DNA Research Advance Access published online on June 25, 2007
DNA Research, doi:10.1093/dnares/dsm012
© The Author 2007. 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
Radiation Hybrid Maps of Medaka Chromosomes LG 12, 17, and 22
Feng Su1,
Yumi Osada2,
Marc Ekker3,
Mario Chevrette4,
Atsushi Shimizu5,
Shuichi Asakawa5,
Aiko Shiohama5,
Takashi Sasaki5,
Nobuyoshi Shimizu5,
Toshiyuki Yamanaka2,
Takao Sasado2,
Hiroshi Mitani6,
Robert Geisler7,
Hisato Kondoh1,2 and
Makoto Furutani-Seiki2,* 
1 The Graduate School of Frontier Biosciences, Osaka University, 1–3 Yamadaoka, Suita, Osaka 565-0871, Japan
2 SORST Kondoh Research Team, Japan Science and Technology Agency (JST), 14 Yoshida-Kawaracho, Sakyo-ku, Kyoto 606-8305, Japan
3 Department of Biology, Center for Advanced Research in Environmental Genomics, University of Ottawa, 20, Marie Curie, Ottawa, ON, Canada K1N 6N5
4 The Research Institute of the McGill University Health Centre and Department of Surgery, McGill University, Montreal, QC, Canada H3G 1A4
5 Department of Molecular Biology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
6 Department of Integrated Bioscience, Graduate School of Frontier Science, The University of Tokyo, Bioscience Building, 102, Kashiwa, Chiba 277-8562, Japan
7 Max-Planck-Institut für Entwicklungsbiologie, Abteilung III–Genetik, Spemannstrasse 35, Tübingen D-72076, Germany
Received 15 December 2006; revised 8 May 2007
 |
Abstract
|
|---|
The Medaka is an excellent genetic system for studies of vertebrate
development and disease and environmental and evolutionary biology
studies. To facilitate the mapping of markers or the cloning
of affected genes in Medaka mutants identified by forward-genetic
screens, we have established a panel of whole-genome radiation
hybrids (RHs) and RH maps for three Medaka chromosomes. RH mapping
is useful, since markers to be mapped need not be polymorphic
and one can establish the order of markers that are difficult
to resolve by genetic mapping owing to low genetic recombination
rates. RHs were generated by fusing the irradiated donor, OLF-136
Medaka cell line, with the host B78 mouse melanoma cells. Of
290 initial RH clones, we selected 93 on the basis of high retention
of fragments of the Medaka genome to establish a panel that
allows genotyping in the 96-well format. RH maps for linkage
groups 12, 17, and 22 were generated using 159 markers. The
average retention for the three chromosomes was 19% and the
average break point frequency was
33 kb/cR. We estimate the
potential resolution of the RH panel to be
186 kb, which is
high enough for integrating RH data with bacterial artificial
chromosome clones. Thus, this first RH panel will be a useful
tool for mapping mutated genes in Medaka.
Key words: Medaka; radiation hybrid mapping; genetic mapping; BAC
|
1. Introduction
|
|---|
Radiation hybrid (RH) mapping is an efficient way for ordering
markers in correlation with physical distance on the chromosome
and establish links with genetic maps and bacterial artificial
chromosome (BAC) contigs.
1
,2 An RH panel consists of cell hybrids
that randomly retain fragments of chromosomes from the donor
cells. These hybrids are produced by fusion of irradiated donor
cell of the species of interest with a recipient cell line,
usually of rodent origin and have the following features: (i)
Markers are scored by PCR analysis for the presence or the absence
of DNA from the hybrids. Therefore, markers to be mapped need
not to be polymorphic in RH mapping, which facilitates the production
of dense maps of the genome. Markers with similar patterns of
retention in the collection of hybrids are placed close to each
other on the map. (ii) RH mapping depends on random physical
breakage of chromosomes by irradiation and thereby reflects
physical distance, whereas genetic mapping relies on meiotic
recombination rate. Markers close to the centromere, which are
difficult to be resolved by genetic mapping, can be ordered
in RH mapping. (iii) Furthermore, the resolution of the RH panel
can be adjusted by the dose of radiation to achieve the resolution
required for linking the RH map with a genetic map and/or with
BAC contigs.
1,2 Thus, RHs of human,
3–5 dog,
6 rat,
7 mouse,
8,9 and zebrafish
10,11 have played a key role in localizing markers
and anchoring BAC contigs on the chromosomes.
The Medaka, Oryzias latipes, a small freshwater fish,12 has proven to be an excellent genetic system for developmental, environmental, and evolutionary biology studies. A genetic linkage map of Medaka that consists of 24 linkage groups (LG) corresponding to the haploid chromosome number of the organism was established.13 Recently, genomic resource of Medaka including EST,14 genetic map,13,15 and genomic DNA sequence,16 whole-genome shotgun data on UT browser (http://medaka.utgenome.org/), has been developed. Furthermore, a large-scale systematic mutagenesis screen was performed in Medaka to explore gene functions in developmental processes.17 To facilitate the identification of affected genes in Medaka mutants, we established a whole-genome Medaka RH panel consisting of 93 clones. As the first step toward the development of a Medaka RH map, we constructed RH maps for three chromosomes LG12, 17, and 22.
|
2. Generation of Medaka RHs
|
|---|
Two-hundred and ninety RH clones were produced by fusing donor
cells from the Medaka fin fibroblast cell line OLF-136
18 (obtained
from Riken Cell Bank, RCB 0184), derived from HB32 South Strain
with B78 mouse melanoma cells, as described by Hukriede et al.
11 For this purpose, a subline of OLF-136 with the highest percentage
of euploid cells was selected by karyotyping and used to generate
RHs. As the mouse melanoma B78 recipient cell line is not deficient
in any enzyme that would allow selection of hybrid cells, we
generated OLF-136 clones that randomly integrated the aminoglycoside
phosphotransferase gene that confers resistance to G418 into
the chromosomes. More than 500 independent G418 OLF-136 clones
were pooled and 3
x 10
7 cells from this pool were subjected
to X-ray irradiation at a dose of 5000 rad (50 Gy). The irradiated
cells were mixed with an equal number of B78 cells and fused
in the presence of polyethylene glycol. After 3 weeks, G418-resistant
colonies were picked and expanded for DNA extraction or frozen
to maintain stocks.
|
3. Establishment of the Medaka RH panel
|
|---|
To carry out the genotyping of the RH panel in a 96-well microtiter
plate format, we selected 93 RH clones by the following procedures:
(i) Among the 290 RHs, we first selected 136 RHs that gave clear
bands in PCR genotyping, using 932 STS (sequence-tagged site)
markers randomly selected from the 24 LGs. (ii) Among these
136 RHs, 93 RHs were selected on the basis of their high retention
of Medaka chromosomes fragments. For independent estimates of
retention,
19 among those markers that gave no more than one
typing error in triplicate genotyping assays, only one or two
markers with the largest distance on the genetic map were chosen
from a single LG. The retention frequency of the selected 93
RH clones based on 26 STS markers from 15 LGs was 16%.
The RHs were genotyped by PCR amplification, followed by gel electrophoresis, and the results of genotyping for a marker, designated as an RH vector, were documented as described.19 Sequences of STS markers were obtained from the MBASE (http://mbase.bioweb.ne.jp/). PCR reactions were set up in a 384-well format, using the Biomeck 2000 robotic system (Beckman, USA). Since the donor Medaka chromosomal fragments are retained at different molarities among the RH cell lines, the intensity of amplified bands may vary among them.3 Therefore, genotyping of the RHs was carried out three times to minimize discordance. Discordance between the multiple runs of a marker was kept below 7% of the total number of RHs. The markers that showed higher discordance were eliminated.
|
4. Generation of RH maps for three Medaka chromosomes
|
|---|
To generate RH maps for the three chromosomes (Fig.
1),
we took the following steps. The numbers of markers relevant
to each step are listed in Table
1.
- From LG12, 17, and 22 of the genetic maps, markers that gave reliable RH vectors were chosen. A total of 159 STS markers from the genetic map, that is, 50, 60, and 49 markers from LG12, 17, and 22, respectively, were subjected to genotyping on the RH panel. Twenty-six of these markers were excluded because they yielded no PCR products or ambiguous bands, leaving 133 markers (84%) for the following RH map construction. We used the TSP/CONCORD program to analyze the RH vectors, as described in the following section.
- We checked whether the 133 markers fall into three groups corresponding to the three genetic LGs by searching linked markers with a threshold of pairwise LOD scores up to 5. This resulted in three LGs in agreement with the genetic map, as well as 17 singletons. The singletons were discarded. The three LGs included 42, 42, and 32 markers (total 116) from LG12, 17, and 22, respectively.
- To generate high-confidence framework maps, markers from each LG in the previous step were analyzed with a pairwise LOD score threshold of 7. Three disconnected framework marker sets with two gaps were formed for LG17 and LG22, whereas a single-framework map with no gap was formed for LG12. Those disconnected framework marker sets were oriented and linked by referring to the linkage information of the genetic map to make one framework map for LG17 and 22.
- Finally, to compose the final RH maps, we put the rest of the markers on the framework map, using the placement program. The two gaps in the framework maps of LG12 and 22 could not be filled up by this procedure.
View larger version (50K):
[in this window]
[in a new window]
[Download PowerPoint slide]
|
Figure 1. Comparison of the RH and genetic maps for the three Medaka chromosomes. Positional relationships of the markers on the RH (left) and genetic (right) maps are indicated by green lines. The distances between adjacent markers are shown in centiRay in the RH maps and centiMorgan in the genetic maps. In the RH maps, there are two gaps indicated as ‘Gap’ in LG17 and 22. The markers used to build the framework map are shown in red and those used for later placement are in black. On the genetic maps, centromeric regions are indicated in purple.
|
|
The final RH maps of the three LGs and the comparison between
the RH and genetic maps are shown in Fig.
1. Remarkably,
comparisons of the placement of the markers in the RH maps with
those in the genetic maps indicated that the markers with poor
resolution in genetic maps in the putative centromeric regions
(shown in purple) could be well resolved in the RH maps.
As shown in Table 2, given the estimated physical lengths, 30, 32, and 29 Mb, of LG12, 17, and 22, respectively, the physical distances corresponding to 1 cR5000 were calculated to be 41, 35, and 46 kb for LG12, 17, and 22, respectively. The average marker retention frequencies for LG12, 17, and 22 were 26, 16, and 13%, respectively.
The three RH maps have a high confidence since the framework
linkage maps were obtained with an LOD score >7 and each
marker was linked at least to one other marker with an LOD score
>5 (corresponding to a likelihood of >100 000:1) in the
final RH maps (Table
1 and Fig.
1). A total of 110
markers, 83% of the 133 markers that gave the RH vectors, could
be placed on the final RH maps (Table
1). The lower success
rate (75%) for LG22 could be due to its lower retention (13%;
Tables
1 and
2). The average resolution of the three RH
maps is 186 kb, which is high enough to place BAC clones (150–200
kb) on the RH maps. The average retention frequency of the 110
markers mapped to the three LGs was 19% (Table
2). This
is comparable with whole-genome RH panels of other species whose
overall retention ranges between 16 and 30%.
9–11,20,21
Recently, the Medaka genome sequence has become accessible: the complete sequence of LG22 by BAC-based sequencing approach15 and the assembled sequence data from the whole-genome shotgun approach (UT genome browser). The alignment of the RH and genetic maps with the complete sequence of LG22 showed a high correlation of the RH map with the physical length of the genome (Fig. 2i). The poorly resolved region in the male genetic map of LG22 (shown by the red line at 33 cM, nine out of 30 markers) was resolved into 170 cR, which corresponds to 11.4 Mb. This region spans nearly one-third of the LG22 genome sequence. Similar results were obtained for LG12 and 17 assembled sequences (Fig. 2ii and iii). Markers that were not found in the genome sequences (those plotted at 0 Mb), 2, 3, and 1 on LG22, 12, and 17, respectively, were successfully mapped on the RH maps. These results further corroborate the usefulness of RH maps for establishing the complete sequence of the Medaka genome.
View larger version (19K):
[in this window]
[in a new window]
[Download PowerPoint slide]
|
Figure 2. Consistency of the RH maps with the genome sequence. Markers on the LG22, 12, 17 were plotted on the Y axis as genetic map position in centi-Morgan (cM) (pink) and RH map position in cR (blue) and on the X axis as the position in the BAC-based genome sequence of (i) LG22 or assembled the whole genome shotgun sequence reads of (ii) LG12 and (iii) LG17. In the case of LG22, markers poorly resolved on the red line (nine out of 30 markers) at 33.8 cM on the genetic map were resolved into 170 cR (B) on the RH map that corresponds to 11.4 Mb (A), one-third of the physical length of LG22. The poorly resolved regions in LG12 and 17 were resolved into 154 and 338 cR, which correspond to13.0 and 14.2 Mb, one-third and nearly a half of the chromosome. Markers that were not found in the genome sequence (those plotted at 0 Mb), 2, 3, and 1 on LG22, 12, and 17, respectively, were successfully mapped on the RH maps.
|
|
Taken together, we produced the first whole-genome RH panel
for mapping genes and markers in Medaka and demonstrated that
it is suitable to build a genome-wide RH map. The construction
of RH maps for the other Medaka LGs is ongoing. We will distribute
the Medaka RH panel upon request to the corresponding author
and provide assistance in RH mapping efforts.
|
5. Computation of RH maps
|
|---|
To construct RH maps, the TSP/CONCORD V2.0 software package,
22 working with IBM DB2, was used on an IBM RS/6000 AIX workstation.
TSP/CONCORD was used in conjunction with CONCORD and QSopt software
to calculate RH maps by solving the Traveling Salesman Problem.
23 This method has been proven to be rapid and efficient for integrating
large data and constructing an RH map.
22 We referred to TSP/CONCORD's
manual to analyze RH vectors and to compute the marker order
of each LG and the distance between markers. In the package,
there are five objective functions for the evaluation of an
RH vector available: two of them are based on obligate chromosome
breaks (OCBs) and three on a maximum likelihood estimate (MLE).
Since the OCB objective functions do not provide indications
for estimating physical distances between markers and for comparing
likelihoods of competing marker orders, only the three MLE objectives,
namely, BASE TSP + MLE, Extended TSP + MLE, and Normalize TSP
+ MLE, were used in our computations. To construct the framework
maps, most of the parameters were set to the program default
values; three of them are sensitive for restricting the number
of markers in computation, they were LIMIT_DISTANCE = 3, LIMIT_
LIKELIHOOD = 3, and UNKNOWN_COUNT = 2.
First, pairwise LOD scores and distances for each pair of markers were computed by using the TSP/CONCORD ‘pairlods_dists’ program. At an LOD score threshold of 5, the program ‘make_groups’ was executed to find LGs for all markers. Singletons were abandoned. For each of those LGs, marker sets were identified at an LOD score threshold of 7 by using again the ‘make_groups’ program. Subsequently, the framework maps of each marker set were computed by using the MLE objective functions in the package. We confirmed the robustness of each framework map by making sure that there are no improving flips of up to eight markers by using the program ‘flips’ and that there are no alternatives within 0.25 LOD units of the best marker order by using the program ‘map_eval’. Subsequently, the markers that were not on the framework maps were placed by performing ‘placement <marker_data> <framework_map >’ iteratively, generating maps for all marker sets. The initial maps of each LG were ordered and oriented relative to each other by referring to the genetic map. Finally, the initial maps of each LG were joined by using the three MLE objective functions of the package to generate three candidate maps. From these three candidates, an optimal one was picked up as the final RH map by comparing the results of the program ‘quality’.
|
Acknowledgments
|
|---|
This research was generously supported by grants from Japan
Science and Technology Agency: a PREST grant to M. F.-S., and
ERATO and SORST grants to H.K. This study was also supported
in part by the Ground-based Research Program for Space Utilization
from the Japan Space Forum to M.F.-S. and H.M. We thank Lucille
Joly and Patricia Tellis for technical assistance. F.S. was
supported by 21st Century COE program ‘Dynamic of Biological
System’.
|
Footnotes
|
|---|
* To whom correspondence should be addressed. Tel. +44 (0) 1225 38 5046. Fax. +44 (0) 1225 38 6779. E-mail: furutaniseiki{at}msi.biglobe.ne.jp
Communicated by Yuji Kohara
Present address: Centre for Regenerative Medicine, Developmental Biology Programme, Department of Biology and Biochemistry, University of Bath, Claverton Down, Bath BA2 7AY, UK 
|
References
|
|---|
- Cox D. R., Burmeister M., Price E. R., Kim S., Myers R. M. Radiation hybrid mapping: a somatic cell genetic method for constructing high-resolution maps of mammalian chromosomes. Science (1990) 250:245–250.[Abstract/Free Full Text]
- Walter M. A., Spillett D. J., Thomas P., Weissenbach J., Goodfellow P. N. A method for constructing radiation hybrid maps of whole genomes. Nat. Genet. (1994) 7:22–28.[CrossRef][Web of Science][Medline]
- Hudson T. J., Stein L. D., Gerety S. S., et al. An STS-based map of the human genome. Science (1995) 270:1945–1954.[Abstract]
- Stewart E. A., McKusick K. B., Aggarwal A., et al. An STS-based radiation hybrid map of the human genome. Genome Res. (1997) 7:422–433.[Abstract/Free Full Text]
- Gyapay G., Schmitt K., Fizames C., et al. A radiation hybrid map of the human genome. Hum. Mol. Genet. (1996) 5:339–346.[Abstract/Free Full Text]
- Priat C., Hitte C., Vignaux F., et al. A whole-genome radiation hybrid map of the dog genome. Genetics (1998) 54:361–378.
- Watanabe T. K., Bihoreau M.-T., McCarthy L. C., et al. A radiation hybrid map of the rat genome containing 5,255 markers. Nat. Genet. (1999) 22:27–36.[CrossRef][Web of Science][Medline]
- McCarthy L. C., Terrett J., Davis M. E., et al. A first-generation whole genome-radiation hybrid map spanning the mouse genome. Genome Res. (1997) 7:1153–1161.[Abstract/Free Full Text]
- Etten W. J. V., Steen R. G., Nguyen H., et al. Radiation hybrid map of the mouse genome. Nat. Genet. (1999) 22:384–387.[CrossRef][Web of Science][Medline]
- Geisler R., Rauch G.-J., Baier H., et al. A radiation hybrid map of the zebrafish genome. Nat. Genet. (1999) 23:86–89.[CrossRef][Web of Science][Medline]
- Hukriede N. A., Joly L., Tsang M., et al. Radiation hybrid mapping of the zebrafish genome. Proc. Natl Acad. Sci. USA (1999) 96:9745–9750.[Abstract/Free Full Text]
- Shima A., Mitani H. Medaka as a research organism: past, present and future. Mech. Dev. (2004) 121:599–604.[CrossRef][Web of Science][Medline]
- Naruse K., Fukamachi S., Mitani H., et al. A detailed linkage map of medaka, Oryzias latipes: comparative genomics and genome evolution. Genetics (2000) 154:1773–1784.[Abstract/Free Full Text]
- Kimura T., Jindo T., Narita T., et al. Large-scale isolation of ESTs from medaka embryos and its application to medaka developmental genetics. Mech. Dev. (2004) 121:915–932.[CrossRef][Web of Science][Medline]
- Naruse K., Tanaka M., Mita K., Shima A., Postlethwait J., Mitani H. A medaka gene map: the trace of ancestral vertebrate proto-chromosomes revealed by comparative gene mapping. Genome Res. (2004) 14:820–828.[Abstract/Free Full Text]
- Sasaki T., Shimizu A., Ishikawa S. K., et al. The DNA sequence of medaka chromosome LG22. Genomics (2007) 89:124–133.[CrossRef][Web of Science][Medline]
- Furutani-Seiki M., Sasado T., Morinaga C., et al. A systematic genome-wide screen for mutations affecting organogenesis in Medaka, Oryzias latipes. Mech. Dev. (2004) 121:647–658.[CrossRef][Web of Science][Medline]
- Etoh H., Suyama I., Hyodo-Taguchi Y., Matsudaira H. Establishment and characteristics of various cell lines from medaka (Teleostei). In: Invertebrate and Fish Tissue Culture 1988—Kuroda Y., Kurstak E., Maramorosch K., eds. (1988) Tokyo/Springer-Verlag, Berlin: Japan Scientific Societies Press.
- Jones H. B. Hybrid selection as a method of increasing mapping power for radiation hybrids. Genome Res. (1996) 6:761–769.[Abstract/Free Full Text]
- Geisler R. Mapping and cloning in zebrafish. In: Nüsslein-Volhard, C. and Dahm, R. eds. In: A Practical Approach (2002) Oxford: Oxford University Press. 261.
- Birren B., Green E. D., Hieter P., eds. Genome Analysis: A Laboratory Manual: Mapping Genome (1999) 4. New York: Cold Spring Harbor Laboratory Press. Genome Analysis Series.
- Morisson M., Lemière A., Bosc S., et al. ChickRH6: a chicken whole-genome radiation hybrid panel. Genet. Sel. Evol. (2002) 34:521–533.[CrossRef][Web of Science][Medline]
- Agarwala R., Applegate D. L., Maglott D., Schuler G. D., Schaffer A. A. A fast and scalable radiation hybrid map construction and integration strategy. Genome Res. (2000) 10:350–364.[Abstract/Free Full Text]
- Applegate D., Bixby R., Chvatal V., Cook W. On the solution of traveling salesman problems. Doc. Math (1998) III:645–656. (J. DMV, Extra Volume) ICM 1998.
CiteULike 
Connotea 
Del.icio.us What's this?
Top
Abstract
1. Introduction