Low nucleosome occupancy is encoded around functional human transcription factor binding sites

<p>Abstract</p> <p>Background</p> <p>Transcriptional regulation of genes in eukaryotes is achieved by the interactions of multiple transcription factors with arrays of transcription factor binding sites (TFBSs) on DNA and with each other. Identification of these TFBSs is an essential step in our understanding of gene regulatory networks, but computational prediction of TFBSs with either consensus or commonly used stochastic models such as Position-Specific Scoring Matrices (PSSMs) results in an unacceptably high number of hits consisting of a few true functional binding sites and numerous false non-functional binding sites. This is due to the inability of the models to incorporate higher order properties of sequences including sequences surrounding TFBSs and influencing the positioning of nucleosomes and/or the interactions that might occur between transcription factors.</p> <p>Results</p> <p>Significant improvement can be expected through the development of a new framework for the modeling and prediction of TFBSs that considers explicitly these higher order sequence properties. It would be particularly interesting to include in the new modeling framework the information present in the nucleosome positioning sequences (NPSs) surrounding TFBSs, as it can be hypothesized that genomes use this information to encode the formation of stable nucleosomes over non-functional sites, while functional sites have a more open chromatin configuration.</p> <p>In this report we evaluate the usefulness of the latter feature by comparing the nucleosome occupancy probabilities around experimentally verified human TFBSs with the nucleosome occupancy probabilities around false positive TFBSs and in random sequences.</p> <p>Conclusion</p> <p>We present evidence that nucleosome occupancy is remarkably lower around true functional human TFBSs as compared to non-functional human TFBSs, which supports the use of this feature to improve current TFBS prediction approaches in higher eukaryotes.</p

A new generation of JASPAR, the open-access repository for transcription factor binding site profiles

JASPAR is the most complete open-access collection of transcription factor binding site (TFBS) matrices. In this new release, JASPAR grows into a meta-database of collections of TFBS models derived by diverse approaches. We present JASPAR CORE—an expanded version of the original, non-redundant collection of annotated, high-quality matrix-based transcription factor binding profiles, JASPAR FAM—a collection of familial TFBS models and JASPAR phyloFACTS—a set of matrices computationally derived from statistically overrepresented, evolutionarily conserved regulatory region motifs from mammalian genomes. JASPAR phyloFACTS serves as a non-redundant extension to JASPAR CORE, enhancing the overall breadth of JASPAR for promoter sequence analysis. The new release of JASPAR is available at

αT-catenin in restricted brain cell types and its potential connection to autism

BACKGROUND: Recent genetic association studies have linked the cadherin-based adherens junction protein alpha-T-catenin (αT-cat, CTNNA3) with the development of autism. Where αT-cat is expressed in the brain, and how its loss could contribute to this disorder, are entirely unknown. METHODS: We used the αT-cat knockout mouse to examine the localization of αT-cat in the brain, and we used histology and immunofluorescence analysis to examine the neurobiological consequences of its loss. RESULTS: We found that αT-cat comprises the ependymal cell junctions of the ventricles of the brain, and its loss led to compensatory upregulation of αE-cat expression. Notably, αT-cat was not detected within the choroid plexus, which relies on cell junction components common to typical epithelial cells. While αT-cat was not detected in neurons of the cerebral cortex, it was abundantly detected within neuronal structures of the molecular layer of the cerebellum. Although αT-cat loss led to no overt differences in cerebral or cerebellar structure, RNA-sequencing analysis from wild type versus knockout cerebella identified a number of disease-relevant signaling pathways associated with αT-cat loss, such as GABA-A receptor activation. CONCLUSIONS: These findings raise the possibility that the genetic associations between αT-cat and autism may be due to ependymal and cerebellar defects, and highlight the potential importance of a seemingly redundant adherens junction component to a neurological disorder

Next-generation muscle-directed gene therapy by in silico vector design

There is an urgent need to develop the next-generation vectors for gene therapy of muscle disorders, given the relatively modest advances in clinical trials. These vectors should express substantially higher levels of the therapeutic transgene, enabling the use of lower and safer vector doses. In the current study, we identify potent muscle-specific transcriptional cisregulatory modules (CRMs), containing clusters of transcription factor binding sites, using a genome-wide data-mining strategy. These novel muscle-specific CRMs result in a substantial increase in muscle-specific gene transcription (up to 400-fold) when delivered using adeno-associated viral vectors in mice. Significantly higher and sustained human micro-dystrophin and follistatin expression levels are attained than when conventional promoters are used. This results in robust phenotypic correction in dystrophic mice, without triggering apoptosis or evoking an immune response. This multidisciplinary approach has potentially broad implications for augmenting the efficacy and safety of muscle-directed gene therapy

Pis the probability that a position is occupied by a nucleosome at any point in time

The position of the non-functional binding site is indicated by the red line at sequence position 3000. Cumulative nucleosome occupancy is distributed evenly across the complete length of the sequence, indicating a uniform distribution of nucleosome-positioning sequences. Figure 1B shows the cumulative probabilities for the true positives data set. At the position of the functional binding site (red line) a drop in the cumulative nucleosome occupancy is observed relative to the surrounding sequence, indicating that this area is less likely to be occupied by nucleosomes than the other areas located further up- and downstream. Furthermore, the cumulative probability in this area is comparable to the level observed for the random sequences data set: non-genomic sequences generated by a zero-order Markov model (Figure 1C). Figure 1D shows the normalized cumulative probability in the data set of non-genomic sequences generated by a first order Markov model and is distributed evenly along the whole sequence and at the same level as that in the false positives data set. It is also at the same level as that in the true positives data set at a range of positions distant to the true TFBS (for instance the 1–2 kb region upstream of the TFBS).<p><b>Copyright information:</b></p><p>Taken from "Low nucleosome occupancy is encoded around functional human transcription factor binding sites"</p><p>http://www.biomedcentral.com/1471-2164/9/332</p><p>BMC Genomics 2008;9():332-332.</p><p>Published online 15 Jul 2008</p><p>PMCID:PMC2490708.</p><p></p

Sample sizes of the different data sets as a function of their constituting motif lengths

<p><b>Copyright information:</b></p><p>Taken from "Low nucleosome occupancy is encoded around functional human transcription factor binding sites"</p><p>http://www.biomedcentral.com/1471-2164/9/332</p><p>BMC Genomics 2008;9():332-332.</p><p>Published online 15 Jul 2008</p><p>PMCID:PMC2490708.</p><p></p

The difference between the average Pof the false positives and true positives set is plotted in blue

The maximal difference (0.2) is observed for α = 0.01. For each data point in the graph, a Welch two-sample t-test was performed on the data sets to assess the statistical significance of the difference in their mean Pvalues. The obtained p-values were plotted in red. The difference in mean between the true and false positives data sets is most significant for α = 0.01 (p-value = 8.46e-9).<p><b>Copyright information:</b></p><p>Taken from "Low nucleosome occupancy is encoded around functional human transcription factor binding sites"</p><p>http://www.biomedcentral.com/1471-2164/9/332</p><p>BMC Genomics 2008;9():332-332.</p><p>Published online 15 Jul 2008</p><p>PMCID:PMC2490708.</p><p></p

The data set of true positive TFBSs were ordered and grouped by their motif lengths

For each motif, 10 randomly matching hits were searched for in upstream promoter regions (both 1 kb and 5 kb upstream of TSS), and the resulting average nucleosome occupancy (P) of these false positives was calculated for each motif length. For comparison, the average nucleosome occupancy was also determined for the true TFBSs grouped per motif length. As can be seen, the reference sets have a higher average nucleosome occupancy for every motif length, indicating that the hits of longer motifs do not enrich the reference data set with true positive hits. Consequently all motif lengths ranging from 5 to 16 bp can be used to construct a reference false positives data set.<p><b>Copyright information:</b></p><p>Taken from "Low nucleosome occupancy is encoded around functional human transcription factor binding sites"</p><p>http://www.biomedcentral.com/1471-2164/9/332</p><p>BMC Genomics 2008;9():332-332.</p><p>Published online 15 Jul 2008</p><p>PMCID:PMC2490708.</p><p></p