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a Laboratory for Genome Exploration Research Group,
RIKEN Genomic Sciences Center (GSC), Yokohama 230-0045, Japan;
b Genome Science Laboratory, i Center for
Biogenic Resources, RIKEN, Tsukuba Institute, Tsukuba 305-0074, Japan;
c Institute of Basic Medical Sciences and
e Biological Sciences, University of Tsukuba, Ibaraki
305-8575, Japan; d Department of Biotechnology, University
of Tokyo, Tokyo 113-8657, Japan; f Core Research for
Evolutional Science and Technology (CREST) of Japan Science and
Technology Corporation; g Second Department of Surgery,
Yokohama City University School of Medicine, Yokohama 236-0004, Japan; h Department of Advanced Surgical Science and
Technology, Graduate School of Medicine, Tohoku University, Sendai
980-8574, Japan; and Departments of j Biochemistry and
k Genetics, Stanford University School of Medicine,
Stanford, CA 94305
Communicated by Webster K. Cavenee, University of California at
San Diego, La Jolla, CA, December 22, 2000 (received for review November 8, 2000)
We have systematically characterized gene expression patterns in 49 adult and embryonic mouse tissues by using cDNA microarrays with 18,816 mouse cDNAs. Cluster analysis defined sets of genes that were expressed
ubiquitously or in similar groups of tissues such as digestive organs
and muscle. Clustering of expression profiles was observed in embryonic
brain, postnatal cerebellum, and adult olfactory bulb, reflecting
similarities in neurogenesis and remodeling. Finally, clustering genes
coding for known enzymes into 78 metabolic pathways revealed a
surprising coordination of expression within each pathway among
different tissues. On the other hand, a more detailed examination of
glycolysis revealed tissue-specific differences in profiles of key
regulatory enzymes. Thus, by surveying global gene expression by using
microarrays with a large number of elements, we provide insights into
the commonality and diversity of pathways responsible for the
development and maintenance of the mammalian body plan.
DNA arrays have been
used to study the expression of all of the protein coding genes in
yeast (1) and Mycobacterium (2). The same sorts of global
studies are already possible in Drosophila (3), and they
will be feasible in mouse (4) and human tissue in the not too distant
future. To date, however, large arrays have not been used to learn
about the development and maintenance of function of mammalian tissues.
One reason for this is the paucity of cDNAs from which one might create
the appropriate arrays. To overcome this problem, we have constructed
many full-length mouse cDNA libraries based on a CAP trapper
full-length cDNA selection method (5), to produce a mouse cDNA
encyclopedia (http://genome.gsc.riken.go.jp/). We sequenced the
3' ends of clones from these libraries and identified a nominally
nonredundant set of cDNAs. We arrayed 18,816 "unique" cDNAs (the
"RIKEN 19K set") and systematically characterized the gene
expression profiles of a number of adult and developing mouse tissues.
We realize that the 19K set is not nonredundant. On the basis of
limited clustering of the clone sequences, we estimate that there are
about 13,600 nonredundant genes in the set.
The advantages of using the mouse for this analysis should be obvious:
(i) collecting fresh tissues at all developmental and adult
stages is easy; (ii) many mutant and gene-knockout mice are
available and are useful for further analysis of gene function; and
(iii) mouse cDNA and genome sequencing projects are
progressing rapidly, and it will soon be possible to print
near-comprehensive arrays of well-annotated cDNAs.
Below we report the expression profile of 49 adult and embryonic
tissues. We performed hierarchical clustering analyses for tissues as
well as genes, and we used our data to understand similarities and
differences in patterns of expression between embryonic and adult
tissues. In addition, we have analyzed patterns of expression of
enzymes known to be part of metabolic pathways. The diversity of gene
expression patterns observed has provided surprising insights into the
commonality and diversity of pathways responsible for the development
and maintenance of the mammalian body plan.
Preparation of Target DNAs.
The target DNAs were collected from RIKEN mouse cDNA libraries
(5), which were constructed by using the CAP trapper method to enrich
for full-length inserts. The cDNAs were amplified by using M13 forward
and reverse primers in a 100-µl PCR with 0.2 µM final concentration
(each) of forward (F1224, 5'-CGCCAGGGTTTTCCCAGTCACGA-3') and reverse
(R1233, 5'-AGCGGATAACAATTTCACACAGGA-3') primers, 250 µM dNTPs, and
1.25 units of Ex Taq in 1× Ex Taq buffer (Takara Shuzo, Tokyo). The PCR product was precipitated with isopropyl alcohol
and resuspended in 15 µl of 3× SSC. The DNA solution was spotted on
poly(L-lysine)-coated slides by using a DNA
arrayer (http://cmgm.stanford.edu/pbrown/mguide/index.html)
with 16 tips (SMP3, TeleChem International, Sunnyvale, CA). The
diameter of the spots was 100-150 µm. Mouse Performance of RIKEN Microarrays.
mRNAs transcribed in vitro from Arabidopsis
full-length cDNAs were serially diluted and mixed with mRNAs from mouse
brain. The Arabidopsis mRNA signal was detectable when 0.3 pg was added to 1 µg of brain mRNA, corresponding to a sensitivity of
1-3 copies of mRNA per cell (data not shown).
Applied Biological Sciences
Delineating developmental and metabolic pathways in
vivo by expression profiling using the RIKEN set of 18,816 full-length enriched mouse cDNA arrays
Abstract
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
Introduction
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
Materials and Methods
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
-actin and
glyceraldehyde-3-phosphate dehydrogenase cDNAs were used as positive
controls and Arabidopsis cDNAs were used as negative
controls (accession nos. X98108, X13611, X90769, Z99707, AF004393,
Z49777, Q03943, U58284). Tissues from which the cDNA libraries were
made (En indicates embryonic day n), and the
number of the clones used (shown in parenthesis) from each cDNA library
are as follows: 06, kidney (338); 07, brain (35); 09, spleen (17); 10, heart (397); 11, E18 (1,771); 12, lung (514); 15, cerebellum (1,200);
16, placenta (437); 17, testis (1,591); 18, pancreas (1,816); 20, small
intestine (1,178); 22, stomach (1,517); 23, tongue (3,110); 24, ES
(995); 25, E13 liver (782); 26, E10 (976); 27, E11 (426); 28, E10 and E11 (1,010); 29, hippocampus (197); 30, E12 head (168); 31, E13 head
(158); 32, E14 head and E17 head (92); 33, E17 head (91).
Preparation of Probe. One microgram of mRNA extracted from each of the 49 tissues was labeled by incorporating Cy3 during random-primed reverse transcription. cDNA derived from entire E17.5 embryos, which we labeled with Cy5, was used as the expression reference for all tissues. Deoxynucleotides labeled with the dyes Cy3 and Cy5 were obtained from Amersham Pharmacia. The labeling was carried out at 42°C for 1 h in a total volume of 30 µl containing 400 units of SuperScript II (GIBCO/BRL); 0.1 mM Cy3-dUTP (or Cy5-dUTP); 0.5 mM each dATP, dCTP, and dGTP; 0.2 mM dTTP, 10 mM DTT, 6 µl of 5× first-strand buffer, and 6 µg of random primers. To remove unincorporated nucleotide, labeled cDNA was mixed with 500 µl of binding buffer (5 M guanidine thiocyanate/10 mM Tris·HCl, pH.7.0/0.1 mM EDTA containing 0.03% gelatin and 2 ng/µl tRNA) and 50 µl of silica matrix buffer (10% matrix/3.5 M guanidine hydrochloride/20% glycerol/0.1 mM EDTA/200 mM NaOAc, pH 4.8-5.0), transferred to a GFX column (Amersham Pharmacia), and centrifuged at 15,000 rpm in a Sorvall centrifuge (RC-3B plus; H6000A/HBB6 rotor) for 30 s. The flow-through was discarded, and the column was washed with 500 µl of wash buffer. The adsorbed probe was eluted into a final volume of 17 µl of distilled water. This labeled probe was mixed with blocking solution containing 3 µl of 10 µg/µl oligo(dA), 3 µl of 20 µg/µl yeast tRNA, 1 µl of 20 µg/µl mouse Cot1 DNA, 5.1 µl of 20× SSC, and 0.9 µl 10% SDS.
Array Hybridization and Data Analysis. The RIKEN full-length mouse cDNA that comprised the target was hybridized in a final volume of 30 µl; the entire array consists of three multiblocks, and each multiblock required 10 µl of hybridization solution. Before hybridization, probe aliquots were heated at 95°C for 1 min and cooled at room temperature. Coverslips were hybridized overnight at 65°C in a Hybricasette (obtained from ArrayIt.com). After hybridization, slides were washed in 2× SSC/0.1% SDS until the coverslips dropped off, and the slides were then transferred into 1× SSC, shaken gently for 2 min, and rinsed with 0.1× SSC for 2 min. After washing, slides were spun at 800 rpm in a Sorvall centrifuge (RC-3B plus; H6000A/HBB6 rotor). These slides were scanned on a ScanArray 5000 confocal laser scanner, and the images were analyzed by using IMAGENE (BioDiscovery; Los Angeles).
Analysis of the Data. To improve the accuracy of the data, we did the experiment twice, labeling the same RNA template in two separate reactions. Data were normalized to the reference standard by subtracting (in log space) the median observed value if it were other than zero. We used only data points that were reproducible. To this end, we developed a filtering program, PRIM (Preprocessing Implementation for Microarray; ref. 6). Briefly, this program (i) deletes the results with "flags" added manually to corrupted spots, (ii) eliminates spots with signal intensities less than the mean + 3 × standard deviation of the background signal intensity in either Cy3 or Cy5, and (iii) eliminates spots located outside the least-mean-squares line ±2 × standard deviation. After the filtering was finished, we compared the results of the two experiments by calculating a Pearson's correlation coefficient. If the coefficient was equal to or greater than 0.7, we used the data in subsequent analyses. If not, we repeated the labeling, hybridization, and scanning up to six times. In this way, we could generate high-quality data for most tissues. Preceding the clustering, ratio values from duplicate experiments were averaged, log-transformed (base 2), and stored in a table. We applied hierarchical clustering to both axes, using the weighted pair-group method with a centroid average as implemented by the program CLUSTER (M.B.E.: http://www.microrrays.org/software.html; ref. 7). The distance matrices we used were the Pearson correlation for clustering the arrays and the inner product of vectors normalized to magnitude 1 for the genes (this is a slight variation of the Pearson correlation). The results were analyzed by using TREEVIEW (M.B.E.: http://www.microrrays.org/software.html; ref. 7).
Cellular Roles.
We were able to assign cellular roles to 2,206 of the RIKEN clones by
comparing the sequences of the 18,816 cDNAs in our set to those of
expressed sequence tags (ESTs) in The Institute for Genomic Research
(TIGR) EGAD database by using the TBLASTX program. The
threshold E-value used to assign an identification to a
clone was 1.0 × 10
50.
Glycolysis Pathway Analysis.
For the glycolysis pathway analysis, we first collected reference gene
sequences for members of the glycolysis pathway from the Kyoto
Encyclopedia of Genes and Genomes (KEGG) database
(http://www.genome.ad.jp/kegg/). Amino acid sequences from
human and mouse were searched against the 18,816 RIKEN sequences with
the TBLASTN program. We also used a text search of enzyme
names against our annotations of the 18,816 genes. We set the
E-value threshold in this BLAST search
to 1.0 × 1030. After we had identified
the members of the glycolysis pathway in our collection, we clustered
them with the help of the
TREEVIEW program.
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Results and Discussion |
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Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
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Expression Profiles of Adult and Developing Tissues. We extracted mRNA from 49 adult and embryonic tissues from C57BL/6J mice, made labeled probes, and hybridized them to the RIKEN 19K set. In total, we completed approximately 1.8 million measurements of gene expression based on 294 microarray analyses of 49 adult and embryonic tissues. We used whole-body mRNA from equal numbers of male and female E17.5 mouse embryos as a reference probe for all tissues. This reference is more easily and reproducibly made than ones produced by mixing RNAs from a variety of cells or tissues. In addition, because it is simple to make, we feel that others will be able to use it to compare their data to ours. Whole E17.5 embryos are quite heterogeneous. RNA from these animals has a more complex expression pattern than does a mixture of RNAs from several major tissues. This difference is important because the reference sample should ideally generate a signal in every spot on the array (i.e., a nonzero denominator for the Cy3/Cy5 ratio). Finally, because embryonic tissues are obtained by Caesarian section, the samples are free from infection. We used this E17.5 whole-body cDNA reference (labeled with Cy5) to calculate the relative abundance of each gene in the experimental mRNA samples (labeled with Cy3).
We used the PRIM program to filter low-quality data. A total of 14,610 clones survived the filtering process. We next used hierarchical clustering to group genes on the basis of tissue data or tissues based on patterns of genes. The data are shown in a matrix format (Fig. 1).
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Patterns of Gene Expression in the Central Nervous System (CNS)
During Development and in Adulthood.
To examine variations in gene expression during development of a
single tissue, we analyzed and clustered our CNS data separate from the
rest. The expression profiles of the CNS samples varied as a function
of developmental age (Fig. 7, which is published as supplemental data
on the PNAS web site, www.pnas.org), as indicated by the colored bars
at the right of the figure. However, genes that are prominently
expressed in the postnatal day 10 (N10) cerebellum also are expressed
in the head of early (e.g., E11, E12, and E13) embryos. Similarly, the
expression profiles of the olfactory bulb are very similar to those of
the head of the E11 embryo. These results suggest functional
similarities between the head of the E11 embryo and the postnatal
cerebellum or the olfactory bulb
a result consistent with that from
the hierarchical clustering of the tissue samples (Fig. 1). Genes that
are specifically expressed in these E11-E13, N10 cerebellum, and
olfactory bulb can be divided into two major groupsthose involved in
cell death or neural remodeling (Fig.
2a) and those involved in cell
division (Fig. 2b). During brain development an excess of
neuroblasts is generated, and those that fail to reach appropriate
targets at the right developmental stage are eliminated by a process of
programmed cell death or apoptosis. Cyclin D1, which is an
essential mediator of apoptotic neuronal cell death (8), is one
of the genes in the "apoptosis" cluster. This is
consistent with the report by Padmanabhan et al. (9) that
multiple cell cycle proteins, including cyclin D1, are involved in
cerebellar granule cell apoptosis. Midkine, a potential
apoptosis inhibitor (10), and nestin, which is found preferentially in the neuroepithelial stem cells (11), are also included in this cluster. The preferential expression of these genes in
early embryonic stages, with little expression in the adult, is
consistent with the report by Wen et al. (12).
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Expression of Functional Classes of Genes. We were able to assign functions to 2,206 RIKEN cDNA clones with expression levels at least twice those in E17.5 whole embryonic tissue. On the basis of these criteria, we found that the expression of genes involved in cell division was higher in early embryonic stages than in adult stages, whereas that of genes involved in metabolism is higher in adult tissues than in embryonic stages (Fig. 3). The expression of genes influencing protein production increased just before birth, and, as we saw earlier, the genes expressed in the medulla oblongata were similar to those in N10 cerebellum and head of E11 and E12 embryos. It will be possible to further test these correlations as functional annotation is added to the gene set.
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Expression Patterns of Metabolic Pathways. Enzymes in all classes of metabolic pathways were represented in the RIKEN 19K set. We separated these enzymes into 78 various synthetic and degradative metabolic pathways and determined the relatedness of expression patterns during development and in adult tissues. The similarities in patterns of expression among genes coding for enzymes in the same metabolic pathway were striking (Fig. 4). Although the expression patterns of individual enzymes have been examined in various tissues of the whole animal, leading to hypotheses regarding whole body regulation of metabolism, it has not previously been possible to examine the coordinate regulation of most metabolic pathways simultaneously. Using microarray expression analysis, we have provided strong evidence that metabolic pathways are coordinately regulated throughout the body of an organism during development and in the adult. Intriguingly, genes were clustered into two major groups in all of the metabolic pathways (Fig. 4). One group was the ubiquitously expressed gene set and the other was a tissue-specifically expressed gene set. Expressed genes in a tissue-specific pattern were mainly clustered into muscle-specific and liver- or kidney-specific genes. For example, tissue-specific genes involved in the amino acid metabolism were mainly found in the liver and kidney, whereas those involved in glycolysis were in muscle (Fig. 5a).
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Conclusions |
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Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
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Understanding the temporal and spatial expression of a gene is useful for further analysis of its function and any associated disease condition. The use of cDNA microarrays allows efficient analysis of the expression of many genes, providing assessment of the function of pathways. We have established an expression database for a large set of genes in 49 different tissues. The quality and accuracy of these data were supported by comparing information for each gene about the tissue from which it was derived with array data. Assigning a functional role to each gene with tissue-specific expression will be quite valuable. The number of functionally annotated genes is low at this time. As this number increases, array data will prove even more useful. For this reason, a FANTOM (Functional Annotation of Mouse cDNAs) (http://genome.gsc.riken.go.jp/FANTOM/) meeting was held to systematically assign functional annotation by intensive computational analysis followed by human inspection. The details of the concept and results of the FANTOM meeting (16) will be reported elsewhere. Of the RIKEN 19K set, 10,004 clones were included in the FANTOM set and their annotations were used in the present analysis. Our future efforts will focus on increasing the number of analyzed genes so that we can draw a complete picture of the expression profiles. Using whole-body cDNA from an E17.5 embryo as the reference material will allow the comparison of data between laboratories. READ is available to the public through our database (http://genome.gsc.riken.go.jp/READ/).
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Acknowledgements |
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We especially thank A. Wynshaw-Boris and M. Brownstein for helpful discussion and English editing. We thank N. Tominaga, M. Gariboldi, T. Ishikawa, T. Sakai, T. Shimoji, C. Sakai, T. Kamoshida, M. Nakamura, R. Yano, M. Nakagawa, and T. Kasukawa for technical assistance and helpful discussion. We also thank C. Weitz, H. Suzuki, T. Endo, and K. Shimizu for helpful advice. We thank K. Shinozaki for kindly providing the full-length Arabidopsis cDNAs. We acknowledge all of the members of the FANTOM consortium for the use of FANTOM annotation. This study was supported in part by Special Coordination Funds for Promoting Science and Technology from the Science and Technology Agency of the Japanese Government to Y. Okazaki. This study has been supported by Special Coordination Funds for Promoting Science and Technology and a Research Grant for the RIKEN Genome Exploration Research Project from the Science and Technology Agency of the Japanese Government, Special Coordination Funds for Promoting the Bioresource Program from RIKEN Tsukuba and CREST (Core Research for Evolutional Science and Technology) and ACT-JST (Research and Development for Applying Advanced Computational Science and Technology) of the Japan Science and Technology Corporation (JST) to Y. Hayashizaki. This work was also supported by a Grant-in-Aid for Scientific Research on Priority Areas and Human Genome Program, from the Ministry of Education, Science and Culture, and by a Grant-in-Aid for a Second Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health and Welfare to Y. Hayashizaki.
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Abbreviations |
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En, embryonic day n; Nn, postnatal day n; EST, expressed sequence tag; FANTOM, Functional Annotation of Mouse cDNAs; CNS, central nervous system.
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Footnotes |
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l To whom reprint requests should be addressed at: RIKEN Genomic Science Center, Yokohama 230-0045, Japan. E-mail: okazaki{at}gsc.riken.go.jp.
m To whom correspondence about all genome resources, including the RIKEN full-length cDNA bank, should be addressed at: RIKEN Genomic Science Center, Yokohama 230-0045, Japan. E-mail: yosihide{at}gsc.riken.go.jp.
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References |
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Abstract
Introduction
Materials and Methods
Results and Discussion
Conclusions
References
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2 to +2 in log base 2 units). Gray indicates missing or
excluded data. FANTOM, Functional Annotation of Mouse cDNAs.
