Gregor Mendel was a genius and gave us some simple rules to describe inheritance. However, a large part of subsequent genetics can be viewed as reconciling those simple rules with a greater biological reality -- by adding lots of complexity. For example, Mendel posited genes which assort entirely independently. This was one of the first rules to be modified with the discovery of linkage. Mendel posited a simple recessive and dominant system, but blended inheritance (such as red flowers x white flowers = pink flowers) showed up. And so on, and so on. If you tried to fully rewrite Mendel's simple rules, they would look like something a lawyer cooked up ("in section 3 subpart B we define a segregation distorter gene...").
An early molecular interpretation of Mendel is that each gene codes for a protein €(Beadle & Tatum) and variant alleles code for variant proteins (Pauling). These were again powerful simple principals which remain very useful, but have again undergone a lot of complexification.
In a species such as ours with two alleles for nearly every gene (minus the sex chromosome genes in males), an interesting question is whether the same amount of each allele is made. A good guess in biology is to guess the more complex case, and indeed that is reality: while in many cases the two alleles generate the same amount of mRNA, that isn't always the case. One of the initial observations of this was to explain the odd inheritance of certain conditions, in which the phenotype depends on which parent a particular allele is inherited from (again deviating from Mendel!). Differential marking ("imprinting") of DNA depending on which parent it is from leads to differential expression.
A new paper in Nucleic Acids Research (free!) uses SNPs in a clever way to extend this beyond imprinting. A particularly nice twist is that not only do they demonstrate differential expression of two alleles, but they use that information to map out some of the regulatory sequences which are driving the difference.
The basic idea, which has been published previously, is to develop assays for an mRNA of interest that can differentiate single nucleotide polymorphisms (SNPs) that vary between the two alleles. SNPs are a common form of genetic variation, and most are probably functionally irrelevant -- which is why they are so common, since there isn't selective pressure to ditch them.
Once they had these assays in hand, they used them on various cancer cell lines to find messages with differential expression between alleles. Then they looked upstream of the gene for SNPs which overlapped predicted binding sites for transcription factors, proteins which regulate the generation of mRNA for the gene. Finally, they tested these sites for binding to the predicted transcription factor. In eight cases they successfully identified SNPs that alter transcription factor binding.
This sort of information is particularly relevant to understanding cancer. One hallmark of cancer is a reduced ability to properly replicate the genome, with the result that mutations occur at a much higher rate. Some cancers are even in part due to the loss of key DNA integrity maintenance systems and have been shown by sequencing to be chock full of mutations. If you have two alleles of a gene and one promotes cancer growth (or resistance to an anti-cancer drug), then expressing more of that allele will be beneficial to the tumor. A small elevation in expression of a tumorigenic allele could make a big difference -- and might escape notice if just looking at bulk expression levels. The converse could apply for a tumor suppressor -- a negatively-acting regulatory SNP, perhaps combined with other negative regulatory mechanisms such as methylation, might reduce a tumor suppressor mRNA level below that required to keep cancer growth in check.
Transcription factor binding site SNPs are not the only way SNPs might alter mRNA abundance -- another recent paper showed a SNP which left the coded protein unchanged ("synonymous SNP") but reduced the stability of the mRNA. And the challenge of predicting the effects of SNPs on proteins was reinforced recently with the first identification of natural SNPs which are synonymous but still succeed in altering protein structure and function.
It is the curse -- and wonder -- of biology that there are no simple rules, or even simple exceptions. The fun part is figuring out how to leverage all those exceptions into tools to explore other facets of biology, as the mRNA SNPs -> transcription factor sites paper did.