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Physiol. Genomics 33: 50-64, 2008. First published December 4, 2007; doi:10.1152/physiolgenomics.00185.2006 Free Article
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Received 22 August 2006; accepted in final form 27 November 2007.
Physiological Genomics 33:50-64 (2008)
1094-8341/08 $8.00 © 2008 American Physiological Society

Map of differential transcript expression in the normal human large intestine

Lawrence C. LaPointe 1,2,3, Robert Dunne 2, Glenn S. Brown 3, Daniel L. Worthley 1, Peter L. Molloy 3, David Wattchow 4 and Graeme P. Young 1

1 Department of Medicine, Flinders University of South Australia, Adelaide, South Australia
2 Preventative Health National Research Flagship, CSIRO Mathematical and Information Sciences, Sydney
3 Preventative Health National Research Flagship, CSIRO Molecular and Health Technologies, Sydney, New South Wales
4 Department of Surgery, Flinders University of South Australia, Adelaide, South Australia, Australia


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
While there is considerable research related to using differential gene expression to predict disease phenotype classification, e.g., neoplastic tissue from nonneoplastic controls, there is little understanding of the range of expression in normal tissues. Understanding patterns of gene expression in nonneoplastic tissue, including regional anatomic expression changes within an organ, is vital to understanding gene expression changes in diseased tissue. To explore the gene expression change along the proximal-distal axis of the large intestine, we analyzed microarray data in 184 normal human specimens using univariate and multivariate techniques. We found 219 probe sets that were differentially expressed between the proximal and distal colorectal regions and 115 probe sets that were differentially expressed between the terminal segments, i.e., the cecum and rectum. We did not observe any probe sets that were statistically different between any two contiguous colorectal segments. The dominant expression pattern (65 probe sets) follows a dichotomous expression pattern consistent with the midgut-hindgut embryonic origins of the gut while a second pattern (50 probe sets) depicts a gradual change in transcript levels from the cecum to the rectum. While the dichotomous pattern includes roughly equal numbers of probe sets that are elevated proximally and distally, nearly all probe sets that show a gradual change demonstrate increasing expression levels moving from proximal to distal segments. These patterns describe an expression map of individual transcript variation as well as multigene expression patterns along the large intestine. This is the first gene expression map of an entire human organ.

colorectal gene expression


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
THE ADVENT OF GENE EXPRESSION profiling has led to an improved understanding of intestinal mucosa development. For example, the regulation of transcription factors involved in producing and maintaining the radial-axis balance from the crypt base to the lumen and those giving rise to epithelial cell differentiation is now better understood as a result of microarray gene expression analysis (43, 48). Similarly, understanding of the developmentally programmed genetic events within the embryonic gut has improved, especially those molecular control mechanisms responsible for regional epithelium differences between the small intestine and colon (17, 42). On the other hand, little is known about the proximal-distal gene expression variation along the longitudinal axis of the colorectum in either the neoplastic or nonneoplastic setting (6). Epidemiologic studies of colorectal adenocarcinoma suggest support for variable incidence, histopathology, and prognosis between proximal and distal tumors (8, 9, 18, 19). Thus an understanding of location-specific variation could provide valuable insight into those diseases that have characteristic distribution patterns along the colorectum, including colorectal cancer (7, 12, 22).

The large intestine is often divided for clinical convenience into six anatomical regions starting from the terminal region of the ileum: the cecum, the ascending colon, the transverse colon, the descending colon, the sigmoid colon, and the rectum. Alternatively, these segments may be grouped to divide the large intestine into a two-region model comprising the proximal and distal large intestine. The proximal ("right") region is generally taken to include the cecum, ascending colon, and the transverse colon, while the distal ("left") region includes the splenic flexure, the descending colon, the sigmoid colon, and the rectum. This division is supported by the distinct embryonic ontogenesis of these regions whose junction is two-thirds along the transverse colon and also by the distinct arterial supply to each region. While the proximal large intestine develops from the embryonic midgut and is supplied by the superior mesenteric artery, the distal large intestine forms from the embryonic hindgut and is supplied by the inferior mesenteric artery (3). A comprehensive of review of proximal/distal differences are provided in Ref. 29.

The longitudinal nature of the large intestine along the proximal-distal axis provides a relatively unique opportunity for constructing a whole organ map of gene expression. Previous research suggests that there is a clear distinction between the gene expression patterns of proximal colonic tissues and distal colorectal tissues (7, 25, 33). While these findings support a broad model of gene expression difference, there have been no studies to explore the detailed nature of expression gradients of such genes. Given the interesting embryology related to the midgut and hindgut junction near the splenic flexure during embryogenesis, the question is raised: Do differentially expressed genes exhibit an abrupt expression schism between the midgut- and hindgut-derived tissues or does expression follow a gentle gradient along the proximal-distal axis?

To explore this question, this work investigates the gene expression patterns observed along the proximal-distal axis of the large intestine. By exploring these patterns in nonneoplastic tissues we aim to improve understanding of gene expression variation in healthy normal adults without the added complexity of neoplasia-related gene expression changes. We have built expression profile "maps" that identify individual genes whose expression appears to be location dependent, and we have described the nature of multigene expression variance longitudinally along the colon. We apply linear models to these maps to compare the embryology-consistent proximal vs. distal two-region model with a more gradual model based on continuously variable expression between the cecum proximally and rectum distally. Such gene expression maps of the normal adult colon will provide a foundation for improved understanding of gene expression variation in both the normal and diseased state.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Gene Expression Data
The data for this study are generated using oligonucleotide microarrays hybridized to labeled cRNA synthesized from poly-A mRNA transcripts isolated from colorectal tissue specimens.

"Discovery" data set.
Gene expression and clinical descriptions for 184 colorectal tissue specimens were purchased from GeneLogic (Gaithersburg, MD). Individual tissue microarray data were selected with the following characteristics: nonneoplastic colorectal mucosa free of nonmucosa contaminating tissue (confirmed by histology) from otherwise healthy tissue specimen (i.e., no evidence of inflammation or other disease at specimen site) with an anatomically identifiable site of resection designated as one of: cecum, ascending colon, descending colon, sigmoid colon, or rectum.

For each tissue selected from the GeneLogic database, we received electronic files of raw data containing a total of 44,928 probe sets (Affymetrix HGU133A and HGU133B, combined), experimental and clinical descriptors for each tissue, and digitally archived microscopy images of the histology preparations. Each data record was manually assessed for clinical consistency, and a sample of records was randomly chosen for histopathology audit using digitally archived histology images. A quality control analysis was performed to identify and remove array results not meeting essential quality control measures as defined by the manufacturer (1, 50).

Gene expression levels were calculated by both Microarray Suite (MAS) 5.0 (Affymetrix) and the robust multichip average (RMA) normalization techniques (1, 28, 30). MAS normalized data were used for performing standard quality control routines, and the final data set was normalized with RMA for all subsequent analyses. A list of GeneLogic sample IDs for the commercial microarray data used in this study is included as supplemental material.1

"Validation" data set.
The colorectal specimens in the validation set were collected from a tertiary referral hospital tissue bank in metropolitan Adelaide, Australia (Repatriation General Hospital and Flinders Medical Centre). The tissue bank and this project were approved by the Research and Ethics Committee of the Repatriation General Hospital, and patient consent was received for each tissue studied. Following surgical resection, specimens were placed in a sterile receptacle and collected from theatre. The time from operative resection to collection from theatre was variable but not more than 30 min. Samples, ~125 mm3 (5 x 5 x 5 mm) in size, were taken from the macroscopically normal tissue as far from pathology as possible, defined both by colonic region as well as by distance either proximal or distal to the pathology. Tissues were placed in cryovials, then immediately immersed in liquid nitrogen and stored at –150°C until processing.

Frozen samples were processed by the authors using standard protocols and commercially available kits. Briefly, frozen tissues were homogenized using a carbide bead mill (Mixer Mill MM 300; Qiagen, Melbourne, Australia) in the presence of chilled Promega SV RNA Lysis Buffer (Promega, Sydney, Australia) to neutralize RNase activity. Homogenized tissue lysates for each tissue were aliquoted to convenient volumes and stored –80°C. Total RNA was extracted from tissue lysates using the Promega SV Total RNA system according to manufacturer's instructions and integrity was assessed visually by gel electrophoresis.

To measure relative expression of mRNA transcripts, tissue RNA samples were analyzed using Affymetrix HG U133 Plus 2.0 GeneChips (Affymetrix, Santa Clara, CA) according to the manufacturer's protocols (2). Biotin-labeled cRNA was prepared using 5 µg (1.0 µg/µl) total RNA (~1 µg mRNA) with the "One-Cycle cDNA" kit [incorporating a T7-oligo(dT) primer] and the GeneChip IVT labeling kit. In vitro transcribed cRNA was fragmented (20 µg) and analyzed for quality control purposes by spectrophotometry and gel electrophoresis prior to hybridization. Finally, an hybridization cocktail was prepared with 15 µg of cRNA (0.5 µg/µl) and hybridized to HG U133 Plus 2.0 microarrays for 16 h at 45°C in an Affymetrix Hybridization Chamber 640. Each cRNA sample was spiked with standard prokaryotic hybridization controls for quality monitoring.

Hybridized microarrays were stained with streptavidin phycoerythrin and washed with a solution containing biotinylated anti-streptavidin antibodies using the Affymetrix Fluidics Station 450. Finally, the stained and washed microarrays were scanned with the Affymetrix Scanner 3000.

The Affymetrix software package was used to transform raw microarray image files to digitized format. As for the Discovery set above, gene expression levels for the validation data set were calculated using MAS 5.0 (Affymetrix) for quality control purposes and with the RMA normalization algorithm for expression data. Finally, the data for the 19 microarrays used for validation in this publication have been deposited in the National Center for Biotechnology Information's Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO Series accession number GSE9254.

Statistical Analysis
For all statistical analysis, we used open source software available from BioConductor for the R statistics environment (BioConductor, www.bioconductor.org) (23, 24).

Gene expression gradients were analyzed using three analytical techniques. First, we compared the gene expression variation of individual genes along the colon using univariate tests. Next, we further explored those particular genes exhibiting statistically significant expression differences with linear models to compare dichotomous (proximal vs. distal) expression change with a gradual (multisegment) model of change. Finally, we applied multivariate techniques to understand subtle genome-wide expression variance along the proximal-distal axis.

Individual Gene Expression Maps
Univariate differential expression.
Differentially expressed gene transcripts between the proximal and distal colon were identified using a moderated t-test implemented in the "limma" Bioconductor library (47). Significance estimates (P values) were corrected to adjust for multiple hypothesis testing using the conservative Bonferroni correction. The subset of tissues limited to the cecum vs. the rectum was similarly tested.

Gene transcripts identified to be differentially expressed were also evaluated in the Validation specimens on a probe set-by-probe set basis using modified t-tests. To assess the significance of the total number of differential probe sets that were likewise differential in the validation data, the number of validated probe sets were compared with a null distribution estimated using a Monte Carlo simulation.

Multisegment colon vs. two-segment colon model comparison.
To evaluate the nature of intersegment gene expression variation we analyzed differentially expressed probe sets for relative fit to linear models in a multisegment vs. a two-segment framework. The goal of this analysis is to explore whether the intersegment expression of probe sets that are known to be differentially expressed between the terminal ends of the large intestine are better modeled by a five-segment linear model that approximates a continual gradation or by a simpler, dichotomous "proximal" vs. "distal" gradient. As our data are only identified by colorectal segment designation and not by a continuous measurement along the length of the colon, we approximate the continuous model using the tissue segment location. We chose probe sets that are differentially expressed between the most terminal segments (cecum and rectum) to maximize the likelihood of identifying transcripts that vary along the proximal-distal axis of the colon.

We first modeled the expression of these probe sets along the proximal-distal axis of the colon using a five-factor robust linear model according to an indicator matrix defined by the colorectal segment for each tissue. For this model each tissue was assigned by biopsy location to one of: cecum, ascending, descending, sigmoid, or rectum. (For reasons described below, transverse tissues were not included in this analysis.) This five-segment model was then compared with a two-factor robust linear model with a design matrix corresponding to the theoretical proximal and distal regions of the colon. The same data were used for both model comparisons; however, for the two-segment model, the first factor (corresponding to the proximal tissues) included all of the tissues from the cecum and ascending colon, while the second factor (corresponding to the distal colon) included all tissues from the descending, sigmoid, and rectum segments.

When comparing these distinct models for each probe set, we used an F-test to evaluate the alternative hypothesis that the improved fit (reduced regression residual) provided by the more complex five-segment model was significantly better than the simpler two-segment model. A nonsignificant residual reduction indicates a failure to reject the null hypothesis: that there is no inherent value to adopting a more complex five-segment model over the simpler alternative.

Multivariate Gene Expression Pattern Mapping
Supervised principal components analysis.
To visualize and explore the structure of expression variability at an organ level, we applied principal component analysis (PCA) and supervised PCA. Supervised PCA is similar to traditional PCA but uses only a subset of the features/genes (usually selected by some univariate means) to derive the principal components (4). We use the set of genes differentially expressed between the cecum and rectum as described above. All software for implementing supervised PCA was developed by us and is available on request. The algorithms for supervised PCA is coded in R.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Gene Expression Data Collection
To explore variation of human gene expression along the nonneoplastic colon, we used gene expression data collected using the Affymetrix GeneChip oligonucleotide microarray system described in Ref. 36. The data are two independent Affymetrix Human Genome 133 GeneChip data sets: a large commercial microarray database of HGU-133 A&B chip data for discovery and a smaller HGU-133 Plus 2.0 microarray data set generated by us for validation.

The larger data set was analyzed to identify gene expression patterns, and the independently derived second expression set was used to validate these patterns. Thus, the first data set was mined for hypothesis generation, while the second set was used for hypothesis testing.

Discovery and validation data sets.
To construct the discovery set, 184 GeneChips hybridized to cRNA from nondiseased tissues meeting inclusion and quality assurance criteria were used for hypothesis generation. The tissues comprised segment subsets as follows: 29 cecum, 45 ascending, 13 descending, 54 sigmoid, and 43 rectum. For each tissue, 44,928 probe sets were background corrected and normalized using RMA preprocessing. The theoretical juncture between the proximal and distal colon is approximately two-thirds the length of the transverse colon measured from the hepatic flexure (3). As sample data were not specific for distance along the transverse colon, these tissues were excluded from the discovery analysis.

To construct the validation data set, 19 HG U133 Plus2.0 GeneChips were hybridized to labeled cRNA prepared from 8 proximal tissue specimens and 11 distal specimens from the hospital tissue bank. Due to stringent quality control parameters for tissue and GeneChip acceptability, this validation data set did not include sufficient tissues to explore multiple segment models. Each microarray measured transcript expression for 54,675 probe sets.

Gene Variation Along the Colon
Individual gene expression changes.
UNIVARIATE DIFFERENTIAL EXPRESSION. To explore the "natural" dividing point between the anatomical segments of the colon, we measured the absolute number of significant probe set expression differences by modified t-test when the hypothetical "divide" was moved stepwise from cecum to rectum. Figure 1 shows the number of probe sets that were differentially expressed for each intersegment divide. The maximum number of probe set differences, 206, occurs when the proximal and distal regions are divided between the ascending and descending segments. As this dividing point is consistent with both our understanding of embryonic development and the usual separation of the proximal and distal segments, the following comparison of proximal and distal tissues were based on this division.


Figure 1
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  		Fig. 1. Comparison of the number of differential probe sets when the divide between proximal and distal regions is moved between different segments: (C)ecum, (A)scending, (D)escending, (S)igmoid, (R)ectum.

 
A total of 206 probe sets, corresponding to ~154 known gene targets, were differentially expressed higher in the proximal or distal colorectal samples compared with the complementary region (Bonferroni corrected P < 0.05). Of these 206 probe sets, 31 (16.5%) were also differentially expressed in the validation data with a significant difference (31/206, P < 10–5 by Monte Carlo estimation).

To further explore differential expression in the discovery set, we identified those transcripts that were different between the most terminal ends of the large bowel. A total of 115 probe sets were differentially expressed between tissues selected only from the cecum (n = 29) and the rectum (n = 43); 102 (89%) of these probe sets were included in the 206 probe sets differing between proximal and distal colon described above. In this subset, 28 probe sets (24.3%) were likewise differentially expressed in the rectum vs. the cecum in the validation data (28/115, P < 10–5 by Monte Carlo estimation). All 28 of these consistent probe sets were included in the 31 consistent probe sets between the distal and proximal regions.

Differentially expressed probe sets and difference statistics for probe sets with elevated expression in proximal (94) and distal (126) tissues are shown in Tables 1 and 2, respectively.


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  		Table 1. List of genes differentially expressed higher in proximal tissues relative to distal tissues (P < 0.05)

 

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  		Table 2. List of probe sets differentially expressed lower in proximal tissues relative to distal tissues in the discovery set

 
MULTISEGMENT GENE EXPRESSION MODELS. An analysis for differential expression was also made for all five intersegment transitions in order from the cecum to the rectum (i.e., cecum vs. ascending, ascending vs. descending, etc.). No transcript was statistically differentially expressed between any two adjoining segments (moderated t-test, P < 0.05).

To explore the nature of these gene transcript expression changes, we built and compared robust linear models fitted to the expression data based on location for each tissue sample. Two robust linear models of univariate probe set expression were compared for each of the 115 probe sets differentially expressed between the two terminal segments of the large intestine, the cecum, and rectum. In particular, we queried whether the expression of those transcripts that were differentially expressed between these terminal segments were better explained (in terms of residual fit) by a simple two-segment model or by the more descriptive five-segment model.

Of the 115 differentially expressed probe sets, the analysis failed to reject the null hypothesis that a complex model does not significantly improve model fit to the observed gene expression data for 65 (57%) of cases (F-test, P > 0.05). Thus, more than half of these differentially expressed transcripts along the colon are satisfactorily modeled by the two-segment expression model whereby expression is dichotomous and defined by either proximal vs. distal location. The most differentially expressed probe set between the cecum and rectum is the transcript for PRAC. A comparison of the two-segment and multisegment models for this transcript is shown in Fig. 2, which is typical of other genes in this category (data not shown).


Figure 2
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  		Fig. 2. Typical example of the dichotomous model: PRAC illustrates the dichotomous/binary pattern that is the dominant pattern of transcript expression along proximal-distal axis of the colorectum. Shown in red is a 2-segment model, while the 5-segment model is shown in blue. Note: the tissue ordering within each segment is essentially random, and no further data are available regarding position within the segment.

 
For the remaining 50 (43%) probe sets, the null hypothesis was rejected (P < 0.05), which suggested that a five-factor model dependent on segment location in fact improves the predictive effectiveness of such transcripts' expression along the proximal-distal axis in a significant manner. Inspection of these models confirms that most probe set levels are monotonic-increasing or monotonic-decreasing in tissues progressing along the large intestine. Forty-one (82%) of the 50 multisegment models showed a gradual transcript level increase across the colon, while only nine models (18%) indicate a gradual decrease from proximal to distal expression. The model for homeobox gene B13 (HOXB13) is significantly improved with the five-segment model compared with the two-segment model as illustrated in Fig. 3.


Figure 3
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  		Fig. 3. HOXB13 illustrates the 2nd pattern that we observe along the proximal-distal axis: a gradual change from segment to segment, in this case increasing distally. Shown in red is a 2-segment model, while the 5-segment model is shown in blue. Note: the tissue ordering within each segment is essentially random, and no further data are available regarding position within the segment.

 
Patterns of gene expression along the colon.
In addition to analyses of individual gene changes along the colon, we used multivariate analytical techniques to explore patterns of gene changes along the proximal-distal axis.

PCA AND SUPERVISED PCA. We analyzed the full 44,928 probe sets of the discovery data set using PCA. The first two dimensions of this analysis are shown in Fig. 4A. Inspection of this low dimension perspective yields no obvious structure within the data that is consistent with tissue segment. This analysis suggests that the major sources of gene expression variation (i.e., the first two principal components) measured across all genes is not dependent on tissue location.


Figure 4
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  		Fig. 4. A: principal components analysis (PCA) using all probe sets shows that there is no discrimination between the proximal and distal tissues. However, in B, a supervised principal components plot using only those probe sets that are differential between the cecum and rectum demonstrates that the dominant source of variability in these probe sets is based on proximal vs. distal tissue location.

 
We also applied a supervised PCA to the data. Supervised PCA is similar to traditional principal components analysis but uses only a subset of the features/genes (usually selected by some univariate means) to derive the principal components. We used the set of genes differentially expressed between the cecum and rectum as described above. For this analysis, a reduced data matrix of all 184 normal tissues was constructed with just the top 115 probe sets differentially expressed between the cecum and rectum. PCA was then performed using this feature-specific data, and the 184 tissues were again visualized along just the first two principal components, shown in Fig. 4B. Inspection of Fig. 4B indicates that there are two broad populations within these tissues corresponding approximately to the proximal vs. distal divide. By reducing the dimensionality of this projection to just a single first component as shown in Fig. 5, A and B, the proximal vs. distal relationship became clear. There is strong overlap between the sigmoid colon and rectum segments distally and between the segments of cecum and ascending colon proximally.


Figure 5
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  		Fig. 5. A: box plot of each tissue's value for the 1st principal component (PC) using all probe sets on the GeneChip. B: the 1st PC value from supervised PCA probe sets using only probe sets that are differentially expressed between cecum and rectum. As with the data projections shown above, there is an obvious proximal vs. distal class structure.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
Map of Gene Differential Expression Along the Colon
Univariate expression analysis using conservative difference measures identified 206 probe sets (of 44,929) corresponding to ~154 unique gene targets that are differentially expressed between the normal proximal and normal distal large intestine regions in human adults. A subset of 115 probe sets (89% common to the proximal vs. distal list) is likewise differentially expressed between the terminal colorectal segments of the cecum and rectum. Interestingly, we found no transcripts that were expressed significantly differently between any two adjacent segments.

To estimate the validity of these findings, we have also measured the expression change of these gene transcripts in an independent set of microarray data. Thirty-one (31) of the 206 differentially expressed probe sets in our initial discovery data set of 184 colorectal tissue samples were also differentially expressed in the validation data of 19 specimens.

Nearly all (28/31, 90%) of these "validated" transcripts were likewise differentially expressed between the two terminal segments of the cecum and rectum.

Some of the gene transcripts that we describe herein were previously identified to be differentially expressed by microarray analysis using a variety of cDNA and oligonucleotide microarrays (7, 25, 33). Five of the gene targets of differential probe sets we found were previously identified in two or more of these earlier studies, including: HOXB13, NR1H4, S100P, SCNN1B, and SIAT4C. Each of these probe sets were also shown to be statistically different (i.e., HOXB13, SIAT4C: P < 0.065) in our validation data set. An additional 33 probe set target genes of the 206 probe sets we present here were previously identified to be differentially expressed along the colon in at least one of these earlier studies.

We identified an additional 28 probe sets that were differential in both our discovery data and our independent validation data but were not reported in the previous reports. In total, 57 of 154 (37%) gene targets corresponding to the 206 probe sets were confirmed to be differentially expressed between the proximal and distal from the validation set. The agreement of our work with earlier studies and with the independent validation set adds credibility to the results, especially given the potential for concern about microarray reproducibility between and within data collection platforms (39). Our analysis has also identified 28 new probe sets of relevance to mapping.

Differential Transcript Expression for Individual Genes
The most significantly differential probe set we observed in our discovery data was against the gene transcript for PRAC, previously described as specifically expressed in prostate, the distal colon and rectum (37). Our data agree with the earlier findings that the probe set for PRAC is highly expressed in the distal colon relative to the proximal tissues. This observation was confirmed by RT-PCR (Supplementary Figure), where essentially no expression was seen in proximal tissues. Furthermore, PRAC appears to be expressed in a low-high pattern along the colon with a sharp expression change occurring between the ascending and descending colorectal specimens.

We found eight probe sets corresponding to seven HOX genes to be differentially expressed between the proximal and distal colon. The 39 members of the mammalian homeobox gene family consist of highly conserved transcription factors that specify the identity of body segments along the anterior-posterior axis of the developing embryo (27, 35). The four groups of HOX gene paralogs are expressed in an anterior-to-posterior sequence, for e.g., from HOXA1 to HOXB13 (40). The expression patterns in our data for these eight probe sets are consistent with the expected pattern: lower numbered HOX genes are expressed higher in the proximal tissues (HOXD3, HOXD4, HOXB6, HOXC6, and HOXA9), while the higher named genes are more expressed in the distal colon (HOXB13 and HOXD13). Elevated expression of HOXB13 in the distal colon was confirmed by RT-PCR (Supplementary Figure). These results are also consistent with examples of specific HOX expression in the literature, such as studies that demonstrate HOXD13 involvement in the development of the anal sphincter in mice (34).

We also report, however, the conspicuous absence in our findings of some gene transcripts that have been previously shown to be differentially expressed along the proximal-distal axis. Our data do not demonstrate a significant expression gradient for the caudal homeobox genes CDX1 or CDX2, transcription factors that have been shown to be involved in intestine pattern development across a range of vertebrates (13, 31, 45). In particular, CDX2 is considered to play a role in maintaining the colonic phenotype in the adult colon and was shown to be present at relatively high concentrations in the proximal colon but absent in the distal colon (31, 45). Neither statistical analysis nor visual inspection of probe set expression for this gene suggests differential expression along the colon in our data (data not shown). Analysis by RT-PCR of a subset of RNA samples from the validation set supported the array data in that expression of CDX2 in the distal colon was equivalent to or greater than in proximal samples (Supplementary Figure).

We observed significant differential transcript expression for a number of the solute-carrier transport genes that can be rationalized based on our current understanding of colorectal physiology. While probe set expression for SLC2A10, SLC13A2, and SLC28A2 is higher in the distal colon, the solute carrier family members SLC9A3, SLC14A2, SLC16A1, SLC20A1, SCL23A3, and SLC37A2 are higher in the proximal tissues. These data support the findings of Glebov et al. (25), including for the Na-dependent dicarboxylic acid transporter member 2 (SLC13A2), which is expressed higher distally, and for the monocarboxylic acid transporter family member 1 (SLC16A1, alias MCT1), which is higher in the proximal tissues. This expression of SLC16A1/MCT1 is consistent with evidence that the short chain fatty acid butyrate, which is most abundant in the proximal gut (38), may regulate SLC16A1/MCT1 expression by both transcriptional control and by transcript stabilization (16).

Our results show that probe sets against all three of the five members of the chromosome 7q22 cluster of membrane-bound mucins previously believed to be expressed in colon, MUC11, MUC12, and MUC17, are differentially expressed at higher levels in the distal gut (10, 49, 26). We also confirmed this differential expression pattern for MUC12 and MUC17 in the independent validation data. Previous reports have raised the question about whether the genomic sequences for MUC11 and MUC12 are from closely related or perhaps even the same gene (10). Correlation analysis of MUC11 and MUC12 probe sets show a strong, positive correlation at the lower end of the probe set expression range with a weaker correlation as expression increases (data not shown). This correlation profile could be due to increased variability at higher expression levels or, possibly, because the expression levels in the distal colon (where they are higher) reflect a distinct transcriptional control. Differences in mucin glycoprotein characteristics between the proximal and distal gut, including the degree of sulfation, were demonstrated 30 years ago (5, 20).

In addition, while previous research has suggested that the secreted, gel-forming mucin MUC5B is only weakly expressed in the colon (10), our results show that probe sets reactive to this transcript are expressed higher in the distal colon as for the membrane-bound mucins. Our data also support earlier reports that transcripts for the estrogen responsive element known as trefoil factor 1 (TFF1, alias pS2) is differentially expressed higher in the distal colon (46).

Many of the expression patterns we report here for humans have been shown to be similarly patterned in the gastrointestinal tracts of rodent models. However, a number of specific genes previously shown to be differentially expressed along the large intestines of mice and rats were not found to be so expressed by us. Such gene transcript targets include solute carrier family 4 member 1 (alias AE1) (44) and Toll-like receptor 4 (TLR4) (41). For TLR4 no significant difference in expression between proximal and distal human samples was seen by RT-PCR in agreement with the microarray data (Supplementary Figure). Using a commercially available RT-PCR assay we were unable to detect SLC4A1 mRNA in any of our validation set including, carbonic anhydrase IV (21). On the other hand, our data are in agreement with earlier studies of expression of aquaporin-8 (AQP8), a gene whose expression product is suspected to be involved in water absorption in the normal rat colon (11). We observe that AQP8 is significantly expressed to a higher level in the proximal human colon compared with the distal tissues (P < 0.006, data not shown).

The family of claudin tight junction proteins may also play a role in maintaining the water barrier integrity in the colon (32). We found claudin-8 (CLDN8) is more highly expressed in the distal colorectal tissues and this observation was supported by RT-PCR analysis (Supplementary Figure). Conversely, claudin-15 (CLDN15), which is also believed to be localized in the tight junction fibrils was expressed at a higher level in the proximal colorectal tissues (15).

Nature of Gene Expression Change Along the Colon
While one goal of this work was to understand which gene transcripts are differentially expressed along the colon, a second aim was to explore the nature of these expression changes along the proximal-distal axis in region or segment-specific detail.

We observed two broad patterns of statistically significant transcript expression change along the colorectum. The major pattern is described by those 65 probe sets that were well fitted by a two-segment expression model. We suggest that the expression of these transcripts is dichotomous in nature: elevated in the proximal segments and decreased in distal segments, or vice-versa.

Such data are consistent with the conventional anatomical view that the "natural" divide between the proximal and distal colon occurs between the ascending and descending colon. This finding is contrary to a recent report by Komuro et al. (33) that a breakpoint between the descending and sigmoid colon yields the largest differential expression. However, we note that in addition to analyzing this pattern in colorectal cancer specimens (we used nondiseased tissues only), Komuro et al. also chose to include the transverse colon in their analysis. We intentionally exclude tissues from that segment to avoid the possible confounding affect related to the predicted midgut-hindgut junction point approximately two-thirds the length of the transverse colon.

A second set of 50 probe sets does not display a dichotomous change but rather shows a significant improvement in fit when the expression data were applied to a five-segment model supporting a more gradual expression gradient moving along the colon from the cecum to the rectum.

These two characteristic expression patterns hint that gene expression along the proximal-distal axis is perhaps coordinated by two underlying systems of organization.

The majority of differentially expressed transcripts in the adult normal tissues measured here are expressed in a pattern that is consistent with a midgut vs. hindgut pattern of embryonic development. Furthermore, multivariate methods including supervised PCA and canonical variate analysis (data not shown) also suggest that the primary source of variation among these data is explained by the proximal vs. distal divide. In a recent study Glebov et al. (25) found that the number of genes differentially expressed between the ascending and descending colon in the adult is substantially larger than the number of genes likewise identified in 17- to 24-wk-old fetal colons. Glebov et al. hypothesize that the gene expression pattern of the adult colon is possibly set concurrently with expression of the adult colonic phenotype at ~30 wk gestation or perhaps even in response to postnatal luminal contents of the gastrointestinal tract. While we did not explore gene expression in the fetal colon, we observe patterns of expression in the adult that support a proximal-distal expression model consistent with the midgut-hindgut embryonic origins.

Most (41 of 50) of those transcripts that exhibit a gradual expression change between the cecum and rectum exhibit a prototypical pattern of increased expression increasing from the cecum to the rectum. This pattern is not observed in the midgut-hindgut differential transcripts where the number of transcripts elevated proximally is approximately equal to the number elevated in the distal region. We propose that the characteristic distally increasing pattern in those transcripts could be a function of extrinsic factors compared with the intrinsically defined midgut-hindgut pattern. Such factors could include the effect of luminal contents that move in a unidirectional manner from the cecum to the rectum and/or the regional changes in microflora along the large intestine. Further work will be required to investigate whether such extrinsic controls are working in a positive manner of inducing transcriptional activity or through a reduced transcriptional silencing.

Gene Expression Changes in Concert Along the Colon
To explore the expression of genes in concert along the colon, we also apply PCA to these expression data. There is strong evidence for a proximal vs. distal gene expression pattern with these multivariate visualization techniques. Though multivariate results do not exclude a subtle proximal-distal gradient, the apparent bimodal nature of the multivariate plots suggests that the major source of expression variation in these tissues is consistent with a midgut- vs. hindgut-derived pattern.

Conclusions
Our work indicates that transcript abundance, and perhaps transcriptional regulation, follows two broad patterns along the proximal-distal axis of the large intestine. The dominant pattern is a dichotomous expression pattern consistent with the midgut-hindgut embryonic origins of the proximal and distal gut. Transcripts that follow this pattern are roughly equally split into those that are elevated distally and those elevated proximally. The second pattern we observe is characterized by a gradual change in transcript levels from the cecum to the rectum, nearly all of which exhibit increasing expression toward the distal tissues. We propose that tissues that exhibit the dichotomous midgut-hindgut patterns are likely to reflect the intrinsic embryonic origins of the large intestine while those that exhibit a gradual change reflect extrinsic factors such as luminal flow and microflora changes. Taken together, these patterns constitute a gene expression map of the large intestine. This is the first such map of an entire human organ.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
L. C. LaPointe is grateful for financial support from an Enterix Research Scholarship from Enterix Pty. Ltd.


   ACKNOWLEDGMENTS
 
We thank Thu Ho for assistance with tissue RNA extraction and microarray analysis. We also thank Glenn Stone for statistical advice related to model comparisons. We are grateful to David Mitchell, Trevor Lockett, and Howard Chandler for reading earlier versions of this manuscript and for providing helpful comments.


   FOOTNOTES
 
Address for reprint requests and other correspondence: L. C. LaPointe, 11 Julius Ave., Riverside Life Sciences Bldg., North Ryde, NSW 2113 Australia (e-mail: larry.lapointe{at}flinders.edu.au).

Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

1 The online version of this article contains supplemental material. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

  1. Affymetrix. GeneChip Expression Analysis Data Analysis Fundamentals. Santa Clara, CA: Affymetrix Inc., 2001.
  2. Affymetrix. Gene Expression Analysis: Technical Manual. Santa Clara, CA: Affymetrix Inc., 2004.
  3. Babyatsky MW, Podolsky DK. Growth and Development of the Gastrointestinal Tract. In: Textbook of Gastroenterology (4th ed.), edited by Yamada T, Alpers DH, Kaplowitz N, Laine L, Owyang C, and Powell DW. Philadelphia, PA: Lippincott Williams & Wilkins, 2003, p. 521–556.
  4. Bair E, Hastie T, Debashis P, Tibshirani R. Prediction by supervised principal components. J Am Statistical Assoc 101: 119–137, 2006.[CrossRef][Web of Science]
  5. Bara J, Nardelli J, Gadenne C, Prade M, Burtin P. Differences in the expression of mucus-associated antigens between proximal and distal human colon adenocarcinomas. Br J Cancer 49: 495–501, 1984.[Web of Science][Medline]
  6. Bates MD, Erwin CR, Sanford LP, Wiginton D, Bezerra JA, Schatzman LC, Jegga AG, Ley-Ebert C, Williams SS, Steinbrecher KA, Warner BW, Cohen MB, Aronow BJ. Novel genes and functional relationships in the adult mouse gastrointestinal tract identified by microarray analysis. Gastroenterology 122: 1467–1482, 2002.[CrossRef][Web of Science][Medline]
  7. Birkenkamp-Demtroder K, Olesen SH, Sorensen FB, Laurberg S, Laiho P, Aaltonen LA, Orntoft TF. Differential gene expression in colon cancer of the caecum versus the sigmoid and rectosigmoid. Gut 54: 374–384, 2005.[Abstract/Free Full Text]
  8. Bonithon-Kopp C, Benhamiche AM. Are there several colorectal cancers? Epidemiological data. Eur J Cancer Prev 8, Suppl 1: S3–S12, 1999.[CrossRef][Web of Science][Medline]
  9. Bufill JA. Colorectal cancer: evidence for distinct genetic categories based on proximal or distal tumor location. Ann Intern Med 113: 779–788, 1990.[Abstract/Free Full Text]
  10. Byrd JC, Bresalier RS. Mucins and mucin binding proteins in colorectal cancer. Cancer Metastasis Rev 23: 77–99, 2004.[CrossRef][Web of Science][Medline]
  11. Calamita G, Mazzone A, Bizzoca A, Cavalier A, Cassano G, Thomas D, Svelto M. Expression and immunolocalization of the aquaporin-8 water channel in rat gastrointestinal tract. Eur J Cell Biol 80: 711–719, 2001.[CrossRef][Web of Science][Medline]
  12. Caldero J, Campo E, Ascaso C, Ramos J, Panades MJ, Rene JM. Regional distribution of glycoconjugates in normal, transitional and neoplastic human colonic mucosa. A histochemical study using lectins. Virchows Arch A Pathol Anat Histopathol 415: 347–356, 1989.[CrossRef][Web of Science][Medline]
  13. Chalmers AD, Slack JM, Beck CW. Regional gene expression in the epithelia of the Xenopus tadpole gut. Mech Dev 96: 125–128, 2000.[CrossRef][Web of Science][Medline]
  14. Chen M, Yang Y, Braunstein E, Georgeson KE, Harmon CM. Gut expression and regulation of FAT/CD36: possible role in fatty acid transport in rat enterocytes. Am J Physiol Endocrinol Metab 281: E916–E923, 2001.[Abstract/Free Full Text]
  15. Colegio OR, Van Itallie CM, McCrea HJ, Rahner C, Anderson JM. Claudins create charge-selective channels in the paracellular pathway between epithelial cells. Am J Physiol Cell Physiol 283: C142–C147, 2002.[Abstract/Free Full Text]
  16. Cuff MA, Lambert DW, Shirazi-Beechey SP. Substrate-induced regulation of the human colonic monocarboxylate transporter, MCT1. J Physiol 539: 361–371, 2002.[Abstract/Free Full Text]
  17. De Santa Barbara P, van den Brink GR, Roberts DJ. Development and differentiation of the intestinal epithelium. Cell Mol Life Sci 60: 1322–1332, 2003.[CrossRef][Web of Science][Medline]
  18. Deng G, Peng E, Gum J, Terdiman J, Sleisenger M, Kim YS. Methylation of hMLH1 promoter correlates with the gene silencing with a region-specific manner in colorectal cancer. Br J Cancer 86: 574–579, 2002.[CrossRef][Web of Science][Medline]
  19. Distler P, Holt PR. Are right- and left-sided colon neoplasms distinct tumors? Dig Dis 15: 302–311, 1997.[Web of Science][Medline]
  20. Filipe MI, Branfoot AC. Mucin histochemistry of the colon. Curr Top Pathol 63: 143–178, 1976.[Medline]
  21. Fleming RE, Parkkila S, Parkkila AK, Rajaniemi H, Waheed A, Sly WS. Carbonic anhydrase IV expression in rat and human gastrointestinal tract regional, cellular, and subcellular localization. J Clin Invest 96: 2907–2913, 1995.[Web of Science][Medline]
  22. Garcia-Hirschfeld J, Blanes Berenguel A, Vicioso Recio L, Marquez Moreno A, Rubio Garrido J, Matilla Vicente A. Colon cancer: p53 expression and DNA ploidy: their relation to proximal or distal tumor site. Rev Esp Enferm Dig 91: 481–488, 1999.[Medline]
  23. Gautier L, Cope L, Bolstad BM, Irizarry RA. Affy–analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20: 307–315, 2004.[Abstract/Free Full Text]
  24. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5: R80, 2004.[CrossRef][Medline]
  25. Glebov OK, Rodriguez LM, Nakahara K, Jenkins J, Cliatt J, Humbyrd CJ, DeNobile J, Soballe P, Simon R, Wright G, Lynch P, Patterson S, Lynch H, Gallinger S, Buchbinder A, Gordon G, Hawk E, Kirsch IR. Distinguishing right from left colon by the pattern of gene expression. Cancer Epidemiol Biomarkers Prev 12: 755–762, 2003.[Abstract/Free Full Text]
  26. Gum JRJ, Crawley SC, Hicks JW, Szymkowski DE, Kim YS. MUC17, a novel membrane-tethered mucin. Biochem Biophys Res Commun 291: 466–475, 2002.[CrossRef][Web of Science][Medline]
  27. Hostikka SL, Capecchi MR. The mouse Hoxc11 gene: genomic structure and expression pattern. Mech Dev 70: 133–145, 1998.[CrossRef][Web of Science][Medline]
  28. Hubbell E, Liu WM, Mei R. Robust estimators for expression analysis. Bioinformatics 18: 1585–1592, 2002.[Abstract/Free Full Text]
  29. Iacopetta B. Are there two sides to colorectal cancer? Int J Cancer 101: 403–408, 2002.[CrossRef][Web of Science][Medline]
  30. Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15, 2003.
  31. James R, Erler T, Kazenwadel J. Structure of the murine homeobox gene cdx-2. Expression in embryonic and adult intestinal epithelium. J Biol Chem 269: 15229–15237, 1994.[Abstract/Free Full Text]
  32. Jeansonne B, Lu Q, Goodenough DA, Chen YH. Claudin-8 interacts with multi-PDZ domain protein 1 (MUPP1) and reduces paracellular conductance in epithelial cells. Cell Mol Biol (Noisy-le-grand) 49: 13–21, 2003.[Web of Science][Medline]
  33. Komuro K, Tada M, Tamoto E, Kawakami A, Matsunaga A, Teramoto K, Shindoh G, Takada M, Murakawa K, Kanai M, Kobayashi N, Fujiwara Y, Nishimura N, Hamada J, Ishizu A, Ikeda H, Kondo S, Katoh H, Moriuchi T, Yoshiki T. Right- and left-sided colorectal cancers display distinct expression profiles and the anatomical stratification allows a high accuracy prediction of lymph node metastasis. J Surg Res 124: 216–224, 2005.[CrossRef][Web of Science][Medline]
  34. Kondo T, Dolle P, Zakany J, Duboule D. Function of posterior HoxD genes in the morphogenesis of the anal sphincter. Development 122: 2651–2659, 1996.[Abstract]
  35. Kosaki K, Kosaki R, Suzuki T, Yoshihashi H, Takahashi T, Sasaki K, Tomita M, McGinnis W, Matsuo N. Complete mutation analysis panel of the 39 human HOX genes. Teratology 65: 50–62, 2002.[CrossRef][Web of Science][Medline]
  36. Lipshutz RJ, Fodor SP, Gingeras TR, Lockhart DJ. High density synthetic oligonucleotide arrays. Nat Genet 21: 20–24, 1999.[CrossRef][Web of Science][Medline]
  37. Liu XF, Olsson P, Wolfgang CD, Bera TK, Duray P, Lee B, Pastan I. PRAC: a novel small nuclear protein that is specifically expressed in human prostate and colon. Prostate 47: 125–131, 2001.[CrossRef][Web of Science][Medline]
  38. Macfarlane GT, Gibson GR, Cummings JH. Comparison of fermentation reactions in different regions of the human colon. J Appl Bacteriol 72: 57–64, 1992.[Medline]
  39. Miklos GL, Maleszka R. Microarray reality checks in the context of a complex disease. Nat Biotechnol 22: 615–621, 2004.[CrossRef][Web of Science][Medline]
  40. Montgomery RK, Mulberg AE, Grand RJ. Development of the human gastrointestinal tract: twenty years of progress. Gastroenterology 116: 702–731, 1999.[CrossRef][Web of Science][Medline]
  41. Ortega-Cava CF, Ishihara S, Rumi MA, Kawashima K, Ishimura N, Kazumori H, Udagawa J, Kadowaki Y, Kinoshita Y. Strategic compartmentalization of Toll-like receptor 4 in the mouse gut. J Immunol 170: 3977–3985, 2003.[Abstract/Free Full Text]
  42. Park YK, Franklin JL, Settle SH, Levy SE, Chung E, Jeyakumar LH, Shyr Y, Washington MK, Whitehead RH, Aronow BJ, Coffey RJ. Gene expression profile analysis of mouse colon embryonic development. Genesis 41: 1–12, 2005.[CrossRef][Web of Science][Medline]
  43. Peifer M. Developmental biology: colon construction. Nature 420: 274–277, 2002.[CrossRef][Medline]
  44. Rajendran VM, Black J, Ardito TA, Sangan P, Alper SL, Schweinfest C, Kashgarian M, Binder HJ. Regulation of DRA and AE1 in rat colon by dietary Na depletion. Am J Physiol Gastrointest Liver Physiol 279: G931–G942, 2000.[Abstract/Free Full Text]
  45. Silberg DG, Swain GP, Suh ER, Traber PG. Cdx1 and cdx2 expression during intestinal development. Gastroenterology 119: 961–971, 2000.[CrossRef][Web of Science][Medline]
  46. Singh S, Poulsom R, Hanby AM, Rogers LA, Wright NA, Sheppard MC, Langman MJ. Expression of oestrogen receptor and oestrogen-inducible genes pS2 and ERD5 in large bowel mucosa and cancer. J Pathol 184: 153–160, 1998.[CrossRef][Web of Science][Medline]
  47. Smyth G. Limma: linear models for microarray data. In: Bioinformatics and Computational Biology Solutions using R and Bioconductor, edited by Gentleman R, Carey V, Dudoit S, Irizarray R, and Huber W. New York: Springer, 2005, p. 397–420.
  48. Traber PG. Transcriptional regulation in intestinal development. Implications for colorectal cancer. Adv Exp Med Biol 470: 1–14, 1999.[Web of Science][Medline]
  49. Williams SJ, McGuckin MA, Gotley DC, Eyre HJ, Sutherland GR, Antalis TM. Two novel mucin genes down-regulated in colorectal cancer identified by differential display. Cancer Res 59: 4083–4089, 1999.[Abstract/Free Full Text]
  50. Wilson C, Miller CJ. Simpleaffy: a BioConductor package for Affymetrix quality control and data analysis. Bioinformatics 21: 3283–3685, 2005.




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