Nucleic Acids Research Advance Access originally published online on October 11, 2007
Nucleic Acids Research 2008 36(Database issue):D747-D752; doi:10.1093/nar/gkm765
Nucleic Acids Research, 2008, Vol. 36, Database issue D747-D752
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
UTGB/medaka: genomic resource database for medaka biology
Budrul Ahsan1,2,
Daisuke Kobayashi2,3,
Tomoyuki Yamada1,2,
Masahiro Kasahara1,
Shin Sasaki1,
Taro L. Saito1,
Yukinobu Nagayasu1,
Koichiro Doi1,
Yoichiro Nakatani1,
Wei Qu1,
Tomoko Jindo3,
Atsuko Shimada3,
Kiyoshi Naruse3,4,
Atsushi Toyoda5,
Yoko Kuroki5,
Asao Fujiyama5,6,
Takashi Sasaki7,
Atsushi Shimizu7,
Shuichi Asakawa7,
Nobuyoshi Shimizu7,
Shin-ichi Hashimoto8,
Jun Yang8,
Yongjun Lee8,
Kouji Matsushima8,
Sumio Sugano9,
Mitsuru Sakaizumi10,
Takanori Narita3,11,
Kazuko Ohishi11,
Shinobu Haga11,
Fumiko Ohta11,
Hisayo Nomoto11,
Keiko Nogata11,
Tomomi Morishita11,
Tomoko Endo11,
Tadasu Shin-I11,
Hiroyuki Takeda3,
Yuji Kohara11 and
Shinichi Morishita1,2,*
1Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa 277-0882, 2Bioinformatics Research and Development (BIRD), Japan Science and Technology Agency (JST), Tokyo 102-8666, 3Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, 4National Institute for Basic Biology, Okazaki 444-8585, 5RIKEN Genomic Sciences Center, Yokohama 230-0045, 6National Institute of Informatics, Tokyo 101-8430, 7Department of Molecular Biology, Keio University School of Medicine, Tokyo 160-8582, 8Department of Molecular Preventive Medicine, School of Medicine, The University of Tokyo, Tokyo 113-0033, 9Department of Medical Genome Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, 10Department of Environmental Science, Faculty of Science, Niigata University, Niigata 950-2181 and 11Center for Genetic Resource Information, National Institute of Genetics, Mishima 411-8540, Japan
* To whom correspondence should be addressed. Tel: +81 47 136 3984; Fax: +81 47 136 3977; Email: moris{at}cb.k.u-tokyo.ac.jp
Received August 15, 2007. Revised September 10, 2007. Accepted September 11, 2007.
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ABSTRACT
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Medaka (
Oryzias latipes) is a small egg-laying freshwater teleost
native to East Asia that has become an excellent model system
for developmental genetics and evolutionary biology. The draft
medaka genome sequence (700 Mb) was reported in June 2007, and
its substantial genomic resources have been opened to the public
through the University of Tokyo Genome Browser Medaka (UTGB/medaka)
database. This database provides basic genomic information,
such as predicted genes, expressed sequence tags (ESTs), guanine/cytosine
(GC) content, repeats and comparative genomics, as well as unique
data resources including (i) 2473 genetic markers and experimentally
confirmed PCR primers that amplify these markers, (ii) 142 414
bacterial artificial chromosome (BAC) and 217 344 fosmid end
sequences that amount to 15.0- and 11.1-fold clone coverage
of the entire genome, respectively, and were used for draft
genome assembly, (iii) 16 519 460 single nucleotide polymorphisms
(SNPs), and 2 859 905 insertions/deletions detected between
two medaka inbred strain genomes and (iv) 841 235 5'-end serial
analyses of gene-expression (SAGE) tags that identified 344
266 transcription start sites on the genome. UTGB/medaka is
available at:
http://medaka.utgenome.org/
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INTRODUCTION
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Teleosts comprise more than half of all vertebrate species and
have adapted to a variety of marine and freshwater habitats
(
1). For the past two decades, smaller teleosts, such as zebrafish
and medaka, have been used to study various aspects of basic
biology because of the power of forward genetics and the availability
of elegant embryo manipulation techniques. Medaka has frequently
been used for carcinogenesis studies and for testing endocrine
disruptors in ecotoxicology analysis (
2). Furthermore, medaka
research has a long, outstanding history in the field of sex
determination: it facilitated the first demonstration of Y-linked
inheritance in any species (
3), the first successful sex-reversal
in vertebrates (
4) and the identification of the male-determining
gene,
DMY, the first non-mammalian functional equivalent of
SRY (
5). Highly polymorphic and healthy inbred strains of medaka
have been used for both mutagenesis screening and genetic mapping.
Furthermore, medaka research has recently been boosted by the
successful generation of hundreds of developmental mutants (
6).
Significantly, some of these mutants have unique phenotypes
that are not covered by zebrafish mutants, probably due to different
gene repertoires. These features make medaka an attractive system
for developmental genetics. To afford users quick access to
medaka developmental biology resources, UTGB/medaka includes
various unique datasets, as well as sophisticated genomics tools.
While general purpose genome browsers, Ensembl and UCSC (
7,
8),
courteously provide the medaka genome and its fundamental features
(e.g. predicted genes, ESTs, GC content, repeats and comparative
genomics), most of genomic resources described in this article
are obtainable only from UTGB/medaka because these resources
are tailored to specific needs in medaka biology and are designed
to facilitate both designing further biological experiments
and obtaining libraries of interest.
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DATA RESOURCES
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Genome sequences
The genome of Hd-rR, an inbred medaka strain, was assembled
from 13.8 million reads that were obtained from the whole genome
shotgun plasmid, fosmid and bacterial artificial chromosome
(BAC) libraries (
9). The total size of the assembled contigs
was 700.4 megabases (Mb), although previous estimates range
from 851 to 1080 Mb, according to the measurement of haploid
weight (
10–13). This discrepancy was an inevitable result
of selecting the whole-genome shotgun sequencing strategy, which
is cost efficient but suffers from inherent technical limitations.
For example, highly homologous repetitive elements are likely
to be grouped into small contigs, and are rarely anchored onto
unique positions in the genome owing to their redundancy (
9).
Therefore, the assembled contigs largely represent the medaka
genome but may fail to include highly repetitive elements. Of
the 700.4 Mb in the sequenced genome, 50% of nucleotides are
covered in scaffolds (or contigs) of length > 1.41 Mb (9.8
kb) that are called N50 values. This contiguity is sufficient
to characterize the genomic structures of genes.
The medaka genome sequence data have been released to the public four times to meet urgent requests from the medaka research community. Four versions named 200406, 200506, version 0.9 and version 1.0 have been created to provide users with timely information. The former two versions had shorter scaffolds that were not anchored on the medaka chromosomes because they were built in 2004 and 2005, before genetics markers were available. Versions 0.9 and 1.0 were created in 2006, when comprehensive genetic markers were available, so that about 90% of their scaffolds and ultracontigs were located on the 24 medaka chromosomes. Versions 0.9 and 1.0 were built from the identical contigs and scaffolds, but the assembly of version 1.0 is longer than that of version 0.9 because more genetic markers could be used to generate version 1.0. Version 0.9 is left open to the public because most of the data analysis in the medaka genome paper (9) was based on version 0.9. In these two versions, two scaffolds linked by a single BAC are connected into one ultracontig if it is consistent with genetic markers. The N50 value of ultracontigs in version 1.0 amounted to 5.1 Mb, excluding gaps, and therefore, the great continuity of ultracontigs promises to accelerate the task of positional cloning with an ample number of confirmed genetic markers in our database.
BAC/Fosmid end sequences
Another principal data resource in our database is the fosmid and BAC end sequences anchored on the medaka chromosomes. Sequencing a gene of interest makes it possible to map the uncovered sequence of the gene onto the genome, but the aligned region may still contain some gaps to be finalized because of the aforementioned limitations in the whole-genome shotgun sequencing method. The availability of BAC or fosmid clones that cover the genomic region of interest is indispensable to the task of filling gaps and finalizing the region. To assist this process, our genome browser displays the positions of end sequences of BAC and fosmid clones surrounding the genomic region of interest (see Figure 1B). Actually, sufficient fosmid and BAC clones have been collected for sequencing the medaka genome; namely, 217 344 fosmid end sequences and 142 414 BAC end sequences have been mapped on the genome. To be more precise, two types of fosmid library are of average size 35.5 and 37.5 kb, and three types of BAC library are of average size 135, 180 and 210 kb. The respective clone coverage of fosmids and BACs are 11.1 and 15.0 times of the medaka genome, demonstrating that sufficient fosmid and BAC libraries are available for completing a specific region.
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Figure 1. Snapshot of UTGB/medaka. (A) Basic genomic information such as bases, quality values and sequence coverages of individual bases, GC content and repeats. (B) Positions of BAC and fosmid end sequences. Right (or left) arrows mean that the BAC/fosmid clone is in the sense (antisense) strand. (C) Single nucleotide polymorphism (SNP), single sequence length polymorphism (SSLP) and restriction fragment length polymorphism (RFLP) markers. (D) SNPs and insertions/deletions between medaka inbred strains Hd-rR and HNI. Details are shown in the magnification view (Figure 1F). (E) In the upper row, the height of a red bar presents the number of 5'SAGE tags observed at the position, while the lower row displays genes predicted from TSSs identified by 5'SAGE tags. The range enclosed in the box is magnified and shown in the lower portion. (F) SNPs and indels. Pink indicates matched bases, while mismatches are highlighted by green, yellow, blue and red that represent A, C, G and T, respectively, in the HNI genome. Cyan indicates the two possibilities, deletions from the HNI genome or insertions into the Hd-rR genome, though the settlement requires comparison with the genome of an outgroup of Hd-rR and HNI. Gray means the failure of the alignment because of low quality bases in either of the two genomes or lack of HNI reads in the region. (G) The positions of individual 5'SAGE tags are illustrated by red boxes. The label associated with each 5'SAGE tag is of the form S_F (L0, L1), where S indicates whether the tag is derived from the sense (+) or the antisense strand (–) of the position, F is the frequency of occurrences of the tag in the collection from a mixture of cDNA, and L0 (L1, resp.) means the number of loci where the tag is aligned to the genome with no mismatch (with one mismatch). Tags are aligned to unique positions if L0 = 1, or L0 = 0 and L1 = 1. For example, a tag labeled with +_4(1,2) is observed four times in the tag collection, it is aligned uniquely to the plus strand of the position without mismatch, and it is also aligned to two other locations with one mismatch. A tag with –_1(0,1) occurs once in the collection and fails to map to the genome with no mismatch but maps uniquely to the minus strand of the position with one mismatch. The figure displays a large number of 5'SAGE tags are observed in both strands. (H) The structures of two predicted genes are shown. Boxes represent protein-coding exons. Right (or left) arrows indicate that the gene is encoded in the sense (antisense) strand.
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Genetic markers
In addition to the genome of the Hd-rR medaka inbred strain,
the genome of another inbred strain HNI (
14,
15) was also sequenced
to produce the draft 648-Mb HNI genome. Inbred strains Hd-rR
and HNI originated in the southern and northern Japanese populations,
respectively. They can mate and produce healthy offspring, although
they are estimated to have diverged about 4 million years ago,
and their genome sequences have diverged by
3.42%. The alignment
of the two medaka genomes identified about 16.4 million single
nucleotide polymorphisms (SNPs), from which 2401 SNPs were selected
and mapped genetically onto medaka chromosomes using a backcross
panel between these two inbred strains. These genetic SNP markers,
together with 140 single sequence length polymorphism (SSLP)
and restriction fragment length polymorphism (RFLP) markers,
were used to anchor scaffolds on chromosomes, to construct the
medaka chromosome map. These confirmed markers should be useful
in isolating responsible genes of interest by positional cloning.
To enable users to use the markers, our database contains PCR
primers for 2473 markers, with the genetic distances between
the markers, and their locations on the chromosomes (
Figure 1C).
SNPs and insertions/deletions
The alignment of the Hd-rR and HNI genomes revealed 16 519 460 SNPs and 2 859 905 insertions/deletions (indels), and the locations of individual SNPs and indels are given in the web database (Figure 1D and F). This information constitutes an excellent resource for exploring a variety of further studies. One typical use is to design PCR primers for SNP markers concentrated in a particular genomic region of interest, to boost positional cloning. Such SNP markers would also be attractive for characterizing the genetic divergence among various inbred and wild-type medaka strains found in Asia. For example, the sequences surrounding a number of SNP markers were collected from four inbred and eight wild-type strains, and the multiple alignment of these sequences generated a phylogenetic tree that was consistent with the regional separation of these strains and confirmed the recent expansion of the northern Japanese population (9). Another intriguing direction would be to analyze whether a specific gene and its regulatory region are evolving slowing or rapidly, by examining the two inbred strains. For instance, genes in the reproduction and sex-related categories were shown to be evolving slowlyly relative to the hominid lineage, presumably because these two inbred strains have not speciated (9). Overall, the set of SNPs and indels reflects a comprehensive view of genetic divergence between the two medaka inbred strains, which is useful in putting forward medaka genetics.
Transcription start sites, predicted genes and gene expression
Given the limited availability of expressed gene tags (EST) and full-length enriched cDNA sequences, a considerable amount of 5'-end serial analyses of gene expression (5'SAGE) data (16), the 19–20 5'-end bases of mRNAs, have been collected, to detect transcription start sites (TSSs) and subsequently protein-coding regions were predicted from the TSSs by using GENSCAN (17). In all, 1 186 742 5'SAGE tags were collected from a mixture of cDNA from 0- to 7-day-old medaka embryos and adult body tissues. Of these, 841 235 (70.9%) were aligned to unique positions in the medaka draft genome, but most of them were duplicates and were expressed from 344 266 transcription start sites. Stated another way, multiple tags are often derived from one locus, and the frequency approximates the expression level of the gene encoded at that locus (Figure 1E and G). From these TSSs, 20 141 genes were predicted (Figure 1E and H), and individual predicted genes were supported by the evidence of some 5' SAGE tags, which was effective in reducing the false-positive ratio of predicted genes. These evidence-based predicted medaka genes were compared with human genes comprehensively, and about 57.7% of the predicted medaka genes have human orthologs, and 21.6% of the genes constitute medaka-human reciprocally best 1:1 ortholog pairs (9), indicating that medaka could serve as a model system for humans.
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SEARCHING THE GENOME
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In UTGB/medaka, biological data are organized along the medaka
genome sequence. One can approach a genomic region of interest
in three different ways. The first is the typical method that
searches for proper keywords, such as scaffold names, gene names
and EST accession numbers. The second is to input a sequence
of interest, such as a cloned and sequenced gene, into the online
mapping window, and subsequently the system returns the list
of location candidates of the given sequence with their alignments
to the genome and displays the selected location in the main
window. The last is to display an overview of all genetic markers
on individual chromosomes that are useful in boosting the positional
cloning of genes responsible for a specific phenotype. Our database
provides a high-resolution mapping of confirmed genetic markers
as well as genomic sequences on which individual genetic markers
are located. As shown in
Figure 1, genomic sequences are associated
with a variety of information, e.g. predicted genes, 5'SAGE
tags, and ESTs. In the meanwhile,
Figure 2 illustrates how to
browse the list of genetic markers along the chromosome of interest.
The maps of genetic markers shown in
Figure 2C and D facilitate
chromosome walking towards the locus that is likely to contain
responsible genes, and clicking the scaffold on the locus presents
precise information, e.g. candidate genes, as shown in
Figure 2F.
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Figure 2. Genetic markers. (A) To display genetic markers on the chromosome of interest, start with the top-level ‘Keyword Search’ view by selecting species as ‘medaka-chr.’ (B) Specify the chromosome number by inputting "CH" followed by the number, e.g. ‘CH01’ or ‘CH16’. (C) Clicking the ‘Search’ button presents all genetic markers horizontally along the chromosome. The distance of a genetic marker from the head of the chromosome is shown in terms of centimorgan (cM). Ultracontigs (series of scaffolds) are categorized into three groups, mapped, unoriented and unordered. Mapped ultracontigs are anchored on the chromosome by multiple genetic markers among which at least one recombination is observed. Unoriented ultracontigs are associated to the specific position on the genetic map, but their directions are unknown because no recombination is observed in the ultracontigs. A cluster of ultracontigs is unordered if it is located on the genetic map but neither the order in the cluster nor the orientation is known because no recombination is observed in the cluster. (D) An enlarged view of the window bounded by two vertical, red lines in Figure 2C. The ultracontig illustrated in the figure has four scaffolds linked by horizontal black lines that represent BAC end pairs. The four blue lines connected to one of the scaffolds from the node labeled with 0.07 cM indicate genetic markers among which no recombination is observed. (E) Clicking the leftmost, blue genetic marker name presents the list of markers surrounding the selected marker. (F) Selecting the scaffold enclosed in the red box displays the view with a variety of precise information associated with the scaffold, which is similar to Figure 1.
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DATA DOWNLOAD
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All of our sequence and annotated data are available for download
in various formats described in
http://download.utgenome.org/pub/.
The latest version 1.0 genomic sequences are registered in DDBJ/GenBank/EMBL
and have been released as accession numbers BAAF04000001-BAAF04134429
(contigs), DF083412-DF090103 (scaffolds), DF090104-DF090315
(ultracontigs) and DG000001
[GenBank]
-DG000024
[GenBank]
(chromosomes). The HNI
assembly version 1.0 is registered as BAAE01000001-BAAE01346141
(contigs) and DF000001-DF038235 (scaffolds). In addition, the
5'SAGE tag data are registered as accession numbers, ACAAA0000001-ACAAA0356693.
BAC end reads are available as accession numbers DE248528-DE283656
(collected at National Institute of Informatics) and DE042646-DE143283
(Keio University) (
18).
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CONCLUSION AND FUTURE PLAN
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To fully exploit the power of the medaka genome for medaka and
developmental biology, UTGB/medaka is equipped with data information
on considerable biological resources and advanced genomic tools.
To support further experiments, we plan to add a number of other
useful data, e.g. RFLP primers and phenotype information of
well-known mutants.
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ACKNOWLEDGEMENTS
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This work was supported by a Grant-in-Aid for Scientific Research
on Priority Areas ‘Genome’ from the Ministry of
Education, Culture, Sports, Science, and Technology of Japan
(MEXT), and the Japan Science and Technology Corporation (JST).
We thank the Human Genome Center, University of Tokyo for computational
time, and the National BioResource Project of MEXT for supplying
the medaka strain and for other support. Funding to pay the
Open Access publication charges for this article was provided
by JST.
Conflict of interest statement. None declared.
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Footnotes
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The authors wish it to be known that, in their opinion, the
second and third authors should be regarded as equally contributed
Authors.
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REFERENCES
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- Nelson JS. Fishes of the World (1994) 3rd. New York: Wiley.
- Patyna PJ, Davi RA, Parkerton TF, Brown RP, Cooper KR. A proposed multigeneration protocol for Japanese medaka (Oryzias latipes) to evaluate effects of endocrine disruptors. Sci. Total Environ (1999) 233:211–220.[CrossRef][Medline]
- Aida T. On the inheritance of color in a fresh-water fish, Aplocheilus latipes Temminck and Schlegel, with special reference to sex-linked inheritance. Genetics (1921) 6:554–573.[Free Full Text]
- Yamamoto T. Artificially induced sex-reversal in genotypic males of the Medaka (Oryzias latipes). J. Exp. Zool (1953) 123:571–594.[CrossRef][ISI]
- Matsuda M, Nagahama Y, Shinomiya A, Sato T, Matsuda C, Kobayashi T, Morrey CE, Shibata N, Asakawa S, et al. DMY is a Y-specific DM-domain gene required for male development in the medaka fish. Nature (2002) 417:559–563.[CrossRef][Medline]
- Furutani-Seiki M, Sasado T, Morinaga C, Suwa H, Niwa K, Yoda H, Deguchi T, Hirose Y, Yasuoka A, et al. A systematic genome-wide screen for mutations affecting organogenesis in Medaka, Oryzias latipes. Mech. Dev (2004) 121:647–658.[CrossRef][ISI][Medline]
- Hubbard TJ, Aken BL, Beal K, Ballester B, Caccamo M, Chen Y, Clarke L, Coates G, Cunningham F, et al. Ensembl 2007. Nucleic Acids Res (2007) 35:D610–617.[Abstract/Free Full Text]
- Kuhn RM, Karolchik D, Zweig AS, Trumbower H, Thomas DJ, Thakkapallayil A, Sugnet CW, Stanke M, Smith KE, et al. The UCSC genome browser database: update 2007. Nucleic Acids Res (2007) 35:D668–673.[Abstract/Free Full Text]
- Kasahara M, Naruse K, Sasaki S, Nakatani Y, Qu W, Ahsan B, Yamada T, Nagayasu Y, Doi K, et al. The medaka draft genome and insights into vertebrate genome evolution. Nature (2007) 447:714–719.[CrossRef][Medline]
- Hinegardner R, Rosen DE. Cellular DNA content and the evolution of teleostean fishes. Am. Nat (1972) 106:621–644.[CrossRef][ISI]
- Uwa H, Iwata A. Karyotype and cellular DNA content of Oryzias javanicus (Oryziatidae, Pisces). Chromosome Inf. Service (1981) 31:24–26.
- Uwa H. Karyotype evolution and geographical distribution in the ricefish, genus Oryzias (Oryziidae). Indo-Pacific Fish Biol (1986) 867–876.
- Lamatsch DK, Steinlein C, Schmid M, Schartl M. Noninvasive determination of genome size and ploidy level in fishes by flow cytometry: detection of triploid Poecilia formosa. Cytometry (2000) 39:91–95.[CrossRef][ISI][Medline]
- Naruse K, Hori H, Shimizu N, Kohara Y, Takeda H. Medaka genomics: a bridge between mutant phenotype and gene function. Mech. Dev (2004) 121:619–628.[CrossRef][ISI][Medline]
- Wittbrodt J, Shima A, Schartl M. Medaka–a model organism from the far East. Nat. Rev. Genet (2002) 3:53–64.[CrossRef][ISI][Medline]
- Hashimoto S, Suzuki Y, Kasai Y, Morohoshi K, Yamada T, Sese J, Morishita S, Sugano S, Matsushima K. 5'-end SAGE for the analysis of transcriptional start sites. Nat. Biotechnol (2004) 22:1146–1149.[CrossRef][ISI][Medline]
- Burge C, Karlin S. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol (1997) 268:78–94.[CrossRef][ISI][Medline]
- Sasaki T, Shimizu A, Ishikawa SK, Imai S, Asakawa S, Murayama Y, Khorasani MZ, Mitani H, Furutani-Seiki M, et al. The DNA sequence of medaka chromosome LG22. Genomics (2007) 89:124–133.[CrossRef][ISI][Medline]
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INTRODUCTION