Eukaryotic genomes are packaged into nucleosome particles that occlude the DNA from interacting with most DNA binding proteins. Nucleosomes have higher affinity for particular DNA sequences, reflecting the ability of the sequence to bend sharply, as required by the nucleosome structure. However, it is not known whether these sequence preferences have a significant influence on nucleosome position in vivo, and thus regulate the access of other proteins to DNA. Here we isolated nucleosome-bound sequences at high resolution from yeast and used these sequences in a new computational approach to construct and validate experimentally a nucleosome–DNA interaction model, and to predict the genome-wide organization of nucleosomes. Our results demonstrate that genomes encode an intrinsic nucleosome organization and that this intrinsic organization can explain ∼50% of the in vivo nucleosome positions. This nucleosome positioning code may facilitate specific chromosome functions including transcription factor binding, transcription initiation, and even remodelling of the nucleosomes themselves.

http://absimage.aps.org/image/MAR08/MWS_MAR08-2008-020581.pdf

The Genomic Code for Nucleosome Positioning

Within 15 years the web has grown from a group work tool for scientists at CERN into a global information space with more than a billion users. Currently, it is both returning to its roots as a read/write tool and also entering a new, more social and participatory stage. These trends have led to a feeling that the web is entering a ‘second phase’ – a new, ‘improved’ Web version 2.0. But how justified is this perception?

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What is Web 2.0? Ideas, technologies and implications for education

Double-stranded RNA-mediated interference (RNAi) is a simple and rapid method of silencing gene expression in a range of organisms. The silencing of a gene is a consequence of degradation of RNA into short RNAs that activate ribonucleases to target homologous mRNA. The resulting phenotypes either are identical to those of genetic null mutants or resemble an allelic series of mutants. Specific gene silencing has been shown to be related to two ancient processes, cosuppression in plants and quelling in fungi, and has also been associated with regulatory processes such as transposon silencing, antiviral defense mechanisms, gene regulation, and chromosomal modification. Extensive genetic and biochemical analysis revealed a two-step mechanism of RNAi-induced gene silencing. The first step involves degradation of dsRNA into small interfering RNAs (siRNAs), 21 to 25 nucleotides long, by an RNase III-like activity. In the second step, the siRNAs join an RNase complex, RISC (RNA-induced silencing complex), which acts on the cognate mRNA and degrades it. Several key components such as Dicer, RNA-dependent RNA polymerase, helicases, and dsRNA endonucleases have been identified in different organisms for their roles in RNAi. Some of these components also control the development of many organisms by processing many noncoding RNAs, called micro-RNAs. The biogenesis and function of micro-RNAs resemble RNAi activities to a large extent. Recent studies indicate that in the context of RNAi, the genome also undergoes alterations in the form of DNA methylation, heterochromatin formation, and programmed DNA elimination. As a result of these changes, the silencing effect of gene functions is exercised as tightly as possible. Because of its exquisite specificity and efficiency, RNAi is being considered as an important tool not only for functional genomics, but also for gene-specific therapeutic activities that target the mRNAs of disease-related genes.

/pdf/rna-interference-biology-mechanism-and-applications-ww381qhd6t.pdf

RNA Interference: Biology, Mechanism, and Applications

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in ∼2500 individuals by using Illumina SNP data, with an emphasis on “hotspots” prone to recurrent mutations. We find variants larger than 500 kb in 5%–10% of individuals and variants greater than 1 Mb in 1%–2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%–1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.

https://www.cell.com/ajhg/pdf/S0002-9297(09)00002-0.pdf

Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

Materials and Methods related to gene targeting (e.g., gene targeting with transcription activator-like effector nucleases; “TALENS”) are provided.

Tal effector-mediated dna modification

gene bodies. The authors suggest a model for this differential DNA methylation pattern on the two copies of the X chromosome. They propose that inactive, untranscribed regions, such as the Xi and intergenic regions, are more likely to undergo loss of methylation, resulting in higher methylation levels remaining at gene bodies on the Xa. Whether this is the case or not, this study alters our views of DNA methylation on the X chromosome, revealing marked differences outside the promoter regions that have been the focus of previous studies and setting the scene for other reassessments of DNA methylation patterns. Louisa Flintoft

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Chipping away at developmental networks

Shapely organs require clear orientation

...nanotechnology has found many uses for DNA that are beyond this molecule’s natural calling. How does the 1.5-fold increase in gene dosage on chromosome 21 lead to the many phenotypes of Down syndrome? New work shows that this pleiotropy can be traced back to two genes — DSCR1 and DYRK1A— that together inhibit a family of transcription factors that have a role in many aspects of vertebrate development. Mice in which components of NFAT signalling have been genetically inactivated have phenotypic features that resemble human Down syndrome. Prompted by these observations, Grabtree, Graef and colleagues examined the critical Down syndrome region on chromosome 21 for genes that might downregulate NFAT. One such gene is DSCR1, which is overexpressed in Down syndrome human fetuses. DSCR1 is an inhibitor of the phosphatase calcineurin, which controls the rate of nuclear import of the calcium-dependent components of NFAT transcription complexes (NFATc proteins). Having examined the 25–30 other candidates in this region of chromosome 21, the authors came across DYRK1A. It encodes a serine/threonine kinase that primes substrates for phosphorylation by GSK3, which in the case of NFATc proteins leads to their inactivation and removal from the nucleus. Once they confirmed the DYRK1A-mediated reduction of NFAT transcriptional activity, the authors made mouse transgenic lines in which both DSCR1 and DYRK1A were overexpressed. They report that 1.5to 3-fold increased levels of expression were sufficient to cause some of the Down syndrome developmental defects. The effects of a modest — 1.5 fold — increase in the expression levels of DSCR1 and DYRK1A are likely to be exaggerated by the fact that members of the NFAT family autoregulate. So to better predict the outcome of NFAT signalling the authors developed a mathematical model. One of the predictions states that NFAT targets might completely fail to be expressed because activation of their promoters might require a certain NFAT threshold level. Another prediction is that the NFAT regulatory circuit might not be equally stable in different tissues, resulting in stronger phenotypic effects in some tissues than others. This work elegantly shows that many of the developmental phenotypes of Down syndrome might be a consequence of perturbing the NFAT regulatory circuit, in response to increased dosage of DSCR1 and DYRK1A. It also has wider implications — if other diseases are also caused by specific weaknesses in genetic regulatory circuits then understanding and exploiting these weaknesses can have therapeutic potential. Magdalena Skipper

It's all in the balance

Differences in the DNA-binding affinities of transcription factors and in the tissue-specific combinations in which transcription factors bind regulatory elements underlie the temporal and spatial patterns of gene expression that characterize development. Although transcription-factor binding sites within promoter and 3′ UTR sequences have received much attention, similar studies of distal enhancer elements have been hindered by both experimental and computational difficulties. In their recent study, Hallikas, Palin and their colleagues have tackled both problems. They have developed a high-throughput method for determining the DNA-binding specificities of representative members of three transcription-factor families and a computational tool to predict the location of novel mammalian enhancers. To address the issue of varying affinities of transcription factors for different DNA sequences, the authors developed a microwell-plate-based, high-throughput method in which the DNA-binding domains of a transcription factor of interest were fused to a luciferase reporter. The fusion proteins were incubated with biotinylated oligonucleotides that had the highest affinity to the transcription factor of interest. Binding was detected by measuring luciferase activity that could be captured by immobilized streptavidin. By adding competing unlabelled oligonucleotides that carried single base substitutions to the reaction, the authors could determine the relative affinity of the given transcription factor. The utility of the assay was demonstrated for members of the GLI family, and for TCF4 and ETS1 transcription factors. Parallel to the experimental approach, the authors developed a computational tool — called enhancer element locator (EEL) for genome-wide enhancer analysis. EEL aligns the order of transcriptionfactor binding sites on orthologous DNA sequences by taking into account clustering, affinity and site conservation. Moreover, a system of correction factors is used to account for cooperativity between transcription factors at a given enhancer. Having tested EEL on welldefined Drosophila enhancers and on mammalian MyoD, the authors carried out pairwise genome-wide alignments of human genes with their orthologues from the mouse, rat, chicken and pufferfish. Several potential enhancers were chosen for further study — for example, to test their ability to drive expression of reporter genes. The confirmation rate was impressive for the highest scoring enhancers, although there were also a few surprises. Some enhancer–reporter gene constructs recapitulated only a part of the expression pattern of the corresponding gene, indicating the regulation of these genes by multiple enhancers. The expression of reporter genes in tissues where the studied transcription factors are potentially not active could in turn be explained by the presence of other transcription-factor binding-site modules within the enhancers tested. The experimental and computational approached described by Hallikas, Palin and colleagues are genome-wide and can be easily generalized to any transcription factor for which binding specificity is known. Together with other recently developed methods to study DNA binding on a global scale, they will help us to dissect the spatio-temporal complexity of gene regulation.

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Magdalena Skipper

Papers

Chipping away at developmental networks

Shapely organs require clear orientation

It's all in the balance

Functional genomics: Affinity for enhancer prediction

The generation switch