Alternative splicing provides a versatile mechanism of gene regulation, which is often subverted in disease. We have used customized oligonucleotide microarrays to interrogate simultaneously the levels of expression of splicing factors and the patterns of alternative splicing of genes involved in tumor progression. Analysis of RNAs isolated from cell lines derived from Hodgkin lymphoma tumors indicate that the relative abundance of alternatively spliced isoforms correlates with transformation and tumor grade. Changes in expression of regulators were also detected, and a subset sample was confirmed at the protein level. Ectopic expression of neuron-specific splicing regulatory proteins of the Nova family was observed in some cell lines and tumor samples, correlating with expression of a neuron-specific mRNA isoform of JNK2 kinase. This microarray design can help assess the role of alternative splicing in a variety of biological and medical problems and potentially serve as a diagnostic tool.
"Similar to ESTs, junction arrays cannot establish if two splicing events in one tissue are in the same or different transcripts, and novel isoform sequences are not described. Cross-hybridization may also generate false positives when genes with similar sequences have strong tissue-specific regulation . "
[Show abstract][Hide abstract] ABSTRACT: Prior to the completion of the human genome project, the human genome was thought to have a greater number of genes as it seemed structurally and functionally more complex than other simpler organisms. This along with the belief of "one gene, one protein", were demonstrated to be incorrect. The inequality in the ratio of gene to protein formation gave rise to the theory of alternative splicing (AS). AS is a mechanism by which one gene gives rise to multiple protein products. Numerous databases and online bioinformatic tools are available for the detection and analysis of AS. Bioinformatics provides an important approach to study mRNA and protein diversity by various tools such as expressed sequence tag (EST) sequences obtained from completely processed mRNA. Microarrays and deep sequencing approaches also aid in the detection of splicing events. Initially it was postulated that AS occurred only in about 5% of all genes but was later found to be more abundant. Using bioinformatic approaches, the level of AS in human genes was found to be fairly high with 35-59% of genes having at least one AS form. Our ability to determine and predict AS is important as disorders in splicing patterns may lead to abnormal splice variants resulting in genetic diseases. In addition, the diversity of proteins produced by AS poses a challenge for successful drug discovery and therefore a greater understanding of AS would be beneficial.
Current Genomics 05/2013; 14(3):182-94. DOI:10.2174/1389202911314030004 · 2.34 Impact Factor
"Owing to the regulatory power of this process, an increasing number of studies are being directed at understanding AS regulation at the single-exon level (Castle et al., 2008; Johnson et al., 2003; Lewis et al., 2003; Wang et al., 2008). In general, researchers in the splicing regulation field have utilized comparative approaches to reveal tissue-specific (Relogio et al., 2005; Ule et al., 2005) or disease-related (Baumer et al., 2009) AS events. However, such methodologies have not been used to generate maps of AS activity within one cellular condition. "
[Show abstract][Hide abstract] ABSTRACT: Alternative splicing (AS) is a pre-mRNA maturation process leading to the expression of multiple mRNA variants from the same primary transcript. More than 90% of human genes are expressed via AS. Therefore, quantifying the inclusion level of every exon is crucial for generating accurate transcriptomic maps and studying the regulation of AS.
Here we introduce SpliceTrap, a method to quantify exon inclusion levels using paired-end RNA-seq data. Unlike other tools, which focus on full-length transcript isoforms, SpliceTrap approaches the expression-level estimation of each exon as an independent Bayesian inference problem. In addition, SpliceTrap can identify major classes of alternative splicing events under a single cellular condition, without requiring a background set of reads to estimate relative splicing changes. We tested SpliceTrap both by simulation and real data analysis, and compared it to state-of-the-art tools for transcript quantification. SpliceTrap demonstrated improved accuracy, robustness and reliability in quantifying exon-inclusion ratios.
SpliceTrap is a useful tool to study alternative splicing regulation, especially for accurate quantification of local exon-inclusion ratios from RNA-seq data.
SpliceTrap can be implemented online through the CSH Galaxy server http://cancan.cshl.edu/splicetrap and is also available for download and installation at http://rulai.cshl.edu/splicetrap/.
Supplementary data are available at Bioinformatics online.
"DNA microarrays  have revolutionized every area in biology . Microarrays allow thousands of genes to be assayed at once, offering global views of biological processes at the transcriptional level , as well as allowing surveys of DNA sequence variation , and alternative splicing . Integration of the results with other data informs many projects, such as those that perform cancer classification , genome annotation  and functional genomics . "
[Show abstract][Hide abstract] ABSTRACT: The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms.
50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods.
Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe "percent bound" value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays.
PLoS ONE 06/2010; 5(6):e11048. DOI:10.1371/journal.pone.0011048 · 3.23 Impact Factor
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