Annotated Gene Expression Research Articles

The Plant Ontology as a Tool for Comparative Plant Anatomy and Genomic Analyses

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly available, collaborative effort to develop and maintain a controlled, structured vocabulary (‘ontology’) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multispecies anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to >110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and quantitative trait loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.

Xenbase: expansion and updates of the Xenopus model organism database

Xenbase (http://www.xenbase.org) is a model organism database that provides genomic, molecular, cellular and developmental biology content to biomedical researchers working with the frog, Xenopus and Xenopus data to workers using other model organisms. As an amphibian Xenopus serves as a useful evolutionary bridge between invertebrates and more complex vertebrates such as birds and mammals. Xenbase content is collated from a variety of external sources using automated and semi-automated pipelines then processed via a combination of automated and manual annotation. A link-matching system allows for the wide variety of synonyms used to describe biological data on unique features, such as a gene or an anatomical entity, to be used by the database in an equivalent manner. Recent updates to the database include the Xenopus laevis genome, a new Xenopus tropicalis genome build, epigenomic data, collections of RNA and protein sequences associated with genes, more powerful gene expression searches, a community and curated wiki, an extensive set of manually annotated gene expression patterns and a new database module that contains data on over 700 antibodies that are useful for exploring Xenopus cell and developmental biology.

Correlation of receptor activator of nuclear factor kappa b (RANK) expression in breast cancer (BC) at the time of diagnosis with recurrence-free survival (RFS) and risk of bone-dominant metastases (BDM) in the I-SPY 1 trial (CALGB 150007/150012; ACRIN 6657).

2 Background: RANK is a tumor necrosis factor receptor family protein that is critical to bone turnover. The ligand to RANK (RANKL) can induce metastases from RANK-expressing tumor cells, and treatment with a RANKL inhibitor can reduce BC metastases (mets) in pre-clinical models and there is an FDA approved drug that targets RANKL. Osteoprotegerin (OPG) is a RANKL decoy receptor that blocks the interaction of RANK/RANKL. I-SPY 1 was a multicenter neoadjuvant trial with well annotated gene expression data and detailed clinical outcomes; we studied the impact of RANK expression on both RFS and BDM. Methods: OPG/RANK/RANKL pathway expression in core biopsies was evaluated at diagnosis in patients (pts) on I-SPY 1, then correlated with ER, intrinsic subtype, stage, response to chemotherapy, site of mets and RFS using the student t-test. Results: Gene arrays were performed on pretreatment tumor from 221 pts; 149 pts have available data with n being ER+. At a median follow-up of 3.5 yrs, 36 pts developed recurrence; 13 pts had BDM, 15 had non-bone mets (NBDM), and 8 pts were not evaluable. RANK, but not OPG or RANKL, was more highly expressed in ER- vs ER+ tumors (p=0.04) and in basal vs luminal A/B subtypes (p= 0.04), but no difference in expression based on tumor grade, node status or response to chemotherapy. Higher (>50%) RANK and lower (<50%) OPG expression correlated with worse RFS (p=0.03). Pts who developed BDM had higher expression of RANK, but not RANKL or OPG compared those with NBDM (p=0.05). After adjusting for ER and intrinsic subtypes, RANK expression was even more significantly correlated with risk for BDM (p=0.004). Conclusions: Higher RANK and lower OPG expression in primary tumor tissue correlates with poor RFS, and high RANK expression is associated with increased risk for BDM. These data suggests that targeting the OPG/RANK/RANKL pathway could be a promising strategy in preventing BDM in pts with high risk BC.

Use of gene set analysis (GSA) for molecular classification of responders and nonresponders to FOLFOX therapy in colorectal cancer (CRC).

3628 Background: Folinic acid (FOL) fluorouracil (F) and oxaliplatin (OX) chemotherapy is a commonly used therapy for CRC. Lacking in current literature are clinically relevant classifiers for potential responders. GSA technique is statistical method that detects significance of sets of genes, instead of examining a gene-by-gene basis. The objective of this study was to identify differential functionally annotated gene expression profiles associated with response to FOLFOX therapy in CRC tumors using gene-by-gene and GSA approaches. Methods: Genome wide expression profile data were collected on pre-treatment tumor tissues from patients with unresectable CRC receiving FOLFOX therapy (n = 83, Affymetrix HG U133A, GSE28702, Tsuji et al. BJC 2012). Gene expression was compared between responders (n = 42) and Non-responders (n = 41). GSA was conducted on 3272 curated gene sets from the Molecular Signatures Database (Subramanian, Tamayo et al. 2005, PNAS 102, 15545-15550) annotated by biological pathway, biochemical function and clinical behavior. Significant analysis of Microarray (SAM) and GSA (Tibshirani et al.) was done to identify gene sets associated with FOLFOX response. Results: Differential expressions of 23 genes were significantly associated with response, based on a single gene approach (p-value < 0.05). 13 of these were located on Chromosome 17 (p < 0.001). Among these, the top 5 ranked genes included NPEPPS, MBTD1, CEP44, LTA4H and CPNE4 which are involved in metal ion binding and aminopeptidase activity. GSA revealed only 44 out of 3272 gene sets were significantly associated with response, with a false discovery rate less than 25%. Increased expression of B-lymphocyte differentiation and Ras-signalling-related gene sets was associated with responders while mTOR signaling and hematopoietic stem cell-related genes set were associated with non-responders. Conclusions: Our data showed that differential biological pathways could be identified to predict response to FOLFOX therapy for CRC patients. Analysis may be useful to help define clinically relevant biologic subtypes among patients with metastatic colorectal cancer.

Retraction: Characterizing the Clinical Relevance of an Embryonic Stem Cell Phenotype in Lung Adenocarcinoma

Purpose: Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear whether these phenotypic similarities are the result of a common biological phenotype, such as regulatory pathways. Experimental Design: Lung cancer cell lines with corresponding gene expression data and genes associated with an embryonic stem cell identity were used to develop a signature of embryonic stemness (ES) activity specific to lung adenocarcinoma. Biological characteristics were elucidated as a function of cancer biology/oncogenic pathway dysregulation. The ES signature was applied to three independent early-stage (I-IIIa) lung adenocarcinoma data sets with clinically annotated gene expression data. The relationship between the ES phenotype and cisplatin (current standard of care) sensitivity was evaluated. Results: Pathway analysis identified specific regulatory networks [Ras ( P = 0.0005), Myc ( P = 0.0224), wound healing ( P P P n = 82; P = 0.0001), National Cancer Institute Director9s Challenge Consortium ( n = 442; P = 0.0002), and Duke ( n = 45; P = 0.06)]. The ES signature was not prognostic in prostate, breast, or ovarian adenocarcinomas. Lung tumors ( n = 569) and adenocarcinoma cell lines ( n = 31) expressing the ES phenotype were more likely to be resistant to cisplatin ( P P = 0.006, respectively). Conclusions: Lung adenocarcinomas that share a common gene expression pattern with normal human embryonic stem cells were associated with decreased survival, increased biological complexity, and increased likelihood of resistance to cisplatin. This indicates the aggressiveness of these tumors. (Clin Cancer Res 2009;15(24):7553–61)

P5-14-04: RANK Expression in Primary Tumor Tissue at the Time of Diagnosis Correlates with Risk of Subsequent Bone Metastases in the I-SPY 1 Trial (CALGB 150007/150012; ACRIN 6657).

Abstract Background RANK (receptor activator of nuclear factor kappa B) is a tumor necrosis factor receptor family protein that is expressed on the surface of osteoclasts and critical to bone turnover. RANK is also expressed on breast cancer (BC) cells, especially in the metastatic setting. Pre-clinical mouse models have shown that the ligand to RANK (RANKL) can induce migration of RANK-expressed tumor cells to bone and lung, and that treatment with a RANKL inhibitor can reduce BC metastases. ISPY is a multicenter neoadjuvant study with well annotated gene expression data. We evaluated RANK expression in primary tumor tissues at the time of diagnosis (dx) in patients (pts) with BC and correlated expression with risk of subsequent metastases. Methods: We evaluated expression of genes in the RANK/RANKL pathway in core biopsies at dx, and correlated this data with risk of recurrence as well as risk of site specific metastases using the student t-test. Results: A total 221 pts were enrolled in this clinical trial, all had locally advanced BC (LABC) and received neo-adjuvant chemotherapy (96.6% pts received adriamycin + cyclophosphamide-based regimens), tumor samples were collected at the time of dx by core biopsy, and underwent gene array study. Total 38508 genes were tested and 149 pts had available gene array data. Average age was 48.0 yr, pt characteristics are listed in the Table. Median follow up was 1260.3 days, range from 175 to 2520 days. Thirty-six pts developed recurrent disease; 13 pts developed bone-dominant metastases (BDM), 15 pts developed non-bone metastases (liver, lung, brain, lymph node and contralateral side breast) (NBDM), and 8 pts were not evaluable. Median RFS for those with BDM was 804 days, and for NBDM was 550 days, not significantly different (p=0.07). When comparing gene expression in the RANK/RANKL pathway, pts who developed BDM had a significantly higher expression of RANK (p=0.05) in primary tumor tissues than those with NBDM, while there was no difference in RANKL expression between the 2 groups. In addition, RANK was also significantly more highly expressed in the ER- group than ER+ group (p=0.006) and in the basal group compared to the luminal A/B group (p= 0.002). Analysis of variance (ANOVA) was then used to adjust clinical variability, after adjusting the difference of ER status, pathology subtypes, and menopausal status, RANK expression is even more significantly correlated with the bone-dominant group (p=0.002). Conclusion: Higher RANK expression in primary tumor tissues correlates with increased risk of subsequent BDM in pts enrolled in iSPY-1 trial. The sample size is small (n=149) and all pts had LABC. Our study suggests that targeting RANK/RANKL pathway is a promising strategy in preventing BDM in pts with high risk BC, further analysis in larger data sets is ongoing. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P5-14-04.

Automatically identifying and annotating mouse embryo gene expression patterns

Motivation: Deciphering the regulatory and developmental mechanisms for multicellular organisms requires detailed knowledge of gene interactions and gene expressions. The availability of large datasets with both spatial and ontological annotation of the spatio-temporal patterns of gene expression in mouse embryo provides a powerful resource to discover the biological function of embryo organization. Ontological annotation of gene expressions consists of labelling images with terms from the anatomy ontology for mouse development. If the spatial genes of an anatomical component are expressed in an image, the image is then tagged with a term of that anatomical component. The current annotation is done manually by domain experts, which is both time consuming and costly. In addition, the level of detail is variable, and inevitably errors arise from the tedious nature of the task. In this article, we present a new method to automatically identify and annotate gene expression patterns in the mouse embryo with anatomical terms.Results: The method takes images from in situ hybridization studies and the ontology for the developing mouse embryo, it then combines machine learning and image processing techniques to produce classifiers that automatically identify and annotate gene expression patterns in these images. We evaluate our method on image data from the EURExpress study, where we use it to automatically classify nine anatomical terms: humerus, handplate, fibula, tibia, femur, ribs, petrous part, scapula and head mesenchyme. The accuracy of our method lies between 70% and 80% with few exceptions. We show that other known methods have lower classification performance than ours. We have investigated the images misclassified by our method and found several cases where the original annotation was not correct. This shows our method is robust against this kind of noise.Availability: The annotation result and the experimental dataset in the article can be freely accessed at http://www2.docm.mmu.ac.uk/STAFF/L.Han/geneannotation/.Contact: l.han@mmu.ac.ukSupplementary Information: Supplementary data are available at Bioinformatics online.

Characterizing the clinical relevance of epithelial mesenchymal transition (EMT) in human tumors.

10507 Background: We propose that the sonic hedge hog pathway (SHH) induces EMT in vitro, resulting in gene expression changes that are clinically relevant. Methods: EMT was induced in lung, breast, and prostate cancer cells in vitro through co-culture with myofibroblasts, a rich source of the SHH ligand. Real-time PCR (QRT-PCR) and immunoflorescence were used to confirm EMT, and invasiveness of the phenotype was assessed with matrigel assays. Microarray analysis was performed on RNA extracted from EMT induced cells and controls and bayesian regression methods were used to generate an EMT signature. Clinically annotated gene expression data from patients with lung (n = 128), breast (n = 286) and prostate (n = 79) cancer was used to ascertain the clinical importance of EMT, using survival as a relevant outcome. Results: QRT-PCR confirmed upregulation of EMT related genes, demonstrating a several fold increase in the expression of Snail, N- cadherin, Gli 2 and SHH genes, respectively (p < 0.0001). Immunoflorescence confirmed the necessary Cadherin switch and the EMT induced cells demonstrated increased invasion (p = 0.001). Cyclopamine inhibited increased expression of Snail, N-cadherin, SHH, and Gli2 (p <0.0001) confirming that SHH was a principal mediator of EMT in human tumors. Using EMT induced cells and control cells, a genomic signature for EMT in adenocarcinoma was characterized, comprised of 200 genes. Upregulated pathways include keratan sulfate biosynthesis and extracellular matrix interaction. Importantly, the EMT signature predicts for 5-yr metastasis-free survival in a large dataset of node negative breast cancer patients (p = 0.004). Similar statistically significant survival differences exist in prostate (p = 0.03) and lung cancer (p = 0.04). In addition, chemosensitivity for over 40 lung cancer cell lines was assessed, with median EC50 values significantly higher in cell lines with a high probability of EMT. Conclusions: Activation of the SHH pathway induces EMT in human cancers and genome-wide changes occurring during EMT can be used to predict clinical outcomes. The SHH pathway represents a unique therapeutic target for suppression of distant metastasis and modulating chemotherapeutic resistance. No significant financial relationships to disclose.

Characterizing the Clinical Relevance of an Embryonic Stem Cell Phenotype in Lung Adenocarcinoma

Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear whether these phenotypic similarities are the result of a common biological phenotype, such as regulatory pathways. Lung cancer cell lines with corresponding gene expression data and genes associated with an embryonic stem cell identity were used to develop a signature of embryonic stemness (ES) activity specific to lung adenocarcinoma. Biological characteristics were elucidated as a function of cancer biology/oncogenic pathway dysregulation. The ES signature was applied to three independent early-stage (I-IIIa) lung adenocarcinoma data sets with clinically annotated gene expression data. The relationship between the ES phenotype and cisplatin (current standard of care) sensitivity was evaluated. Pathway analysis identified specific regulatory networks [Ras (P = 0.0005), Myc (P = 0.0224), wound healing (P < 0.0001), chromosomal instability (P < 0.0001), and invasiveness (P < 0.0001)] associated with the ES phenotype. The prognostic relevance of the ES signature, as related to patient survival, was characterized in three cohorts [CALGB 9761 (n = 82; P = 0.0001), National Cancer Institute Director's Challenge Consortium (n = 442; P = 0.0002), and Duke (n = 45; P = 0.06)]. The ES signature was not prognostic in prostate, breast, or ovarian adenocarcinomas. Lung tumors (n = 569) and adenocarcinoma cell lines (n = 31) expressing the ES phenotype were more likely to be resistant to cisplatin (P < 0.0001 and P = 0.006, respectively). Lung adenocarcinomas that share a common gene expression pattern with normal human embryonic stem cells were associated with decreased survival, increased biological complexity, and increased likelihood of resistance to cisplatin. This indicates the aggressiveness of these tumors.

Comparison of melanoblast expression patterns identifies distinct classes of genes.

A full understanding of transcriptional regulation requires integration of information obtained from multiple experimental datasets. These include datasets annotating gene expression within the context of an entire organism under normal and genetically perturbed conditions. Here we describe an expression dataset annotating pigment cell-expressed genes of the developing melanocyte and retinal pigmented epithelium lineages. Expression images are annotated and available at http://research.nhgri.nih.gov/manuscripts/Loftus/March2009/. Data are also summarized in a standardized manner using a universal melanoblast scoring scale that accounts for the embryonic location of cells and regional cell density. This approach allowed us to classify 14 pigment genes into four groupings classified by cell lineage expression, temporal-spatial context, and differential alteration in response to altered MITF and SOX10 status. Significant differences in regional populations were also observed across inbred strain backgrounds, highlighting the value of this approach to identify modifier allele influences on melanoblast number and distributions. This analysis revealed novel features of in vivo expression patterns that are not measurable by in vitro-based assays, providing data that in combination with genomic analyses will allow modeling of pigment cell gene expression in development and disease.

Automated pipeline for atlas-based annotation of gene expression patterns: Application to postnatal day 7 mouse brain

Massive amounts of image data have been collected and continue to be generated for representing cellular gene expression throughout the mouse brain. Critical to exploiting this key effort of the post-genomic era is the ability to place these data into a common spatial reference that enables rapid interactive queries, analysis, data sharing, and visualization. In this paper, we present a set of automated protocols for generating and annotating gene expression patterns suitable for the establishment of a database. The steps include imaging tissue slices, detecting cellular gene expression levels, spatial registration with an atlas, and textual annotation. Using high-throughput in situ hybridization to generate serial sets of tissues displaying gene expression, this process was applied toward the establishment of a database representing over 200 genes in the postnatal day 7 mouse brain. These data using this protocol are now well-suited for interactive comparisons, analysis, queries, and visualization.

Characterizing the clinical relevance of an embryonic stem cell phenotype in lung adenocarcinoma

11001 Background: Cancer cells possess traits reminiscent of those ascribed to normal stem cells. It is unclear whether these phenotypic similarities between normal/embryonic stem cells and mature tumor cells, specific to lung cancer, are a result of underlying biologic processes, such as specific molecular pathways and regulatory networks. Methods: Using a large cohort of lung cancer cell lines with associated gene expression data, genes associated with an embryonic stem cell identity were used to develop a ‘signature’ representative of embryonic stemness (ES) activity specific to lung adenocarcinoma. Differential biology was evaluated using Gene Set Enrichment Analysis (GSEA) and signatures of oncogenic pathway deregulation. The ES signature was applied to three independent early (stage I - IIIa) lung adenocarcinoma data sets (N = 634) with clinically annotated gene expression data. The relationship between the ES phenotype and cisplatin sensitivity was also evaluated. Results: Using Bayesian regression analysis, a 100 gene signature representative of ES activity in lung adenocarcinoma was developed and validated in a leave-one-out-analysis. GSEA identified gene sets significantly represented in the ES signature: signature of neoplastic transformation, signature of undifferentiated cancer, BRCA pathway, and fibroblast serum response pathway, all associated with cancer invasiveness. Adenocarcinomas with ES demonstrated increased activation of RAS (p = 0.0002), MYC (p = 0.0057), wound healing (angiogenesis) (p &lt; 0.0001), chromosomal instability (p &lt; 0.0001), and invasiveness (p &lt; 0.0001) gene signatures. Adenocarcinomas (N= 634) with ES had a decreased survival (p&lt;0.04). The ES signature was not prognostic in prostate, ovarian, or breast adenocarcinomas. Lung tumors (N=634) and adenocarcinoma cell lines (N=31) with ES were more resistant to cisplatin (p&lt;0.0001 and p=0.0063, respectively). Conclusions: Lung adenocarcinomas that share a common gene expression pattern with normal stem cells were associated with decreased survival and increased likelihood of resistance to cisplatin, indicating the aggressiveness of lung tumors with a stem cell phenotype. No significant financial relationships to disclose.

A bag-of-words approach for Drosophila gene expression pattern annotation

BackgroundDrosophila gene expression pattern images document the spatiotemporal dynamics of gene expression during embryogenesis. A comparative analysis of these images could provide a fundamentally important way for studying the regulatory networks governing development. To facilitate pattern comparison and searching, groups of images in the Berkeley Drosophila Genome Project (BDGP) high-throughput study were annotated with a variable number of anatomical terms manually using a controlled vocabulary. Considering that the number of available images is rapidly increasing, it is imperative to design computational methods to automate this task.ResultsWe present a computational method to annotate gene expression pattern images automatically. The proposed method uses the bag-of-words scheme to utilize the existing information on pattern annotation and annotates images using a model that exploits correlations among terms. The proposed method can annotate images individually or in groups (e.g., according to the developmental stage). In addition, the proposed method can integrate information from different two-dimensional views of embryos. Results on embryonic patterns from BDGP data demonstrate that our method significantly outperforms other methods.ConclusionThe proposed bag-of-words scheme is effective in representing a set of annotations assigned to a group of images, and the model employed to annotate images successfully captures the correlations among different controlled vocabulary terms. The integration of existing annotation information from multiple embryonic views improves annotation performance.

Automated annotation of Drosophila gene expression patterns using a controlled vocabulary

Regulation of gene expression in space and time directs its localization to a specific subset of cells during development. Systematic determination of the spatiotemporal dynamics of gene expression plays an important role in understanding the regulatory networks driving development. An atlas for the gene expression patterns of fruit fly Drosophila melanogaster has been created by whole-mount in situ hybridization, and it documents the dynamic changes of gene expression pattern during Drosophila embryogenesis. The spatial and temporal patterns of gene expression are integrated by anatomical terms from a controlled vocabulary linking together intermediate tissues developed from one another. Currently, the terms are assigned to patterns manually. However, the number of patterns generated by high-throughput in situ hybridization is rapidly increasing. It is, therefore, tempting to approach this problem by employing computational methods. In this article, we present a novel computational framework for annotating gene expression patterns using a controlled vocabulary. In the currently available high-throughput data, annotation terms are assigned to groups of patterns rather than to individual images. We propose to extract invariant features from images, and construct pyramid match kernels to measure the similarity between sets of patterns. To exploit the complementary information conveyed by different features and incorporate the correlation among patterns sharing common structures, we propose efficient convex formulations to integrate the kernels derived from various features. The proposed framework is evaluated by comparing its annotation with that of human curators, and promising performance in terms of F1 score has been reported.

VitisExpDB: a database resource for grape functional genomics.

BackgroundThe family Vitaceae consists of many different grape species that grow in a range of climatic conditions. In the past few years, several studies have generated functional genomic information on different Vitis species and cultivars, including the European grape vine, Vitis vinifera. Our goal is to develop a comprehensive web data source for Vitaceae.DescriptionVitisExpDB is an online MySQL-PHP driven relational database that houses annotated EST and gene expression data for V. vinifera and non-vinifera grape species and varieties. Currently, the database stores ~320,000 EST sequences derived from 8 species/hybrids, their annotation (BLAST top match) details and Gene Ontology based structured vocabulary. Putative homologs for each EST in other species and varieties along with information on their percent nucleotide identities, phylogenetic relationship and common primers can be retrieved. The database also includes information on probe sequence and annotation features of the high density 60-mer gene expression chip consisting of ~20,000 non-redundant set of ESTs. Finally, the database includes 14 processed global microarray expression profile sets. Data from 12 of these expression profile sets have been mapped onto metabolic pathways. A user-friendly web interface with multiple search indices and extensively hyperlinked result features that permit efficient data retrieval has been developed. Several online bioinformatics tools that interact with the database along with other sequence analysis tools have been added. In addition, users can submit their ESTs to the database.ConclusionThe developed database provides genomic resource to grape community for functional analysis of genes in the collection and for the grape genome annotation and gene function identification. The VitisExpDB database is available through our website .

Regulatory Pathway Analysis by High-Throughput In Situ Hybridization

Automated in situ hybridization enables the construction of comprehensive atlases of gene expression patterns in mammals. Such atlases can become Web-searchable digital expression maps of individual genes and thus offer an entryway to elucidate genetic interactions and signaling pathways. Towards this end, an atlas housing ∼1,000 spatial gene expression patterns of the midgestation mouse embryo was generated. Patterns were textually annotated using a controlled vocabulary comprising >90 anatomical features. Hierarchical clustering of annotations was carried out using distance scores calculated from the similarity between pairs of patterns across all anatomical structures. This process ordered hundreds of complex expression patterns into a matrix that reflects the embryonic architecture and the relatedness of patterns of expression. Clustering yielded 12 distinct groups of expression patterns. Because of the similarity of expression patterns within a group, members of each group may be components of regulatory cascades. We focused on the group containing Pax6, an evolutionary conserved transcriptional master mediator of development. Seventeen of the 82 genes in this group showed a change of expression in the developing neocortex of Pax6-deficient embryos. Electromobility shift assays were used to test for the presence of Pax6-paired domain binding sites. This led to the identification of 12 genes not previously known as potential targets of Pax6 regulation. These findings suggest that cluster analysis of annotated gene expression patterns obtained by automated in situ hybridization is a novel approach for identifying components of signaling cascades.

Physiological genomics special issue on animal functional genomics

this special issue of Physiological Genomics highlights 12 papers that reflect presentations made by 110 international delegates of the 2nd International Symposium on Animal Functional Genomics (2nd ISAFG) held May 16th-19th, 2006, at Michigan State University (East Lansing, MI). This was the second

XcisClique: analysis of regulatory bicliques

BackgroundModeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions.MethodsXcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution), and on the new sum of absolute values statistic (SAV) that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion.ResultsXcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at .

A Digital Atlas to Characterize the Mouse Brain Transcriptome

Massive amounts of data are being generated in an effort to represent for the brain the expression of all genes at cellular resolution. Critical to exploiting this effort is the ability to place these data into a common frame of reference. Here we have developed a computational method for annotating gene expression patterns in the context of a digital atlas to facilitate custom user queries and comparisons of this type of data. This procedure has been applied to 200 genes in the postnatal mouse brain. As an illustration of utility, we identify candidate genes that may be related to Parkinson disease by using the expression of a dopamine transporter in the substantia nigra as a search query pattern. In addition, we discover that transcription factor Rorb is down-regulated in the barrelless mutant relative to control mice by quantitative comparison of expression patterns in layer IV somatosensory cortex. The semi-automated annotation method developed here is applicable to a broad spectrum of complex tissues and data modalities.

Adult mouse brain gene expression patterns bear an embryologic imprint

The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional "imprint" consistent with both embryological origins and classic evolutionary relationships. Embryonic cellular position along the anterior-posterior axis of the neural tube was shown to be closely associated with, and possibly a determinant of, the gene expression patterns in adult structures. We also observed a significant number of embryonic patterning and homeobox genes with region-specific expression in the adult nervous system. The relationships between global expression patterns for different anatomical regions and the nature of the observed region-specific genes suggest that the adult brain retains a degree of overall gene expression established during embryogenesis that is important for regional specificity and the functional relationships between regions in the adult. The complete collection of extensively annotated gene expression data along with data mining and visualization tools have been made available on a publicly accessible web site (www.barlow-lockhart-brainmapnimhgrant.org).