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Results for “Expression profiling”

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PubMed2006

High-throughput genomic technology in research and clinical management of breast cancer. Exploiting the potential of gene expression profiling: is it ready for the clinic?

Gene expression profiling is a relatively new technology for the study of breast cancers, but within the past few years there has been a rapid rise in interest in its potential to improve the clinical management of breast cancer. This technology has contributed to our knowledge of the molecular pathology of breast tumours and shows promise as a tool to predict response to therapy and outcome, such as risk of metastasis. Microarray technology is continually developing and it is becoming apparent that, despite the various platforms available, robust conclusions can still be drawn that apply across the different array types. Gene expression profiling is beginning to appear in the breast cancer clinic but it is not yet fully evaluated. This review explores the questions that must be addressed before this technology can become an everyday clinical tool.

Breast Neoplasms↗

PubMed2007

Differential expression profile of MAGE family in non-small-cell lung cancer.

The expression of the melanoma-associated antigen (MAGE) genes consists of variables in all tumor types, such as lung cancer, which are relevant to be silent in all normal tissues except germ cells. They are considered as tumor-specific antigens, and are ideal targets for cancer immunotherapy. A complete MAGE genes differential expression profile analysis of lung cancer can provide this study not only various target genes for immunotherapy, but also valuable markers for further diagnosis and prognosis. This research has constructed a membrane array, which was consisted 32 MAGE genes, to detect whether the differential expression profile occurred in 52 pairs of non-small-cell lung cancer (NSCLC) samples. Nearly 32 MAGE genes have been differential expressed in NSCLC except MAGE-B1 and -E2. MAGE-B, -C, -D, and subgroup -B6, -D4 have showed prominences in lung adenocarcinoma. High-frequent expression of MAGE-D, and subgroup -A2, -D2 has also been discovered in non-metastasis group (p<0.05). However, there is no significant difference of MAGE genes differential expression shown among different primary tumor (T), nodal involvement (N) and overall stages. Several MAGE subgroup genes, such as MAGE-A5, -A7, -A8, -A9, -A11, -B3, -B4, -B10, -D2, -D3, -F1, -G1, -H1, and -L2, have been first discovered to show differential expression in NSCLC. Although the small size of the sample may limit the diagnostic and prognostic value of MAGE genes, the function of the membrane array can provide this study a high-throughput method to detect the whole MAGE genes differential expression profile.

Antigens, Neoplasm↗

PubMed2024

Identification of miRNA expression profile in middle ear cholesteatoma using small RNA-sequencing.

BACKGROUND: The present study aims to identify the differential miRNA expression profile in middle ear cholesteatoma and explore their potential roles in its pathogenesis. METHODS: Cholesteatoma and matched normal retroauricular skin tissue samples were collected from patients diagnosed with acquired middle ear cholesteatoma. The miRNA expression profiling was performed using small RNA sequencing, which further validated by quantitative real-time PCR (qRT-PCR). Target genes of differentially expressed miRNAs in cholesteatoma were predicted. The interaction network of 5 most significantly differentially expressed miRNAs was visualized using Cytoscape. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were processed to investigate the biological functions of miRNAs in cholesteatoma. RESULTS: The miRNA expression profile revealed 121 significantly differentially expressed miRNAs in cholesteatoma compared to normal skin tissues, with 56 upregulated and 65 downregulated. GO and KEGG pathway enrichment analyses suggested their significant roles in the pathogenesis of cholesteatoma. The interaction network of the the 2 most upregulated (hsa-miR-21-5p and hsa-miR-142-5p) and 3 most downregulated (hsa-miR-508-3p, hsa-miR-509-3p and hsa-miR-211-5p) miRNAs identified TGFBR2, MBNL1, and NFAT5 as potential key target genes in middle ear cholesteatoma. CONCLUSIONS: This study provides a comprehensive miRNA expression profile in middle ear cholesteatoma, which may aid in identifying therapeutic targets for its management.

Humans↗

PubMed2004

Expression profiling of murine acute promyelocytic leukemia cells reveals multiple model-dependent progression signatures.

Leukemia results from the expansion of self-renewing hematopoietic cells that are thought to contain mutations that contribute to disease initiation and progression. Studies of the gene expression profiles of human acute myeloid leukemia samples has allowed their classification based on the presence of translocations and French-American-British subtypes, but it is not yet clear whether their molecular signatures reflect the initiating mutations or mutations acquired during progression. To begin to address this question, we examined the expression profiles of normal murine promyelocyte-enriched samples, nontransformed murine promyelocytes expressing human promyelocytic leukemia-retinoic acid receptor alpha (PML-RARalpha) fusion gene, and primary acute promyelocytic leukemia cells. The expression profile of nontransformed cells expressing PML-RARalpha was remarkably similar to that of wild-type promyelocytes. In contrast, the expression profiles of fully transformed cells from three acute promyelocytic leukemia model systems were all different, suggesting that the expression signature of acute promyelocytic leukemia cells reflects the genetic changes that contributed to progression. To further evaluate these progression events, we compared two high-penetrance acute promyelocytic leukemia models that both commonly acquire an interstitial deletion of chromosome 2 during progression. The two models exhibited distinct gene expression profiles, suggesting that the dominant molecular signatures of murine acute promyelocytic leukemia can be influenced by several independent progression events.

Animals↗

PubMed2002

cDNA arrays: gene expression profiles of Hodgkin's disease and anaplastic large cell lymphoma cell lines.

cDNA arrays are a powerful tool for the identification of differentially expressed genes in malignant tumors. We used this technique to study the gene expression profiles of anaplastic large cell lymphoma (ALCL) and Hodgkin's disease (HD). Gene expression of 11 lymphoma cell lines was analyzed covering 1176 cDNA sequences. Comparing these data to the expression profiles of B- and T-lymphocytes, we identified 27 genes that were deregulated in all cell lines or in a particular entity. For the establishment of gene expression profiles the 27 genes were assigned to four groups composed of genes deregulated in (i) all lymphoma cell lines, (ii) ALCL and HD, (iii) only HD, and (iv) ALCL exclusively. Our results indicate that ALCL and HD share the differential expression of at least five genes. In addition, both entities are characterized by the differentially deregulated expression of four genes in HD and seven genes in ALCL. Because the expression profiling was performed on cell lines, further studies are needed to clarify the biological significance of the differentially expressed genes.

B-Lymphocytes↗

PubMed2004

[Molecular classification in leukemias using gene expression profiling].

A comprehensive approach to the diagnosis in leukemias relies on cytomorphology, cytochemistry, cytogenetics, fluorescence in situ hybridization, multiparameter flow cytometry, and molecular methods. Recently, gene expression profiling using microarrays was invented to measure the expression of thousands of genes in one step. A specific signature stands for the molecular fingerprint of a tumor sample. Therefore, gene expression profiling may lead to a better molecular classification of leukemias and insights into pathophysiology. Furthermore, gene expression profiling may lead to new targeted therapies and can detect genes to be used for minimal residual disease studies. Very recent studies point also to the possibility to use gene expression profiling for prognostication. In conclusion, microarrays may lead to a single platform approach in leukemia diagnosis with quick and very robust results. This new technique should be further validated in parallel to the standard work-flow and has to be proven before substituting other methods in the future.

Algorithms↗

PubMed2003

[Infection of Coxsackievirus group B type 3 regulates the expression profile of chemokines in myocardial tissue/cells].

OBJECTIVE: To investigate the role of Coxsackievirus group B type 3 (CVB3) infection on the expression profile of chemokines (ChKs) in myocardial tissue/cells. METHODS: CVB3 was inoculated into male BALB/c intraperitoneally and primary neonatal myocardial cells of BALB/c to establish CVB3 infection models in vivo and in vitro, where the expression profile of ChKs was detected at different time points post-infection as well as under different loading of CVB3 qualitatively and quantitatively by RT-PCR. RESULTS: The expression of MIP-2 and IP-10 was induced post-infection, while SDF-1, MCP-1, MCP-2, MCP-3, MCP-5, MDC, FKN and Ltn were constitutively expressed in myocardial tissue. The expression of MCP-1, MCP-2, MCP-3, MCP-5, MDC and Ltn increased 1.8, 1.9, 3.7, 1.7, 1.3 and 1.2 folds post-infection higher than that of uninfected control (P < 0.01). There was not significant difference in the expression of SDF-1 and FKN between infected myocardial tissue and uninfected myocardial tissue (P > 0.05). The expression of Eot was not detected in infected and uninfected myocardial tissue. Every chemokine had different expression at different infection time points. For example, the expression of MIP-2 at the 4th day was 1.1 and 1.5 times than that of the 7th and 14th day (P < 0.01). IP-10 showed similar expression between the 4th and 7th days (P > 0.05), which is 2.47 and 2.54 times compared to that of the 9th day (P < 0.01). And the expression of MCP-1 at the 14th day post-infection was 1.3, 1.2 and 1.0 times comparing to that of the 4th, 7th, 9th day post-infection, which showed statistical meaning. The expression of MCP-2 at the 4th was 1.4, 1.5 and 2.2 times comparing to that of the 7th, 9th, 14th day, and moreover, the expression was lower than that of the basal expression. The expression of MCP-1 and MCP-3 was up-regulated significantly, which occurred at different time points post-infection in vitro. While the expression of MIP-2 and MCP-5 was down-regulated in vitro. The expression patterns of MCP-2, MCP-3, MCP-5 and MDC were consistent with CVB3 loading. But that of the others (FKN, SDF-1, et al) were inconsistent with CVB3 loading. There was a correlation between change patterns of MCP-3 and CVB3 loading post-infection (r = 0.881, P < 0.05) within 14 days after infection. The varied expression trend of MCP-1 and MCP-3 was similar to the titer of anti-CVB3 antibody (r = 0.913, P = 0.031), while the expression of MCP-2, MCP-5 and MDC shows contrary change. There was not a significant correlation between change patterns of other ChKs (IP-10, SDF-1, et al) and the titer of anti-CVB3 antibody. A positive correlation between anti-CVB3 antibody and MCP-1 (r = 0.976, P < 0.05) was showed. CONCLUSION: The expression level and kind of ChKs in vivo and in vitro was varied significantly in clusters after CVB3 infection. The ChKs changed in clusters consisted of the expression profiles of ChKs. There were complexity and unbalance in the change of the expression of ChKs in every expression profile. It suggested that CVB3 infection could regulate the expression of ChKs in myocardial tissue/cells likely in different ways.

Animals↗

PubMed2006

Expression profiling of clonal lymphocyte cell cultures from Rett syndrome patients.

BACKGROUND: More than 85% of Rett syndrome (RTT) patients have heterozygous mutations in the X-linked MECP2 gene which encodes methyl-CpG-binding protein 2, a transcriptional repressor that binds methylated CpG sites. Because MECP2 is subject to X chromosome inactivation (XCI), girls with RTT express either the wild type or mutant MECP2 in each of their cells. To test the hypothesis that MECP2 mutations result in genome-wide transcriptional deregulation and identify its target genes in a system that circumvents the functional mosaicism resulting from XCI, we performed gene expression profiling of pure populations of untransformed T-lymphocytes that express either a mutant or a wild-type allele. METHODS: Single T lymphocytes from a patient with a c.473C>T (p.T158M) mutation and one with a c.1308-1309delTC mutation were subcloned and subjected to short term culture. Gene expression profiles of wild-type and mutant clones were compared by oligonucleotide expression microarray analysis. RESULTS: Expression profiling yielded 44 upregulated genes and 77 downregulated genes. We compared this gene list with expression profiles of independent microarray experiments in cells and tissues of RTT patients and mouse models with Mecp2 mutations. These comparisons identified a candidate MeCP2 target gene, SPOCK1, downregulated in two independent microarray experiments, but its expression was not altered by quantitative RT-PCR analysis on brain tissues from a RTT mouse model. CONCLUSION: Initial expression profiling from T-cell clones of RTT patients identified a list of potential MeCP2 target genes. Further detailed analysis and comparison to independent microarray experiments did not confirm significantly altered expression of most candidate genes. These results are consistent with other reported data.

Animals↗

PubMed2005

Application of restriction fragment differential display-polymerase chain reaction in study on differential expression profiles of human diseases.

OBJECTIVE: To establish the restriction fragment differential display-polymerase chain reaction (RFDD-PCR) as an efficient technique for constructing and studying the gene expression profile of human tissues. METHODS: The tissues of mamma adenocarcinoma (T), cancerometastasis lymph node (L) and normal mammary (N) from one mammary infiltrating ductal carcinoma case were collected, and the gene expression profile of each kind of tissue was constructed using RFDD-PCR technique at equal pace according to the operating manual of Qbio-gene Company. Then all fragments of the three gene expression profiles were separated and displayed by electrophoresis. With the use of gene database at the website http://www.Qbio-gene.com/display, the authors identified the names of the probable fragments by bioinformatics analysis. Through comparison of the three profiles, the numbers and types of most differentially expressed gene fragments were displayed. RESULTS: The expression profiles of the three kinds of tissue have been constructed covering 1716 fragments of mammary adenocarcinoma, 1769 of cancerometastasis lymph nodes and 1922 of normal mammary tissue. Among these 5407 fragments, 39.39% were exactly the same. While 33.9% sequences of T and L showed differences in abundance or presence, 40.9% of T and N and 39.6% fragments of L and N were observed differentially expressed. These differentially expressed gene fragments were found to relate with metastasis, differentiation, inflammation and so on. CONCLUSION: RFDD-PCR is an efficient technique for research in human diseases genomics as a mass screening for complete gene expression profile with high-flux. Through comparison among three or more profiles, the screening for candidate genes of a certain disease can be accomplished, and there is probably a chance to identify novel gene or expressed sequence tag.

Adenocarcinoma↗

PubMed2001

Gene expression profiles in Ciona intestinalis tailbud embryos.

A set of 3423 expressed sequence tags derived from the Ciona intestinalis tailbud embryos was categorized into 1213 independent clusters. When compared with DNA Data Bank of Japan database, 502 clusters of them showed significant matches to reported proteins with distinct function, whereas 184 lacked sufficient information to be categorized (including reported proteins with undefined function) and 527 had no significant similarities to known proteins. Sequence similarity analyses of the 502 clusters in relation to the biosynthetic function, as well as the structure of the message population at this stage, demonstrated that 390 of them were associated with functions that many kinds of cells use, 85 with cell-cell communication and 27 with transcription factors and other gene regulatory proteins. All of the 1213 clusters were subjected to whole-mount in situ hybridization to analyze the gene expression profiles at this stage. A total of 387 clusters showed expression specific to a certain tissue or organ; 149 showed epidermis-specific expression; 34 were specific to the nervous system; 29 to endoderm; 112 to mesenchyme; 32 to notochord; and 31 to muscle. Many genes were also specifically expressed in multiple tissues. The study also highlighted characteristic gene expression profiles dependent on the tissues. In addition, several genes showed intriguing expression patterns that have not been reported previously; for example, four genes were expressed specifically in the nerve cord cells and one gene was expressed only in the posterior part of muscle cells. This study provides molecular markers for each of the tissues and/or organs that constitutes the Ciona tailbud embryo. The sequence information will also be used for further genome scientific approach to explore molecular mechanisms involved in the formation of one of the most primitive chordate body plans.

Animals↗

PubMed2006

The impact of expression profiling on prognostic and predictive testing in breast cancer.

Expression profiling has been extensively applied to the study of breast cancer and undoubtedly is changing the way breast cancer is perceived. Over the past few years, several groups have described prognostic "signatures" (gene lists) that are purported to be more accurate prognostic factors than well established clinical and pathological features. In addition, cDNA and oligonucleotide microarrays have also been used to devise predictive "signatures" in the setting of neoadjuvant chemotherapy setting. However, it seems that the enthusiasm with this new technology has led most of us to turn a blind eye to some serious methodological problems which are evident in landmark papers on breast cancer expression profiling. These issues include small and biased cohorts of patients, inappropriate statistical analysis and lack of thorough validation of the technology. In this review, we critically revisit the most relevant cDNA microarray studies on breast cancer prognosis and prediction published to date. Although the results are promising, further optimisation and standardisation of the technique and properly designed clinical trials are required before microarrays can reliably be used as tools for clinical decision making.

Breast Neoplasms↗

PubMed2006

A new method to remove hybridization bias for interspecies comparison of global gene expression profiles uncovers an association between mRNA sequence divergence and differential gene expression in Xenopus.

The recent sequencing of a large number of Xenopus tropicalis expressed sequences has allowed development of a high-throughput approach to study Xenopus global RNA gene expression. We examined the global gene expression similarities and differences between the historically significant Xenopus laevis model system and the increasingly used X.tropicalis model system and assessed whether an X.tropicalis microarray platform can be used for X.laevis. These closely related species were also used to investigate a more general question: is there an association between mRNA sequence divergence and differences in gene expression levels? We carried out a comprehensive comparison of global gene expression profiles using microarrays of different tissues and developmental stages of X.laevis and X.tropicalis. We (i) show that the X.tropicalis probes provide an efficacious microarray platform for X.laevis, (ii) describe methods to compare interspecies mRNA profiles that correct differences in hybridization efficiency and (iii) show independently of hybridization bias that as mRNA sequence divergence increases between X.laevis and X.tropicalis differences in mRNA expression levels also increase.

Animals↗

PubMed2003

[Changes in the gene expression profile of the left heart ventricle during growth in the rat].

Wistar rats of 8, 10 and 12-week-old were chosen for study of the relationship between cardiac growth and its gene expression profile changes during maturation. The ultrasonic parameters of rat hearts were recorded before sacrifice, then total RNA of left ventricle were extracted and gene expression profiles were analyzed by cDNA microarray. During growth from 8 weeks to 12 weeks, the body weight increased by 45.5% (287+/-13 g vs 197+/-10 g), and the increment in the first two-week period was equal to that of the second two-week period. The mass of left ventricle and the posterior wall thickness increased by 27.7% (0.60+/-0.03 g vs 0.47+/-0.02 g) and 23.6% (2.04+/-0.04 mm vs 1.65+/-0.13 mm), respectively, and their increment in the first two-week period was much more than that in the second one. Meanwhile, the gene expression profile of the left ventricle changed significantly, which involved cellular structure, metabolism, oxidative stress, signal transduction, etc. Compared with the 8-week-old rats, these genes were mostly up-regulated in 10-week-old rats, while for 12-week-old rats, the gene expression profile of the left ventricle recovered to the pattern of 8-week-old rats again on the whole. These results suggest that the relationship between the changes in cardiac function and gene expression profile can be analyzed comprehensively with the technique of microarray, and that the changes in gene expression profile of the left ventricle during rat maturation adapt to the physiological growth of heart, which is of benefit for keeping the metabolism balance between materials and energy.

Animals↗

PubMed2003

SamCluster: an integrated scheme for automatic discovery of sample classes using gene expression profile.

MOTIVATION: Feature (gene) selection can dramatically improve the accuracy of gene expression profile based sample class prediction. Many statistical methods for feature (gene) selection such as stepwise optimization and Monte Carlo simulation have been developed for tissue sample classification. In contrast to class prediction, few statistical and computational methods for feature selection have been applied to clustering algorithms for pattern discovery. RESULTS: An integrated scheme and corresponding program SamCluster for automatic discovery of sample classes based on gene expression profile is presented in this report. The scheme incorporates the feature selection algorithms based on the calculation of CV (coefficient of variation) and t-test into hierarchical clustering and proceeds as follows. At first, the genes with their CV greater than the pre-specified threshold are selected for cluster analysis, which results in two putative sample classes. Then, significantly differentially expressed genes in the two putative sample classes with p-values < or = 0.01, 0.05, or 0.1 from t-test are selected for further cluster analysis. The above processes were iterated until the two stable sample classes were found. Finally, the consensus sample classes are constructed from the putative classes that are derived from the different CV thresholds, and the best putative sample classes that have the minimum distance between the consensus classes and the putative classes are identified. To evaluate the performance of the feature selection for cluster analysis, the proposed scheme was applied to four expression datasets COLON, LEUKEMIA72, LEUKEMIA38, and OVARIAN. The results show that there are only 5, 1, 0, and 0 samples that have been misclassified, respectively. We conclude that the proposed scheme, SamCluster, is an efficient method for discovery of sample classes using gene expression profile. AVAILABILITY: The related program SamCluster is available upon request or from the web page http://www.sph.uth.tmc.edu:8052/hgc/Downloads.asp.

Algorithms↗

PubMed2003

Gene expression profile in diabetic KK/Ta mice.

BACKGROUND: To identify susceptibility genes for diabetic nephropathy, GeneChip Expression Analysis was employed to survey the gene expression profile of diabetic KK/Ta mouse kidneys. METHODS: Kidneys from three KK/Ta and two BALB/c mice at 20 weeks of age were dissected. Total RNA was extracted and labeled for hybridizing to the Affymetrix Murine Genome U74Av2 array. The gene expression profile was compared between KK/Ta and BALB/c mice using GeneChip expression analysis software. Competitive reverse transcription-polymerase chain reaction (RT-PCR) was used to confirm the results of GeneChip for a selected number of genes. RESULTS: Out of 12,490 probe pairs present on GeneChip, 98 known genes and 31 expressed sequence tags (ESTs) were found to be differentially expressed between KK/Ta and BALB/c kidneys. Twenty-one known genes and seven ESTs that increased in expression and 77 known genes and 24 ESTs that decreased in KK/Ta kidneys were identified. These genes are related to renal function, extracellular matrix expansion and degradation, signal transduction, transcription regulation, ion transport, glucose and lipid metabolism, and protein synthesis and degradation. In the vicinity of UA-1 (quantitative trait locus for the development of albuminuria in KK/Ta mice), candidate genes that showed differential expression were identified, including the Sdc4 gene for syndecan-4, Ahcy gene for S-adenosylhomocysteine hydrolase, Sstr4 gene for somatostatin receptor 4, and MafB gene for Kreisler leucine zipper protein. CONCLUSION: The gene expression profile in KK/Ta kidneys is different from that in age-matched BALB/c kidneys. Altered gene expressions in the vicinity of UA-1 may be responsible for the development of albuminuria in diabetic KK/Ta mice.

Adenosylhomocysteinase↗

PubMed2002

Classifying toxicity and pathology by gene-expression profile--taking a lead from studies in neoplasia.

Microarray technology has given rise to the ability to classify and predict toxin-induced pathological change using gene-expression profiles. However, to date gene-expression profiling of pathological subtype has been exploited mainly in the pathological classification of neoplasia. Using an example of resistance to doxorubicin in vitro and gene-expression profiling in neoplasia, this article explores the potential and challenges for gene-expression profiling in the delineation and understanding of toxicity and toxin-induced pathological change.

Animals↗

PubMed2005

Integrating time-course microarray gene expression profiles with cytotoxicity for identification of biomarkers in primary rat hepatocytes exposed to cadmium.

MOTIVATION: DNA microarrays can provide information about the expression levels of thousands of genes simultaneously at the transcriptomic level, while conventional cell viability and cytotoxicity measurement methods provide information about the biological functions at the cellular level. Integrating these data at different levels provides a promising approach for evaluating or predicting how cells respond to chemical exposure. It is important to investigate the multi-scale biological system in a systematic way to better understand the gene regulation networks and signal transduction pathways involved in the cellular responses to environmental factors. RESULTS: Primary rat hepatocytes were exposed to cadmium acetate at 0, 1.25 and 2 microM. mRNA expression profiles at 0, 3, 6, 12 and 24 h were measured using the Affymetrix RatTox U34 GeneChip arrays. Simultaneously, cytotoxicity was assessed by lactase dehydrogenase leakage assay. Gene expression profiles at different time points were used to evaluate cytotoxicity at subsequent time points using partial least squares, and it was found that gene expression profiles at 0 h had the best prediction accuracy for the cytotoxicity observed at 12 h. Some biomarkers whose expression profiles showed strong relationship with cytotoxicity were identified and the underlying pathways were reconstructed to illustrate how hepatocytes respond to cadmium exposure. Permutation studies were also applied to assess the reliability of the predictive models. AVAILABILITY: Matlab source code is available upon request and DNA microarray data are available at GEO (http://www.ncbi.nlm.nih.gov/geo).

Algorithms↗

PubMed2004

Identification of hair cycle-associated genes from time-course gene expression profile data by using replicate variance.

The hair-growth cycle is an example of a cyclic process that is well characterized morphologically but understood incompletely at the molecular level. As an initial step in discovering regulators in hair-follicle morphogenesis and cycling, we used DNA microarrays to profile mRNA expression in mouse back skin from eight representative time points. We developed a statistical algorithm to identify the set of genes expressed within skin that are associated specifically with the hair-growth cycle. The methodology takes advantage of higher replicate variance during asynchronous hair cycles in comparison with synchronous cycles. More than one-third of genes with detectable skin expression showed hair-cycle-related changes in expression, suggesting that many more genes may be associated with the hair-growth cycle than have been identified in the literature. By using a probabilistic clustering algorithm for replicated measurements, these genes were grouped into 30 time-course profile clusters, which fall into four major classes. Distinct genetic pathways were characteristic for the different time-course profile clusters, providing insights into the regulation of hair-follicle cycling and suggesting that this approach is useful for identifying hair follicle regulators. In addition to revealing known hair-related genes, we identified genes that were not previously known to be hair cycle-associated and confirmed their temporal and spatial expression patterns during the hair-growth cycle by quantitative real-time PCR and in situ hybridization. The same computational approach should be generally useful for identifying genes associated with cyclic processes from complex tissues.

Algorithms↗