# Dynamic Expression of Genes Involved in Proteoglycan/Glycosaminoglycan Metabolism during Skin Development

Authors: P. J. E. Uijtdewilligen; E. M. Versteeg; E. M. A. van de Westerlo; J. van der Vlag; W. F. Daamen; T. H. van Kuppevelt
Journal: BioMed Research International
 (2018)

---

## Abstract

Glycosaminoglycans are important for cell signaling and therefore for proper embryonic development and adult homeostasis. Expressions of genes involved in proteoglycan/glycosaminoglycan (GAG) metabolism and of genes coding for growth factors known to bind GAGs were analyzed during skin development by microarray analysis and real time quantitative PCR. GAG related genes were organized in six categories based on their role in GAG homeostasis,viz. (1) production of precursor molecules, (2) production of core proteins, (3) synthesis of the linkage region, (4) polymerization, (5) modification, and (6) degradation of the GAG chain. In all categories highly dynamic up- and downregulations were observed during skin development, including differential expression of GAG modifying isoenzymes, core proteins, and growth factors. In two mice models, one overexpressing heparanase and one lacking C5 epimerase, differential expression of only few genes was observed. Data show that during skin development a highly dynamic and complex expression of GAG-associated genes occurs. This likely reflects quantitative and qualitative changes in GAGs/proteoglycans, including structural fine tuning, which may be correlated with growth factor handling.


---

## Body

## 1. Introduction

During various cell signaling processes, glycosaminoglycans (GAGs), such as heparan sulfate (HS), chondroitin sulfate (CS), and dermatan sulfate (DS), play a role in binding, guiding, and modulating signaling molecules,e.g., growth factors and morphogens [1–3]. In skin this role can be illustrated by the importance of GAGs in adult wound healing [2, 4] and in the extracellular matrix architecture formed during dermal development [5, 6]. A further example to illustrate the importance of GAGs comes from mice overexpressing heparanase, an enzyme involved in the degradation of HS, showing accelerated hair growth [7], indicating its involvement in hair follicle morphogenesis and homeostasis. Other observations show that HS is involved in hair follicle cycling, sebaceous gland morphogenesis, and homeostasis [8]. Finally, HS and heparanase influence wound healing in adult mice by enhancing keratinocyte migration and stimulating blood vessel maturation [9]. Taken together, GAGs play an important role in skin healing and development and this prompted us to evaluate the expression of GAG related genes during (embryonic) development in skin.Inhibition of the expression of genes coding for enzymes involved in GAG modification reactions clearly indicates the importance of GAGs during organogenesis [10], especially with respect to growth factor handling. For example, mice deficient in Ndst1 (N-deacetylase sulfotransferase isoenzyme 1) die neonatally due to several defects in which defective sonic hedgehog (Shh) signaling is implicated [11, 12]; mice deficient in Hs2st (heparan sulfate 2-O sulfotransferase) or Glce (glucuronic acid epimerase) display renal agenesis [13, 14], whereas mice deficient in Hs6st1 (heparan sulfate 6-O sulfotransferase isozyme 1) show aberrant signaling of VEGF (vascular endothelial growth factor) and impaired lung development [15]. A skin phenotype of the above mouse models, however, has not been reported.In general, it is thought that specific modifications of the GAG chain are involved in the binding and modulation of signaling molecules resulting in cell-type and/or tissue specific reactions [2, 3]. GAG mimetics like the RGTAs (regenerating agents) have been used to treat skin disorders and improve skin healing [16, 17]. To obtain insight in GAG metabolism during skin development we studied the expression of GAG related genes covering six functional classes ranging from the synthesis of precursor molecules to the synthesis and degradation of GAGs. In addition, we probed the expression of a number of (GAG binding) signaling molecules.


## 2. Materials and Methods

An overview of the experimental setup on the gene expression during murine skin development is given in Figure1.Figure 1
Experimental setup used for the analysis of gene expression involved in GAG biology during skin development in mice. Based on literature data, specific time points in skin development were selected. RNA was isolated, verified, and subsequently analyzed with GeneChip exon arrays and TLDA gene expression cards.


### 2.1. Animals for the Study on Skin Development

NIH guidelines for the care and use of laboratory animals (NIH publication 85–23 Rev. 1985) were followed. The study was approved by the Ethics Committee of the Radboud university medical center (DEC 2005-111, project: 81027). C57BL6/j mice were obtained from Elevage Janvier (Le Genest Saint Isle, France). Mice aged 90 days (90 days post birth [P90]) were used for timed mating and dorsal skin was collected at 14 days (E14) and 16 days after conception (E16). At E14 hair follicle development is initiated, and at E16 this process is almost completed in combination with a stratified epidermis and organized dermis [18, 19]. For the RNA samples of E14, dorsal skin of seven embryos from one female was pooled and used for RNA isolation. Skin was isolated at E14 by snap freezing the whole embryo in liquid nitrogen followed by scraping the skin layer in a cryomicrotome with a scalpel to minimize contamination with other embryonic tissues (skin is very thin at this time point). Samples were stored at -80°C. RNA samples for E16 were taken from two females, collecting dorsal skin form 7 embryos each. In addition, skin from 1-day old pups (P1) and adult mice (P90) was collected. At P1 skin is more organized and has been exposed to air [18, 19]. For the two dorsal skin samples for P1, three pups from two females were taken per sample. Two adult three-month old mice were used for the two dorsal skin samples at P90. Samples for RNA isolation for E16, P1, and P90 were collected by removing dorsal skin and snap freezing it in liquid nitrogen and storage at -80°C.


### 2.2. Tissue of Genetically Modified Mice

Skin samples of glucuronic acid epimerase (Glce) knockout mice (E18.5 for expression analysis; E17.5 and E18.5 for histological analysis) and of heparanase overexpression (Hpse) mice (P70) were provided by Prof. Dr. Jin-Ping Li (Department of Medical Biochemistry and Microbiology, University of Uppsala, Sweden) and Prof. Dr. Israel Vlodavsky (Vascular and Cancer Biology Research Center Rappaport Faculty of Medicine and Research Institute Technion-Israel Institute of Technology, Israel), respectively [7, 20]. For RNA isolation two wildtype and two mutant mice were used of both mouse models.


### 2.3. RNA Isolation, Real Time Quantitative PCR, and Microarray Analysis

Frozen samples were grinded in a micro-dismembrator (Sartorius, Bunnik, The Netherlands) and RNA was isolated using the TRIZOL-method (Invitrogen, Paisley, UK) in combination with RNeasy Mini kit with DNAse step (Qiagen, Hilden, Germany). RNA quality was assessed using the Bioanalyzer system (Agilent Technologies, Amstelveen, The Netherlands). The RNA integrity numbers (RIN, 27) were 8.8±0.25 (technical replicate N=2), 8.0±0.35, 8.5±0.55, and 7.3±0.2 for E14, E16, P1, and P90 (biological replicates N=2), respectively. The same procedure was used for the RNA isolation for the Glce knockout mouse and Hpse overexpression mouse. The RIN was 6.5±0.51 forGlce-/- samples and 8.0±0.48 forGlce+/+ and 6.3±0.3 and 7.7±0.6 for HPA-TG and HPA-WT, respectively (all biological replicate N=2).Gene Chip Mouse exon 1.0 ST Arrays (Affymetrix, High Mycombe, UK) were used to analyze gene expression for E14, E16, P1, and P90 using 1μg of RNA per chip. Expression data were preprocessed to check sensitivity and specificity of the results based on Kadota et al. (2009) as shown in Uijtdewilligen et al. (2016) [18, 21]. Gene level expression data were calculated for the CORE transcripts (probe sets supported by RefSeq mRNAs) using Affymetrix Expression Console software with quantile normalization (all arrays are considered to have an equal intensity distribution), GC-content background correction (probes with high GC-content hybridize better, corrected for with built-in probes with different known GC-contents) and summarization with the RMA algorithm [22]. Data were imported into GeneSpring GX 7.3 (Agilent Technologies), duplicates were averaged, and the expression of each transcript was normalized to the median per array.Real Time-Quantitative PCR (qPCR) was performed using custom designed Taqman Low Density arrays (TLDA) (Applied Biosystems, Nieuwerkerk aan de IJssel, the Netherlands) containing probes against genes involved in GAG metabolism and GAG binding proteins (Supplementary data Table1). Glce and Hpse samples were analyzed using qPCR using custom designed TLDA with an adapted design containing additional GAG related genes (Supplementary data Table 2).For the TLDA cards, 100 ng cDNA in Taqman Universal PCR Master Mix (Applied Biosystems) was loaded on the TLDA card per slot and run on a 7900HT Fast Real Time PCR System (Applied Biosystems). Expression was analyzed based on the threshold cycle (Ct) which was obtained using the SDS 2.3 software and RQ Manager 1.2 of Applied Biosystems using the combined expression data of the tested TLDA cards. In Microsoft Excel the reference genes for ΔCt calculation were checked for stability of expression by analyzing the results of the reference genes across all used TLDA cards and selecting the reference genes with the smallest deviation across the cards tested. Subsequently ΔCt values were calculated using a reference gene with the smallest difference between the average Ct found for the gene of interest and for the reference gene. The obtained ΔCt values were further processed using the2-ΔΔCt method using P90 as a calibration point in case of the developmental study and the wild type background (C57BL6 mice) data in case of the two mouse models [23].


### 2.4. Statistical Methods

Statistical significance of the exon array data was analyzed using ANOVA and Benjamini-Hoghberg multiple testing correction [24]. Statistical significance of the TLDA card data was tested with an unpaired T-test (2-tailed) using Microsoft Excel. Data with a statistical threshold of p<0.10 and a fold threshold of >2.0 were considered statistically significant.


## 2.1. Animals for the Study on Skin Development

NIH guidelines for the care and use of laboratory animals (NIH publication 85–23 Rev. 1985) were followed. The study was approved by the Ethics Committee of the Radboud university medical center (DEC 2005-111, project: 81027). C57BL6/j mice were obtained from Elevage Janvier (Le Genest Saint Isle, France). Mice aged 90 days (90 days post birth [P90]) were used for timed mating and dorsal skin was collected at 14 days (E14) and 16 days after conception (E16). At E14 hair follicle development is initiated, and at E16 this process is almost completed in combination with a stratified epidermis and organized dermis [18, 19]. For the RNA samples of E14, dorsal skin of seven embryos from one female was pooled and used for RNA isolation. Skin was isolated at E14 by snap freezing the whole embryo in liquid nitrogen followed by scraping the skin layer in a cryomicrotome with a scalpel to minimize contamination with other embryonic tissues (skin is very thin at this time point). Samples were stored at -80°C. RNA samples for E16 were taken from two females, collecting dorsal skin form 7 embryos each. In addition, skin from 1-day old pups (P1) and adult mice (P90) was collected. At P1 skin is more organized and has been exposed to air [18, 19]. For the two dorsal skin samples for P1, three pups from two females were taken per sample. Two adult three-month old mice were used for the two dorsal skin samples at P90. Samples for RNA isolation for E16, P1, and P90 were collected by removing dorsal skin and snap freezing it in liquid nitrogen and storage at -80°C.


## 2.2. Tissue of Genetically Modified Mice

Skin samples of glucuronic acid epimerase (Glce) knockout mice (E18.5 for expression analysis; E17.5 and E18.5 for histological analysis) and of heparanase overexpression (Hpse) mice (P70) were provided by Prof. Dr. Jin-Ping Li (Department of Medical Biochemistry and Microbiology, University of Uppsala, Sweden) and Prof. Dr. Israel Vlodavsky (Vascular and Cancer Biology Research Center Rappaport Faculty of Medicine and Research Institute Technion-Israel Institute of Technology, Israel), respectively [7, 20]. For RNA isolation two wildtype and two mutant mice were used of both mouse models.


## 2.3. RNA Isolation, Real Time Quantitative PCR, and Microarray Analysis

Frozen samples were grinded in a micro-dismembrator (Sartorius, Bunnik, The Netherlands) and RNA was isolated using the TRIZOL-method (Invitrogen, Paisley, UK) in combination with RNeasy Mini kit with DNAse step (Qiagen, Hilden, Germany). RNA quality was assessed using the Bioanalyzer system (Agilent Technologies, Amstelveen, The Netherlands). The RNA integrity numbers (RIN, 27) were 8.8±0.25 (technical replicate N=2), 8.0±0.35, 8.5±0.55, and 7.3±0.2 for E14, E16, P1, and P90 (biological replicates N=2), respectively. The same procedure was used for the RNA isolation for the Glce knockout mouse and Hpse overexpression mouse. The RIN was 6.5±0.51 forGlce-/- samples and 8.0±0.48 forGlce+/+ and 6.3±0.3 and 7.7±0.6 for HPA-TG and HPA-WT, respectively (all biological replicate N=2).Gene Chip Mouse exon 1.0 ST Arrays (Affymetrix, High Mycombe, UK) were used to analyze gene expression for E14, E16, P1, and P90 using 1μg of RNA per chip. Expression data were preprocessed to check sensitivity and specificity of the results based on Kadota et al. (2009) as shown in Uijtdewilligen et al. (2016) [18, 21]. Gene level expression data were calculated for the CORE transcripts (probe sets supported by RefSeq mRNAs) using Affymetrix Expression Console software with quantile normalization (all arrays are considered to have an equal intensity distribution), GC-content background correction (probes with high GC-content hybridize better, corrected for with built-in probes with different known GC-contents) and summarization with the RMA algorithm [22]. Data were imported into GeneSpring GX 7.3 (Agilent Technologies), duplicates were averaged, and the expression of each transcript was normalized to the median per array.Real Time-Quantitative PCR (qPCR) was performed using custom designed Taqman Low Density arrays (TLDA) (Applied Biosystems, Nieuwerkerk aan de IJssel, the Netherlands) containing probes against genes involved in GAG metabolism and GAG binding proteins (Supplementary data Table1). Glce and Hpse samples were analyzed using qPCR using custom designed TLDA with an adapted design containing additional GAG related genes (Supplementary data Table 2).For the TLDA cards, 100 ng cDNA in Taqman Universal PCR Master Mix (Applied Biosystems) was loaded on the TLDA card per slot and run on a 7900HT Fast Real Time PCR System (Applied Biosystems). Expression was analyzed based on the threshold cycle (Ct) which was obtained using the SDS 2.3 software and RQ Manager 1.2 of Applied Biosystems using the combined expression data of the tested TLDA cards. In Microsoft Excel the reference genes for ΔCt calculation were checked for stability of expression by analyzing the results of the reference genes across all used TLDA cards and selecting the reference genes with the smallest deviation across the cards tested. Subsequently ΔCt values were calculated using a reference gene with the smallest difference between the average Ct found for the gene of interest and for the reference gene. The obtained ΔCt values were further processed using the2-ΔΔCt method using P90 as a calibration point in case of the developmental study and the wild type background (C57BL6 mice) data in case of the two mouse models [23].


## 2.4. Statistical Methods

Statistical significance of the exon array data was analyzed using ANOVA and Benjamini-Hoghberg multiple testing correction [24]. Statistical significance of the TLDA card data was tested with an unpaired T-test (2-tailed) using Microsoft Excel. Data with a statistical threshold of p<0.10 and a fold threshold of >2.0 were considered statistically significant.


## 3. Results

Genes involved in glycosaminoglycan (GAG) synthesis, modification, and degradation were studied during skin development at 14 and16 daysafterconception (E14 and E16, respectively) and at one day after birth (P1) and compared to mature skin of a 3 month old mouse (P90). In addition, two mouse models, a Glce knockout mouse (E18.5) and an Hpse overexpression mouse model (P70), were analyzed. Taqman Low Density Array (TLDA) cards were designed to contain genes involved in GAG metabolism (Supplementary data Tables 1 and 2). The expression data obtained using TLDA cards and exon arrays were screened for genes with 2-fold differential expression at a statistical threshold of p<0.10 (Tables 1, 2, 3, and 4, Supplementary data Tables 4, 5, and 6).Table 1
Comparison of the number of differentially expressed genes during skin development in mice (p<0.10, fold>2.0) based on real-time qPCR and on exon array analysis.
Total genes System  E14 vs. P90  E16 vs. P90  P1 vs. P90 Down Up  Down Up  Down Up Production of precursors 43 TLDA  1 4  3 2  1 2 43 Exon  2 6  2 0  1 0 Overlap  0 2  2 0  1 0 Core proteins 14 TLDA  2 3  1 1  2 2 14 Exon  3 2  1 1  0 2 Overlap  2 2  0 1  0 2 Preparation of linkage region 8 TLDA  0 1  0 1  0 1 8 Exon  0 2  0 0  0 0 Overlap  0 0  0 0  0 0 Glycosaminoglycan chain polymerisation 13 TLDA  1 4  1 2  0 2 13 Exon  1 2  0 0  0 0 Overlap  0 0  0 0  0 0 Glycosaminoglycan chain modification 32 TLDA  1 9  0 5  0 8 32 Exon  1 3  0 3  0 1 Overlap  1 2  0 1  0 0 Glycosaminoglycan chain degradation 19 TLDA  2 2  3 1  0 1 19 Exon  3 1  1 1  2 0 Overlap  2 1  1 1  0 0 Growth factors 37 TLDA  0 13  3 8  1 11 37 Exon  2 14  3 10  1 4 Overlap  0 10  2 8  0 4 ∗ P values for the exon array measurements were calculated using Benjamini–Hochberg multitesting correction. P values for the TLDA assay were calculated using an unpaired T-test. Overlap refers to genes differentially expressed in both TLDA card and exon array.Table 2
Differentially expressed GAG related genes during skin development in mice in comparison to mature skin (p<0.10) based on real-time qPCR.
E14 vs. P90  E16 vs. P90  P1 vs. P90 Gene symbol Full gene name and probe set  P-value Relative change  P-value Relative change  P-value Relative change Production of precursors Galk1 ‡ Galactokinase 1  0.029 5.897  0.057 3.867  0.074 3.043 Mm00444182_m1 Galt ‡ Gal-1-P-Uridylyltransferase  0.042 0.573  0.027 0.497  0.832 0.964 Mm00489459_g1 Gfpt1 ‡ Glu-Fru-6-P-Transaminase 1  0.002 2.378  0.160 1.273  0.282 1.481 Mm00600127_m1 Gfpt2 ‡ Glu-Fru-6-P-Transaminase 2  0.269 0.772  0.079 0.494  0.356 0.780 Mm00496565_m1 Hk2 ‡ Hexokinase 2  0.027 0.652  0.253 1.390  0.586 0.904 Mm00443385_m1 Pgm3 ‡ Phosphoglucomutase 2  0.058 1.876  0.296 1.249  0.098 1.470 Mm00459270_m1 Pgm5 ‡ Phosphoglucomutase 5  0.002 4.053  0.033 2.792  0.019 2.515 Mm00723432_m1 Slc13a5 ‡ Solute Carrier Family 13 Member A5  Not detected  Not detected  Not detected Mm00523288_m1 Slc26a9 ‡ Solute Carrier Family 26 Member A9  Not detected  0.036 0.264  0.023 0.318 Mm00628490_m1 Slc35a3 ‡ Solute Carrier Family 35 Member a3  0.008 0.444  0.060 0.567  0.455 0.811 Mm00523288_m1  Core proteins Cd44 CD44 Molecule  0.018 0.536  0.171 0.637  0.223 1.385 Mm01277164_m1 Gpc2 ‡ Glypican 2  0.005 11.686  0.638 1.294  0.369 1.249 Mm00549650_m1 Gpc3 † Glypican 3  <0.001 6.765  0.019 3.734  0.013 8.044 Mm00516722_m1 Gpc6 ‡ Glypican 6  0.027 2.880  0.275 1.376  0.130 1.926 Mm00516235_m1 Hspg2 ‡ Perlecan  0.030 1.504  0.064 1.959  0.007 3.325 Mm01181179_g1 Sdc1 ‡ Syndecan 1  0.012 0.293  0.107 0.313  0.069 0.403 Mm00448918_m1 Sdc4 † Syndecan 4  0.002 0.201  0.039 0.240  0.065 0.471 Mm00488527_m1  Preparation of linkage region B3gat1 β-1,3-Glucuronyltransferase 1  Not detected  Not detected  Not detected Mm00661499_m1 B3gat2 β-1,3-Glucuronyltransferase 2  Not detected  Not detected  Not detected Mm00549042_m1 B4galt2 ‡ β-1,4-Galactosyltransferase 2  0.023 4.562  0.059 2.679  0.038 3.384 Mm00479556_m1  Glycosaminoglycan chain polymerisation Chpf ‡ Chondroitin Polymerizing Factor  <0.001 2.991  0.059 1.865  0.050 2.401 Mm01262239_g1 Chsy1 ‡ CS Synthase 1  0.013 3.900  0.024 2.282  0.072 2.229 Mm01319178_m1 Chsy3 ‡ CS Synthase 3  0.026 4.006  0.075 2.184  0.101 2.013 Mm01545329_m1 Csgalnact1 ‡ CS-GalNAc-transferase 1  0.099 0.496  0.098 0.475  0.634 1.128 Mm00555164_m1 Extl1 ‡ Exostoses (multiple)-like 1  Not detected  Not detected  Not detected Mm00621977_s1 Extl2 ‡ Exostoses (multiple)-like 2  0.007 2.043  0.660 1.220  0.106 1.765 Mm00469621_m1 Has2 ‡ Hyaluronan Synthase 2  0.188 1.933  0.235 1.705  0.410 1.577 Mm00515089_m1  Glycosaminoglycan chain modification Chst11 ‡ Chondroitin 4-O-Sulfotransferase 1  0.002 3.000  0.087 1.195  0.087 1.957 Mm00517563_m1 Chst14 ‡ Dermatan 4 Sulfotransferase 1  0.026 2.459  0.156 1.513  0.203 1.707 Mm00511291_s1 Chst2 ‡ Carbohydrate Sulfotransferase 2  0.014 3.664  0.010 3.145  0.006 2.773 Mm00490018_g1 Chst3 ‡ Chondroitin 6-O-Sulfotransferase 1  0.041 3.241  0.152 1.941  0.028 3.550 Mm00489736_m1 Chst8 ‡ GalNAc-4-O-Sulfotransferase 1  0.089 2.587  0.221 0.591  0.139 2.280 Mm00558321_m1 Hs3st1 ‡ HS 3-O-sulfotransferase  0.051 1.796  0.039 1.937  0.027 2.809 Mm01964038_m1 Hs3st3b1‡ HS 3-O-sulfotransferase 3b1  0.004 3.204  0.028 2.511  0.002 2.629 Mm00479621_m1 Hs3st6 ‡ HS 3-O-sulfotransferase 6  0.006 0.208  0.089 0.664  0.041 1.765 Mm01299930_m1 Hs6st2 HS 6-O-sulfotransferase 2  Not detected  Not detected  Not detected Mm00479296_m1 Ndst1 ‡ N-deacet./N-sulfotrans. 1  0.118 1.487  0.140 1.449  0.054 2.202 Mm00447005_m1 Ndst2 ‡ N-deacet./N-sulfotrans. 2  0.008 1.347  0.001 2.017  0.002 2.021 Mm00447818_m1 Ndst3 ‡ N-deacet./N-sulfotrans. 3  0.004 4.708  0.041 7.910  0.004 12.034 Mm00453178_m1 Sulf1 ‡ Sulfatase 1  0.004 4.644  0.079 2.674  0.089 2.077 Mm00552283_m1 Sumf2 ‡ Sulfatase modifying factor 2  0.008 2.657  0.104 2.023  0.038 1.857 Mm01197721_m1  Glycosaminoglycan chain degradation ArsJ ‡ Arylsulfatase J  0.013 7.805  0.010 12.075  0.014 7.146 Mm00557970_m1 ArsK ‡ Arylsulfatase K  0.306 0.801  0.059 0.466  0.143 0.678 Mm00513099_m1 Galns ‡ Galactosamine (N-Acetyl)-6-Sulfatase  <0.001 2.648  0.066 1.674  0.091 1.584 Mm00489575_m1 Hpse ‡ Heparanase  0.044 0.304  0.342 1.450  0.169 0.578 Mm00461768_m1 Hyal1 ‡ Hyaluronoglucosamini-dase 1  0.001 0.198  0.008 0.288  0.006 0.607 Mm00476206_m1 Sgsh ‡ N-Sulfoglucosamine Sulfohydrolase  0.055 0.647  0.002 0.435  0.644 0.897 Mm00450747_m1  Growth factors Areg Amphiregulin  Not detected  Not detected  0.656 0.834 Mm00437583_m1 Bmp3 ‡ Bone morphogenetic growth factor 3  0.007 4.270  0.004 7.240  0.002 11.628 Mm00557790_m1 Bmp5 ‡ Bone morphogenetic growth factor 5  0.022 12.051  0.303 1.788  0.587 1.300 Mm00432091_m1 Ctgf ‡ Connective tissue growth factor  0.668 1.079  0.011 0.232  0.076 0.580 Mm01192931_g1 Fgf10 ‡ Fibroblast growth factor 10  0.063 1.649  0.050 1.801  0.093 2.262 Mm00433275_m1 Fgf13 ‡ Fibroblast growth factor 13  0.002 3.205  0.059 1.750  0.181 1.544 Mm00438910_m1 Fgf2 ‡ Fibroblast growth factor 2  0.277 0.651  0.166 0.539  0.382 1.446 Mm01285715_m1 Fgf20 Fibroblast growth factor 20  Not detected  Not detected  Not detected Mm00748347_m1 Fgf22 ‡ Fibroblast growth factor 22  Not detected  0.386 0.632  0.060 0.614 Mm00445749_m1 Fgf7 ‡ Fibroblast growth factor 7  0.045 0.606  0.002 0.394  0.087 0.630 Mm00433291_m1 Fgf8 Fibroblast growth factor 8  Not detected  Not detected  Not detected Mm00438921_m1 Figf ‡ C-fos induced growth factor  0.081 1.397  0.030 1.787  0.545 0.834 Mm01131929_m1 Gdf10 ‡ Growth differentaition factor 10  0.015 3.181  0.454 1.143  0.166 1.519 Mm03024279_s1 Hbegf ‡ Heparin-binding epidermal growth factor  Not detected  0.015 0.347  0.016 0.423 Mm00439305_g1 Hdgf † Hepatoma-derived growth factor  0.257 1.221  0.737 0.911  0.975 1.008 Mm00725733_s1 Igf1 ‡ Insulin-like growth factor 1  0.320 1.207  0.217 0.705  0.364 0.790 Mm00439560_m1 Igf2 † Insulin-like growth factor 2  <0.001 592.335  0.002 338.094  0.001 416.096 Mm00439565_g1 Nog ‡ Noggin  0.054 2.945  0.019 2.935  0.021 3.067 Mm01297833_s1 Pdgfa ‡ Platelet-derived growth factor a  0.021 3.005  Not detected  0.016 3.669 Mm01205760_m1 Pdgfb ‡ Platelet-derived growth factor b  0.321 1.098  0.033 1.468  0.010 2.096 Mm01298578_m1 Pdgfc ‡ Platelet-derived growth factor c  Not detected  0.016 2.362  Not detected Mm00480205_m1 Pdgfd ‡ Platelet-derived growth factor d  Not detected  0.288 0.709  0.139 1.644 Mm00546829_m1 Shh Sonic hedgehog  Not detected  Not detected  Not detected Mm00436527_m1 Tgfb1 ‡ Transforming growth factor beta 1  0.027 0.540  0.488 0.817  0.157 1.372 Mm01178820_m1 Tgfb2 ‡ Transforming growth factor beta 2  0.039 2.697  0.757 1.081  0.127 1.809 Mm01321739_m1 Tgfb3 ‡ Transforming growth factor beta 3  0.033 2.420  0.094 1.854  0.034 2.517 Mm01307950_m1 Vegfa ‡ Vascular endothelial growth factor a  0.394 1.108  0.112 1.613  0.461 1.358 Mm01281447_m1 Vegfb Vascular endothelial growth factor b  Not detected  Not detected  Not detected Mm00442102_m1 Vegfc ‡ Vascular endothelial growth factor c  0.024 1.839  0.303 1.250  0.015 1.996 Mm00437313_m1 Wnt10b ‡ Wingless-related integration site 10b  0.180 5.829  0.122 9.688  0.105 11.748 Mm00442104_m1 Wnt16 ‡ Wingless-related integration site 16  0.066 2.094  0.016 4.809  0.014 4.362 Mm00446420_m1 Wnt2 ‡ Wingless-related integration site 2  0.054 3.144  0.090 3.555  0.074 3.760 Mm00470018_m1 Wnt2b Wingless-related integration site 2b  Not detected  Not detected  Not detected Mm00437330_m1 Wnt3a ‡ Wingless-related integration site 3a  0.394 1.610  0.441 1.520  0.840 1.106 Mm00437337_m1 Wnt6 ‡ Wingless-related integration site 6  0.015 11.709  0.018 10.400  0.016 10.758 Mm00437353_m1 Wnt7a Wingless-related integration site 7a  Not detected  Not detected  Not detected Mm00437355_m1 Wnt7b ‡ Wingless-related integration site 7b  0.003 4.180  0.056 6.076  0.003 4.181 Mm00437357_m1 Numbers in italic are significant (p<0.10); numbers in bold are >2-fold differentially expressed. Gene symbols indicated with a †-symbol are normalized using GAPDH as a reference gene. Gene symbols indicated with a ‡-symbol are normalized using TBP as a reference gene. Genes, for which a signal was not or only partly detected at a given time point or multiple time points and therefore a fold change and/or p value could not be calculated based on the available data, are given as “not detected.” Gene symbols for which all time points were classified as “not detected” do not show a symbol for the used reference gene due to lack of data for a calculation.Table 3
Differentially expressed GAG related genes during skin development in mice in comparison to mature skin (p<0.10) based on gene Chip Mouse Exon 1.0 ST Arrays.
E14 vs. P90  E16 vs. P90  P1 vs. P90 Gene symbol Full gene name and probe set  Stepup P-value Fold change  Stepup P-value Fold change  Stepup P-value Fold change Production of precursors Galk1 Galactokinase 1  0.030 4.242  0.126 2.483  0.231 2.194 6792485 Galt Gal-1-P-Uridylyltransferase  0.664 0.814  0.231 1.864  0.665 1.340 6912944 Gfpt1 Glu-Fru-6-P-Transaminase 1  0.020 2.110  0.077 1.682  0.801 1.081 6947679 Gfpt2 Glu-Fru-6-P-Transaminase 2  0.176 0.610  0.087 0.426  0.229 0.547 6780767 Hk2 Hexokinase 2  0.003 0.451  0.040 1.375  0.039 0.655 6954982 Pgm3 Phosphoglucomutase 2  0.083 2.193  0.676 1.178  0.654 1.286 6997513 Pgm5 Phosphoglucomutase 5  0.058 2.338  0.104 2.209  0.291 1.696 6872290 Slc13a5 Solute Carrier Family 13 Member A5  0.003 2.588  0.059 1.322  0.576 1.075 6789531 Slc26a9 Solute Carrier Family 26 Member A9  0.012 0.227  0.090 0.471  0.091 0.392 6753079 Slc35a3 Solute Carrier Family 35 Member A3  0.105 0.767  0.596 0.925  0.572 0.890 6908510  Core proteins Cd44 CD44 Molecule  0.009 0.370  0.144 0.728  0.873 0.955 6889258 Gpc2 Glypican 2  Not measured  Not measured  Not measured Gpc3 Glypican 3  0.003 4.339  0.013 3.305  0.015 4.721 7016826 Gpc6 Glypican 6  0.019 2.767  0.109 1.747  0.193 1.640 6821985 Hspg2 Perlecan  0.309 1.183  0.075 1.554  0.042 2.230 6917933 Sdc1 Syndecan 1  0.031 0.380  0.067 0.413  0.103 0.424 6793226 Sdc4 Syndecan 4  0.017 0.341  0.094 0.536  0.215 0.621 6892905  Preparation of linkage region B3gat1 β-1,3-Glucuronyltransferase 1  0.008 3.467  0.256 1.302  0.828 0.929 6987632 B3gat2 β-1,3-Glucuronyltransferase 2  0.009 3.241  0.286 1.269  0.690 1.129 6748174 B4galt2 β-1,4-Galactosyltransferase 2  0.039 1.726  0.053 1.856  0.176 1.477 6924869  Glycosaminoglycan chain polymerisation Chpf Chondroitin Polymerizing Factor  0.071 1.679  0.182 1.459  0.309 1.403 6759816 Chsy1 CS Synthase 1  Not measured  Not measured  Not measured Chsy3 CS Synthase 3  0.429 1.153  0.056 1.769  0.849 1.058 6861281 Cs-galnact1 CS-GalNAc-transferase 1  0.137 0.512  0.202 0.541  0.974 0.975 6983073 Extl1 Exostoses (multiple)-like 1  0.025 0.407  0.149 0.625  0.144 0.505 6926017 Extl2 Exostoses (multiple)-like 2  0.085 1.702  0.819 1.066  0.518 1.272 6900659 Has2 Hyaluronan Synthase 2  0.095 2.107  0.157 1.969  0.537 1.403 6854042  Glycosaminoglycan chain modification Chst11 Chondroitin 4-O-Sulfotransferase 1  0.049 1.922  0.465 1.208  0.239 1.531 6769366 Chst14 Dermatan 4 Sulfotransferase 1  0.151 1.491  0.506 1.191  0.773 1.122 6880476 Chst2 Carbohydrate Sulfotransferase 2  0.035 2.302  0.072 2.160  0.207 1.682 6997990 Chst3 Chondroitin 6-O-Sulfotransferase 1  0.885 1.034  0.108 1.545  0.162 1.530 6774295 Chst8 GalNAc-4-O-Sulfotransferase 1  0.945 1.007  0.569 1.054  0.420 1.108 6966453 Hs3st1 HS 3-O-sulfotransferase 1  0.074 1.658  0.105 1.688  0.119 1.824 6937654 Hs3st3b1 HS 3-O-sulfotransferase 3b1  0.683 1.178  0.253 1.634  0.511 1.432 6788991 Hs3st6 HS 3-O-sulfotransferase 6  0.019 0.406  0.291 0.771  0.721 1.130 6849317 Hs6st2 HS 6O-sulfotransferase 2  0.004 6.417  0.012 5.609  0.041 3.080 7016808 Ndst1 N-Deacetylase and N-Sulfotransferase 1  0.090 1.363  0.056 1.649  0.067 1.763 6865926 Ndst2 N-Deacetylase and N-Sulfotransferase 2  0.822 1.044  0.059 1.697  0.083 1.733 6823122 Ndst3 N-Deacetylase and N-Sulfotransferase 3  0.173 2.472  0.111 3.856  0.122 4.860 6908958 Sulf1 Sulfatase 1  0.010 4.522  0.051 2.546  0.232 1.627 6747641 Sumf2 Sulfatase modifying factor 2  Not measured  Not measured  Not measured  Glycosaminoglycan chain degradation ArsJ Arylsulfatase J  0.003 2.498  0.006 3.164  0.031 1.702 6901136 ArsK Arylsulfatase K  0.368 0.784  0.102 0.543  0.514 0.779 6814451 Galns Galactosamine (N-Acetyl)-6-Sulfatase  0.087 1.671  0.322 1.311  0.786 1.115 6985943 Hpse Heparanase  0.021 0.267  0.540 1.244  0.095 0.360 6940363 Hyal1 Hyaluronoglucosamini-dase 1  0.003 0.154  0.011 0.222  0.041 0.402 6992224 Sgsh N-Sulfoglucosamine Sulfohydrolase  0.017 0.458  0.052 0.537  0.201 0.699 6792702  Growth factors Areg Amphiregulin  0.016 0.157  0.043 0.200  0.333 0.550 6932394 Bmp3 Bone morphogenetic growth factor 3  0.280 1.392  0.067 2.381  0.100 2.365 6932718 Bmp5 Bone Morphogenetic growth factor 5  0.001 7.247  0.141 1.191  0.688 1.057 6990569 Ctgf Connective tissue growth factor  0.148 0.729  0.025 0.366  0.068 0.485 6766623 Fgf10 Fibroblast growth factor 10  0.138 1.521  0.057 2.250  0.094 2.142 6810592 Fgf13 Fibroblast growth factor 13  0.012 2.998  0.075 1.824  0.296 1.391 7017134 Fgf2 Fibroblast growth factor 2  0.201 0.664  0.279 0.696  0.952 0.967 6896850 Fgf20 Fibroblast growth factor 20  0.659 1.228  0.125 2.483  0.777 1.220 6981854 Fgf22 Fibroblast growth factor 22  0.005 0.329  0.972 0.994  0.097 0.646 6769141 Fgf7 Fibroblast growth factor 7  0.531 0.740  0.078 0.286  0.212 0.418 6880900 Fgf8 Fibroblast growth factor 8  0.492 0.883  0.655 1.085  0.682 0.895 6873363 Figf C-fos induced growth factor  0.051 1.734  0.062 1.909  0.548 0.832 7015007 Gdf10 Growth differentiation factor 10  0.028 2.334  0.757 1.086  0.894 1.060 6818153 Hbegf Heparin-binding epidermal growth factor  0.037 0.551  0.063 0.547  0.087 0.530 6864680 Hdgf Hepatoma-derived growth factor  0.104 1.246  0.575 1.070  0.409 1.147 6899028 Igf1 Insulin-like growth factor 1  0.235 0.631  0.173 0.537  0.398 0.641 6769597 Igf2 Insulin-like growth factor 2  0.001 59.615  0.002 55.864  0.002 52.364 6972317 Nog Noggin  0.275 2.605  0.517 1.773  0.677 1.712 6790670 Pdgfa Platelet-derived growth factor a  0.028 2.013  0.035 2.347  0.057 2.338 6942654 Pdgfb Platelet-derived growth factor b  0.037 0.704  0.199 1.197  0.157 1.298 6837144 Pdgfc Platelet-derived growth factor c  0.019 2.152  0.035 2.207  0.902 1.042 6898686 Pdgfd Platelet-derived growth factor d  0.925 0.952  0.191 0.504  0.790 1.205 6986677 Shh Sonic hedgehog  0.448 0.595  0.308 2.117  0.152 4.571 6936889 Tgfb1 Transforming growht factor beta 1  0.106 0.552  0.241 0.653  0.975 0.981 6959236 Tgfb2 Transforming growht factor beta 2  0.057 2.441  0.448 1.335  0.264 1.802 6764953 Tgfb3 Transforming growth factor beta 3  0.026 2.386  0.238 1.408  0.100 2.077 6802449 Vegfa Vascular endothelial growth factor a  0.779 0.875  0.721 1.174  0.940 1.061 6855659 Vegfb Vascular endothelial growth factor b  0.008 1.461  0.031 1.318  0.060 1.277 6871273 Vegfc Vascular endothelial growth factor c  0.088 2.120  0.477 1.316  0.316 1.700 6976200 Wnt10b Wingless-related integration site 10b  0.629 1.280  0.120 2.812  0.240 2.325 6838399 Wnt16 Wingless-related integration site 16  0.358 1.180  0.026 2.402  0.093 1.710 6944581 Wnt2 Wingless-related integration site 2  0.057 3.047  0.082 3.260  0.122 3.219 6951974 Wnt2b Wingless-related integration site 2b  0.009 2.189  0.024 2.030  0.077 1.590 6907887 Wnt3a Wingless-related integration site 3a  0.457 1.199  0.103 1.728  0.684 1.159 6788662 Wnt6 Wingless-related integration site 6  0.011 3.166  0.032 2.668  0.064 2.352 6750567 Wnt7a Wingless-related integration site 7a  0.060 2.117  0.131 1.865  0.395 1.456 6955539 Wnt7b Wingless-related integration site 7b  0.072 2.297  0.050 3.623  0.237 1.912 6837582 Numbers in Italic are significant (p<0.10); numbers in bold are >2-fold differentially expressed. Genes indicated as “not measured” represent genes for which probes were not available on the used exon array version.Table 4
Differentially expressed genes in C5 epimerase (Glce) knockout mouse (p<0.10) based on real-time qPCR.
Gene symbol Full gene name and probe set  P-value Relative change Production of precursors Gnpnat1 Glucosamine-Phosphate N-Acetyltransferase 1  0.033 0.468 Mm00834602_mH Slc2a4 Solute Carrier Family 2 Member 4  0.086 2.526 Mm01245507_g1 Core proteins Acan Aggrecan  0.005 0.242 Mm00545807_m1 Aspn Asporin  0.010 0.382 Mm00445945_m1 Glycosaminoglycan chain polymerisation Csgalnact CS N-Acetylgalactosaminyltransferase 2  0.049 0.431 2 Mm00513340_m1 Glycosaminoglycan chain modification Glce Glucuronic Acid Epimerase  0.013 0.079 Mm00473667_m1 Numbers in Italic are significant (p<0.10); numbers in bold are >2 fold differentially expressed. All genes were normalized using 18S RNA as a reference gene.In Tables1–3 and Supplementary data Table 3, an overview is given of the differentially expressed genes applying TLDA cards and exon arrays. In all categories of genes involved in GAG metabolism, i.e., production of precursor molecules, core proteins, synthesis of linkage region, polymerization, modification and degradation of the GAG chain, and differences in expression were found (Tables 1–3). This indicates a highly dynamic expression pattern during skin development. Some isoenzymes were upregulated, whereas other isoenzymes were downregulated, further stressing metabolic complexity. This is, for instance, the case with GFPT1 and 2, both rates limiting enzymes involved in the production of hexosamines, and the isoenzymes HS 3-O sulfotransferase 6 and 3b1.With respect to the core proteins, differential expression was found for both HS and CS/DS proteoglycans. Differential expression was found for two of the four syndecans,viz. Sdc1 andSdc4, three of the six glypicans,viz. Gpc2, Gpc3, andGpc6, andHspg2 (Tables 2 and 3). The syndecans were downregulated, while the glypicans were upregulated, indicating an embryonic role for glypicans as described in literature [25, 26].Hspg2, a secreted HS presenting proteoglycan coding for perlecan [2], was found to be upregulated (Tables 2 and 3). Based on the exon array the CS/DS core protein of versican (Vcan) was upregulated at all time points (Supplementary data Table 5).The upregulated expression of genes involved in the synthesis of the linkage region may signal increased GAG synthesis during development since after the formation of the linkage region the GAG chain is formed. For HS polymerization differential expression was found for,e.g.,Extl1 andExtl2.Extl1 showed downregulation at E14 whileExtl2was upregulated, and both enzymes are involved in the initiation and elongation of the HS chain [2].During and after synthesis of the glycosaminoglycan chain, disaccharide units within the chain are specifically modified. These modifications determine which effector molecules can bind to the chain and thus play a role in cell signaling [1, 3]. Upregulated expression was found for three of the four N-deacetylase/N-sulfotransferases (Ndst; TLDA cards, Table 2), especially isoenzymeNdst3. Upregulation was also found for two out of seven genes coding for 3-O-sulfotransferases (Hs3st1andHs3st3b1), involved in 3-O sulfation of GlcNS and GlnNAc residues, whereas one was downregulated (Hs3st6).The GlcNS and GlcNAc residues can also be 6-O sulfated by 6-O-sulfotransferases (Hs6st) [2] and selectively desulfated extracellularly by two sulfatases (Sulf1 andSulf2) aided by two cofactors (Sumf1 andSumf2) [2, 27].Hs6st2 was upregulated at all time points (Table 3).Sulf1 was upregulated during embryonic development, whereasSumf2 was upregulated at E14 (Tables 2 and 3). These results indicate that specific expression of GAG modifying enzymes may play a role in specific cellular signaling during skin development.Within the class of genes encoding for GAG chain degradation enzymes, two genes were differentially expressed. Heparanase expression was downregulated at E14 and P1 (Tables2 and 3), whereas N-sulfoglucosamine sulfohydrolase (Sgsh) was downregulated during embryonic development at E16 (Table 2) and at E14 (Table 3).In addition to genes involved in GAG metabolism, the TLDA card contained 37 genes encoding growth factors, which were also present in the microarray (Tables2 and 3). Differential expression was found by both TLDA card and microarray analysis for 10, 9 and 4 growth factors at E14, E16 and P1 respectively. Examples are insulin-like growth factor 2(Igf2), wingless-related integration site 6 (Wnt6), andWnt7b.Igf2 was dramatically upregulated at all time points, as expected based on previous research [18].Wnt6 was also upregulated at all time points, whileWnt7b was upregulated only during embryonic development.Next to their expression during development, gene expression of GAG-associated genes was studied in aGlce (glucuronyl epimerase) knockout mouse model and a heparanase overexpression mouse model using TLDA cards. In theGlce knockout mice six genes were differentially expressed (Table 4). Three of them are involved in CS and DS proteoglycans and were downregulated,i.e., aggrecan (Acan), asporin (Aspn), and chondroitin sulfate N-acetylgalactosaminyltransferase 2 (Csgalnact2). Up/downregulation was not found for HS related genes, except forGlce, which was downregulated as expected. For the heparanase overexpression mouse model, in which a human heparanase was overexpressed [7], the results showed only one gene to be differentially expressed, i.e., aggrecan(Acan) which was 2.5-fold upregulated. The complete results of both theGlceknockout mouse and the Hpse overexpression mouse are given in Supplementary data Table 6.


## 4. Discussion

GAGs play a regulating role during embryonic development of various organs [1–3]. Therefore, we examined the expression of genes involved in GAG metabolism during skin development using custom designed Taqman Low Density Arrays (TLDA card) and exon arrays. To structure the data we studied gene expression in six functional classes,viz. the production of precursor molecules, the synthesis of core proteins and the linkage region, and the synthesis, modification, and degradation of the GAG chain proper. In addition we studied a number of growth factors, since GAGs are involved in their regulation including growth factor diffusion and signaling [3, 28].With respect to core proteins, the heparan sulfate proteoglycans syndecan and glypican showed notable differential expression (Tables2 and 3). Glypicans play an important role in development and cell signaling [12, 26, 29], and we found upregulation of 3 out of 6 glypican core proteins.Gpc3 was upregulated during embryonic development and one day postbirth, suggesting that this glypican has a role during skin development. A possible function ofGpc3 in skin has been suggested for theGpc3-null mouse, which showed pigmentation defects [30]. Humans deficient inGpc3 suffer from the Simpson-Golabi-Behmel syndrome (SBGS). Based on the symptoms of SGBS and the phenotype found for theGpc3-null mice, it has been suggested that Gpc3 is involved in the regulation of hedgehog signaling [31], a signaling pathway involved in hair follicle development [32]. Surprisingly, theGpc3-null mice did not show a defect in appendage formation [30], indicating a functional but not essential role. Further research is needed to elucidate the role ofGpc3 and the two other differentially expressed glypicans,i.e., Gpc2 andGpc6.Syndecans are described to take part in adult wound healing [33]. We found downregulation of the core proteins of two syndecans during embryonic development, which could indicate that these proteoglycans do not play a major general role during skin development. Specific roles, such as the involvement ofSdc1 in hair follicle development, as described on basis of immunohistochemical data [34], can, however, not be excluded.In the class of GAG chain polymerization, we found differential expression of genes encoding for the initiation of HS or CS/DS synthesis. HS chain polymerization is initiated by the addition of GlcNAc byExtl2 [35] orExtl3 [36], while CS/DS chain polymerization is initiated by the addition of GalNAc byCsgalnact1 [37].Extl2was upregulated during early skin development (Table 2), whileCsgalnact1was downregulated (Supplementary data Table 5), which suggests that during early skin development HS production is stimulated in comparison to CS/DS production.Enzyme mediated chemical modifications of the GAG chains result in the creation of specific binding sites for effector molecules [38]. Enzymes forming the class of N-deacetylase/sulfotransferases (Ndst’s) are initiating elements in this respect. EspeciallyNdst3 was upregulated, being one of four enzymes responsible for the removal of the acetyl group from the N-acetylated glycosamine and for the addition of a sulfate group. The additional expression ofNdst3in combination withNdst1 andNdst2points to the fine tuning of HS chains for specific recognition of ligands.Ndst3 has a higher deacetylation activity in comparison to the N-sulfotransferase activity, whileNdst1 andNdst2 have a slightly higher N-sulfotransferase activity [39]. In addition, the data on the expression of heparan sulfate 3-O sulfotransferases (Hs3sts) [40] and heparan sulfate 6-O-sulfotransferases (Hs6sts) [41] suggest dynamic and specific modification of HS chains.Three genes encoding for enzymes involved in HS and CS/DS degradation were differentially expressed, one of them beingHpse (heparanase).Hpse is downregulated at E14 and at P1, but not at E16 at which time point hair follicle development is taking place.Hpse has been reported to be involved in this process [42, 43].Glycosaminoglycans are involved in growth factor regulation during developmental processes [1, 2]. We therefore studied 37 growth factors implied in skin development. A number of genes encoding growth factors were differentially expressed during development and the data are in line with earlier results for, e.g.,Igf2 [18],Wnt6, andWnt7b [44]. Although speculative, the dynamics in GAG structure may be correlated with the dynamics of growth factors.Next to skin development we also studied gene expression in skin of aGlce (glucuronyl epimerase) knockout mouse and an Hpse (heparanase) overexpression mouse [7, 13]. In theGlce knockout mice relatively few genes were differentially expressed, suggesting that skin is relatively unaffected by the lack ofGlce in line with the observation that skin in these mice is phenotypically normal [20]. The skin phenotype of the Hpse overexpression mouse shows accelerated hair growth [7]. Gene expression analysis of this model showed only one differentially expressed gene (aggrecan). These results may touch upon the regulation of translation of mRNAs coding for GAG related enzymes. Enzymes involved in the synthesis and modification of GAGs as well genes coding for (some) growth factors share a common alternative translation mechanism via IRES sites [45, 46]. In general mRNAs are translated by the ribosomal scanning mechanism which scans for short leader sequences of 50 to 70 nucleotides [46, 47]. The leader sequences of the HS modifying enzymes and growth factors are characterized by long but structured sequences, which are not recognized by the ribosomal scanning mechanism [46, 47]. Within these sequences internal ribosomal entry sites (IRES) allow alternative translation, e.g., under stress conditions [47]. This indicates that in addition to mRNA levels an additional control mechanism on the translational level may be present. In addition, other types of regulatory levels are known including the interaction of biosynthetic enzymes with each other and the (possible) presence of large biosynthetic complexes (GAGosomes) [48]. This makes the regulation of GAG biosynthesis very complex, gene expression being only a part of it.Taken together, it is concluded that a highly dynamic expression of genes involved in GAG metabolism and in GAG binding growth factors is associated with skin development. This indicates the importance of fine tuning of GAG structures during developmental processes. Further studies should focus on the biochemical analysis of the GAGs chains themselves.



---

*Source: 9873471-2018-08-29.xml*