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(Circulation. 1997;96:4146-4203.)
© 1997 American Heart Association, Inc.
Articles |
A Genome-Based Resource for Molecular Cardiovascular Medicine
Toward a Compendium of Cardiovascular Genes
From the Cardiac Gene Unit, Departments of Laboratory Medicine and Pathobiology and Medicine, Centre for Cardiovascular Research, The Toronto Hospital, University of Toronto, Ontario, Canada (D.M.H., A.A.D., R.X.W., M.R., J.D.B., K.-S.D., H.-Y.W., H.M., E.C., C.-Y.L., C.-C.L.); China National Center for Biotechnology Development, STC, Beijing, China (Y.-Q.L., J.-R.G.); National Center for Biotechnology Information, Bethesda, Md (J.-H.Z.); and the Department of Biochemistry, Chinese University of Hong Kong, Shatin (S.K.W.T., M.M.Y.W., K.-P.F., C.-Y.L., C.-C.L.). D.M. Hwang and A.A. Dempsey contributed equally to this work.
Correspondence to C.C. Liew, Banting Institute, University of Toronto, 100 College St, Toronto, Ontario M5G 1L5, Canada. E-mail liewcc{at}tcgu.med.utoronto.ca
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Abstract |
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 Top Abstract IntroductionMethodsResultsDiscussionReferences |
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Background Large-scale partial sequencing of cDNA libraries to generate expressed sequence tags (ESTs) is an effective means of discovering novel genes and characterizing transcription patterns in different tissues. To catalogue the identities and expression levels of genes in the cardiovascular system, we initiated large-scale sequencing and analysis of human cardiac cDNA libraries.
Methods and Results Using automated DNA sequencing, we generated 43 285 ESTs from human heart cDNA libraries. An additional 41 619 ESTs were retrieved from public databases, for a total of 84 904 ESTs representing more than 26 million nucleotides of raw cDNA sequence data from 13 independent cardiovascular system–based cDNA libraries. Of these, 55% matched to known genes in the Genbank/EMBL/DDBJ databases, 33% matched only to other ESTs, and 12% did not match to any known sequences (designated cardiovascular system–based ESTs, or CVbESTs). ESTs that matched to known genes were classified according to function, allowing for detection of differences in general transcription patterns between various tissues and developmental stages of the cardiovascular system. In silico Northern analysis of known gene matches identified widely expressed cardiovascular genes as well as genes putatively exhibiting greater tissue specificity or developmental stage specificity. More detailed analysis identified 48 genes potentially overexpressed in cardiac hypertrophy, at least 10 of which were previously documented as differentially expressed. Computer-based chromosomal localizations of 1048 cardiac ESTs were performed to further assist in the search for disease-related genes.
Conclusions These data represent the most extensive compilation of cardiovascular gene expression information to date. They further demonstrate the untapped potential of genome research for investigating questions related to cardiovascular biology and represent a first-generation genome-based resource for molecular cardiovascular medicine.
Key Words: cardiomyopathy • cardiovascular diseases • cDNA library • expressed sequence tags • heart failure • human genome project • hypertrophy
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Introduction |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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The complexity of the human cardiovascular system is derived from its multicomponent constituency, with the heart at its center and the vascular network at its periphery. These further reduce to a diversity of cell types that function in concert to generate normal cardiovascular function, including muscle cells involved in producing and maintaining pulsatile flow, neuroendocrine cells involved in control and regulation, endothelial cells lining the vascular tree, and matrix secretory cells responsible for the deposition and upkeep of fibrous and elastic components of the system.
Underlying this complexity at the macroscopic level is tremendous complexity at the molecular level. The intricacies of cardiovascular function are determined by a proportion of the 60 000 to 120 000 genes of the human genome,1,2 between 15 000 and 30 000 of which are expressed in any given single cell of the cardiovascular system. Although a significant proportion of these are devoted to the maintenance of basic cellular function and are widely expressed, more restricted expression (eg, spatial, temporal, contextual, or kinetic restriction) of subsets of genes presumably gives rise to the diversity of cell types, tissues, and organs of the system. Thus, changes in gene expression in response to developmental cues drive the growth and differentiation of the heart and blood vessels, resulting in the establishment of normal circulatory function. Further, dynamic interaction of the cardiovascular system with physiological or pathological stimuli also elicits alterations in gene expression, ultimately leading to generation of adaptive responses.
Recent years have seen encouraging progress in understanding the genetic basis of cardiovascular function, development, and disease (for reviews, see References 3 through 103 4 5 6 7 8 9 10 ). However, many questions remain unanswered. For example, the identities of the vast majority of genes expressed in the cardiovascular system, together with their roles in the processes of ontogeny, growth, and normal function, remain unknown. Furthermore, although some inroads have been made in identifying genes involved in monogenic disorders,5 the genetic factors underlying multifactorial disorders and their roles in the pathogenesis of such common conditions as hypertension, atherosclerosis, coronary artery disease, and heart failure remain elusive.
To provide a base to aid in the exploration of some of these unknowns, we initiated a project to characterize gene expression in various developmental and pathological states of the cardiovascular system by use of high-throughput sequencing of randomly selected clones from human heart cDNA libraries to generate "expressed sequence tags" (ESTs).11–14 This approach has proved to be a powerful means of discovering novel genes expressed in a wide variety of human tissues.11–33 Because cDNA libraries are representative of gene transcription in cells or tissues used to construct the library, random sampling and sequencing by the EST approach simultaneously generate gene expression profiles that are useful for detailed genetic-level comparisons of different developmental and pathological states of the cells and tissues of interest.14,17,19 In this report, we present the analysis of 84 904 ESTs from 13 cDNA libraries of the cardiovascular system, representing the most extensive compilation of cardiovascular gene expression information to date, and we discuss the potential impact of this genome-based resource on the field of molecular cardiovascular medicine.
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Methods |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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RNA Isolation
Total RNA was isolated from human heart samples by the method of Chomczynski and Sacchi.34 Tissues were powdered under liquid nitrogen before homogenization and two rounds of extraction with acidic guanidinium isothiocyanate–phenol-chloroform. The poly(A)+ RNA fraction was isolated by oligo-dT cellulose chromatography (Pharmacia; Stratagene). Purity and RNA integrity were assessed by absorbance at 260/280 nm and by agarose gel electrophoresis.
cDNA Library Construction
Initially, we used nondirectionally cloned human adult and fetal
heart cDNA libraries, which were purchased from Clontech. Subsequent to
concerns regarding the presence of bacterial or yeast contaminating
sequences in some commercial libraries, unidirectional cDNA libraries
were constructed with 3 to 5 µg poly(A)+ RNA in a modified Gubler and
Hoffman one-tube cDNA synthesis procedure.35,36
All libraries were constructed in the 
ZAP Express vector
(Stratagene) according to protocols supplied by the manufacturer, with
the exception of one library constructed in the gt22A
vector.13,14 Briefly, first-strand cDNA was
synthesized with an Xho I–oligo(dT) adapter-primer in the
presence of 5'-methyl dCTP to protect the synthesized cDNA from
subsequent Xho I restriction. After second-strand synthesis
and ligation of EcoRI adapters, cDNA was digested with
Xho I, generating cDNA flanked by EcoRI sites at
the 5'-ends and Xho I sites at the 3'-ends. Digested cDNAs
were size-fractionated in Sephacryl S-500 spin columns to recover cDNAs
larger than 0.5 kb before ligation into ZAP Express vector
predigested with EcoRI and Xho I. The resulting
DNA/cDNA concatomers were packaged by use of Gigapack Gold
packaging extracts. After titration, aliquots of primary packaging mix
were stored in 7% DMSO at -80°C as primary library stocks, and the
remainder was amplified to establish stable library stocks.
Large-Scale Sequencing of cDNA Inserts
Protocols for large-scale PCR-based sequencing of gt11 and
gt22A libraries have been described
previously11–14 and are outlined in Fig 1
. These protocols made use of phage
plaques as the direct source of cDNA clones, thus eliminating problems
of bias due to in vivo excision associated with most other EST
projects. For ZAP Express libraries, phage plaques were plated
at low density (<500 pfu/150-mm plate) onto Escherichia
coli XL1-blue MRF' lawns, with IPTG/X-gal for color selection.
Plaques were picked into 75 µL suspension medium buffer. Phage
eluates (5 µL) were used for PCR reactions (50 µL final volume) in
the presence of 125 µmol/L of each dNTP (Pharmacia), 10
pmol each of modified T3 (5'-GCCAAGCTC GAAATTAACCCTCACTAAAGGG-3')
and T7 (5'-CCAGT GAATTGTAATACGACTCACTATAGGGCG-3') primers, and 2 U
of Taq DNA polymerase (Pharmacia). PCR samples were
incubated at 95°C for 5 minutes, followed by 28 cycles of
amplification (94°C, 45 seconds; 55°C, 30 seconds; 72°C, 3
minutes) and a terminal isothermal extension (72°C, 3 minutes) in a
DNA Thermal Cycler (Perkin-Elmer). After agarose gel electrophoresis to
assess purity and concentration, PCR products (100 to 150 ng) were
used directly, without further purification, for DNA sequencing
reactions using Taq Cyclist (Stratagene) or Amplicycle
(Perkin-Elmer) cycle sequencing kits and 5 pmol of a dye-labeled
(fluorescein or Cy5) modified T3 primer
(5'-GAAATTAACCCTCACTAAAGGG-3'). Reactions were incubated at 94°C for
2 minutes, followed by linear amplification (94°C, 30 seconds;
50°C, 15 seconds; 72°C, 1 minute for 20 cycles and 94°C, 30
seconds; 72°C, 1 minute for 15 cycles), then stopped by addition of
0.5 vol loading buffer (95% formamide, 20 mmol/L EDTA, 10
mg/mL blue dextran). Sequencing reactions were electrophoresed
with A.L.F. and A.L.F. Express DNA sequencers
(Pharmacia).
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Data Acquisition and Analysis
EST sequence data from other tissues of the
cardiovascular system were retrieved by various
strategies from the Genbank/EMBL/DDBJ databases at the National Center
for Biotechnology Information (NCBI). When possible, entire data sets
from individual libraries were isolated and retrieved by text string
searching. Failing this, individual accession numbers for each library
were obtained from field-restricted dbEST queries, and sequences were
retrieved with Batch Entrez. Sequences from the Genome Sequencing
Center at Washington University24 were obtained
by retrieving Genbank accessions for each data set from the Genome
Sequencing Center worldwide web site (URL:
http://genome.wustl.edu/est/esthmpg.html) and retrieving the
corresponding sequences with Batch Entrez.
Sequence similarity searching of all ESTs against the nonredundant Genbank/EMBL/DDBJ and dbEST databases (Release 98.0) were performed with the BLAST algorithm37,38 on a Pentium Pro200 Solaris x86 platform (Micron Electronics). Assignments of putative identities for ESTs exhibiting matches to known genes or to other ESTs required a minimum value of P=10-10 and nucleotide sequence identity >95%. Gene homologues were defined as those ESTs that had a value of P<10-10 but that exhibited <95% sequence identity to a known gene. Relative gene expression frequencies were computed by summing the number of ESTs matching to that particular gene or its equivalent (ie, a single gene can have more than one entry in the GenBank database) and dividing the sum by the total number of ESTs matching to known genes. Functional assignments of ESTs with known gene matches were made according to categories described in Adams et al,19 with minor modifications, with the assistance of the Genome Directory19 (search engine, http://www.tigr.org/tdb/hgi/hgi.html), UniGene (http://www.ncbi.nlm.nih.gov/UniGene/index.html), and Entrez and PubMed at the NCBI (http://www.ncbi.nlm.nih.gov/Entrez/ and http://www.ncbi.nlm.nih.gov/PubMed/medline.html, respectively). Genes represented by at least one EST in each tissue and developmental stage (ie, aorta, endothelial cell, adult heart, and fetal heart) were considered to be widely expressed in the cardiovascular system. Genes for which EST frequency was at least three times higher in a specific tissue or stage than in other tissues were considered highly expressed in that tissue or stage.
To identify differentially expressed genes in cardiac hypertrophy, EST frequencies from two independent cDNA libraries from hypertrophic myocardium were compared with frequencies expected on the basis of observed frequencies in other heart cDNA libraries used for this study (except normalized libraries, because normalization changes relative frequencies within the library). To minimize the effects of stochastic library amplification events on the identification of such genes, only genes represented by ESTs in both hypertrophic libraries were selected. Poisson probabilities for observing at least the observed number of ESTs in each library were calculated. Combined Poisson probabilities for observed frequencies of each gene in both libraries were calculated by multiplying individual probabilities. Genes with values of P<.10 for both libraries and combined P<.01 were considered to be strong candidates for differential expression. Genes with combined P<.01 but with one individual value of P>.10 were designated good candidates for differential expression, whereas genes with combined value of .01<P<.05 were designated weak candidates for differential expression.
Cardiovascular gene chromosome transcript maps were generated from 22 623 heart ESTs generated by our laboratory. Briefly, the ESTs were combined with all entries in the UniGene database and processed by use of a sequence clustering algorithm. Those that belonged to a cluster were isolated as one group. A second group was compiled consisting of statistically significant matches to database entries after BLAST searches were performed against the Genbank databases (W=12, E=1.0x10-6). Chromosome locations of the cardiovascular ESTs were determined from the integrated genome mapping and sequencing data compiled at the NCBI (Zhang and Ostell, unpublished; http://www.ncbi.nlm.nih.gov/Entrez/Genome/org.html) based on significant sequence similarity between members of either group and sequences on the integrated map.
Sequence deposition in dbEST39 was by the standard flat file submission format. Further clone information is available through NCBI or at the Cardiac Gene Unit world-wide web site (URL: http://www.tcgu.med.utoronto.ca). Clones are available on request, as detailed in GenBank reports.
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Results |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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Large-Scale cDNA Sequencing and EST Acquisition
A total of 43 285 ESTs were generated in our laboratories from six different human cardiac cDNA libraries representing several developmental stages and disease states (Table 1
A). An additional 41 619 ESTs from
seven cardiovascular tissues or cell types were
obtained through dbEST (Table 1B), for a total of 84 904 ESTs
representing 26 million nucleotides of raw cDNA
sequence data. In the entire cardiovascular EST data
set, 55% represented sequences with significant identity
to known sequences in the nonredundant nucleotide and
peptide databases, and 33% matched to other ESTs in dbEST but not to
any known gene sequences. The remaining 12% were novel transcripts
exhibiting no similarity to any known sequences and were designated
CVbESTs. Proportions for individual cDNA libraries varied widely. The
fraction of known gene matches ranged from 18% for an aorta library
(T. Fujiwara) to 78% for an endothelial cell
library (Stratagene), whereas the proportion of matches to other ESTs
ranged from 17% (hypertrophic heart) to 72% (aorta). The lowest level
of novel transcripts was observed in the endothelial
cell library (2%) and the highest in an adult heart library (Clontech,
25%) sequenced in our laboratories (Table 1).
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Known Gene Expression in the Cardiovascular System
General
The composition of known genes represented by ESTs was
widely variable between libraries. Although most transcripts
corresponding to known genes were nuclear-encoded, mitochondrial
transcripts were observed in every library (with the exception of an
aorta library [T. Fujiwara]), ranging from a low of 0.1% of total
ESTs in a normalized fetal heart library (NbHH19 weeks, M.B. Soares) to
a high of 29% in a hypertrophic heart library (data not shown).
Ribosomal proteins also formed a major class of transcripts in most
libraries (1% to 10% of total ESTs), most dramatically in the
endothelial cell library, where together they
constituted 25% of all transcripts. Sequences corresponding to
repetitive elements ranged from 0.8% (aorta, Clontech) to 14%
(Atrium, Genethon).
Functional Categorization
ESTs matching to known genes (excluding repetitive elements and
probable microbial contaminant sequences) were catalogued into seven
general categories (cell division, cell signaling/cell
communication, cell structure/motility, cell/organism defense,
gene/protein expression, metabolism, and unclassified)
based on the putative functions of the known genes, as described by
Adams et al19 (summarized in Table 2; see Appendix 1 for alphabetical
listing of all genes). Two subcategories were added under cell
structure/motility, namely, contractile proteins and vesicular
transport.
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In total, up to 4575 unique known genes were represented in
the data set (Table 2
). In concordance with the results observed by
Adams et al,19 the largest class of genes
represented those involved in gene and protein expression
(24% of all genes represented). This was followed by genes
involved in cell signaling/cell communication (18%),
metabolism (16%), cell structure/motility (10%),
cell/organism defense (7%), and cell division (6%). Genes
lacking enough information to be classified constituted the remaining
20%. A more detailed breakdown by cDNA library (Table 3) found that in general, the fractions
of genes devoted to these cellular functions did not deviate
significantly from the overall average, except in the case of the
endothelial cell library, which had slightly more genes
devoted to gene/protein expression and slightly fewer for cell
structure/motility, and in the case of several heart libraries that
exhibited a greater proportion of genes involved in cell structure and
motility.
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Although the proportions of unique genes involved in each function were
relatively uniform between cDNA libraries, striking differences existed
between actual levels of gene expression (Table 4). For example,
endothelial cells exhibited elevated expression of
genes involved in gene and protein expression (52%) and relatively
depressed levels of metabolic (12%) and cell
structure/motility (8%) genes compared with all other tissues, most
likely reflective of rapid proliferation in culture. As previously
described,14 the fetal heart consistently
exhibited higher expression of genes involved in gene and protein
expression and lower expression of cell structure/motility genes than
the adult heart (22% to 33% versus 14% to 18% and 12% to 17%
versus 22% to 25%, respectively). Interestingly, the expression of
cell structure/motility genes in adult hypertrophic hearts (14% to
16%) was also significantly diminished compared with normal adult
hearts (22% to 25%), whereas expression of transcripts involved in
cell/organism defense was slightly increased in both
hypertrophic heart libraries (7% to 8%) compared with all other
cardiac libraries (4% to 6%), with the exception of the two
normalized libraries (7% and 11%).
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In Silico Northern Analysis
Relative frequencies of known ESTs for each gene were computed,
and frequencies were represented by differing intensities
to generate an "in silico Northern blot" of known genes of the
cardiovascular system (Table 5). As for conventional Northern blots,
higher frequencies were represented by darker intensities
and lower frequencies by lighter intensities, allowing for convenient
assessment of the relative abundance of large numbers of transcripts in
different tissues and in different developmental and pathological
states of the cardiovascular system.
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Several transcripts were widely expressed throughout most tissues and
developmental stages (Table 6), although
none were uniformly observed in all libraries, probably because of the
small sample sizes of several of the libraries used in the
analysis (Table 1). A large proportion of these widely
expressed genes are involved in basic cellular functions such as
protein synthesis (eg, ribosomal proteins), energy generation (eg,
cytochromes and ATP synthases), and maintenance of cell and
tissue structure (eg, cytoskeletal and extracellular matrix proteins).
A number of genes also appeared to be more restricted in their
distribution, being highly expressed only in specific tissue types or
developmental states (Table 7). Several
of these were not unexpected, on the basis of known gene and organ
functions (eg, plasminogen activator
inhibitor and platelet–endothelial
cell adhesion molecule in endothelial cells, smooth
muscle caldesmon in aorta, myosin genes in adult heart, and 
-globin
in fetal heart). Others (eg, SDF5 isologue in aorta, G
protein–activated potassium channel in atrium, and osteoblast
specific factor in fetal heart) may warrant further verification as to
their tissue specificity.
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Analysis of Known Gene Expression in Disease
Cardiac Hypertrophy
In silico Northern analysis was used to identify genes
potentially overexpressed in cardiac hypertrophy compared
with normal myocardium. In total, 69 genes were
represented by at least one EST in both hypertrophic cDNA
libraries. Of these, 23 were identified to be strong candidates for
high expression in cardiac hypertrophy, including
mitochondrial genome transcripts (which were counted as a single
entity), myosin light chain-2, brain natriuretic peptide,
desmin, heat shock protein 70, and superoxide dismutase (Table 8A). Another 11 were good candidates,
including atrial natriuretic factor, 
-skeletal muscle
tropomyosin, and -cardiac actin (Table 8B), whereas an additional 14
were identified as weak candidates for differential expression (Table
8C). The remaining 21 genes exhibited combined values of
P>.05 and were therefore not identified as differentially
expressed (data not shown).
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Similar analyses were performed to identify genes exhibiting
diminished expression in cardiac hypertrophy compared with
normal myocardium by identifying genes highly expressed in
other libraries that were absent from both hypertrophic libraries.
These analyses identified only three genes achieving
statistical significance: atrial myosin light chain-2
(P=1.5x10-7), -globin
(P=.0004), and -tubulin (P=.02).
Identification of Disease Genes in the
Cardiovascular EST Data Set: Database Search and
Chromosome Localization
A large number of known disease genes were identified in the
cardiovascular EST data set. These include genes
identified by biochemical and positional strategies for a variety of
cardiovascular system–related (Table 9A)
and noncardiovascular (Table 9B) disorders. To assist
in the search for new candidates for cardiovascular
genetic disorders, 22 623 human heart ESTs generated in our laboratory
were analyzed for chromosome map locations. With the protocols
described in the methods section, 19 158 ESTs were matched to entries
in the GenBank databases; of these, 1048 were localized to chromosomes
(Fig 2; see Appendix 2 for complete
listing).
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Discussion |
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TopAbstractIntroductionMethodsResultsDiscussionReferences |
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The application of molecular biological techniques to the study of cardiovascular biology has proved to be a powerful means of exploring the molecular mechanisms underlying cardiovascular function, development, and disease. Although these methods have traditionally focused on the discovery and characterization of single genes or of relatively limited combinations of genes, recent developments in human genome research have led to the rapid discovery of thousands of previously unknown genes and increasingly to the ability to analyze large numbers of genes simultaneously. However, although ESTs and related genome-based data represent an important resource for the Human Genome Project, their vast potential for molecular medicine remains largely untapped.
Previously, we reported the development and application of an efficient
protocol for the large-scale sequencing of human cardiac cDNA
libraries11–14 and demonstrated the utility of
EST data for studying the genetics of cardiac
development.14 In this report, we present
results from the analysis in our laboratories of an additional
38 000 ESTs from six human heart cDNA libraries and compile detailed
expression data for known genes of the cardiovascular
system from these and all other ESTs derived from
cardiovascular system–based cDNA libraries currently
in dbEST. Preliminary analysis found that 12% of
cardiovascular ESTs represented novel
transcripts (CVbESTs), although this number appeared to be tissue
and/or library dependent (Table 1). Nevertheless, these numbers suggest
that EST generation remains a reasonable method for the discovery of
novel genes of the cardiovascular system, despite the
850 000 human ESTs currently available in dbEST.
Functional categorization of ESTs with known gene matches highlighted
general differences in gene expression between different tissues and
developmental states of the cardiovascular system.
Previous work established that fetal heart exhibited fewer transcripts
representing contractile proteins and more transcripts
representing signal transduction and cell regulatory
proteins than adult heart, consistent with a less
differentiated, rapidly growing
phenotype.14 The data presented
in this paper (Table 4) strengthen these findings by verifying them in
a larger number of independent libraries (although it should be noted
that the categories used in this study were slightly different from
those used previously).14 They further suggest
that global changes in gene expression are occurring in the adult
hypertrophic heart, for example, in the decreased expression of cell
structure/motility genes, perhaps reminiscent of a switch to more
embryonic patterns of gene expression, and in the increased expression
of genes involved in cell and organ defense.
In addition to observation of global patterns of gene transcription,
EST data were used for more detailed large-scale monitoring of single
gene expression in various tissues of the
cardiovascular system and in different developmental
and pathological states of the heart. Cross-comparisons between cDNA
libraries identified a number of genes that were widely expressed
throughout the tissues of the cardiovascular system
(Table 6), as well as several genes more restricted in their patterns
of expression (Table 7). Perhaps the most striking example, however,
was seen in the identification of potentially differentially expressed
genes in hypertrophic cardiomyopathy using
multiple-tissue in silico Northern analysis. In this approach,
expression frequencies of individual genes in the normal heart were
estimated from the number of ESTs matching to those genes in normal
heart cDNA libraries. Expected frequencies of gene expression in the
hypertrophic heart were calculated on the basis of observed gene
frequencies in the normal cardiac libraries. Statistically significant
deviations from expected frequency values identified potentially
differentially expressed genes.
To identify genes differentially expressed in cardiac
hypertrophy, a small sample of ESTs was generated from each
of two independent hypertrophic heart cDNA libraries (1089 ESTs and 474
ESTs, respectively; see Table 1). To minimize the effects of stochastic
clone amplification events during cDNA library construction and of
variations in gene expression levels between individuals, only genes
represented by at least one EST in both hypertrophic
libraries were selected. Potentially differentially expressed genes
were grouped into three categories based on Poisson probabilities, as
described above (Table 8). At least 10 genes identified in this manner
as either strong candidates or potential candidates for differentially
expressed genes have previously been demonstrated to be elevated or
involved in cardiac hypertrophy, including atrial
natriuretic factor,40–42 brain
natriuretic factor,42 myosin light
chain-2,43 desmin,44,45
heat shock protein 70,46 superoxide
dismutase,47,48 -cardiac
actin,49,50 ß-actin,51
and -tropomyosin.52,53 Further, the ADP/ATP
translocator, identified as a weak candidate, is known to be
activated in severe cardiac hypertrophy and
congestive heart failure.54 Two sarcomeric
proteins also identified as weak candidates have been well
characterized as being involved in the pathogenesis of hypertrophic
cardiomyopathy, ie, ß-myosin heavy
chain55,56 and cardiac troponin
T.52,53
In addition to the genes previously known to be involved in cardiac
hypertrophy, this approach also suggests several new genes
to be differentially regulated in hypertrophy. A number of
these were involved in energy or high-energy phosphate
metabolism (myoglobin, mitochondrial genome transcripts,
muscle and mitochondrial isoforms of creatine kinase, pyruvate
dehydrogenase -subunit, NADH dehydrogenase subunit ND2, cytochrome
c oxidase subunit VIIc, and ATPase coupling factor 6
subunit), which might be anticipated, given known alterations in
substrate delivery and energy metabolism in the
hypertrophied heart. Several others were involved in protein synthesis
(ribosomal protein S28) or in regulating protein turnover, either in
the intracellular (-B-crystallin, ubiquitin, 26S proteosome subunit
p31) or the extracellular (thrombin inhibitor, tissue
inhibitor of metalloproteinase-3) compartments. Although
there is no direct evidence in the literature for differential
regulation of these specific genes, thyroxine-induced
hypertrophy was found to increase rates of protein
synthesis and protein degradation in rabbit
hearts,57 and the remodeling of the cardiac
interstitium during hypertrophy is well documented,
suggesting a possible role for these and other related genes in such
processes. Also of some interest was the identification of
prostaglandin D synthases as strong candidates for
differential expression. Given that prostaglandin D2 has
been shown to have positive inotropic effects on rodent
hearts58,59 and that prostaglandin F2
but not prostaglandin D2 induces cardiomyocyte
hypertrophy and cardiac growth,60
further investigation into whether differential regulation of these and
other prostaglandin synthases is occurring and into what
role these may play in cardiac hypertrophy and heart
failure appears to be warranted.
Despite the preliminary nature of these data, the fact that a large number of genes identified as candidates for differential expression by the in silico method correspond to genes actually known to be differentially expressed suggests that a combined Poisson probability cutoff of P<.05 is appropriate for screening and that this method holds tremendous potential for genome-wide searching for novel genes involved in cardiovascular disorders such as cardiac hypertrophy and heart failure, even with relatively small EST data sets (1089 ESTs and 474 ESTs in the two hypertrophic libraries). Nevertheless, increased numbers of ESTs from both normal and diseased tissues would undoubtedly increase the sensitivity of this approach, especially for transcripts normally expressed at very low levels and for detection of transcripts that might be underexpressed in disease. It should also be noted that the analyses presented here included only ESTs with known gene matches. Extension of this strategy to ESTs without known gene matches presents more of a challenge because, in the absence of full-length gene sequences, it is not always apparent whether two ESTs represent two different genes or nonoverlapping segments of the same gene.
Progress toward the tagging and eventual sequencing of the entire set of human genes suggests that other similar genome-based methods such as serial analysis of gene expression61,62 or differential hybridization of arrayed cDNA clones63–65 will become increasingly informative and powerful for such analyses in coming years. However, the observation that 12% of cardiovascular ESTs do not match to any known sequences suggests that a significant proportion of human genes may remain untagged despite the large number of ESTs currently available and hence that EST generation will continue to play a key role in large-scale gene discovery and expression studies.
The utility of EST information for the identification of novel genes
involved in disease was further demonstrated by the number of known
disease genes for both cardiovascular and
noncardiovascular disorders represented in
the cardiovascular EST data set (Table 9), the
implication being that a substantial number of currently unknown
disease genes are also likely to be represented within the
data set. Large-scale mapping of ESTs to their chromosomal
loci66 should expedite the search for novel
disease genes by positional candidate
approaches67,68 in which ESTs mapping to a known
disease locus serve as candidate genes for that disorder. Compilation
of map data for cardiovascular ESTs (Fig 2, Appendix 2)
should ultimately allow for correlation of expression data with map
location and enhance the usefulness of this resource for the
identification of genes associated with cardiovascular
disease susceptibility loci.
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Future Directions
Exploitation of the wealth of information generated by
genome research holds exciting prospects for the field of
cardiovascular science. Although an extensive database
of human cardiac ESTs is rapidly being compiled, ESTs from other human
cardiovascular tissues or cell types or from diseased
specimens remain relatively limited. Moreover,
cardiovascular EST data from most other model organisms
widely used for cardiovascular research (eg, rat,
mouse, chicken, frog, zebrafish) are almost nonexistent. Continued
generation of ESTs from such specimens, coupled with application of
other strategies such as serial analysis of gene expression and
differential hybridization, is therefore essential.
At the same time, as increasing numbers of genes are identified, increasing emphasis needs to be placed on functional analysis of newly discovered genes in the cardiovascular system and on developing strategies to maximize extraction of useful information from the large body of raw data currently available. The construction of cardiovascular gene databases at different stages of development and pathology, coupled with integration of information gleaned from large-scale mapping, expression, and functional analyses, will establish an invaluable resource for future genetic studies of cardiovascular function and cast light on the complex genetic mechanisms underlying disease, development, and evolution of the cardiovascular system.
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Acknowledgments |
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The Cardiac Gene Unit was established in memory of Nigel M.S. Martin. This work was supported by The Canadian Genome Analysis and Technology Program, The Medical Research Council of Canada, The Heart and Stroke Foundation of Ontario, Spectral Diagnostics, Inc, and the Research Grants Council of Hong Kong (CUHK 418/95M, CUHK 205/96M). D.M.H. is a recipient of a Medical Research Council of Canada Studentship. M.R. is a recipient of a Heart and Stroke Foundation of Ontario Traineeship. K.-S.D. is a recipient of a University of Toronto Graduate Studies Award for International Students. S.K.W.T. is a recipient of a Postdoctoral Fellowship from the Chinese University of Hong Kong.
Received April 17, 1997; revision received July 16, 1997; accepted August 1, 1997.
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 P.-H. Chu, W. M. Bardwell, Y. Gu, J. Ross Jr., and J. Chen FHL2 (SLIM3) Is Not Essential for Cardiac Development and Function Mol. Cell. Biol., October 15, 2000; 20(20): 7460 - 7462. [Abstract] [Full Text]
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 S. Bortoluzzi, F. d’Alessi, and G. A. Danieli A Novel Resource for the Study of Genes Expressed in the Adult Human Retina Invest. Ophthalmol. Vis. Sci., October 1, 2000; 41(11): 3305 - 3308. [Abstract] [Full Text]
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P. D. Sehl, J. T. N. Tai, K. J. Hillan, L. A. Brown, A. Goddard, R. Yang, H. Jin, and D. G. Lowe Application of cDNA Microarrays in Determining Molecular Phenotype in Cardiac Growth, Development, and Response to Injury Circulation, April 25, 2000; 101(16): 1990 - 1999. [Abstract] [Full Text] [PDF]
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 S. Bortoluzzi, F. d'Alessi, C. Romualdi, and G. A. Danieli The Human Adult Skeletal Muscle Transcriptional Profile Reconstructed by a Novel Computational Approach Genome Res., March 1, 2000; 10(3): 344 - 349. [Abstract] [Full Text]
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 M. Rezvani, J.D. Barrans, K.-S. Dai, and C.-C. Liew Apoptosis-related genes expressed in cardiovascular development and disease: an EST approach Cardiovasc Res, February 1, 2000; 45(3): 621 - 629. [Abstract] [Full Text] [PDF]
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 M. Ko, J. Kitchen, X Wang, T. Threat, X Wang, A Hasegawa, T Sun, M. Grahovac, G. Kargul, M. Lim, et al. Large-scale cDNA analysis reveals phased gene expression patterns during preimplantation mouse development Development, January 4, 2000; 127(8): 1737 - 1749. [Abstract] [PDF]
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 J.-M. Claverie Computational methods for theidentification of differential and coordinated gene expression Hum. Mol. Genet., September 1, 1999; 8(10): 1821 - 1832. [Abstract] [Full Text] [PDF]
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R. E. Pratt and V. J. Dzau Genomics and Hypertension : Concepts, Potentials, and Opportunities Hypertension, January 1, 1999; 33(1): 238 - 247. [Abstract] [Full Text] [PDF]
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S. Bortoluzzi, L. Rampoldi, B. Simionati, R. Zimbello, A. Barbon, F. d'Alessi, N. Tiso, A. Pallavicini, S. Toppo, N. Cannata, et al. A Comprehensive, High-Resolution Genomic Transcript Map of Human Skeletal Muscle Genome Res., August 1, 1998; 8(8): 817 - 825. [Abstract] [Full Text]
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 M. Mao, G. Fu, J.-S. Wu, Q.-H. Zhang, J. Zhou, L.-X. Kan, Q.-H. Huang, K.-L. He, B.-W. Gu, Z.-G. Han, et al. Identification of genes expressed in human CD34+ hematopoietic stem/progenitor cells by expressed sequence tags and efficient full-length cDNA cloning PNAS, July 7, 1998; 95(14): 8175 - 8180. [Abstract] [Full Text] [PDF]
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M. Rezvani and C.-C. Liew Role of the Adenomatous Polyposis Coli Gene Product in Human Cardiac Development and Disease J. Biol. Chem., June 9, 2000; 275(24): 18470 - 18475. [Abstract] [Full Text] [PDF]
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K.-S. Dai and C.-C. Liew A Novel Human Striated Muscle RING Zinc Finger Protein, SMRZ, Interacts with SMT3b via Its RING Domain J. Biol. Chem., June 22, 2001; 276(26): 23992 - 23999. [Abstract] [Full Text] [PDF]
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X. Wang, H. Osinska, R. Klevitsky, A. M. Gerdes, M. Nieman, J. Lorenz, T. Hewett, and J. Robbins Expression of R120G-{alpha}B-Crystallin Causes Aberrant Desmin and {alpha}B-Crystallin Aggregation and Cardiomyopathy in Mice Circ. Res., July 6, 2001; 89(1): 84 - 91. [Abstract] [Full Text] [PDF]
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