPs, 1.5 mM MgCl2, 50 mM KCl, 20 mM Tris-HCl and 0.25 U of AmpliTaq Gold Exon 2 F- CATTCTCCATTGCTTCACATGACC 520 bp 60°C polymerase (Applied Biosystems, Branchburg, NJ). R- ATGGCAGACAACTCATCCCAGTTT PCR conditions were as follows: 95ºC for 10 minutes, Exon 14 F- CTTGTATCTCCTCCTCCCACCTCA 538 bp 60°C 35 cycles of 94ºC for 30 sec, 60ºC for 30 sec, and 72ºC R- CAGGCAAACAGCAGCCTAAAAGTC for 30 sec, and an extension step at 72ºC for 10 min. SULT1A1 PCR amplicons were sequenced on a capillary se- Promoter F- AGGCAAGAATACTGGAGTGGGTTG 601 bp 60°C quencer by High-Throughput Sequencing Solutions (Seattle, WA). A total of 19 mutations were identified R- AGATGCCAAGAGTTCAGGTGGAAG in five of these six genes, including 2 single nucleotide Exon 8 F- AGAGGACCACAGTCAAGGAACAGG 576 bp 60°C polymorphisms (SNP) in DSEL, 1 multiple nucleotide R- ATATGCCTCCAGAGGACCACTCAC length polymorphism (MNLP) in EXTL1, 8 SNPs in 3’UTR F- CTGTTGGGAGCAAAGAACAAACCT 507 bp 60°C HS6ST1, 3 SNPs and 1 MNLP in HS6ST3 and 4 SNPs R- GACTGCGTTCACACATCTCCACTT in NDST3, respectively (Figure S1). Based on the ini- tial linkage disequilibrium of these mutations ob- served among six Wagyu x Limousin F bulls and 1 As described previously [8-9], 19 phenotypes their compatibility in forming multiplexes for geno- were measured on these F animals, including 5 car- typing with the Sequenom iPLEX assay design, only 2 cass, 6 eating quality and 8 fatty acid composition six mutations (see Figure S1) were genotyped on 246 traits. Associations between genotypes and pheno- F animals by the Genomics Center at the University 2 types were evaluated using linear models described of Minnesota. previously by Daniels et al. [6]. Systematic factors in the linear models included the effects of harvest year http://www.biolsci.org Int. J. Biol. Sci. 2011, 7 661 (i=1,2,3), sex (j=1,2), sire (k=1,2,3,4,5,6), and age in cantly affected MUFA in an additive QTM. The p days at harvest (as a covariate). The effects of markers values of genetic modes were obtained from Monte were estimated either individually in the model or Carlo simulation with 10,000 replicates. For example, jointly in a multiple regression. In single-marker over-dominance genetic mode was evaluated as Hα: { analyses, ANOVA was conducted by testing the ˆQq max ˆ qq , ˆ QQ or ˆQq min ˆ qq , ˆ QQ } vs. model with the presence of marker effects 3 H0: {Otherwise}, where ˆ X was the estimated effect ( y* x b e ) vs. the model assuming null i ij j i of genotype X. Note that, when two or more markers j1 (genes) significantly affected a trait, the effects esti- marker effects ( y *=µ+e ), where y * is the phenotypic i i i mated by single marker analyses were theoretically value of the i-th individual which has been adjusted biased. So, the three markers with their QTMs on dif- for the effects of harvest years, sexes, sires, and age in ferent phenotypes were then merged with other days at harvest using a full model. Equivalently, this markers previously reported by Jiang et al. [9] and yields the null hypothesis H : µ = µ = µ = µ vs. the 0 1 2 3 combined into a multiple regression analysis for each alternative H : {Otherwise), where µ = µ+b is the α i i trait in attempt to identify their roles in the genetic mean of the i-th genotypes. The resulting p values regulation of fatty acid composition. The AIC-based were adjusted using the Bonferroni correction [10]. model selection suggested that the addition of Briefly, let the significance level for the whole family HS6ST1 with SCD1 and UQCRC1 formed a three-gene of tests be (at most) α, then the Bonferroni correction network for R3 (Figure 1B), because it had a smaller evaluate each of the individual association tests at a AIC value (which was 1499.11) than the model fea- significance level of α/n, where n = 6 is the number of turing a two-gene (UQCRC1 and SCD1) network independent tests (i.e., association tests per trait under (which was 1521.87).

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