188 J. A. Traherne positions (MVPs) in the human genome. The MHC was chosen as the ﬁrst target of the project because it is highly polymorphic, gene-rich and associated with disease. The study investigated seven cell types (adipose, brain, breast, lung, liver, prostate and muscle) across 32 individuals (Rakyan et al., 2004). Over 100 000 CpG methylation values within 253 amplicons were analysed. The second phase of HEP comprised about 1.9 million CpG methyl- ation values within 2524 amplicons across chromosomes 6, 20 and 22 in 43 samples (derived from 12 different tissues) (Eckhardt et al., 2006). In both studies, the methylation proﬁling was undertaken by high-throughput bisulphite DNA sequencing. The combined data from these projects have been integrated with the human genome sequence using the ENSEMBL interface to establish a database (www.epigenome.org), where the ﬁndings of the MHC pilot study and the second HEP project are publicly available. Overall, the methylation proﬁles were similar in both studies; the MHC did not show signiﬁcantly fewer or more amplicons that were either hypo- or hypermethylated. In general, the two studies drew the same three main conclusions. First, methylation levels are bimodally distributed (the majority of amplicons being either hypo- or relatively hypermethylated). Second, methyl- ation proﬁles show tissue speciﬁcity. Third, many regions display interindividual variation. Other projects have used chromatin immunoprecipitation (ChIP) coupled with next-generation sequencing for high- throughput proﬁling of histone changes and delineation of transcription factor binding across different cell types and cellular stimuli (Barski et al., 2007; Mikkelsen et al., 2007). Developing epigenetic resources such as these will add another layer of information to genomic annotation, by not only deﬁning regions that control gene activity in cell types, but also by uncovering sites of imprinting and allele-speciﬁc transcription. These ﬁndings will beneﬁt our understanding of complexities of MHC gene function in normal cellular homeostasis and disease states. In this way, epigenetic research could provide markers for dis- ease conditions and new targets for drug development. It may offer new explanations in well-studied areas such as autoimmunity, and will provide a basis for novel approaches to research on environmental effects, nutri- tion and ageing in complex disease. In this respect, the ﬁnding that DNA methylation proﬁles are associated with DNA alleles is a signiﬁcant discovery (Raval et al., 2007), which could provide new insight into the rather in- consistent MHC association studies in complex disease. Epi-alleles and epihaplotypes that combine epigenetic information with DNA sequence could provide improved risk prediction for a disease than either of the two factors analysed alone. Two concepts have been proposed for integrating disease genetics and epigenetics: haplo-epitype (hepitype) analysis (Murrell et al., 2005) and CDGE (common disease genetic epidemiology in the context of both genetic and epigenetic) analysis (Bjornsson et al., 2004). Finally, although the focus in this section has been on how epigenetics modiﬁes gene activity, it is also of interest that chromatin modiﬁcations have been evoked as controlling activity of recombination and chromosome breakpoints (Neumann & Jeffreys, 2006; Barski et al., 2007), which could have signiﬁcant bearing on the LD relationships within the MHC. Regulatory RNAs It has recently come to light that a signiﬁcant proportion of the genome expresses non-coding RNA, and that there is extensive overlap of transcriptional units and regulatory elements (Kapranov et al., 2007). Some of these abundant RNA transcripts, termed microRNA (miRNA), together with sequence polymorphisms and epigenetic factors, modulate gene expression at transcription and post- transcriptional level. The regulatory properties of miRNAs are implicated in gene coexpression, gene silenc- ing, imprinting and DNA methylation, and are achieved by affecting mRNA degradation and translation. Interest- ingly, miRNAs often arise from demethylation of tandem repeats (Lippman & Martienssen, 2004), and thus inter- individual variability in tandem repeats could account for differences in gene expression that result in inherited phenotypic variability (Flanagan et al., 2006). The emerging paradigm that genomic architecture is not co-linear, but is instead interleaved and modular, has clear repercussions in MHC research in terms of increased information content, transcriptional complexity, regula- tion of immune functioning and evolution. The involve- ment of regulatory RNA in disease predisposition clearly warrants more detailed investigation along with increased scrutiny and consideration of non-coding DNA sequences. Intriguingly, miRNAs may also function in interspecies regulation involving viral miRNAs and host immune system genes. A recent study shows that a miRNA encoded by human cytomegalovirus (HCMV) during infection reduces host cell killing by NK cells by speciﬁcally down- regulating expression of a ‘stress-induced’ gene (MICB) that encodes a ligand for the NK cell activating receptor NKG2D (Stern-Ginossar et al., 2007). The miRNA-based immunoevasion mechanism, exploited by HCMV, adds to the many ways infectious agents have of immune evasion (Wu et al., 2003; Wang et al., 2005; Pennini et al., 2006). One can envisage ‘counteractive’ evolution of the host immune defence genes in order to disrupt the interaction of pathogen miRNA with target host genes. As a ﬁnal point, down-regulation of host genes by inter- action of their mRNAs with viral miRNA could lead to novel therapeutics. Targeting these viral miRNAs might constitute an antiviral therapy, while mimicking their role could provide a means of immunosuppression. A diagrammatic representation of factors discussed in this review that may combine to inﬂuence MHC associa- tions with complex disease phenotypes is given in Fig. 7. Conclusion and outlook The MHC provides a prototype for the genetic footprints created by clusters of genes that are individually under © 2008 The Author Journal compilation © 2008 Blackwell Publishing Ltd, International Journal of Immunogenetics 35, 179–192