ABSTRACT
We developed a Perl-based tool called LyM to determine the best factor for changes in the expression level for each transcript across two sets of expression libraries. LyM includes a Bayesian framework that analyzes the prior and posterior probability density function for each transcript considering the size of the libraries. To find out the best factor for change in each distribution, LyM was implemented with a binary search. In this work we aimed to validate the performance of LyM tool using SAGE libraries from different human tissues. The results were compared with those generated by DGED (Digital Gene Expression Displayer), which worked as the gold standard, on the same data set, to assess accuracy. SAGE libraries were selected from CGAP for the following tissues (normal versus tumor): breast, colon, lung and stomach, consisting of eight SAGE libraries and 381,569 tags. DGED analyses were performed with five arbitrary factors for gene expression in two expression libraries: 2, 4, 8, 16 and 32. The results were confronted using the ratio between LyM and DGED factors and were quantitatively well-matched. LyM was capable of retrieving the best value of F, a factor that represents the fold difference in the expression of a specific gene between two expression libraries, represented by its SAGE tags. However, the optimal value of F is only shown in DGED output after multiple manual interactions. As a result, there was a significant economy of time with the LyM binary search algorithm. In some anecdotal cases we observed that the differential expression levels reached values above 100-fold for a fixed value of P = 0.05, an information that initially remained hidden in DGED. Finally, LyM proved to be relatively fast, portable to the standard workstation present in the molecular biology laboratory, assisting accurate and convenient gene search in expression experiments with minimal user interactions.
Subject(s)
Gene Expression Profiling , Algorithms , Bayes Theorem , Computational Biology/methods , Databases, Genetic , Gene Expression , Gene Library , Humans , Models, Genetic , Probability , Programming Languages , Software , Tissue DistributionABSTRACT
Hydroxycarbamide (HC) (or hydroxyurea) has been reported to increase fetal haemoglobin levels and improve clinical symptoms in sickle cell anaemia (SCA) patients. However, the complete pathway by which HC acts remains unclear. To study the mechanisms involved in the action of HC, global gene expression profiles were obtained from the bone marrow cells of a SCA patient before and after HC treatment using serial analysis of gene expression. In the comparison of both profiles, 147 differentially expressed transcripts were identified. The functional classification of these transcripts revealed a group of gene categories associated with transcriptional and translational regulation, e.g. EGR-1, CENTB1, ARHGAP4 and RIN3, suggesting a possible role for these pathways in the improvement of clinical symptoms of SCA patients. The genes involved in these mechanisms may represent potential tools for the identification of new targets for SCA therapy.
Subject(s)
Anemia, Sickle Cell/drug therapy , Anemia, Sickle Cell/genetics , Antisickling Agents/therapeutic use , Gene Expression Profiling , Hydroxyurea/therapeutic use , Oligonucleotide Array Sequence Analysis , Adult , Bone Marrow Cells/metabolism , Cell Line , ERG1 Potassium Channel , Ether-A-Go-Go Potassium Channels , Female , Gene Expression/drug effects , Globins/genetics , Heat-Shock Proteins/genetics , Hemoglobins/genetics , Humans , Ion Channels/genetics , Leukocytes/metabolism , Peroxidases/genetics , Peroxiredoxins , Potassium Channels, Voltage-Gated/genetics , RNA, Messenger/analysis , Reticulocytes/metabolism , Reverse Transcriptase Polymerase Chain Reaction , Signal Transduction/genetics , Transcription, GeneticABSTRACT
A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. In addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available.
