Differential gene expression in response to mechanical wounding and insect feeding in Arabidopsis.

Wounding in multicellular eukaryotes results in marked changes in gene expression that contribute to tissue defense and repair. Using a cDNA microarray technique, we analyzed the timing, dynamics, and regulation of the expression of 150 genes in mechanically wounded leaves of Arabidopsis. Temporal accumulation of a group of transcripts was correlated with the appearance of oxylipin signals of the jasmonate family. Analysis of the coronatine-insensitive coi1-1 Arabidopsis mutant that is also insensitive to jasmonate allowed us to identify a large number of COI1-dependent and COI1-independent wound-inducible genes. Water stress was found to contribute to the regulation of an unexpectedly large fraction of these genes. Comparing the results of mechanical wounding with damage by feeding larvae of the cabbage butterfly (Pieris rapae) resulted in very different transcript profiles. One gene was specifically induced by insect feeding but not by wounding; moreover, there was a relative lack of water stress-induced gene expression during insect feeding. These results help reveal a feeding strategy of P. rapae that may minimize the activation of a subset of water stress-inducible, defense-related genes.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

The fine-scale architecture of structural variants in 17 mouse genomes.

BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.

Variant within the promoter region of the CHRNA3 gene associated with FTN dependence is not related to self-reported willingness to quit smoking.

INTRODUCTION: Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region is robustly associated with smoking quantity. Conversely, the association between one of the most significant single nucleotide polymorphisms (SNPs; rs1051730 within the CHRNA3 gene) with perceived difficulty or willingness to quit smoking among current smokers is unknown. METHODS: Cross-sectional study including current smokers, 502 women, and 552 men. Heaviness of smoking index (HSI), difficulty, attempting, and intention to quit smoking were assessed by questionnaire. RESULTS: The rs1051730 SNP was associated with increased HSI (age, gender, and education-adjusted mean ± SE: 2.6 ± 0.1, 2.2 ± 0.1, and 2.0 ± 0.1 for AA, AG, and GG genotypes, respectively, p < .01). Multivariate logistic regression adjusting for gender, age, education, leisure-time physical activity, and personal history of cardiovascular or lung disease showed rs1051730 to be associated with higher smoking dependence (odds ratio [OR] and 95% CI for each additional A-allele: 1.38 [1.11-1.72] for smoking more than 20 cigarette equivalents/day; 1.31 [1.00-1.71] for an HSI ≥5 and 1.32 [1.05-1.65] for smoking 5 min after waking up) and borderline associated with difficulty to quit (OR = 1.29 [0.98-1.70]), but this relationship was no longer significant after adjusting for nicotine dependence. Also, no relationship was found with willingness (OR = 1.03 [0.85-1.26]), attempt (OR = 1.00 [0.83-1.20]), or preparation (OR = 0.95 [0.38-2.38]) to quit. Similar findings were obtained for other SNPs, but their effect on nicotine dependence was no longer significant after adjusting for rs1051730. Conclusions: These data confirm the effect of rs1051730 on nicotine dependence but failed to find any relationship with difficulty, willingness, and motivation to quit.

Chromosomal gene movements reflect the recent origin and biology of therian sex chromosomes

Mammalian sex chromosomes stem from ancestral autosomes and have substantially differentiated. It was shown that X-linked genes have generated duplicate intronless gene copies (retrogenes) on autosomes due to this differentiation. However, the precise driving forces for this out-of-X gene "movement" and its evolutionary onset are not known. Based on expression analyses of male germ-cell populations, we here substantiate and extend the hypothesis that autosomal retrogenes functionally compensate for the silencing of their X-linked housekeeping parental genes during, but also after, male meiotic sex chromosome inactivation (MSCI). Thus, sexually antagonistic forces have not played a major role for the selective fixation of X-derived gene copies in mammals. Our dating analyses reveal that although retrogenes were produced ever since the common mammalian ancestor, selectively driven retrogene export from the X only started later, on the placental mammal (eutherian) and marsupial (metatherian) lineages, respectively. Together, these observations suggest that chromosome-wide MSCI emerged close to the eutherian-marsupial split approximately 180 million years ago. Given that MSCI probably reflects the spread of the recombination barrier between the X and Y, crucial for their differentiation, our data imply that these chromosomes became more widely differentiated only late in the therian ancestor, well after the divergence of the monotreme lineage. Thus, our study also provides strong independent support for the recent notion that our sex chromosomes emerged, not in the common ancestor of all mammals, but rather in the therian ancestor, and therefore are much younger than previously thought

Detection of Brazilian hantavirus by reverse transcription polymerase chain reaction amplification of N gene in patients with hantavirus cardiopulmonary syndrome

We report a nested reverse transcription-polymerase chain reaction (RT-PCR) assay for hantavirus using primers selected to match high homology regions of hantavirus genomes detected from the whole blood of hantavirus cardiopulmonary syndrome (HCPS) patients from Brazil, also including the N gene nucleotide sequence of Araraquara virus. Hantavirus genomes were detected in eight out of nine blood samples from the HCPS patients by RT-PCR (88.9% positivity) and in all 9 blood samples (100% positivity) by nested-PCR. The eight amplicons obtained by RT-PCR (P1, P3-P9), including one obtained by nested-PCR (P-2) and not obtained by RT-PCR, were sequenced and showed high homology (94.8% to 99.1%) with the N gene of Araraquara hantavirus. Although the serologic method ELISA is the most appropriate test for HCPS diagnosis, the use of nested RT-PCR for hantavirus in Brazil would contribute to the diagnosis of acute hantavirus disease detecting viral genomes in patient specimens as well as initial genomic characterization of circulating hantaviruses.

Evolution of vitellogenin genes: comparative analysis of the nucleotide sequences downstream of the transcription initiation site of four Xenopus laevis and one chicken gene.

Electron microscopic analysis of heteroduplexes between the most distantly related Xenopus vitellogenin genes (A genes X B genes) has revealed the distribution of homologous regions that have been preferentially conserved after the duplication events that gave rise to the multigene family in Xenopus laevis. DNA sequence analysis was limited to the region downstream of the transcription initiation site of the Xenopus genes A1, B1 and B2 and a comparison with the Xenopus A2 and the major chicken vitellogenin gene is presented. Within the coding regions of the first three exons, nucleotide substitutions resulting in amino acid changes accumulate at a rate similar to that observed in globin genes. This suggests that the duplication event which led to the formation of the A and B ancestral genes in Xenopus laevis occurred about 150 million years ago. Homologous exons of the A1-A2 and B1-B2 gene pairs, which formed about 30 million years ago, show a quite similar sequence divergence. In contrast, A1-A2 homologous introns seem to have evolved much faster than their B1-B2 counterparts.

SNCA, MAPT, and GSK3B in Parkinson disease: a gene-gene interaction study.

Background and purpose:  Recent evidence suggests that variation in the SNCA, MAPT, and GSK3B genes interacts in affecting risk for Parkinson disease (PD). In the current study, we attempt to validate previously published findings, evaluating gene-gene interactions between SNCA, MAPT, and GSK3B in association with PD. Methods:  Three Caucasian PD patient-control series from the United States, Ireland, and Norway (combined n = 1020 patients and 1095 controls) were genotyped for SNCA rs356219, MAPT H1/H2-discriminating SNP rs1052553, and GSK3B rs334558 and rs6438552. Results:  Our findings indicate that as previously reported, the SNCA rs356219-G allele and MAPT rs1052553 (H1 haplotype) were both associated with an increased risk of PD, whilst contrary to previous reports, GSK3B variants were not. No pair-wise interaction was observed between SNCA, MAPT, and GSK3B; the risk effects of SNCA rs356219-G and MAPT rs1052553-H1 were seen in a similar manner across genotypes of other variants, with no evidence suggesting synergistic, antagonistic, or deferential effects. Conclusions:  In the Caucasian patient-control series examined, risk for PD was influenced by variation in SNCA and MAPT but not GSK3B. Additionally, those three genes did not interact in determining disease risk.

Fine-scale spatial genetic structure and gene dispersal in Silene latifolia.

Plants are sessile organisms, often characterized by limited dispersal. Seeds and pollen are the critical stages for gene flow. Here we investigate spatial genetic structure, gene dispersal and the relative contribution of pollen vs seed in the movement of genes in a stable metapopulation of the white campion Silene latifolia within its native range. This short-lived perennial plant is dioecious, has gravity-dispersed seeds and moth-mediated pollination. Direct measures of pollen dispersal suggested that large populations receive more pollen than small isolated populations and that most gene flow occurs within tens of meters. However, these studies were performed in the newly colonized range (North America) where the specialist pollinator is absent. In the native range (Europe), gene dispersal could fall on a different spatial scale. We genotyped 258 individuals from large and small (15) subpopulations along a 60 km, elongated metapopulation in Europe using six highly variable microsatellite markers, two X-linked and four autosomal. We found substantial genetic differentiation among subpopulations (global F(ST)=0.11) and a general pattern of isolation by distance over the whole sampled area. Spatial autocorrelation revealed high relatedness among neighboring individuals over hundreds of meters. Estimates of gene dispersal revealed gene flow at the scale of tens of meters (5-30 m), similar to the newly colonized range. Contrary to expectations, estimates of dispersal based on X and autosomal markers showed very similar ranges, suggesting similar levels of pollen and seed dispersal. This may be explained by stochastic events of extensive seed dispersal in this area and limited pollen dispersal.

Implication of DNA methylation and PAX5 factor in the transcriptional regulation of hTERT, the human telomerase reverse transcriptase gene

RESUME La télomérase est une enzyme dite "d'immortalité" qui permet aux cellules de maintenir la longueur de leurs télomères, ce qui confère une capacité de réplication illimitée aux cellules reproductrices et cancéreuses. A l'inverse, les cellules somatiques normales, qui n'expriment pas la télomérase, ont une capacité de réplication limitée. La sous-unité catalytique de la télomérase, hTERT, est définie comme le facteur limitant l'activité télomérasique. Entre activateurs et répresseurs, le rôle de la méthylation de l'ADN et de l'acétylation des histones, de nombreux modèles ont été suggérés. La découverte de l'implication de CTCF dans la régulation transcriptionnelle de hTERT explique en partie le mécanisme de répression de la télomérase dans la plupart des cellules somatiques et sa réactivation dans les cellules tumorales. Dans les cellules télomérase-positives, l'activité inhibitrice de CTCF est bloquée par un mécanisme dépendent ou non de la méthylation. Dans la plupart des carcinomes, une hyperméthylation de la région 5' de hTERT bloque l'effet inhibiteur de CTCF, alors qu'une petite région hypométhylée permet un faible niveau de transcription du gène. Nous avons démontré que la protéine MBD2 se lie spécifiquement sur la région 5' méthylée de hTERT dans différentes lignées cellulaires et qu'elle est impliquée dans la répression partielle de la transcription de hTERT dans les cellules tumorales méthylées. Par contre, nous avons montré que dans les lymphocytes B normaux et néoplasiques, la régulation de hTERT est indépendante de la méthylation. Dans ces cellules, le facteur PAX5 se lie sur la région 5' de hTERT en aval du site d'initiation de la traduction (ATG). L'expression exogène de PAX5 dans les cellules télomérase-négatives active la transcription de hTERT, alors que la répression de PAX5 dans les cellules lymphomateuses inhibe la transcription du gène. PAX5 est donc directement impliqué dans l'activation de l'expression de hTERT dans les lymphocytes B exprimant la télomérase. Ces résultats révèlent des différences entre les niveaux de méthylation de hTERT dans les cellules de carcinomes et les lymphocytes B exprimant la télomérase. La méthylation de hTERT en tant que biomarqueur de cancer a été évaluée, puis appliquée à la détection de métastases. Nous avons ainsi montré que la méthylation de hTERT est positivement corrélée au diagnostic cytologique dans les liquides céphalorachidiens. Nos résultats conduisent à un modèle de régulation de hTERT, qui aide à comprendre comment la transcription de ce gène est régulée par CTCF, avec un mécanisme lié ou non à la méthylation du gène hTERT. La méthylation de hTERT s'est aussi révélée être un nouveau et prometteur biomarqueur de cancer. SUMMARY Human telomerase is an "immortalizing" enzyme that enables cells to maintain telomere length, allowing unlimited replicative capacity to reproductive and cancer cells. Conversely, normal somatic cells that do not express telomerase have a finite replicative capacity. The catalytic subunit of telomerase, hTERT, is defined as the limiting factor for telomerase activity. Between activators and repressors, and the role of DNA methylation and histone acetylation, an abundance of hTERT regulatory models have been suggested. The discovery of the implication of CTCF in the transcriptional regulation of hTERT in part explained the mechanism of silencing of telomerase in most somatic cells and its reactivation in neoplastic cells. In telomerase-positive cells, the inhibitory activity of CTCF is blocked by methylation-dependent and -independent mechanisms. In most carcinoma cells, hypermethylation of the hTERT 5' region has been shown to block the inhibitory effect of CTCF, while a short hypomethylated region allows a low transcription level of the gene. We have demonstrated that MBD2 protein specifically binds the methylated 5' region of hTERT in different cell lines and is therefore involved in the partial repression of hTERT transcription in methylated tumor cells. In contrast, we have shown that in normal and neoplastic B cells, hTERT regulation is methylation-independent. The PAX5 factor has been shown to bind to the hTERT 5'region downstream of the ATG translational start site. Ectopic expression of PAX5 in telomerase-negative cells or repression of PAX5 expression in B lymphoma cells respectively activated and repressed hTERT transcription. Thus, PAX5 is strongly implicated in hTERT expression activation in telomerase-positive B cells. These results reveal differences between the hTERT methylation patterns in telomerase-positive carcinoma cells and telomerase-positive normal B cells. The potential of hTERT methylation as a cancer biomarker was evaluated and applied to the detection of metastasis. We have shown that hTERT methylation correlates with the cytological diagnosis in cerebrospinal fluids. Our results suggest a model of hTERT gene regulation, which helps us to better understand how hTERT transcription is regulated by CTCF in methylation-dependant and independent mechanisms. Our data also indicate that hTERT methylation is a promising new cancer biomarker.

Interpretation of array comparative genome hybridization data: a major challenge.

The advent and application of high-resolution array-based comparative genome hybridization (array CGH) has led to the detection of large numbers of copy number variants (CNVs) in patients with developmental delay and/or multiple congenital anomalies as well as in healthy individuals. The notion that CNVs are also abundantly present in the normal population challenges the interpretation of the clinical significance of detected CNVs in patients. In this review we will illustrate a general clinical workflow based on our own experience that can be used in routine diagnostics for the interpretation of CNVs.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Post-genomic update on a classical candidate gene for coronary artery disease: ESR1.

BACKGROUND: After age, sex is the most important risk factor for coronary artery disease (CAD). The mechanism through which women are protected from CAD is still largely unknown, but the observed sex difference suggests the involvement of the reproductive steroid hormone signaling system. Genetic association studies of the gene-encoding Estrogen Receptor α (ESR1) have shown conflicting results, although only a limited range of variation in the gene has been investigated. METHODS AND RESULTS: We exploited information made available by advanced new methods and resources in complex disease genetics to revisit the question of ESR1's role in risk of CAD. We performed a meta-analysis of 14 genome-wide association studies (CARDIoGRAM discovery analysis, N=≈87,000) to search for population-wide and sex-specific associations between CAD risk and common genetic variants throughout the coding, noncoding, and flanking regions of ESR1. In addition to samples from the MIGen (N=≈6000), WTCCC (N=≈7400), and Framingham (N=≈3700) studies, we extended this search to a larger number of common and uncommon variants by imputation into a panel of haplotypes constructed using data from the 1000 Genomes Project. Despite the widespread expression of ERα in vascular tissues, we found no evidence for involvement of common or low-frequency genetic variation throughout the ESR1 gene in modifying risk of CAD, either in the general population or as a function of sex. CONCLUSIONS: We suggest that future research on the genetic basis of sex-related differences in CAD risk should initially prioritize other genes in the reproductive steroid hormone biosynthesis system.

The role of CTCFL/BORIS in Meiosis

The complexity of mammalian genome organization demands a complex interplay of DNA and proteins to orchestrate proper gene regulation. CTCF, a highly conserved, ubiquitously expressed protein has been postulated as a primary organizer of genome architecture because of its roles in transcriptional activation/repression, insulation and imprinting. Diverse regulatory functions are exerted through genome wide binding via a central eleven zinc finger DNA binding domain and an array of diverse protein-protein interactions through N- and C- terminal domains. CTCFL has been identified as a paralog of CTCF expressed only in spermatogenic cells of the testis. CTCF and CTCFL have a highly homologous DNA-binding domain, while the flanking amino acid sequences exhibit no significant similarity. Genome- wide mapping of CTCF binding sites has been carried out in many cell types, but no data exist for CTCFL apart from a few identified loci. The lack of high quality antibodies prompted us to generate an endogenously flag-tagged CTCFL mouse model using BAC recombination. IHC staining using anti-flag antibodies confirmed CTCFL localization to type Β spermatogonia and preleptotene spermatocytes and a mutually exclusive pattern of expression with CTCF. ChIP followed by high-throughput sequencing identified 10,382 binding sites showing 70% overlap but representing only 20% of CTCF sites. Consensus sequence analysis identified a significantly longer binding motif with prominently less ambiguity of base calling at every position. The significant difference between CTCF and CTCFL genomic binding patterns proposes that their binding to DNA is differentially regulated. Analysis of CTCFL binding to methylated regions on a genome wide scale identified approximately 1,000 loci. Methylation-independent binding of CTCFL might be at least one of the mechanisms that ensures distinct binding patterns of CTCF and CTCFL since CTCF binding is methylation- sensitive. Co-localization of CTCF with cohesin has been well established and analysis of CTCFL and SMC3 overlap identified around 3,300 binding sites from which two related but distinct consensus sequence motifs were derived. Because virtually all data for cohesin binding originate from mitotically proliferating cells, the anticipated overlap is expected to be considerably higher in meiotic cells. Meiosis-specific cohesin subunit Rec8 is specific for spermatocytes and 6 out of the 12 identified binding sites are also bound by CTCFL. In conclusion, this was the first genome-wide mapping of CTCFL binding sites in spermatocytes, the only cell type where CTCF is not expressed. CTCFL has a unique binding site repertoire distinct from CTCF, binds to methylated sequences and shows a significant overlap with cohesin binding sites. Future efforts will be oriented towards deciphering the role CTCFL plays in conversion of chromatin structure and function from mitotic to meiotic chromosomes. - La complexité de l'organisation du génome des mammifères exige une interaction particulière entre ADN et protéines pour orchestrer une régulation appropriée de l'expression des gènes. CTCFL, une protéine ubiquitaire très conservée, serait le principal organisateur de l'architecture du génome de par son rôle dans l'activation / la répression de la transcription, la protection et la localisation des gènes. Diverses régulations sont opérées, d'une part au travers d'interactions à différents endroits du génome par le biais d'un domaine protéique central de liaison à l'ADN à onze doigts de zinc, et d'autre part par des interactions protéine-protéine variées au niveau de leur domaine N- et C-terminal. CTCFL a été identifié comme un paralogue de CTCF exprimé uniquement dans les cellules spermatiques du testicule. CTCFL et CTCF ont un domaine de liaison à l'ADN très homologue, tandis que les séquences d'acides aminés situées de part et d'autre de ce domaine ne présentent aucune similitude. Une cartographie générale des sites de liaison au CTCF a été réalisée pour de nombreux types cellulaires, mais il n'existe aucune donnée pour CTCFL à l'exception de l'identification de quelques loci. L'absence d'anticorps de bonne qualité nous a conduit à générer un modèle murin portant un CTCFL endogène taggué grâce à un procédé de recombinaison BAC. Une coloration IHC à l'aide d'anticorps anti-FLAG a confirmé la présence de CTCFL au niveau des spermatogonies de type Β et des spermatocytes au stade préleptotène, et une distribution mutuellement exclusive avec CTCF. Une méthode de Chromatine Immunoprecipitation (ChIP) suivie d'un séquençage à haut débit a permis d'identifier 10.382 sites de liaison montrant 70% d'homologie mais ne représentant que 20% des sites CTCF. L'analyse de la séquence consensus révèle un motif de fixation à l'ADN nettement plus long et qui comporte bien moins de bases aléatoires à chaque position nucléotidique. La différence significative entre les séquences génomiques des sites de liaison au CTCF et CTCFL suggère que leur fixation à l'ADN est régulée différemment. Appliquée à l'échelle du génome, l'étude de l'interaction de CTCFL avec des régions méthylées de l'ADN a permis d'identifier environ 1.000 loci. Contrairement à CTCFL, la liaison de CTCF dépend de l'état de méthylation de l'ADN ; cette modification épigénétique constitue donc au moins un des mécanismes de régulation expliquant une localisation de CTCF et CTCFL à des sites distincts du génome. La co- localisation de CTCF avec la cohésine étant établie, l'analyse de la superposition des séquences de CTCFL avec la sous-unité SMC3 identifie environ 3.300 sites de liaison parmi lesquels deux mêmes motifs consensus distincts par leur séquence sont mis en évidence. La presque quasi-totalité des données sur la cohésine ayant été établie à partir de cellules en prolifération mitotique, il est probable que la similitude au sein des séquences consensus soit encore plus grande dans le cas des cellules en méiose. La sous-unité Rec8 de la cohésine propre à l'état de méiose est spécifiquement exprimée dans les spermatocytes. Or 6 des 12 sites de liaison identifiés sont également utilisés par CTCFL. Pour conclure, ce travail constitue la première cartographie à l'échelle du génome des sites de liaison de CTCFL dans les spermatocytes, seul type cellulaire où CTCFL n'est pas exprimé. CTCFL possède un répertoire unique de sites de fixation à l'ADN distinct de CTCF, se lie à des séquences méthylées et présente un nombre important de sites de liaison communs avec la cohésine. Les perspectives futures sont d'élucider le rôle de CTCFL dans le remodelage de la structure de la chromatine et de définir sa fonction dans le processus de méiose.