MiSolRNA: A tomato micro RNA relational database

BMC Plant Biology

Volumn 10, Issue , 2010, Pages

  Bazzini, Ariel A ^a   Asís, Ramón ^a,b   González, Virginia ^c   Bassi, Sebastián ^c   Conte, Mariana ^a   Soria, Marcelo ^d   Fernie, Alisdair R ^e   Asurmendi, Sebastián ^a   Carrari, Fernando ^a  

^a INSTITUTO NACIONAL DE TECNOLOGÍA AGROPECUARIA INTA   (Argentina)

^b UNIVERSIDAD NACIONAL DE CÓRDOBA   (Argentina)

^c Genes digitales Bioinformatic group ^*  (Argentina)

^d UNIVERSIDAD DE BUENOS AIRES   (Argentina)

^e MAX PLANCK INSTITUTE OF MOLECULAR PLANT PHYSIOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LYCOPERSICON ESCULENTUM; MAGNOLIOPHYTA; SOLANACEAE;

MICRORNA;

ARTICLE; BINDING SITE; BIOLOGY; FRUIT; GENE EXPRESSION REGULATION; GENETIC DATABASE; GENETICS; GROWTH, DEVELOPMENT AND AGING; INFORMATION RETRIEVAL; METABOLISM; METHODOLOGY; NUCLEOTIDE SEQUENCE; TOMATO;

BASE SEQUENCE; BINDING SITES; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; FRUIT; GENE EXPRESSION REGULATION, DEVELOPMENTAL; GENE EXPRESSION REGULATION, PLANT; INFORMATION STORAGE AND RETRIEVAL; LYCOPERSICON ESCULENTUM; MICRORNAS;

EID: 78049455414     PISSN: None     EISSN: 14712229     Source Type: Journal    
DOI: 10.1186/1471-2229-10-240     Document Type: Article

References (44)

1. Rhee SY, Crosby B. Biological databases for plant research. Plant Physiol 2005, 138:1-3. 10.1104/pp.104.900158, 1104154, 15888672.
2. Menda N, Buels RM, Tecle I, Mueller LA. A community-based annotation framework for linking Solanaceae genomes with phenomes. Plant Physiol 2008, 147:1788-1799. 10.1104/pp.108.119560, 2492603, 18539779.
3. Liang C, Jaiswal P, Hebbard C, Avraham S, Buckler ES, Casstevens T, Hurwitz B, McCouch S, Ni J, Pujar A, et al. Gramene: a growing plant comparative genomics resource. Nucleic Acids Res 2008, (36 Database):D947-953. 2238951, 17984077.
4. Urbanczyk-Wochniak E, Sumner LW. MedicCyc: a biochemical pathway database for Medicago truncatula. Bioinformatics 2007, 23:1418-1423. 10.1093/bioinformatics/btm040, 17344243.
5. Thimm O, Blasing O, Gibon Y, Nagel A, Meyer S, Kruger P, Selbig J, Muller LA, Rhee SY, Stitt M. MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 2004, 37:914-939. 10.1111/j.1365-313X.2004.02016.x, 14996223.
6. Urbanczyk-Wochniak E, Usadel B, Thimm O, Nunes-Nesi A, Carrari F, Davy M, Blasing O, Kowalczyk M, Weicht D, Polinceusz A, et al. Conversion of MapMan to allow the analysis of transcript data from Solanaceous species: effects of genetic and environmental alterations in energy metabolism in the leaf. Plant Mol Biol 2006, 60:773-792. 10.1007/s11103-005-5772-4, 16649112.
7. Goffard N, Weiller G. Extending MapMan: application to legume genome arrays. Bioinformatics 2006, 22:2958-2959. 10.1093/bioinformatics/btl517, 17046975.
8. Sreenivasulu N, Usadel B, Winter A, Radchuk V, Scholz U, Stein N, Weschke W, Strickert M, Close TJ, Stitt M, et al. Barley grain maturation and germination: metabolic pathway and regulatory network commonalities and differences highlighted by new MapMan/PageMan profiling tools. Plant Physiol 2008, 146:1738-1758. 10.1104/pp.107.111781, 2287347, 18281415.
9. Schauer N, Semel Y, Roessner U, Gur A, Balbo I, Carrari F, Pleban T, Perez-Melis A, Bruedigam C, Kopka J, et al. Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat Biotechnol 2006, 24:447-454. 10.1038/nbt1192, 16531992.
10. Schauer N, Semel Y, Balbo I, Steinfath M, Repsilber D, Selbig J, Pleban T, Zamir D, Fernie AR. Mode of inheritance of primary metabolic traits in tomato. Plant Cell 2008, 20:509-523. 10.1105/tpc.107.056523, 2329927, 18364465.
11. Eshed Y, Zamir D. An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL. Genetics 1995, 141:1147-1162. 1206837, 8582620.
12. Lippman ZB, Semel Y, Zamir D. An integrated view of quantitative trait variation using tomato interspecific introgression lines. Curr Opin Genetics Dev 2007, 17:545-552.
13. Bermudez L, Urias U, Milstein D, Kamenetzky L, Asis R, Fernie AR, Van Sluys MA, Carrari F, Rossi M. A candidate gene survey of quantitative trait loci affecting chemical composition in tomato fruit. J Exp Bot 2008, 59:2875-2890. 10.1093/jxb/ern146, 2486480, 18552354.
14. Chen K, Rajewsky N. The evolution of gene regulation by transcription factors and microRNAs. Nat Rev Genet 2007, 8:93-103. 10.1038/nrg1990, 17230196.
15. Jones-Rhoades MW, Bartel DP. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 2004, 14:787-799. 10.1016/j.molcel.2004.05.027, 15200956.
16. Shuklaa LI, Chinnusamyb V, Sunkar R. The role of microRNAs and other endogenous small RNAs in plant stress responses. BBA-Gene Struct Expr 2008, 1779:743-748.
17. Ori N, Cohen AR, Etzioni A, Brand A, Yanai O, Shleizer S, Menda N, Amsellem Z, Efroni I, Pekker I, et al. Regulation of LANCEOLATE by miR319 is required for compound-leaf development in tomato. Nat Genet 2007, 39:787-791. 10.1038/ng2036, 17486095.
18. Griffiths-Jones S. The microRNA Registry. Nucleic Acids Res 2004, (32 Database):D109-D111. 10.1093/nar/gkh023, 308757, 14681370.
19. Mueller LA, Lankhorst RK, Tanksley SD, Giovannoni JJ, et al. A Snapshot of the Emerging Tomato Genome Sequence. Plant Genome 2009, 2:78-92.
20. Stanke M, Steinkamp R, Waack S, Morgenstern B. AUGUSTUS: a web server for gene finding in eukaryotes. Nucleic Acids Res 2004, 32:309-312.
21. Gremme G, Brendel V, Sparks ME, Kurtz S. Engineering a software tool for gene structure prediction in higher organisms. Inform Software Tech 2005, 47:965-978.
22. Carrari F, Baxter C, Usadel B, Urbanczyk-Wochniak E, Zanor MI, Nunes-Nesi A, Nikiforova V, Centero D, Ratzka A, Pauly M, et al. Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior. Plant Physiol 2006, 142:1380-1396. 10.1104/pp.106.088534, 1676044, 17071647.
23. Eby PJ. Python Web Server Gateway Interface v1.0. , http://www.python.org/dev/peps/pep-0333/
24. Moxon S, Jing R, Szittya G, Schwach F, Rusholme Pilcher RL, Moulton V, Dalmay T. Deep sequencing of tomato short RNAs identifies microRNAs targeting genes involved in fruit ripening. Genome Res 2008, 18:1602-1609. 10.1101/gr.080127.108, 2556272, 18653800.
25. Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS. MicroRNA targets in Drosophila. Genome Biol 2003, 5:R1. 10.1186/gb-2003-5-1-r1, 395733, 14709173.
26. Zhang Y. miRU: an automated plant miRNA target prediction server. Nucleic Acids Res 2005, (33 Web Server):W701-W704. 10.1093/nar/gki383, 1160144, 15980567.
27. Alves L, Niemeier S, Hauenschild A, Rehmsmeier M, Merkle T. Comprehensive prediction of novel microRNA targets in Arabidopsis thaliana. Nucleic Acids Res 2009, 37:4010-4021. 10.1093/nar/gkp272, 2709567, 19417064.
28. Bartel B, Bartel DP. MicroRNAs: at the root of plant development?. Plant Physiol 2003, 132:709-717. 10.1104/pp.103.023630, 523861, 12805599.
29. Reinhart BJ, Weinstein EG, Rhoades MW, Bartel B, Bartel DP. MicroRNAs in plants. Gene Dev 2002, 16:1616-1626. 10.1101/gad.1004402, 186362, 12101121.
30. Adai A, Johnson C, Mlotshwa S, Archer-Evans S, Manocha V, Vance V, Sundaresan V. Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res 2005, 15:78-91. 10.1101/gr.2908205, 540280, 15632092.
31. Axtell MJ, Bartel DP. Antiquity of microRNAs and their targets in land plants. Plant Cell 2005, 17:1658-1673. 10.1105/tpc.105.032185, 1143068, 15849273.
32. Lu C, Tej SS, Luo S, Haudenschild CD, Meyers BC, Green PJ. Elucidation of the small RNA component of the transcriptome. Science 2005, 309:1567-1569. 10.1126/science.1114112, 16141074.
33. Sunkar R, Zhu JK. Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell 2004, 16:2001-2019. 10.1105/tpc.104.022830, 519194, 15258262.
34. Chiou TJ. The role of microRNAs in sensing nutrient stress. Plant Cell Environ 2007, 30:323-332. 10.1111/j.1365-3040.2007.01643.x, 17263777.
35. Allen E, Xie Z, Gustafson AM, Carrington JC. microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell 2005, 121:207-221. 10.1016/j.cell.2005.04.004, 15851028.
36. Kawashima CG, Yoshimoto N, Maruyama-Nakashita A, Tsuchiya YN, Saito K, Takahashi H, Dalmay T. Sulphur starvation induces the expression of microRNA-395 and one of its target genes but in different cell types. Plant J 2009, 57:313-321. 10.1111/j.1365-313X.2008.03690.x, 18801012.
37. Leustek T. Sulfate Metabolism. The Arabidopsis Book 2002, American Society of Plant Biologists, Rockville, MD.
38. Fitzgerald MA, Ugalde TD, Anderson JW. Sulphur nutrition affects delivery and metabolism of S in developing endosperms of wheat. J Exp Bot 2001, 52:1519-1526. 10.1093/jexbot/52.360.1519, 11457912.
39. Boualem A, Laporte P, Jovanovic M, Laffont C, Plet J, Combier JP, Niebel A, Crespi M, Frugier F. MicroRNA166 controls root and nodule development in Medicago truncatula. Plant J 2008, 54:876-887. 10.1111/j.1365-313X.2008.03448.x, 18298674.
40. Gruber AR, Lorenz R, Bernhart SH, Neubock R, Hofacker IL. The Vienna RNA website. Nucleic Acids Res 2008, (36 Web Server):W70-74. 10.1093/nar/gkn188, 2447809, 18424795.
41. Mathews DH, Sabina J, Zuker M, Turner DH. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J Mol Biol 1999, 288:911-940. 10.1006/jmbi.1999.2700, 10329189.
42. Mallory AC, Bouche N. MicroRNA-directed regulation: to cleave or not to cleave. Trends Plant Sci 2008, 13:359-367. 10.1016/j.tplants.2008.03.007, 18501664.
43. Itaya A, Bundschuh R, Archual AJ, Joung JG, Fei Z, Dai X, Zhao PX, Tang Y, Nelson RS, Ding B. Small RNAs in tomato fruit and leaf development. BBA-Gene Struct Expr 2008, 1779:99-107.
44. Mueller LA, Mills AA, Skwarecki B, Buels RM, Menda N, Tanksley SD. The SGN comparative map viewer. Bioinformatics 2008, 24:422-423. 10.1093/bioinformatics/btm597, 18202028.