Cap analysis of gene expression (CAGE) and noncoding regulatory elements.

Cap analysis of gene expression (CAGE) was developed to detect the 5' end of RNA. Trapping of the RNA 5'-cap structure enables the enrichment and selective sequencing of complete transcripts. Upscaled high-throughput versions of CAGE have enabled the genome-wide identification of transcription start sites, including transcriptionally active promoters and enhancers. CAGE sequencing can be exploited to draw comprehensive maps of active genomic regulatory elements in a cell type- and activation-specific manner. The cells of the immune system are among the best candidates to be analyzed in humans, since they are easily accessible. In this review, we discuss how CAGE data are instrumental for integrative analyses with quantitative trait loci and omics data, and their usefulness in the mechanistic interpretation of the effects of genetic variations over the entire human genome. Integrating CAGE data with the currently available omics information will contribute to better understanding of the genome-wide association study variants that lie outside of annotated genes, deepening our knowledge on human diseases, and enabling the targeted design of more specific therapeutic interventions.

Functional genetics for studying the human immune system.

Although small numbers of immune-mediated diseases are inherited due to rare genetic mutations, most are multifactorial diseases caused by multiple elements including genetic and environmental factors. In the case of autoimmune diseases, many disease-susceptibility genes, including several in the major histocompatibility gene complex, have been reported, and over the past 10 years, genome-wide association studies (GWAS) have been used to analyze disease-susceptibility loci in representative diseases. Furthermore, many disease-susceptibility variants have been found to be related to gene expression levels. The expression of genes involved in disease pathogenesis is often cell-type-specific, and this is closely related to epigenome alterations. Genomic information is present even before the onset of a disease and has a clear causal relationship to the disease (i.e. the outcome). Therefore, it is important to establish functional genetics in human immunology to understand the pathogenesis of diseases using these pieces of information. We can then apply these results to drug discovery. Here, we will review these issues, especially focusing on autoimmune diseases, and discuss current and future directions of human immune system research.

Functional genomics of autoimmune diseases.

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.