Data origin

Diversity data

The "MiniGB" is a core collection of 280 accessions of O. sativa established by scientists from Cirad and from IRRI on the basis of the species enzymatic diversity. The collection was assembled to represent the geographic, ecotypic and enzymatic diversity of O. sativa, drawing on the enzymatic and phytopathological studies performed on this material by Glaszmann (1987), Bonman et al (1990) and Glaszmann et al (1995).

  References concerning the MiniGB:

» Bonman JM, Mackill AO, Glaszmann J-C (1990) Resistance to Gerlachia oryzae in rice. Plant Disease 74:306-309

» Glaszmann J-C (1987) Isozymic classification of Asian rice varieties. Theor Appl Genet, 74:21-30

» Glaszmann J-C, de los Reyes BG, Khush GS (1988) Electrophoretic variation of isozymes in plumules of rice: a key to identification of 76 alleles at 24 loci. IRRI Research Paper Series, 134, 13p.

» Glaszmann J-C, Mew T, Hibino H, Kim CK, Mew TI, Vera Cruz CH, Notteghem J-L, Bonman JM (1995) Molecular variation as a diverse source of disease resistance in cultivated rice. In: Rice Genetics III, IRRI, Los Banos, Phillipines, p460-46

» Glaszmann J-C, Grivet L, Courtois B, Noyer JL, Luce C, Jacquot M, Albar M, Ghesquière A, Second G (2003) Asian rices. In: Genetic Diversity of Cultivated Tropical Crops, Hamon P, Seguin M, Perrier X, Glaszmann JC (eds), CIRAD, Montpellier, France, p77-98.

Synthetic map

The rice synthetic map available under CMap is actually just a list of genetic markers with their physical position on the pseudomolecules (TIGR v4.0). For each marker, the data source is given in the "remark" field.  Gramene data or Blast results based on sequence information were used when available. Otherwise, as in the case of AFLPs, the nearest marker with a known sequence on the relevant genetic map was used as a proxy.

QTLs for tolerance/resistance to abiotic stress

The QTLs listed in this DB come from a compilation of the published literature on rice. We extracted from the QTL papers the data we thought were relevant for the purpose of meta-analysis. This statistical approach allows combining QTL results from independent studies in a single result (Goffinet and Gerber, 2000; Veyrieras et al, 2007). In the present version, QTL for drought resistance, salinity tolerance, duration and those detected on the IR64 x Azucena population, all traits confounded, are compiled.  In comparison with the QTL module of Gramene, additional parameters characterizing each individual QTLs were recorded, notably parameters concerning the experimental conditions important to qualify abiotic stresses (e.g. well watered versus stressed conditions; aerobic versus anaerobic conditions).

The data result from our interpretation of published papers in the framework of a meta-analysis and may sometimes appear to be different from the original paper. For reasons of homogeneity across studies, we had to modify some elements.
The most common modification concerned trait names. An ontology associated to a trait definition largely inspired from Gramene but adapted by us to an abiotic stress context was developed and is available elsewhere in Tropgene.
Because of missing information on genetic distances and discrepancies between genetic maps, we chose to define a QTL position by the physical position of its flanking markers on the pseudo molecules (see synthetic map above) rather than by their genetic position on a composite genetic map.

For original data or additional details on the experiments, users should go back to the initial publications that constitute the reference.

  References concerning the QTLs:

» Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155:463-4733

» Veyrieras JB, Goffinet B, Charcosset A (2007) Meta QTL: a package of new computational methods for the meta-analysis of QTL mapping experiments. BMC Bioinformatics 8:49