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11. Genome-wide association study identifies multiple risk loci for renal cell carcinoma

Author

Scelo, G, Purdue, MP, Brown, KM, Johansson, M, Wang, Z, Eckel-Passow, JE, Ye, Y, Hoffman, JN, Choi, J, Foll, M, Gaborieau, V, Machiela, MJ, Colli, LM, Li, P, Sampson, JN, Abedi-Ardekani, B, Besse, C, Blanche, H, Boland, A, Burdette, L, Charbrier, A, Durand, G, Le Calvez-Kelm, F, Prokhortchouk, E, Robinot, N, Skyrabin, KG, Wozniak, MB, Yeager, M, Basta-Jovanovich, G, Dzamic, Z, Foretova, L, Holcatova, I, Janout, V, Mates, D, Mukeriya, A, Rascu, S, Zaridze, D, Bencko, V, Cybulski, C, Fabianova, E, Jinga, V, Lissowska, J, Lubinski, J, Navratilova, M, Rudnai, P, Szeszenia-Dabrowska, N, Benhamou, S, Cancel-Tassin, G, Cussenot, O, Baglietto, L, Boeing, H, Khaw, K-T, Weiderpass, E, Ljungberg, B, Sitaram, RT, Bruinsma, F, Jordan, SJ, Severi, G, Winship, I, Hveem, K, Vatten, LJ, Fletcher, T, Koppova, K, Larsson, SC, Wolk, A, Banks, RE, Selby, PJ, Easton, DF, Pharoah, P, Andreotti, G, Beane Freeman, LE, Koutros, S, Albanes, D, Mannisto, S, Weinstein, S, Clark, PE, Edwards, TL, Lipworth, L, Gapstur, SM, Stevens, VL, Carol, H, Freedman, ML, Pomerantz, MM, Cho, E, Kraft, P, Preston, MA, Wilson, KM, Gaziano, JM, Sesso, HD, Black, A, Freedman, ND, Huang, WY, Anema, JG, Kahnoski, RJ, Lane, BR, Noyes, SL, Petillo, D, Teh, BT, Peters, U, White, E, Anderson, GL, Johnson, L, Luo, J, Buring, J, Lee, I-M, Chow, W-H, Moore, LE, Wood, C, Eisen, T, Henrion, M, Larkin, J, Barman, P, Leibovich, BC, Choueiri, TK, Lathrop, GM, Rothman, N, Deleuze, J-F, McKay, JD, Parker, AS, Wu, X, Houlston, RS, Brennan, P, and Chanock, SJ

Abstract

Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10−10), 3p22.1 (rs67311347, P=2.5 × 10−8), 3q26.2 (rs10936602, P=8.8 × 10−9), 8p21.3 (rs2241261, P=5.8 × 10−9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10−8), 11q22.3 (rs74911261, P=2.1 × 10−10) and 14q24.2 (rs4903064, P=2.2 × 10−24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.

Published
2017

12. Common colorectal cancer risk alleles contribute to the multiple colorectal adenoma phenotype, but do not influence colonic polyposis in FAP

Author

Cheng, T. H. T., Gorman, M., Martin, L., Barclay, E., Casey, G., Newcomb, P. A., Conti, D. V., Schumacher, F. R., Gallinger, S., Lindor, N. M., Hopper, J., Jenkins, M., Hunter, D. J., Kraft, P., Jacobs, K. B., Cox, D. G., Yeager, M., Hankinson, S. E., Wacholder, S., Wang, Z., Welch, R., Hutchinson, A., Wang, J., Yu, K., Chatterjee, N., Orr, N., Willett, W. C., Colditz, G. A., Ziegler, R. G., Berg, C. D., Buys, S. S., McCarty, C. A., Feigelson, H. S., Calle, E. E., Thun, M. J., Hayes, R. B., Tucker, M., Gerhard, D. S., Fraumeni, J. F., Jr., Hoover, R. N., Thomas, G., Chanock, S. J., Ciampa, J., Gonzalez-Bosquet, J., Berndt, S., Amundadottir, L., Diver, W. R., Albanes, D., Virtamo, J., Weinstein, S. J., Cancel-Tassin, G., Cussenot, O., Valeri, A., Andriole, G. L., Crawford, E. D., Haiman, C. A., Henderson, B., Kolonel, L., March, L. L., Siddiq, A., Riboli, E., Key, T. J., Kaaks, R., Isaacs, W., Isaacs, S., Wiley, K. E., Gronberg, H., Wiklund, F., Stattin, P., Xu, J., Zheng, S. L., Sun, J., Vatten, L. J., Hveem, K., Kumle, M., Purdue, M. P., Johansson, M., Zelenika, D., Toro, J. R., Scelo, G., Moore, L. E., Prokhortchouk, E., Wu, X., Kiemeney, L. A., Gaborieau, V., Chow, W. -H., Zaridze, D., Matveev, V., Lubinski, J., Trubicka, J., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., Fabianova, E., Bucur, A., Bencko, V., Foretova, L., Janout, V., Boffetta, P., Colt, J. S., Davis, F. G., Schwartz, K. L., Banks, R. E., Selby, P. J., Harnden, P., Hsing, A. W., Grubb, R. L., III, Boeing, H., Vineis, P., Clavel-Chapelon, F., Palli, D., Tumino, R., Krogh, V., Panico, S., Duell, E. J., Quirós, J. R., Sanchez, M. -J., Navarro, C., Ardanaz, E., Dorronsoro, M., Khaw, K. -T., Allen, N. E., Bueno-de-Mesquita, H. B., Peeters, P. H. M., Trichopoulos, D., Linseisen, J., Ljungberg, B., Overvad, K., Tjønnel, Romieu, I., Mukeria, A., Shangina, O., Stevens, V. L., Gapstur, S. M., Pharoah, P. D., Easton, D. F., Njølstad, I., Tell, G. S., Stoltenberg, C., Kumar, R., Koppova, K., Benhamou, S., Oosterwijk, E., Vermeulen, S. H., Aben, K. K. H., Van Der Marel, S. L., Ye, Y., Wood, C. G., Pu, X., Mazur, A. M., Boulygina, E. S., Chekanov, N. N., Foglio, M., Lechner, D., Gut, I., Heath, S., Blanche, H., Skryabin, K. G., McKay, J. D., Rothman, N., Lathrop, M., Brennan, P., Saunders, B., Thomas, H., Clark, S., Tomlinson, I., and Cheng, T.H.T. and Gorman, M. and Martin, L. and Barclay, E. and Casey, G. and Newcomb, P.A. and Conti, D.V. and Schumacher, F.R. and Gallinger, S. and Lindor, N.M. and Hopper, J. and Jenkins, M. and Hunter, D.J. and Kraft, P. and Jacobs, K.B. and Cox, D.G. and Yeager, M. and Hankinson, S.E. and Wacholder, S. and Wang, Z. and Welch, R. and Hutchinson, A. and Wang, J. and Yu, K. and Chatterjee, N. and Orr, N. and Willett, W.C. and Colditz, G.A. and Ziegler, R.G. and Berg, C.D. and Buys, S.S. and McCarty, C.A. and Feigelson, H.S. and Calle, E.E. and Thun, M.J. and Hayes, R.B. and Tucker, M. and Gerhard, D.S. and Fraumeni, J.F., Jr. and Hoover, R.N. and Thomas, G. and Chanock, S.J. and Ciampa, J. and Gonzalez-Bosquet, J. and Berndt, S. and Amundadottir, L. and Diver, W.R. and Albanes, D. and Virtamo, J. and Weinstein, S.J. and Cancel-Tassin, G. and Cussenot, O. and Valeri, A. and Andriole, G.L. and Crawford, E.D. and Haiman, C.A. and Henderson, B. and Kolonel, L. and Marchand, L.L. and Siddiq, A. and Riboli, E. and Key, T.J. and Kaaks, R. and Isaacs, W. and Isaacs, S. and Wiley, K.E. and Gronberg, H. and Wiklund, F. and Stattin, P. and Xu, J. and Zheng, S.L. and Sun, J. and Vatten, L.J. and Hveem, K. and Kumle, M. and Purdue, M.P. and Johansson, M. and Zelenika, D. and Toro, J.R. and Scelo, G. and Moore, L.E. and Prokhortchouk, E. and Wu, X. and Kiemeney, L.A. and Gaborieau, V. and Chow, W.-H. and Zaridze, D. and Matveev, V. and Lubinski, J. and Trubicka, J. and Szeszenia-Dabrowska, N. and Lissowska, J. and Rudnai, P. and Fabianova, E. and Bucur, A. and Bencko, V. and Foretova, L. and Janout, V. and Boffetta, P. and Colt, J.S. and Davis, F.G. and Schwartz, K.L. and Banks, R.E. and Selby, P.J. and Harnden, P. and Hsing, A.W. and Grubb, R.L., III and Boeing, H. and Vineis, P. and Clavel-Chapelon, F. and Palli, D. and Tumino, R. and Krogh, V. and Panico, S. and Duell, E.J. and Quirós, J.R. and Sanchez, M.-J. and Navarro, C. and Ardanaz, E. and Dorronsoro, M. and Khaw, K.-T. and Allen, N.E. and Bueno-de-Mesquita, H.B. and Peeters, P.H.M. and Trichopoulos, D. and Linseisen, J. and Ljungberg, B. and Overvad, K. and Tjønneland, A. and Romieu, I. and Mukeria, A. and Shangina, O. and Stevens, V.L. and Gapstur, S.M. and Pharoah, P.D. and Easton, D.F. and Njølstad, I. and Tell, G.S. and Stoltenberg, C. and Kumar, R. and Koppova, K. and Benhamou, S. and Oosterwijk, E. and Vermeulen, S.H. and Aben, K.K.H. and Van Der Marel, S.L. and Ye, Y. and Wood, C.G. and Pu, X. and Mazur, A.M. and Boulygina, E.S. and Chekanov, N.N. and Foglio, M. and Lechner, D. and Gut, I. and Heath, S. and Blanche, H. and Skryabin, K.G. and McKay, J.D. and Rothman, N. and Lathrop, M. and Brennan, P. and Saunders, B. and Thomas, H. and Clark, S. and Tomlinson, I.

Subjects
Male, pathogenesi, genetic association, phenotype, Adenomatous Polyposis Coli Protein, colorectal cancer, Colorectal Neoplasm, cancer risk, gene frequency, Polymorphism, Single Nucleotide, Article, DNA glycosyltransferase, adult, DNA glycosylase MutY, colon polyposi, single nucleotide polymorphism, genetic variability, middle aged, controlled study, Genetic Predisposition to Disease, human, DNA Glycosylase, Germ-Line Mutation, Aged, colorectal adenoma, Allele, modifier gene, Genes, Modifier, disease predisposition, APC protein, human, major clinical study, digestive system diseases, human tissue, APC protein, female, priority journal, Adenomatous Polyposis Coli, germline mutation, familial colon polyposi, adenoma, single nucleotide polymorphism, Adenoma, genetic, genetic predisposition
Abstract

The presence of multiple (5-100) colorectal adenomas suggests an inherited predisposition, but the genetic aetiology of this phenotype is undetermined if patients test negative for Mendelian polyposis syndromes such as familial adenomatous polyposis (FAP) and MUTYH-associated polyposis (MAP). We investigated whether 18 common colorectal cancer (CRC) predisposition single-nucleotide polymorphisms (SNPs) could help to explain some cases with multiple adenomas who phenocopied FAP or MAP, but had no pathogenic APC or MUTYH variant. No multiple adenoma case had an outlying number of CRC SNP risk alleles, but multiple adenoma patients did have a significantly higher number of risk alleles than population controls (P = 5.7 × 10-7). The association was stronger in those with ≥ 10 adenomas. The CRC SNPs accounted for 4.3% of the variation in multiple adenoma risk, with three SNPs (rs6983267, rs10795668, rs3802842) explaining 3.0% of the variation. In FAP patients, the CRC risk score did not differ significantly from the controls, as we expected given the overwhelming effect of pathogenic germline APC variants on the phenotype of these cases. More unexpectedly, we found no evidence that the CRC SNPs act as modifier genes for the number of colorectal adenomas in FAP patients. In conclusion, common colorectal tumour risk alleles contribute to the development of multiple adenomas in patients without pathogenic germline APC or MUTYH variants. This phenotype may have 'polygenic' or monogenic origins. The risk of CRC in relatives of multiple adenoma cases is probably much lower for cases with polygenic disease, and this should be taken into account when counselling such patients. © 2015 Macmillan Publishers Limited All rights reserved.

Published
2015

15. Toward high-resolution population genomics using archaeological samples

Author

Morozova, I., Flegontov, P., Mikheyev, A.S., Bruskin, S., Asgharian, H., Ponomarenko, P., Klyuchnikov, V., ArunKumar, G., Prokhortchouk, E., Gankin, Y., Rogaev, E., Nikolsky, Y., Baranova, A., Elhaik, E., Tatarinova, T.V., University of Zurich, and Morozova, Irina

Subjects
1311 Genetics, 11294 Institute of Evolutionary Medicine, 1312 Molecular Biology, 570 Life sciences, biology, 610 Medicine & health
Abstract

The term ‘ancient DNA’ (aDNA) is coming of age, with over 1,200 hits in the PubMed database,\ud beginning in the early 1980s with the studies of ‘molecular paleontology’. Rooted in cloning\ud and limited sequencing of DNA from ancient remains during the pre-PCR era, the field has\ud made incredible progress since the introduction of PCR and next-generation sequencing. Over\ud the last decade, aDNA analysis ushered in a new era in genomics and became the method of\ud choice for reconstructing the history of organisms, their biogeography, and migration routes,\ud with applications in evolutionary biology, population genetics, archaeogenetics, paleoepidemiology,\ud and many other areas. This change was brought by development of new strategies\ud for coping with the challenges in studying aDNA due to damage and fragmentation, scarce\ud samples, significant historical gaps, and limited applicability of population genetics methods. In this review, we describe the state-of-the-art achievements in aDNA studies, with particular focus\ud on human evolution and demographic history. We present the current experimental and theoretical\ud procedures for handling and analysing highly degraded aDNA. We also review the challenges\ud in the rapidly growing field of ancient epigenomics. Advancement of aDNA tools and\ud methods signifies a new era in population genetics and evolutionary medicine research.

Published
2016

18. Genome-wide association study of renal cell carcinoma identifiestwo susceptibility loci on 2p21 and 11q13.3

Author

Purdue MP, Johansson M, Zelenika D, Toro JR, Scelo G, Moore LE, Prokhortchouk E, Wu X, Kiemeney LA, Gaborieau V, Jacobs KB, Chow WH, Zaridze D, Matveev V, Lubinski J, Trubicka J, Szeszenia Dabrowska N, Lissowska J, Rudnai P, Fabianova E, Bucur A, Bencko V, Foretova L, Janout V, Boffetta P, Colt JS, Davis FG, Schwartz KL, Banks RE, Selby PJ, Harnden P, Berg CD, Hsing AW, Grubb RL 3rd, Boeing H, Vineis P, Clavel Chapelon F, Palli D, Tumino R, Krogh V, Duell EJ, Quirós JR, Sanchez MJ, Navarro C, Ardanaz E, Dorronsoro M, Khaw KT, Allen NE, Bueno de Mesquita HB, Peeters PH, Trichopoulos D, Linseisen J, Ljungberg B, Overvad K, Tjønneland A, Romieu I, Riboli E, Mukeria A, Shangina O, Stevens VL, Thun MJ, Diver WR, Gapstur SM, Pharoah PD, Easton DF, Albanes D, Weinstein SJ, Virtamo J, Vatten L, Hveem K, Njølstad I, Tell GS, Stoltenberg C, Kumar R, Koppova K, Cussenot O, Benhamou S, Oosterwijk E, Vermeulen SH, Aben KK, van der Marel SL, Ye Y, Wood CG, Pu X, Mazur AM, Boulygina ES, Chekanov NN, Foglio M, Lechner D, Gut I, Heath S, Blanche H, Hutchinson A, Thomas G, Wang Z, Yeager M, Fraumeni JF Jr, Skryabin KG, McKay JD, Rothman N, Chanock SJ, Lathrop M, Brennan P., PANICO, SALVATORE, Purdue, Mp, Johansson, M, Zelenika, D, Toro, Jr, Scelo, G, Moore, Le, Prokhortchouk, E, Wu, X, Kiemeney, La, Gaborieau, V, Jacobs, Kb, Chow, Wh, Zaridze, D, Matveev, V, Lubinski, J, Trubicka, J, Szeszenia Dabrowska, N, Lissowska, J, Rudnai, P, Fabianova, E, Bucur, A, Bencko, V, Foretova, L, Janout, V, Boffetta, P, Colt, J, Davis, Fg, Schwartz, Kl, Banks, Re, Selby, Pj, Harnden, P, Berg, Cd, Hsing, Aw, Grubb RL, 3rd, Boeing, H, Vineis, P, Clavel Chapelon, F, Palli, D, Tumino, R, Krogh, V, Panico, Salvatore, Duell, Ej, Quirós, Jr, Sanchez, Mj, Navarro, C, Ardanaz, E, Dorronsoro, M, Khaw, Kt, Allen, Ne, Bueno de Mesquita, Hb, Peeters, Ph, Trichopoulos, D, Linseisen, J, Ljungberg, B, Overvad, K, Tjønneland, A, Romieu, I, Riboli, E, Mukeria, A, Shangina, O, Stevens, Vl, Thun, Mj, Diver, Wr, Gapstur, Sm, Pharoah, Pd, Easton, Df, Albanes, D, Weinstein, Sj, Virtamo, J, Vatten, L, Hveem, K, Njølstad, I, Tell, G, Stoltenberg, C, Kumar, R, Koppova, K, Cussenot, O, Benhamou, S, Oosterwijk, E, Vermeulen, Sh, Aben, Kk, van der Marel, Sl, Ye, Y, Wood, Cg, Pu, X, Mazur, Am, Boulygina, E, Chekanov, Nn, Foglio, M, Lechner, D, Gut, I, Heath, S, Blanche, H, Hutchinson, A, Thomas, G, Wang, Z, Yeager, M, Fraumeni JF, Jr, Skryabin, Kg, Mckay, Jd, Rothman, N, Chanock, Sj, Lathrop, M, and Brennan, P.

Published
2011

24. Genome-wide nucleosome map and cytosine methylation levels of an ancient human genome

Author

Pedersen, J., Valen, E., Velazquez, A., Parker, B., Rasmussen, M., Lindgreen, S., Lilje, B., Tobin, D., Kelly, T., Vang, S., Andersson, R., Jones, P., Hoover, C., Tikhonov, A., Prokhortchouk, E., Rubin, E., Sandelin, A., Gilbert, Thomas, Krogh, A., Willerslev, E., Orlando, L., Pedersen, J., Valen, E., Velazquez, A., Parker, B., Rasmussen, M., Lindgreen, S., Lilje, B., Tobin, D., Kelly, T., Vang, S., Andersson, R., Jones, P., Hoover, C., Tikhonov, A., Prokhortchouk, E., Rubin, E., Sandelin, A., Gilbert, Thomas, Krogh, A., Willerslev, E., and Orlando, L.

Abstract

Epigenetic information is available from contemporary organisms, but is difficult to track back in evolutionary time. Here, we show that genome-wide epigenetic information can be gathered directly from next generation sequence reads of DNA isolated from ancient remains. Using the genome sequence data generated from hair shafts of a four thousand year old Palaeo-Eskimo belonging to the Saqqaq culture, we generate the first ancient nucleosome map coupled with a genome-wide survey of cytosine methylation levels. The validity of both nucleosome map and methylation levels were confirmed by the recovery of the expected signals at promoter regions, exon/intron boundaries, and CTCF sites. The top-scoring nucleosome calls revealed distinct DNA positioning biases attesting to nucleotide-level accuracy. The ancient methylation levels exhibited high conservation over time, clustering closely with modern hair tissues. Using ancient methylation information we estimated the age at death of the Saqqaq individual and illustrate how epigenetic information can be used to infer ancient gene expression. Similar epigenetic signatures were found in other fossil material, such as 110-130 kyr-old bones, supporting the contention that ancient epigenomic information can be reconstructed from a deep past. Our findings lay the foundation for extracting epigenomic information from ancient samples, allowing shifts in epialleles to be tracked through evolutionary time as well as providing an original window into modern epigenomics.

Published
2014

26. Genome-wide association study of renal cell carcinoma identifies two susceptibility loci on 2p21 and 11q13.3

Author

Purdue, M.P., Johansson, M., Zelenika, D., Toro, J.R., Scelo, G., Moore, L.E., Prokhortchouk, E., Wu, X., Kiemeney, L.A.L.M., Gaborieau, V., Jacobs, K.B., Chow, W.H., Zaridze, D., Matveev, V., Lubinski, J., Trubicka, J., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., Fabianova, E., Bucur, A., Bencko, V., Foretova, L., Janout, V., Boffetta, P., Colt, J.S., Davis, F.G., Schwartz, K.L., Banks, R.E., Selby, P.J., Harnden, P., Berg, C.D., Hsing, A.W., Grubb, R.L. 3rd, Boeing, H., Vineis, P., Clavel-Chapelon, F., Palli, D., Tumino, R., Krogh, V., Panico, S., Duell, E.J., Quiros, J.R., Sanchez, M.J., Navarro, C, Ardanaz, E., Dorronsoro, M., Khaw, K.T., Allen, N.E., Bueno-De-Mesquita, H.B., Peeters, P.H.M., Trichopoulos, D., Linseisen, J., Ljungberg, B, Overvad, K., Tjonneland, A., Romieu, I., Riboli, E., Mukeria, A., Shangina, O., Stevens, V.L., Thun, M.J., Diver, W.R., Gapstur, S.M., Pharoah, P.D., Easton, D.F., Albanes, D., Weinstein, S.J., Virtamo, J., Vatten, L., Hveem, K., Njolstad, I., Tell, G.S., Stoltenberg, C., Kumar, R., Koppova, K., Cussenot, O., Benhamou, S., Oosterwijk, E., Vermeulen, H.H.M., Aben, K.K.H., Marel, S.L. van der, Ye, Y., Wood, C.G., Pu, X., Mazur, A.M., Boulygina, E.S., Chekanov, N.N., Foglio, M., Lechner, D., Gut, I, Heath, S., Blanche, H., Hutchinson, A., Thomas, G., Wang, Z., Yeager, M., Fraumeni, J.F. Jr., Skryabin, K.G., McKay, J.D., Purdue, M.P., Johansson, M., Zelenika, D., Toro, J.R., Scelo, G., Moore, L.E., Prokhortchouk, E., Wu, X., Kiemeney, L.A.L.M., Gaborieau, V., Jacobs, K.B., Chow, W.H., Zaridze, D., Matveev, V., Lubinski, J., Trubicka, J., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., Fabianova, E., Bucur, A., Bencko, V., Foretova, L., Janout, V., Boffetta, P., Colt, J.S., Davis, F.G., Schwartz, K.L., Banks, R.E., Selby, P.J., Harnden, P., Berg, C.D., Hsing, A.W., Grubb, R.L. 3rd, Boeing, H., Vineis, P., Clavel-Chapelon, F., Palli, D., Tumino, R., Krogh, V., Panico, S., Duell, E.J., Quiros, J.R., Sanchez, M.J., Navarro, C, Ardanaz, E., Dorronsoro, M., Khaw, K.T., Allen, N.E., Bueno-De-Mesquita, H.B., Peeters, P.H.M., Trichopoulos, D., Linseisen, J., Ljungberg, B, Overvad, K., Tjonneland, A., Romieu, I., Riboli, E., Mukeria, A., Shangina, O., Stevens, V.L., Thun, M.J., Diver, W.R., Gapstur, S.M., Pharoah, P.D., Easton, D.F., Albanes, D., Weinstein, S.J., Virtamo, J., Vatten, L., Hveem, K., Njolstad, I., Tell, G.S., Stoltenberg, C., Kumar, R., Koppova, K., Cussenot, O., Benhamou, S., Oosterwijk, E., Vermeulen, H.H.M., Aben, K.K.H., Marel, S.L. van der, Ye, Y., Wood, C.G., Pu, X., Mazur, A.M., Boulygina, E.S., Chekanov, N.N., Foglio, M., Lechner, D., Gut, I, Heath, S., Blanche, H., Hutchinson, A., Thomas, G., Wang, Z., Yeager, M., Fraumeni, J.F. Jr., Skryabin, K.G., and McKay, J.D.

Abstract

Contains fulltext : 97937.pdf (publisher's version ) (Closed access), We conducted a two-stage genome-wide association study of renal cell carcinoma (RCC) in 3,772 affected individuals (cases) and 8,505 controls of European background from 11 studies and followed up 6 SNPs in 3 replication studies of 2,198 cases and 4,918 controls. Two loci on the regions of 2p21 and 11q13.3 were associated with RCC susceptibility below genome-wide significance. Two correlated variants (r(2) = 0.99 in controls), rs11894252 (P = 1.8 x 10) and rs7579899 (P = 2.3 x 10), map to EPAS1 on 2p21, which encodes hypoxia-inducible-factor-2 alpha, a transcription factor previously implicated in RCC. The second locus, rs7105934, at 11q13.3, contains no characterized genes (P = 7.8 x 10(1)). In addition, we observed a promising association on 12q24.31 for rs4765623, which maps to SCARB1, the scavenger receptor class B, member 1 gene (P = 2.6 x 10). Our study reports previously unidentified genomic regions associated with RCC risk that may lead to new etiological insights.

Published
2011

27. International network of cancer genome projects

Author

Hudson, TJ, Anderson, W, Aretz, A, Barker, AD, Bell, C, Bernabe, RR, Bhan, MK, Calvo, F, Eerola, I, Gerhard, DS, Guttmacher, A, Guyer, M, Hemsley, FM, Jennings, JL, Kerr, D, Klatt, P, Kolar, P, Kusuda, J, Lane, DP, Laplace, F, Lu, Y, Nettekoven, G, Ozenberger, B, Peterson, J, Rao, TS, Remacle, J, Schafer, AJ, Shibata, T, Stratton, MR, Vockley, JG, Watanabe, K, Yang, H, Yuen, MMF, Knoppers, M, Bobrow, M, Cambon-Thomsen, A, Dressler, LG, Dyke, SOM, Joly, Y, Kato, K, Kennedy, KL, Nicolas, P, Parker, MJ, Rial-Sebbag, E, Romeo-Casabona, CM, Shaw, KM, Wallace, S, Wiesner, GL, Zeps, N, Lichter, P, Biankin, AV, Chabannon, C, Chin, L, Clement, B, de Alava, E, Degos, F, Ferguson, ML, Geary, P, Hayes, DN, Johns, AL, Nakagawa, H, Penny, R, Piris, MA, Sarin, R, Scarpa, A, van de Vijver, M, Futreal, PA, Aburatani, H, Bayes, M, Bowtell, DDL, Campbell, PJ, Estivill, X, Grimmond, SM, Gut, I, Hirst, M, Lopez-Otin, C, Majumder, P, Marra, M, Ning, Z, Puente, XS, Ruan, Y, Stunnenberg, HG, Swerdlow, H, Velculescu, VE, Wilson, RK, Xue, HH, Yang, L, Spellman, PT, Bader, GD, Boutros, PC, Flicek, P, Getz, G, Guigo, R, Guo, G, Haussler, D, Heath, S, Hubbard, TJ, Jiang, T, Jones, SM, Li, Q, Lopez-Bigas, N, Luo, R, Pearson, JV, Quesada, V, Raphael, BJ, Sander, C, Speed, TP, Stuart, JM, Teague, JW, Totoki, Y, Tsunoda, T, Valencia, A, Wheeler, DA, Wu, H, Zhao, S, Zhou, G, Stein, LD, Lathrop, M, Ouellette, BFF, Thomas, G, Yoshida, T, Axton, M, Gunter, C, McPherson, JD, Miller, LJ, Kasprzyk, A, Zhang, J, Haider, SA, Wang, J, Yung, CK, Cross, A, Liang, Y, Gnaneshan, S, Guberman, J, Hsu, J, Chalmers, DRC, Hasel, KW, Kaan, TSH, Knoppers, BM, Lowrance, WW, Masui, T, Rodriguez, LL, Vergely, C, Cloonan, N, Defazio, A, Eshleman, JR, Etemadmoghadam, D, Gardiner, BA, Kench, JG, Sutherland, RL, Tempero, MA, Waddell, NJ, Wilson, PJ, Gallinger, S, Tsao, M-S, Shaw, PA, Petersen, GM, Mukhopadhyay, D, DePinho, RA, Thayer, S, Muthuswamy, L, Shazand, K, Beck, T, Sam, M, Timms, L, Ballin, V, Ji, J, Zhang, X, Chen, F, Hu, X, Yang, Q, Tian, G, Zhang, L, Xing, X, Li, X, Zhu, Z, Yu, Y, Yu, J, Tost, J, Brennan, P, Holcatova, I, Zaridze, D, Brazma, A, Egevad, L, Prokhortchouk, E, Banks, RE, Uhlen, M, Viksna, J, Ponten, F, Skryabin, K, Birney, E, Borg, A, Borresen-Dale, A-L, Caldas, C, Foekens, JA, Martin, S, Reis-Filho, JS, Richardson, AL, Sotiriou, C, van't Veer, L, Birnbaum, D, Blanche, H, Boucher, P, Boyault, S, Masson-Jacquemier, JD, Pauporte, I, Pivot, X, Vincent-Salomon, A, Tabone, E, Theillet, C, Treilleux, I, Bioulac-Sage, P, Decaens, T, Franco, D, Gut, M, Samuel, D, Zucman-Rossi, J, Eils, R, Brors, B, Korbel, JO, Korshunov, A, Landgraf, P, Lehrach, H, Pfister, S, Radlwimmer, B, Reifenberger, G, Taylor, MD, von Kalle, C, Majumder, PP, Pederzoli, P, Lawlor, RT, Delledonne, M, Bardelli, A, Gress, T, Klimstra, D, Zamboni, G, Nakamura, Y, Miyano, S, Fujimoto, A, Campo, E, de Sanjose, S, Montserrat, E, Gonzalez-Diaz, M, Jares, P, Himmelbaue, H, Bea, S, Aparicio, S, Easton, DF, Collins, FS, Compton, CC, Lander, ES, Burke, W, Green, AR, Hamilton, SR, Kallioniemi, OP, Ley, TJ, Liu, ET, Wainwright, BJ, Hudson, TJ, Anderson, W, Aretz, A, Barker, AD, Bell, C, Bernabe, RR, Bhan, MK, Calvo, F, Eerola, I, Gerhard, DS, Guttmacher, A, Guyer, M, Hemsley, FM, Jennings, JL, Kerr, D, Klatt, P, Kolar, P, Kusuda, J, Lane, DP, Laplace, F, Lu, Y, Nettekoven, G, Ozenberger, B, Peterson, J, Rao, TS, Remacle, J, Schafer, AJ, Shibata, T, Stratton, MR, Vockley, JG, Watanabe, K, Yang, H, Yuen, MMF, Knoppers, M, Bobrow, M, Cambon-Thomsen, A, Dressler, LG, Dyke, SOM, Joly, Y, Kato, K, Kennedy, KL, Nicolas, P, Parker, MJ, Rial-Sebbag, E, Romeo-Casabona, CM, Shaw, KM, Wallace, S, Wiesner, GL, Zeps, N, Lichter, P, Biankin, AV, Chabannon, C, Chin, L, Clement, B, de Alava, E, Degos, F, Ferguson, ML, Geary, P, Hayes, DN, Johns, AL, Nakagawa, H, Penny, R, Piris, MA, Sarin, R, Scarpa, A, van de Vijver, M, Futreal, PA, Aburatani, H, Bayes, M, Bowtell, DDL, Campbell, PJ, Estivill, X, Grimmond, SM, Gut, I, Hirst, M, Lopez-Otin, C, Majumder, P, Marra, M, Ning, Z, Puente, XS, Ruan, Y, Stunnenberg, HG, Swerdlow, H, Velculescu, VE, Wilson, RK, Xue, HH, Yang, L, Spellman, PT, Bader, GD, Boutros, PC, Flicek, P, Getz, G, Guigo, R, Guo, G, Haussler, D, Heath, S, Hubbard, TJ, Jiang, T, Jones, SM, Li, Q, Lopez-Bigas, N, Luo, R, Pearson, JV, Quesada, V, Raphael, BJ, Sander, C, Speed, TP, Stuart, JM, Teague, JW, Totoki, Y, Tsunoda, T, Valencia, A, Wheeler, DA, Wu, H, Zhao, S, Zhou, G, Stein, LD, Lathrop, M, Ouellette, BFF, Thomas, G, Yoshida, T, Axton, M, Gunter, C, McPherson, JD, Miller, LJ, Kasprzyk, A, Zhang, J, Haider, SA, Wang, J, Yung, CK, Cross, A, Liang, Y, Gnaneshan, S, Guberman, J, Hsu, J, Chalmers, DRC, Hasel, KW, Kaan, TSH, Knoppers, BM, Lowrance, WW, Masui, T, Rodriguez, LL, Vergely, C, Cloonan, N, Defazio, A, Eshleman, JR, Etemadmoghadam, D, Gardiner, BA, Kench, JG, Sutherland, RL, Tempero, MA, Waddell, NJ, Wilson, PJ, Gallinger, S, Tsao, M-S, Shaw, PA, Petersen, GM, Mukhopadhyay, D, DePinho, RA, Thayer, S, Muthuswamy, L, Shazand, K, Beck, T, Sam, M, Timms, L, Ballin, V, Ji, J, Zhang, X, Chen, F, Hu, X, Yang, Q, Tian, G, Zhang, L, Xing, X, Li, X, Zhu, Z, Yu, Y, Yu, J, Tost, J, Brennan, P, Holcatova, I, Zaridze, D, Brazma, A, Egevad, L, Prokhortchouk, E, Banks, RE, Uhlen, M, Viksna, J, Ponten, F, Skryabin, K, Birney, E, Borg, A, Borresen-Dale, A-L, Caldas, C, Foekens, JA, Martin, S, Reis-Filho, JS, Richardson, AL, Sotiriou, C, van't Veer, L, Birnbaum, D, Blanche, H, Boucher, P, Boyault, S, Masson-Jacquemier, JD, Pauporte, I, Pivot, X, Vincent-Salomon, A, Tabone, E, Theillet, C, Treilleux, I, Bioulac-Sage, P, Decaens, T, Franco, D, Gut, M, Samuel, D, Zucman-Rossi, J, Eils, R, Brors, B, Korbel, JO, Korshunov, A, Landgraf, P, Lehrach, H, Pfister, S, Radlwimmer, B, Reifenberger, G, Taylor, MD, von Kalle, C, Majumder, PP, Pederzoli, P, Lawlor, RT, Delledonne, M, Bardelli, A, Gress, T, Klimstra, D, Zamboni, G, Nakamura, Y, Miyano, S, Fujimoto, A, Campo, E, de Sanjose, S, Montserrat, E, Gonzalez-Diaz, M, Jares, P, Himmelbaue, H, Bea, S, Aparicio, S, Easton, DF, Collins, FS, Compton, CC, Lander, ES, Burke, W, Green, AR, Hamilton, SR, Kallioniemi, OP, Ley, TJ, Liu, ET, and Wainwright, BJ

Abstract

The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

Published
2010

28. Metagenomic Analysis of the Dynamic Changes in the Gut Microbiome of the Participants of the MARS-500 Experiment, Simulating Long Term Space Flight

Author

Mardanov, A. V., primary, Babykin, M. M., additional, Beletsky, A. V., additional, Grigoriev, A. I., additional, Zinchenko, V. V., additional, Kadnikov, V. V., additional, Kirpichnikov, M. P., additional, Mazur, A. M., additional, Nedoluzhko, A. V., additional, Novikova, N. D., additional, Prokhortchouk, E. B., additional, Ravin, N. V., additional, Skryabin, K. G., additional, and Shestakov, S. V., additional

Published
2013
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29. Identification of novel micro RNA genes in freshwater and marine ecotypes of the three-spined stickleback ( Gasterosteus aculeatus).

Author

Rastorguev, S. M., Nedoluzhko, A. V., Sharko, F. S., Boulygina, E. S., Sokolov, A. S., Gruzdeva, N. M., Skryabin, K. G., and Prokhortchouk, E. B.

Subjects
BIOLOGICAL adaptation, THREESPINE stickleback, MICRORNA, GENETIC speciation, BIOINFORMATICS
Abstract

The three-spined stickleback ( Gasterosteus aculeatus L.) is an important model organism for studying the molecular mechanisms of speciation and adaptation to salinity. Despite increased interest to micro RNA discovery and recent publication on micro RNA prediction in the three-spined stickleback using bioinformatics approaches, there is still a lack of experimental support for these data. In this paper, high-throughput sequencing technology was applied to identify micro RNA genes in gills of the three-spined stickleback. In total, 595 mi RNA genes were discovered; half of them were predicted in previous computational studies and were confirmed here as micro RNAs expressed in gill tissue. Moreover, 298 novel micro RNA genes were identified. The presence of mi RNA genes in selected 'divergence islands' was analysed and 10 mi RNA genes were identified as not randomly located in 'divergence islands'. Regulatory regions of mi RNA genes were found enriched with selective SNPs that may play a role in freshwater adaptation. [ABSTRACT FROM AUTHOR]

Published
2016
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32. Combining Two Technologies for Full Genome Sequencing of Human

Author

Skryabin, K G, primary, Prokhortchouk, E B, additional, Mazur, A M, additional, Boulygina, E S, additional, Tsygankova, S V, additional, Nedoluzhko, A V, additional, Rastorguev, S M, additional, Matveev, V B, additional, Chekanov, N N, additional, Goranskaya, D A, additional, Teslyuk, A B, additional, Gruzdeva, N M, additional, Velikhov, V E, additional, Zaridze, D G, additional, and Kovalchuk, M V, additional

Published
2009
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34. The p120 catenin partner Kaiso is a DNA methylation-dependent transcriptional repressor.

Author

Prokhortchouk, A, Hendrich, B, Jørgensen, H, Ruzov, A, Wilm, M, Georgiev, G, Bird, A, and Prokhortchouk, E

Abstract

We describe a novel mammalian DNA binding activity that requires at least two symmetrically methylated CpG dinucleotides in its recognition sequence, preferably within the sequence 5'CGCG. A key component of the activity is Kaiso, a protein with POZ and zinc-finger domains that is known to associate with p120 catenin. We find that Kaiso behaves as a methylation-dependent transcriptional repressor in transient transfection assays. Kaiso is a constituent of one of two methyl-CpG binding complexes originally designated as MeCP1. The data suggest that zinc-finger motifs are responsible for DNA binding, and may therefore target repression to specific methylated regions of the genome. As Kaiso associates with p120 catenin, Kaiso may link events at the cell surface with DNA methylation-dependent gene silencing.

Published
2001
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35. Molecular cloning and characterization of the mouse tag7 gene encoding a novel cytokine.

Author

Kiselev, S L, Kustikova, O S, Korobko, E V, Prokhortchouk, E B, Kabishev, A A, Lukanidin, E M, and Georgiev, G P

Abstract

Cloning of the mouse tag7 gene encoding a novel cytokine is described. The Tag7 protein consists of 182 amino acids. Genomic organization of the tag7 gene and its promoter region remind those of the genes of the tumor necrosis factor locus, although the tag7 gene is not linked to this locus. The gene is located on chromosome 7 at the area that corresponds to band 7A3, which has genetic linkage with lupus-like disease in mouse models. tag7 transcription is essential for lymphoid organs. It is also detected in certain areas of lungs, brain, and intestine and in some tumors. Tag7 protein is detectable in both cell-associated and soluble forms. The soluble form of Tag7 triggers apoptosis in mouse L929 cells in vitro and does not involve NF-kappaB activation. The relationship between Tag7 and tumor necrosis factor family of ligands is discussed.

Published
1998

36. A kappaB-related binding site is an integral part of the mts1 gene composite enhancer element located in the first intron of the gene.

Author

Tulchinsky, E, Prokhortchouk, E, Georgiev, G, and Lukanidin, E

Abstract

The transcription of the mts1 gene correlates with the metastatic potential of mouse adenocarcinomas. Here we describe strong enhancer whose location coincides with the DNase I hypersensitivity area in the first intron of the mts1 gene. The investigation of the transcriptional activity of a series of plasmids bearing deletions in the first intron sequences revealed that the observed enhancer has a composite structure. The enhancer activity is partially formed by the kappaB-related element: GGGGTTTTTCCAC. This sequence element was able to form several sequence-specific complexes with nuclear proteins extracted from both Mts1-expressing CSML100 and Mts1-non-expressing CSML0 adenocarcinoma cells. Two of these complexes were identified as NF-kappaB/Rel-specific p50.p50 homo- and p50.p65 heterodimers. The third complex was formed by the 200-kDa protein. Even though the synthetic kappaB-responsible promoter was active in mouse adenocarcinoma cells, a mutation preventing NF-kappaB binding had no effect on the mts1 natural enhancer activity. On the contrary, the mutation in the kappaB-related element, which abolished the binding of the 200-kDa protein, led to the functional inactivation of this site in the mts1 first intron. The mts1 kappaB-like element activated transcription from its own mts1 gene promoter, as well as from the heterologous promoter in both CSML0 and CSML100 cells. However, in vivo occupancy of this site was observed only in Mts1-expressing CSML100 cells, suggesting the involvement of the described element in positive control of mts1 transcription.

Published
1997

37. Genome-wide association study of renal cell carcinoma identifies two susceptibility loci on 2p21 and 11q13.3

Author

Jorge R. Toro, Vladimir Janout, Zhaoming Wang, Françoise Clavel-Chapelon, Petra H.M. Peeters, Paul Brennan, Camilla Stoltenberg, Hélène Blanché, Diana Zelenika, Vsevolod Matveev, Naomi E. Allen, Rosario Tumino, Vladimir Bencko, H. Bas Bueno-de-Mesquita, Lee E. Moore, María José Sánchez, Mark P. Purdue, Stephen J. Chanock, Kim Overvad, Kvetoslava Koppova, Joanne S. Colt, Eleonora Fabianova, Yuanqing Ye, Grethe S. Tell, Simon Heath, José Ramón Quirós, Egbert Oosterwijk, Amy Hutchinson, Jan Lubinski, Kristian Hveem, Peter Rudnai, Alexandru Bucur, Elio Riboli, James McKay, Ivo Gut, Paolo Vineis, Rosamonde E. Banks, Douglas F. Easton, Jarmo Virtamo, Wong-Ho Chow, Neonila Szeszenia-Dabrowska, Isabelle Romieu, Mark Lathrop, Demetrius Albanes, Kevin B. Jacobs, Sita H. Vermeulen, Egor Prokhortchouk, Carmen Navarro, Ann W. Hsing, Doris Lechner, M. Dorronsoro, Kendra Schwartz, Konstantin G. Skryabin, Mattias Johansson, Eric J. Duell, Valerie Gaborieau, W. Ryan Diver, Susan M. Gapstur, Börje Ljungberg, Dimitrios Trichopoulos, Paul D.P. Pharoah, Gilles Thomas, Victoria L. Stevens, Paolo Boffetta, Vittorio Krogh, David Zaridze, Lambertus A. Kiemeney, Joseph F. Fraumeni, Eugenia S. Boulygina, Kay-Tee Khaw, Olivier Cussenot, Heiner Boeing, Nathaniel Rothman, Michael J. Thun, Saskia S. L. van der Marel, Anush Mukeria, Alexander M. Mazur, Salvatore Panico, Peter Selby, Ghislaine Scelo, Faith G. Davis, Simone Benhamou, Joanna Trubicka, Christine D. Berg, Anne Tjønneland, Eva Ardanaz, Jolanta Lissowska, Katja K.H. Aben, Xifeng Wu, Rajesh Kumar, Jakob Linseisen, Nikolai N. Chekanov, Domenico Palli, Stephanie J. Weinstein, Inger Njølstad, Mario Foglio, Lars J. Vatten, Meredith Yeager, Xia Pu, Robert L. Grubb, Oxana Shangina, Christopher G. Wood, Patricia Harnden, Lenka Foretova, Purdue, M.P., Johansson, M., Zelenika, D., Toro, J.R., Scelo, G., Moore, L.E., Prokhortchouk, E., Wu, X., Kiemeney, L.A., Gaborieau, V., Jacobs, K.B., Chow, W.-H., Zaridze, D., Matveev, V., Lubinski, J., Trubicka, J., Szeszenia-Dabrowska, N., Lissowska, J., Rudnai, P., Fabianova, E., Bucur, A., Bencko, V., Foretova, L., Janout, V., Boffetta, P., Colt, J.S., Davis, F.G., Schwartz, K.L., Banks, R.E., Selby, P.J., Harnden, P., Berg, C.D., Hsing, A.W., Grubb, R.L., Boeing, H., Vineis, P., Clavel-Chapelon, F., Palli, D., Tumino, R., Krogh, V., Panico, S., Duell, E.J., Quiós, J.R., Sanchez, M.-J., Navarro, C., Ardanaz, E., Dorronsoro, M., Khaw, K.-T., Allen, N.E., Bueno-De-Mesquita, H.B., Peeters, P.H.M., Trichopoulos, D., Linseisen, J., Ljungberg, B., Overvad, K., Tjønneland, A., Romieu, I., Riboli, E., Mukeria, A., Shangina, O., Stevens, V.L., Thun, M.J., Diver, W.R., Gapstur, S.M., Pharoah, P.D., Easton, D.F., Albanes, D., Weinstein, S.J., Virtamo, J., Vatten, L., Hveem, K., Njølstad, I., Tell, G.S., Stoltenberg, C., Kumar, R., Koppova, K., Cussenot, O., Benhamou, S., Oosterwijk, E., Vermeulen, S.H., Aben, K.K.H., Van Der Marel, S.L., Ye, Y., Wood, C.G., Pu, X., Mazur, A.M., Boulygina, E.S., Chekanov, N.N., Foglio, M., Lechner, D., Gut, I., Heath, S., Blanche, H., Hutchinson, A., Thomas, G., Wang, Z., Yeager, M., Fraumeni Jr., J.F., Skryabin, K.G., McKay, J.D., Rothman, N., Chanock, S.J., Lathrop, M., and Brennan, P.

Subjects
Genetics and epigenetic pathways of disease [NCMLS 6], Single-nucleotide polymorphism, Locus (genetics), Genome-wide association study, Biology, carcinoma, association study, Genome, Polymorphism, Single Nucleotide, susceptibility, Article, Càncer de ronyó, Genomic disorders and inherited multi-system disorders [IGMD 3], Molecular epidemiology [NCEBP 1], 03 medical and health sciences, 0302 clinical medicine, Gene mapping, Risk Factors, Genetics, Humans, Genetic Predisposition to Disease, Genome-wide, Gene, Carcinoma, Renal Cell, 030304 developmental biology, 11q13.3, Molecular epidemiology Aetiology, screening and detection [NCEBP 1], 0303 health sciences, Genome, Human, Chromosomes, Human, Pair 11, Kidney cancer, Genomics, 2p21, SCARB1, Kidney Neoplasms, 3. Good health, Genòmica, 030220 oncology & carcinogenesis, Case-Control Studies, Chromosomes, Human, Pair 2, loci, Human genome, renal, Genome-Wide Association Study
Abstract

Contains fulltext : 97937.pdf (Publisher’s version ) (Closed access) We conducted a two-stage genome-wide association study of renal cell carcinoma (RCC) in 3,772 affected individuals (cases) and 8,505 controls of European background from 11 studies and followed up 6 SNPs in 3 replication studies of 2,198 cases and 4,918 controls. Two loci on the regions of 2p21 and 11q13.3 were associated with RCC susceptibility below genome-wide significance. Two correlated variants (r(2) = 0.99 in controls), rs11894252 (P = 1.8 x 10) and rs7579899 (P = 2.3 x 10), map to EPAS1 on 2p21, which encodes hypoxia-inducible-factor-2 alpha, a transcription factor previously implicated in RCC. The second locus, rs7105934, at 11q13.3, contains no characterized genes (P = 7.8 x 10(1)). In addition, we observed a promising association on 12q24.31 for rs4765623, which maps to SCARB1, the scavenger receptor class B, member 1 gene (P = 2.6 x 10). Our study reports previously unidentified genomic regions associated with RCC risk that may lead to new etiological insights.

Published
2011

38. The Rurikids: The First Experience of Reconstructing the Genetic Portrait of the Ruling Family of Medieval Rus' Based on Paleogenomic Data.

Author

Zhur KV, Sharko FS, Sedov VV, Dobrovolskaya MV, Volkov VG, Maksimov NG, Seslavine AN, Makarov NA, and Prokhortchouk EB

Abstract

The Rurikids were the reigning house of Rus', its principalities and, ultimately the Tsardom of Russia, for seven centuries: from the IX to the end of the XVI century. According to the Primary Chronicle (the Tale of Bygone Years), the main chronicle of Rus', the Rurik dynasty was founded by the Varangian prince Rurik, invited to reign in Novgorod in 862, but still there is no direct genetic evidence of the origin of the early Rurikids. This research, for the first time, provides a genome-wide paleogenetic analysis of bone remains belonging to one of the Rurikids, Prince Dmitry Alexandrovich (?-1294), the son of the Grand Prince of Vladimir Alexander Yaroslavich Nevsky (1221-1263). It has been established that his Y chromosome belongs to the N1a haplogroup. Most of the modern Rurikids, according to their genealogies, belonging to the N1a haplogroup, have the most similar variants of Y chromosomes to each other, as well as to the Y chromosome of Prince Dmitry Alexandrovich. Genome-wide data of the medieval and modern Rurikids unequivocally indicates that they belong to the N1a haplogroup of the Y chromosome, starting at least from the XI century (since the time of Prince Yaroslav the Wise). All the other alleged Rurikids, both ancient and modern, being carriers of other haplogroups (R1a, I2a), possess high heterogeneity of the sequence of Y chromosomes, meaning that we cannot confirm their common ancestry. The most probable ancestors of Prince Dmitry Alexandrovich in the male line were the men who left the burial ground Bolshoy Oleny Island on the coast of the Kola Peninsula about 3,600 years ago. The reconstruction of the genome of Prince Dmitry Alexandrovich indicates the contribution of three ancestral components to his origin: (1) the early medieval population of the east of Scandinavia from the island of Oland, (2) representatives of the steppe nomadic peoples of the Eurasian steppes of the Iron Age or the early medieval population of central Europe (steppe nomads from the territory of Hungary), and (3) the ancient East-Eurasian component. Reliable statistics were also obtained when the Scandinavians were replaced with the Medieval Russian Slavic populations of the XI century. Thus, for the first time, we have shown the complex nature of interethnic interactions in the formation of the nobility of medieval Rus' on the example of the ancient Rurikid., (Copyright ® 2023 National Research University Higher School of Economics.)

Published
2023
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39. Distortion of Population Statistics due to the Use of Different Methodological Approaches to the Construction of Genomic DNA Libraries.

Author

Sharko FS, Zhur KV, Trifonov VA, and Prokhortchouk EB

Abstract

Several different methods of DNA library preparation for paleogenetic studies are now available. However, the chemical reactions underlying each of them can affect the primary sequence of ancient DNA (aDNA) in the libraries and taint the results of a statistical analysis. In this paper, we compare the results of a sequencing of the aDNA libraries of a Bronze Age sample from burials of the Caucasian burial ground Klady, prepared using three different approaches: (1) shotgun sequencing, (2) strategies for selecting target genomic regions, and (3) strategies for selecting target genomic regions, including DNA pre-treatment with a mixture of uracil-DNA glycosylase (UDG) and endonuclease VIII. The impact of the studied approaches to genomic library preparation on the results of a secondary analysis of the statistical data, namely F4 statistics, ADMIXTURE, and principal component analysis (PCA), was analyzed. It was shown that preparation of genomic libraries without the use of UDG can result in distorted statistical data due to postmortem chemical modifications of the aDNA. This distortion can be alleviated by analyzing only the single nucleotide polymorphisms caused by transversions in the genome., (Copyright ® 2023 National Research University Higher School of Economics.)

Published
2023
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40. DNA Methylation: Genomewide Distribution, Regulatory Mechanism and Therapy Target.

Author

Kaplun DS, Kaluzhny DN, Prokhortchouk EB, and Zhenilo SV

Abstract

DNA methylation is the most important epigenetic modification involved in the regulation of transcription, imprinting, establishment of X-inactivation, and the formation of a chromatin structure. DNA methylation in the genome is often associated with transcriptional repression and the formation of closed heterochromatin. However, the results of genome-wide studies of the DNA methylation pattern and transcriptional activity of genes have nudged us toward reconsidering this paradigm, since the promoters of many genes remain active despite their methylation. The differences in the DNA methylation distribution in normal and pathological conditions allow us to consider methylation as a diagnostic marker or a therapy target. In this regard, the need to investigate the factors affecting DNA methylation and those involved in its interpretation becomes pressing. Recently, a large number of protein factors have been uncovered, whose ability to bind to DNA depends on their methylation. Many of these proteins act not only as transcriptional activators or repressors, but also affect the level of DNA methylation. These factors are considered potential therapeutic targets for the treatment of diseases resulting from either a change in DNA methylation or a change in the interpretation of its methylation level. In addition to protein factors, a secondary DNA structure can also affect its methylation and can be considered as a therapy target. In this review, the latest research into the DNA methylation landscape in the genome has been summarized to discuss why some DNA regions avoid methylation and what factors can affect its level or interpretation and, therefore, can be considered a therapy target., (Copyright ® 2022 National Research University Higher School of Economics.)

Published
2022
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41. Genomic Estimated Breeding Value of Milk Performance and Fertility Traits in the Russian Black-and-White Cattle Population.

Author

Sharko FS, Khatib A, and Prokhortchouk EB

Abstract

A breakthrough in cattle breeding was achieved with the incorporation of animal genomic data into breeding programs. The introduction of genomic selection has a major impact on traditional genetic assessment systems and animal genetic improvement programs. Since 2010, genomic selection has been officially introduced in the evaluation of the breeding and genetic potential of cattle in Europe, the U.S., Canada, and many other developed countries. The purpose of this study is to develop a system for a genomic evaluation of the breeding value of the domestic livestock of Black-and-White and Russian Holstein cattle based on 3 milk performance traits: daily milk yield (kg), daily milk fat (%), and daily milk protein content (%) and 6 fertility traits: age at first calving (AFC), calving interval (CI), calving to first insemination interval (CFI), interval between first and last insemination (IFL), days open (DO), and number of services (NS). We built a unified database of breeding animals from 523 breeding farms in the Russian Federation. The database included pedigree information on 2,551,529 cows and 69,131 bulls of the Russian Holstein and Black-and-White cattle breeds, as well as information on the milk performance of 1,597,426 cows with 4,771,366 completed lactations. The date of birth of the animals included in the database was between 1975 and 2017. Genotyping was performed in 672 animals using a BovineSNP50 v3 DNA Analysis BeadChip microarray (Illumina, USA). The genomic estimated breeding value (GEBV) was evaluated only for 644 animals (427 bulls and 217 cows) using the single-step genomic best linear unbiased prediction - animal model (ssGBLUP-AM). The mean genetic potential was +0.88 and +1.03 kg for the daily milk yield, -0.002% for the milk fat content, and -0.003 and 0.001% for the milk protein content in the cows and bulls, respectively. There was negative genetic progress in the fertility traits in the studied population between 1975 and 2017. The reliability of the estimated breeding value (EBV) for genotyped bulls ranged from 89 to 93% for the milk performance traits and 85 to 90% for the fertility traits, whereas the reliability of the genomic estimated breeding value (GEBV) varied 54 to 64% for the milk traits and 23 to 60% for the fertility traits. This result shows that it is possible to use the genomic estimated breeding value with rather high reliability to evaluate the domestic livestock of Russian Holstein and Black-and-White cattle breeds for fertility and milk performance traits. This system of genomic evaluation may help bring domestic breeding in line with modern competitive practices and estimate the breeding value of cattle at birth based on information on the animal's genome., (Copyright ® 2022 National Research University Higher School of Economics.)

Published
2022
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42. Kaiso Regulates DNA Methylation Homeostasis.

Author

Kaplun D, Starshin A, Sharko F, Gainova K, Filonova G, Zhigalova N, Mazur A, Prokhortchouk E, and Zhenilo S

Subjects
DNA (Cytosine-5-)-Methyltransferases genetics, DNA (Cytosine-5-)-Methyltransferases metabolism, Fibroblasts metabolism, Fibroblasts pathology, Gene Editing, HEK293 Cells, Humans, Insulin-Like Growth Factor II genetics, Promoter Regions, Genetic, Transcription Factors antagonists & inhibitors, Transcription Factors genetics, Tripartite Motif Proteins genetics, Tripartite Motif Proteins metabolism, Ubiquitin-Protein Ligases genetics, Ubiquitin-Protein Ligases metabolism, DNA Methyltransferase 3B, DNA Methylation, Genomic Imprinting, Insulin-Like Growth Factor II metabolism, Locus Control Region, RNA, Long Noncoding genetics, Transcription Factors metabolism
Abstract

Gain and loss of DNA methylation in cells is a dynamic process that tends to achieve an equilibrium. Many factors are involved in maintaining the balance between DNA methylation and demethylation. Previously, it was shown that methyl-DNA protein Kaiso may attract NCoR, SMRT repressive complexes affecting histone modifications. On the other hand, the deficiency of Kaiso resulted in reduced methylation of ICR in H19/Igf2 locus and Oct4 promoter in mouse embryonic fibroblasts. However, nothing is known about how Kaiso influences DNA methylation at the genome level. Here we show that deficiency of Kaiso led to whole-genome hypermethylation, using Kaiso deficient human renal cancer cell line obtained via CRISPR/CAS9 genome editing. However, Kaiso serves to protect genic regions, enhancers, and regions with a low level of histone modifications from demethylation. We detected hypomethylation of binding sites for Oct4 and Nanog in Kaiso deficient cells. Kaiso immunoprecipitated with de novo DNA methyltransferases DNMT3a/3b, but not with maintenance methyltransferase DNMT1. Thus, Kaiso may attract methyltransferases to surrounding regions and modulate genome methylation in renal cancer cells apart from being methyl DNA binding protein.

Published
2021
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44. Isolation and phylogenetic analysis of SARS-CoV-2 variants collected in Russia during the COVID-19 outbreak.

Author

Kozlovskaya L, Piniaeva A, Ignatyev G, Selivanov A, Shishova A, Kovpak A, Gordeychuk I, Ivin Y, Berestovskaya A, Prokhortchouk E, Protsenko D, Rychev M, and Ishmukhametov A

Subjects
COVID-19, Disease Outbreaks, Genome, Viral, Humans, Pandemics, Phylogeny, Russia epidemiology, SARS-CoV-2, Betacoronavirus genetics, Coronavirus Infections epidemiology, Coronavirus Infections virology, Pneumonia, Viral epidemiology, Pneumonia, Viral virology
Abstract

Objectives: The outbreak of coronavirus disease 2019 (COVID-19) started in December 2019 in China and then spread worldwide over the following months, involving 188 countries. The objective of this study was to determine the molecular epidemiology of the COVID-19 outbreak in Russia., Methods: In this study, two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains were isolated and genetically characterized. A phylogenetic analysis of all available Russian sequences was then performed and these were compared to the epidemiological data on COVID-19 incidence to evaluate the molecular epidemiology and pattern of virus spread in the territory of Russia., Results and Conclusions: Whole genome analysis of the isolates obtained in this study and 216 others isolated in Russia revealed a set of seven common mutations when compared to the original Wuhan virus, including amino acid substitutions in spike protein S and nucleoprotein N, possibly affecting their properties. Phylogenetic analysis of all Russian sequences and 8717 sequences from other countries showed multiple importations of the virus into Russia, local circulation, and several patterns of virus spread., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Published
2020
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45. Sex specific associations in genome wide association analysis of renal cell carcinoma.

Author

Laskar RS, Muller DC, Li P, Machiela MJ, Ye Y, Gaborieau V, Foll M, Hofmann JN, Colli L, Sampson JN, Wang Z, Bacq-Daian D, Boland A, Abedi-Ardekani B, Durand G, Le Calvez-Kelm F, Robinot N, Blanche H, Prokhortchouk E, Skryabin KG, Burdett L, Yeager M, Radojevic-Skodric S, Savic S, Foretova L, Holcatova I, Janout V, Mates D, Rascu S, Mukeria A, Zaridze D, Bencko V, Cybulski C, Fabianova E, Jinga V, Lissowska J, Lubinski J, Navratilova M, Rudnai P, Świątkowska B, Benhamou S, Cancel-Tassin G, Cussenot O, Trichopoulou A, Riboli E, Overvad K, Panico S, Ljungberg B, Sitaram RT, Giles GG, Milne RL, Severi G, Bruinsma F, Fletcher T, Koppova K, Larsson SC, Wolk A, Banks RE, Selby PJ, Easton DF, Pharoah P, Andreotti G, Beane Freeman LE, Koutros S, Albanes D, Männistö S, Weinstein S, Clark PE, Edwards TL, Lipworth L, Carol H, Freedman ML, Pomerantz MM, Cho E, Kraft P, Preston MA, Wilson KM, Michael Gaziano J, Sesso HD, Black A, Freedman ND, Huang WY, Anema JG, Kahnoski RJ, Lane BR, Noyes SL, Petillo D, Teh BT, Peters U, White E, Anderson GL, Johnson L, Luo J, Chow WH, Moore LE, Choueiri TK, Wood C, Johansson M, McKay JD, Brown KM, Rothman N, Lathrop MG, Deleuze JF, Wu X, Brennan P, Chanock SJ, Purdue MP, and Scelo G

Subjects
Computational Biology, Female, Humans, Male, Odds Ratio, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Factors, Carcinoma, Renal Cell epidemiology, Carcinoma, Renal Cell genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Kidney Neoplasms epidemiology, Kidney Neoplasms genetics
Abstract

Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (OR male ) = 0.83 [95% CI = 0.78-0.89], P male  = 1.71 × 10 -8 compared with female odds ratio (OR female ) = 0.98 [95% CI = 0.90-1.07], P female  = 0.68) and 12q23.3 (intergenic, OR male  = 0.75 [95% CI = 0.68-0.83], P male  = 1.59 × 10 -8 compared with OR female  = 0.93 [95% CI = 0.82-1.06], P female  = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.

Published
2019
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46. Kaiso is required for MTG16-dependent effects on colitis-associated carcinoma.

Author

Short SP, Barrett CW, Stengel KR, Revetta FL, Choksi YA, Coburn LA, Lintel MK, McDonough EM, Washington MK, Wilson KT, Prokhortchouk E, Chen X, Hiebert SW, Reynolds AB, and Williams CS

Subjects
Adenocarcinoma pathology, Animals, Carcinogenesis metabolism, Carcinogenesis pathology, Colitis pathology, Colonic Neoplasms pathology, Female, HCT116 Cells, HEK293 Cells, Humans, Inflammation complications, Inflammation genetics, Inflammation metabolism, Inflammation pathology, Intestinal Mucosa metabolism, Intestinal Mucosa pathology, Male, Mice, Mice, Inbred C57BL, Mice, Knockout, Transcription Factors genetics, Adenocarcinoma genetics, Carcinogenesis genetics, Colitis complications, Colitis genetics, Colonic Neoplasms genetics, Repressor Proteins genetics, Transcription Factors physiology
Abstract

The myeloid translocation gene family member MTG16 is a transcriptional corepressor that relies on the DNA-binding ability of other proteins to determine specificity. One such protein is the ZBTB family member Kaiso, and the MTG16:Kaiso interaction is necessary for repression of Kaiso target genes, such as matrix metalloproteinase-7. Using the azoxymethane and dextran sodium sulfate (AOM/DSS) murine model of colitis-associated carcinoma, we previously determined that MTG16 loss accelerates tumorigenesis and inflammation. However, it was unknown whether this effect was modified by Kaiso-dependent transcriptional repression. To test for a genetic interaction between MTG16 and Kaiso in inflammatory carcinogenesis, we subjected single and double knockout (DKO) mice to the AOM/DSS protocol. Mtg16 -/- mice demonstrated increased colitis and tumor burden; in contrast, disease severity in Kaiso -/- mice was equivalent to wild-type controls. Surprisingly, Kaiso deficiency in the context of MTG16 loss reversed injury and pro-tumorigenic responses in the intestinal epithelium following AOM/DSS treatment, and tumor numbers were returned to near to wild-type levels. Transcriptomic analysis of non-tumor colon tissue demonstrated that changes induced by MTG16 loss were widely mitigated by concurrent Kaiso loss, and DKO mice demonstrated downregulation of metabolism and cytokine-associated gene sets with concurrent activation of DNA damage checkpoint pathways as compared with Mtg16 -/- . Further, Kaiso knockdown in intestinal enteroids reduced stem- and WNT-associated phenotypes, thus abrogating the induction of these pathways observed in Mtg16 -/- samples. Together, these data suggest that Kaiso modifies MTG16-driven inflammation and tumorigenesis and suggests that Kaiso deregulation contributes to MTG16-dependent colitis and CAC phenotypes.

Published
2019
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48. Kaiso Gene Knockout Promotes Somatic Cell Reprogramming.

Author

Kaplun DS, Fok RE, Korostina VS, Prokhortchouk EB, and Zhenilo SV

Subjects
Animals, Mice, Mice, Inbred C57BL, Mice, Knockout, Transcription Factors metabolism, Cellular Reprogramming, Gene Knockout Techniques, Induced Pluripotent Stem Cells cytology, Induced Pluripotent Stem Cells metabolism, Transcription Factors deficiency, Transcription Factors genetics
Abstract

Reprogramming of somatic cells is associated with overcoming the established epigenetic barrier. Key events in this process are changes in the DNA methylation landscape and histone modifications. Studying the factors affecting epigenetic plasticity will allow not only to reveal the principles underlying cell reprogramming but also to find possible ways to influence this process. Kaiso transcription factor is one of the protein interpreters of methylated DNA. By binding to methylated DNA, Kaiso attracts corepressor complexes affecting chromatin structure. In this work, we showed that the Kaiso gene knockout contributes to more efficient somatic reprogramming by affecting both cell proliferation and DNA methylation. The proposed mechanisms for the increase in the efficiency of somatic reprogramming associated with the Kaiso gene knockout is a decrease in the methylation level of the Oct4 promoter region in mouse embryonic fibroblasts before reprogramming.

Published
2019
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49. The influence of obesity-related factors in the etiology of renal cell carcinoma-A mendelian randomization study.

Author

Johansson M, Carreras-Torres R, Scelo G, Purdue MP, Mariosa D, Muller DC, Timpson NJ, Haycock PC, Brown KM, Wang Z, Ye Y, Hofmann JN, Foll M, Gaborieau V, Machiela MJ, Colli LM, Li P, Garnier JG, Blanche H, Boland A, Burdette L, Prokhortchouk E, Skryabin KG, Yeager M, Radojevic-Skodric S, Ognjanovic S, Foretova L, Holcatova I, Janout V, Mates D, Mukeriya A, Rascu S, Zaridze D, Bencko V, Cybulski C, Fabianova E, Jinga V, Lissowska J, Lubinski J, Navratilova M, Rudnai P, Benhamou S, Cancel-Tassin G, Cussenot O, Weiderpass E, Ljungberg B, Tumkur Sitaram R, Häggström C, Bruinsma F, Jordan SJ, Severi G, Winship I, Hveem K, Vatten LJ, Fletcher T, Larsson SC, Wolk A, Banks RE, Selby PJ, Easton DF, Andreotti G, Beane Freeman LE, Koutros S, Männistö S, Weinstein S, Clark PE, Edwards TL, Lipworth L, Gapstur SM, Stevens VL, Carol H, Freedman ML, Pomerantz MM, Cho E, Wilson KM, Gaziano JM, Sesso HD, Freedman ND, Parker AS, Eckel-Passow JE, Huang WY, Kahnoski RJ, Lane BR, Noyes SL, Petillo D, Teh BT, Peters U, White E, Anderson GL, Johnson L, Luo J, Buring J, Lee IM, Chow WH, Moore LE, Eisen T, Henrion M, Larkin J, Barman P, Leibovich BC, Choueiri TK, Lathrop GM, Deleuze JF, Gunter M, McKay JD, Wu X, Houlston RS, Chanock SJ, Relton C, Richards JB, Martin RM, Davey Smith G, and Brennan P

Subjects
Blood Glucose analysis, Blood Pressure, Body Mass Index, Carcinoma, Renal Cell genetics, Diabetes Mellitus, Type 2 complications, Female, Genetic Markers, Genome-Wide Association Study, Humans, Insulin blood, Kidney Neoplasms genetics, Lipids blood, Male, Mendelian Randomization Analysis, Obesity genetics, Risk Factors, Carcinoma, Renal Cell etiology, Kidney Neoplasms etiology, Obesity complications
Abstract

Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation., Methods and Findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose., Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: TE declared employment, research support, and stock in AstraZeneca and research support from Bayer and Pfizer. PCH is a population health fellow of Cancer Research UK. GDS is a member of the Editorial Board of PLOS Medicine.

Published
2019
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50. DeSUMOylation switches Kaiso from activator to repressor upon hyperosmotic stress.

Author

Zhenilo S, Deyev I, Litvinova E, Zhigalova N, Kaplun D, Sokolov A, Mazur A, and Prokhortchouk E

Subjects
Animals, Apoptosis drug effects, Blood Pressure drug effects, CRISPR-Cas Systems genetics, Cell Line, HEK293 Cells, Humans, Hypertension pathology, Mice, Mice, Inbred C57BL, Mice, Knockout, Mutagenesis, Site-Directed, RNA Interference, RNA, Small Interfering metabolism, Sodium Chloride pharmacology, Sumoylation drug effects, Transcription Factors antagonists & inhibitors, Transcription Factors genetics, Transcription, Genetic, Tripartite Motif Proteins genetics, Tripartite Motif Proteins metabolism, Ubiquitin-Protein Ligases genetics, Ubiquitin-Protein Ligases metabolism, Osmotic Pressure, Transcription Factors metabolism
Abstract

Kaiso is a member of the BTB/POZ zinc finger family, which is involved in cancer progression, cell cycle control, apoptosis, and WNT signaling. Depending on promoter context, it may function as either a transcriptional repressor or activator. Previous studies found that Kaiso might be SUMOylated due to heat shock, but the biological significance of Kaiso SUMOylation is unclear. Here, we find that K42 is the only amino acid within Kaiso that is modified with SUMO. Kaiso is monoSUMOylated at lysine 42 in cell lines of kidney origin under normal physiological conditions. SUMOylated Kaiso can activate transcription from exogenous methylated promoters, wherein the deSUMOylated form of the protein kept the ability to be a repressor. Rapid Kaiso deSUMOylation occurs in response to hyperosmotic stress and is reversible upon return to an isotonic environment. DeSUMOylation occurs within minutes in HEK293 cells treated with 100 mM NaCl and relaxes in 3 h even in a salt-containing medium. Genomic editing of Kaiso by conversion of K42 into R42 (K42R) in HEK293 cells that resulted in fully deSUMOylated endogenous protein led to misregulation of genes associated with ion transport, blood pressure, and the immune response. TRIM25 was significantly repressed in two K42R HEK293 clones. By a series of rescue experiments with K42R and KO HEK293 cells, we show that TRIM25 is a direct transcriptional target for Kaiso. In the absence of Kaiso, the level of TRIM25 is insensitive to hyperosmotic stress. Extending our observations to animal models, we show that in response to a high salt diet, Kaiso knockout mice are characterized by significantly higher blood pressure increases when compared to wild-type animals. Thus, we propose a novel biological role for Kaiso in the regulation of homeostasis.

Published
2018
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