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Final project – Computational Biology Identifying transcription factories not involved in pre-mRNA splicing מר יהודה ברודי טל-ד"ר ירון שב :בהנחיית ניסים נעים עדי פוטוק :מגישים Introduction There is evidence of transcription factories which contain accumulations of RNA polymerase II. Genes are moving towards the factories in order to be transcribed. Introduction Splicing is a co-transcriptional modification of an mRNA, in which introns are removed and exons are joined. U1 and U2 are parts of the spliceosome machinery. http://www.mpibpc.mpg.de/groups/pr/PR/2008/08_10_eng_RN/ Project goal Identification and classification of transcription factories, and categorizing the factories by their probability to undergo splicing. RNA FISH Fluorescence In-Situ Hybridization Using a labeled oligonucleotide probe to detect a specific mRNA of interest. Immunofluorescence Using a fluorescent labeled antibody to detect U1snRNA, U1snRNA and RNA polymerase II. mRNA Wide-Field Microscopy The cells are illuminated with light of a certain wavelength and emit light of a different wavelength. This technique is used to acquire 3D images of a specimen. Each image is composed of several 2D layers. Deconvolution Problem: The light emitted from the fluorescent molecules disperses, as the layer gets farther away from the molecules. Solution: this method is used to focus the light back to its original source, in order to create an image more similar to the original image. Deconvolution Before After Image analysis IMARIS – Tool for analyzing images Wide graphical abilities. Embedded link to MATLAB programs. Gene constructs: e1 and e3 • e1 gene: no splicing • e3 gene: undergoes splicing Splicing is co-transcriptional Splicing factors can be identified at the site of transcription U1 snRNA snRNAU1 MS2 MS2 Transcription site e1 U1 snRNA MS2 U2 snRNA snRNAU2 Transcription site U1 snRNA U2 snRNA snRNAU1 Nucleoplasm U1 snRNA U2 snRNA snRNAU2 e3 Nucleoplasm U2 snRNA Splicing is co-transcriptional snRNAU1 Splicing factors can be identified at the site of transcription RNA pol II Immunofluorescence Cytoplasm Nucleolus Nucleoplasm Transcription factory Step I – Identify Factories • Use “dynamic threshold” to intensify the areas with high values, compared with their surroundings. Dynamic threshold Intensity of pixels in the image Step I – Identify Factories Locate the centers of these areas Step I – Identify Factories Expand each center to the whole factory area Step I – Identify Factories Use the “find connected components” function to differentiate between factories. e3 transcription factory LacI mRNA RNA Pol II e3 transcription factory mRNA molecules surrounding the gene RNA pol II and mRNA molecules surrounding the gene Step II – Calculate Correlation • Normalization of the U1 and U2 images. • Correction of pixel shift. Step II – Calculate Correlation • We tried several methods to calculate correlation: Pearson coefficient average of U1 / average of U2 curve fit (aX + b) Normalized count Normalized count Current results U1 / U2 U1 / U2 Step III – classifying factories • The best method to divide the factories into two distinct groups, is …. • Consensus correlation similar to that of e3 gene high probability of undergoing splicing. • Different / No consensus correlation low probability of undergoing splicing. The final output • Using color gradient to color factories according to the probability of undergoing splicing. Biological conclusions • A few hundreds of transcription factories in each nucleus, as mentioned in articles from recent years. ? Do factories tend to gather, or do they operate throughout the nucleus. ? Do active factories concentrate in the center of the nucleus. What’s next? • Improve factory identification (more automatically). • Displaying each factory as an individual object in IMARIS. • Analyze more images of e1 and e3 genes, to find the differences between their factories. • Check the correlation of U1 and U4 factors. Thanks Dr. Yaron Shav-Tal Mr. Yehuda Brody http://io9.com/photogallery/scienceart2009/1008301614