Expressed Sequence Tag (EST) analysis has pioneered genome-wide gene discovery and expression profiling. In order to establish a gene expression index in the rice cultivar indica, we sequenced and analyzed 86,136 ESTs from nine rice cDNA libraries from the super hybrid cultivar LYP9 and its parental cultivars. We assembled these ESTs into 13,232 contigs and leave 8,976 singletons. Overall, 7,497 sequences were found similar to existing sequences in GenBank and 14,711 are novel. These sequences are classified by molecular function, biological process and pathways according to the Gene Ontology. We compared our sequenced ESTs with the publicly available 95,000 ESTs from japonica, and found little sequence variation, despite the large difference between genome sequences. We then assembled the combined 173,000 rice ESTs for further analysis. Using the pooled ESTs, we compared gene expression in metabolism pathway between rice and Arabidopsis according to KEGG. We further profiled gene expression patterns in different tissues, developmental stages, and in a conditional sterile mutant, after checking the libraries are comparable by means of sequence coverage. We also identified some possible library specific genes and a number of enzymes and transcription factors that contribute to rice development.
Arabidopsis ; genetics ; DNA, Complementary ; metabolism ; Databases as Topic ; Expressed Sequence Tags ; Gene Library ; Genome, Plant ; Genomics ; methods ; Multigene Family ; Open Reading Frames ; Oryza ; genetics ; Quality Control ; Software

OBJECTIVETo establish a risk early warning model of human infection with avian influenza A (H7N9) virus and predict the area with high risk of the outbreak of H7N9 virus infection.

METHODSThe incidence data of human infection with H7N9 virus at prefecture level in China from February 2013 to June 2014 were collected, and the geographic and meteorological data during the same period in these areas were collected too. Spatial auto regression (SAR) model and generalized additive model (GAM) were used to estimate different risk factors. Afterwards, the risk area map was created based on the predicted value of both models.

RESULTSAll the human infections with H7N9 virus occurred in the predicted areas by the early warning model in February 2014. The early warning model successfully predicted the spatial moving trend of the disease, and this trend was verified by two outbreaks in northern China in April and May 2014.

CONCLUSIONThe established early warning model showed accuracy and precision in short-term prediction, which might be applied in the active surveillance, early warning and prevention/control of the outbreak of human infection with H7N9 virus.

China ; epidemiology ; Disease Outbreaks ; Humans ; Incidence ; Influenza A Virus, H7N9 Subtype ; Influenza, Human ; epidemiology ; virology ; Models, Statistical ; Population Surveillance ; methods ; Risk ; Risk Factors