PCA2GO: a new multivariate statistics based method to identify highly expressed GO-Terms

<p>Abstract</p> <p>Background</p> <p>Several tools have been developed to explore and search Gene Ontology (GO) databases allowing efficient GO enrichment analysis and GO tree visualization. Nevertheless, identification of highly specific GO-terms in complex data sets is relatively complicated and the display of GO term assignments and GO enrichment analysis by simple tables or pie charts is not optimal. Valuable information such as the hierarchical position of a single GO term within the GO tree (topological ordering), or enrichment within a complex set of biological experiments is not displayed. Pie charts based on GO tree levels are, themselves, one-dimensional graphs, which cannot properly or efficiently represent the hierarchical specificity for the biological system being studied.</p> <p>Results</p> <p>Here we present a new method, which we name PCA2GO, capable of GO analysis using complex multidimensional experimental settings. We employed principal component analysis (PCA) and developed a new score, which takes into account the relative frequency of certain GO terms and their specificity (hierarchical position) within the GO graph. We evaluated the correlation between our representation score <it>R </it>and a standard measure of enrichment, namely <it>p</it>-values to convey the versatility of our approach to other methods and point out differences between our method and commonly used enrichment analyses. Although <it>p </it>values and the <it>R </it>score formally measure different quantities they should be correlated, because relative frequencies of GO terms occurrences within a dataset are an indirect measure of protein numbers related to this term. Therefore they are also related to enrichment. We showed that our score enables us to identify more specific GO-terms i.e. those positioned further down the GO-graph than other common tools used for this purpose. PCA2GO allows visualization and detection of multidimensional dependencies both within the acyclic graph (GO tree) and the experimental settings. Our method is intended for the analysis of several experimental sets, not for one set, like standard enrichment tools. To demonstrate the usefulness of our approach we performed a PCA2GO analysis of a fractionated cardiomyocyte protein dataset, which was identified by enhanced liquid chromatography-mass spectrometry (GeLC-MS). The analysis enabled us to detect distinct groups of proteins, which accurately reflect properties of biochemical cell fractions.</p> <p>Conclusions</p> <p>We conclude that PCA2GO is an alternative efficient GO analysis tool with unique features for detection and visualization of multidimensional dependencies within the dataset under study. PCA2GO reveals strongly correlated GO terms within the experimental setting (in this case different fractions) by PCA group formation and improves detection of more specific GO terms within experiment dependent GO term groups than standard <it>p </it>value calculations.</p

A Microarray Analysis of Gene Expression Patterns During Early Phases of Newt Lens Regeneration

Purpose: Notophthalmus viridescens, the red-spotted newt, possesses tremendous regenerative capabilities. Among the tissues and organs newts can regenerate, the lens is regenerated via transdifferentiation of the pigment epithelial cells of the dorsal iris, following complete removal (lentectomy). Under normal conditions, the same cells from the ventral iris are not capable of regenerating. This study aims to further understand the initial signals of lens regeneration

Newt-omics: a comprehensive repository for omics data from the newt Notophthalmus viridescens

Notophthalmus viridescens, a member of the salamander family is an excellent model organism to study regenerative processes due to its unique ability to replace lost appendages and to repair internal organs. Molecular insights into regenerative events have been severely hampered by the lack of genomic, transcriptomic and proteomic data, as well as an appropriate database to store such novel information. Here, we describe ‘Newt-omics’ (http://newt-omics.mpi-bn.mpg.de), a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centred database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ∼50 000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13 810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise

Analysis of newly established EST databases reveals similarities between heart regeneration in newt and fish

<p>Abstract</p> <p>Background</p> <p>The newt <it>Notophthalmus viridescens </it>possesses the remarkable ability to respond to cardiac damage by formation of new myocardial tissue. Surprisingly little is known about changes in gene activities that occur during the course of regeneration. To begin to decipher the molecular processes, that underlie restoration of functional cardiac tissue, we generated an EST database from regenerating newt hearts and compared the transcriptional profile of selected candidates with genes deregulated during zebrafish heart regeneration.</p> <p>Results</p> <p>A cDNA library of 100,000 cDNA clones was generated from newt hearts 14 days after ventricular injury. Sequencing of 11520 cDNA clones resulted in 2894 assembled contigs. BLAST searches revealed 1695 sequences with potential homology to sequences from the NCBI database. BLAST searches to TrEMBL and Swiss-Prot databases assigned 1116 proteins to Gene Ontology terms. We also identified a relatively large set of 174 ORFs, which are likely to be unique for urodele amphibians. Expression analysis of newt-zebrafish homologues confirmed the deregulation of selected genes during heart regeneration. Sequences, BLAST results and GO annotations were visualized in a relational web based database followed by grouping of identified proteins into clusters of GO Terms. Comparison of data from regenerating zebrafish hearts identified biological processes, which were uniformly overrepresented during cardiac regeneration in newt and zebrafish.</p> <p>Conclusion</p> <p>We concluded that heart regeneration in newts and zebrafish led to the activation of similar sets of genes, which suggests that heart regeneration in both species might follow similar principles. The design of the newly established newt EST database allows identification of molecular pathways important for heart regeneration.</p

Spiked-in Pulsed in Vivo Labeling Identifies a New Member of the CCN Family in Regenerating Newt Hearts

The newt <i>Notophthalmus viridescens</i>, which belongs to the family of salamanders (Urodela), owns remarkable regenerative capacities allowing efficient scar-free repair of various organs including the heart. Salamanders can regrow large parts of the myocardium unlike mammals, which cannot replace lost cardiomyocytes efficiently. Unfortunately, very little is known about the molecules and the regulatory circuits facilitating efficient heart regeneration in newts or salamanders. To identify proteins that are involved in heart regeneration, we have developed a pulsed SILAC-based mass spectrometry method based on the detection of paired peptide peaks after ¹³C₆-lysine incorporation into proteins in vivo. Proteins were identified by matching mass spectrometry derived peptide sequences to a recently established normalized newt EST library. Our approach enabled us to identify more than 2200 nonredundant proteins in the regenerating newt heart. Because of the pulsed in vivo labeling approach, accurate quantification was achieved for 1353 proteins, of which 72 were up- and 31 down-regulated with a (|log 2 ratio| > 1) during heart regeneration. One deregulated member was identified as a new member of the CCN protein family, showing a wound specific activation. We reason that the detection of such deregulated newt-specific proteins in regenerating hearts supports the idea of a local evolution of tissue regeneration in salamanders. Our results significantly improve understanding of dynamic changes in the complex protein network that underlies heart regeneration and provides a basis for further mechanistic studies