-74. 17. Favaloro EJ, McDonald D, Lippi G. Laboratory investigation of thrombophilia: the good, the bad, and the ugly. Semin Thromb Hemost 2009; 35(7): 695-710. 18. Varga EA, Kujovich JL. Management of inherited thrombophilia: guide for genetics professionals. Clin Genet 2012; 81(1): 7-17. 19. Malarstig A, Buil A, Souto JC, Clarke R, Blanco-Vaca F, Fontcuberta J, et al. Identification of ZNF366 and PTPRD as novel determinants of plasma homocysteine in a fa mily-based genome-wide association study. Blood 2009; 114: 1417
Ivana Novaković, Nela Maksimović, Aleksandra Pavlović, Milena Žarković, Branislav Rovčanin, Duško Mirković, Tatjana Pekmezović and Dragana Cvetković
Sonja Pavlović, Branka Zukić and Maja Stojiljković Petrović
and serum profiling. Mol Cell Proteomics 2003; 2: 1342-9. 9. Soon WW, Hariharan M, Snyder MP. High-throughput sequencing for biology and medicine. Mol Syst Biol 2013; 9: 640. 10. Gorreta F, Carbone W, Barzaghi D. Genomic profiling: cDNA arrays and oligoarrays. Methods Mol Biol 2012; 823: 89-105. 11. Bush WS, Moore JH. Chapter 11: Genome-wide association studies. PLoS Comput Biol 2012; 8(12): e1002822. 12. Drmanac R. Medicine. The ultimate genetic test. Science 2012; 336(6085): 1110
technology, February 2005. Recommendation for Human Cancer Genome Project. http://www.genome.gov/pages/about/NACHGR/may Goldsmith ZG, Danasekeran N. The microevolution: applications and impacts of microarray technology on molecular biology and medicine (review). Int J Molec Med 2004; 13 : 483-95. Weaver ChH, Deutrer D. Medical genomics: implications for clinical oncology. Current Topics in Oncology 2005. Nambiar PR, Boutin SR, Raja R, Rosenberg DW. Global gene expression profiling: a
References 1. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature 2001; 409: 860-921. 2. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The sequence of the human genome. Science 2001; 291: 1304-51. 3. Collins FS, Morgan M, Patrinos A. The Human Genome Project: lessons from large-scale biology. Science 2003; 300: 286-90. 4. Feingold E, Good P, Guyer M, Kamholz S, Liefer L, Wetterstrand K, et al
2009; 1: 25. MacFarlane AJ, Strom A, Scott FW. Epigenetics: deciphering how environmental factors may modify autoimmune type 1 diabetes. Mamm Genome 2009; 20: 624-32. Čolak E, Majkić-Singh N. The effect of hyperglicemia and oxidative stress on the development and progress of vascular complications in type 2 diabetes. Journal of Medical Biochemistry 2009; 28: 63-71. Rich SS, Concannon P, Erlich H, Julier C, Morahan G, Todd JA. The Type 1 Diabetes Genetic Consortium. Ann NY Acad Sci 2006
preliminary application to Caenorhabditis elegans. Proteomics 2001; 1: 295-303. Raman R, Raguram S, Venkataraman G, Paulson JC, Sasisekharan R. Glycomics: an integrated approach to structure-function relationships of glycans. Nat Methods 2005; 2(11): 817-24. Campbell C, Yarema KJ. Large-scale approaches for glycobiology. Genome Biol 2005; 6 (11): 236. Turnbull JE, Field RA. Emerging glycomics technologies. Nat Chem Biol 2007; 3: 74-7. Taniguchi N, Hancock W, Lubman DM
Sanja Stanković, Milika Ašanin and Nada Majkić-Singh
Coll Cardiol 2010; 56(19): 1552-63. 56. Barber MJ, Mangravite LM, Hyde CL, Chasman DI, Smith JD, McCarty CA, et al. Genome-wide association of lipid-lowering response to statins in combined study populations. PLoS One 2010; 5: e9763. 57. Nieminen T, Kahonen M, Viiri LE, Gronroos P, Lehtimaki T. Pharmacogenetics of apolipoprotein E gene during lipid-lowering therapy: lipid levels and prevention of coronary heart disease. Pharmacogenomics 2008; 9(10): 1475-86. 58. Thompson JF, Hyde CL, Wood LS, Paciga SA, Hinds DA, Cox DR
Olga A. Baturina, Alexey E. Tupikin, Tatyana V. Lukjanova, Svetlana V. Sosnitskaya and Igor V. Morozov
Background: Efficient treatment of inherited hyperphenyl-alaninemia requires exact identification of mutations defining the trait. Such knowledge is important both for effective individual therapy and understanding of the genetic history and evolution of regional populations.
Methods: DNA sequencing of amplified genome regions was used to identify mutations.
Results: Hyperphenylalaninemia-associated mutations in the phenylalanine hydroxylase locus were identified for 76 unrelated patients from the Novosibirsk region, Russia and for their family members. Twenty-one mutation types were identified, most of them rare and one (IVS2+1delG) not previously described. Common for European populations, the mutation p.R408W appeared to be the most frequent, with allele frequency 63.33%. We also looked for mutations in the quinoid dihydropteridine reductase locus in some patients. For 36 unrelated children PKU patients with known blood phenylalanine levels, we tried to find correlations between this level and the genotype.
Conclusions: Comparative analysis revealed correlations between blood phenylalanine levels and genotypes. The spectrum of phenylalanine hydroxylase mutations in the Novosibirsk region population appeared to be rather complex, probably as a result of mixed ethnic composition, formed by several multidirectional migration flows.
Maciej Ostrowski and Anna Jakubowska
UDP-glycosyltransferases (GTases, UGT) catalyze the transfer of the sugar moiety from the uridine-diphosphate-activated monosaccharide (e.g. uridine-diphosphate-5’-glucose, UDPG) molecule to the specific acceptor. Glycosides contain aglycons attached by a β-glycosidic bond to C1 of the saccharide moiety. Glycosylation is one of the mechanisms maintaining cellular homeostasis through the regulation of the level, biological activity, and subcellular distribution of the glycosylated compounds. The glycosides play various functions in plant cells, such as high-energy donors, or signalling molecules, and are involved in biosynthesis of cell walls. Plant cells exhibit structural and functional diversity of UGT proteins. The Arabidopsis thaliana genome contains more than 100 genes encoding GTases, which belong to 91 families, and are deposited in the CAZY (Carbohydrate Active enzyme) database (www. cazy.org/GlycosylTransferases.html). The largest UGT1 class is divided into 14 subfamilies (A-N), and includes proteins containing highly conserved 44-amino acid PSPG (Plant Secondary Product Glycosyltransferase) motif at the C-terminus. The PSPG motif is involved in the binding of UDP-sugar donors to the enzyme. UGT1’s catalyze the biosynthesis of both ester-type and ether-type conjugates of plant hormones (phytohormones). Conjugation of the phytohormones is an important mechanism that regulates the concentration of physiological active hormone levels during growth and development of plants. Glycoconjugation of phytohormones is widespread in the plant kingdom and all known phytohormones are able to form these conjugates. Most plant hormone conjugates do not indicate physiological activity, but rather are involved in transport, storage and degradation of the phytohormones. UDPG-dependent glycosyltransferases possess high substrate specificity, even within a given class of phytohormones. In many cases, the phenotype of plants is strongly affected by loss-of-function mutations in UGT genes. In this paper, advances in the isolation and characterization of glycosyltransferases of all plant hormones: auxin, brassinosteroids, cytokinin, gibberellin, abscisic acid, jasmonates, and salicylate is described
Dorota Sitnicka, Katarzyna Figurska and Slawomir Orzechowski
References  AGI: THE ARABIDOPSIS GENOME INITIATIVE. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 2000; 408: 796-815  ALTSCHUL SF, GISH W, MILLER W, MYERS EW, LIPMAN DJ. Basic local alignment search tool. J Mol Biol 1990; 215: 403-410.  ALTSCHUL SF, MADDEN TL, SCHAFFER AA, ZHANG J, ZHANG Z, MILLER W, LIPMAN DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997; 25: 3389-3402.  AMBROS V, CHEN X