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Today, I used Athena, a web app that lets one check out and compare promoter sequences in Arabidopsis, for my Functional Genomics class. You can check out the Bioinformatics publication that announces this cool tool, if you want. But I must admit it is not really applicable to the rest of this post… the only reason I bring it up is because it influenced what I’ve been thinking about the whole day: promoters and how they effect gene expression and ultimately phenotype, especially since last week I wrote up an overview on how mutations in the promoter sequence of the dopamine gene has serious behavioral ramification.

Promoters are often neglected parts of the genome. They are critical areas that contain landing spots for other proteins that control gene expression. These regions are upstream of genes, but their location isn’t always fixed at an exact spot. Sometimes they are 2,000 bases upstream or more, and other times they are just a couple bases from the start codon.

While their locations vary, they all contain cis-acting elements which are areas of the DNA that have binding sites for proteins called transcription factors. The transcription factors have specific binding sites, and they latch onto the area that best matches their specificity. Based upon what other specific binding sites are located in the promoter, a whole cohort of proteins form a complex that recruits polymerase to being transcribing the gene and expressing it. All the components of the complex need to be present for polymerase to do its thing, which expands the flexibility of the expression and regulation of genes. The following illustration documents tones down this complexity with just the basic role of a transcription factor:

The Role of Transcription Factors

Basically, all I want you to appreciate is that promoter sequences are critical to understand gene expression and regulation. They are effectively the on and off switches that begin transcription of a gene into a product. Now, if you’re still confused and angry with why I’ve dumped all this molecular biology on your tired Monday night eyes, don’t blame me.

Blame the early online PLoS Genetics release that inspired me to introduce you to the wonderful world of promoters, enhancers, gene expression and gene regulation. See with a title like this, “Differential Allelic Expression in the Human Genome: A Robust Approach to Identify Genetic and Epigenetic Cis-Acting Mechanisms Regulating Gene Expression,” I just had to pass the goodness onto y’all.

In a nut shell, the article is important because it confronts one of the biggest mantras going around and offers an explanation that shifts the meaning behind the mantra. The mantra goes something like this, “Humans are genetically 99.9% identical.” Part of the mantra, is true, because we’re more or less genetically identical in the genes that code for proteins. And most of these protein encoding genes make proteins that are important for basic cellular functions, which we all need. But, that’s about all the mantra has going for it.

Our differences are manifested by many different genetic anomalies, from SNPs within exons to repetitive sequences. But a lot of our phenotypic differences come about from the different patterns in which our otherwise homologous genes are expressed or regulated. And the DNA the ares of the promoter that effect gene expression and regulation, and make us different, are neglected and not analyzed because linkage/association mapping of gene expression is notably costly and is a hell of a lot of work. In this new paper, a new method is described with all of the catch phrases that excite many molecular biologists, such as “robust” and “high-throughput” ways to,

“directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 60:40) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms.”

Effectively what this paper describes is a way to sequence and screen promoter regions of a lot of human genes, to see and compare what’s in them. With an understanding of the allelic differences that are represented in the promoter region of a gene of a population, we can begin to see how different combinations of transcription factors being to alter gene expression and phenotypic differences, and why humans are so diverse.