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Mirta Milić

Genomska nestabilnost i test osjetljivosti na bleomicin

Procjena individualne osjetljivosti na mutagene često je dio istraživanja u epidemiološkim studijama koje prate pojavnost zloćudnih bolesti u populacijama. Posljedica djelovanja mutagena u genomu izloženih osoba jest nastanak osoba jest nastanak određene, manje ili veće, količine oštećenja, uvjetovane individualnim razlikama u osjetljivosti. Viša razina takve genomske nestabilnosti znači opasnost (rizik) od razvoja zloćudnih bolesti. Interindividualne razlike u odgovoru na mutagene obično se povezuju i s promijenjenom (većinom smanjenom) sposobnosti (kapacitetom) za popravak DNA. Citogenetičke studije su pokazale da je genom tumorskih stanica nestabilniji od normalnih, a time i skloniji akumuliranju oštećenja, bilo da je nestabilnost uzrokovana nasljeđem, izloženošću ili kombinacijom tih dvaju učinaka. U oboljelih ispitanika utvrđena je povećana učestalost kromatidnih i kromosomskih aberacija naspram normalne populacije te sklonost razvoju određenih vrsta neoplazija. U praćenju povezanosti promijenjenog odgovora i pojavnosti tumora služe nam različiti biomarkeri. Kao indirektni pokazatelji uspješnosti popravka DNA često se rabe testovi osjetljivosti na mutagene u kulturama limfocita periferne krvi. Jedan od takvih testova je i bleomicinski test. Radiomimetik i citostatik, a po strukturi glikopeptid, bleomicin se u stanici prevodi u aktivni oblik sposoban cijepati molekulu DNA što uzrokuje brojne jednolančane i dvolančane lomove. Kao jednostavna i jeftina metoda, zasniva se na utvrđivanju ukupnog broja jednolančanih lomova u kromosomima limfocita uzgajanih u staničnoj kulturi koji su u uvjetima in vitro tijekom kasne G2-faze staničnog ciklusa bili izloženi bleomicinu. Ovaj revijalni rad daje pregled utjecaja raznih faktora na rezultate samog testa i pokazuje njegovu široku primjenu u proučavanju genomske nestabilnosti koju najčešće uzrokuje kombinacija raznih faktora.

Open access

I. Domarkienė, A. Pranculis, Š. Germanas, A. Jakaitienė, D. Vitkus, V. Dženkevičiūtė, Za. Kučinskienė and V. Kučinskas

. Lorenzo C, Serrano-Rios M, Martinez-Larrad MT, Gonzalez-Sanchez JL, Seclen S, Villena A, et al. Geographic variations of the International Diabetes Federation and the National Cholesterol Education Program-Adult Treatment Panel III definitions of the metabolic syndrome in nondiabetic subjects. Diabetes Care. 2006; 29(3): 685-691. 6. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am J Hum Genet. 2007; 81(3): 559-575. 7. Spielman

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Xiangyan Zhou, Jingfang Ma, Wangtian Wang, Na Gong, Yanyun zhang and Jianquan Liu

References Abreu IS, Carvalho CR, and Clarindo WR. 2008. Chromosomal DNA content of sweet pepper determined by association of cytogenetic and cytometric tools. Plant Cell Reports 27: 1227-1233. Arumuganathan K, and Earle ED. 1991. Nuclear DNA content of some important plant species. Plant Molecular Biology Reporter 9: 208-219. Baack EJ, Whitney KD, and Rieseberg LH. 2005. Hybridization and genome size evolution: timing and magnitude of nuclear DNA content increases in

Open access

Edo D’Agaro

: 2001). 36. Yip KY, Cheng C, Gerstein M. Machine learning and genome annotation: a match meant to be? Genome biol 2013; 14:205. 37. Day N, Hemmaplardh A, Thurman RE, Stamatoyannopoulos JA, Noble WS. Unsupervised segmentation of continuous genomic data. Bioinformatics. 2007; 23: 1424–1426. 38. Boser BE, Guyon IM, Vapnik VN. A training algorithm for optimal margin classifiers. (Pittsburgh, PA: ACM Press: 1992). 39. Noble WS. What is a support vector machine? Nature Biotech 2006; 24: 1565–1567. 40. Hastie T, Tibshirani R, Friedman J

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B. Rukova, R. Staneva, S. Hadjidekova, G. Stamenov, V. Milanova and D. Toncheva

-2883. 9. Jones PA. Functions of DNA methylation: Islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012; 13(7): 484-492. 10. Moore LD, Le T, Fan G. DNA Methylation and its basic function. Neuropsychopharmacology. 2013; 38(1): 23-38. 11. Rakyan VK, Down TA, Thorne NP, Flicek P, Kulesha E, Graf S, et al. An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs). Genome Res. 2008; 18(9): 1518-1529. 12. Connor CM, Akbarian S. DNA methylation

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Marcin Samiec and Maria Skrzyszowska

during oogenesis and interference by reproductive technologies: Studies in mouse and bovine models. Reprod. Fertil. Dev., 27: 739-754. Armstrong L.M., Lako W., Dean W., Stojkovic M. (2006). Epigenetic modification is central to genome reprogramming in somatic cell nuclear transfer. Stem Cells, 24: 805-814. Bonk A.J., Cheong H.T., Li R., Lai L., Hao Y., Liu Z., Samuel M., Fergason E.A., Whitworth K.M., Murphy C.N., Antoniou E., Prather R.S. (2007). Correlation of developmental differences of nuclear transfer embryos cells to the

Open access

Svetlana Kryštofová

Abstract

Targeted genome editing using engineered nucleases such as ZFNs and TALENs has been rapidly replaced by the CRISPR/Cas9 (clustered, regulatory interspaced, short palindromic/ CRISPR-associated nuclease) system. CRISPR/Cas9 technology represents a significant improvement enabling a new level of targeting, efficiency and simplicity. Gene editing mediated by CRISPR/Cas9 has been recently used not only in bacteria but in many eukaryotic cells and organisms, from yeasts to mammals. Other modifications of the CRISPR-Cas9 system have been used to introduce heterologous domains to regulate gene expressions or label specific loci in various cell types. The review focuses not only on native CRISPR/Cas systems which evolved in prokaryotes as an endogenous adaptive defense mechanism against foreign DNA attacks, but also on the CRISPR/Cas9 adoption as a powerful tool for site-specific gene modifications in fungi, plants and mammals.

Open access

Ingrida Mazeikiene, Darius Kviklys, Jurate Brone Siksnianiene, Dainius Zinkus and Vidmantas Stanys

Abstract

Prunus necrotic ring spot ilarvirus (PNRSV) and Apple chlorotic leaf spot trichovirus (ACLSV) are common in plum orchards. The aim of the study was to obtain virus-free planting material of Prunus domestica L. by chemotherapy in vitro. Ribavirin at concentrations of 10 to 50 mg·l−1 was added to Murashige–Skoog (MS) nutrition medium for virus eradication from microshoots. After a two-week period of chemotherapy, meristems were subcultured monthly on MS medium and proliferation index of shoots was estimated. Microshoots were retested by reverse transcription polymerase chain reaction for presence of virus. At lowest concentrations of 10 mg·l−1 ribavirin was entirely ineffective for ACLSV and 10 to 30 mg·l−1 was ineffective for PNRSV elimination. Ribavirin concentrations of 40 and 50 mg·l−1 destroyed both pathogens. However, at higher concentrations of 40 and 50 mg·l−1 ribavirin exhibited some signs of phytotoxicity on microshoots in the first sub-cultivation period. In order to test the genetic stability of the microplants after chemotherapy the amplified fragment length polymorphism (AFLP) method was applied. Plant genome stability in ‘Magna Glauca’ at concentrations of 40 mg·l−1 was damaged, as the presence of polymorphic AFLP markers were observed.

Open access

Monika Bugno-Poniewierska, Beata Staroń, Leszek Potocki, Artur Gurgul and Maciej Wnuk

Abstract

Sarcoid is the most common skin cancer in horses. The etiology of the tumor is associated with BPV infection (BPV-1, -2, -13), which is an inducer of malignant transformation. The comparative genomic hybridization (CGH) technique identifying the unbalanced chromosome aberrations was used to analyze the genome of equine sarcoid cells and to diagnose the chromosome rearrangements involving large deletions or amplification. The results were based on the analysis of 100 metaphases and their karyograms as well as the diagram showing the average ratio of the intensity of the green to red fluorescence, using MetaSystems software (Isis). Based on a comparison of the fluorescence intensity ratios we found duplication in the subtelomeric regions of chromosome pairs 1, 4, 7, 8 and 23. Duplicated region of chromosome pair 1 also included the coding region of the rDNA. In the chromosome 23 next to the duplication occurring in the centromeric region of q arm (23q11) we also found the presence of deletions involving 23q18-23q19 region. For the chromosome pairs 25 to 31 and the X chromosome the software failed to generate CGH diagram, but on the individual karyograms we were able to observe fluorescence signals characteristic of duplication (red), in rDNA regions of chromosome pairs 28 and 31. The study showed that duplications of DNA present in the sarcoid cells are found mainly in the telomeric and rDNA regions. The presence of the duplication of telomeric regions is associated with increased activity of the telomerase enzyme, which is a hallmark of cancer cells, affecting the immortality of these cells. Accordingly, duplications of rDNA coding regions increase activity of nucleolar organizer region which is a tumor marker.

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Bohdan Ostash