A global assembly of cotton ESTs.

Approximately 185,000 Gossypium EST sequences comprising >94,800,000 nucleotides were amassed from 30 cDNA libraries constructed from a variety of tissues and organs under a range of conditions, including drought stress and pathogen challenges. These libraries were derived from allopolyploid cotton (Gossypium hirsutum; A(T) and D(T) genomes) as well as its two diploid progenitors, Gossypium arboreum (A genome) and Gossypium raimondii (D genome). ESTs were assembled using the Program for Assembling and Viewing ESTs (PAVE), resulting in 22,030 contigs and 29,077 singletons (51,107 unigenes). Further comparisons among the singletons and contigs led to recognition of 33,665 exemplar sequences that represent a nonredundant set of putative Gossypium genes containing partial or full-length coding regions and usually one or two UTRs. The assembly, along with their UniProt BLASTX hits, GO annotation, and Pfam analysis results, are freely accessible as a public resource for cotton genomics. Because ESTs from diploid and allotetraploid Gossypium were combined in a single assembly, we were in many cases able to bioinformatically distinguish duplicated genes in allotetraploid cotton and assign them to either the A or D genome. The assembly and associated information provide a framework for future investigation of cotton functional and evolutionary genomics.

Large-scale identification of expressed sequence tags involved in rice and rice blast fungus interaction.

To better understand the molecular basis of the defense response against the rice blast fungus (Magnaporthe grisea), a large-scale expressed sequence tag (EST) sequencing approach was used to identify genes involved in the early infection stages in rice (Oryza sativa). Six cDNA libraries were constructed using infected leaf tissues harvested from 6 conditions: resistant, partially resistant, and susceptible reactions at both 6 and 24 h after inoculation. Two additional libraries were constructed using uninoculated leaves and leaves from the lesion mimic mutant spl11. A total of 68,920 ESTs were generated from 8 libraries. Clustering and assembly analyses resulted in 13,570 unique sequences from 10,934 contigs and 2,636 singletons. Gene function classification showed that 42% of the ESTs were predicted to have putative gene function. Comparison of the pathogen-challenged libraries with the uninoculated control library revealed an increase in the percentage of genes in the functional categories of defense and signal transduction mechanisms and cell cycle control, cell division, and chromosome partitioning. In addition, hierarchical clustering analysis grouped the eight libraries based on their disease reactions. A total of 7,748 new and unique ESTs were identified from our collection compared with the KOME full-length cDNA collection. Interestingly, we found that rice ESTs are more closely related to sorghum (Sorghum bicolor) ESTs than to barley (Hordeum vulgare), wheat (Triticum aestivum), and maize (Zea mays) ESTs. The large cataloged collection of rice ESTs in this study provides a solid foundation for further characterization of the rice defense response and is a useful public genomic resource for rice functional genomics studies.

An integrated physical and genetic map of the rice genome.

Rice was chosen as a model organism for genome sequencing because of its economic importance, small genome size, and syntenic relationship with other cereal species. We have constructed a bacterial artificial chromosome fingerprint-based physical map of the rice genome to facilitate the whole-genome sequencing of rice. Most of the rice genome ( approximately 90.6%) was anchored genetically by overgo hybridization, DNA gel blot hybridization, and in silico anchoring. Genome sequencing data also were integrated into the rice physical map. Comparison of the genetic and physical maps reveals that recombination is suppressed severely in centromeric regions as well as on the short arms of chromosomes 4 and 10. This integrated high-resolution physical map of the rice genome will greatly facilitate whole-genome sequencing by helping to identify a minimum tiling path of clones to sequence. Furthermore, the physical map will aid map-based cloning of agronomically important genes and will provide an important tool for the comparative analysis of grass genomes.