Advances in the identification and analysis of allele-specific expression

Allele-specific expression (ASE) is essential for normal development and many cellular processes but, if impaired, can result in disease. ASE is a feature of organisms with genomes consisting of more than one set of homologous chromosomes. The higher the number of chromosome sets (ploidy) per cell, the higher the potential complexity of ASE. Humans, for instance, are diploid (except germ cells, which are haploid), resulting in multiple possible expression states in time and space for each set of alleles. ASE is invoked and modulated by both genetic and epigenetic changes, affecting the underlying DNA sequence or chromatin of each allele, respectively. Although numerous methods have been developed to assay ASE, they usually require RNA to be available and are dependent upon genetic polymorphisms (such as single nucleotide polymorphisms (SNPs)) to differentiate between allelic transcripts. The rapid convergence to secondgeneration sequencing as the method of choice to examine genomic, epigenomic and transcriptomic data enables an integrated and more general approach to define and predict ASE, independent of SNPs. This ‘Omni-Seq’ approach has the potential to advance our understanding of the biology and pathophysiology of ASE-mediated processes by elucidating subtle combinatorial effects, leading to the accurate delineation of sub-phenotypes with consequential benefit for improved insight into disease etiology

Integrative DNA methylome analysis of pan-cancer biomarkers in cancer discordant monozygotic twin-pairs

BACKGROUND: A key focus in cancer research is the discovery of biomarkers that accurately diagnose early lesions in non-invasive tissues. Several studies have identified malignancy-associated DNA methylation changes in blood, yet no general cancer biomarker has been identified to date. Here, we explore the potential of blood DNA methylation as a biomarker of pan-cancer (cancer of multiple different origins) in 41 female cancer discordant monozygotic (MZ) twin-pairs sampled before or after diagnosis using the Illumina HumanMethylation450 BeadChip. RESULTS: We analysed epigenome-wide DNA methylation profiles in 41 cancer discordant MZ twin-pairs with affected individuals diagnosed with tumours at different single primary sites: the breast, cervix, colon, endometrium, thyroid gland, skin (melanoma), ovary, and pancreas. No significant global differences in whole blood DNA methylation profiles were observed. Epigenome-wide analyses identified one novel pan-cancer differentially methylated position at false discovery rate (FDR) threshold of 10 % (cg02444695, P = 1.8 × 10(-7)) in an intergenic region 70 kb upstream of the SASH1 tumour suppressor gene, and three suggestive signals in COL11A2, AXL, and LINC00340. Replication of the four top-ranked signals in an independent sample of nine cancer-discordant MZ twin-pairs showed a similar direction of association at COL11A2, AXL, and LINC00340, and significantly greater methylation discordance at AXL compared to 480 healthy concordant MZ twin-pairs. The effects at cg02444695 (near SASH1), COL11A2, and LINC00340 were the most promising in biomarker potential because the DNA methylation differences were found to pre-exist in samples obtained prior to diagnosis and were limited to a 5-year period before diagnosis. Gene expression follow-up at the top-ranked signals in 283 healthy individuals showed correlation between blood methylation and gene expression in lymphoblastoid cell lines at PRL, and in the skin tissue at AXL. A significant enrichment of differential DNA methylation was observed in enhancer regions (P = 0.03). CONCLUSIONS: We identified DNA methylation signatures in blood associated with pan-cancer, at or near SASH1, COL11A2, AXL, and LINC00340. Three of these signals were present up to 5 years prior to cancer diagnosis, highlighting the potential clinical utility of whole blood DNA methylation analysis in cancer surveillance

Epigenomic insights into common human disease pathology

The epigenome—the chemical modifications and chromatin-related packaging of the genome—enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological ‘clocks’ constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition

Human-specific CpG 'beacons' identify human-specific prefrontal cortex H3K4me3 chromatin peaks.

Background: Targeted recruitment of chromatin-modifying enzymes to clusters of CpG dinucleotides contributes toward the formation of accessible chromatin. By interprimate comparison we previously identified the set of nonpolymorphic human-specific CpGs (CpG 'beacons') and revealed that these loci were enriched for human disease traits. Due to their human-specific CpG density change, extreme CpG 'beacon' clusters (≥20 CpG beacons/kb) were predicted to identify permissive chromatin peaks within the human genome. Aim: We set out to explore these sequence-defined regions for evidence of an active chromatin signature. Results: Using available comparative primate epigenomic data from neurons of the prefrontal cortex, we show that these CpG 'beacon' clusters are indeed enriched for being human-specific H3K4me3 peaks (χ(2): p < 2.2 × 10(-16)) and thus predictive of permissive chromatin states. These sequence regions had a higher predictive value than previous selective analyses. We also show that both human-specific H3K4me3 and CpG 'beacon' clusters are increased within current and ancestral telomeric regions, supporting an association with recombination, which is higher towards the distal ends of chromosomes. Conclusion: Therefore, CpG-focused comparative sequence analysis can precisely pinpoint chromatin structures that contribute to the human-specific phenotype and further supports an integrated approach in genomic and epigenomic studies

The Genomic Loci of Specific Human tRNA Genes Exhibit Ageing-Related DNA Hypermethylation

The epigenome has been shown to deteriorate with age, potentially impacting on ageing-related disease. tRNA, while arising from only ~46kb (<0.002% genome), is the second most abundant cellular transcript. tRNAs also control metabolic processes known to affect ageing, through core translational and additional regulatory roles. Here, we interrogate the DNA methylation state of the genomic loci of human tRNA. We identify a genomic enrichment for age-related DNA hypermethylation at tRNA loci. Analysis in 4,350 MeDIP-seq peripheral-blood DNA methylomes (16-82 years), identifies 44 and 21 hypermethylating specific tRNAs at study-and genome-wide significance, respectively, contrasting with 0 hypomethylating. Validation and replication (450k array & independent targeted Bisuphite-sequencing) supported the hypermethylation of this functional unit. Tissue-specificity is a significant driver, although the strongest consistent signals, also independent of major cell-type change, occur in tRNA-iMet-CAT-1-4 and tRNA-Ser-AGA-2-6. This study presents a comprehensive evaluation of the genomic DNA methylation state of human tRNA genes and reveals a discreet hypermethylation with advancing age

Human-specific CpG "beacons" identify loci associated with human-specific traits and disease.

Regulatory change has long been hypothesized to drive the delineation of the human phenotype from other closely related primates. Here we provide evidence that CpG dinucleotides play a special role in this process. CpGs enable epigenome variability via DNA methylation, and this epigenetic mark functions as a regulatory mechanism. Therefore, species-specific CpGs may influence species-specific regulation. We report non-polymorphic species-specific CpG dinucleotides (termed "CpG beacons") as a distinct genomic feature associated with CpG island (CGI) evolution, human traits and disease. Using an inter-primate comparison, we identified 21 extreme CpG beacon clusters (≥ 20/kb peaks, empirical p < 1.0 × 10(-3)) in humans, which include associations with four monogenic developmental and neurological disease related genes (Benjamini-Hochberg corrected p = 6.03 × 10(-3)). We also demonstrate that beacon-mediated CpG density gain in CGIs correlates with reduced methylation in these species in orthologous CGIs over time, via human, chimpanzee and macaque MeDIP-seq. Therefore mapping into both the genomic and epigenomic space the identified CpG beacon clusters define points of intersection where a substantial two-way interaction between genetic sequence and epigenetic state has occurred. Taken together, our data support a model for CpG beacons to contribute to CGI evolution from genesis to tissue-specific to constitutively active CGIs