Around the triangle Chris Evelo BiGCaT Bioinformatics Maastricht May arrays QTLs paths

Involve information about chromosome locations of traits in expression analyses

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

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

From arrays to QTLs arrays QTLs paths 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

Get all QTL genes example blood pressure QTLs From Ensembl ( 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 ( Retrieve QTL annotation

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

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

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

Create QTL Mapps and map expression results Example QTL1a With a number of (slightly) upregulated genes

Initial array results Loosing too many genes 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

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

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

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

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)

Temporary Solution: double selection arrays QTLs paths 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

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