An overview of the Phalaenopsisorchid genome through BAC end sequence analysis
- Chia-Chi Hsu†1,
- Yu-Lin Chung†1,
- Tien-Chih Chen†1,
- Yu-Ling Lee†1,
- Yi-Tzu Kuo1,
- Wen-Chieh Tsai2, 3,
- Yu-Yun Hsiao1,
- Yun-Wen Chen1,
- Wen-Luan Wu1, 2, 3Email author and
- Hong-Hwa Chen1, 2, 3Email author
© Hsu et al; licensee BioMed Central Ltd. 2011
Received: 19 July 2010
Accepted: 6 January 2011
Published: 6 January 2011
Phalaenopsis orchids are popular floral crops, and development of new cultivars is economically important to floricultural industries worldwide. Analysis of orchid genes could facilitate orchid improvement. Bacterial artificial chromosome (BAC) end sequences (BESs) can provide the first glimpses into the sequence composition of a novel genome and can yield molecular markers for use in genetic mapping and breeding.
We used two BAC libraries (constructed using the BamHI and HindIII restriction enzymes) of Phalaenopsis equestris to generate pair-end sequences from 2,920 BAC clones (71.4% and 28.6% from the BamHI and HindIII libraries, respectively), at a success rate of 95.7%. A total of 5,535 BESs were generated, representing 4.5 Mb, or about 0.3% of the Phalaenopsis genome. The trimmed sequences ranged from 123 to 1,397 base pairs (bp) in size, with an average edited read length of 821 bp. When these BESs were subjected to sequence homology searches, it was found that 641 (11.6%) were predicted to represent protein-encoding regions, whereas 1,272 (23.0%) contained repetitive DNA. Most of the repetitive DNA sequences were gypsy- and copia-like retrotransposons (41.9% and 12.8%, respectively), whereas only 10.8% were DNA transposons. Further, 950 potential simple sequence repeats (SSRs) were discovered. Dinucleotides were the most abundant repeat motifs; AT/TA dimer repeats were the most frequent SSRs, representing 253 (26.6%) of all identified SSRs. Microsynteny analysis revealed that more BESs mapped to the whole-genome sequences of poplar than to those of grape or Arabidopsis, and even fewer mapped to the rice genome. This work will facilitate analysis of the Phalaenopsis genome, and will help clarify similarities and differences in genome composition between orchids and other plant species.
Using BES analysis, we obtained an overview of the Phalaenopsis genome in terms of gene abundance, the presence of repetitive DNA and SSR markers, and the extent of microsynteny with other plant species. This work provides a basis for future physical mapping of the Phalaenopsis genome and advances our knowledge thereof.
The family Orchidaceae, which contains at least 25,000 species, is one of the largest families of flowering plants . As with all other living organisms, present-day orchids have evolved from ancestral forms as a result of selection pressure and adaptation. Orchids show a wide diversity of epiphytic and terrestrial growth forms, and these plants have successfully colonized almost every habitat on earth. The factors promoting the richness of orchid species may include specific interactions between orchid flowers and pollinators , sequential and rapid interplay between drift and natural selection , obligate orchid-mycorrhizal interactions , and epiphytism. The latter mode is the growth form of more than 70% of all orchids , which comprise approximately two-thirds of the epiphytic flora of the world.
Expansion of diversity may have taken place more quickly in the orchid family than in most other flowering plant families, which had already started to diversify in the mid-Cretaceous . The time at which orchids originated is disputed, but it has been suggested to be 80-40 million years ago (Mya) (thus in the late Cretaceous to late Eocene) . Recently, the Orchidaceae were dated using an amber fossil of an orchid pollinia on the back of the pollinator, a stingless bee . The most recent common ancestor of extant orchids is believed to have lived in the late Cretaceous (76-84 Mya) . Perhaps the only general statement that can be made about the origin of orchids is that most extant groups are probably very young.
Orchids are known for the diversity of their specialized reproductive and ecological strategies. Formation of the labellum and gynostemium (a fused structure of the androecium and gynoecium) to facilitate pollination has been thoroughly documented, and the co-evolution of orchid flowers and pollinators thereof is well understood [9, 10]. The successful evolutionary progress of orchids may be explained by the packaging of mature pollen grains as pollinia, the pollination-based regulation of ovary/ovule development, the synchronized timing of micro- and mega-gametogenesis for effective fertilization, and the release of thousands or millions of immature embryos (endosperm-free seeds) in a mature capsule . However, despite the unique aspects of developmental reproductive biology and the specialized pollination and ecological strategies of orchids, relatively few molecular studies have focused on orchids compared to other species-rich plant families .
The genomic sequence resources for orchids are limited. A number of studies have used Sanger sequencing to develop expressed sequence tag (EST) resources for orchids [13–15]. These works have highlighted the usefulness of cDNA sequencing in the discovery of candidate genes for orchid floral development [16, 17], floral scent production [14, 18], and flowering time determination , in the absence of a full genomic sequence. However, we do not yet have a comprehensive description of all genes that are expressed in orchids.
Hybrids of the genus Phalaenopsis are among the top-traded blooming potted plants worldwide. Because the plants possess favorable commercial traits, such as numerous spikes and branches, along with many colorful flowers, P. equestris is often used as a parent for breeding in its native Taiwan. P. equestris is a diploid plant with 38 chromosomes (2n = 2x) that are small and uniform in size (< 2 μm long) . The plant has an estimated haploid genome size of 1,600 Mb (3.37 pg/diploid genome), which is relatively small compared to those of other members of the genus Phalaenopsis . Public databases of floral bud ESTs from P. equestris and P. bellina have been developed and analyzed [14, 17]; they provide valuable opportunities for researchers to directly access genes of interest [16–18] and to identify molecular markers useful in marker-assisted breeding programs or cultivar identification (unpublished data). However, we still lack basic information on the sequence, organization, and structure of the Phalaenopsis genome.
One efficient and viable strategy for gaining insight into the sequence content and complexity of the Phalaenopsis genome is afforded by the construction of bacterial artificial chromosome (BAC) libraries and end-sequencing of randomly selected BAC clones. Such BAC end sequences (BESs) can be used as a primary scaffold for genome shotgun-sequence assembly and to generate comparative physical maps . Analysis of BES data can provide an overview of the sequence composition of a novel genome, yielding information on gene density, and the presence of potential transposable elements (TEs) and microsatellites [23–26]. In addition, BESs can identify molecular markers that may be used for genomic mapping and cloning, and in phylogenetic analysis. Even for the rice genome, which has been fully sequenced, the Oryza Map Alignment Project (OMAP) constructed deep-coverage large-insert BAC libraries from 11 wild and 1 cultivated African Oryza species (O. glaberrima); clones from these 12 BAC libraries were next fingerprinted and end-sequenced. The resulting data were used to construct physical maps of the Oryza species to permit studies on evolution, genome organization, domestication, gene regulatory networks, and efforts toward crop improvement [27, 28]. However, such work has not yet been performed in orchids.
In the present study, we analyzed 5,535 BESs of two genomic BAC libraries of P. equestris, focusing on simple sequence repeat (SSR) or microsatellite content, repeat element composition, GC content, and protein-encoding regions. The annotated BESs reported herein offer the first detailed insights into the sequence composition of the P. equestris genome, and should be a useful resource for future molecular marker development.
Results and Discussion
BAC end sequencing
Two large-insert bacterial artificial chromosome (BAC) libraries were used for end-sequencing in the present study. One library, constructed from a partial HindIII digest of P. equestris genomic DNA, consisted of 100,992 clones with an average insert size of 100 kb. The other library, constructed from a partial BamHI digest, consisted of 33,428 clones with an average insert size of 111 kb. The two libraries represent approximately 8.4 equivalents of the wild-type Phalaenopsis haploid genome.
Statistical analysis of Phalaenopsis equestris bacterial artificial chromosome (BAC) end sequences (BESs)
Total number of BESs
No. of paired BESs
No. of non-paired BESs
Total length (bp)
Minimum length (bp)
Maximum length (bp)
Average length (bp)
Potential transposable elements (%)
Simple sequence repeats (%)
Protein coding regions (%)
Chloroplast sequences (%)
Unknown genomic sequences (%)
Database sequence searches
The P. equestris BESs were subjected to sequence homology analysis using the RepBase and TIGR plant repeat databases, and RepeatMasker and BLAST were employed to predict repeat sequences and potential TEs, respectively. A total of 1,272 BESs (23.0% of total) were found to harbor putative TEs and repeats. The BESs were also RepeatMasked and compared to data in the NCBI non-redundant protein databases. A total of 641 (11.6%) were found to contain protein-coding sequences; of these, 29 BESs (0.5% of the total) contained putative chloroplast DNA-encoded genes (Table 1).
Analysis of repetitive DNA in the BESs
The large genome size of P. equestris (1,600 kb) implies that the content of repetitive DNA could be high, rendering the genome more similar to that of maize than rice. The 29 BESs containing apparent chloroplast sequences were removed from analysis, and the remaining 5,506 BESs were screened for repetitive DNA sequences, using RepeatMasker and the TIGR plant repeat database. As for other eukaryotic genomes, that of Phalaenopsis was found to contain a significant proportion of repeat sequences and potential TEs; 1,272 BESs (23% of the total) contained such TEs (Table 1). This percentage was higher than that of apple (20.9%) , but lower than that of Citrus clementina (25.4%) , carrot (28.3%) , or Musa acuminata (36.6%) .
Number of bacterial artificial chromosome (BAC) end sequences (BESs) containing repetitive DNA
Class, subclass, group
No. of BESs
% of BESs with repetitive DNA
Class I retrotransposons
Class II DNA transposons
Miniature inverted-repeat transposable elements
BLASTN was used to compare the 641 BESs containing protein-encoding sequences to the sequences contained in our orchid EST databases [12, 13]. We found that 417 BESs (65.1%) yielded matches and are known to be expressed in orchids (data not shown), whereas 224 (34.9%) did not show sequence matches when compared with the orchid EST databases.
Based on the fact that 641 predicted protein-encoding sequences covered 4,544 kb of the Phalaenopsis genome, as identified from 5,535 BESs, gene density analysis predicted that a gene should occur in every 7.1 kb of the Phalaenopsis genome. By comparison, banana (M. acuminata) has a gene density of 6.4 kb , rice (O. sativa) is predicted to have a gene every 6.2 kb , whereas A. thaliana is thought to have a gene every 4.5 kb .
BLASTX (E-values < 1e-5) was used to compare the RepeatMasked BESs to the protein databases of O. sativa (downloaded from the Rice Annotation Project Database, http://rapdb.dna.affrc.go.jp/download/index.html) and V. vinifera (downloaded from the NCBI V. vinifera protein database, ftp://ftp.ncbi.nih.gov/genomes/Vitis_vinifera/protein/). Of the 5,506 BESs, 550 (9.99%) were homologous to V. vinifera proteins. Thus, based on an estimated genome size of 1,600 Mb for P. equestris, it may be predicted that the total coding sequences of the P. equestris genome might represent approximately 159.8 Mb. If an average gene length of 3.4 kb, as in V. vinifera , is assumed, an estimate of the total gene content of the P. equestris genome is 47,007. When the rice genome was used for comparison, 504 Phalaenopsis BESs showed matches to the rice protein database, accounting for 9.15% of rice proteins. Similar estimations indicate that protein-encoding sequences cover 146.5 Mb of the Phalaenopsis genome and, assuming an average gene length of 2.7 kb in Oryza , predict that the Phalaenopsis genome contains 54,259 genes. These values are comparable to the 30,434 protein-encoding genes identified in the 487-Mb grape genome  and the 37,544 protein-encoding genes found in the 389-Mb rice genome . Notably, gene distribution is fairly homogeneous along the chromosomes of rice and Arabidopsis, but genes are distributed more heterogeneously in V. vinifera. Pachytene karyotyping analyses of the P. equestris genome showed that the distribution of heterochromatin was pericentromeric, suggesting that genes of the Phalaenopsis orchids are more homogeneously distributed (personal communication, Dr. S. B. Chang, Department of Life Sciences, National Cheng Kung University, Taiwan). Based on the genome size of Phalaenopsis, we believe that both average gene length and gene distribution may be similar to those of the rice genome, and that approximately 54,259 heterogeneously distributed genes may be present.
Simple sequence repeats (SSRs)
Distribution of simple sequence repeats in P. equestris bacterial artificial chromosome (BAC) end sequences
Distribution and frequency of simple sequence repeats (SSRs) detected in different plant species
No. of BESs
Total sequence length (bp)
Most frequent SSR motif
SSR markers have been widely used for genotyping of crop plant species [35, 36]. Of the 950 detected SSRs, we chose 206 for use in primer design (Additional file 1), and subsequently assessed whether the primers could successfully distinguish 12 Phalaenopsis species, based on allelic polymorphisms. More than 85% of primer pairs successfully amplified products from at least 1 of the 12 tested Phalaenopsis species, all of which have been extensively used as parents in breeding programs (Additional file 2). The cross-species transferability rate of the tested SSRs ranged from 76.1- 54.8% (Additional file 2), and most primer pairs produced polymorphic bands in the majority of tested Phalaenopsis species (Additional file 3). In a future study, we will examine the efficacy of such SSR markers for genotyping of commercial orchid cultivars.
Comparative mapping of orchid BAC ends to other plant genomes for identification of microsynteny
Microsynteny between Phalaenopsis and A. thaliana, O. sativa, P. trichocarpa and V. vinifera
No. of hits
50- to 300-kb sequence
The simple Monte Carlo Test  was used to assess the statistical significance of the microsynteny results. The sequences of each Phalaenopsis BES were randomly shuffled 100 times to obtain 550,600 simulated sequences, which were next BLASTN- compared to the genomic sequences of poplar, grape, rice, and Arabidopsis. None of the simulated sequences mapped to the genomes of the various plants, suggesting that our results with respect to microsynteny mapping of orchid BESs onto other plant genomes are meaningful.
Most paired ends that mapped together on plant chromosomes were annotated as ribosomal DNA (rDNA); these sequences accounted for 10 of 14 end-pairs in poplar, 10 of 12 in grape and Arabidopsis, and all 6 end-pairs of rice. In addition, all end-pairs that contained rDNA mapped to a single chromosome in each plant species.
Number of bacterial artificial chromosome (BAC) end sequences (BESs) containing Phalaenopsis chloroplast DNA with hits to the nuclear and chloroplast DNA of A. thaliana, O. sativa, P. trichocarpa and V. vinifera
Previous reports found negligible colinearity between onion (Asparagales) and rice (Poales) [38, 39]. The Asparagales include a number of economically important plants, such as asparagus, chives, garlic, leeks, onions, and orchids. Similarly, the well-documented high-level synteny among grass genomes is not found among members of other monocot orders [e.g., Musa (Zingiberales)], even though microsynteny persisted beyond the time of divergence of the Commelinid orders Poales and Zingiberales . In the present work, we failed to find any syntenic relationship between orchid and rice sequences, confirming the previously noted lack of synteny between Asparagales and Poales.
Whole-genome duplication, resulting in polyploidy, occurred in early monocots such as the Poales and Zingiberales [40, 41]. Duplication, and gene loss and rearrangements occurring after such whole-genome duplication, led to subsequent evolution and increases in morphological complexity. This may also have occurred in the orchid genome, as suggested by the presence of the four AP3-like paralogs that form the basis for the complicated floral morphologies of Phalaenopsis . Interestingly, these paralogs are present in at least four out of the five subfamilies of the Orchidaceae . Future whole-genome sequencing of Phalaenopsis should provide additional insights into genome reorganization and help to clarify differences in genomic composition between orchids and other plant species.
This analysis of Phalaenopsis BAC end sequences offers the first insights into the composition of the Phalaenopsis genome in terms of GC content, transposable elements present, protein-encoding regions, SSRs, and potential microsynteny between Phalaenopsis and other plant species. The protein sequence similarities between Phalaenopsis and grape and the potential microsynteny between Phalaenopsis and poplar are interesting and should be confirmed by large-scale BAC end sequencing. The present work also provides a good basis for additional sequence analysis of Phalaenopsis BAC libraries, and will also encourage contig fingerprinting and physical mapping of the Phalaenopsis genome.
Orchid BAC-end sequencing
BAC clones were randomly chosen from 96-well microplates and inoculated into 96-well deep-well plates containing 1.5 ml of 2x LB medium with 12.5 μg/ml chloramphenicol. Plates were incubated at 37°C with continuous shaking at 100 rpm for 20-24 h. BAC-end sequencing was performed using BigDye® Terminator v 1.1 and ABI PRISM® 3730 DNA Analyzer technologies (Applied Biosystems, Life Technologies Corporation, Foster City, CA). The work was performed by the Sequencing Core Facility of the National Yang Ming University Genome Center (YMGC, Taipei, Taiwan) and the Arizona Genomics Institute DNA Sequencing Center (AGI, Tucson, AZ).
BESs were base-called and processed using CodonCode Aligner software (Version 2.0; CodonCode Corporation, Dedham, MA), which integrates the PHRED program . We used the default parameters of "maximize region with error rate < 0.1" to trim bases from flanking sequences and next performed the operations "move all sequences shorter than 25 bases to trash" and "move all sequences with fewer than 50 Phred-20 bases to trash." Vector sequences were trimmed using Sequencher V4.1 (Gene Codes Corporation, Ann Arbor, MI) with reference to the pIndigoBAC5 DNA sequence. We next discarded all BESs < 100 bp, which yielded a set of 5,535 BESs. These were BLASTN-searched against the chloroplast DNA sequence of P. aphrodite subsp. formosana (GenBank accession no. NC_007499)  and the mitochondrial DNA sequence of O. sativa (japonica) cultivar Nipponbare (accession no. DQ167400) , using a stringent threshold of < 1e-50.
Analysis of repetitive sequences
BESs were analyzed for repetitive sequences using RepeatMasker . We applied the same default conditions as were employed in construction of the Arabidopsis, rice, and maize sections of the RepBase Update databases . We next used BLASTN and TBLASTX to search the TIGR plant repeat database (downloaded on Sep. 5, 2009)  with E-values < 1e-10 and < 1e-5, respectively. Repetitive sequences were annotated using the RepeatMasker default setting or were classified employing the TIGR codes for repetitive plant sequences.
Functional annotation of PhalaenopsisBESs
The 5,506 RepeatMasked BESs were further analyzed for protein-encoding regions via BLASTX searching of NCBI non-redundant protein databases (E-values < 1e-5). Protein-encoding BESs were BLASTN-searched against our in-house orchid EST databases [12, 13], using an E-value < 1e-20. BESs containing protein-encoding regions homologous to proteins found in the NCBI non-redundant protein databases were further analyzed in terms of Gene Ontology (GO) annotations, using a BLASTX search of the Arabidopsis genome annotation database (ftp://ftp.arabidopsis.org/home/tair/Genes/TAIR9_genome_release/; E-value < 1e-7). Categories were assigned based on biological, functional, and molecular annotations available from GO http://www.geneontology.org/.
SSR identification and marker development
BESs from A. thaliana, B. napus, M. acuminata, O. sativa, V. vinifera, and Z. mays were obtained from the Genome Survey Sequences (GSS) database of the NCBI (downloaded on Dec. 11, 2009), and subjected to SSR analysis using the same parameters as were employed in our analysis of orchid BESs. SSR types (mononucleotide to hexanucleotide) were identified using the MIcroSAtellite (MISA) tool ; the analysis required a minimum length of 20 bases for mononucleotide repeats and at least 15 bases for dinucleotide-to-hexanucleotide repeats, and allowed a maximum of an 100-nt interruption if compound repeats were encountered. Primer3 software http://frodo.wi.mit.edu/primer3/ was used for primer design. The following parameters were employed: (1) BESs with a minimum of eight dinucleotide, five trinucleotide, four tetranucleotide, three pentanucleotide, or three hexanucleotide repeats; or an SSR motif length longer than 15 bp; (2) primer lengths of 18-25 nt, with 20 nt being considered optimal; and (3) predicted PCR products of 150-350 bp. A total of 206 primer pairs (Additional file 1) were synthesized and used to amplify genomic DNA from 12 Phalaenopsis species: P. amabilis, P. aphrodite subsp. formosana, P. schilleriana, P. stuartiana, P. equestris, P. sanderiana, P. lueddemanniana, P. amboinensis, P. pulcherrima, P. fasciata, P. venosa, and P. gigantea. Genomic DNA was isolated from leaf samples using a BioKit Plant Genomic DNA Purification Kit. PCR was performed using 10 ng of genomic DNA, paired primers, dNTPs, 10× buffer, and Taq polymerase, in 20-μl reaction volumes. The PCR amplification conditions were: 94°C for 5 min followed by 45 cycles of 94°C for 60 sec, annealing (45-60°C) for 40 sec and 72°C for 40 sec, and a final extension for 5 min at 72°C. PCR products were separated on either 3% (w/v) agarose or 8% (w/v) denaturing polyacrylamide gels, which were next stained with ethidium bromide for visualization of SSR bands.
Microsynteny between P. equestris and A. thaliana, O. sativa, P. trichocarpa, and V. vinifera
Phalaenopsis BESs (not RepeatMasked) were compared with the genomic sequences of A. thaliana, O. sativa, P. trichocarpa, and V. vinifera (downloaded from the NCBI database ftp://ftp.ncbi.nih.gov/genomes/ on Feb. 27, 2010) by means of a BLASTN search with an E-value < 1e-10. To identify BACs from the Phalaenopsis library that showed microsynteny with the reference genomes, as described in a previous study on Musa , we searched the Phalaenopsis genomic sequence for BESs, both ends of which showed highly significant matches to A. thaliana, O. sativa, P. trichocarpa, or V. vinifera sequences, and that were located 50-300 kb apart in the Phalaenopsis genome.
The simple Monte Carlo Test  was used to assess the statistical significance of microsynteny between Phalaenopsis BESs and the genomes of A. thaliana, O. sativa, P. trichocarpa, and V. vinifera. The sequence of each Phalaenopsis BES was randomly shuffled 100 times to obtain 550,600 simulated sequences, which were then compared, using BLASTN, to the Arabidopsis, rice, poplar, and grape genomes (E-value < 1e-10).
List of abbreviations
bacterial artificial chromosome
BAC end sequences
MIcroSAtellite identification tool
simple sequence repeats
We thank Dr. Michel Delseny (Laboratory of Plant Genome and Plant Physiology, University of Perpignan, France) for helpful discussions and critical reading of the manuscript. We acknowledge the technical services provided by the Sequencing Core Facility at the National Yang-Ming University Genome Research Center (YMGC, Taipei, Taiwan). The Sequencing Core Facility is supported by the National Research Program for Genomic Medicine (NRPGM) of the National Science Council, Taiwan. We also acknowledge the technical services provided by the Arizona Genomics Institute (AGI) DNA Sequencing Center and the AGI Physical Mapping Center, Arizona, USA. This work was supported by grants 98-2321-B-006-004-MY3 from National Science Council, Taiwan, and 98AS-1.2.1-ST-a4 and 100AS-1.2.2-ST-a2 from Council of Agriculture, Taiwan.
- Atwood JT: The size of Orchidaceae and the systematic distribution of epiphytic orchids. Selbyana. 1986, 9: 16-Google Scholar
- Cozzolino S, Widmer A: Orchid diversity: an evolutionary consequence of deception?. Trends Ecol Evol. 2005, 20: 487-494. 10.1016/j.tree.2005.06.004.PubMedView ArticleGoogle Scholar
- Tremblay RL, Ackerman JD, Zimmerman JK, Calvo RN: Variation in sexual reproduction in orchids and its evolutionary consequences: a spasmodic journey to diversification. Biol J Linn Soc. 2005, 84: 1-54. 10.1111/j.1095-8312.2004.00400.x.View ArticleGoogle Scholar
- Otero JT, Flanagan NS: Orchid diversity--beyond deception. Trends Ecol Evol. 2006, 21: 64-65. 10.1016/j.tree.2005.11.016.PubMedView ArticleGoogle Scholar
- Gravendeel B, Smithson A, Slik FJ, Schuiteman A: Epiphytism and pollinator specialization: drivers for orchid diversity?. Philos Trans R Soc Lond B Biol Sci. 2004, 359: 1523-1535. 10.1098/rstb.2004.1529.PubMedPubMed CentralView ArticleGoogle Scholar
- Crane PR, Friis EM, Pedersen KR: The origin and early diversification of angiosperm. Nature. 1995, 374: 27-33. 10.1038/374027a0.View ArticleGoogle Scholar
- Dressler RL: Phylogeny and Classification of the Orchid Family. Portland: Dioscorides Press; 1993.Google Scholar
- Ramirez SR, Gravendeel B, Singer RB, Marshall CR, Pierce NE: Dating the origin of the Orchidaceae from a fossil orchid with its pollinator. Nature. 2007, 448: 1042-1045. 10.1038/nature06039.PubMedView ArticleGoogle Scholar
- Yu H, Goh CJ: Molecular genetics of reproductive biology in orchids. Plant Physiol. 2001, 127: 1390-1393. 10.1104/pp.010676.PubMedPubMed CentralView ArticleGoogle Scholar
- Schiestl FP, Peakall R, Mant JG, Ibarra F, Schulz C, Franke S, Francke W: The chemistry of sexual deception in an orchid-wasp pollination system. Science. 2003, 302: 437-438. 10.1126/science.1087835.PubMedView ArticleGoogle Scholar
- Tsai WC, Hsiao YY, Pan ZJ, Kuoh CS, Chen WH, Chen HH: The role of ethylene in orchid ovule development. Plant Sci. 2008, 175: 98-105. 10.1016/j.plantsci.2008.02.011.View ArticleGoogle Scholar
- Peakall R: Speciation in the Orchidaceae: confronting the challenges. Mol Ecol. 2007, 16: 2834-2837. 10.1111/j.1365-294X.2007.03311.x.PubMedView ArticleGoogle Scholar
- Tsai WC, Hsiao YY, Lee SH, Tung CW, Wang DP, Wang HC, Chen WH, Chen HH: Expression analysis of the ESTs derived from the flower buds of Phalaenopsis equestris. Plant Sci. 2006, 170: 426-432. 10.1016/j.plantsci.2005.08.029.View ArticleGoogle Scholar
- Hsiao YY, Tsai WC, Kuoh CS, Huang TH, Wang HC, Wu TS, Leu YL, Chen WH, Chen HH: Comparison of transcripts in Phalaenopsis bellina and Phalaenopsis equestris (Orchidaceae) flowers to deduce monoterpene biosynthesis pathway. BMC Plant Biol. 2006, 6: 14-10.1186/1471-2229-6-14.PubMedPubMed CentralView ArticleGoogle Scholar
- Tan J, Wang HL, Yeh KW: Analysis of organ-specific, expressed genes in Oncidium orchid by subtractive expressed sequence tags library. Biotechnol Lett. 2005, 27: 1517-1528. 10.1007/s10529-005-1468-8.PubMedView ArticleGoogle Scholar
- Tsai WC, Kuoh CS, Chuang MH, Chen WH, Chen HH: Four DEF-like MADS box genes displayed distinct floral morphogenetic roles in Phalaenopsis orchid. Plant Cell Physiol. 2004, 45: 831-844. 10.1093/pcp/pch095.PubMedView ArticleGoogle Scholar
- Tsai WC, Lee PF, Chen HI, Hsiao YY, Wei WJ, Pan ZJ, Chuang MH, Kuoh CS, Chen WH, Chen HH: PeMADS6, a GLOBOSA/PISTILLATA-like gene in Phalaenopsis equestris involved in petaloid formation, and correlated with flower longevity and ovary development. Plant Cell Physiol. 2005, 46: 1125-1139. 10.1093/pcp/pci125.PubMedView ArticleGoogle Scholar
- Hsiao YY, Jeng MF, Tsai WC, Chuang YC, Li CY, Wu TS, Kuoh CS, Chen WH, Chen HH: A novel homodimeric geranyl diphosphate synthase from the orchid Phalaenopsis bellina lacking a DD(X)2-4D motif. Plant J. 2008, 55: 719-733. 10.1111/j.1365-313X.2008.03547.x.PubMedView ArticleGoogle Scholar
- Wang CY, Chiou CY, Wang HL, Krishnamurthy R, Venkatagiri S, Tan J, Yeh KW: Carbohydrate mobilization and gene regulatory profile in the pseudobulb of Oncidium orchid during the flowering process. Planta. 2008, 227: 1063-1077. 10.1007/s00425-007-0681-1.PubMedView ArticleGoogle Scholar
- Kao YY, Chang SB, Lin TY, Hsieh CH, Chen YH, Chen WH, Chen CC: Differential accumulation of heterochromatin as a cause for karyotype variation in Phalaenopsis orchids. Ann Bot-London. 2001, 87: 387-395. 10.1006/anbo.2000.1348.View ArticleGoogle Scholar
- Lin S, Lee HC, Chen WH, Chen CC, Kao YY, Fu YM, Chen YH, Lin TY: Nuclear DNA Contents of Phalaenopsis sp. and Doritis pulcherrima. J Amer Soc Hort Sci. 2001, 126: 195-199.Google Scholar
- Shultz JL, Kazi S, Bashir R, Afzal JA, Lightfoot DA: The development of BAC-end sequence-based microsatellite markers and placement in the physical and genetic maps of soybean. Theor Appl Genet. 2007, 114: 1081-1090. 10.1007/s00122-007-0501-9.PubMedView ArticleGoogle Scholar
- Lai CWJ, Yu QY, Hou S, Skelton RL, Jones MR, Lewis KLT, Murray J, Eustice M, Guan P, Agbayani R, Moore PH, Ming R, Presting GG: Analysis of papaya BAC end sequences reveals first insights into the organization of a fruit tree genome. Mol Genet Genomics. 2006, 276: 1-12. 10.1007/s00438-006-0122-z.PubMedView ArticleGoogle Scholar
- Cheung F, Town CD: A BAC end view of the Musa acuminata genome. BMC Plant Biology. 2007, 7: 29-10.1186/1471-2229-7-29.PubMedPubMed CentralView ArticleGoogle Scholar
- Han Y, Korban SS: An overview of the apple genome through BAC end sequence analysis. Plant Mol Biol. 2008, 67: 581-588. 10.1007/s11103-008-9321-9.PubMedView ArticleGoogle Scholar
- Cavagnaro PF, Chung SM, Szklarczyk M, Grzebelus D, Senalik D, Atkins AE, Simon PW: Characterization of a deep-coverage carrot (Daucus carota L.) BAC library and initial analysis of BAC-end sequences. Mol Genet Genomics. 2009, 281: 273-288. 10.1007/s00438-008-0411-9.PubMedView ArticleGoogle Scholar
- Wing RA, Ammiraju JS, Luo M, Kim H, Yu Y, Kudrna D, Goicoechea JL, Wang W, Nelson W, Rao K, Brar D, Mackill DJ, Han B, Soderlund C, Stein L, SanMiguel P, Jackson S: The Oryza map alignment project: the golden path to unlocking the genetic potential of wild rice species. Plant Mol Biol. 2005, 59: 53-62. 10.1007/s11103-004-6237-x.PubMedView ArticleGoogle Scholar
- 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 , 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.PubMedPubMed CentralView ArticleGoogle Scholar
- Capesius I, Nagl W: Molecular and cytological characteristics of nuclear DNA and chromatin for agniosperm systematics: DNA diversification in the evolution of four orchids. Plant Syst Evol. 1978, 129: 143-166. 10.1007/BF00990757.View ArticleGoogle Scholar
- Terol J, Naranjo MA, Ollitrault P, Talon M: Development of genomic resources for Citrus clementina: characterization of three deep-coverage BAC libraries and analysis of 46,000 BAC end sequences. BMC Genomics. 2008, 9: 423-10.1186/1471-2164-9-423.PubMedPubMed CentralView ArticleGoogle Scholar
- Yuan Q, Ouyang S, Wang A, Zhu W, Maiti R, Lin H, Hamilton J, Haas B, Sultana R, Cheung F, Wortman J, Buell CR: The institute for genomic research Osa1 rice genome annotation database. Plant Physiol. 2005, 138: 18-26. 10.1104/pp.104.059063.PubMedPubMed CentralView ArticleGoogle Scholar
- The Arabidopsis Genome Initiative: Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature. 2000, 408: 796-815. 10.1038/35048692.View ArticleGoogle Scholar
- Jaillon O, Aury JM, Noel B, Policriti A, Clepet C, Casagrande A, Choisne N, Aubourg S, Vitulo N, Jubin C, Vezzi A, Legeai F, Hugueney P, Dasilva C, Horner D, Mica E, Jublot D, Poulain J, Bruye`re C, Billault A, Segurens B, Gouyvenoux M, Ugarte E, Cattonaro F, Anthouard F, Vico V, Fabbro CD, Alaux M, Gaspero GD, Dumas V, et al: The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature. 2007, 449: 463-467. 10.1038/nature06148.PubMedView ArticleGoogle Scholar
- International Rice Genome Sequencing Project: The map-based sequence of the rice genome. Nature. 2005, 436: 793-800. 10.1038/nature03895.View ArticleGoogle Scholar
- Hayden MJ, Nguyen TM, Waterman A, McMichael GL, Chalmers KJ: Application of multiplex-ready PCR for fluorescence-based SSR genotyping in barley and wheat. Mol Breed. 2008, 21: 271-281. 10.1007/s11032-007-9127-5.View ArticleGoogle Scholar
- Singh H, Deshmukh RK, Singh A, Singh AK, Gaikwad K, Sharma TR, Mohapatra T, Singh NK: Highly variable SSR markers suitable for rice genotyping using agarose gels. Mol Breed. 2010, 25: 359-364. 10.1007/s11032-009-9328-1.View ArticleGoogle Scholar
- Hope ACA: A simplified Monte Carlo significance test procedure. J Stat Soc (Ser B). 1968, 30: 582-598.Google Scholar
- Martin WJ, McCallum J, Shigyo M, Jakse J, Kuhl JC, Yamane N, Joyce MP, Gokce AF, Sink KC, Town CD, Havey MJ: Genetic mapping of expressed sequences in onion and in silico comparisons with rice show scant colinearity. Mol Gen Genomics. 2005, 274: 197-204. 10.1007/s00438-005-0007-6.View ArticleGoogle Scholar
- Jakse J, Telgmann A, Jung C, Khar A, Melgar S, Cheung F, Town CD, Havey MJ: Comparative sequence and genetic analyses of asparagus BACs reveal no microsynteny with onion or rice. Theor Appl Genet. 2006, 114: 31-39. 10.1007/s00122-006-0407-y.PubMedView ArticleGoogle Scholar
- Lescot M, Piffanelli P, Ciampi AY, Ruiz M, Blanc G, Mack JL, da Silva FR, Santos CMR, D'Hont A, Garsmeur O, Vilarinhos AD, Kanamori H, Matsumoto T, Ronning CM, Cheung F, Haas BJ, Althoff R, Arbogast T, Hine E, Pappas GJ, Sasaki T, Souza MT, Miller RNG, Glaszmann JC, Town CD: Insights into the Musa genome: Syntenic relationships to rice and between Musa species. 2008, 9: 58-Google Scholar
- Tang H, Bowers JE, Wang X, Paterson AH: Angiosperm genome comparisons reveal early polyploidy in the monocot lineage. Proc Natl Acad Sci USA. 2010, 107: 472-477. 10.1073/pnas.0908007107.PubMedPubMed CentralView ArticleGoogle Scholar
- Mondragon-Palomino M, Theissen G: MADS about the evolution of orchid flowers. Trends Plant Sci. 2008, 13: 51-59.PubMedView ArticleGoogle Scholar
- Ewing B, Hillier L, Wendl MC, Green P: Base-calling of automated sequencer traces using phred. I. Accuracy assessment. Genome Res. 1998, 8: 175-185.PubMedView ArticleGoogle Scholar
- Chang CC, Lin HC, Lin IP, Chow TY, Chen HH, Chen WH, Cheng CH, Lin CY, Liu SM, Chaw SM: The chloroplast genome of Phalaenopsis aphrodite (Orchidaceae): comparative analysis of evolutionary rate with that of grasses and its phylogenetic implications. Mol Biol Evol. 2006, 23: 279-291. 10.1093/molbev/msj029.PubMedView ArticleGoogle Scholar
- Tian X, Zheng J, Yu J: The rice mitochondrial genomes and their variations. Plant Physiol. 2006, 140: 401-410. 10.1104/pp.105.070060.PubMedPubMed CentralView ArticleGoogle Scholar
- Smit AFA, Hubley R, Green P: RepeatMasker Open-3.0. 1996, [http://www.repeatmasker.org]Google Scholar
- Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J: Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res. 2005, 110: 462-467. 10.1159/000084979.PubMedView ArticleGoogle Scholar
- Ouyang S, Buell CR: The TIGR Plant Repeat Databases: a collective resource for the identification of repetitive sequences in plants. Nucleic Acids Res. 2004, 32: 360-363. 10.1093/nar/gkh099.View ArticleGoogle Scholar
- Thiel T, Michalek W, Varshney RK, Graner A: Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet. 2003, 106: 411-422.PubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.