Tiling microarray analysis of rice chromosome 10 to identify the transcriptome and relate its expression to chromosomal architecture
- Lei Li†1,
- Xiangfeng Wang†2, 3, 4,
- Mian Xia5,
- Viktor Stolc1, 6,
- Ning Su1,
- Zhiyu Peng2,
- Songgang Li3,
- Jun Wang4,
- Xiping Wang5 and
- Xing Wang Deng1Email author
© Li et al.; licensee BioMed Central Ltd. 2005
Received: 14 January 2005
Accepted: 25 April 2005
Published: 27 May 2005
Sequencing and annotation of the genome of rice (Oryza sativa) have generated gene models in numbers that top all other fully sequenced species, with many lacking recognizable sequence homology to known genes. Experimental evaluation of these gene models and identification of new models will facilitate rice genome annotation and the application of this knowledge to other more complex cereal genomes.
We report here an analysis of the chromosome 10 transcriptome of the two major rice subspecies, japonica and indica, using oligonucleotide tiling microarrays. This analysis detected expression of approximately three-quarters of the gene models without previous experimental evidence in both subspecies. Cloning and sequence analysis of the previously unsupported models suggests that the predicted gene structure of nearly half of those models needs improvement. Coupled with comparative gene model mapping, the tiling microarray analysis identified 549 new models for the japonica chromosome, representing an 18% increase in the annotated protein-coding capacity. Furthermore, an asymmetric distribution of genome elements along the chromosome was found that coincides with the cytological definition of the heterochromatin and euchromatin domains. The heterochromatin domain appears to associate with distinct chromosome level transcriptional activities under normal and stress conditions.
These results demonstrated the utility of genome tiling microarray in evaluating annotated rice gene models and in identifying novel transcriptional units. The tiling microarray sanalysis further revealed a chromosome-wide transcription pattern that suggests a role for transposable element-enriched heterochromatin in shaping global transcription in response to environmental changes in rice.
As one of the most important crop species in the world and a model for the Gramineae family, rice (Oryza sativa) was selected as the first monocotyledonous plant to have its genome completely sequenced. Draft genome sequences of the two major subspecies of rice, indica and japonica, were made available in 2002 [1, 2]. These were followed by the advanced sequences of japonica chromosomes 1, 4 and 10 [3–5]. The finish-quality whole-genome sequences of indica and japonica have recently been obtained [6–8].
Available rice sequences have been subjected to extensive annotation using ab initio gene prediction, comparative genomics, and a variety of other methods. These analyses revealed abundant compositional and structural features of the predicted rice genes that deviate from genes in other model organisms. For example, distinctive negative gradients of GC content, codon usage, and amino-acid usage along the direction of transcription were observed in many rice gene models [2, 9]. On the other hand, many predicted rice genes that lack significant homology to genes in other organisms also exhibit characteristics such as unusual GC composition and distribution, suggesting that they might not be true genes [10, 11]. Furthermore, the abundance and diversity of transposable elements (TEs) within the rice genome that possess a coding capacity pose an additional challenge to accurate annotation of the rice genome [10, 12, 13].
As such, our understanding of the rice genome is largely limited to the state-of-the-art gene prediction and annotation programs. This is probably best reflected by the lack of a consensus of the estimation of the total gene number in rice [6–8, 10, 11]. Estimated total gene number based on the draft sequences of japonica and indica ranged widely from 30,000 to 60,000 [1, 2]. Finished sequences of chromosome 1, 4 and 10 allowed a more finely tuned estimate that placed the total number of rice genes between 57,000 and 62,500 [3–5]. These estimates included a large number of gene models that contain TE-related open reading frames (ORFs). Excluding the TE-related ORFs could reduce the gene number to about 45,000 [6–8]. Even then, between one third and one half of the predicted genes appear to have no recognizable homologs in the other model plant Arabidopsis thaliana [6–8]. Further, aggressive manual annotations of portions of the finished rice sequence have disqualified many of the low-homology gene models as TE-related or artifacts, arguing that there are no more than 40,000 nonredundant genes in rice .
Experimental evidence such as full-length cDNA sequences and expressed sequence tags (ESTs) is critical for evaluation and improvement of the genome annotation [14–16]. Large collections of rice full-length cDNA and ESTs are available [15, 17]; however, given the large number of rice genes, current methods for collecting expressed sequences do not provide the necessary depth of coverage. For example, based on high-stringency alignments to EST sequences available at that time, only 24.7% of the 3,471 initially predicted genes of chromosome 10 were matched . Conversely, other experiment-oriented approaches, such as massively parallel signature sequencing , are able to provide sufficient coverage of the transcriptome but by their nature are limited in their ability to define gene structures. Thus, it is important to survey the transcriptome using additional experimental means that permit detailed analyses of current gene models and the identification of new models.
Recent studies in several model organisms have demonstrated the utility of tiling microarrays in transcriptome identification [19–27]. Armed with new microarray technologies, it is now possible to prepare high-density oligonucleotide tiling microarrays to interrogate genomic sequences irrespective of their annotations. Consequently, results from these studies indicate that a significant portion of the transcriptome resides outside the predicted coding regions [19–21, 24, 25]. In addition, these studies show that tiling microarrays are able to improve or correct the predicted gene structures [19, 23, 26]. Based on considerations of feature density, versatility of modification, and compatibility with our existing conventional microarray facility, the maskless array synthesizer (MAS) platform [24, 26, 28, 29] was chosen for our rice transcriptome analysis.
Here we report the construction and analysis of two independent sets of custom high-density oligonucleotide tiling microarrays with unique 36-mer probe sequences tiled throughout the nonrepetitive sequences of chromosome 10 for both japonica and indica rice. Hybridized with a mixed pool of cDNA targets, these tiling microarrays detected over 80% of the annotated nonredundant gene models in both japonica and indica, and identified a large number of transcriptionally active intergenic regions. These results, coupled with comparative gene model mapping and reverse transcription PCR (RT-PCR) analysis, allowed the first comprehensive identification and analysis of a rice chromosomal transcriptome. These results further revealed an association of chromosome 10 transcriptome regulation with the euchromatin-heterochromatin organization at the chromosomal level.
Rice chromosome 10 oligonucleotide tiling microarrays
Based on recent studies using MAS oligonucleotide tiling microarrays to obtain gene expression and structure information [24, 26, 28, 29], we designed two independent sets of 36-mer probes, with 10-nucleotide intervals, tiled throughout both strands of japonica and indica chromosome 10, respectively. After filtering out those probes that represent sequences with a high copy number or a high degree of complementarity, 750,282 and 838,816 probes were retained to interrogate the entire nonrepetitive sequences of japonica and indica chromosome 10 and were synthesized in two sets of MAS microarrays [24, 26, 29]. The arrays were hybridized with target cDNA prepared from equal amounts of four selected poly(A)+ RNA populations (the N Arrays), namely, seedling roots, seedling shoots, panicles, and suspension cultured cells of the respective rice subspecies. In addition, a set of japonica arrays was hybridized to shoot poly(A)+ RNA derived from seedlings with a mineral/nutrient disturbance (the S Arrays).
Rice chromosome 10 gene models
Classification and array detection of rice chromosome 10 gene models
Nonredundant protein-coding gene model
For comparison, the so-called BGI japonica gene models were included, whereby the japonica chromosome 10 sequence was independently annotated by the Beijing Genomics Institute (BGI) [6, 30]. This model set, generated by the FGENESH output with limited full-length cDNA/EST input, contains 851 TE, 943 CG, 272 EG, and 1,549 UG models (Table 1, Figure 2). To analyze the indica chromosome 10 transcriptome, and for comparative analysis, the BGI indica models were also examined [2, 6, 30]. Classification of the indica models identified 574 TE, 821 CG, 328 EG, and 1,660 UG models (Table 1, Figure 2 and see Additional data file 2).
Tiling microarray detection of rice chromosome 10 gene models
Analysis of the N arrays detected 2,428 out of 2,809 BGI indica (86.4%), 2,319 out of 2,764 BGI japonica (83.9%), and 2,472 out of 3,019 TIGR japonica (81.9%) nonredundant gene models (Table 1). Although no technical replication was performed, several observations indicate that tiling microarray analysis provides a reliable evaluation of the expression of the gene models. First, consistent with their classification, gene models with previous experimental support (CG and EG) showed a higher detection rate than the unsupported models (Table 1). For example, 93.2% and 90.7% of the TIGR japonica CG and EG models were detected, respectively, whereas only 74.3% of the UG models were (Table 1). Second, supported models (CG and EG) exhibited very similar array detection rates across the three sets of gene models. Because the same cDNA and ESTs were used to classify the three sets of gene models, this result implies a strong correlation between tiling microarray detection and expressed sequences. In supporting of this conclusion, TIGR japonica models with at least one match with rice EST sequences exhibited a 92.7% (1,010 of 1,089) detection rate whereas only 75.7% (1,458 of 1,925) models without a matching EST were detected. Third, examination of signal probe distribution, measured by hybridization rate (HR, see Materials and methods), in the annotated exonic and intronic regions indicates that the tiling microarrays detected transcription predominantly locate in the exons. Across the three annotations, the HRs of both the intronic regions (dashed lines) and exonic regions (solid lines) showed bimodal distributions, with their respective major peaks well separated (Figure 1d). The minor intronic HR peak likely reflects transcriptional activities of exons misidentified as introns or in uncharacterized splice variants. Conversely, the minor exonic HR peak is likely to be due to misinterpretation of introns as exons, or exons or genes not expressed at all in the RNA populations used (Figure 1d).
Analysis of previously unsupported gene models
The relatively poor detection rate for the unsupported models suggests that their expression may be more restricted to specific cell types or developmental stages, thus eluding tiling array detection. Alternatively, some of these UG models might be false and do not represent real genes. For further analysis, gene models were classified as high homology (HH) and low homology (LH) models based on comparison using an expect value of e-7 for predicted protein homology between rice and Arabidopsis . It should be noted that the simple sequence alignment is likely to fail to detect some structural homology. However, this simple division is useful for separating two groups of gene models for expression comparison. For example, in the BGI japonica annotation, there are 589 UG/HH and 960 UG/LH models. By comparison, our tiling microarray detected 495 (84.0%) UG/HH models, but only 707 (73.7%) UG/LH models. Because the UG/LH models lack any previous supporting evidence (either homology or expression), concerns have been raised as to whether they represent real genes [10, 11]; therefore, the expression properties of the UG/LH models are of particular interest for further evaluation.
To investigate the possibility that expression of some UG/LH models is restricted to special conditions, we analyzed the S Arrays with regard to UG model expression. Of the gene models in the BGI japonica annotation, 63.4% were detected in seedling shoots under a variety of stress conditions that are known to significantly alter gene expression profiles [31, 32]. These included 39 (2 CG/HH, 2 EG/HH, 8 UG/HH, 2 CG/LH, 2 EG/LH and 23 UG/LH) models that eluded detection by the N Arrays. The enrichment of UG/LH models in S Arrays-specific models indicates that some UG/LH models indeed have specialized expression. Though it is entirely possible that additional UG/LH models could be detected under other stress conditions, the small number of UG/LH models specifically detected from the S Arrays (23 of 960, or 2.4%) suggests that specialized expression of UG/LH models alone may not account for the overall low detection rate of the UG/LH models.
Identification and analysis of intergenic TARs
Several lines of evidence support the idea that the majority of intergenic TARs represent legitimate elements of the rice transcriptome. Sequence analysis revealed that 301 (55.0%) indica and 455 (46.0%) japonica intergenic TARs possess a significant coding capacity (more than 50 amino acids). Selected intergenic TARs were used as probes in RNA gel-blot analysis to confirm expression of these TARs. Overall, 26 out of 34 probes detected a discrete band, with tissue specificity, whereas the rest failed to detect any, suggesting that the majority of the intergenic TARs correspond to in vivo transcripts rather than being caused by cross hybridization (Figure 4b-d). A total of 280 intergenic TARs were selected for further analysis using an RT-PCR strategy designed to clone transcripts containing an intergenic TAR and its entire downstream (3') sequence (see Materials and methods and Additional data file 5). Of the 77 cloned transcripts whose sequences could be unambiguously confirmed, 37 overlap with existing gene models (Figure 3b,d), suggesting they are uncharacterized portions, such as 5' or 3' untranslated regions (UTRs), or splice variants of the neighboring gene models. The rest of the confirmed transcripts (40 out of 77) were located entirely in intergenic regions, suggesting that they likely represent independent novel transcriptional units (Figure 3b,d).
To further characterize the 988 japonica intergenic TARs, they were aligned to the output of the rice gene finder BGF [2, 6, 30] using the japonica chromosome 10 sequence, and 72 novel gene models were identified (Additional data file 1). Comparison with the cloned intergenic TARs showed that 23 of the 40 cloned novel transcripts (57.5%) were also predicted in the novel BGF models (Figure 3b), indicating that the BGF program was able to detect half of the potential novel genes represented by the intergenic TARs. However, the incomplete nature of the 17 unaccounted transcripts (Figure 3b) made it difficult to unambiguously determine whether they encode proteins.
Tiling microarray-based gene model comparison and integration
To provide a comprehensive representation of the japonica chromosome 10 transcriptome, the 549 new models, including 363 BGI japonica models, 114 BGI indica models, and 72 novel BGF models (see above), were integrated with the TIGR japonica gene models (Figure 5b). The resulting 3,568 nonredundant protein-coding gene models, including the 3,019 TIGR models, represent an 18% increase in the annotated coding capacity of japonica chromosome 10 (Figure 5b). The integrated models included 3005 (84.2%) that were detected by tiling arrays, of which, 1,120 (31.4%) were not previously supported by expression data or homology. Thus, 3,255 (91.2%) models in the integrated set now have at least one piece of supporting evidence (for example, expressed sequences, homology, or tiling microarray) (Figure 5c). Classification of the array-detected and undetected models, based on exon number, homology to Arabidopsis genes, and previous supporting evidence, indicates that detection by our tiling microarray was not biased regarding gene structure and was in general agreement with all other annotation information (Figure 5c). These results demonstrate tiling microarray analysis as a useful platform to validate and incorporate information from multiple sources to fully identify the rice transcriptome.
Heterochromatin-associated regulation of chromosome-wide transcriptional activity
These results coincide with cytological data showing that domain I is primarily heterochromatin, whereas domain II is primarily euchromatin [5, 33]. Although it remains to be seen whether the phenomena mentioned above are general features associated with the division of heterochromatin and euchromatin in rice, these results collectively indicate that the heterochromatic domain of chromosome 10 is more evolutionarily active and compositionally dynamic. Our results further indicate that the genomic characteristics of the heterochromatin domain are associated with its transcriptional activities (Figure 6).
Sequencing of the rice genome provides a cornerstone to understand the biology of this agriculturally important crop [1–8, 34–36]. A first step in fully realizing the potential of available genome sequence is to understand its coding information and expression; however, current annotated gene models and other functional elements of a genome by and large represent hypotheses that must be experimentally tested and validated. Importantly, approximately 20,000 predicted rice genes exhibit no recognizable sequence homology to genes in other organisms, especially Arabidopsis, the first model plant sequenced [1–8]. The unusual compositional and structural features, as well as the lack of EST coverage for a large number of novel genes, require high-throughput experimental means that are not limited by the current annotations.
Identification of the rice chromosome 10 transcriptome by tiling microarrays
In this study, we developed whole-chromosome oligonucleotide tiling microarrays, and demonstrated their utility in experimentally identifying the transcriptome of both japonica and indica chromosome 10. Because oligonucleotide tiling microarrays provide unbiased end-to-end coverage of the entire chromosome and measure transcriptional activity of gene models from multiple independent probes (Figure 2), they can detect the transcriptome in a comprehensive and unbiased way [19–21, 23–25]. The tiling microarray analysis of rice chromosome 10 detected transcription of 86.4% BGI indica (2,428/2,809), 83.9% BGI japonica (2,319/2,764), and 81.9% TIGR japonica (2,472/3,019) gene models (Table 1). Using a set of the least reliable gene models (UG models, see below), RT-PCR analysis revealed disparity in gene structure of close to 50% of these models (Figure 3). These results are consistent with previous assessments of current computational gene finders, which can reliably locate a gene model in the correct chromosome locus, but are less than satisfactory to predict the fine gene structure [37, 38].
Based on alignment to rice full-length cDNA and EST sequences, the gene models for both japonica and indica chromosome 10 were classified as UG, EG, and CG models (Table 1, Figure 2). This classification places the gene models in three groups with an ascending order of confidence, because the presence of an expressed sequence provides strong support to the corresponding model. In keeping with this idea, these three classes of gene models were also detected by tiling microarrays in an ascending order (Table 1). This result, together with the high detection rate of CG models, suggests that the chromosome 10 transcriptomes identified by the tiling microarrays are rather exhaustive. In support of this conclusion, tiling array analysis of rice seedlings which had undergone severe stress treatments only identified an additional 39 (less than 1.7% of the total detected) models. These results likely can be attributed to the high sensitivity of the tiling microarrays such that even if activation of certain genes is conditional, the basal level transcripts could still be detected by the tiling microarray.
Therefore, the UG models (particularly UG/LH) that failed to be detected by the tiling microarray need to be more closely inspected (Table 1, Figure 3). We did find that the gene models specifically detected following the stress treatments were enriched with UG/LH models (23/39), suggesting that some UG/LH might be stress responsive and their expression is not readily detectable under normal conditions. It should be noted that though redundant gene models such as those derived from long terminal repeat (LTR) retrotransposons and Pack-MULEs are generally under-represented in the expressed sequence collections [12, 39], many are stress responsive and share similar cis-elements with plant defense genes . Thus, it cannot be ruled out that some of the UG/LH models are related to low copy number retrotransposons with unusual structures.
Reasoning that the tiling microarray-detected transcriptome is both exhaustive and reliable, tiling microarray-supported gene models were mapped and integrated. This analysis identified 363 unique BGI japonica, 114 unique BGI indica, and 72 novel models that could be integrated into the TIGR japonica gene model set to comprehensively represent the japonica chromosome 10 transcriptome (Figure 5). Note that the added gene models do not necessarily increase the number of japonica chromosome 10 genes, even if their transcription was detected. As elaborated above, some of these gene models could be unrecognized TEs, uncharacterized UTRs or alternative exons. However, as all these extra gene models are transcribed, their identification will not only better represent the transcriptome, but further examination of these elements will also yield insight into rice genome composition and structure.
Extensive antisense transcription was observed for the rice chromosome 10 gene models. For instance, in a preliminary analysis whereby regions of the antisense strand covering the 3,019 TIGR japonica gene models were examined, excluding those that contain less than three signal oligos, 591 (19.6%) were found to have antisense expression. The proportion of rice gene models showing antisense transcription is consistent with that reported from tiling microarray analyses in Arabidopsis  and human [24, 25], adding to an increasing body of evidence that indicates antisense transcription as an inherent property of the genomes. However, it should be cautioned that the potential effects of several experimental artifacts such as unintended second-strand synthesis, formation of specific RNA-DNA hybrids, or spurious priming events during target preparation have to be precisely assessed before a final conclusion on the nature and extent of antisense transcription in rice can be drawn.
Transcriptional activities outside the annotated gene models in the form of intergenic TARs, accounted for approximately 3% of the chromosome size (Figure 4a). RNA gel blotting and RT-PCR analyses confirmed only a portion of the selected TARs (Figure 3, 4), suggesting that the unconfirmed TARs could be experimental artifacts or correspond to transcripts of extreme low abundance [21, 25, 27]. Transcriptome components outside of previously annotated gene models are expected to correspond to: novel genes with unusual sequence composition; under-represented UTRs or exons of splice variants; nonprotein coding RNA transcripts; or uncharacterized transcribed TEs. RT-PCR analysis of selected japonica intergenic TARs suggests that the majority of the TARs belong to the first two groups (Figure 3b). This conclusion is consistent with the observation that the intergenic TARs were slightly enriched in regions of the chromosome with lower gene density (Figure 7d). A preliminary analysis whereby 214 plant miRNAs (including 122 from rice and 92 from Arabidopsis) [41, 42] were used in a BLAST search against the intergenic TARs revealed no significant hits, suggesting that the TARs do not contain known plant microRNAs.
We thus focused our efforts on further analyzing the first two groups of TARs. For the current rice annotation, five different gene finders (primarily FGENESH) were used to generate gene models . To annotate the intergenic TARs, we used the relatively new rice gene-finder program BGF [2, 6, 30], which identified 72 novel gene models (Figure 5). Sequence comparison between the 40 cloned intergenic TAR transcripts and the novel BGF models showed that 23 (57.5%) were predicted (Figure 3b), indicating that the BGF program was able to detect slightly more than half of the novel transcriptional units that might be represented by the intergenic TARs. Extrapolation from these observations suggests that there might be up to 2,000 novel genes yet to be recognized by current rice gene finders; however, the incomplete nature of the cloned transcripts made it difficult to unambiguously determine whether they encode proteins. Thus, it is possible that some of these transcripts may correspond to noncoding RNAs.
Association of chromosomal architecture with transcriptional activity
Eukaryotic genomes contain heterochromatin as cytologically intensely staining nuclear materials that are thought to be composed mainly of noncoding DNA and silent transposons [33, 43]. A salient feature of rice chromosome 10 is that its heterochromatin is not limited to the pericentric regions, but includes the entire short arm as well as the proximal portion of the long arm . Comparison of cytological and sequence data suggests that this heterochromatin region is roughly 11-12 Mb in length [5, 33]. Although recent genetic and microarray studies in plants have indicated a role for gene regulation by well defined small heterochromatin regions [44–47], virtually no data are available regarding the association of transcriptional activity with large-scale heterochromatin domains in regulating gene expression, chromosome behavior, and genome evolution.
Profiling the transcriptional activities of rice chromosome 10 using tiling microarrays revealed that gene expression in the heterochromatin region is generally low under normal growth conditions (the N Arrays) relative to the euchromatin (Figure 6a-c). Consistent with this observation, gene model distribution showed that the heterochromatin domain is relatively low in CG models but more abundant in UG models (Figure 7b). In support of the cytological data, an enrichment of TE models in the heterochromatin domain is evident (Figure 7a) . Exclusion of the high copy number TEs and repetitive sequences from the tiling microarray analysis might contribute to the lower gene model density in the heterochromatin (Figure 7a-c); however, the generally lower detection rate of gene expression indicates that expression of many non-TE models is also somewhat repressed (Figure 7a-c). Interestingly, when plants were subjected to mineral or nutrient stresses, a general activation of transcription was observed in the heterochromatin (Figure 6d). These results are consistent with findings that heterochromatin stability and heterochromatin-mediated gene silencing can be regulated by development [48, 49] or by modulating levels of specific transcription factors .
The distribution of TE and non-TE gene models in the heterochromatic and euchromatic regions was a near mirror image (Figure 7a). This result suggests that the heterochromatin and euchromatin may have similar capacities to accommodate protein-coding gene models (TE and non-TE), even though the heterochromatin is enriched with repetitive sequences (Figure 6a) . Furthermore, the heterochromatin is relatively enriched with LH models and low in CG models compared with the euchromatin (Figure 7b, c). Thus it is likely that the differential packaging of genome elements in heterochromatin and euchromatin might enable rice to regulate and coordinate gene expression at the chromosomal level. Although the underlying molecular mechanism of this regulation is currently unknown, DNA methylation, histone modifications, and small interfering RNAs have all been implicated [51–55].
The distance between corresponding japonica and indica CG models along the chromosome was more skewed in the heterochromatin, with many CG genes shuffled more than 1 Mb in physical distance from the location of their orthologous counterparts. In contrast, the gene distance in the euchromatin is largely homogeneous (Figure 8). Previous studies have shown a mosaic organization of grass genomes where conserved sequences are disrupted by nonconserved sequences, and that gene amplification, movement, and activity of retrotransposons account for the bulk of the interspersing nonconserved sequences [56–58]. Thus, these results collectively indicate that the heterochromatin domain is more evolutionarily active and compositionally dynamic. Such a conclusion is in keeping with the genomic stress hypothesis that TEs are involved in host adaptation to environmental changes [39, 40, 59].
Materials and methods
Plant materials and treatments
Oryza sativa ssp. japonica cv. Nipponbare and Oryza sativa ssp. indica cv. 93-11 were used for all experiments. Seeds were surface-sterilized, imbibed at 37°C for 2 days, and then transferred to MS medium (Invitrogen) solidified with 0.8% (w/v) agar. Seedlings were kept under continuous light at 28°C for seven days before harvest for total RNA isolation. Alternatively, 7-day-old seedlings were transferred to soil and maintained under long-day conditions (16 h light/8 h dark) at 26-28°C in the greenhouse until flowering. Heading and filling stage panicles were then collected from these plants. Suspension-cultured cells were prepared and maintained as previously described . For stress treatment, japonica seedlings were grown for seven days on MS medium under four different conditions: MS medium deprived of nitrogen; MS medium deprived of phosphorus, or supplemented with 150 mM NaCl or 100 μM CdSO4. For RNA isolation, plant materials were frozen in liquid nitrogen and homogenized. Total RNA and mRNA were isolated using the RNeasy Plant Mini kit (Qiagen) and the Oligotex mRNA kit (Qiagen) according to the manufacturer's recommendations, respectively.
MAS microarray design, production, and hybridization
Based on the MAS platform, a minimal tiling strategy was designed to effectively represent the nonrepetitive sequences of rice chromosome 10 [24, 26]. Briefly, 36-mer oligonucleotides were designed using an algorithm based on sequence-dependent factors such as length, extent of complementarity, and the overall base composition. Oligos that could form a stem-loop structure with stem length greater than seven bases and those that have an oligo index score greater than 5 were excluded. To calculate the index score for each oligo, the 20 possible consecutive 17-mer sequences within each oligo were searched against the whole genome. The average copy number of the 17-mer sequences was scored as the oligo index. MAS microarray production was performed as previously described [24, 26, 29] using the sequences of chromosome 10 for japonica and indica rice as were available on 12 April, 2004  and 1 August, 2003 [6, 30], respectively. Oligos were synthesized at a density of 389,000 oligos per array in a chessboard design wherein each positive feature, which contains an interrogating oligo, was surrounded by four negative features and vice versa.
The japonica and indica N Arrays both included four individual MAS arrays that contain oligos representing other portions of the genome (other than chromosome 10) not analyzed in the current study. The N Arrays were hybridized to cDNA target mixtures derived in equal amounts from seedling roots, seedling shoots, panicles, and suspension-cultured cells of both japonica (cv. Nipponbare) and indica (cv. 93-11) rice. Additionally, a set of two japonica arrays (S Arrays) were hybridized to targets derived from pooled poly(A)+ RNA isolated from leaves of stress-treated japonica seedlings. Target preparation, array hybridization, and hybridization intensity value acquisition were carried out as previously described [24, 26, 29, 61]. Tiling microarray design and experimental data are available in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus under series GSE2500.
Chromosome 10 gene model compilation
The japonica (TIGR Rice Pseudomolecule released on 12 April 2004)  and indica (released by BGI on 1 August 2003) [6, 30] chromosome 10 annotations were used in this study. In addition, the japonica chromosome 10 sequence was annotated using the BGI gene prediction flow to generate the BGI japonica gene model set. All gene models were aligned to a collection of rice full-length cDNA sequences  and all available rice EST sequences in GenBank  as of 15 April 2004 by the BLAT program  using cutoff criteria of 100 bp overlap and 90% identity over the entire length of each match. The predicted genes without matches to cDNA and EST sequences, excluding those with coding capacities of less than 50 amino acids, were classified as UG models.
Determination of gene model expression and identification of intergenic TARs
Hybridization intensity of all positive and all negative features within each array was plotted separately and then scaled to have a peak log2 intensity of 8.0 (Figure 1a,b). Signal and noise probe determination is shown in Figure 1c and discussed in main text. Expression level of a given gene model was represented by the value of hybridization intensity (HI) of this model locus that takes into account two parameters: FI, which is the mean of fluorescence intensity of all signal probes of a given gene model, and hybridization rate (HR), which is defined as the percentage of signal probes over total interrogating probes per kilobase of genomic sequence. HI is calculated using the formula HI = FI + FI × (HR E - HR M ) in which HR E is HR of the exon regions whilst HR M is the mean HR of all intron regions. HI value of each model was then compared against a threshold designated as the mean fluorescence intensity plus twice the standard deviation (95% confidence) of all noise probes within each array.
To identify intergenic TARs, HR was calculated in a sliding window of 500 nucleotides across the intergenic regions of chromosome 10 with a bandwidth equal to an interrogating probe. Windows with HR above a threshold of 0.4 were considered positive. Contiguously transcribed regions (TARs) were generated by joining overlapping positive windows that were delineated by the 5' probe of the first window and 3' probe of the last. TARs less than 220 bp (five consecutive probes) long were discarded. The japonica intergenic TARs were first identified using the BGI japonica annotation, followed by comparison with TIGR models. TARs overlapping with TIGR models were masked. Sequences of all retained intergenic TARs were aligned to the BGF gene predictions, and were used to BLASTX search the nonredundant protein database SWISS-PROT. Those BGF-predicted genes that overlap more than 100 bp with the sequence of intergenic TARs on the same strand of DNA were considered positive.
Cloning and verification of UG models and intergenic TARs
Selected UG models were cloned by means of RT-PCR. The PCR products were cloned into the pGEM-T vector (Promega) and sequenced. To clone intergenic TARs with downstream sequence, reverse transcription was performed on mixed poly(A)+ RNA derived from seedling roots, seedling shoots, panicles and suspension-cultured cells of japonica rice using the primer RT-CPK (5'-TGCAGTCTAGCTGGAATGACCTCATTGCAGAAT24). The PCR procedure to clone the TARs was carried out using a cascade of thermal asymmetric interlaced PCR cycles [63, 64] that employ three consecutively nested gene-specific primers to pair with primer RT-1 (5'-GCAGTCTAGCTGGAAT), RT-2 (5'-CTGGAATGACCTCATT), and RT-3 (5'-GCTGGAATGACCTCATTGCAGAAT), which anneal to overlapping regions of RT-CPK. Sequences of all the cloned PCR products were aligned back to japonica chromosome 10 using BLAT  to confirm their identify and to map their corresponding gene structure. RNA gel-blot analysis of intergenic TARs was conducted as previously described .
Integration of japonicachromosome 10 gene models
All japonica chromosome 10 related gene models were sorted, and only those that met certain criteria were retained. The TIGR nonredundant gene models that can be mapped to the japonica chromosome 10 sequence were all retained. The additional models included BGI japonica, BGI indica models mapped to japonica chromosome 10, and tiling array-derived novel BGF models. From these models, those without previous full-length cDNA/EST or tiling microarray support, or those overlapping with TIGR models were discarded. All retained models were aligned back to the japonica chromosome 10 sequences to further confirm their identities and were combined with the TIGR japonica models.
Additional data files
The following additional data files are available with the online verison of this paper. Additional data file 1 contains a table of integrated japonica chromosome 10 nonredundant gene models. Additional data file 2 contains a table of indica chromosome 10 nonredundant gene models. Additional data file 3 contains a table of the sequence analysis of cloned UG models. Additional data file 4 contains japonica chromosome 10 intergenic TARs. Additional data file 5 contains the sequence analysis of cloned intergenic TARs. Additional data file 6 contains a comparison of BGI and TIGR japonica chromosome 10 gene models. Additional data file 7 contains a comparison of BGI indica and japonica chromosome 10 gene models.
We thank Jessica Habashi for critical reading of the manuscript. The rice tiling microarray project at Yale University was supported by a grant from the NSF Plant Genome Program (DBI-0421675). The collaborative research effort in China was supported by the 863-rice functional genomics program from the Ministry of Science and Technology of China, and by the National Institute of Biological Sciences at Beijing. L.L. was initially supported by a Yale University Brown postdoctoral fellowship.
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