Gene clusters, molecular evolution and disease: a speculation

A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Emerging trends in genomic and epigenomic regulation of plant specialised metabolism

Regulation of specialised metabolism genes is multilayered and complex, influenced by an array of genomic, epigenetic and epigenomic mechanisms. Here, we review the most recent knowledge in this field, drawing from discoveries in several plant species. Our aim is to improve understanding of how plant genome structure and function influence specialised metabolism. We also highlight key areas for future exploration. Gene regulatory mechanisms influencing specialised metabolism include gene duplication and neo-functionalization, conservation of operon-like clusters of specialised metabolism genes, local chromatin modifications, and the organisation of higher order chromatin structures within the nucleus. Genomic and epigenomic research to-date in the discipline have focused on a relatively small number of plant species, primarily at whole organ or tissue level. This is largely due to the technical demands of the experimental methods needed. However, a high degree of cell-type specificity of function exists in specialised metabolism, driven by similarly specific gene regulation. In this review we focus on the genomic characteristics of genes that are found in different types of clusters within the genome. We propose that acquisition of cell-resolution epigenomic datasets in emerging models, such as the glandular trichomes of Cannabis sativa, will yield important advances. Data such as chromatin accessibility and histone modification profiles can pinpoint which regulatory sequences are active in individual cell types and at specific times in development. These could provide fundamental biological insight as well as novel targets for genetic engineering and crop improvement.

Genome-enabled discovery of candidate virulence loci in Striga hermonthica, a devastating parasite of African cereal crops

Parasites have evolved proteins, virulence factors (VFs), that facilitate plant colonisation, however VFs mediating parasitic plant-host interactions are poorly understood. Striga hermonthica is an obligate, root-parasitic plant of cereal hosts in sub-Saharan Africa, causing devastating yield losses. Understanding the molecular nature and allelic variation of VFs in S. hermonthica is essential for breeding resistance and delaying the evolution of parasite virulence. We assembled the S. hermonthica genome and identified secreted proteins using in silico prediction. Pooled sequencing of parasites growing on a susceptible and a strongly resistant rice host allowed us to scan for loci where selection imposed by the resistant host had elevated the frequency of alleles contributing to successful colonisation. Thirty-eight putatively secreted VFs had very different allele frequencies with functions including host cell wall modification, protease or protease inhibitor and kinase activities. These candidate loci had significantly higher Tajima's D than the genomic background, consistent with balancing selection. Our results reveal diverse strategies used by S. hermonthica to overcome different layers of host resistance. Understanding the maintenance of variation at virulence loci by balancing selection will be critical to managing the evolution of virulence as part of a sustainable control strategy.

Many faces and functions of GSKIP: a temporospatial regulation view

Glycogen synthase kinase 3 (GSK3)-β (GSK3β) interaction protein (GSKIP) is one of the smallest A-kinase anchoring proteins that possesses a binding site for GSK3β. Recently, our group identified the protein kinase A (PKA)-GSKIP-GSK3β-X axis; knowledge of this axis may help us decipher the many roles of GSKIP and perhaps help explain the evolutionary reason behind the interaction between GSK3β and PKA. In this review, we highlight the critical and multifaceted role of GSKIP in facilitating PKA kinase activity and its function as a scaffolding protein in signaling pathways. We also highlight how these pivotal PKA and GSK3 kinases can control context-specific functions and interact with multiple target proteins, such as β-catenin, Drp1, Tau, and other proteins. GSKIP is a key regulator of multiple mechanisms because of not only its location at certain subcellular compartments but also its serial changes during the developmental process. Moreover, the involvement of critical upstream regulatory signaling pathways in GSKIP signaling in various cancers, such as miRNA (microRNA) and lncRNA (long noncoding RNA), may help in the identification of therapeutic targets in the era of precision medicine and personalized therapy. Finally, we emphasize on the model of the early stage of pathogenesis of Alzheimer Disease (AD). Although the model requires validation, it can serve as a basis for diagnostic biomarkers development and drug discovery for early-stage AD.

Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer

Background

Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types.

Methods

In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction.

Results

We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway.

Conclusions

Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03179-5.

Trends and Applications of Omics Technologies to Functional Characterisation of Enzymes and Protein Metabolites Produced by Fungi

Identifying and adopting industrial applications for proteins and enzymes derived from fungi strains have been at the focal point of several studies in recent times. To facilitate such studies, it is necessary that advancements and innovation in mycological and molecular characterisation are concomitant. This review aims to provide a detailed overview of the necessary steps employed in both qualitative and quantitative research using the omics technologies that are pertinent to fungi characterisation. This stems from the understanding that data provided from the functional characterisation of fungi and their metabolites is important towards the techno-economic feasibility of large-scale production of biological products. The review further describes how the functional gaps left by genomics, internal transcribe spacer (ITS) regions are addressed by transcriptomics and the various techniques and platforms utilised, including quantitive reverse transcription polymerase chain reaction (RT-qPCR), hybridisation techniques, and RNA-seq, and the insights such data provide on the effect of environmental changes on fungal enzyme production from an expressional standpoint. The review also offers information on the many available bioinformatics tools of analysis necessary for the analysis of the overwhelming data synonymous with the omics approach to fungal characterisation.

Plant Metabolic Gene Clusters: Evolution, Organization, and Their Applications in Synthetic Biology

Plants are a remarkable source of high-value specialized metabolites having significant physiological and ecological functions. Genes responsible for synthesizing specialized metabolites are often clustered together for a coordinated expression, which is commonly observed in bacteria and filamentous fungi. Similar to prokaryotic gene clustering, plants do have gene clusters encoding enzymes involved in the biosynthesis of specialized metabolites. More than 20 gene clusters involved in the biosynthesis of diverse metabolites have been identified across the plant kingdom. Recent studies demonstrate that gene clusters are evolved through gene duplications and neofunctionalization of primary metabolic pathway genes. Often, these clusters are tightly regulated at nucleosome level. The prevalence of gene clusters related to specialized metabolites offers an attractive possibility of an untapped source of highly useful biomolecules. Accordingly, the identification and functional characterization of novel biosynthetic pathways in plants need to be worked out. In this review, we summarize insights into the evolution of gene clusters and discuss the organization and importance of specific gene clusters in the biosynthesis of specialized metabolites. Regulatory mechanisms which operate in some of the important gene clusters have also been briefly described. Finally, we highlight the importance of gene clusters to develop future metabolic engineering or synthetic biology strategies for the heterologous production of novel metabolites.

Homeotic Genes: Clustering, Modularity, and Diversity

Hox genes code for transcription factors and are evolutionarily conserved. They regulate a plethora of downstream targets to define the anterior-posterior (AP) body axis of a developing bilaterian embryo. Early work suggested a possible role of clustering and ordering of Hox to regulate their expression in a spatially restricted manner along the AP axis. However, the recent availability of many genome assemblies for different organisms uncovered several examples that defy this constraint. With recent advancements in genomics, the current review discusses the arrangement of Hox in various organisms. Further, we revisit their discovery and regulation in Drosophila melanogaster. We also review their regulation in different arthropods and vertebrates, with a significant focus on Hox expression in the crustacean Parahyale hawaiensis. It is noteworthy that subtle changes in the levels of Hox gene expression can contribute to the development of novel features in an organism. We, therefore, delve into the distinct regulation of these genes during primary axis formation, segment identity, and extra-embryonic roles such as in the formation of hair follicles or misregulation leading to cancer. Toward the end of each section, we emphasize the possibilities of several experiments involving various organisms, owing to the advancements in the field of genomics and CRISPR-based genome engineering. Overall, we present a holistic view of the functioning of Hox in the animal world.

Deletion of a Seminal Gene Cluster Reinforces a Crucial Role of SVS2 in Male Fertility

Multiple genes, whose functions or expression are overlapping, compensate for the loss of one gene. A gene cluster in the mouse genome encodes five seminal vesicle proteins (SVS2, SVS3, SVS4, SVS5, and SVS6). These proteins are produced by male rodents and function in formation of the copulatory plug following mating. SVS2 plays an essential role in the successful internal fertilization by protecting the sperm membrane against a uterine immune attack. We hypothesized that the four remaining seminal vesicle proteins (SVPs) of this gene cluster may partially/completely compensate for the deficiency of SVS2. For confirming our hypothesis, we generated mice lacking the entire SVP-encoding gene cluster and compared their fecundity with Svs2-deficient (Svs2^−/−) mice; that is, mice deficient in Svs2 alone. A single loxP site remained after the deletion of the Svs2 gene. Therefore, we inserted another loxP site by combining the CRISPR/Cas9 system with single-stranded oligodeoxynucleotides (ssODN). Male mice lacking the entire SVP-encoding gene cluster (Svs2–6^−/− mice) and thereby all five SVP proteins, generated by the deletion of 100kbp genomic DNA, showed low fecundity. However, the fecundity level was comparable with that from Svs2^−/− male mice. Our results demonstrate that SVS3, SVS4, SVS5, and SVS6 do not function in the protection of sperm against a uterine immune attack in the absence of SVS2. Thus, Svs2 is the critical gene in the SVP gene cluster.

A complete annotation of the chromosomes of the cellulase producer Trichoderma reesei provides insights in gene clusters, their expression and reveals genes required for fitness

BACKGROUND

Investigations on a few eukaryotic model organisms showed that many genes are non-randomly distributed on chromosomes. In addition, chromosome ends frequently possess genes that are important for the fitness of the organisms. Trichoderma reesei is an industrial producer of enzymes for food, feed and biorefinery production. Its seven chromosomes have recently been assembled, thus making an investigation of its chromosome architecture possible.

RESULTS

We manually annotated and mapped 9194 ORFs on their respective chromosomes and investigated the clustering of the major gene categories and of genes encoding carbohydrate-active enzymes (CAZymes), and the relationship between clustering and expression. Genes responsible for RNA processing and modification, amino acid metabolism, transcription, translation and ribosomal structure and biogenesis indeed showed loose clustering, but this had no impact on their expression. A third of the genes encoding CAZymes also occurred in loose clusters that also contained a high number of genes encoding small secreted cysteine-rich proteins. Five CAZyme clusters were located less than 50 kb apart from the chromosome ends. These genes exhibited the lowest basal (but not induced) expression level, which correlated with an enrichment of H3K9 methylation in the terminal 50 kb areas indicating gene silencing. No differences were found in the expression of CAZyme genes present in other parts of the chromosomes. The putative subtelomeric areas were also enriched in genes encoding secreted proteases, amino acid permeases, enzyme clusters for polyketide synthases (PKS)-non-ribosomal peptide synthase (NRPS) fusion proteins (PKS-NRPS) and proteins involved in iron scavenging. They were strongly upregulated during conidiation and interaction with other fungi.

CONCLUSIONS

Our findings suggest that gene clustering on the T. reesei chromosomes occurs but generally has no impact on their expression. CAZyme genes, located in subtelomers, however, exhibited a much lower basal expression level. The gene inventory of the subtelomers suggests a major role of competition for nitrogen and iron supported by antibiosis for the fitness of T. reesei. The availability of fully annotated chromosomes will facilitate the use of genetic crossings in identifying still unknown genes responsible for specific traits of T. reesei.

Clustering of gene ontology terms in genomes

Although protein coding genes occupy only a small fraction of genomes in higher species, they are not randomly distributed within or between chromosomes. Clustering of genes with related function(s) and/or characteristics has been evident at several different levels. To study how common the clustering of functionally related genes is and what kind of functions the end products of these genes are involved, we collected gene ontology (GO) terms for complete genomes and developed a method to detect previously undefined gene clustering. Exhaustive analysis was performed for seven widely studied species ranging from human to Escherichia coli. To overcome problems related to varying gene lengths and densities, a novel method was developed and a fixed number of genes were analyzed irrespective of the genome span covered. Statistically very significant GO term clustering was apparent in all the investigated genomes. The analysis window, which ranged from 5 to 50 consecutive genes, revealed extensive GO term clusters for genes with widely varying functions. Here, the most interesting and significant results are discussed and the complete dataset for each analyzed species is available at the GOme database at http://bioinf.uta.fi/GOme. The results indicated that clusters of genes with related functions are very common, not only in bacteria, in which operons are frequent, but also in all the studied species irrespective of how complex they are. There are some differences between species but in all of them GO term clusters are common and of widely differing sizes. The presented method can be applied to analyze any genome or part of a genome for which descriptive features are available, and thus is not restricted to ontology terms. This method can also be applied to investigate gene and protein expression patterns. The results pave a way for further studies of mechanisms that shape genome structure and evolutionary forces related to them.

Chapter 15: disease gene prioritization

Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases.

Genome-Wide Detection of Gene Coexpression Domains Showing Linkage to Regions Enriched with Polymorphic Retrotransposons in Recombinant Inbred Mouse Strains

Although gene coexpression domains have been reported in most eukaryotic organisms, data available to date suggest that coexpression rarely concerns more than doublets or triplets of adjacent genes in mammals. Using expression data from hearts of mice from the panel of AxB/BxA recombinant inbred mice, we detected (according to window sizes) 42−53 loci linked to the expression levels of clusters of three or more neighboring genes. These loci thus formed “cis-expression quantitative trait loci (eQTL) clusters” because their position matched that of the genes whose expression was linked to the loci. Compared with matching control regions, genes contained within cis-eQTL clusters showed much greater levels of coexpression. Corresponding regions showed: (1) a greater abundance of polymorphic elements (mostly short interspersed element retrotransposons), and (2) significant enrichment for the motifs of binding sites for various transcription factors, with binding sites for the chromatin-organizing CCCTC-binding factor showing the greatest levels of enrichment in polymorphic short interspersed elements. Similar cis-eQTL clusters also were detected when we used data obtained with several tissues from BxD recombinant inbred mice. In addition to strengthening the evidence for gene expression domains in mammalian genomes, our data suggest a possible mechanism whereby noncoding polymorphisms could affect the coordinate expression of several neighboring genes.

Catecholamine-related gene expression in blood correlates with tic severity in tourette syndrome

Tourette syndrome (TS) is a heritable disorder characterized by tics that are decreased in some patients by treatment with alpha adrenergic agonists and dopamine receptor blockers. Thus, this study examines the relationship between catecholamine gene expression in blood and tic severity. TS diagnosis was confirmed using Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria and tic severity measured using the Yale Global Tic Severity Scale (YGTSS) for 26 un-medicated subjects with TS. Whole blood was collected and Ribonucleic acid (RNA) processed on Affymetrix Human Exon 1.0 ST arrays. An Analysis of Covariance (ANCOVA) identified 3627 genes correlated with tic severity (p<0.05). Searches of Medical Subject Headings, Gene Ontology, Allen Mouse Brain Atlas, and PubMed determined genes associated with catecholamines and located in the basal ganglia. Using GeneCards, PubMed, and manual curation, seven genes associated with TS were further examined: DRD2, HRH3, MAOB, BDNF, SNAP25, SLC6A4, and SLC22A3. These genes are highly associated with TS and have also been implicated in other movement disorders, Attention Deficit Hyperactivity Disorder (ADHD), and Obsessive-Compulsive Disorder (OCD). Correlation of gene expression in peripheral blood with tic severity may allow inferences about catecholamine pathway dysfunction in TS subjects. Findings built on previous work suggest that at least some genes expressed peripherally are relevant for central nervous system (CNS) pathology in the brain of individuals with TS.

Intrinsic features of Aedes aegypti genes affect transcriptional responsiveness of mosquito genes to dengue virus infection

Dengue virus infection causes significant morbidity and mortality in humans world-wide. The Aedes aegypti mosquito is the major vector that spreads dengue virus to humans. Interaction between dengue viruses and A. aegypti is a multi-factorial phenomena that is determined by both virus and mosquito genotypes. Although, studies have suggested significant association of mosquito vectorial capacity with population variation of dengue virus, specifications of the vector factors that may influence vector-virus compatibility are very limited in the literature. Recently, we have shown that a large number of genes are differentially expressed between MOYO-S (susceptible) and MOYO-R (refractory) A. aegypti strains upon infection with dengue virus (JAM-1409 genotype). In the current study, we show that specific intrinsic features of A. aegypti genes are significantly associated with 'responsiveness' of mosquito genes to dengue infection. Binomial logistic regression analysis further reveals differential marginal effects of these features on gene responsiveness of mosquitoes to the viral infection. Thus, our result shows that intrinsic features of genes significantly affect differential expression of A. aegypti genes to dengue infection. The information will benefit further investigations on evolution of genes among natural populations of A. aegypti conferring differential susceptibility to dengue virus.

Bioinformatics for personal genome interpretation

An international consortium released the first draft sequence of the human genome 10 years ago. Although the analysis of this data has suggested the genetic underpinnings of many diseases, we have not yet been able to fully quantify the relationship between genotype and phenotype. Thus, a major current effort of the scientific community focuses on evaluating individual predispositions to specific phenotypic traits given their genetic backgrounds. Many resources aim to identify and annotate the specific genes responsible for the observed phenotypes. Some of these use intra-species genetic variability as a means for better understanding this relationship. In addition, several online resources are now dedicated to collecting single nucleotide variants and other types of variants, and annotating their functional effects and associations with phenotypic traits. This information has enabled researchers to develop bioinformatics tools to analyze the rapidly increasing amount of newly extracted variation data and to predict the effect of uncharacterized variants. In this work, we review the most important developments in the field--the databases and bioinformatics tools that will be of utmost importance in our concerted effort to interpret the human variome.

Disruption of genomic neighbourhood at the imprinted IGF2-H19 locus in Beckwith-Wiedemann syndrome and Silver-Russell syndrome

Hyper- and hypomethylation at the IGF2-H19 imprinting control region (ICR) result in reciprocal changes in IGF2-H19 expression and the two contrasting growth disorders, Beckwith-Wiedemann syndrome (BWS) and Silver-Russell syndrome (SRS). DNA methylation of the ICR controls the reciprocal imprinting of IGF2 and H19 by preventing the binding of the insulator protein, CTCF. We here show that local changes in histone modifications and CTCF--cohesin binding at the ICR in BWS and SRS together with DNA methylation correlate with the higher order chromatin structure at the locus. In lymphoblastoid cells from control individuals, we found the repressive histone H3K9me3 and H4K20me3 marks associated with the methylated paternal ICR allele and the bivalent H3K4me2/H3K27me3 mark together with H3K9ac and CTCF--cohesin associated with the non-methylated maternal allele. In patient-derived cell lines, the mat/pat asymmetric distribution of these epigenetic marks was lost with H3K9me3 and H4K20me3 becoming biallelic in the BWS and H3K4me2, H3K27me3 and H3K9ac together with CTCF-cohesin becoming biallelic in the SRS. We further show that in BWS and SRS cells, there is opposing chromatin looping conformation mediated by CTCF--cohesin binding sites surrounding the locus. In normal cells, lack of CTCF--cohesin binding at the paternal ICR is associated with monoallelic interaction between two CTCF sites flanking the locus. CTCF--cohesin binding at the maternal ICR blocks this interaction by associating with the CTCF site downstream of the enhancers. The two alternative chromatin conformations are differently favoured in BWS and SRS likely predisposing the locus to the activation of IGF2 or H19, respectively.

Genome evolution following host jumps in the Irish potato famine pathogen lineage

Many plant pathogens, including those in the lineage of the Irish potato famine organism Phytophthora infestans, evolve by host jumps followed by specialization. However, how host jumps affect genome evolution remains largely unknown. To determine the patterns of sequence variation in the P. infestans lineage, we resequenced six genomes of four sister species. This revealed uneven evolutionary rates across genomes with genes in repeat-rich regions showing higher rates of structural polymorphisms and positive selection. These loci are enriched in genes induced in planta, implicating host adaptation in genome evolution. Unexpectedly, genes involved in epigenetic processes formed another class of rapidly evolving residents of the gene-sparse regions. These results demonstrate that dynamic repeat-rich genome compartments underpin accelerated gene evolution following host jumps in this pathogen lineage.

Evolutionary origin of the cell nucleus and its functional architecture

Understanding the evolutionary origin of the nucleus and its compartmentalized architecture provides a huge but, as expected, greatly rewarding challenge in the post-genomic era. We start this chapter with a survey of current hypotheses on the evolutionary origin of the cell nucleus. Thereafter, we provide an overview of evolutionarily conserved features of chromatin organization and arrangements, as well as topographical aspects of DNA replication and transcription, followed by a brief introduction of current models of nuclear architecture. In addition to features which may possibly apply to all eukaryotes, the evolutionary plasticity of higher-order nuclear organization is reflected by cell-type- and species-specific features, by the ability of nuclear architecture to adapt to specific environmental demands, as well as by the impact of aberrant nuclear organization on senescence and human disease. We conclude this chapter with a reflection on the necessity of interdisciplinary research strategies to map epigenomes in space and time.

Chromosomal organization at the level of gene complexes

Metazoan genomes primarily consist of non-coding DNA in comparison to coding regions. Non-coding fraction of the genome contains cis-regulatory elements, which ensure that the genetic code is read properly at the right time and space during development. Regulatory elements and their target genes define functional landscapes within the genome, and some developmentally important genes evolve by keeping the genes involved in specification of common organs/tissues in clusters and are termed gene complex. The clustering of genes involved in a common function may help in robust spatio-temporal gene expression. Gene complexes are often found to be evolutionarily conserved, and the classic example is the hox complex. The evolutionary constraints seen among gene complexes provide an ideal model system to understand cis and trans-regulation of gene function. This review will discuss the various characteristics of gene regulatory modules found within gene complexes and how they can be characterized.

Genome-wide DNA methylation analysis in cohesin mutant human cell lines

The cohesin complex has recently been shown to be a key regulator of eukaryotic gene expression, although the mechanisms by which it exerts its effects are poorly understood. We have undertaken a genome-wide analysis of DNA methylation in cohesin-deficient cell lines from probands with Cornelia de Lange syndrome (CdLS). Heterozygous mutations in NIPBL, SMC1A and SMC3 genes account for ∼65% of individuals with CdLS. SMC1A and SMC3 are subunits of the cohesin complex that controls sister chromatid cohesion, whereas NIPBL facilitates cohesin loading and unloading. We have examined the methylation status of 27 578 CpG dinucleotides in 72 CdLS and control samples. We have documented the DNA methylation pattern in human lymphoblastoid cell lines (LCLs) as well as identified specific differential DNA methylation in CdLS. Subgroups of CdLS probands and controls can be classified using selected CpG loci. The X chromosome was also found to have a unique DNA methylation pattern in CdLS. Cohesin preferentially binds to hypo-methylated DNA in control LCLs, whereas the differential DNA methylation alters cohesin binding in CdLS. Our results suggest that in addition to DNA methylation multiple mechanisms may be involved in transcriptional regulation in human cells and in the resultant gene misexpression in CdLS.