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DNA Research Advance Access originally published online on February 23, 2006
DNA Research 2005 12(6):417-427; doi:10.1093/dnares/dsi019
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© The Author 2006. Kazusa DNA Research Institute
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Genome-wide Investigation of Intron Length Polymorphisms and Their Potential as Molecular Markers in Rice (Oryza sativa L.)

Xusheng Wang {dagger}, Xiangqian Zhao {dagger}, Jun Zhu and Weiren Wu*

Institute of Bioinformatics, Huajiachi Campus, Zhejiang University Hangzhou, 310029, P. R. China

Received 6 October 2005


   Abstract
Top
 Abstract
1. Introduction
 2. Materials and Methods
 3. Results and discussion
 Acknowledgements
 References
 
Intron length polymorphisms (ILPs) have been used as genetic markers in some studies. However, a systematic investigation and large-scale exploitation of ILP markers has not been reported. In this study, we performed a genome-wide search of ILPs between two subspecies (indica and japonica) in rice using the draft genomic sequences of cultivars 93-11 (indica) and Nipponbare (japonica) and 32 127 full-length cDNA sequences of Nipponbare obtained from public databases. We identified 13 308 putative ILPs. Based on these putative ILPs, we developed 5811 candidate ILP markers via electronic-PCR with primers designed in flanking exons. We further conducted experiment to verify the candidate ILP markers. Out of 215 candidate ILP markers tested on 93-11, Nipponbare and their hybrid, we successfully exploited 173 codominant ILP markers. Further analyses on 10 rice accessions showed that these ILP markers were widely applicable and most (71.1%) exhibited subspecies specificity. This feature suggests that ILPs would be useful for the studies of genome evolution and inter-subspecies heterosis and for cross-subspecies marker-assisted selection in rice. In addition, by testing 51 pairs of the ILP primers on five Gramineae plants and three dicot plants, we found another desirable characteristic of rice ILP markers that they have high transferability to other plants.

Key words: rice (Oryza sativa L.); intron length polymorphism (ILP); molecular marker; genome


   1. Introduction
Top
 Abstract
 1. Introduction
2. Materials and Methods
 3. Results and discussion
 Acknowledgements
 References
 
Introns are non-coding sequences in a gene that are transcribed but spliced out of the precursor mRNA.1Go,2Go Introns are widespread and abundant in eukaryotic genomes.3Go,4Go For example, introns constitute ~11 and 24% of the fruit fly5Go and human6Go genomes, respectively. Generally speaking, introns have little functional significance, although some introns may influence the level of gene expression.7Go Therefore, introns are more variable than coding sequences.

Variations or polymorphisms in DNA sequences can be exploited as genetic markers (usually called molecular markers), which are very useful tools for genetic research (e.g. construction of genetic maps, mapping of genes or quantitative trait loci) and breeding (e.g. marker-assisted selection). Botstein et al.8Go first utilized restriction fragment length polymorphisms (RFLPs) as genetic markers to construct human genetic map. Since then, many new molecular markers have been developed, such as random amplified polymorphic DNA (RAPD),9Go amplified fragment length polymorphism (AFLP),10Go microsatellite or simple sequence repeat (SSR),11Go,12Go sequence-related amplified polymorphism (SRAP)13Go and single-nucleotide polymorphism (SNP).14Go

Intron polymorphisms can also be exploited as genetic markers. They have been successfully utilized in population genetics surveys15Go–17Go and gene mapping.18Go There could be various polymorphisms in introns, but intron length polymorphism (ILP) is the most easily recognizable type. It can be conveniently detected by the PCR. To amplify introns by PCR, primers can be designed in flanking exons. This approach is called exon-primed intron-crossing PCR (EPIC-PCR).19Go The advantage of EPIC-PCR is that exon sequences are relatively more conservative and therefore the primers designed in exons may have more extensive applications than those designed in non-coding sequences. Using this approach, Bierne et al.20Go developed several ILP markers in penaeid shrimps. To date, however, studies of exploiting intron polymorphism markers have been restricted to a few genes. No efforts on genome-wide exploitation of intron polymorphism markers have been reported.

In rice (Oryza sativa), draft genome sequences of two cultivars, 93-1121Go and Nipponbare,22Go representing indica and japonica subspecies, respectively, and a set of over 28 000 full-length cDNA sequences from Nipponbare23Go have been released. Moreover, complete sequences of chromosomes 1, 4 and 10 and, more recently, the whole genome of Nipponbare have been published.24Go–27Go In addition, a tentative assembly of all chromosomes of rice has been released (The Institute of Genomic Research, TIGR; http://www.tigr.org). These data provide us with an opportunity to systematically search for DNA polymorphisms between the two subspecies and to exploit DNA markers on a large scale in rice. Recently, Shen et al.28Go and Feltus et al.29Go independently conducted genome-wide investigations of SNPs and InDels or single-base InDels using the same set of released genome drafts of 93-11 and Nipponbare. However, it is astonishing that while Shen et al.28Go identified 1 703 176 SNPs and 479 406 InDels, among which there were 277 858 single-base InDels according to our count from their online database, Feltus et al.29Go only identified 384 341 SNPs and 24 557 single-base InDels—the numbers of SNPs and single-base InDels identified by Shen et al.28Go are 4.4 and 11.3 times greater than those identified by Feltus et al.29Go respectively. The great inconsistency between the two studies suggests that there might be many mistakes in the reported SNPs and InDels.

ILPs are caused by InDels, but many of them cannot be simply considered equivalent to the generally defined InDels because an ILP may contain several (instead of only one) InDels. In addition, even if we take all ILPs as InDels, they are at least a special subset of InDels exhibiting polymorphisms in the non-coding regions of genes. This may make ILPs possess special characteristics and usefulness. In the work described here, we performed a genome-wide search for ILPs and a large-scale exploitation of candidate ILP markers via electronic EPIC-PCR based on the released genomic and cDNA sequence data in rice. We also developed a set of ILP markers selected from the candidates and investigated their characteristics by experiment. Moreover, we established a web-accessible database for rice ILP markers.


   2. Materials and Methods
Top
 Abstract
 1. Introduction
 2. Materials and Methods
3. Results and discussion
 Acknowledgements
 References
 
2.1. Data sources of rice genomic and cDNA sequences
We downloaded genomic sequence data of two rice cultivars, Nipponbare (ssp. japonica) and 93-11 (ssp. indica), released by the International Rice Genome Sequencing Project (IRGSP) and Beijing Genomics Institute (BGI), from web sites http://www.tigr.org/ and http://rise.genomics.org.cn/rice/link/download.jsp, respectively. In addition, we downloaded 32 127 full-length cDNA sequences of Nipponbare from web site http://cdna01.dna.affrc.go.jp/cDNA/.

2.2. Search of ILPs
We developed a pipeline using Perl script to search ILPs between Nipponbare and 93-11 and exploit candidate ILP markers. The initial step was to identify the most likely positions of the available cDNA sequences in rice genome by aligning the cDNA sequences of Nipponbare with the genomic sequences of Nipponbare and 93-11 using BLASTN.30Go We used a high E-value (= 10–20) for the BLASTN to remove paralogues. Then we used the program SIM431Go to align each cDNA with its corresponding BAC clone from Nipponbare and Scaffold from 93-11 to examine the gene structure (number of introns and positions of splice sites) and putative ILPs between the two cultivars in the gene. Although there could be several possible types of ILPs, we restricted our ILP search to those genes that showed the same structure (i.e. same number of introns with same positions of splice sites) in the two cultivars because ILPs in those genes could potentially be exploited as PCR-based codominant markers.

2.3. Exploitation of candidate ILP markers by electronic EPIC-PCR
To exploit ILP markers from the putative ILPs identified by BLASTN and SIM4, we designed PCR primers based on the cDNA sequences (of Nipponbare) corresponding to the flanking exons using ePrime3 (http://www.hgmp.mrc.ac.uk/).32Go For convenience, we used a 200 bp cDNA sequence with 100 bp on each side of the target intron for the primer design for each ILP. A simulation study conducted beforehand had shown that the cDNA length could guarantee 93% success in primer design. Then we tested the designed primers by electronic PCR (e-PCR)33Go on the genomic sequences of Nipponbare and 93-11, respectively. To increase the quality and usability of the in silico exploited ILP markers, we required exact matches between primers and templates and set a 1100 bp margin on the product size for the e-PCR. We took a putative ILP locus as a candidate ILP marker when it was successfully and uniquely detected by the e-PCR and named it with the abbreviation RI (for Rice ILP) followed by a unique number (e.g. RI03281).

2.4. Verification and evaluation of ILP markers by experiment
We selected 215 candidate ILP markers for the experimental evaluation. According to the RGP's rice genetic map,34Go the selected candidate ILP markers were approximately evenly distributed in rice genome with an average of ~8 cM between adjacent ILP loci. While we directly adopted the PCR primers designed in flanking exons for most of the selected candidate ILP markers, we also redesigned primers in introns for some with smaller intron length difference (ILD) but larger intron size in order that polymorphisms could be detected via electrophoresis. All primers were synthesized by either Shanghai Sangon Biological Engineering & Technology Company or Shanghai BioAsia Biotechnology Company.

We tested the synthesized primers at first using Nipponbare, 93-11 and their F1. We extracted genomic DNAs from young leaves using CTAB method35Go with modification. We conducted PCR in a 15 µl reaction mixture containing 50 ng template DNA, 0.5 µM of each primer, 200 µM of each dNTP, 1.5 mM MgCl2, 0.1% Triton X-100 and 1 U Taq polymerase and 1.5 µl of 10x PCR buffer. We first tested all primer pairs with a touchdown PCR (Td-PCR)36Go program: 5 min at 94°C; 10 cycles of 30 s at 94°C, 30 s at 59°C minus 0.3°C/cycle, 1 min at 72°C; 20 cycles of 30 s at 94°C, 30 s at 56°C, 1 min at 72°C; and 5 min at 72°C for final extension. For primer pairs that did not generate good amplification results, we adjusted the initial annealing temperature (59°C) to 60 or 57°C. The purpose of using Td-PCR was to increase the specificity of amplification, but some primer pairs only required a routine PCR program: 5 min at 94°C; 35 cycles of 30 s at 94°C, 30 s at 54°C, and 1 min at 72°C; and 5 min at 72°C for final extension. For most primers, we used 6% non-denaturing PAGE (250 V, 2 h) for separating PCR products and silver staining for visualizing DNA bands following Xu et al.37Go with modification. We also used 2% agarose gel for some primers.

For primers generating correct PCR products as expected, we further tested them using 10 rice varieties including Nipponbare and 93-11 (Table 1), which were kindly provided by the China National Rice Research Institute (CNRRI). Based on the PCR data, we evaluated the allelic diversity of each ILP marker using the polymorphism information content (PIC) value defined as Formula, where pij is the frequency of the jth pattern for the ith marker.38Go


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  		Table 1. Rice accessions used for testing ILP markers

 
We also employed some of the ILP primers to perform PCR in other plants including five Gramineae plants (wheat, barley, maize, sorghum and bamboo) and three dicot plants (rape, cotton and tobacco), using either a Td-PCR program (with an initial annealing temperature of 55°C) or a routine PCR program (with an annealing temperature of 52°C).


   3. Results and discussion
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results and discussion
Acknowledgements
 References
 
3.1. Number, distribution and density of ILPs in rice
By aligning 32 127 full-length cDNA sequences from Nipponbare with the genomic sequences of Nipponbare and 93-11 using BLASTN and SIM4, we found 120 489 and 108 312 introns in the two cultivars, respectively, and identified 13 308 putative ILPs between the two cultivars. All the cDNAs were localized to the BAC clones of Nipponbare as expected, but 1279 (3.98%) cDNAs did not align to the scaffolds of 93-11 with an E-value below the BLAST criterion of 10–20. That could be the reason that fewer introns were found in 93-11. By referring to the TIGR psuedomolecule assembly of rice, we have plotted the density distribution curve of ILPs in rice genome (Fig. 1). Due to discrepancies between GenBank and TIGR in the assembly of some BAC clones, 32 ILPs could not be assigned to chromosomes and 302 ILPs could not be located, although their chromosomes were known. Therefore, we did not count these ILPs when plotting the density distribution curves, but still took those ILPs into account when calculating the total number and overall density of ILPs on each chromosome (Fig. 1). Most (>100) of the non-located ILPs were in chromosome 10.


Figure 1
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  		Figure 1. Density distribution of ILPs across rice genome. A gray rectangle on each x-axis indicates the position of centromere. The total number and overall density (number per Mb) of ILPs on each chromosome are also presented.

 
It is obvious from Fig. 1 that the ILP density fluctuates dramatically along the genome and varies among chromosomes, ranging from 23.04 per Mb (chromosome 12) to 45.31 per Mb (chromosome 2) with an average of 32.52 per Mb; or from 6.25 per cM (chromosome 9) to 11.45 per cM (chromosome 2) with an average of 8.48 per cM. ILPs are clearly not randomly distributed in rice genome. In addition, the number of ILPs on each chromosome also varies greatly, ranging from 584 (chromosome 9) to 1848 (chromosome 3) with an average of 1106 (Fig. 1). The ILPs on chromosomes 1, 2 and 3 together constitute ~40% of the total number.

Rice genome is estimated to contain 46 022–55 615 genes.21Go In this study, we have found 13 308 ILPs between Nipponbare and 93-11 based on 32 127 full-length cDNA sequences, suggesting that there are 0.414 ILPs per cDNA on average. If we approximately consider a cDNA as a gene, then we can deduce that the total number of ILPs between the two cultivars would be 19 064 to 23 037 according to the estimate obtained in this study. It should be emphasized that we restricted the ILP search to those genes having the same structure (number and positions of introns) in both Nipponbare and 93-11. Therefore, there were some genes not taken into account. In fact, we have mentioned above that 1279 (3.98%) cDNAs did not hit the scaffolds of 93-11 in the BLAST with an E-value below 10–20. These genes might either be specific to japonica or have large variation between indica and japonica during evolution.39Go For the former case, all introns in the genes could be taken as ILPs with null alleles in indica and therefore could be potentially exploited as dominant ILP markers. For the latter case, ILPs could also exist. We thus see that ILPs are very rich in the rice genome and should be a huge resource of molecular markers.

3.2. Candidate ILP markers
Using primers designed in flanking exons, we successfully obtained e-PCR products from 10 572 (79.4%) and 7742 (58.2%) putative ILP loci in Nipponbare and 93-11, respectively. Although we designed the primers based on the cDNAs from Nipponbare, we failed to acquire e-PCR products from ~1/5 putative ILP loci in Nipponbare, probably due to the several constraint conditions set for the primer design and e-PCR (see Materials and Methods). There were a higher proportion of putative ILPs in 93-11 not detected by e-PCR because mismatches might occur between some primers and the genomic sequence of 93-11. Although perfect match between primer and template was required in the e-PCR, there still were 1009 primer pairs detecting multiple BAC clones located on different chromosomes and appearing to have multiple copies in Nipponbare. Similarly, 880 primer pairs detected multiple scaffolds and showed multiple copies in 93-11. A typical example was the primer pair designed in cDNA AK064639 [GenBank] , which detected a total of 106 occurrences on japonica genome, indicating that the primer pair might be designed in the conserved sequences of a big gene family. As multiple-copy is not desirable for molecular markers, we discarded these primer pairs. It is noted that the 10 572 ILP loci detected by e-PCR in Nipponbare were located only on 2405 (~61%) BAC clones, leaving 1526 clones without ILP hits. The result also reflects the nonrandom distribution of ILPs in rice genome.

By combining the e-PCR results in Nipponbare and 93-11, we obtained 5811 candidate single-copy ILP markers. The number of candidate ILP markers on each chromosome ranged from 130 (chromosome 9) to 990 (chromosome 2) with an average of 484; and the density on each chromosome ranged from 4.91 per Mb (chromosome 4) to 24.81 per Mb (chromosome 2) with an average of 13.06 per Mb, or from 1.39 per cM (chromosome 9) to 6.27 per cM (chromosome 2) with an average of 3.42 per cM (Fig. 2). Based on the TIGR psuedomolecule assembly of rice, we have constructed a physical map of the 5811 candidate ILP markers and a comparative map of 2275 RFLP and 2740 SSR markers (Fig. 2). The map shows that the candidate ILP markers are not evenly distributed. This seems to be consistent with the distribution of ILPs (Fig. 1). However, it is surprising that some genomic regions (particularly in the long arms of chromosomes 1, 4, 9 and 12) are nearly devoid of candidate ILP markers although the putative ILPs in these regions are not rare (Fig. 2). By examining the distribution of e-PCR hits in the whole genome, we found that these regions appeared to have high frequencies of No-EPCR-Hit-in-93-11 (NEH9) (Fig. 3). This could explain why there were so few candidate ILP markers obtained in these regions. The major reason of NEH9 for a putative ILP locus could be that mismatches occurred between the primers designed based on the cDNA of Nipponbare and the genomic sequence of 93-11. The high frequencies of mismatches in these regions imply that these regions might have a higher level of genetic variation between the two subspecies. To develop ILP markers in these regions, we need to identify conserved sequences of each gene for designing PCR primers.


Figure 2
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  		Figure 2. Physical map of 5811 candidate ILP markers and comparative map of 2275 RFLP and 2740 SSR markers. Each vertical short bar indicates the position of a candidate ILP marker. The three numbers in the brackets on the right of the map of each chromosome are the total number, number per Mb and number per cM of candidate ILP markers.

 

Figure 3
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  		Figure 3. Density distribution of NEH9s on chromosomes 1, 4, 9 and 12. The horizontal axis shows the pseudomolecule position (Mb); the vertical axis shows the number of NEH9s per Mb.

 
The length difference between allelic introns (referred to as intron length difference, ILD) in the candidate ILP marker loci appeared to follow an exponential distribution with a mean value of 11.42 bp (Fig. 4). Most (72.6%) of the ILDs were <5 bp; 23.5% fell between 5 and 50 bp; and very few (3.9%) were >50 bp. Generally speaking, the larger the ILD is, the easier the detection will be. Therefore, the candidate ILP markers with ILDs ≥ 5 bp should be preferentially considered in practical studies. However, the candidate ILP markers with small ILDs (<5 bp) should not be ignored too, because they are in the majority.


Figure 4
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  		Figure 4. The number distribution of intron length difference in 5811 candidate ILP markers.

 
Since ILPs are detected with specific PCR primers, they usually can be used as STS (sequence-tagging site) markers like SSRs. By examining the intron sequences of the 5811 candidate ILP markers, we found that only 208 (3.58%) of the ILPs were due to SSR variation, of which TA was the most frequent motif (19.2%), followed by GA (14.4%). This means that there is only a very small overlap between ILPs and SSRs in rice. In addition, we have seen that ILPs exist in many gaps in the physical map of RFLP and SSR markers (Fig. 2). Therefore, ILPs are a new source of STS markers different from SSRs and can complement SSR and RFLP markers. In principle, every ILP is potentially a genetic marker as long as a suitable detection method is available.

3.3. ILP markers exploited by experiment
In order to detect ILPs by non-denaturing PAGE or agarose gel electrophoresis, we only chose candidate ILP markers with ILD ≥ 3 bp for the experiment. Of the 215 candidate ILP markers tested, 173 (80.47%) yielded stable and clear PCR products as expected in both Nipponbare and 93-11, and appeared to be codominant in the F1. Besides, six (2.79%) candidate ILP markers yielded the expected PCR products in either of the parents and appeared to be dominant in the F1. The number of ILP markers on each chromosome is shown in Table 2.


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  		Table 2. Number of ILP markers obtained by experiment

 
To increase PCR specificity in the amplification of ILP loci, we adopted a Td-PCR program. Most (138/173) of the ILP markers obtained could be amplified well by the Td-PCR with the default initial annealing temperature (59°C). Some other (25 or 8) markers required a lower (57°C) or higher (60°C) initial annealing temperature. Eight markers could be well amplified at a constant annealing temperature (54°C).

We further tested the 173 codominant markers on 10 rice varieties. All the markers were successfully detected in those varieties (Fig. 5), suggesting that the markers exploited are widely applicable. Based on the resolution capacity of the non-denaturing PAGE or agarose gel used, it appeared that most of the markers only possessed 2 (i.e. Nipponbare's and 93-11's) alleles among the 10 varieties. Only nine markers appeared to have multiple alleles, of which five were attributed to SSR variation. The PIC values of the markers varied from 0.18 to 0.66 with an average of 0.451. The results indicate that the polymorphism level of ILP marker is not high in general. However, a higher estimate of the polymorphism level of ILP markers could probably be obtained if methods of DNA fragment analysis with higher resolution capacity (e.g. denaturing PAGE, usually used for SSR analysis or DNA sequencing) were adopted.


Figure 5
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  		Figure 5. PCR products of ILP marker RI01015 in rice accessions separated by electrophoresis on 2% agarose gel. Lanes from left to right: M = DNA molecular weight marker; 1 = 93-11; 2 = Nipponbare; 3 = 9311/Nipponbare F1; 4 = Guangluai-4; 5 = Xieqingzao; 6 = IR64; 7 = Koshihikari; 8 = Xiushui-11; 9 = Merim; 10 = Katy; 11 = Kyeema.

 
3.4. WIN-PCR for ILP detection
In the present study, we adopted electronic EPIC-PCR to screen for candidate ILP markers. However, because the ILDs of >70% candidate ILP markers were <5 bp (Fig. 3) and the average size of the EPIC-PCR products was ~580 bp, most of the candidate ILP markers would be difficult to detect by real EPIC-PCR. To solve this problem, a possible way is to design PCR primers within introns so as to obtain smaller PCR products. For this purpose, we examined nucleotide substitutions (SNPs) in introns between Nipponbare and 93-11 by sequence comparison in silico. We identified 17 374 putative nucleotide substitutions in the introns of the 5811 candidate ILP markers, approximately equivalent to 6 SNPs/kb (Table 3). Although the estimate of SNP frequency in intron sequences between the two subspecies of rice is much larger than that of whole genome average (1.06 SNPs/kb),29Go it is still not very high. Hence, it should be suitable to design PCR primers within introns to detect cross-subspecies ILPs in rice. To distinguish this technique, we call this approach Within INtron PCR (WIN-PCR). In this study, we have obtained 57 ILP markers from 69 candidate ILP markers by WIN-PCR. The success rate (57/69 = 82.61%) is very similar to that of EPIC-PCR (122/146 = 83.56%) (Table 2). The results indicate that WIN-PCR could be as efficient as EPIC-PCR. In principle, WIN-PCR would permit the detection of single-nucleotide ILPs.


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  		Table 3. Single-nucleotide substitutions between 93-11 and Nipponbare in the intron sequences of 5811 candidate ILP markers

 
3.5. Subspecies specificity and intra-subspecies diversity of ILPs
Among the 10 accessions used for ILP analysis in the present study (Table 1), 93-11, Guangluai-4 and Xieqingzao could be taken as typical indica cultivars and Nipponbare, Xiushui-11 and Koshihikari as typical japonica cultivars according to their origins. Based on these typical accessions, 123 (71.1%) out of the 173 ILP markers tested showed subspecies-specific genotypes (i.e. different between but the same within subspecies). The result suggests that ILPs in rice have apparent subspecies specificity. This feature could be useful for analyzing the genetic compositions of rice cultivars. A typical example comes from the accession Kyeema. The accession was categorized as an indica cultivar based on morphological characters.40Go However, we have found that it is more likely to be a japonica cultivar because out of the 123 subspecies-specific ILP markers assayed on it, only 21 (17.1%) exhibited indica genotype, while 100 (81.3%) showed japonica genotype. This is consistent with its pedigree. In fact, Kyeema was derived from a triple cross involving one indica (Della) and two japonica (Pelde and Kulu) parents. We can expect that the offspring of the triple cross (Pelde//Della/Kulu) would contain 25% indica and 75% japonica genetic components on average. We see that the proportions in Kyeema's genome estimated by ILP markers are close to the expected values. Another example worthy of note is the accession Katy, a suggested japonica cultivar derived from a complicated cross Bonnet73/CI9722//Starbonnet/Tetep///Lebonnet, where Tetep is a typical indica parent. Our study has found that out of the 123 subspecies-specific ILP markers, 22 (17.9%) showed indica genotype in Katy. Therefore, Katy cannot be a typical japonica cultivar. In addition, 9 ILP markers showed heterozygous genotypes in Katy, suggesting that the accession might not be a pure line. A more interesting result we obtained concerns the javanica variety Merim. In this accession, 94 (or 76.4%) out of the 123 subspecies-specific ILP markers showed japonica genotype. This confirms that javanica belongs to japonica.41Go

Although ILPs in rice have strong subspecies specificity, they still exist within subspecies. Based on the three typical indica and three typical japonica cultivars mentioned above, we found that of the 173 ILP markers tested, 44 (25.4%) showed polymorphisms among indica cultivars and 10 (5.8%) showed polymorphisms among japonica cultivars. The result indicates that indica rice has much higher genetic diversity than japonica rice. This is consistent with previous studies based on RAPD42Go and RFLP43Go markers. The finding implies that indica rice might have evolved earlier than japonica rice.

3.6. Transferability of ILP markers to other plants
We randomly selected 51 pairs of rice ILP primers to perform EPIC-PCR in other 8 plants (see Materials and Methods) and found that 24 (47.1%) pairs yielded desirable results with 1–5 clear and stable bands in all the plants; 31 (60.8%) pairs worked well in all the 5 Gramineae plants; only 6 (11.8%) pairs did not generate any PCR products. In cotton alone, 36 (70.6%) pairs of the primers yielded clear and stable PCR products and 11 (30.6%) of them revealed polymorphisms between two cultivated cotton species, Gossypium barbadense L. and Gossypium hirsutum L. The results suggest that a high proportion of rice ILP markers are transferable to other plants.

To examine whether the PCR products in other plants were really specifically amplified or homologous to the target genes in rice, we randomly isolated electrophoretic bands produced by primer pair RI02862 from wheat, maize and cotton, respectively (Fig. 6) and sequenced them (by Shanghai Sangon Biological Engineering & Technology Company). Multiple alignment of the sequences of wheat, maize and cotton together with those of rice using computer programs ClustalX44Go and GeneDoc45Go showed that they were really from homologous genes as expected: the exon regions (two sides) were well conserved and the intron region (middle) were highly varied among the plants (Fig. 7). This suggests that most, if not all, of the clear and stable PCR products obtained in other plants must be resulted from specific amplification.


Figure 6
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  		Figure 6. PCR products of ILP marker RI02862 in rice and other plants separated by electrophoresis on 6% non-denaturing PAGE. Lanes from left to right: 1 = japonica rice (Nipponbare); 2 = indica rice (93-11); 3 = barley; 4 = wheat; 5 = maize; 6 = sorghum; 7 = bamboo; 8 = rape; 9 = tobacco; 10 = cotton (Gossypium hirsutum L.); 11 = cotton (Gossypium barbadense L.).

 

Figure 7
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  		Figure 7. Multiple alignment of sequences amplified from maize, wheat and cotton (Gossypium hirsutum L.) by primer pair RI02862 and available target sequences from japonica rice (Nipponbare) and indica rice (93-11).

 
For comparison, we also applied 32 pairs of rice SSR primers to the 9 plants. We found that although all the SSR primers could generate PCR products in all the plants, the electrophoretic bands produced by each pair of primers were generally quite many (at least 10) and unstable, suggesting that most, if not all, of the bands are produced by unspecific amplification as seen in the randomly primed markers such as RAPD.9Go Therefore, it appears that most of the rice SSR markers are not transferable to other plants, but can only serve as unspecific PCR markers in other plants.

3.7. Advantages of ILP markers
ILP is a new type of molecular marker, which has not been reported extensively. We have seen that ILPs are abundant between the two cultivated subspecies in rice. ILP has many similar advantages to SSR including specific (being a STS marker), codominant (providing complete information of genotypes), neutral (no phenotypic effect), convenient (detectable by PCR) and reliable (result stable). In addition, ILP has a special advantage, namely, it directly reflects variation within genes. Therefore, the genetic maps constructed with ILP markers would be more valuable for genetic studies because they are similar to conventional maps consisting of morphological markers. Moreover, ILP marker would be more useful for marker-assisted breeding because it allows us to trace a gene directly as long as an ILP can be found in the gene.

We have seen that ILPs have significant subspecies specificity in rice. This characteristic could be useful for genetic study and breeding in rice. Apart from the use for analyzing genetic compositions of rice cultivars discussed above, it might be useful for the studies of genome evolution and inter-subspecies heterosis and for cross-subspecies marker-assisted breeding.

In addition, we have seen the high transferability of rice ILP markers to other plants. This characteristic would make ILP markers very useful for (i) construction of molecular marker maps in other plants that have weaker genetic research basis; (ii) genome comparison among plants; (iii) gene mapping with the help of synteny or collinearity between model plants and other plants; (iv) research of phylogenetic relationships among different species, genera, families or even higher taxonomic ranks in plants and (v) marker-assisted breeding in other plants.

3.8. ILP database
We have established a database (http://ibi.zju.edu.cn/ILPs/index.htm) for depositing the information of the 5811 candidate ILP markers, including ILP name, cDNA name, japonica BAC clone accession number, japonica BAC clone name, marker start position in japonica (bp), maker end position in japonica (bp), marker length in japonica (bp), indica scaffold name, marker start position in indica (bp), marker end position in indica (bp), marker length in indica (bp), length difference between japonica and indica (bp), position in RFLP map (cM), forward primer and reverse primer. For convenience, the ILP information is searched by key words, such as ILP name, BAC clone and scaffold. In addition, the 173 codominant ILP markers obtained have been submitted to GenBank (accession nos.: BV209990–BV210161, BV210393).


   Acknowledgements
Top
 Abstract
 1. Introduction
 2. Materials and Methods
 3. Results and discussion
 Acknowledgements
References
 
This work was funded by the National High-Tech Research and Development Program of China (project: 2003AA207160 & 2002AA234031) and by IBM Shared University Research (SUR) program. The authors thank Dr Adrian Cutler from Plant Biotechnology Institute, National Research Council of Canada for helpful suggestions on the manuscript.


   Footnotes
 
*To whom correspondence should be addressed. Tel/Fax. +86-571-86971910, E-mail: wuwr{at}zju.edu.cn

{dagger}These authors contributed equally to this work. Back

Communicated by Satoshi Tabata


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 1. Introduction
 2. Materials and Methods
 3. Results and discussion
 Acknowledgements
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