1. eQTLs

2. microarray Complementary DNA probes are prepared and added to a chip
mRNA is extracted, fluorecently labeled, and hybridized to the probes
The intensity of fluorescence is a measure of the mRNA quantity

3. Supplementary fig. 2. Expression levels of predictive genes in independent dataset. The expression levels of the 50 genes most highly correlated with the ALL-AML distinction in the initial dataset were determined in the independent dataset. Each row corresponds to a gene, with the columns corresponding to expression levels in different samples. The expression level of each gene in the independent dataset is shown relative to the mean of expression levels for that gene in the initial dataset. Expression levels greater than the mean are shaded in red, and those below the mean are shaded in blue. The scale indicates standard deviations above or below the mean. The top panel shows genes highly expressed in ALL, the bottom panel shows genes more highly expressed in AML.

4. eQTLs in Yeast Brem and Krugluak, Science 2002
Two yeast strains were chosen (BY/RM)
6 independent microarray measurements of each
1528 genes were differentially expressed at P<0.005
These differences can be shown to be genetic

5. eQTLs in Yeast
40 haploid segregant crosses were isolated and genotyped.
3312 genetics markers were identified

6. Linkage of markers and gene expression
Expression levels of parents and segregants for gene YL007C, and YIL101C

7. Linkage of markers
Brem and Kruglyak treated each of the expression values of 6215 genes as a ‘phenotype’
Each phenotype was tested against each of 3312 markers
570 messages showed linkage to at least one marker P<10-5
Is this significant?
53 is expected by chance (?)
The loci might act in cis, or in trans.

8. Causal mechanisms for eQTL
The transcription of a gene is governed by DNA binding transcription factors (TFs) that switch the gene on or off
Mutations might have a clear effect on the expression of a nearby gene (a ‘cis’ effect)
The expression of the gene can affect the expression of more distant genes (a ‘trans’ effect)

9. A connection to biological networks
Cellular proteins function as a complex network.
Extra-cellular and other signals are propagated, and result in switching on/off of other pathways (by regulation of gene expression)
eQTLs can help identify some of these regulatory dependencies

10. Cis trans eQTLs 185 of the 570 messages were linked to cis-eQTLs
The linked loci clustered into distinct bins, with 10 dense bins
Each bin contains the number of transcripts linking to the markers in the bin
In many case, the genes are members of the same pathway.

11. The trans e-QTLs seem to be associated with groups of genes that have a ‘common purpose’
Critique this assertion! Is there a mangling of cause and effect here?

12. eQTLs in other species
FIGURE 1. Genomic architecture of eQTL across five Arabidopsis chromosomes
Other studies in Arabidopsis,mouse seem to reinforce these findings
Regulatory genetic variation is characterized by a high rate of cis-acting alleles, and a small number of trans-acting alleles with widespread transcriptional effects.
West, M. A. L. et al. Genetics 2007;175:
Copyright © 2007 by the Genetics Society of America

13. Computational problem
eQTL
Regulatory edge
An eQTL identifies a regulatory relationship between 2 genes.
Given eQTL, and other data, can we reconstruct regulatory networks?
Some of the questions on inferring networks will be addressed in Bix 3