Genomic analysis of immediate/early response to shear stress in human coronary artery endothelial cells
D. G. Peters1,3,
X.-C. Zhang1,
P. V. Benos1,2,3,
E. Heidrich-OHare1 and
R. E. Ferrell1,3
1 Departments of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
2 Center for Computational Biology and Bioinformatics, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
3 University of Pittsburgh Cancer Institute, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
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ABSTRACT
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The involvement of shear stress in the pathogenesis of vascular disease has motivated efforts to define the endothelial cell response to applied shear stress in vitro. A central question has been the mechanisms by which endothelial cells perceive and respond to changes in fluid flow. We have utilized cDNA microarrays to characterize the immediate/early genomic response to applied laminar shear stress (LSS) in primary cultures of human coronary artery endothelial cells (HCAECs). Cells were exposed, in a parallel plate flow chamber, to 0, 15, or 45 dyn/cm2 LSS for 1 h, and gene expression profiles were determined using human GEM1 cDNA microarrays. We find that a high proportion of LSS-responsive genes are transcription factors, and these are related by their involvement in growth arrest. These likely play a central role in the reprogramming of endothelial homeostasis following the switch from a static to a shear-stressed environment. LSS-responsive genes were also found to encode factors involved in vasoreactivity, signal transduction, antioxidants, cell cycle-associated genes, and markers of cytoskeletal function and dynamics.
gene expression; atherosclerosis; endothelial cell; microarray
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INTRODUCTION
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PHYSICAL FORCES ARE EMERGING as major determinants of physiological state, and there have been extensive studies describing gene expression changes in response to defined mechanical stress. One area of particular interest is the response of vascular endothelial cells to applied fluid flow. Shear stress is known to elicit modulation in the expression levels of a number of genes involved in vascular reactivity. Based on in vitro analyses, under high fluid shear stresses (>15 dyn/cm2) vascular endothelial cells enter a quiescent, antiproliferative, antioxidant, and antithrombotic state which is reflected by the downmodulation of a number of atherogenic factors. For example, high fluid shear stress results in the downregulation of vascular cell adhesion molecule 1 (VCAM-1) (35), upregulation of antioxidant genes [copper-zinc superoxide dismutase (SOD1) and manganese superoxide dismutase (SOD2)] (21), downregulation of vasoconstrictive factors [endothelin-1 (ET-1)] (31), and upregulation of vasodilatory factors [endothelial nitric oxide synthase (eNOS)] (26). In contrast, endothelial cells exposed to low or oscillatory fluid shear stress are thought to enter in a procoagulant and prothrombotic state. Specifically, such conditions have been shown to cause the upregulation of ET-1 (54), endothelin converting enzyme (ECE) (32), angiotensin converting enzyme (ACE) (41), and platelet-derived growth factors (PDGF) A and B (25, 40). Recent developments in genomics have resulted in the availability of techniques for simultaneous parallel expression analysis of multiple genes at the level of transcription.
Three recent reports have utilized filter-based microarrays and radioisotope-labeled cDNA to characterize the genomic response of vascular endothelial cells to long-term shear stress exposure (7, 17, 33). Here we report the use of glass-based microarrays and fluorescently labeled cDNA to characterize the immediate/early transcriptional response of human coronary artery endothelial cells (HCAECs) to different levels of laminar shear stress (LSS) in vitro. This reveals a rapid transcriptional response after 1 h of exposure involving modulation of genes representing a number of distinct functional classes. In addition to simultaneously confirming that the antiproliferative, antioxidant, and vasodilatory response to shear stress is realized at the level of transcription within 1 h of the onset of flow, we identify numerous transcription factors (TFs) that are likely to be the primary targets of shear stress-responsive signal transduction cascades.
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METHODS
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Cell culture and exposure to LSS.
Primary cultures of human coronary artery endothelial cells were purchased from BioWhittaker. Cells were obtained at passage 3 and cultured in EGM2MV medium (BioWhittaker). Cells at passage 5 were seeded at a density of
5 x 104 cells/cm2 on glass microscope slides and cultured at 37°C in humidified 5% CO2 95% air. Confluent monolayers of cells were then placed in a parallel plate flow chamber (16) under aseptic conditions and perfused in EGM2MV at 37°C in humidified 5% CO2-95% air for 1 h. Control cells not exposed to LSS were also cultured in EGM2MV for an identical length of time as LSS-treated cells.
RNA isolation cDNA microarray analysis.
Cells were harvested directly into Trizol reagent (Life Technologies) and total RNA extracted according to the manufacturers instructions. mRNA was prepared from total RNA using the Dynabeads mRNA purification kit (Dynal) and pooled at a ratio of 1:1:1 from the three identical experiments. RNA was reverse transcribed in the presence of Cy3 or Cy5 fluorescently labeled dNTPs and hybridized to 9,128 gene/EST-containing human GEM1-glass based microarrays (Incyte Genomics) as previously described (14).
Northern analysis.
Shear stress experiments were repeated as above to generate RNA for Northern analysis, which was performed by standard methods using formaldehyde/agarose gels in which 20 µg of total RNA was loaded per lane. Gene-specific DNA probes were prepared by RT-PCR using gene-specific primers. These were radioactively labeled by random-primed DNA labeling in the presence of [
-33P]dCTP. Signal intensity was measured using a Storm PhosphorImager (Molecular Dynamics).
Data analysis.
Functional classification of genes was performed using the GEMTools software package (Incyte Genomics). Clustering of microarray data sets and generation of scatter plots were carried out using the GeneSpring software package (Silicon Genetics). Criteria for identifying differentially expressed genes demanded that the signal in at least one channel (per spot) was 2.5-fold that of background signal. A ±1.8-fold cutoff for identifying differentially expressed genes. Although a ±2-fold cutoff is often used to identify differentially expressed genes, less dramatic fold changes can be considered to be of interest within the context of the coordinately regulated expression of many genes within functional classes. Less than ±2-fold stringent cutoff criteria have previously been successfully applied to microarray data sets [for example, see Chen et al. 2001 (7)].
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RESULTS
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Scatter plots of pairwise microarray analyses of CAECs exposed to 0, 15, and 45 dyn/cm2 shear stress are shown in Fig. 1 (AC). Only a small proportion of genes on the microarrays were differentially expressed by LSS exposure. Using a ±1.8-fold cutoff (see METHODS), 23 distinct cDNAs (out of 9,128 total cDNAs contained on the microarray) were found to be positively regulated and 91 negatively regulated by 15 dyn/cm2 LSS compared with a no flow control (Fig. 1A). Similarly, 25 cDNAs were positively and 25 negatively regulated by 45 dyn/cm2 LSS (Fig. 1B). Differences between LSS-exposed and control cells were largely corroborated by direct microarray comparison of RNA extracted from cells exposed to 15 and 45 dyn/cm2 LSS (Fig. 1C).

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Fig. 1. Scatter plots and clustering analysis of microarray data from 0 vs. 15 dyn/cm2 (A), 0 vs. 45 dyn/cm2 (B), and 15 vs. 45 dyn/cm2 (C) comparisons. For A and B, genes positively and negatively regulated by shear stress are represented in blue and red, respectively. For C, genes positively and negatively regulated in cells exposed to 15, relative to 45 dyn/cm2 are shown in red and blue, respectively. The ±1.8-fold cutoffs are indicated by diagonal lines.
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We further identified 26 genes whose expressions are altered ±1.8-fold in cells exposed to both 15 and 45 dyn/cm2 LSS compared with 0 dyn/cm2 controls. LSS-responsive genes fall into a number of functional categories including transcription factors, genes involved in signal transduction, nuclear transport, cell proliferation, and vascular reactivity (Table 1).
LSS exposure results in modulation of transcription factor gene expression.
It is well established that shear stress exposure results in extensive changes in cellular physiology both in vitro and in vivo. With the exception of rapid cell signaling in response to applied stimuli, such physiological responses require de novo nuclear transcription that is mediated primarily by the highly regulated activity of multiple transcription factors. LSS results in modulation of the levels of expression of a number of transcription factors in response to LSS (Table 2). Of the 26 genes that were found to be differentially expressed in cells exposed to both 15 and 45 dyn/cm2 LSS (Table 1), six (23%) are transcription factors and all have previously been described as immediate early genes whose expression is induced by a range of stimuli. These transcription factors include; Kruppel-like factor 4 (KLF4), TGF-ß inducible early growth response gene (TIEG), nuclear receptor subfamily 4 A1 (NGF4A1), activating transcription factor 3 (ATF3), v-fos FBJ murine osteosarcoma viral oncogene homolog, and EGR1. With the exception of EGR1 (24), these factors have not previously been associated with the vascular endothelial response to shear stress. It appears, however, that they are functionally united by involvement in cell growth arrest (see below). This is significant, given the well-documented reduction in endothelial cell proliferation following exposure to LSS in vitro (28).
LSS exposure results in the modulation of gene expression in other distinct functional groups.
Exposure of CAECs to LSS results in a coordinated reduction in the expression levels of a number of genes encoding markers of cell cycle progression (Table 3). This trend is more pronounced in the 0 vs. 15 dyn/cm2 comparison although it is also evident when comparing 0 and 45 dyn/cm2 LSS. Notable genes involved in cell cycle progression include CDC27, MRE11, centromere-associated proteins E and F, and nibrin.
LSS also results in a coordinated reduction in the expression of a number of genes encoding cytoskeletal-associated factors (Table 4). Negatively regulated cytoskeletal genes include the microtubule-associated proteins (MAPs); kinesin family member 5B (KIF5B, kinesin 1), kinesin heavy chain member 2 (KIF2), kinectin (KTN1), and restin (CLIP170). Also downmodulated under these conditions are the chromatin remodeling factor SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily A, member 5 (SMARCA5); the actin remodeling factor actin-related protein 2/3 complex, subunit 5 (ARPC5); and the adherens junction protein catenin ß-1 (CTNNB1).
Given the proposed involvement of G protein-mediated signaling pathways in the transduction of the shear stress signal(s), it is interesting that our data show a general downmodulation in G protein signaling factors (Table 5). Exposure of CAECs to both 15 and 45 dyn/cm2 shear stress results in downmodulation in the expression of a number of genes involved in G protein signaling, although this is more pronounced at 15 dyn/cm2 than 45 dyn/cm2. Under these conditions, no genes known to be involved in G protein signaling were found to be upmodulated by LSS. Those genes that are downmodulated by LSS include the negative regulator of G protein signaling RGS4.
A number of other genes that have functional significance are also modulated by LSS. For example, the heme oxygenase (HO) 1 gene (HMOX1) is positively regulated by LSS at both 15 and 45 dyn/cm2 (Table 1). HO is an antioxidant, which has been shown to mediate the cytoprotective effect of nitric oxide (NO) (39) and has also been implicated in reducing vasoconstriction following vascular injury (15). LSS also results in the upmodulation of the heat shock factor genes HSPA1A and HSP70B (Table 1), which also play a cytoprotective role, for example, within the context of hypoxia/reperfusion injury (22). Also positively regulated by both 15 and 45 dyn/cm2 LSS is the prostaglandin-endoperoxide synthase 2 (COX2) gene, which is involved in the production of the vasoactive substance prostaglandin I2 (PI2). mRNA corresponding to the pro-inflammatory adhesion molecule E-selectin is also dramatically induced by LSS (Table 1).
Confirmation of microarray data.
Northern blotting was carried out on four genes (KLF4, NGF4A1, ATF3, and HSP70B') to confirm the transcriptional changes identified by microarray. It can be seen from Table 6 that Northern analysis generally resulted in greater estimated differences in gene expression between individual samples than the differences estimated by microarrays, particularly in the case of NGF4A1. However, the LSS-responsive differential expression identified by microarray was qualitatively corroborated by Northern analysis for these four genes.
Computational analysis of the promoter regions of LSS-responsive genes.
Benos et al. (3) recently published a method that can model probabilistically the DNA binding specificity of proteins of a given family. This method is based on the statistical mechanics theory and uses data from in vitro randomization/selection experiments [namely, SELEX (11) and phage display (12)] of a member of this family to calculate the probabilistic "recognition code" ("P-code") that best explains the data. This P-code consists of the energetic potentials of each base-amino acid contact. In Benos et al. (4), the authors reported their P-code for the EGR family, and they evaluated it by predicting the known in vivo binding sites of EGR1 and other Cys2His2 zinc finger proteins. The predictions were in very good agreement with the known in vivo binding sites. They also showed that the predicted binding probabilities were in good agreement with the measured binding affinities of the EGR proteins and their variants to a number of DNA targets. We used their model for the EGR protein family to investigate further whether EGR1 directly regulates some of the LSS-responsive genes that we identified in our previous analysis (see Table 1). First, we used their weight matrix to calculate the probabilities of all possible 9-bp-long targets that bind to the EGR1 protein. Then we calculated the score matrix, presented in Table 7, as the logarithm of the probability of binding over the reference probability of the target. We considered each base in the human genome to be equiprobable, so a reference probability of 0.25 is used for each base in each base position. Higher scores correspond to higher binding probabilities and, in general, positive scores correspond to favorable binding. As expected, for most positions only one base is preferred (i.e., has a positive score). The range of the scores for all possible 9-bp-long targets is -41.32 to 9.62. According to Table 7, the two "best targets" for the EGR proteins are 5'-GCGGGGGCG-3' and 5'-GCGTGGGCG-3' with scores 9.62 and 8.97, respectively.
The weight matrix of Table 7 is used as input for the program "patser" (20) to scan the 2-kb upstream genomic regions of the 23 known genes (of 26) that we found to be responsive to LSS (Table 1). All of the LSS-responsive genes were found to have at least one binding site with a positive score in their upstream regions; 56.5% of them (13 of the 23) had a score of 7.00 or greater. The lowest scores were observed for the genes OSF2 (4.32) and HSPA1A (4.62). No correlation was observed between the level of expression and the highest "patser" score of the putative binding sites. This is not surprising, given that gene regulation in eukaryotes can be a complex process and sometimes depends in more than one transcription factors. In addition, limitations of both the probabilistic modeling of the binding sites and the microarray technology can further explain this lack of correlation.
Although we cannot be sure whether the 23 early responsive genes that were identified through the microarray analysis are all regulated by the EGR1 protein, the existence of good putative EGR1 binding sites in the upstream regions of many of them further supports this notion.
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DISCUSSION
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We present a comprehensive analysis of the immediate/early genomic response to applied LSS at 0, 15, and 45 dyn/cm2 using high-density cDNA microarrays. This semiglobal analysis of transcription focuses on the early nuclear events following shear stress exposure. Using this approach, we have identified a number of genes representing a broad range of functional classes whose expression are modulated by LSS. Although a small number of these transcriptional events are predicted by previous studies, most of these differentially expressed genes have not been implicated in shear stress-responsive endothelial cell molecular physiology. Preliminary identification of LSS-responsive genes that may be directly regulated by one of the LSS-responsive transcription factors (EGR1) was performed using a novel computational approach. This is a first step toward a detailed functional analysis of the gene regulatory networks that underlie the transcriptional profiling data presented. This information will help guide future work to experimentally define the downstream targets of EGR1 within the context of exposure to LSS.
The functional class of genes most dramatically responsive to 1 h of LSS exposure is that of the transcription factors. This likely reflects the extensive molecular reprogramming undertaken by endothelial cells following the onset of flow. That extensive transcriptional modulation occurs after 60-min exposure to shear stress is not unexpected, given previous temporal analysis of gene expression in other systems using similar technology (48). Our results indicate that the reprogramming of gene expression in response to LSS is rapid and involves genes, particularly transcription factors, that modulate the cellular response to a variety of stresses.
It is well established that shear stress results in a reduction in endothelial cell proliferation (28), and this is reflected by our own data. Transcription factors involved in this process have not, however, been extensively described. One such factor is KLF4, also known as gut-enriched Kruppel-like factor (GKLF)/epithelial zinc finger (EZF). KLF4 has previously been shown to be expressed in vascular endothelial cells by Yet et al. in 1998 (52). It is significant that KLF4, which has been reported to act as either a transcriptional activator or a repressor (52), inhibits DNA synthesis and is associated with growth arrest. This inhibitory effect on cell proliferation is mainly exerted at the G1/S boundary of the cell cycle (9).
Also notable is the upregulation by LSS of TIEG. Like KLF4, TIEG exerts an antiproliferative effect. TIEG has been shown to play a role in linking TGF-ß-mediated signaling cascades to the regulation of pancreatic cell growth (45). Similarly, NGF4A1, a human homolog of mouse nur77/NGFI-B, is thought to be involved in growth arrest. Nur77/NGFI-B has also been shown to be transcriptionally upregulated 30 min after the onset of flow in a rat focal ischemia-reperfusion model (30) and may be induced under hypoxic conditions in mice (47). Also of interest is ATF3, which is also upregulated by both 15 and 45 dyn/cm2 LSS. ATF3 is a member of the ATF/CREB protein family of transcription factors and is able to bind ATF binding sites in target genes whereupon it acts as a transcriptional repressor. An alternatively spliced isoform (ATF3 delta Zip), which lacks the leucine zipper domain, does not bind DNA and may act as a transcriptional activator by sequestering inhibitory cofactors away from specific gene promoters (8). ATF3 expression has been demonstrated in vascular endothelial cells where it has been implicated in having an antiproliferative effect on cell physiology (5). Like nur77/NGFI-B, ATF3 expression is upregulated by ischemia/reperfusion (53).
Further evidence that the molecular events leading to the antiproliferative effect of shear stress are mediated within 60 min of flow onset can be seen by the downmodulation of genes encoding cell cycle factors. For example, the human homologs of the yeast genes CDC10 and CDC27, which are required for progress through the G1 phase of the cell cycle and for DNA synthesis (respectively) (43, 44), are both downmodulated by LSS. Also downmodulated by LSS is the nuclease encoding MRE11 gene, which is associated with replicating nuclei and required to yield normal DNA replication products (13). MRE11 is thought to be involved in T loop formation at the telomere, thereby assisting in the protection and replication of telomeres (18). Similarly, the centromeric proteins E and F are required for cell cycle progression (29, 51).
In light of the fact that long-term exposure of endothelial cells to shear stress results in their elongation and alignment in the direction of flow, we mined our data for genes that are known to encode proteins involved in cytoskeletal structure and dynamics. Although this approach identified a general downmodulation of cytoskeletal markers in response to 15 dyn/cm2 (but not the 45 dyn/cm2) LSS, these do not appear to encode proteins that are directly involved in the structural remodeling that occurs following LSS exposure. For example, a number of microtubule-associated proteins (MAPs) are regulated by LSS. One group of these, the kinesins (e.g., KIF5B and KIF2), are microtubule-based motor proteins involved in the transport of organelles in eukaryotic cells and mitosis (42, 46). Also involved in vesicle motility and downmodulated by LSS are kinectin, a large integral endoplasmic reticulum membrane protein (27) and restin (CLIP70) (38). Coordinated regulation of these MAPs suggests extensive reorganization of cellular activity following exposure to LSS. Genes involved in structural remodeling in response to LSS may be represented by, for example, ß-catenin (CTNNB). CTNNB encodes a cytoplasmic component of the adherens junction, which is involved in mediating adhesion between cells, communicating extracellular stimuli, and anchoring the actin cytoskeleton. Macrophin (ACF7), which belongs to the plakin family of cytoskeletal linker proteins, has functional actin and microtubule binding domains and may function in microtubule dynamics to facilitate actin-microtubule interactions at the cell periphery and to couple the microtubule network to cellular junctions (37). Similarly, ARPC5 is thought to be involved in assembly of the actin cytoskeleton (50). No obvious changes in cell morphology were observed during the duration of exposure to LSS in our experiments (not shown).
It has been reported that G protein signaling plays a central role in transducing the shear stress stimulus to the nucleus (19). We identified genes within our data sets that are involved in G protein signaling and found that the expression of these tended to be downmodulated by 15 dyn/cm2 LSS, and to a lesser extent 45 dyn/cm2 LSS. These downmodulated genes include a number of GTPase activating factors (GAPs) and regulator of G protein signaling (RGS) family members (e.g., RGS4). RGS family members are regulatory molecules that act as GAPs for G
subunits of heterotrimeric G proteins. RGS proteins are able to deactivate G protein subunits of the Gi
, Go
, and Gq
subtypes. They drive G proteins into their inactive GDP-bound forms and so are able to act as negative regulators of heterotrimeric G protein coupled receptor signaling. RGS4, which we found to be more than twofold downmodulated by LSS, belongs to this family and may, therefore, be involved in a derepression of G protein signaling in response to LSS. This finding is consistent with previous reports of the involvement of G protein signaling in response to shear stress (19).
A number of other functional classes were represented by LSS-responsive genes. Perhaps the most dramatically regulated of these is E-selectin, which, somewhat surprisingly, is positively regulated by both 15 and 45 dyn/cm2 LSS. This positive regulation contrasts previous evidence that LSS has a minimal effect on E-selectin expression (34). It is possible that E-selectin induction by LSS is caused by the rapid transition between static conditions and the onset of LSS in our experimental system, which may result in a functionally significant temporal gradient in shear stress. In support of this, it has been demonstrated that E-selectin expression is positively regulated by exposure of endothelial cells to temporal gradients in shear stress (6). Significantly, Bao et al. (1999) have shown differential endothelial cell response to temporal gradients in shear stress vs. steady shear stress (2). Which, if any, of the LSS-responsive genes observed in our experiments, or those of others (7, 33), are specifically responding to temporal changes in shear stress vs. steady shear stress remains to be determined.
Also positively regulated by both 15 and 45 dyn/cm2 LSS is COX2, which is involved in the production of the vasoactive substance PI2 and is also known to be responsive to shear stress (36). Similarly, the gene encoding the vasoconstrictive substance ET-1 is downmodulated by both 15 and 45 dyn/cm2 LSS, confirming that the vasodilatory effect of LSS is manifested, at least at the level of transcription, within 60 min of the onset of flow. Less predictable is the dramatic upregulation of the HMOX1 gene, whose biological activity leads to production of HO. HO catalyzes the first and rate-limiting step in the oxidative degradation of heme to bilirubin (1), resulting in the production of biliverdin and carbon monoxide (CO), and the release of free iron (10). HO-1, which has previously been shown to be induced by shear stress in vascular smooth muscle cells (49), is known to protect against oxidant-induced cellular injury (23), and CO is thought to promote vasodilation (55).
In summary, we describe the immediate/early transcriptional response to different levels of LSS using cDNA microarrays as a broad-spectrum discovery tool. We have identified a number of LSS-responsive immediate/early genes including transcription factors and cell cycle regulators whose modulation may reflect the key nuclear signaling events that lead to the modulation of cell physiology exhibited by endothelial cells exposed to fluid flow. Characterization of the coordinated regulation of these shear-responsive gene families will help further elucidate the mechanisms governing the endothelial cell response to shear stress. Such information will have an impact in a number of areas of human disease including atherosclerosis, vascular tissue engineering, and aneurysmal disease.
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ACKNOWLEDGMENTS
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This work was supported by National Heart, Lung, and Blood Institute Grants HL-44682 (to R. E. Ferrell), the University of Pittsburgh Central Research Development Fund (to D. G. Peters), and by National Aeronautics and Space Administration Grant NCCI-1227 (to D. G. Peters). The work of P. V. Benos was supported by intramural funds of the Department of Human Genetics, the Center for Computational Biology and Bioinformatics, and the University of Pittsburgh Cancer Institute.
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FOOTNOTES
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Address for reprint requests and other correspondence: D. G. Peters, Dept. of Human Genetics, Graduate School of Public Health, Univ. of Pittsburgh, Pittsburgh, PA 15261 (E-mail: david.peters{at}mail.hgen.pitt.edu).
10.1152/physiolgenomics.00016.2002.
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