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Around the triangle

Around the triangle. arrays. Chris Evelo BiGCaT Bioinformatics Maastricht May 19 2004. paths. QTLs. Involve information about chromosome locations of traits in expression analyses. Around the triangle. How to combine expression data with known pathways and

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Around the triangle

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  1. Around the triangle arrays Chris Evelo BiGCaT Bioinformatics Maastricht May 19 2004 paths QTLs

  2. Involve information about chromosome locations of traits in expression analyses

  3. Around the triangle How to combine expression data with known pathways and known quantitative trade loci from congenic animals arrays paths QTLs

  4. From arrays to pathways Gene expression mapping Like what was shown in the previous talk. Annotate the genes Filter array data, normalize, filter and set a change criterion arrays paths QTLs

  5. From arrays to QTLs We need to get all the genes from the QTLs To create a QTL map To annotate the map backpage And to map real expression changes arrays paths QTLs

  6. Get all QTL genesexample blood pressure QTLs • From Ensembl (http://www.ensembl.org) • Using Ensmart to retrieve: • QTL range • gene (all exon) sequence • or all available gene ID’s • Or use direct SQL queries to ENSEMBL database • From RGD (http://rgd.mcw.edu/) • Retrieve QTL annotation

  7. The high blood pressure QTLs Those QTLs span almost half the genome! chromosomes

  8. Selected QTLs Basepairs Filter QTLs For overlapping QTLs: take the smaller one Use Mathematica procedure to proces QTL locations and overlaps

  9. Filtered high blood pressure QTLs This might be the really interesting regions chromosomes

  10. Create QTL Mappsand map expression results Example QTL1a With a number of(slightly) upregulated genes

  11. Initial array resultsLoosing too many genes • 15908 reporters on two arrays • 784 with interesting regulation (>1.4 fold) • only 127 with known Unigene ID’s • only 63 linked to chromosomes • 9 located within the QTL’s

  12. How to improve the mapping?Work in progress • Create a BLAST database from ENSEMBL QTL genes (use full gene and exon only) • BLAST (or BLAT) reporter clone sequences • Select good hits • Combine the two sets • Modify the QTL mapp backpages to contain reporter IDs • We expect to find > 60 % in the genome (that is a 400% increase) • And thus about 40 in the QTLs

  13. Around the trianglecan we understand the QTLSs? Get all QTL genes Annotate them (with SwissProt or trEMBL IDs). Assume in silico expression of all genes Perform standard mapping arrays paths QTLs

  14. Bad annotation again! • Only a small fraction of ENSEMBL genes has Swissprot/trEMBL annotation (or other that can be crosslinked). • So we need to reannotate the genes. • Separate annotation project uses double Swall X- linked trEMBL subdatabase. • Still needs to be combined

  15. Current QTL genes spread out • Lots of genes in Mapps • But… Most Mapps contain just a few QTL genes • Impossible to find most important Mapps (except by expert knowledge)

  16. Temporary Solution: double selection Get pathways with many regulated genes Select those that also contain QTL genes Yields: 22 GO, 4 local Mapps Among those: TGFβ signaling & Wnt signaling arrays paths QTLs

  17. Acknowledgements • Yigal Pinto and Umesh Sharma for high blood pressure rat array data • Incyte Genomics for (what still is) the best microarray platform ever • BMT TUe MDP project students: Greetje Groenendaal, Gijs Huisman, Sanne Reulen, Gijs Snieders, Marloes Damen, Freek van Dooren, Thijs Hendrix and Thomas Kelder • Stan Gaj for data mining • Willem Ligtenberg and Joris Korbeeck for generating BLAST databases and BLAST parser scripts • Andra Waagmeester for SQL queries • Rachel van Haaften for advices on mapping • Edwin ter Voert for allowing us to think about problems instead of computers

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