Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion.

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

AptCompare: optimized de novo motif discovery of RNA aptamers via HTS-SELEX.

SUMMARY: High-throughput sequencing can enhance the analysis of aptamer libraries generated by the Systematic Evolution of Ligands by EXponential enrichment. Robust analysis of the resulting sequenced rounds is best implemented by determining a ranked consensus of reads following the processing by multiple aptamer detection algorithms. While several such approaches have been developed to this end, their installation and implementation is problematic. We developed AptCompare, a cross-platform program that combines six of the most widely used analytical approaches for the identification of RNA aptamer motifs and uses a simple weighted ranking to order the candidate aptamers, all driven within the same GUI-enabled environment. We demonstrate AptCompare's performance by identifying the top-ranked candidate aptamers from a previously published selection experiment in our laboratory, with follow-up bench assays demonstrating good correspondence between the sequences' rankings and their binding affinities. AVAILABILITY AND IMPLEMENTATION: The source code and pre-built virtual machine images are freely available at https://bitbucket.org/shiehk/aptcompare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Differential DNA methylation patterns of homeobox genes in proximal and distal colon epithelial cells.

Region and cell-type specific differences in the molecular make up of colon epithelial cells have been reported. Those differences may underlie the region-specific characteristics of common colon epithelial diseases such as colorectal cancer and inflammatory bowel disease. DNA methylation is a cell-type specific epigenetic mark, essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. Little is known about any region-specific variations in methylation patterns in human colon epithelial cells. Using purified epithelial cells and whole biopsies (n= 19) from human subjects, we generated epigenome-wide DNA methylation data (using the HELP-tagging assay), comparing the methylation signatures of the proximal and distal colon. We identified a total of 125 differentially methylated sites (DMS) mapping to transcription start sites of protein-coding genes, most notably several members of the homeobox (HOX) family of genes. Patterns of differential methylation were validated with MassArray EpiTYPER. We also examined DNA methylation in whole biopsies, applying a computational technique to deconvolve variation in methylation within cell types and variation in cell-type composition across biopsies. Including inferred epithelial proportions as a covariate in differential methylation analysis applied to the whole biopsies resulted in greater overlap with the results obtained from purified epithelial cells compared with when the covariate was not included. Results obtained from both approaches highlight region-specific methylation patterns of HOX genes in colonic epithelium. Regional variation in methylation patterns has implications for the study of diseases that exhibit regional expression patterns in the human colon, such as inflammatory bowel disease and colorectal cancer.

Clinical and molecular significance of microvascular inflammation in transplant kidney biopsies.

The diagnostic criteria for antibody-mediated rejection (AMR) are continuously evolving. Here we investigated the clinical and molecular significance of different Banff microvascular inflammation (MVI) scores in transplant kidney biopsies. A total of 356 patients with clinically indicated kidney transplant biopsies were classified into three groups based on MVI scores of 0, 1, 2, or more for Groups 1-3, respectively. Gene expression profiles were assessed using arrays on a representative subset of 93 patients. The incidence of donor-specific anti-HLA antibodies was increased from 25% in Group 1 to 36% in Group 2 and to 54% in Group 3. Acute and chronic AMR were significantly more frequent in Group 3 (15% and 35%) compared with the Group 2 (3% and 15%) and Group 1 (0% and 5%), respectively. Gene expression profiles showed increased interferon-γ and rejection-induced, cytotoxic and regulatory T-cell, natural killer cell-associated and donor-specific antibody (DSA)-selective transcripts in Group 3 compared with Groups 1 and 2. There was no significant difference in gene expression profiles between the Groups 1 and 2. Increased intragraft expression of DSA-selective transcripts was found in the biopsies of C4d- Group 3 patients. Thus, an MVI score of 2 or more was significantly associated with a histological diagnosis of acute and chronic antibody-mediated rejection. Hence, increased intragraft DSA-selective gene transcripts may be used as molecular markers for AMR, especially in C4d- biopsies.

Alignment-free clustering of transcription factor binding motifs using a genetic-k-medoids approach.

BACKGROUND: Familial binding profiles (FBPs) represent the average binding specificity for a group of structurally related DNA-binding proteins. The construction of such profiles allows the classification of novel motifs based on similarity to known families, can help to reduce redundancy in motif databases and de novo prediction algorithms, and can provide valuable insights into the evolution of binding sites. Many current approaches to automated motif clustering rely on progressive tree-based techniques, and can suffer from so-called frozen sub-alignments, where motifs which are clustered early on in the process remain 'locked' in place despite the potential for better placement at a later stage. In order to avoid this scenario, we have developed a genetic-k-medoids approach which allows motifs to move freely between clusters at any point in the clustering process. RESULTS: We demonstrate the performance of our algorithm, GMACS, on multiple benchmark motif datasets, comparing results obtained with current leading approaches. The first dataset includes 355 position weight matrices from the TRANSFAC database and indicates that the k-mer frequency vector approach used in GMACS outperforms other motif comparison techniques. We then cluster a set of 79 motifs from the JASPAR database previously used in several motif clustering studies and demonstrate that GMACS can produce a higher number of structurally homogeneous clusters than other methods without the need for a large number of singletons. Finally, we show the robustness of our algorithm to noise on multiple synthetic datasets consisting of known motifs convolved with varying degrees of noise. CONCLUSIONS: Our proposed algorithm is generally applicable to any DNA or protein motifs, can produce highly stable and biologically meaningful clusters, and, by avoiding the problem of frozen sub-alignments, can provide improved results when compared with existing techniques on benchmark datasets.

Increased intragraft rejection-associated gene transcripts in patients with donor-specific antibodies and normal biopsies.

We investigated why some donor-specific antibody-positive patients do not develop antibody-mediated rejection. Of 71 donor-specific antibody-positive patients, 46 had diagnosis of antibody-mediated rejection and 25 had normal biopsies. Fifty donor-specific antibody-negative patients with normal biopsies were used as a control group. A subgroup of 61 patients with available biopsy and 64 with blood samples were analyzed by microarrays. Both donor-specific antibody-positive/antibody-mediated rejection-positive and negative biopsies showed increased expression of gene transcripts associated with cytotoxic T cells, natural killer cells, macrophages, interferon-gamma, and rejection compared to donor-specific antibody-negative biopsies. Regulatory T-cell transcripts were upregulated in donor-specific antibody-positive/antibody-mediated rejection-positive and B-cell transcripts in donor-specific antibody-positive/antibody-mediated rejection-negative biopsies. Whole-blood gene expression analysis showed increased immune activity in only donor-specific antibody-positive/antibody-mediated rejection-positive but not negative patients. During a median follow-up of 36 months, 4 donor-specific antibody-positive/antibody-mediated rejection-negative patients developed antibody-mediated rejection, 12 continued to have donor-specific antibody, but 9 lost their donor-specific antibody. Gene expression profiles did not predict the development of antibody-mediated rejection or the persistence of donor-specific antibody. Thus, donor-specific antibody-positive/antibody-mediated rejection-negative patients had increased rejection-associated gene transcripts in their allografts despite no histologic findings of rejection but not in their blood. This was found in both biopsy and blood samples of donor-specific antibody-positive/antibody-mediated rejection-positive patients.

Gene-set analysis is severely biased when applied to genome-wide methylation data.

MOTIVATION: DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used, for example, to identify processes or pathways that are perturbed in disease development. We show that gene-set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters. RESULTS: We demonstrate this bias using published data from a study of differential CpG island methylation in lung cancer and a dataset we generated to study methylation changes in patients with long-standing ulcerative colitis. We show that several of the gene sets that seem enriched would also be identified with randomized data. We suggest two existing approaches that can be adapted to correct the bias. Accounting for the bias in the lung cancer and ulcerative colitis datasets provides novel biological insights into the role of methylation in cancer development and chronic inflammation, respectively. Our results have significant implications for many previous genome-wide methylation studies that have drawn conclusions on the basis of such strongly biased analysis. CONTACT: cathal.seoighe@nuigalway.ie SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Wasp System: an open source environment for managing and analyzing genomic data.

The challenges associated with the management, analysis and interpretation of assays based on massively-parallel sequencing (MPS) are both individually complex and numerous. We describe what we believe to be the appropriate solution, one that represents a departure from traditional computational biology approaches. The Wasp System is an open source, distributed package written in Spring/J2EE that creates a foundation for development of an end-to-end solution for MPS-based experiments or clinical tests. Recognizing that one group will be unable to solve these challenges in isolation, we describe a nurtured open source development model that will allow the software to be collectively used, shared and developed. The ultimate goal is to emulate resources such as the Virtual Observatory of the astrophysics community, enabling computationally-inexpert scientists and clinicians to explore and interpret their MPS data. Here we describe the current implementation and development of the Wasp System and the roadmap for its community development.

Teaching graduate research skills in genomics via an integrated 'flipped' journal club program.

Journal clubs are well regarded as a highly effective means of engaging graduate students with the contemporary research literature, where individual students prepare and deliver presentations on selected research articles to their peers, followed by a group discussion. Regular journal clubs have the advantage of enhancing student scientific reading, assessment and communication skills as well as developing a better understanding of the field. We developed a flipped journal club program as part of the one semester module 'Genomics Research Methods' with the goal of enhancing-and quantifying-individual student ability to engage with the genomics scientific literature. This involves all students and faculty reviewing a given manuscript, with the former submitting research relevant questions they would wish to ask the presenting student at the journal club, and the latter grading them. These questions are then ranked based on their median grade, and subsequently discussed in class. This cycle repeats weekly until all students have presented. Our analysis of question grade data over three consecutive years demonstrated clear improvements in student performance for all students between the start and end of the module. While no difference in performance was noted based on gender over the full semester, improvement in performance was significantly evident for the female cohort between the start and end of the module. Our results are consistent with module survey feedback of overall reported enhanced research self-efficacy. This demonstrates that this flipped journal club implementation is a highly effective means of both assessing and improving individual student learning in genomics research ability. The involvement of the teaching faculty furthermore offers a means to foster a dynamic research community for all participants involved. This methodology is easily transferable to other bioscience graduate/undergraduate programs seeking to effectively teach essential research ability skills and enhance student self-efficacy.

The regulatory effect of miRNAs is a heritable genetic trait in humans.

BACKGROUND: microRNAs (miRNAs) have been shown to regulate the expression of a large number of genes and play key roles in many biological processes. Several previous studies have quantified the inhibitory effect of a miRNA indirectly by considering the expression levels of genes that are predicted to be targeted by the miRNA and this approach has been shown to be robust to the choice of prediction algorithm. Given a gene expression dataset, Cheng et al. defined the regulatory effect score (RE-score) of a miRNA as the difference in the gene expression rank of targets of the miRNA compared to non-targeted genes. RESULTS: Using microarray data from parent-offspring trios from the International HapMap project, we show that the RE-score of most miRNAs is correlated between parents and offspring and, thus, inter-individual variation in RE-score has a genetic component in humans. Indeed, the mean RE-score across miRNAs is correlated between parents and offspring, suggesting genetic differences in the overall efficiency of the miRNA biogenesis pathway between individuals. To explore the genetics of this quantitative trait further, we carried out a genome-wide association study of the mean RE-score separately in two HapMap populations (CEU and YRI). No genome-wide significant associations were discovered; however, a SNP rs17409624, in an intron of DROSHA, was significantly associated with mean RE-score in the CEU population following permutation-based control for multiple testing based on all SNPs mapped to the canonical miRNA biogenesis pathway; of 244 individual miRNA RE-scores assessed in the CEU, 214 were associated (p < 0.05) with rs17409624. The SNP was also nominally significantly associated (p = 0.04) with mean RE-score in the YRI population. Interestingly, the same SNP was associated with 17 (8.5% of all expressed) miRNA expression levels in the CEU. We also show here that the expression of the targets of most miRNAs is more highly correlated with global changes in miRNA regulatory effect than with the expression of the miRNA itself. CONCLUSIONS: We present evidence that miRNA regulatory effect is a heritable trait in humans and that a polymorphism of the DROSHA gene contributes to the observed inter-individual differences.

An integrated genome screen identifies the Wnt signaling pathway as a major target of WT1.

WT1, a critical regulator of kidney development, is a tumor suppressor for nephroblastoma but in some contexts functions as an oncogene. A limited number of direct transcriptional targets of WT1 have been identified to explain its complex roles in tumorigenesis and organogenesis. In this study we performed genome-wide screening for direct WT1 targets, using a combination of ChIP-ChIP and expression arrays. Promoter regions bound by WT1 were highly G-rich and resembled the sites for a number of other widely expressed transcription factors such as SP1, MAZ, and ZNF219. Genes directly regulated by WT1 were implicated in MAPK signaling, axon guidance, and Wnt pathways. Among directly bound and regulated genes by WT1, nine were identified in the Wnt signaling pathway, suggesting that WT1 modulates a subset of Wnt components and responsive genes by direct binding. To prove the biological importance of the interplay between WT1 and Wnt signaling, we showed that WT1 blocked the ability of Wnt8 to induce a secondary body axis during Xenopus embryonic development. WT1 inhibited TCF-mediated transcription activated by Wnt ligand, wild type and mutant, stabilized beta-catenin by preventing TCF4 loading onto a promoter. This was neither due to direct binding of WT1 to the TCF binding site nor to interaction between WT1 and TCF4, but by competition of WT1 and TCF4 for CBP. WT1 interference with Wnt signaling represents an important mode of its action relevant to the suppression of tumor growth and guidance of development.

The Einstein Genome Gateway using WASP - a high throughput multi-layered life sciences portal for XSEDE.

Massively-parallel sequencing (MPS) technologies and their diverse applications in genomics and epigenomics research have yielded enormous new insights into the physiology and pathophysiology of the human genome. The biggest hurdle remains the magnitude and diversity of the datasets generated, compromising our ability to manage, organize, process and ultimately analyse data. The Wiki-based Automated Sequence Processor (WASP), developed at the Albert Einstein College of Medicine (hereafter Einstein), uniquely manages to tightly couple the sequencing platform, the sequencing assay, sample metadata and the automated workflows deployed on a heterogeneous high performance computing cluster infrastructure that yield sequenced, quality-controlled and 'mapped' sequence data, all within the one operating environment accessible by a web-based GUI interface. WASP at Einstein processes 4-6 TB of data per week and since its production cycle commenced it has processed ~ 1 PB of data overall and has revolutionized user interactivity with these new genomic technologies, who remain blissfully unaware of the data storage, management and most importantly processing services they request. The abstraction of such computational complexity for the user in effect makes WASP an ideal middleware solution, and an appropriate basis for the development of a grid-enabled resource - the Einstein Genome Gateway - as part of the Extreme Science and Engineering Discovery Environment (XSEDE) program. In this paper we discuss the existing WASP system, its proposed middleware role, and its planned interaction with XSEDE to form the Einstein Genome Gateway.

Exploring breast and prostate cancer RNA-seq derived radiosensitivity with the Genomic Adjusted Radiation Dose (GARD) model.

The use of a 10 gene transcriptional signature as part of the GARD model has been shown to be predictive of radiotherapy benefit for a range of cancers, with the potential to determine an optimal overall dose per patient. We used publicly available RNA-seq transcriptomics data from a luminal B breast cancer patient and from 14 prostate cancer patients to explore the radiosensitivity indices (RSI) and so GARD estimates of both tumour and proximal normal biopsies from each individual. Clear differences of clinical relevance in derived radiobiological properties between tumour and proximal normal tissues were evident for the breast cancer patient, whilst such differences across the prostate cancer cohort were more equivocal. Using the prostate cancer cohort's median tumour predicted GARD value as a threshold for high therapeutic effect for radiotherapy, we found evidence that a higher overall prescribed dose than the widely used 72 Gy/36fx could benefit half of these patients. This exploratory study demonstrates the potential combining the GARD model with sequencing based transcriptomics could have in informing personalised radiotherapeutic practise for both breast and prostate cancer patients.

GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal.

Exploratory analysis of cancer consortia data curated by the cBioPortal repository typically requires advanced programming skills and expertise to identify novel genomic prognostic markers that have the potential for both diagnostic and therapeutic exploitation. We developed GNOSIS (GeNomics explOrer using StatistIcal and Survival analysis in R), an R Shiny App incorporating a range of R packages enabling users to efficiently explore and visualise such clinical and genomic data. GNOSIS provides an intuitive graphical user interface and multiple tab panels supporting a range of functionalities, including data upload and initial exploration, data recoding and subsetting, data visualisations, statistical analysis, mutation analysis and, in particular, survival analysis to identify prognostic markers. GNOSIS also facilitates reproducible research by providing downloadable input logs and R scripts from each session, and so offers an excellent means of supporting clinician-researchers in developing their statistical computing skills.

Loss of MMR and TGFBR2 Increases the Susceptibility to Microbiota-Dependent Inflammation-Associated Colon Cancer.

BACKGROUND AND AIMS: Mutations in DNA mismatch repair (MMR) genes are causative in Lynch syndrome and a significant proportion of sporadic colorectal cancers (CRCs). MMR-deficient (dMMR) CRCs display increased mutation rates, with mutations frequently accumulating at short repetitive DNA sequences throughout the genome (microsatellite instability). The TGFBR2 gene is one of the most frequently mutated genes in dMMR CRCs. Therefore, we generated an animal model to study how the loss of both TGFBR2 signaling impacts dMMR-driven intestinal tumorigenesis in vivo and explore the impact of the gut microbiota. METHODS: We generated VCMsh2/Tgfbr2 mice in which Msh2loxP and Tgfbr2loxP alleles are inactivated by Villin-Cre recombinase in the intestinal epithelium. VCMsh2/Tgfbr2 mice were analyzed for their rate of intestinal cancer development and for the mutational spectra and gene expression profiles of tumors. In addition, we assessed the impact of chemically induced chronic inflammation and gut microbiota composition on colorectal tumorigenesis. RESULTS: VCMsh2/Tgfbr2 mice developed small intestinal adenocarcinomas and CRCs with histopathological features highly similar to CRCs in Lynch syndrome patients. The CRCs in VCMsh2/Tgfbr2 mice were associated with the presence of colitis and displayed genetic and histological features that resembled inflammation-associated CRCs in human patients. The development of CRCs in VCMsh2/Tgfbr2 mice was strongly modulated by the gut microbiota composition, which in turn was impacted by the TGFBR2 status of the tumors. CONCLUSIONS: Our results demonstrate a synergistic interaction between MMR and TGFBR2 inactivation in inflammation-associated colon tumorigenesis and highlight the crucial impact of the gut microbiota on modulating the incidence of inflammation-associated CRCs.

Survival outcomes are associated with genomic instability in luminal breast cancers.

Breast cancer is the leading cause of cancer related death among women. Breast cancers are generally diagnosed and treated based on clinical and histopathological features, along with subtype classification determined by the Prosigna Breast Cancer Prognostic Gene Signature Assay (also known as PAM50). Currently the copy number alteration (CNA) landscape of the tumour is not considered. We set out to examine the role of genomic instability (GI) in breast cancer survival since CNAs reflect GI and correlate with survival in other cancers. We focused on the 70% of breast cancers classified as luminal and carried out a comprehensive survival and association analysis using Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data to determine whether CNA Score Quartiles derived from absolute CNA counts are associated with survival. Analysis revealed that patients diagnosed with luminal A breast cancer have a CNA landscape associated with disease specific survival, suggesting that CNA Score can provide a statistically robust prognostic factor. Furthermore, stratification of patients into subtypes based on gene expression has shown that luminal A and B cases overlap, and it is in this region we largely observe luminal A cases with reduced survival outlook. Therefore, luminal A breast cancer patients with quantitatively elevated CNA counts may benefit from more aggressive therapy. This demonstrates how individual genomic landscapes can facilitate personalisation of therapeutic interventions to optimise survival outcomes.

BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

SUMMARY: BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. AVAILABILITY: BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

A review of subtidal kelp forests in Ireland: From first descriptions to new habitat monitoring techniques.

AIM: Kelp forests worldwide are important marine ecosystems that foster high primary to secondary productivity and multiple ecosystem services. These ecosystems are increasingly under threat from extreme storms, changing ocean temperatures, harvesting, and greater herbivore pressure at regional and global scales, necessitating urgent documentation of their historical to present-day distributions. Species range shifts to higher latitudes have already been documented in some species that dominate subtidal habitats within Europe. Very little is known about kelp forest ecosystems in Ireland, where rocky coastlines are dominated by Laminaria hyperborea. In order to rectify this substantial knowledge gap, we compiled historical records from an array of sources to present historical distribution, kelp and kelp forest recording effort over time, and present rational for the monitoring of kelp habitats to better understand ecosystem resilience. LOCATION: Ireland (Northern Ireland and Éire). METHODS: Herbaria, literature from the Linnaean society dating back to late 1700s, journal articles, government reports, and online databases were scoured for information on L. hyperborea. Information about kelp ecosystems was solicited from dive clubs and citizen science groups that are active along Ireland's coastlines. RESULTS: Data were used to create distribution maps and analyze methodology and technology used to record L. hyperborea presence and kelp ecosystems within Ireland. We discuss the recent surge in studies on Irish kelp ecosystems, fauna associated with kelp ecosystems that may be used as indicators of ecosystem health and suggest methodologies for continued monitoring. MAIN CONCLUSIONS: While there has been a steady increase in recording effort of the dominant subtidal kelp forest species, L. hyperborea, only recently have studies begun to address other important eco-evolutionary processes at work in kelp forests including connectivity among kelp populations in Ireland. Further monitoring, using suggested methodologies, is required to better understand the resilience of kelp ecosystems in Ireland.

Correction: Septin 9 isoforms promote tumorigenesis in mammary epithelial cells by increasing migration and ECM degradation through metalloproteinase secretion at focal adhesions.

The original version of this Article contained an error in the author affiliations. Vladislav V. Verkhusha was incorrectly associated with the School of Mathematics, Statistics & Applied Mathematics, National University of Ireland Galway, Galway, Ireland. The correct affiliation is Anatomy and Structural Biology, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA.

CG dinucleotide clustering is a species-specific property of the genome.

Cytosines at cytosine-guanine (CG) dinucleotides are the near-exclusive target of DNA methyltransferases in mammalian genomes. Spontaneous deamination of methylcytosine to thymine makes methylated cytosines unusually susceptible to mutation and consequent depletion. The loci where CG dinucleotides remain relatively enriched, presumably due to their unmethylated status during the germ cell cycle, have been referred to as CpG islands. Currently, CpG islands are solely defined by base compositional criteria, allowing annotation of any sequenced genome. Using a novel bioinformatic approach, we show that CG clusters can be identified as an inherent property of genomic sequence without imposing a base compositional a priori assumption. We also show that the CG clusters co-localize in the human genome with hypomethylated loci and annotated transcription start sites to a greater extent than annotations produced by prior CpG island definitions. Moreover, this new approach allows CG clusters to be identified in a species-specific manner, revealing a degree of orthologous conservation that is not revealed by current base compositional approaches. Finally, our approach is able to identify methylating genomes (such as Takifugu rubripes) that lack CG clustering entirely, in which it is inappropriate to annotate CpG islands or CG clusters.