The genetics of regulatory variation in the human genome

Abstract

The regulation of gene expression plays an important role in complex phenotypes, including disease in humans. For some genes, the genetic mechanisms influencing gene expression are well elucidated; however, it is unclear how applicable these results are to gene expression on a genome-wide level. Studies in model organisms and humans have clearly documented gene expression variation among individuals and shown that a significant proportion of this variation has a genetic basis. Recent studies combine microarray surveys of gene expression for thousands of genes with dense marker maps, and are beginning to identify regions in the human genome that have functional effects on gene expression. This paper reviews recent developments and methodologies in this field, and discusses implications and future directions of this research in the context of understanding the influence of human genomic variation on the regulation of gene expression.

Figure 1

The different levels at which regulatory mutations can have an effect. 'Reg' indicates a regulatary region. Red stars indicate the position of a putative mutation. There can be mutations that: i) have an effect on the stability of the pre-mRNA; ii) have an effect on the stability of the mRNA or the rate of its translation (eg micro-RNA pairing); iii) have an effect on the structure of the protein and influence interactions with DNA or other proteins; iv) have an effect directly at the DNA level and abolish or modify sites of protein binding or affect DNA conformation.

Figure 2

(A) Structure of a hypothetical gene and the haplotype organisation of single nucleotide polymorphisms (SNPs) in the region. Vertical lines represent the location of SNPs, with two nucleotides of a single SNP shown. Horizontal blue lines represent the arrangement of SNPs into haplotype blocks. (B) Relationship between a hypothetical phenotypic distribution and associated SNP genotypic frequencies in a population. In this example, the individuals with highest transcript abundance are almost exclusively genotype CC, and those with lowest transcript abundance are almost exclusively AA. The individuals with transcript abundance closest to the population mean are primarily AC. (C) A hypothetical family pedigree used to identify functional variants through family-based linkage analysis. The individuals are coloured in grey scale according to a two-locus genotype additive model, with black corresponding to AABB and white corresponding to aabb.