Skip to main content

Construction, alignment and analysis of twelve framework physical maps that represent the ten genome types of the genus Oryza


We describe the establishment and analysis of a genus-wide comparative framework composed of 12 bacterial artificial chromosome fingerprint and end-sequenced physical maps representing the 10 genome types of Oryza aligned to the O. sativa ssp. japonica reference genome sequence. Over 932 Mb of end sequence was analyzed for repeats, simple sequence repeats, miRNA and single nucleotide variations, providing the most extensive analysis of Oryza sequence to date.


Comparative genomics is a powerful tool for unraveling the evolutionary history and gene functionality of related species. The availability of high resolution genetic and physical maps and genome assemblies has established comparative genomics platforms in organisms ranging from bacteria and fungi to animals and plants [17]. The majority of sequence-based eukaryotic platforms have focused on comparisons between genera [811]. Although highly informative, the divergence times between genera are often too distant to be useful for the identification of conserved noncoding sequences such as transcription factor binding sites, enhancers and matrix attachment regions (for example, see [12, 13]). Sequence comparisons between species within a single genus have focused primarily on orthologous loci or genomic regions [14, 15]. Whole genome comparative platforms within a genus are still in their infancy, with the most notable exception being the generation of whole genome shotgun assemblies of 12 Drosophila species that span an evolutionary time frame of approximately 60 million years [16].

In plants, rice (Oryza sativa) and thale cress (Arabidopsis thaliana) are important model systems for functional and evolutionary biology. Both genomes have been completely sequenced [17, 18] and serve as the reference sequences for the major monocot and dicot plant lineages. Rice has added significance by virtue of being the world's most important crop, directly feeding half the human population. The population that depends on rice is expected to double in 25-50 years and there is thus an intense effort by breeders to double current rice yields using less land and water and on poorer soils [19]. To achieve this goal, the plant biology community is engaged in a concerted effort to functionally characterize all plant genes in both model plants using approaches including genetics, transgenetics, and comparative genomics. These efforts have significance not only to world food and bio-energy security issues but also to fundamental eukaryotic biology.

Comparative genomics across the cereals and within the genus Oryza will play a major role in these efforts. Oryza is composed of 24 species, including 2 domesticated (O. sativa, and O. glaberrima) and 22 wild species [20, 21]. These species are classified into ten genome types (six diploids and four allotetraploids) based on crossing barriers [22, 23], chromosome pairing [24, 25], morphology [26, 27], and molecular phylogenetics [28]. Compared to the domesticates, the wild relatives of rice are phenotypically inferior grass-like plants, but are a virtually untapped reservoir of agriculturally important genes and allelic variants that can be used to improve cultivated rice [21, 29]. Therefore, comparative genomics of wild and domesticated Oryza species may not only provide useful materials for breeding, but will also shed light on the evolution and domestication of cultivated rice.

Our long-term objective is to develop a genome-level comparative experimental system for the genus Oryza (the Oryza Map Alignment Project (OMAP)). Our strategy is to develop bacterial artificial chromosome (BAC)-end sequence (BES) physical frameworks of the ten genome types of Oryza and align them to the reference sequence. These frameworks can then be populated with an array of phenotypic, genetic, biochemical, and physiological data to address fundamental questions in biology and agriculture. Previously, we described the construction and characterization of 12 BAC libraries from representative species that encompass the 10 genome types of Oryza [30]. Here we report the construction of 12 BAC/BES framework physical maps derived from these libraries and an analysis of the BESs in terms of transposable element, simple sequence repeat (SSR), microRNA (miRNA), and single nucleotide variation (SNV) content.


Fingerprinting, BAC end sequencing and contig assembly to generate phase I physical maps for the ten genome types of Oryza

BAC-based physical maps for the ten genome types of Oryza were generated using a two-step procedure. First, clones from 12 Oryza BAC libraries [30] were fingerprinted [31] and BAC end sequenced. Fingerprints from each library were then assembled into contigs using FPC [32]. Fingerprint, BES and FPC assembly statistics are summarized in Tables 1 and 2. Briefly, we generated a total of 710,536 fingerprints and 1,452,912 BESs (approximately 932 Mb). Fingerprinting and BES success rates ranged from 85-94% and 88-96%, respectively. BESs represented approximately 8-17% of each Oryza genome, corresponding to one sequence tag per every 4-8 kb. From 90-98% of the BESs were paired and ranged in sequence length from 559 bp in O. minuta [BBCC] to 717 bp in O. officinalis [CC]. More importantly, an average of 89% of the fingerprinted clones had paired BESs. An average of 95% of the fingerprints assembled into contigs, with the remainder existing as singletons. The number of assembled contigs for each species ranged from 422 in O. brachyantha [FF] to 3,962 in O. minuta [BBCC], which roughly correlated with the size of each genome. The 12 unedited FPC assemblies are defined as phase I physical maps (Table 2) and are available interactively using WebFPC [33] or CMap, or as downloadable FPC files (see Materials and methods).

Table 1 Summary of BAC end sequences of 12 Oryza species
Table 2 Summary of phase I FPC physical maps of 12 Oryza species

To determine the approximate genome coverage of each of the 12 phase I physical maps, we estimated the size of the ordered consensus bands for each map in kilobases based on the average insert size of each BAC library and the average number of fingerprint bands observed for each species. Using this estimation, the genome coverage of the phase I physical maps ranged from 136% in O. granulata [GG] to 77% in O. brachyantha [FF]. In total, 7 of the physical maps had coverages greater that 100% (O. nivara, O. rufipogon, O. glaberrima, O. minuta, O. alta, O. granulata, and O. ridleyi), 4 had coverages between 98% and 87% (O. punctata, O. officinalis, O. australiensis, and O. coarctata) and 1 had a coverage of 77% (O. brachyantha). Coverage discrepancies above or below 100% could be due to a number of parameters, including: possible overlaps between the contigs that were not merged by the criteria used in this study; inaccurate estimation of genome size; and over-estimation of average insert sizes of the BAC libraries that would lead to an over-estimation of kilobases per consensus band (CB).

Alignment of phase I physical maps to the O. sativareference sequence

To evaluate the coverage of the phase I physical maps graphically, we aligned the BESs associated with each FPC contig to the O. sativa reference sequence (RefSeq) [18] using SyMAP [34]. SyMAP displays for all 12 physical maps can be viewed at [35] (display details are in Additional data file 1) and are summarized in Table 3 and Additional data file 2. Overall, between 61% and 95% of the contigs from each of the phase I physical maps could be aligned to the O. sativa RefSeq. Contigs not assigned a chromosomal position were generally small (133-289 CB/contig) and had few clones per contig (3-38 clones/contig) (Table 3). The percentage of BESs aligned, under identical parameters, was the least in O. alta [CCDD] (8% alignment) and the greatest in the AA genome type species O. nivara (60% alignment). Interestingly, the FF (O. brachyantha) and HHKK (O. coarctata) genome type species showed substantially more alignments to the O. sativa RefSeq than more closely related species (CC, BBCC, CCDD, EE, GG, and HHJJ).

Table 3 Summary of alignments of 12 OMAP Phase I FPC maps to the O. sativa RefSeq

Figure 1 shows a SyMAP alignment of chromosome 1 of the eight diploid Oryza species to the O. sativa RefSeq as an example. As expected, the most co-linear map alignments were observed with species that were evolutionarily less divergent (for example, AA, BB, CC). Regions of disrupted colinearity were detected mostly in the centromeric regions of the O. sativa genome. Although SyMAP alignments were also performed for the four polyploid species, we cannot conclude anything conclusive about their genome organization until their physical maps can be manually subdivided into each of their subgenomes.

Figure 1

SyMAP view of unedited physical maps of chromosome 1 from eight diploid Oryza species aligned to the O. sativa ssp. japonica chromosome 1 RefSeq. The numbers in the small rectangles on the left are contig numbers of OMAP phase I physical maps. Beige bars on the right represent the O. sativa RefSeq (IRGSP V.4 assembly) and the red crosses on the beige bars represent the CentO position of O. sativa [18]. Purple lines represent BESs aligned to the O. sativa RefSeq. The order of the species from the left to right is; O. nivara [AA], O. rufipogon [AA], O. glaberrima [AA], O. punctata [BB]; O. officinalis [CC], O. australiensis [EE]; O. brachyantha [FF], O. granulata [GG].

Sequence analysis of the OMAP BES data set: repeats, SSRs, miRNAs, and SNV

The large BES data set produced by this project offered a unique opportunity to explore sequence content and variation across the Oryza. We next investigated repeat and SSR content across all twelve species and identified miRNA content and SNV amongst the three AA and one BB genomes.


RepeatMasker [36] in conjunction with a curated rice (O. sativa) repeat database was used to identify and classify previously identified repetitive elements. RECON [37] was used to identify repeats de novo. Results reported here relate to the number of bases covered by each element class, rather than the total number of members of each element class with the exception of small transposable elements (that is, miniature inverted repeat transposable elements (MITEs) and short interspersed elements (SINEs)), as BES reads are too short to span complete elements. The repeat content results ranged from a high of 76% in O. australiensis [EE] to a low of 36% in O. coarctata [HHKK] (Table 4). The repeats extracted by RECON overlapped with those identified by RepeatMasker by 32% in O. coarctata [HHKK] to 74% in O. punctata [BB]. This is expected as the curated repeat library used for RepeatMasker is O. sativa [AA] specific and, therefore, more distantly related species would be expected to share fewer repeats. Interestingly, the total repeat content of two CC genome containing allotetraploid species (O. minuta [BBCC] and O. alta [CCDD]) was less than the CC diploid genome of O. officinalis. It was also observed that the highest amount of unique or species-specific repetitive DNA was present in O. australiensis [EE] (21% corresponding to 203 Mb) and the lowest in O. granulata [GG] (10% corresponding to 92 Mb). These sequences were compiled into species-specific repeat databases.

Table 4 Repeat content analysis of 12 Oryza species using RepeatMasker and RECON

The amount of repeats in each genome was directly proportional to the genome size except for O. granulata [GG] (Additional data file 3), suggesting that repetitive sequences play a major role in genome size expansion in the genus Oryza. O. australiensis [EE] had a high amount of repetitive DNA, consistent with the observation of a rapid burst of retrotransposons in this species [38].

We attempted to sub-classify the repetitive elements identified by their class. Only the results from the RepeatMasker search were used for classification (Figure 2) as the de novo repeats identified by RECON were mostly truncated. Retrotransposons (both long terminal repeats (LTRs) and non-LTRs) comprised the major fraction of the total repeats in all species and ranged from 46% of the genome in O. australiensis [EE] to 9% in O. brachyantha [FF]. Among all types of retroelements, the Ty-3/gypsy elements were the most predominant, followed by Ty-1/copia, LINEs and SINEs, respectively. The second most abundant class was DNA (non-MITE) transposons consisting mainly of the cacta-En/Spm, mutator, mariner, ping/pong/snoopy, hAT, and Ac/Ds elements, with En/Spm being the most predominant. These non-MITE DNA transposons ranged from 7% of the genome in O. ridleyi [HHJJ] to 2% in O. coarctata [HHKK]. An exception to this trend was O. brachyantha [FF], which had more MITEs (7%) than DNA (non-MITE) transposons (2%). MITEs were the third most abundant elements in the genus Oryza with the exception of O. brachyantha; MITEs ranged from 0.9% of the genome in O. australiensis to 7% in O. brachyantha. The three AA genome species, as well as O. sativa, have approximately equal amounts of both DNA (non-MITE) transposons as well as MITEs, although with slight differences. Since MITEs represent a large class of repeats with many different types, we calculated the percentage of different MITEs from the overall total as shown in Additional data file 4. Some types of MITEs were more abundant than others and also some were specific to a particular species - for instance, the three AA genome species illustrated a similar pattern for each element. Similarly, the distribution pattern of the MITE elements to the classification of MITE types and their proportion was more comparable among O. punctata [BB], O. officinalis [CC], O. minuta [BBCC] and O. alta [CCDD] genome species rather than those of the other genomes. A similar pattern was also detected between O. ridleyi [HHJJ] and O. coarctata [HHKK] species. This result indicates that the abundance and composition of the MITE elements are closely related to genome type evolution in the genus Oryza.

Figure 2

Comparison of classified repeat composition in the genomes of 12 Oryza species and the O. sativa RefSeq.

Analysis of O. alta [CCDD] revealed that approximately 9% of the BESs were categorized as unclassified repeats, high relative to other 12 Oryza species (2% in O. minuta [BBCC] to 0.2% in O. coarctata [HHKK]), implying the existence of one or more unique classes of repeats in O. alta or the presence of highly diverged repeats that were recognized by our current stringency parameters. On closer inspection, we identified a copia type LTR retrotransposon in a fully sequenced BAC (OA_BBa0237I11) representing a large family of retrotransposons that accounts for the majority of these unclassified repeats. This element, considered in detail elsewhere [39], accounted for two-thirds (2,939,525 bases of 4,392,322 bases) of these unclassified repeat sequences when assayed using cross_match alone.

Simple sequence repeats

SSRs are extremely useful for detecting variation between species and generating molecular genetic maps. A total of 16,980 non-redundant SSRs were detected from the 1.45 million BESs analyzed, which equates to approximately 18 SSRs/Mb of Oryza sequence. Overall, the AA and FF genome species (O. nivara [AA], O. rufipogon [AA], O. glaberrima [AA] and O. brachyantha [FF]) showed the highest SSR content, with an average of 27 SSRs/Mb, whereas the tetraploid (O. minuta [BBCC], O. alta [CCDD], O. ridleyi [HHJJ] and O. coarctata [HHKK]) and non-AA genome diploid species (O. punctata [BB], O. officinalis [CC], O. australiensis [EE], and O. granulata [GG]) showed 17.6 and 17.2 SSRs/Mb, respectively (Table 5). Among the 16,980 non-redundant SSRs, di- and tri-nucleotide SSRs were the most abundant, representing 48.6% and 26.7% of the total dataset, respectively. The relative frequency of di-nucleotide SSRs in all the Oryza species was 6-7% higher than in the O. sativa reference genomes (Table 5; Additional data file 5). In contrast, the relative frequency of tri-nucleotide SSRs was 4-5% lower than in the O. sativa reference genomes and was inversely related to that of the di-nucleotide repeats in each species (Additional data file 5).

Table 5 Distribution of OMAP non-redundant SSRs by motif type

The top ten predominant motifs from the five most frequent SSRs in each species comprised between 68% (O. sativa ssp. japonica) and 80% (O. granulata) of all the SSRs identified (Figure 3). The TA, GA and CGG motifs were the most abundant and accounted for a total of 51% (30%, 15%, and 6%, respectively) of all the Oryza SSRs. Interestingly, two SSR motifs showed biased compositions in a species-specific manner. The TAA and CAA motifs were significantly higher in O. ridleyi (9.6% for TAA, 13% for CAA) and O. granulata (9% for CAA) compared to the average (4.2% and 3%, respectively) for all Oryza species (Figure 3). Further investigation using the rice repeats revealed that 137 of 235 BESs (58%) containing the TAA motif in O. ridleyi were associated with an uncharacterized LTR retrotransposon (Additional data file 6a). We failed to detect the known interspersed rice repeats in BESs containing the CAA repeat, but a BLAST search against O. granulata and O. ridleyi BESs revealed that more than 76% of total CAA-BESs in both species hit other BESs more than 50 times. This suggests the amplification of certain repeat elements contributed to increase the TAA and CAA repeats in both species (Additional data file 6b).

Figure 3

Comparison of the ten most frequent SSR motif compositions in 14 Oryza species (japonica, O. sativa ssp. japonica; indica, O. sativa ssp. indica; OMAP, average of 12 OMAP species).

The di-nucleotide SSRs showed the longest tracks of repeats, with an average of 44.5 ± 45.2 bp in the OMAP SSRs (Table 6). The TA repeat class showed the most variable repeat length among SSRs analyzed, with an average of 53.3 ± 55 bp (Additional data file 7). O. coarctata showed the least variable TA repeat length (31 ± 22.8 bp) and O. rufipogon showed the most variable length (73.8 ± 92.1 bp) in the Oryza species. We observed that the length of tri-nucleotide SSRs was inversely related to the G/C composition of their motifs (Additional data file 7). G/C rich motifs (CGA, CAG, CGG, TGG and GGA) revealed a shorter repeat length, with an average of 24.6 bp ± 4.5 bp in OMAP SSRs. The same trend was detected in japonica (24.9 ± 5.6 bp) and indica (24.8 ± 5.6 bp). However, A/T rich tri-nucleotide repeats (CAA, CAT, TAG, GAA and TAA) showed relatively longer tracks of repeats, with a length of 33.6 ± 18.2 bp in OMAP SSRs, 42.3 ± 30.1 bp in japonica, and 40.2 ± 25.9 bp in indica.

Table 6 Distribution of SSR length by the repeat types

Identification of miRNAs in four Oryzaspecies based on OMAP alignment data

miRNAs play an important role in plant developmental and physiological processes by negatively controlling gene expression [4043]. To detect evolutionarily conserved miRNAs between wild rice and O. sativa genomes, we anlayzed BES datasets from one domesticated and three wild Oryza genomes using an alignment-based approach.

In total, 64 paralogous miRNA precursors of O. sativa belonging to 22 miRNA families were identified among the four Oryza species (Table 7). O. rufipogon showed the highest number of conserved O. sativa miRNAs while O. punctata showed the lowest (22 and 7, respectively). This is consistent with our expectations since, as the evolutionary distance among species increases, the divergence within the miRNA precursor structure also increases [44]. The miRNA families of miR166 and miR171, known to play a key role in apical meristem development, were detected in all four species; the highest number of copies of each was 9 and 7, respectively. Both of these miRNAs are known to be widely shared among plant lineages. In addition, four unknown locus miRNAs (miR420, miRNA441, miR442, and miR446) appeared to be AA genome specific.

Table 7 miRNAs conservation between O. sativa and four wild rice species detected from their BES datasets

Variation discovery in four wild rice species and O. sativa

Candidate SNVs between wild rice BESs and the O. sativa genome were detected with a multi-tiered alignment strategy [45] using BLASTZ [46] and cross_match followed by a base-by-base analysis of the resulting high quality alignment (see Materials and methods). Putative nucleotide variations were further filtered using sequence quality scores and quality scores of neighboring regions to exclude variations that were due to possible sequencing error.

Our initial data set contained 330,993 high quality BESs (73,716 from O. rufipogon, 110,589 from O. nivara, 73,344 from O. glaberrima and 73,344 from O. punctata). Since two assemblies of the O. sativa ssp. japonica RefSeq (International Rice Genome Sequencing Project (IRGSP) V.4 and The Institute for Genomic Research (TIGR) V.4) were available, we detected variations on both assemblies using a quality score cutoff of 23. We were able to accurately map 217,202 BESs (53,426 from O. rufipogon, 76,886 from O. nivara, 50,736 from O. glaberrima, and 36,154 from O. punctata) to the IRGSP V.4 assembly and 217,258 BESs (53,273 from O. rufipogon, 76,833 from O. nivara, 50,833 from O. glaberrima, and 36,319 from O. punctata) to the TIGR V.4 assembly. A total of 1,619,446 non-redundant SNVs (Additional data file 8a) and 319,974 insertions and deletions (INDELs; Additional data file 8b) were detected between the BESs from the four Oryza species (O. rufipogon, O. nivara, O. glaberrima, and O. punctata) and the O. sativa genome assembly from IRGSP V.4. Likewise 1,619,557 SNVs (Additional data file 8c) and 320,592 INDELs (Additional data file 8d) were detected on the TIGR V.4 assembly. The overall divergence rate was found to be 1.22%, 1.32%, 1.59% and 7.15% for O. rufipogon, O. nivara, O. glaberrima and O. punctata, respectively. The variation rate was found to be 12.2, 13.2, 15.9 and 71.5 SNVs/kb and 1.5, 1.6, 2.0 and 11.4 INDELs/kb for O. rufipogon, O. nivara, O. glaberrima and O. punctata, respectively. In comparison, the polymorphism rate reported by the Beijing Genomics Institute [47] between the indica and japonica cultivars of O. sativa was 1.70 SNPs/kb and 0.11 INDELs/kb [48]. Therefore, the rate of variation between Oryza species is roughly an order of magnitude greater than the polymorphism rate within species, as we would expect. The variation data are available through dbSNP and Gramene [49]. An example view of the variation data in Gramene is shown in Additional data file 9.


We describe here the generation and analysis of a comparative genomics resource for the genus Oryza that can be used as a research platform to address grand challenge questions in basic and applied biology. The primary resources developed were 1,452,912 BESs, 710,536 fingerprints, 12 phase I physical maps aligned to the rice RefSeq, and repeat, SSR, miRNA and SNV analyses. All sequences and variations have been deposited in GenBank and dbSNP, and all physical maps can be visualized using SyMAP [34] and CMAP at the OMAP [50] and Gramene [49] websites, respectively. The BAC libraries, BESs, SNaPshot fingerprints, and phase I physical maps have been publicly available since January 2006 and have been extensively accessed by the international community [31, 38, 5156].

Estimates of genome coverage of the physical maps relative to flow cytometry data were quite close except for O. granulate. To make the Oryza physical maps more useful for future research, they must now be manually edited to merge contigs and resolve any conflicts and mis-assemblies, as was done for O. punctata [BB] [31]. Manual editing will be particularly challenging for the four allotetraploid species, where contigs need to be assigned to one of two subgenomes for each species. Fortunately for two tetraploids, O. minuta [BBCC] and O. alta [CCDD], we can use BES information from their diploid progenitors to assist in this process.

The BES data set represents an unprecedented sampling of genomic sequence from the Oryza. This resource is enhanced by the fact that the majority of BESs are binned in FPC contigs where 6-60% of BESs (depending on species) can be mapped to the rice RefSeq, and approximately 95% are paired. Here, we mined the BES data set for repeat, SSR, miRNA and SNV content. Repetitive sequences, especially transposable elements, are major components of plant genomes and contribute significantly to genome size variation. Detailed analysis of the BES resource for O. australiensis [EE] and O. granulata [GG] BESs have already demonstrated that retrotranspositional bursts of RIRE2, Wallaby and Kangaroo in the EE genome [38] and Gran3 in the GG genome [51] account for 50% and 25% of the genome sizes of these species, respectively. The RECON data described here for O. alta [CCDD] may likely represent yet a third retrotransposon burst accounting for genome size variation, subsequent to speciation [39].

Further analysis of the Oryza BES data identified 16,980 and 1,619,446 non-redundant SSRs and SNVs, respectively. The SSRs and SNVs can be immediately translated into polymorphic markers for breeding crosses between the two sequenced O. sativa genomes with the AA genome OMAP accessions to accelerate crop improvement. Further, the SSRs will serve as candidates to identify polymorphic genetic makers for intraspecific Oryza mapping populations currently under development (for example, BB × BB; CC × CC, and so on). The availability of molecular genetic maps tied to our physical maps for all 12 accessions will make these resources even stronger for functional and map-based cloning applications.

Paired-end data are also extremely important for studying structural variation, such as expansions, contractions, inversions and translocations [57, 58]. Using our paired BES database, we plan to catalogue all such variation across the Oryza in order to address fundamental questions on the roles of such variation on the speciation process.

To our knowledge, the combined resources described herein comprise the most comprehensive within-genus comparative genomics framework available for any higher eukaryote, exceeded only by Drosophila, for which 12 draft genome sequences of wild flies are available [16]. We envisage that the OMAP system will be a model for other within-genus comparative frameworks, including large genome plant genera like Gossypium (cotton), Solanum (tomato), Zea (corn) and Phaseolus (soybean). Having physical map frameworks for all genome types of a particular genus aligned to a reference genome provides immediate access to any orthologous or unique region of a genome(s) for functional and evolutionary analysis. Such frameworks are also highly compatible with next generation sequencing technologies whereby whole genomes can be sequenced in 4-8 Mb chunks, thereby reducing assemblies to the size of a bacterial genome [59].


The development and analysis of genus-wide research platforms is the next frontier in comparative systems biology. The genus Oryza, which includes the world's most important cereal, rice, is composed of 24 species (2 domesticated and 22 wild) with wide geographical distribution and contains 10 distinct genome types (6 diploid (2N = 24) and 4 polyploid (2N = 48)) and a 3.6-fold genome size variation (357-1,283 Mb).

We generated BAC-based physical maps of 12 Oryza species representing all the 10 genome types and aligned them to the O. sativa RefSeq. The 12 physical maps covered between 77% and 136% of each Oryza genome and revealed extensive colinearity to the O. sativa RefSeq. We analyzed the BES for repeats, SSRs, miRNA and SNVs. The repeat analysis not only cataloged the repeat content of each species, it suggested the possible roll they have played on genome size variation during the course of evolution. The SSR analysis identified 16,908 non-redundant SSRs from OMAP BESs, providing 18 SSRs/Mb of SSR density in the Oryza. We also found that the amplification of certain repeat elements contributed to an increase of the TAA and CAA motif repeats in the O. granulata [GG] and O. ridleyi [HHJJ] genomes. A total of 1,619,446 non-redundant SNVs and 319,974 insertions and deletions (INDELs) were detected between the BESs from four Oryza species (O. rufipogon, O. nivara, O. glaberrima, and O. punctata) and the O. sativa RefSeq. The SSR, SNV and INDEL markers can be immediately used for marker assistant selection as well as evolutionary studies. The miRNA analysis identified 64 paralogous miRNA precursors of O. sativa with more conservation in evolutionarily closer species. In addition, we observed species-wide miRNA families (miR166 and miR171) and AA genome specific miRNAs (miR420, miRNA441, miR442, and miR446).

All biological reagents are available at the AGI BAC/EST Resource Center [60] and all fingerprints and BESs are available at [49, 50] and GenBank. We envision that the resources and analysis presented here will serve as a model for the establishment of similar genus-wide frameworks for plants and animals. The genus-wide physical framework also fits in well with next generation sequencing technologies where an entire genome or targeted regions across a genus can be reduced to bacterial genome size chunks that can be easily sequenced and assembled as opposed to a whole genome sequencing approach.

Materials and methods

BAC libraries, end sequencing, fingerprinting and FPC assembly

All BAC libraries and methods have been described previously [30, 31].

FPC map alignment to the O. sativaRefSeq

SyMAP [34] was used for alignment and display of FPC contigs from each of the 12 phase I physical maps to the O. sativa RefSeq (IRGSP V.4). Briefly, the 12 BES data sets were repeat-masked [36] and then searched for sequence similarity to the rice genome using BLAT [61]. To capture weaker sequence similarities from the more divergent species, BLAT parameters were adjusted as follows (-minIdentity = 70 -tileSize = 10 -minScore = 30 -qMask = lower -maxIntron = 10,000). BLAT results were filtered, to reduce false-positives, by retaining the top two hits for each query, as measured by match length, and subject to the additional criteria that no retained hit had a match length within 25% of a discarded hit. Approximate linear chains were computed from the retained hits using dynamic programming and then merged to form synteny blocks that were displayed by SyMAP. After the Oryza BESs were positioned on the O. sativa RefSeq, contigs containing the aligned BESs were anchored to the chromosomes and then renumbered in FPC. Contigs that aligned to less than 200 bp of O. sativa RefSeq were ignored in the alignment analysis (Table 3). All 12 SyMAP alignment results are available at [35].

Synteny analysis pipeline and incorporation of data in the CMap, Genome Browser and SyntenyView displays in Gramene

We constructed a pipeline to align clones and contigs from the OMAP species to O. sativa by combining data from the BES alignments to O. sativa and the phase I physical maps. The pipeline consisted of 6 steps: 1) upload phase I physical maps and BES data, 2) align BES to the RefSeq, 3) determine the best alignments for each clone, 4) assemble the clone positions to determine the region where the contig is found to align, 5) create blocks of synteny between selected OMAP species and O. sativa, 6) utilize the data to create visualizations in CMap, the Genome Browser, and SyntenyView in Gramene. Details on each step can be found at [62] Screen shots of the data in Gramene are shown in Additional data file 9.

Repeat analysis

RepeatMasker (V3.1.5), loaded with a custom Oryza repeat database, was used to identify repeats from the Oryza BES data set and the O. sativa RefSeq. The custom database was composed of annotated repeats from: TIGR rice repeat database [63]; Dr Susan Wessler (University of Georgia, USA); and Dr Tom Bureau (McGill University, Canada).

RECON [37] was used to identify de novo repeats from the Oryza BES data set. To increase the speed and efficiency of the program, the BLAST output was parsed to discard self hits as well as hits with an e-value greater than 1e-5. The RECON output, which identified repetitive elements and classified them into distinct families, was parsed for sequences greater than 40 bp in length that were found at least 5 times/family. Overlap between the de novo and the custom library was determined using RepeatMasker. Sequences left unmasked by this process and, thus, were not a part of our custom repeat database, were extracted, assembled using PHRAP [64] and annotated using BLASTN at an e-value = 1e-4 against the NCBI non-redundant nucleotide database [65] and a dataset of 2,050 full length LTR-retrotransposons identified from the whole genome sequence of Nipponbare through LTR_STRUC [66]. Finally, these sequences were compiled into repeat databases specific to each species. The procedure is outlined in Additional data file 10.

Simple sequence repeat analysis

A total of 20,064 SSRs were identified from 1,452,912 BESs using RepeatMasker (V3.1.5) with a cutoff of longer than 20 bp and less than 5% sequence divergence. BESs containing SSRs (SSR-BES) were assembled for each species using CAP3 [67] to collect a total of 16,980 non-redundant SSRs. An SSR was considered redundant when the BAC clones came from the same FPC contig, and an assembled CAP contig contained the same SSR motif, repeat length and sequence divergence. Abundance and relative frequency of SSRs from the Oryza BESs were compared to SSRs identified from two rice genomic sequences: 20,653 SSRs from the japonica RefSeq [18] and 19,370 from the indica draft [68, 69] sequences using identical criteria. Other interspersed repeats in SSR-BESs were detected using RepeatMasker with a custom repeat database (courtesy of Dr Ning Jiang, Michigan State University).

Identification of OryzamiRNA genes

O.sativa japonica miRNA precursors from miRBase (Version 8.2) [70], including 250 nucleotides upstream and downstream, were extracted from the O. sativa RefSeq [18] and aligned, using BLASTN [71], against BES of four closely related wild rice species (AA and BB genomes). Alignments were filtered and multiple hits to the same region of a BES were discarded, keeping the hit with the lowest e-value. The best orthologous match typically had more conservation in the region surrounding the precursor and, therefore, had a much lower e-value. If two miRNAs aligned to different regions of the same BES, they were not discarded, since they were likely to be tandemly duplicated miRNA genes. To obtain the exact coordinates and secondary structure of the miRNA precursor within the remaining BES, a pattern matching approach was used to align the mature miRNA precursor to the BES. Once the mature miRNA was mapped to the BES, the extended sequence was then submitted to MFold to determine if it could form a stable hairpin structure [72]. MFold alignments were checked for the following criteria: had conserved orientation; contained fewer than eight mismatches; was not overlapping the loop region; and lacked some types of asymmetric bulges. A precursor was discarded if the bulge had four or more nucleotides that failed to match with any nucleotide from the opposite strand. A precursor was retained if a bulge of four or fewer nucleotides on one stem corresponded, although not necessarily matching, with one or more nucleotides on the opposite strand. If the sequence that aligned to the mature miRNA met these criteria, it was categorized as the opposing stem (miRNA*). Both stems and the intervening loop region were extracted and resubmitted as input to MFold. If this refined sequence formed a stable hairpin structure under the four conditions, it was categorized as a paralogous miRNA precursor.

Variation discovery

BES trace files from O. rufipogon, O. nivara, O. glaberrima and O. punctata were compared to the O. sativa genome with BLASTZ [46] using the S1-S2 scoring method to select only the best alignment for each read. Each chromosome was then divided into 5 Mb segments and BESs aligned to each region from the previous step were re-aligned to the segment using cross_match [64] (-bandwidth 100 -alignments -discrep_lists) with variation filtering using the neighborhood quality standard (NQS) [73]. Settings for NQS were such that candidate variation in the read had a Phred quality value (Q) of at least 23, its neighboring 7 bases on either side of the candidate variation all had Phred quality values of ≥ 15 and at least 11 of the 14 neighbors matched. If a read aligned to more than one place in the genome, then only the longest alignment with the fewest SNVs was reported. To decrease the number of false positive insertions or deletions, variations were filtered out if they had a single base variation and the quality score was less than 40 or if they were multiple base variations and the quality score was less than 23. Since two assemblies of the O. sativa RefSeq were available (IRGSP V.4 and TIGR V.4), variations were detected using both assemblies (Additional data file 8a-d). All data have been deposited into dbSNP and can be viewed at Gramene [49].

Additional data files

The following additional data are available with the online version of this paper. Additional data file 1 is a figure describing the SyMAP display details. Additional data file 2 is a table listing distribution of CB units from the O. sativa reference genome aligned contigs to each chromosome of 12 OMAP phase I physical maps. Additional data file 3 is a figure showing correlation of genome size and repeat content in the genus Oryza. Additional data file 4 is a figure presenting a comparison of MITE compositions in 12 OMAP genomes and the O. sativa genome. Additional data file 5 is a figure showing distribution of OMAP non-redundant SSR by motif types. Additional data file 6 is a table listing repeat association analysis for TAA and CAA motifs of O. ridleyi and O. granulata and BLAST analysis of CAA-BESs. Additional data file 7 is a figure comparing the SSR length and sequence compositions of OMAP SSR motifs. Additional data file 8 is a table listing SNVs and INDELs found between the BESs for O. rufipogon, O. nivara, O. glaberrima, O. punctata and the IRGSP V.4 pseudomolecules (or the TIGR V.4 pseudomolecules). Additional data file 9 is a figure describing wild rice BESs and variation data at Gramene. Additional data file 10 is a figure showing the strategy of repeat analysis and classification using the OMAP BES resources.



bacterial artificial chromosome


BAC end sequence


consensus band


insertions and deletions


International Rice Genome Sequencing Project


long terminal repeat




miniature inverted repeat transposable element


Oryza map alignment project


reference sequence


single nucleotide variation


simple sequence repeat


The Institute for Genomic Research.


  1. 1.

    Riesenfeld CS, Schloss PD, Handelsman J: Metagenomics: genomic analysis of microbial communities. Annu Rev Genet. 2004, 38: 525-552. 10.1146/annurev.genet.38.072902.091216.

    PubMed  CAS  Article  Google Scholar 

  2. 2.

    Ciccarelli FD, Doerks T, Mering CV, Creevey CJ, Sne B, Bork P: Toward automatic reconstruction of a highly resolved tree of life. Science. 2006, 311: 1283-1287. 10.1126/science.1123061.

    PubMed  CAS  Article  Google Scholar 

  3. 3.

    Galagan JE, Calvo SE, Cuomo C, Ma LJ, Wortman JR, Batzoglou S, Lee SI, Basturkmen M, Spevak CC, Clutterbuck J, Kapitonov V, Jurka J, Scazzocchio C, Farman M, Butler J, Purcell S, Harris S, Braus GH, Draht O, Busch S, D'Enfert C, Bouchier C, Goldman GH, Bell-Pedersen D, Griffiths-Jones S, Doonan JH, Yu J, Vienken K, Pain A, Freitag M, et al: Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae. Nature. 2005, 438: 1105-1115. 10.1038/nature04341.

    PubMed  CAS  Article  Google Scholar 

  4. 4.

    Thomas JW, Touchman JW: Vertebrate genome sequencing: building a backbone for comparative genomics. Trends Genet. 2002, 18: 104-108. 10.1016/S0168-9525(02)02599-4.

    PubMed  CAS  Article  Google Scholar 

  5. 5.

    Yogeeswaran K, Frary A, York TL, Amenta A, Lesser AH, Nasrallah JB, Tanksley SD, Nasrallah ME: Comparative genome analyses of Arabidopsis spp.: inferring chromosomal rearrangement events in the evolutionary history of A. thaliana. Genome Res. 2005, 15: 505-515. 10.1101/gr.3436305.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  6. 6.

    Devos KM: Updating the 'crop circle'. Curr Opin Plant Biol. 2005, 8: 155-162. 10.1016/j.pbi.2005.01.005.

    PubMed  CAS  Article  Google Scholar 

  7. 7.

    Town CD, Cheung F, Maiti R, Crabtree J, Haas BJ, Wortman JR, Hine EE, Althoff R, Arbogast TS, Tallon LJ, Vigouroux M, Trick M, Bancroft I: Comparative genomics of Brassica oleracea and Arabidopsis thaliana reveal gene loss, fragmentation, and dispersal after polyploidy. Plant Cell. 2006, 18: 1348-1359. 10.1105/tpc.106.041665.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  8. 8.

    Suwabe K, Tsukazaki H, Iketani H, Hatakeyama K, Kondo M, Fujimura M, Nunome T, Fukuoka H, Hirai M, Matsumoto S: Simple sequence repeat-based comparative genomics between Brassica rapa and Arabidopsis thaliana: the genetic origin of clubroot resistance. Genetics. 2006, 173: 309-319. 10.1534/genetics.104.038968.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  9. 9.

    Patterson N, Richter DJ, Gnerre S, Lander ES, Reich D: Genetic evidence for complex speciation of humans and chimpanzees. Nature. 2006, 441: 1103-1108. 10.1038/nature04789.

    PubMed  CAS  Article  Google Scholar 

  10. 10.

    Peng JH, Zadeh H, Lazo GR, Gustafson JP, Chao S, Anderson OD, Qi LL, Echalier B, Gill BS, Dilbirligi M, Sandhu D, Gill KS, Greene RA, Sorrells ME, Akhunov ED, Dvorák J, Linkiewicz AM, Dubcovsky J, Hossain KG, Kalavacharla V, Kianian SF, Mahmoud AA, Miftahudin , Conley EJ, Anderson JA, Pathan MS, Nguyen HT, McGuire PE, Qualset CO, Lapitan NL: Chromosome bin map of expressed sequence tags in homoeologous group 1 of hexaploid wheat and homoeology with rice and Arabidopsis. Genetics. 2004, 168: 609-623. 10.1534/genetics.104.034793.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  11. 11.

    Bossolini E, Wicker T, Knobel PA, Keller B: Comparison of orthologous loci from small grass genomes Brachypodium and rice: implications for wheat genomics and grass genome annotation. Plant J. 2007, 49: 704-717. 10.1111/j.1365-313X.2006.02991.x.

    PubMed  CAS  Article  Google Scholar 

  12. 12.

    Mouse Genome Sequencing Consortium, Waterston RH, Lindblad-Toh K, Birney E, Rogers J, Abril JF, Agarwal P, Agarwala R, Ainscough R, Alexandersson M, An P, Antonarakis SE, Attwood J, Baertsch R, Bailey J, Barlow K, Beck S, Berry E, Birren B, Bloom T, Bork P, Botcherby M, Bray N, Brent MR, Brown DG, Brown SD, Bult C, Burton J, Butler J, Campbell RD: Initial sequencing and comparative analysis of the mouse genome. Nature. 2002, 420: 520-562. 10.1038/nature01262.

    Article  Google Scholar 

  13. 13.

    Prabhakar S, Poulin F, Shoukry M, Afzal V, Rubin EM, Couronne O, Pennacchio LA: Close sequence comparisons are sufficient to identify human cis-regulatory elements. Genome Res. 2006, 16: 855-863. 10.1101/gr.4717506.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  14. 14.

    Grover CE, Kim H, Wing RA, Paterson AH, Wendel JF: Incongruent patterns of local and global genome size evolution in cotton. Genome Res. 2004, 14: 1474-1482. 10.1101/gr.2673204.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  15. 15.

    Hurle B, Swanson W, NISC Comparative Sequencing Program, Green ED: Comparative sequence analyses reveal rapid and divergent evolutionary changes of the WFDC locus in the primate lineage. Genome Res. 2007, 17: 276-286. 10.1101/gr.6004607.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  16. 16.

    Drosophila 12 Genomes Consortium: Evolution of genes and genomes on the Drosophila phylogeny. Nature. 2007, 450: 203-218. 10.1038/nature06341.

    Article  Google Scholar 

  17. 17.

    Arabidopsis Genome Initiative (AGI): Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature. 2000, 408: 796-815. 10.1038/35048692.

    Article  Google Scholar 

  18. 18.

    International Rice Genome Sequencing Project (IRGSP): The map-based sequence of the rice genome. Nature. 2005, 436: 793-800. 10.1038/nature03895.

    Article  Google Scholar 

  19. 19.

    Peng S, Cassman KG, Virmani SS, Sheehy J, Khush GS: Yield potential trends of tropical rice since the release of IR8 and the challenge of increasing rice yield potential. Crop Sci. 1999, 39: 1552-1559.

    Article  Google Scholar 

  20. 20.

    International Rice Research Institute (IRRI): Rice Germplasm: Collecting, Preservation, Use. 1991, Manila: IRRI

    Google Scholar 

  21. 21.

    Vaughan DA, Morishima H, Kadowaki K: Diversity in the Oryza genus. Curr Opin Plant Biol. 2003, 6: 139-146. 10.1016/S1369-5266(03)00009-8.

    PubMed  CAS  Article  Google Scholar 

  22. 22.

    Tateoka T: Taxonomic studies of Oryza III. Key to the species and their enumeration. Bot Mag Tokyo. 1963, 76: 165-173.

    Article  Google Scholar 

  23. 23.

    Tateoka T: Notes of some grasses. XVI. Embryo structure of the genus Oryza in relation to their systematics. Am J Bot. 1964, 51: 539-543. 10.2307/2440283.

    Article  Google Scholar 

  24. 24.

    Nayar M: Origin and cytogenetics of rice. Adv Genet. 1973, 17: 153-292.

    Article  Google Scholar 

  25. 25.

    Li CB, Zhang DM, Ge S, Lu BR, Hong DY: Differentiation and inter-genomic relationships among C, E and D genomes in the Oryza officinalis complex (Poaceae) as revealed by multicolor genomic in situ hybridization. Theor Appl Genet. 2001, 103: 197-203. 10.1007/s001220100562.

    CAS  Article  Google Scholar 

  26. 26.

    de Wit JMJ: Concepts and systematics of domesticated cereals. Kulturpflanze. 1981, 29: 177-198. 10.1007/BF02014749.

    Article  Google Scholar 

  27. 27.

    Juliano AB, Naredo MEB, Jackson MT: Taxonomic status of Oryza glumaepatula Steud. I. Comparative morphological studies of New World diploids and Asian AA genome species. Genet Res Crop Evol. 1998, 45: 197-203. 10.1023/A:1008682316449.

    Article  Google Scholar 

  28. 28.

    Ge S, Sang T, Lu BR, Hong DY: Phylogeny of rice genomes with emphasis on origins of allotetraploid species. Proc Natl Acad Sci. 1999, 96: 14400-14405. 10.1073/pnas.96.25.14400.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  29. 29.

    Brar DS, Khush GS: Alien introgression in rice. Plant Mol Biol. 1997, 35: 35-47. 10.1023/A:1005825519998.

    PubMed  CAS  Article  Google Scholar 

  30. 30.

    Ammiraju JS, Luo M, Goicoechea JL, Wang W, Kudrna D, Mueller C, Talag J, Kim H, Sisneros NB, Blackmon B, Fang E, Tomkins JB, Brar D, MacKill D, McCouch S, Kurata N, Lambert G, Galbraith DW, Arumuganathan K, Rao K, Walling JG, Gill N, Yu Y, SanMiguel P, Soderlund C, Jackson S, Wing RA: The Oryza bacterial artificial chromosome library resource: construction and analysis of 12 deep-coverage large-insert BAC libraries that represent the 10 genome types of the genus Oryza. Genome Res. 2006, 16: 140-147. 10.1101/gr.3766306.

    PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Kim H, SanMiguel P, Nelson W, Collura K, Wissotski M, Walling JG, Kim JP, Jackson SA, Soderlund C, Wing RA: Comparative physical mapping between O. sativa (AA genome type) and O. punctata (BB genome type). Genetics. 2007, 176: 379-390. 10.1534/genetics.106.068783.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  32. 32.

    Soderlund C, Humphray S, Dunham A, French L: Contigs built with fingerprints, markers, and FPC V4.7. Genome Res. 2000, 10: 1772-1787. 10.1101/gr.GR-1375R.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  33. 33.

    Pampanwar V, Engler F, Hatfield J, Blundy S, Gupta G, Soderlund C: FPC Web tools for rice, maize, and distribution. Plant Physiol. 2005, 138: 116-126. 10.1104/pp.104.056291.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  34. 34.

    Soderlund C, Nelson W, Shoemaker A, Paterson A: SyMAP: a system for discovering and viewing syntenic regions of FPC maps. Genome Res. 2006, 16: 1159-1168. 10.1101/gr.5396706.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  35. 35.

    OMAP SyMAP. []

  36. 36.

    RepeatMasker. []

  37. 37.

    Bao Z, Eddy SR: Automated de novo identification of repeat sequence families in sequenced genomes. Genome Res. 2002, 12: 1269-1276. 10.1101/gr.88502.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  38. 38.

    Piegu B, Guyot R, Picault N, Roulin A, Saniyal A, Kim H, Collura K, Brar DS, Jackson S, Wing RA, Panaud O: Doubling genome size without polyploidization: dynamics of retrotransposition-driven genomic expansions in Oryza australiensis, a wild relative of rice. Genome Res. 2006, 16: 1262-1269. 10.1101/gr.5290206.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  39. 39.

    Zuccolo A, Sebastian A, Talag J, Yu Y, Kim H, Collura K, Kudrna D, Wing RA: Transposable element distribution, abundance and role in genome size variation in the genus Oryza. BMC Evol Biol. 2007, 7: 152-10.1186/1471-2148-7-152.

    PubMed  PubMed Central  Article  Google Scholar 

  40. 40.

    Palatnik JF, Allen E, Wu X, Schommer C, Schwab R, Carrington JC, Weigel D: Control of leaf morphogenesis by microRNAs. Nature. 2003, 425: 257-263. 10.1038/nature01958.

    PubMed  CAS  Article  Google Scholar 

  41. 41.

    Vaucheret H, Vazquez F, Crete P, Bartel DP: The action of ARGONAUTE1 in the miRNA pathway and its regulation by the miRNA pathway are crucial for plant development. Genes Dev. 2004, 18: 1187-1197. 10.1101/gad.1201404.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  42. 42.

    Allen E, Xie Z, Gustafson AM, Carrington JC: MicroRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell. 2005, 121: 207-221. 10.1016/j.cell.2005.04.004.

    PubMed  CAS  Article  Google Scholar 

  43. 43.

    Vaucheret H: Post-transcriptional small RNA pathways in plants: mechanisms and regulations. Genes Dev. 2006, 20: 759-771. 10.1101/gad.1410506.

    PubMed  CAS  Article  Google Scholar 

  44. 44.

    Maher C, Stein L, Ware D: Evolution of Arabidopsis microRNA families through duplication events. Genome Res. 2006, 16: 510-519. 10.1101/gr.4680506.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  45. 45.

    Margulies EH, Vinson JP, Miller W, Jaffe DB, Lindblad-Toh K, Chang JL, Green ED, Lander ES, Mullikin JC, Clamp M: An initial strategy for the systematic identification of functional elements in the human genome by low-redundancy comparative sequencing. Proc Natl Acad Sci. 2005, 102: 4795-4800. 10.1073/pnas.0409882102.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  46. 46.

    Schwartz S, Kent WJ, Smit A, Zhang Z, Baertsch R, Hardison RC, Haussler D, Miller W: Human-mouse alignments with BLASTZ. Genome Res. 2003, 13: 103-107. 10.1101/gr.809403.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  47. 47.

    Beijing Genomics Institute. []

  48. 48.

    Feltus A, Wan J, Schulze S, Estill J, Jiang N, Paterson A: An SNP resource for rice genetics and breeding based on subspecies Indica and Japonica genome assemblies. Genome Res. 2004, 14: 1812-1819. 10.1101/gr.2479404.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  49. 49.

    Gramene. []

  50. 50.

    The Oryza Map Alignment Project (OMAP). []

  51. 51.

    Ammiraju JS, Zuccolo A, Yu Y, Song X, Piegu B, Chevalier F, Walling JG, Ma J, Talag J, Brar DS, SanMiguel PJ, Jiang N, Jackson SA, Panaud O, Wing RA: Evolutionary dynamics of an ancient retrotransposon family provides insights into evolution of genome size in the genus Oryza. Plant J. 2007, 52: 342-351. 10.1111/j.1365-313X.2007.03242.x.

    PubMed  CAS  Article  Google Scholar 

  52. 52.

    Zhang S, Gu YQ, Singh J, Coleman-Derr D, Brar DS, Jiang N, Lemaux PG: New insights into Oryza genome evolution: high gene colinearity and differential retrotransposon amplification. Plant Mol Biol. 2007, 64: 589-600. 10.1007/s11103-007-9178-3.

    PubMed  CAS  Article  Google Scholar 

  53. 53.

    Hass-Jacobus BL, Futrell-Griggs M, Abernathy B, Westerman R, Goicoechea JL, Stein J, Klein P, Hurwitz B, Zhou B, Rakhshan F, Sanyal A, Gill N, Lin JY, Walling JG, Luo MZ, Ammiraju JS, Kudrna D, Kim HR, Ware D, Wing RA, San Miguel P, Jackson SA: Integration of hybridization-based markers (overgos) into physical maps for comparative and evolutionary explorations in the genus Oryza and in Sorghum. BMC Genomics. 2006, 7: 199-10.1186/1471-2164-7-199.

    PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Lu J, Tang T, Tang H, Huang J, Shi S, Wu CI: The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication. Trends Genet. 2006, 22: 126-131. 10.1016/j.tig.2006.01.004.

    PubMed  CAS  Article  Google Scholar 

  55. 55.

    Tang T, Lu J, Huang J, He J, McCouch SR, Shen Y, Kai Z, Purugganan MD, Shi S, Wu CI: Genomic variation in rice: genesis of highly polymorphic linkage blocks during domestication. PLoS Genet. 2006, 2: e199-10.1371/journal.pgen.0020199.

    PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    The Rice Chromosome 3 Sequencing Consortium: Sequence, annotation, and analysis of synteny between rice chromosome 3 and diverged grass species. Genome Res. 2005, 15: 1284-1291. 10.1101/gr.3869505.

    Article  Google Scholar 

  57. 57.

    Roberto R, Capozzi O, Wilson RK, Mardis ER, Lomiento M, Tuzun E, Cheng Z, Mootnick AR, Archidiacono N, Rocchi M, Eichler EE: Molecular refinement of gibbon genome rearrangements. Genome Res. 2007, 17: 249-257. 10.1101/gr.6052507.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  58. 58.

    Newman TL, Tuzun E, Morrison VA, Hayden KE, Ventura M, McGrath SD, Rocchi M, Eichler EE: A genome-wide survey of structural variation between human and chimpanzee. Genome Res. 2005, 15: 1344-1356. 10.1101/gr.4338005.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  59. 59.

    Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk GP, Jando SC, Alenquer ML, Jarvie TP, Jirage KB, Kim JB, Knight JR, Lanza JR, Leamon JH, Lefkowitz SM, Lei M, Li J, et al: Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005, 437: 376-380.

    PubMed  CAS  PubMed Central  Google Scholar 

  60. 60.

    AGI BAC/EST Resource Center. []

  61. 61.

    Kent WJ: BLAT - the BLAST-like alignment tool. Genome Res. 2002, 12: 656-664. 10.1101/gr.229202. Article published online before March 2002.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  62. 62.

    GRAMENE: Synteny Analysis Pipeline. []

  63. 63.

    TIGR Rice Repeat Database. []

  64. 64.

    PHRAP. []

  65. 65.

    NCBI non-redundant nucleotide database. []

  66. 66.

    McCarthy EM, McDonald JF: LTR_STRUC: a novel search and identification program for LTR retrotransposons. Bioinformatics. 2003, 19: 362-367. 10.1093/bioinformatics/btf878.

    PubMed  CAS  Article  Google Scholar 

  67. 67.

    Huang X, Madan A: CAP3: a DNA sequence assembly program. Genome Res. 1999, 9: 868-877. 10.1101/gr.9.9.868.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  68. 68.

    Yu J, Hu S, Wang J, Wong GK, Li S, Liu B, Deng Y, Dai L, Zhou Y, Zhang X, Cao M, Liu J, Sun J, Tang J, Chen Y, Huang X, Lin W, Ye C, Tong W, Cong L, Geng J, Han Y, Li L, Li W, Hu G, Huang X, Li W, Li J, Liu Z, Li L, et al: A draft sequence of the rice genome (Oryza sativa L. ssp. indica). Science. 2002, 296: 79-92. 10.1126/science.1068037.

    PubMed  CAS  Article  Google Scholar 

  69. 69.

    Yu J, Wang J, Lin W, Li S, Li H, Zhou J, Ni P, Dong W, Hu S, Zeng C, Zhang J, Zhang Y, Li R, Xu Z, Li S, Li X, Zheng H, Cong L, Lin L, Yin J, Geng J, Li G, Shi J, Liu J, Lv H, Li J, Wang J, Deng Y, Ran L, Shi X, et al: The genomes of Oryza sativa : a history of duplications. PLoS Biol. 2005, 3: e38-10.1371/journal.pbio.0030038.

    PubMed  PubMed Central  Article  Google Scholar 

  70. 70.

    Griffiths-Jones S: miRBase: The microRNA sequence database. Methods Mol Biol. 2006, 342: 129-138.

    PubMed  CAS  Google Scholar 

  71. 71.

    Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ: Basic local alignment search tool. J Mol Biol. 1990, 215: 403-410.

    PubMed  CAS  Article  Google Scholar 

  72. 72.

    Mathews DH, Sabina J, Zuker M, Turner DH: Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J Mol Biol. 1999, 288: 911-940. 10.1006/jmbi.1999.2700.

    PubMed  CAS  Article  Google Scholar 

  73. 73.

    The International SNP Map Working Group: A map of human genome sequence variation containing 1.4 million single nucleotide polymorphisms. Nature. 2001, 409: 928-933. 10.1038/35057149.

    Article  Google Scholar 

Download references


We thank Dr K Arumuganathan (Virginia Mason Research Center, Seattle, WA, USA) for determining the genome size of O. coarctata [HHJJ]. This work was supported by National Science Foundation grant DBI-0321678 (to RAW, SJ, LS, CS), the Bud Antle Endowed Chair (to RAW), and the Intramural Research Program of the National Human Genome Research Institute, National Institutes of Health (to LS).

Author information



Corresponding author

Correspondence to Rod A Wing.

Additional information

Authors' contributions

HK, LS, DW, SAJ, and RAW designed the research; HK, KC, PS, MW, DK, and JLG performed the research; WN, MB, and CS contributed analytical tools; HK, BH, YY, NG, PS, JCM, and CM analyzed the data; HK, BH, YY, NG, PS, CM, WN, LS, DW, SAJ, CS, and RAW wrote the paper.

Electronic supplementary material

Additional data file 1: SyMAP display details. (DOC 2 MB)

Additional data file 2: Distribution of CB units from the O. sativa reference genome aligned contigs to each chromosome of 12 OMAP phase I physical maps. (DOC 30 KB)

Additional data file 3: Correlation of genome size and repeat content in the genus Oryza. (DOC 102 KB)

Additional data file 4: Comparison of MITE compositions in 12 OMAP genomes and the O. sativa genome. (DOC 85 KB)

Additional data file 5: Distribution of OMAP non-redundant SSR by motif types. (DOC 27 KB)

Additional data file 6: Repeat association analysis for TAA and CAA motifs of O. ridleyi and O. granulata and BLAST analysis of CAA-BESs. (DOC 40 KB)

Additional data file 7: Comparison of the SSR length and sequence compositions of OMAP SSR motifs. (DOC 41 KB)

Additional data file 8: SNVs and INDELs found between the BESs for O. rufipogon, O. nivara, O. glaberrima, O. punctata and the IRGSP V.4 pseudomolecules (or the TIGR V.4 pseudomolecules). (DOC 30 KB)

Additional data file 9: Wild rice BESs and variation data at Gramene. (DOC 324 KB)

Additional data file 10: The strategy of repeat analysis and classification using the OMAP BES resources. (DOC 31 KB)

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Authors’ original file for figure 3

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Kim, H., Hurwitz, B., Yu, Y. et al. Construction, alignment and analysis of twelve framework physical maps that represent the ten genome types of the genus Oryza. Genome Biol 9, R45 (2008).

Download citation


  • Bacterial Artificial Chromosome
  • Additional Data File
  • Bacterial Artificial Chromosome Library
  • Single Nucleotide Variation
  • Genome Type