The first generation of a BAC-based physical map of Brassica rapa
© Mun et al; licensee BioMed Central Ltd. 2008
Received: 06 November 2007
Accepted: 12 June 2008
Published: 12 June 2008
The genus Brassica includes the most extensively cultivated vegetable crops worldwide. Investigation of the Brassica genome presents excellent challenges to study plant genome evolution and divergence of gene function associated with polyploidy and genome hybridization. A physical map of the B. rapa genome is a fundamental tool for analysis of Brassica "A" genome structure. Integration of a physical map with an existing genetic map by linking genetic markers and BAC clones in the sequencing pipeline provides a crucial resource for the ongoing genome sequencing effort and assembly of whole genome sequences.
A genome-wide physical map of the B. rapa genome was constructed by the capillary electrophoresis-based fingerprinting of 67,468 Bacterial Artificial Chromosome (BAC) clones using the five restriction enzyme SNaPshot technique. The clones were assembled into contigs by means of FPC v8.5.3. After contig validation and manual editing, the resulting contig assembly consists of 1,428 contigs and is estimated to span 717 Mb in physical length. This map provides 242 anchored contigs on 10 linkage groups to be served as seed points from which to continue bidirectional chromosome extension for genome sequencing.
The map reported here is the first physical map for Brassica "A" genome based on the High Information Content Fingerprinting (HICF) technique. This physical map will serve as a fundamental genomic resource for accelerating genome sequencing, assembly of BAC sequences, and comparative genomics between Brassica genomes. The current build of the B. rapa physical map is available at the B. rapa Genome Project website for the user community.
The genus Brassica is one of the most important vegetable crop genera in the world because it contributes to human diet, condiments, animal feed, forage, and edible or industrial oil. Many cultivated species of Brassica are also increasingly recognized as good sources of healthy metabolites such as vitamin C, soluble fiber, and multiple anti-cancer glucosinolate compounds including diindolylmethane and sulforaphane . In addition, current emphasis on rapeseed oil as a biofuel or a renewable resource for industry worldwide makes Brassica a good target of metabolic engineering.
The close phylogenetic relationship between the Brassica species and model plant Arabidopsis thaliana predicts that the knowledge transfer from Arabidopsis for Brassica crop improvement would be straightforward. However, the complex genome organization of the Brassica species as a result of multiple rounds of polyploidy and genome hybridization makes the identification of orthologous relationships of genes between the genomes highly difficult. In particular, comparative genomics study of Flowering Locus C region between B. rapa and A. thaliana genomes revealed that the Brassica genome triplicated 13 to 17 million years ago very soon after divergence from the Arabidopsis lineage. A following extensive interspersed gene loss or gain events and large scale chromosomal rearrangements including segmental duplications or deletions in the Brassica lineage complicated the orthologous relationships of the loci between the two genomes . Hybridization between Brassica species is another source of the Brassica genome complexity. The interspecific breeding between three diploid Brassica species, B. rapa (AA genome), B. nigra (BB genome), and B. oleracea (CC genome), resulted in the creation of three new species of allotetraploid hybrids B. juncea (AABB genome), B. napus (AACC genome), and B. carinata (BBCC genome) . Thus, investigation of the Brassica genome provides substantial opportunities to study the divergence of gene function and genome evolution associated with polyploidy, extensive duplication and hybridization.
Several crop Brassica species have had their genomes characterized in-depth. With favorable genetic attributes, B. rapa has been selected as a model species representing the Brassica "A" genome and is the focus of multinational genome projects. The early fruits of investigation with this well-characterized genome are evident in the recent advance in our understanding of Brassica "A" genome structure and evolution [2, 4–7]. Linkage maps have been constructed for B. rapa ssp. pekinensis cv. Jangwon , cv. VCS (Kim et al., unpublished our data), and cv. Chiifu . These genetic maps with associated markers and comparative genomics study have enabled the identification of quantitative trait loci (QTL) for club root resistance and flowering time. Large EST databases are publicly available and a 24 K oligo microarray has been developed and used to examine the transcriptome profile of B. rapa . More than 127,000 Bacterial Artificial Chromosome (BAC) end sequences and about 580 seed BAC sequences of phase 2 or 3 are also available at the National Center for Biotechnology Information (NCBI) database. In parallel to these activities, international programs are collaborating to characterize the Brassica "A" genome at the whole genome sequence level through a BAC-by-BAC sequencing approach .
A crucial component of successful genome sequencing activity with the BAC-by-BAC strategy is the availability of a genome-wide, BAC-based physical map . To date, the utility of a physical map has been reported by major genome sequencing projects of human , A. thaliana , Oryza sativa , and Medicago truncatula . These physical maps were constructed with a combination of restriction-enzyme digested BAC fragments fingerprinting on agarose gels and assembly of the fingerprints by means of FingerPrinted Contigs (FPC) software package . The agarose method has been successful, but it has limited throughput because of the need for human band calling. This is a time-consuming process requiring ample skill even when using image software . Another disadvantage of the agarose method is that few large fragments are generated, and they are difficult to size. Bands manually selected using the agarose method can often lead to a poor map [17, 18]. Fluorescence-labeled fingerprinting methods using DNA sequencing gel [19, 20] or capillary electrophoresis [21, 22] are alternative methods that have been developed to make larger and more accurate contigs with increased throughput. Fluorescence-labeled capillary electrophoresis methods include the 3-enzyme method  and the High-Information Content Fingerprinting (HICF) methods which use type IIS restriction enzyme  or the SNaPshot labeling technique [21, 23–25]. These methods facilitate improved physical map construction both in terms of throughput and quality of fingerprinting compared to the agarose method due to their automatic workflow and higher resolution [17, 22]. However, an increase in the number of enzymes and labeling colors in the HICF method can give partial digestion, star activity, and low labeling efficiency . Accordingly, several whole-genome HICF assembly maps have been built for small fungi genomes [23, 24] as well as for large genomes of maize  and catfish .
Brassica rapa has a haploid genome size of 550 megabase pairs (Mb) . Here we report the first genome-wide, BAC-based SNaPshot physical map of the Brassica "A" genome. To build a physical map, we have fingerprinted about 99,000 BAC clones by the HICF method using an ABI SNaPshot labeling kit and constructed a BAC clone contig map by means of FPC v8.5.3. Sequence-tagged site genetic markers incorporated in the genetic map anchored the euchromatic portion of the physical map to chromosomal loci. The resulting physical map allows facilitated selection of BAC clones for the B. rapa whole genome sequencing effort.
Results and discussion
BAC library source and fingerprinting
Characteristics of the three source BAC libraries of Brassica rapa ssp. pekinensis cv. Chiifu that were used in the HICF map.
Genomic DNA partially digested with
Average insert size (kb)
No. of 384 plate
No. of BACs
Average no. of valid bands per clonesb
No. of BACs with successful fingerprints
No. of BACs with repetitive sequences
Summary of the B. rapa physical map autobuild produced from assembly of the 67,468 BAC clones.
Avr. contig length (kb)b
Longest contig (kb)
Physical length (Mb)b
Q clones (%)
No. of contigs of different sizes
To assemble the physical map contigs of the B. rapa genome from BAC fingerprints, we used the program FPC v8.5.3. Before contig assembly, a series of tests were performed to determine the FPC parameter suitable for contig assembly of the full data set. Contig build at high stringency prevents chimeric joining of duplicated regions, whereas starting builds at low stringency results in maps with larger contigs that encompass more genome space . Thus, the best approach should rely on the structural characteristics of a target genome. The automatic contig build using a randomly chosen data set was tried with different cutoff values from 1e-40 to 1e-80. Based on the preliminary test, the initial cutoff value was chosen to be 1e-45. The initial parameter is reasonably stringent because the contigs generated at this cutoff value included up to 70% of the clones with less than 10% questionable clones (Q clones) which can cause chimeric assembly. Of course, assembly at higher stringency improved the build by reducing Q clones but contig coverage reduced significantly. For example, contig build at 1e-70 included only 40% of the fingerprints in contigs and left 60% as singletons. Based on this analysis, we assembled the physical map contigs in three steps. First, a cutoff value of 1e-45 was used for automatic contig assembly. Second, the "DQer" function was used to break up Q contigs (contigs containing more than 10% of Q clones) from the initial builds. Third, the remaining contigs were end-merged by "End to End" function and then singletons were added to the end of contigs by "Singles to End" function at 6 successively lower cutoffs, starting at 1e-40 and terminating at 1e-15. At each round, additional "DQer" was used to break up all bad contigs containing more than 15% Q clones (Table 2). As a result, the first contig build resulting from automatic assembly and DQer contained 4,726 contigs assembled with 42,427 (63%) clones but 25,041 (37%) clone fingerprints remained as singletons. Following an iterative process of consecutive FPC functions, "End to End", "Singles to End", and "Dqer", each successive round contributed nicely to a decrease in the contig number, singleton number, and genome coverage but to an increase in average contig length (Table 2). It is obvious that merger of singletons into the assembly is responsible for most of the increase in the number of Q clones in the map . However, Table 2 shows that only ~34% of singletons integrated into the end of the contigs contributed to the increase of Q clones in the build. This result suggests that many clones that remained as singletons at the initial stringency cutoff are not just because their fingerprints were low quality but because they may come from regions of low coverage. If this is true, the BAC libraries we used would not deeply cover the whole B. rapa genome. An unsatisfactory aspect of this assembly is its large number of Q clones (Table 2). The Q clones in this assembly corresponded to 15% of the clones. This is a bigger proportion than the cases reported from catfish (7.3%)  and maize (11%) . A large number of Q clones may result from fingerprinting error due to partial digestion, star activity, or low labeling efficiency. Though we removed the fingerprints containing centromeric repeat sequences, the remaining dataset still included highly repetitive DNA sequences. If repetitive sequences significantly affect contig assembly, deep contigs (too many clones assembled in a small region) can be made. The impact of repetitive DNA sequences on the contig assembly has been estimated. Of the 1,417 contigs, three were found to be deep contigs. Chloroplast DNA can be a source of deep contig assembly . However, Blast analysis of B. rapa chloroplast sequence against BAC-end sequences from the deep contigs suggested that these deep contigs may be derived from B. rapa genomic DNA. These three deep contigs included 71–84% of the clones as Q clones, which contribute to ~48.3% of all Q clones in the initial build. Thus, when we kill three deep contigs of the initial build due to false positive overlaps, the Q clones in the remaining 1,414 contigs correspond to 7.7% of the whole clones.
The initial build, named B. rapa physical map Build 1, has 1,417 contigs with an average length of 512 kb covering 725 Mb, 1.3× coverage of the genome. The total coverage of the physical contigs suggests that most contigs are not sufficiently overlapping and the gaps between the contigs need to be closed by additional fingerprinting. However, with our current assembly, more fingerprinting of the same libraries would not be effective in increasing coverage of the contigs and closing the gaps efficiently, because a higher proportion of the BAC clones are covering repetitive sequence regions and some regions of the genome could be poorly represented in those libraries generated by restriction enzyme digestion. For this reason, we will add more fingerprint data from a randomly sheared BAC library that is under construction, and will develop a new contig build.
Validation of contigs and manual editing
Summary of sequence-tagged site genetic markers used for contig integration into the B. rapa genetic map.
Total number of markers used
Total number of positive clones
Positive clones in contigs
Positive singleton clones
Number of markers in contigs
Number of markers in singletons
Number of contigs containing genetic markers
Contigs containing one genetic marker
Contigs containing more than one genetic markers
Finally, the reliability of the assembly has been confirmed by the results of ongoing genome sequencing of B. rapa. Integration of physical contigs into the genetic loci identified a conflict between anchors of sequence-tagged site markers. Contig 166 was found to be assembled by a false joining. Two of the markers, KS50140 and KR50161, anchored on this contig belonged to linkage group R3 but KS10551 marker was assigned to R9. We checked the CB maps of the fingerprint order of this contig and found that two independent contigs were joined by end merge at 1e-25. To further test that the merger of two structurally related genome clusters at low stringency generated a chimeric contig, we analyzed nine BAC clone sequences of this contig which were included in our genome sequencing pipeline for chromosomes R3 and R9. Sequence analysis demonstrated that seven BAC clones, associated with markers KS50140 and KR50161, assembled with one sequence scaffold of chromosome R3, whereas two BAC clones, associated with marker KS10551, merged into an existing sequence block of chromosome R9 (data not shown). Based on these results, we manually broke up this contig into two independent contigs, contig 87 and contig 190, by splitting at the weak point of the CB map. A similar conflict was found in one of the deep contigs previously mentioned. Due to complex fingerprint information and many Q clones originating from repetitive sequences, we killed this contig rather than split it. Since our analysis included only a few contigs, overall reliability of current contig build is limited. However, this validation study provided a contig assembly error estimated at 5%, in agreement with the previous reports of maize (4%)  and catfish (5%) , in which the HICF method was used. As of December 2007, chromosome sequencing of R3 and R9 on our sequencing pipeline have generated 21 and 27 sequence scaffolds which cover approximately 23 Mb and 26 Mb, respectively. Sequence analysis of the scaffolds provided validation of at least 204 contigs (data not shown).
Summary of the B. rapa physical map Build 2.
Number of clones fingerprinted
Number of clones with successful fingerprints
Number of clones used for the map construction
Number of singletons
Number of contigs
Physical length of the contigs (Mb)
Number and length of contigs anchored to chromosomea
We constructed a genome-wide BAC contig map of the B. rapa genome. This is the first whole genome physical map representing the Brassica "A" genome. As of August 7, 2007, B. rapa physical map Build 2 can be accessed by the user community by means of WebFPC. The physical map created in this study contributes to a fundamental understanding of the Brassica "A" genome structure and function as well as to the ongoing genome sequencing project as a resource for facilitating BAC selection and assembly of the genome sequence. With the goal of constructing a sequence-ready physical map, the current anchors of the contig assembly provide 242 seed points which are being extended by the BAC-by-BAC genome sequencing approach of the Multinational Brassica Genome Sequencing Project (MBGSP). In addition, the map will serve as a platform to accelerate development of Brassica comparative genomics by merging data collected from B. oleracea, a model of Brassica "C" genome (Paterson and Pires, personal communication). Efforts continue to improve the map by adding fingerprints from a randomly sheared BAC library, additional genetic mapping, and hybridization using overgo probes. All data presented in this paper with updates are available through the B. rapa Genome Project website .
Source BAC Libraries
Three BAC libraries used in this study were constructed using partial digests with three different restriction enzymes, Bam HI, Hin dIII, and Sau 3AI, as described previously (Table 1) [7, 8]. The DNA source for the BAC libraries was from the reference plant line of B. rapa ssp. pekinensis cv. Chiifu. Nearly all BAC clones used for fingerprinting were from the Bam HI and Hin dIII libraries, with a few BACs from the Sau 3AI library.
BAC clones maintained in a 384-well microplate were inoculated in four 96-deep well plates containing 2 ml of 1× LB medium with 12.5 ug/ml chloramphenicol using a Biomek-FX liquid handler (Beckman Coulter, USA). Plates were covered with Airpore gas-permeable plate sealant (Qiagen) and incubated at 37°C for 20–24 hours with continuous shaking at 900 rpm on a BioShaker (Taitek, Japan). BAC DNA was isolated using a modified alkaline lysis method followed by purification. Typically 1 to 1.5 ug of BAC DNA was obtained per BAC clone. Purified BAC DNA was digested with a mixture of five restriction endonucleases, Bam HI, Eco RI, Xba I, Xho I, and Hae III, for fragmentation. The digested DNA was labeled using ABI PRISM SNaPshot Multiplex kit (ABI No. 4323159) according to the manufacturer's instruction. The fluorescent BAC fingerprinting fragments were resuspended in 10 ul per well of Hi-Di formamide solution and then loaded onto an ABI 3730 xl DNA analyzer with 0.05 ul GeneScan-500 LIZ (ABI No. 4322682, size range from 35 to 500 bp) as an internal size standard.
Fingerprint data collection and BAC contig assembly
The fingerprint profiles for each BAC clone were collected by GeneMapper v3.7 (ABI) and then converted to a data format suitable for FPC application via GenoProfiler v2.1. Bands ranging from 50 to 500 bp in size were collected for contig assembly. For the data quality control, vector bands and clones failing fingerprinting or lacking inserts were removed manually. In addition, all samples with fewer than 50 band fragments and more than 200 band fragments were also removed. Contig assembly was carried out using FPC v8.5.3  on an HP ML370G5, with two 2.66-GHz Dual-Core Intel Xeon 5150 processors, equipped with a Redhat Enterprise Linux AS 4 platform. FPC parameter was adjusted as described by Luo et al.  and Nelson et al.  for the HICF technique. Briefly, a series of tests were conducted in which fingerprints of several sets of overlapping clones were compared using different tolerance (from 4 to 6) and cutoff (from 1e-80 to 1e-40) values. On the basis of these tests, tolerance was set at 4 to obtain the 0.4 bp optimal tolerance value determined by Luo et al.  for HICF-SNaPshot fingerprinting and the gel length was set at 20,000 bp. An initial Sulston cutoff score of 1e-45 was finally selected to be optimal for contig assembly in order to minimize the number of contigs without overly increasing the number of questionable clones. Contigs with more than 10 Q clones were reassembled by the "DQer" function of FPC. The resulting contigs were merged by "End to End" auto merge function with a minimum of two matching ends. The remaining singletons were merged to the contigs by "Singles to End" function and the "DQer" function was used to finish the process by removing Q clones from the resulting contigs.
BAC anchoring and manual contig editing
To anchor BAC-based physical contigs to the genetic and cytogenetic maps, 315 sequence-tagged site genetic markers developed from the sequenced BAC clones were used [ and Jin et al., unpublished our result]. During BAC anchoring, the contigs showing conflict in the marker-BAC relationship were manually split based on CB map and BES information. Centromeric repetitive sequences (CentBr and CRB), pericentromeric repetitive sequences (PCRBr, 5S, and 25S rDNA), and chloroplast sequence (NCBI accession DQ231548) were analyzed by BLASTN search at cutoff value 1e-10 against BAC end sequence database downloaded from NCBI.
High-density BAC filter screen and Southern blot analysis
The high-density Hin dIII BAC filters were made according to Park et al. . The BAC DNA (50 ng) was digested with Eco RV or Hin dIII, separated in 1% agarose gel, and transferred onto a nylon membrane (Hybond N+, Amersham Pharmacia Biotech) using the standard capillary transfer method. To make RFLP probes, insert DNA of BAN2, BAN235 and BAN245 cDNA clones were amplified by PCR using T3 and T7 primers and then purified by Qiagen gel extraction kit. Probes were labeled using random oligonucleotide priming under the conditions according to the manufacturer's instruction (Megaprime Labeling System, Amersham Pharmacia Biotech). Hybridizations were carried out at 65°C for 24 h with [α-32P]-labeled DNA probes. Following hybridization, membranes were washed twice in 2 × SSC and 0.5% SDS for 15 min, followed by 1 × SSC and 0.1% SDS for 20 min, and 0.5 × SSC and 0.1% SDS for 20 min at 65°C. The membranes were exposed to X-ray film for 2–3 days at -80°C with intensifying screens.
We thank Hee-Ju Yu of NHRI for sincere discussion and Young Joo Seol and Jang-Ho Hahn of NIAB for IT support. This work was supported by the BioGreen 21 Program (20050301034438) and by the National Institute of Agricultural Biotechnology (05-1-12-2-1), Rural Development Administration, Korea.
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