INVESTIGADORES
PRATTA Guillermo Raul
congresos y reuniones científicas
Título:
Visualization of genetic and proteomic biodiversity in four maturity stages of tomato fruit ripening
Autor/es:
MACAT, PAULA; KOVALEVSKI, LEANDRO; QUAGLINO, M.; PRATTA, G.R.
Lugar:
Bariloche
Reunión:
Congreso; 5to Congreso Argentino de Bioinformática y Biología Computacional; 2014
Institución organizadora:
A2B2C
Resumen:
Background Tomato (Solanum lycopersicum) is a climacteric fruit whose ripening is characterized by sequential changes in protein expression, resulting in different profiling of polypeptide bands at each maturity stage [1]. However fruits from diverse tomato genotypes vary in their ripening [2]. Hence tomato fruit ripening is a biological process affected by multidimensional sources of variation, i.e.: maturity stage, genotype and protein expression. Correspondence analysis (CA) is a multidimensional scaling technique allowing a rapid visualization of associations among different sources of variations assessed by dichotomic data [3]. CA was applied in microarrays [3] and protein functional [5] studies. The aim of this work was to visualize the tomato fruit ripening by a CA that allow measuring the relative contribution of different genotypes, maturity stages and polypeptide bands to the total variation observed during the whole process, in a bioinformatic application at the individual level of biological organization. Materials and methods Fruits from 15 genotypes (five Recombinant Inbred Lines -RIL- and their ten diallel Second Cycle Hybrids -SCH-) were screened by SDS-PAGE for 25 polypeptide bands at 4 maturity stages: Mature Green (MG), Breaker (B), Mature Red attached to plant (MRa) and Mature Red in shelves (MRs) according to [6]. A database of 15 x 25 x 4 dimension was analysed firstly by univariate analysis for presence of each band (overall and by stage) and secondly by multivariate CA at each maturity stage. Finally, an integrative CA was made to the complete database. Results The overall presence of all polypeptide bands in the 4 maturity stages for the 15 genotypes was 0.52, having values of 0.46 at MG, 0.55 at B, 0.53 at MRa, and 0.54 at MRs. Minimum and maximum overall presence of each band varied from 0.05 (nearly absent) to 1 (full presence) for two given polypeptides. For most polypeptide bands, their presence varied through different maturity stages. Some polypeptides were more frequent at later maturity stages while others were just present in earlier stages. A higher variation among genotypes for protein expression was found at MG and MRs by CA, supporting the hypothesis that a broader genetic diversity should be expected for fruit traits that are less exposed to natural selection pressures [6]. The first two dimensions explained 35% of total variation at MG, which was the most variable maturity stage for the analyzed polypeptide profiles. Two RIL and two SCH clearly differentiated from the rest of genotypes at this stage, the polypeptide bands mostly associated to each of this four genotypes being completely opposite in their presence (Figure 1). Respecting to the other maturity stages, the first two dimensions explained 37% of total variation at B, 53% at MRa and 48% at MRs. The more divergent genotypes and their corresponding associated polypeptides were varying according to maturity stage, verifying that ripening is jointly affected by the three source of variation considered in this report, i.e., it is a multidimensional biological process. Integrative CA identified one hybrid as the most variable individual along ripening, and seven polypeptide bands highly associated to its discrepant performance in relation to the other genotypes of the diallel crossing. Conclusions Visualization of tomato fruit ripening at four maturity stages allowed measuring the relative contribution of genetic and proteomic diversity to this multidimensional biological process. The bioinformatic application at the individual level of organization was efficient for identifying the most variable genotypes and their associated polypeptide bands at each different maturity stage and along the complete ripening. References 1. Giovannonni JJ: Genetic regulation of fruit development and ripening The Plant Cell 2004, 16: p. S160-76. 2. Rodriguez GR, Sequin L, Pratta GR, Zorzoli R, and Picardi LA: Protein profiling in F1 and F2 generations of two tomato genotypes differing in ripening time Biologia Plantarum 2008, 52: p. 548-52. 3. Lebart L, Morineau A, and Warwick KM: Multivariate descriptive statistical analysis Wiley Chichester 1984, John Wiley & Sons Ltd. 4. Fellenberg K, Hauser NC, Brors B, Neutzner A, Hoheisel JD, and Vingron M: Correspondence analysis applied to microarray data PNAS 2001, 98: p 10781-86. 5. Chang JM, Taly JF, Erb I, Sung TY, Hsu WL, Tang CY, Notredame C, and Su ECY: Efficient and interpretable prediction of protein functional classes by Correspondence Analysis and Compact Set Relations PLOS 2013, 8: e75542. doi:10.1371/journal.pone.0075542. 6. Marchionni Basté E, Pereira da Costa JH, Rodríguez GR, Zorzoli R, and Pratta GR: Genetic analysis of tomato fruit ripening at polypeptide profiles level through quantitative and multivariate approaches American Journal of Plant Sciences 2014, 5: p. 1926-35.