We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family.

We describe an algorithm, ReAS, to recover ancestral sequences for transposable elements (TEs) from the unassembled reads of a whole genome shotgun. The main assumptions are that these TEs must exist at high copy numbers across the genome and must not be so old that they are no longer recognizable in comparison to their ancestral sequences. Tested on the japonica rice genome, ReAS was able to reconstruct all of the high copy sequences in the Repbase repository of known TEs, and increase the effectiveness of RepeatMasker in identifying TEs from genome sequences. Transposable elements (TEs) are a major component of the genomes of multicellular organisms. They are parasitic creatures that invade the genome, insert multiple copies of themselves, and then die. All we see now are the decayed remnants of their ancestral sequences. Reconstruction of these ancestral sequences can bring dead TEs back to life. Algorithms for detecting TEs compare present-day sequences to a library of ancestral sequences. Unknown to many, pervasive use of whole genome shotgun (WGS) methods in large-scale sequencing have made TE reconstructions increasingly problematic. To minimize assembly errors, WGS methods must reject the highly repetitive sequences that characterize most TEs, especially the most recent TEs, which are the least diverged from their ancestral sequences (and most informative for reconstruction). This is acceptable to many, because the most important parts of the genes are not repetitive, but for the TE aficionados, it is a problem. ReAS is a novel algorithm that does TE reconstruction using only the unassembled reads of a WGS. Tested against the WGS for japonica rice, it is shown to produce a library that is superior to the manually curated Repbase database of known ancestral TEs.