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3. The ecoresponsive genome of Daphnia pulex

Author

Colbourne, J. K., Pfrender, M. E., Gilbert, D., Thomas, W. K., Tucker, A., Oakley, T. H., Tokishita, S., Aerts, A., Arnold, G. J., Basu, M. K., Bauer, D. J., C當eres, C. E., Carmel, L., Casola, C., Choi, J. H., Detter, J. C., Dong, Q., Dusheyko, S., Eads, B. D., Frlich, T., Geiler-Samerotte, K. A., Gerlach, D., Hatcher, P., Jogdeo, S., Krijgsveld, J., Kriventseva, E. V., K�ltz, D., Laforsch, C., Lindquist, E., Lopez, J., Manak, J. R., Muller, J., Pangilinan, J., Patwardhan, R. P., Pitluck, S., Pritham, E. J., Rechtsteiner, A., Rho, M., Rogozin, I. B., Sakarya, O., Salamov, A., Schaack, S., Shapiro, H., Shiga, Y., Skalitzky, C., Smith, Z., Souvorov, A., Sung, W., Tang, Z., Tsuchiya, D., Tu, H., Vos, H., Wang, M., Wolf, Y. I., Yamagata, H., Yamada, Takuji, Ye, Y., Shaw, J. R., Andrews, J., Crease, T. J., Tang, H., Lucas, S. M., Robertson, H. M., Bork, P., Koonin, E. V., Zdobnov, E. M., Grigoriev, I. V., Lynch, M., Boore, J. L., Gerlach, Daniel, Kriventseva, Evgenia, and Zdobnov, Evgeny

Subjects
0106 biological sciences, Molecular Sequence Data, Gene Conversion, Gene Expression, Biology, Environment, 010603 evolutionary biology, 01 natural sciences, Genome, Daphnia pulex, Evolution, Molecular, 03 medical and health sciences, Genes, Duplicate, Gene Duplication, Gene duplication, Gene family, Animals, ddc:576.5, Gene conversion, Amino Acid Sequence, Gene, Ecosystem, Phylogeny, 030304 developmental biology, Regulation of gene expression, Genetics, 0303 health sciences, Multidisciplinary, Base Sequence, Daphnia/genetics/physiology, Metabolic Networks and Pathways/genetics, Gene Expression Profiling, fungi, Chromosome Mapping, Molecular Sequence Annotation, Sequence Analysis, DNA, biology.organism_classification, Adaptation, Physiological, Gene expression profiling, Daphnia, Gene Expression Regulation, Genes, Multigene Family, Metabolic Networks and Pathways
Abstract

We describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 megabases and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than a third of Daphnia's genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The coexpansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes, including many additional loci within sequenced regions that are otherwise devoid of annotations, are the most responsive genes to ecological challenges.

Published
2011
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4. The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

Author

Bultet, LA, Aguilar-Rodriguez, J, Ahrens, CH, Ahrne, EL, Ai, N, Aimo, L, Akalin, A, Aleksiev, T, Alocci, D, Altenhoff, A, Alves, I, Ambrosini, G, Pedone, PA, Angelina, P, Anisimova, M, Appel, R, Argoud-Puy, G, Arnold, K, Arpat, B, Artimo, P, Ascencao, K, Auchincloss, A, Axelsen, K, Gerritsen, VB, Bairoch, A, Barisal, P, Baratin, D, Barbato, A, Barbie, V, Barras, D, Barreiro, M, Barret, S, Bastian, F, Batista Neto, TM, Baudis, M, Beaudoing, E, Beckmann, JS, Bekkar, AK, Cammoun, LBH, Benmohammed, S, Bernard, M, Bertelli, C, Bertoni, M, Bienert, S, Bignucolo, O, Bilbao, A, Bilican, A, Blank, D, Blatter, M-C, Blum, L, Bocquet, J, Boeckmann, B, Bolleman, JT, Bordoli, L, Bosshard, L, Boucher, G, Bougueleret, L, Boutet, E, Bovigny, C, Bratulic, S, Breuza, L, Bridge, AJ, Britan, A, Brito, F, Frazao, JB, Bruggmann, R, Bucher, P, Burdet, F, Burger, L, Cabello, EM, Gomez, RMC, Calderon, S, Cannarozzi, G, Carl, S, Casas, CC, Catherinet, S, Perier, RC, Charpilloz, C, Chaskar, PD, Chen, W, Pepe, AC, Chopard, B, Chu, HY, Civic, N, Claassen, M, Clottu, S, Colombo, M, Cosandier, I, Coudert, E, Crespo, I, Creus, M, Cuche, B, Cuendet, MA, Cusin, I, Daga, N, Daina, A, Dauvillier, J, David, F, Davydov, I, Ferreira, MDSRM, de Beer, T, de Castro, E, de Santana, C, Delafontaine, J, Delorenzi, M, Delucinge-Vivier, C, Demirel, O, Derham, R, Dermitzakis, EM, Dib, L, Diene, S, Dilek, N, Dilmi, J, Domagalski, MJ, Dorier, J, Dornevil, D, Dousse, A, Dreos, R, Duchen, P, Roggli, PD, Duperret, ID, Durinx, C, Duvaud, S, Engler, R, Frkek, S, Lopez, PE, Fstreicher, A, Excoffier, L, Fabbretti, R, Falcone, J-L, Falquet, L, Famiglietti, ML, Ferreira, A-M, Feuermann, M, Filliettaz, M, Hegel, V, Foucal, A, Franceschini, A, Fucile, G, Gaidatzis, D, Garcia, V, Gasteiger, E, Gateau, A, Gatti, L, Gaudet, P, Gaudinat, A, Gehant, S, Gfeller, D, Gharib, WH, Ghraichy, M, Gidoin, C, Gil, M, Gleizes, A, Gobeill, J, Gonnet, G, Gos, A, Gotz, L, Gouy, A, Grbic, D, Groux, R, Gruaz-Gumowski, N, Grun, D, Gschwind, A, Guex, N, Gupta, S, Getaz, M, Haake, D, Haas, J, Hatzimanikatis, V, Heckel, G, Gardiol, DFH, Hinard, V, Hinz, U, Homicsko, K, Horlacher, O, Hosseini, S-R, Hotz, H-R, Hulo, C, Hundsrucker, C, Ibberson, M, Ilmjarv, S, Ioannidis, V, Ioannidis, P, Iseli, C, Ivanek, R, Iwaszkiewicz, J, Jacquet, P, Jacquot, M, Jagannathan, V, Jan, M, Jensen, J, Johansson, MU, Johner, N, Jungo, F, Junier, T, Kahraman, A, Katsantoni, M, Keller, G, Kerhornou, A, Khalid, F, Klingbiel, D, Kimljenovic, A, Kriventseva, E, Kryuchkova, N, Kumar, S, Kutalik, Z, Kuznetsov, D, Kuzyakiv, R, Lane, L, Lara, V, Ledesma, L, Leleu, M, Lemercier, P, Lew, D, Lieberherr, D, Liechti, R, Lisacek, F, Fischer, H, Litsios, G, Liu, J, Lombardot, T, Mace, A, Maffioletti, S, Mahi, M-A, Maiolo, M, Majjigapu, SR, Malmstrom, L, Mangold, V, Marek, D, Mariethoz, J, Marin, R, Martin, O, Martin, X, Martin-Campos, T, Mary, C, Masclaux, F, Masson, P, Meier, C, Messina, A, Lenoir, MM, Meyer, X, Michel, P-A, Michielin, O, Milanese, A, Missiaglia, E, Perez, JM, Caria, VM, Moret, P, Moretti, S, Morgat, A, Mottaz, A, Mottin, L, Mouscaz, Y, Mueller, M, Murri, R, Mylonas, R, Neuenschwander, S, Nikitin, F, Niknejad, A, Nouspikel, N, Nso, LN, Okoniewski, M, Omasits, U, Paccaud, B, Pachkov, M, Paesano, SG, Pagni, M, Palagi, PM, Pasche, E, Payne, JL, Pedruzzi, I, Peischl, S, Peitsch, M, Perlini, S, Pilbout, S, Podvinec, M, Pohlmann, R, Polizzi, D, Potter, D, Poux, S, Pozzato, M, Pradervand, S, Praz, V, Pruess, M, Pujadas, E, Racle, J, Raschi, M, Ratib, O, Rausell, A, de Laval, VR, Redaschi, N, Rempfer, C, Ren, G, Vandati, RAR, Rib, L, Grognuz, OR, Altimiras, ER, Rivoire, C, Robin, T, Robinson-Rechavi, M, Rodrigues, J, Roechert, B, Roelli, P, Romano, V, Rossier, G, Roth, A, Rougemont, J, Roux, J, Royo, H, Ruch, P, Ruinelli, M, Rustom, M, Sates, A, Roehrig, UF, Rueeger, S, Salamin, N, Sankar, M, Sarkar, N, Saxenhofer, M, Schaeffer, M, Schaerli, Y, Schaper, E, Schmid, A, Schmid, E, Schmid, C, Schmid, M, Schmidt, S, Schmocker, D, Schneider, M, Schuepbach, T, Schwede, T, Schuetz, F, Sengstag, T, Serrano, M, Sethi, A, Shahmirzadi, O, Sigrist, C, Silvestro, D, Simao Neto, FA, Simillion, C, Simonovic, M, Skunca, N, Sluzek, K, Soneson, C, Sprouffske, K, Stadler, M, Staehli, S, Stevenson, B, Stockinger, H, Straszewski, J, Stricker, T, Studer, G, Stutz, A, Suffiotti, M, Sundaram, S, Szklarczyk, D, Szovenyi, P, Tegenfeldt, F, Teixeira, D, Tellenbach, S, Smith, AAT, Tognolli, M, Topolsky, I, Thuong, VDT, Tsantoulis, P, Tzika, AC, Agote, AU, van Nimwegen, E, von Mering, C, Varadarajan, A, Veranneman, M, Verbregue, L, Veuthey, A-L, Vishnyakova, D, Vyas, R, Wagner, A, Walther, D, Wan, HW, Wang, M, Waterhouse, R, Waterhouse, A, Wicki, A, Wigger, L, Wirapati, P, Witschi, U, Wyder, S, Wyler, K, Wuethrich, D, Xenarios, I, Yamada, K, Yan, Z, Yasrebi, H, Zahn, M, Zangger, N, Zdobnov, E, Zerzion, D, Zoete, V, Zoller, S, Bultet, LA, Aguilar-Rodriguez, J, Ahrens, CH, Ahrne, EL, Ai, N, Aimo, L, Akalin, A, Aleksiev, T, Alocci, D, Altenhoff, A, Alves, I, Ambrosini, G, Pedone, PA, Angelina, P, Anisimova, M, Appel, R, Argoud-Puy, G, Arnold, K, Arpat, B, Artimo, P, Ascencao, K, Auchincloss, A, Axelsen, K, Gerritsen, VB, Bairoch, A, Barisal, P, Baratin, D, Barbato, A, Barbie, V, Barras, D, Barreiro, M, Barret, S, Bastian, F, Batista Neto, TM, Baudis, M, Beaudoing, E, Beckmann, JS, Bekkar, AK, Cammoun, LBH, Benmohammed, S, Bernard, M, Bertelli, C, Bertoni, M, Bienert, S, Bignucolo, O, Bilbao, A, Bilican, A, Blank, D, Blatter, M-C, Blum, L, Bocquet, J, Boeckmann, B, Bolleman, JT, Bordoli, L, Bosshard, L, Boucher, G, Bougueleret, L, Boutet, E, Bovigny, C, Bratulic, S, Breuza, L, Bridge, AJ, Britan, A, Brito, F, Frazao, JB, Bruggmann, R, Bucher, P, Burdet, F, Burger, L, Cabello, EM, Gomez, RMC, Calderon, S, Cannarozzi, G, Carl, S, Casas, CC, Catherinet, S, Perier, RC, Charpilloz, C, Chaskar, PD, Chen, W, Pepe, AC, Chopard, B, Chu, HY, Civic, N, Claassen, M, Clottu, S, Colombo, M, Cosandier, I, Coudert, E, Crespo, I, Creus, M, Cuche, B, Cuendet, MA, Cusin, I, Daga, N, Daina, A, Dauvillier, J, David, F, Davydov, I, Ferreira, MDSRM, de Beer, T, de Castro, E, de Santana, C, Delafontaine, J, Delorenzi, M, Delucinge-Vivier, C, Demirel, O, Derham, R, Dermitzakis, EM, Dib, L, Diene, S, Dilek, N, Dilmi, J, Domagalski, MJ, Dorier, J, Dornevil, D, Dousse, A, Dreos, R, Duchen, P, Roggli, PD, Duperret, ID, Durinx, C, Duvaud, S, Engler, R, Frkek, S, Lopez, PE, Fstreicher, A, Excoffier, L, Fabbretti, R, Falcone, J-L, Falquet, L, Famiglietti, ML, Ferreira, A-M, Feuermann, M, Filliettaz, M, Hegel, V, Foucal, A, Franceschini, A, Fucile, G, Gaidatzis, D, Garcia, V, Gasteiger, E, Gateau, A, Gatti, L, Gaudet, P, Gaudinat, A, Gehant, S, Gfeller, D, Gharib, WH, Ghraichy, M, Gidoin, C, Gil, M, Gleizes, A, Gobeill, J, Gonnet, G, Gos, A, Gotz, L, Gouy, A, Grbic, D, Groux, R, Gruaz-Gumowski, N, Grun, D, Gschwind, A, Guex, N, Gupta, S, Getaz, M, Haake, D, Haas, J, Hatzimanikatis, V, Heckel, G, Gardiol, DFH, Hinard, V, Hinz, U, Homicsko, K, Horlacher, O, Hosseini, S-R, Hotz, H-R, Hulo, C, Hundsrucker, C, Ibberson, M, Ilmjarv, S, Ioannidis, V, Ioannidis, P, Iseli, C, Ivanek, R, Iwaszkiewicz, J, Jacquet, P, Jacquot, M, Jagannathan, V, Jan, M, Jensen, J, Johansson, MU, Johner, N, Jungo, F, Junier, T, Kahraman, A, Katsantoni, M, Keller, G, Kerhornou, A, Khalid, F, Klingbiel, D, Kimljenovic, A, Kriventseva, E, Kryuchkova, N, Kumar, S, Kutalik, Z, Kuznetsov, D, Kuzyakiv, R, Lane, L, Lara, V, Ledesma, L, Leleu, M, Lemercier, P, Lew, D, Lieberherr, D, Liechti, R, Lisacek, F, Fischer, H, Litsios, G, Liu, J, Lombardot, T, Mace, A, Maffioletti, S, Mahi, M-A, Maiolo, M, Majjigapu, SR, Malmstrom, L, Mangold, V, Marek, D, Mariethoz, J, Marin, R, Martin, O, Martin, X, Martin-Campos, T, Mary, C, Masclaux, F, Masson, P, Meier, C, Messina, A, Lenoir, MM, Meyer, X, Michel, P-A, Michielin, O, Milanese, A, Missiaglia, E, Perez, JM, Caria, VM, Moret, P, Moretti, S, Morgat, A, Mottaz, A, Mottin, L, Mouscaz, Y, Mueller, M, Murri, R, Mylonas, R, Neuenschwander, S, Nikitin, F, Niknejad, A, Nouspikel, N, Nso, LN, Okoniewski, M, Omasits, U, Paccaud, B, Pachkov, M, Paesano, SG, Pagni, M, Palagi, PM, Pasche, E, Payne, JL, Pedruzzi, I, Peischl, S, Peitsch, M, Perlini, S, Pilbout, S, Podvinec, M, Pohlmann, R, Polizzi, D, Potter, D, Poux, S, Pozzato, M, Pradervand, S, Praz, V, Pruess, M, Pujadas, E, Racle, J, Raschi, M, Ratib, O, Rausell, A, de Laval, VR, Redaschi, N, Rempfer, C, Ren, G, Vandati, RAR, Rib, L, Grognuz, OR, Altimiras, ER, Rivoire, C, Robin, T, Robinson-Rechavi, M, Rodrigues, J, Roechert, B, Roelli, P, Romano, V, Rossier, G, Roth, A, Rougemont, J, Roux, J, Royo, H, Ruch, P, Ruinelli, M, Rustom, M, Sates, A, Roehrig, UF, Rueeger, S, Salamin, N, Sankar, M, Sarkar, N, Saxenhofer, M, Schaeffer, M, Schaerli, Y, Schaper, E, Schmid, A, Schmid, E, Schmid, C, Schmid, M, Schmidt, S, Schmocker, D, Schneider, M, Schuepbach, T, Schwede, T, Schuetz, F, Sengstag, T, Serrano, M, Sethi, A, Shahmirzadi, O, Sigrist, C, Silvestro, D, Simao Neto, FA, Simillion, C, Simonovic, M, Skunca, N, Sluzek, K, Soneson, C, Sprouffske, K, Stadler, M, Staehli, S, Stevenson, B, Stockinger, H, Straszewski, J, Stricker, T, Studer, G, Stutz, A, Suffiotti, M, Sundaram, S, Szklarczyk, D, Szovenyi, P, Tegenfeldt, F, Teixeira, D, Tellenbach, S, Smith, AAT, Tognolli, M, Topolsky, I, Thuong, VDT, Tsantoulis, P, Tzika, AC, Agote, AU, van Nimwegen, E, von Mering, C, Varadarajan, A, Veranneman, M, Verbregue, L, Veuthey, A-L, Vishnyakova, D, Vyas, R, Wagner, A, Walther, D, Wan, HW, Wang, M, Waterhouse, R, Waterhouse, A, Wicki, A, Wigger, L, Wirapati, P, Witschi, U, Wyder, S, Wyler, K, Wuethrich, D, Xenarios, I, Yamada, K, Yan, Z, Yasrebi, H, Zahn, M, Zangger, N, Zdobnov, E, Zerzion, D, Zoete, V, and Zoller, S

Abstract

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

Published
2016

5. Toward community standards in the quest for orthologs

Author

Dessimoz, C, Gabaldon, T, Roos, D S, Sonnhammer, E L L, Herrero, J, Altenhoff, A, Apweiler, R, Ashburner, M, Blake, J, Boeckmann, B, Bridge, A, Bruford, E, Cherry, M, Conte, M, Dannie, D, Datta, R, Domelevo Entfellner, J-B, Ebersberger, I, Galperin, M, Joseph, J, Koestler, T, Kriventseva, E, Lecompte, O, Leunissen, J, Lewis, S, Linard, B, Livstone, M S, et al, University of Zurich, and Dessimoz, C

Subjects
1303 Biochemistry, 1312 Molecular Biology, 1706 Computer Science Applications, 2613 Statistics and Probability, 142-005 142-005, 2605 Computational Mathematics, 1703 Computational Theory and Mathematics
Published
2012
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6. Functional and evolutionary insights from the genomes of three parasitoid Nasonia species

Author

Werren, J. H., Richards, S., Desjardins, C. A., Niehuis, O., Gadau, J., Colbourne, J. K., Beukeboom, L. W., Desplan, C., Elsik, C. G., Grimmelikhuijzen, C. J., Kitts, P., Lynch, J. A., Murphy, T., Oliveira, D. C., Smith, C. D., van de Zande, L., Worley, K. C., Zdobnov, E. M., Aerts, M., Albert, S., Anaya, V. H., Anzola, J. M., Barchuk, A. R., Behura, S. K., Bera, A. N., Berenbaum, M. R., Bertossa, R. C., Bitondi, M. M., Bordenstein, S. R., Bork, P., Bornberg-Bauer, E., Brunain, M., Cazzamali, G., Chaboub, L., Chacko, J., Chavez, D., Childers, C. P., Choi, J. H., Clark, M. E., Claudianos, C., Clinton, R. A., Cree, A. G., Cristino, A. S., Dang, P. M., Darby, A. C., de Graaf, D. C., Devreese, B., Dinh, H. H., Edwards, R., Elango, N., Elhaik, E., Ermolaeva, O., Evans, J. D., Foret, S., Fowler, G. R., Gerlach, D., Gibson, J. D., Gilbert, D. G., Graur, D., Gr�nder, S., Hagen, D. E., Han, Y., Hauser, F., Hultmark, D., Hunter, H. C., Hurst, G. D., Jhangian, S. N., Jiang, H., Johnson, R. M., Jones, A. K., Junier, T., Kadowaki, T., Kamping, A., Kapustin, Y., Kechavarzi, B., Kim, J., Kiryutin, B., Koevoets, T., Kovar, C. L., Kriventseva, E. V., Kucharski, R., Lee, H., Lee, S. L., Lees, K., Lewis, L. R., Loehlin, D. W., Logsdon, J. M., Lopez, J. A., Lozado, R. J., Maglott, D., Maleszka, R., Mayampurath, A., Mazur, D. J., McClure, M. A., Moore, A. D., Morgan, M. B., Muller, J., Munoz-Torres, M. C., Muzny, D. M., Nazareth, L. V., Neupert, S., Nguyen, N. B., Nunes, F. M., Oakeshott, J. G., Okwuonu, G. O., Pannebakker, B. A., Pejaver, V. R., Peng, Z., Pratt, S. C., Predel, R., Pu, L. L., Ranson, H., Raychoudhury, R., Rechtsteiner, A., Reese, J. T., Reid, J. G., Riddle, M., Robertson, H. M., Romero-Severson, J., Rosenberg, M., Sackton, T. B., Sattelle, D. B., Schl�ns, H., Schmitt, T., Schneider, M., Sch�ler, A., Schurko, A. M., Shuker, D. M., Sims, Z. L., Sinha, S., Smith, Z., Solovyev, V., Souvorov, A., Springauf, A., Stafflinger, E., Stage, D. E., Stanke, M., Tanaka, Y., Telschow, A., Trent, C., Vattathil, S., Verhulst, E. C., Viljakainen, L., Wanner, K. W., Waterhouse, R. M., Whitfield, J. B., Wilkes, T. E., Williamson, M., Willis, J. H., Wolschin, F., Wyder, S., Yamada, Takuji, Yi, S. V., Zecher, C. N., Zhang, L., Gibbs, R. A., Group, Nasonia Genome Working, Zdobnov, Evgeny, Gerlach, Daniel, Junier, Thomas, Muller, Jean, Beukeboom lab, and Van de Zande lab

Subjects
0106 biological sciences, Male, Wasp Venoms/chemistry/toxicity, Insecta, Insect Viruses/genetics, PARASITOLOGIA, VITRIPENNIS, Wasps, Genome, Insect, HYMENOPTERA, Wasp Venoms, Genes, Insect, 01 natural sciences, Genome, Nasonia vitripennis, HONEYBEE, PTEROMALIDAE, Wasps/ genetics/physiology, Arthropods/parasitology, Pteromalidae, DNA METHYLATION, ddc:616, Recombination, Genetic, 0303 health sciences, Multidisciplinary, biology, Ecology, WASP NASONIA, Biological Evolution, 3. Good health, Insects, DROSOPHILA, APIS-MELLIFERA, Insect Proteins, Wolbachia, Female, Wolbachia/genetics, Nasonia, GENES, Gene Transfer, Horizontal, Evolution, Genetic Speciation, Molecular Sequence Data, Quantitative Trait Loci, Insect Viruses, Quantitative trait locus, 010603 evolutionary biology, Article, Host-Parasite Interactions, 03 medical and health sciences, Genetic model, Animals, Life Science, Arthropods, 030304 developmental biology, fungi, Genetic Variation, Sequence Analysis, DNA, DNA Methylation, biology.organism_classification, SOCIAL INSECTS, Insects/genetics, Evolutionary biology, DNA Transposable Elements, Insect Proteins/genetics/metabolism
Abstract

Parasitoid Wasp Genomes Parasitoid wasps, which prey on and reproduce in host insect species, play important roles in plant herbivore interactions, and may provide valuable tools in the biological control of pest species. The Nasonia Genome Working Group (p. 343 ; see the news story by Pennisi ) presents the genome of three very closely related species: Nasonia vitripennis, N. giraulti , and N. longicornis . The findings document rapid evolution between a host and endosymbiont that can cause nuclear-cytoplasmic incompatibilities that may affect speciation.

Published
2010

7. Genomic analysis of Drosophila chromosome underreplication reveals a link between replication control and transcriptional territories

Author

Belyakin, S., Christophides, G., Alekseyenko, A., Kriventseva, E., Belyaeva, E., Nanayev, R., Makunin, I., Hild, M., Beckmann, B., Haas, S., Koch, B., Solovyev, V., Busold, C., Fellenberg, K., Boutros, M., Vingron, M., Sauer, F., Hoheisel, J., Paro, R., and Heidelberg Fly Array Consortium

Subjects
DNA Replication, Male, Transcription, Genetic, Gene Dosage, Mitosis, Biology, Gene dosage, Genome, Chromosomes, Cell Line, Animals, Drosophila Proteins, Gene, Oligonucleotide Array Sequence Analysis, Regulation of gene expression, Genetics, Multidisciplinary, Polytene chromosome, Intercalary heterochromatin, Chromosome, Genomics, Biological Sciences, DNA-Binding Proteins, Gene Expression Regulation, Multigene Family, Mutation, Heterochromatin protein 1, Drosophila, Female
Abstract

In Drosophila polytene chromosomes, most late-replicating regions remain underreplicated. A loss-of-function mutant of the suppressor of underreplication [ Su(UR) ] gene suppresses underreplication (UR), whereas extra copies of this gene enhance the level and number of regions showing UR. By combining DNA microarray analysis with manipulation of the number of Su(UR) gene copies, we achieved genomic-scale molecular identification of 1,036 genes that are arranged in clusters located in 52 UR chromosomal regions. These regions overlap extensively (96%) but are not completely identical with late-replicating regions of mitotically dividing Kc cells in culture. Reanalysis of published gene expression profiles revealed that genomic regions defined by replication properties include clusters of coordinately expressed genes. Genomic regions that are UR in polytene chromosomes and late replicated in Kc cell chromosomes show a particularly common association with transcriptional territories that are expressed in testis/males but not ovary/females or embryos. An attractive hypothesis for future testing is that factors involved in replication control, such as SU(UR), may interact physically with those involved in epigenetic silencing of transcription territories.

Published
2005

13. Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes.

Author

Apweiler, R, Biswas, M, Fleischmann, W, Kanapin, A, Karavidopoulou, Y, Kersey, P, Kriventseva, E V, Mittard, V, Mulder, N, Phan, I, and Zdobnov, E

Abstract

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac. uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31-67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Published
2001
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15. Creating hierarchical models of protein families based on Expressed Sequence Tags: the "Sprockets" analysis pipeline.

Author

Gordon PM, Weinel C, Jacobi C, Kämpf U, Kriventseva E, and Sensen CW

Abstract

We have created an analysis pipeline called Sprockets, which can be used to classify proteins into various hierarchical "families", and build searchable models of these families. The construction of these families is based on data from Expressed Sequence Tags (ESTs) and Coding DNA Sequences (CDSs), making Sprockets clusters especially suitable for studying gene families in organisms for which the completely sequenced genome does not (yet) exist. The pipeline consists of two main parts: pair-wise analysis and grouping of sequences with Z-score statistics, followed by hierarchical splitting of clusters into alignable protein families. Various computational and statistical techniques applied in Sprockets allow it to act like a massive and selective multiple sequence alignment engine for combining individual sequence collections and related public sequences. The end result is a database of gene Hidden Markov Models, each related to the other by three levels of similarity: secondary structure, function and evolutionary origin. For a sample 20,000 EST set from Lactuca spp., Sprockets provided a 9% improvement in mapping of function to unknown sequences over traditional pair-wise search methods and InterPro mapping.

Published
2006
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16. The Proteome Analysis database: a tool for the in silico analysis of whole proteomes.

Author

Pruess M, Fleischmann W, Kanapin A, Karavidopoulou Y, Kersey P, Kriventseva E, Mittard V, Mulder N, Phan I, Servant F, and Apweiler R

Subjects
Animals, Archaeal Proteins chemistry, Bacterial Proteins chemistry, Data Interpretation, Statistical, Humans, Mice, Proteins chemistry, Proteins classification, Proteins physiology, Proteome physiology, Sequence Analysis, Protein, Sequence Homology, Amino Acid, Databases, Protein, Proteome chemistry
Abstract

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Published
2003
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17. Applications of InterPro in protein annotation and genome analysis.

Author

Biswas M, O'Rourke JF, Camon E, Fraser G, Kanapin A, Karavidopoulou Y, Kersey P, Kriventseva E, Mittard V, Mulder N, Phan I, Servant F, and Apweiler R

Subjects
Amino Acid Sequence, Genome, Human, Humans, Internet, Protein Conformation, Sequence Analysis, Protein, Software, Computational Biology, Databases, Protein, Genome, Proteins chemistry, Proteins classification, Proteins genetics, Proteins physiology, Proteome analysis
Abstract

The applications of InterPro span a range of biologically important areas that includes automatic annotation of protein sequences and genome analysis. In automatic annotation of protein sequences InterPro has been utilised to provide reliable characterisation of sequences, identifying them as candidates for functional annotation. Rules based on the InterPro characterisation are stored and operated through a database called RuleBase. RuleBase is used as the main tool in the sequence database group at the EBI to apply automatic annotation to unknown sequences. The annotated sequences are stored and distributed in the TrEMBL protein sequence database. InterPro also provides a means to carry out statistical and comparative analyses of whole genomes. In the Proteome Analysis Database, InterPro analyses have been combined with other analyses based on CluSTr, the Gene Ontology (GO) and structural information on the proteins.

Published
2002
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18. Theoretical analysis of alternative splice forms using computational methods.

Author

Boué S, Vingron M, Kriventseva E, and Koch I

Subjects
Algorithms, Computer Simulation, Expressed Sequence Tags, Humans, Models, Molecular, Protein Conformation, Transcription Factors metabolism, Alternative Splicing genetics, Exons genetics, Models, Genetic, Sequence Alignment methods, Sequence Analysis, Protein methods, Sequence Analysis, RNA methods, Transcription Factors chemistry, Transcription Factors genetics
Abstract

Nowadays understanding alternative splicing is one of the greatest challenges in biology, because it is a genetic process much more important than thought at the time of its discovery. In this paper, we explain the approach of using the different available databases and software tools to start a large scale investigation of alternative splice forms. To collect information about alternative splicing we investigated known data in the databases using different computational methods. The investigations proceeded from the genomic sequence data to structural protein data. Then, we interpreted those data to find the relationship between alternative splice forms and protein function and structure. We found some interesting features of alternative splicing which are presented here. We discuss the results of one chosen example. They concern the coverage quality of the protein sequence of a known structure, an EST analysis, the validation of splice variants, the determination of the alternative splice type, and finally the link between alternative splicing and disease.

Published
2002
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19. Clustering and analysis of protein families.

Author

Kriventseva EV, Biswas M, and Apweiler R

Subjects
Sequence Alignment methods, Amino Acid Motifs, Databases, Factual, Phylogeny, Proteins
Abstract

Various sequence-motif and sequence-cluster databases have been integrated into a new resource known as InterPro. Because the contributing databases have different clustering principles and scoring sensitivities, the combined assignments complement each other for grouping protein families and delineating domains. InterPro and new developments in the analysis of both the phylogenetic profiles of protein families and domain fusion events improve the prediction of specific functions for numerous proteins.

Published
2001
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20. [Statistical analysis of the exon-intron structure of higher eukaryote genes].

Author

Kriventseva EV, Makeev VIu, and Gel'fand MS

Subjects
Algorithms, Animals, Humans, RNA Splicing, Arabidopsis genetics, Drosophila genetics, Exons, Genome, Introns
Abstract

The exon-intron structure of human, insect (Drosophila sp.), and dicot plant (Arabidopsis thaliana) genes was considered. In each genome there exists a characteristic intron length. Anomalously long introns was usually the first introns in genes. In each sample there are correlations between the lengths of neighboring exons and between exon lengths and closeness to the consensus of the sites at exon boundaries. Exons and exon pairs containing an integer number of triplets are preferred. These results are relevant to the study of splicing mechanism and evolution of introns, as well as construction of gene recognition algorithms.

Published
1999

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