1. Grid-based
expression QTL Analysis
Ann-Kristin Grimm, Steffen Möller
University of Lübeck
Institute for Neuro- and Bioinformatics
BOSC09
Stockholm

2. Statistical genetics for complex diseases
● Isolation of homozygous strains
● susceptible or
● resistant
to disease
● Identification of chromosomal markers that
differ between strains
● Generating offspring with mixed genotypes,
score the disease phenotypes of every
individual
● Determine statistical association of markers
with score BOSC09
Stockholm

3. Back-Cross: F1 x P
BOSC09
Stockholm

4. Analysis
● Markers sufficiently dense to spot all X-overs
● Interval-mapping: neighbouring markers
● Both homozygous: no X-over
● Both heterozygous: no X-over
● One hetero-, one homozygous: X-over in between
● Continuous refinements
● Steady (directed) increase of markers
● Additional phenotypes being investigated
● Additional mice being bread
– Stronger statistics
– More cross-overs
BOSC09
Stockholm

5. Peak: inferring ML of disease location
● A stretch between two markers
may be found to be influencing the
strong
score
Effect
● The position of the controlling
locus may be estimated from
weak
● the fraction of individuals with X-over
● that show the same effect
A/A A/B A/A
A/A A/B A/B
● The exact locus remains undefined Marker-Combination
● … but what if we have more molecular scores ...?
BOSC09
Stockholm

6. Expression QTL
● Use gene expression levels as scores
● Disease phenotypes + sex + mitochondrial
inheritance are covariates
● Every locus is described by
● genes that it controls
● pathways/GO terms/TFBS/miRNA these share
● Super-linear (epistatic) effects with other loci
● Conversely genes → genetic loci
● Direct effects from locus → gene
● Singular effects are of interest, even should the
QTG never be determined BOSC09
Stockholm

7. Huge amount of data
● Compute time so long you don't want to do this
twice.
30000 genes
x 200 markers (^2 for interactions)
x 150 individuals
x 20 phenotypes (^2)
● But for better insights biologists do – with
updated data.
BOSC09
Stockholm

8. Increased communication through
distributed computation
● Dynamic website to
● Ship raw data to
compute nodes
● Humanely present
(interim) results of
computations
● Grid jobs retrieve
series of work units
● Continuous input to
biological researchers
BOSC09
Stockholm

9. Please join in: http://eqtl.berlios.de
Acknowledgments
Programming: Ann-Kristin Grimm, Jan Kolbaum, Hajo Krabbenhöfft, Patrick Wernhoff
Data: Maja Jagodic, Mèlanie Thessèn-Hedreul, Dirk Koczan, Saleh Ibrahim
Computations: Olli Tourhunen and the NDGF BOSC09
Stockholm