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?

/pdf/what-is-web-2-0-ideas-technologies-and-implications-for-owt9hvxita.pdf

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

NATURE REVIEWS | GENETICS VOLUME 3 | JUNE 2002 | 411 Circadian rhythms are most often studied in association with behaviour and the underlying gene-expression changes in the brain. But circadian clocks that generate transcription periodicity also exist in many peripheral organs, as discussed in a new study published in Nature that demonstrates extensive circadian gene regulation in the hearts and livers of mice. In the biggest study of its kind, the authors show that this type of gene regulation is more extensive than previously thought and that, although it has a specialized role in a given tissue, it also has a broad biological function. Although the fact that peripheral tissues have circadian regulation is not new, the extent of this regulation remained largely unknown. To investigate this, Storch et al. performed a microarray analysis on the hearts and livers of mice whose light/dark cycle had been synchronized. Using a set of genes with known circadian regulation as a guide, they found that 10% of liver genes and 8% of heart genes were regulated by the circadian clock. Although oscillations in gene expression were generally out of phase with each other in the liver, they were much more synchronized in the heart. Interestingly, there was very little overlap between the genes that oscillate in the heart and in the liver — only 37 genes shared the same phase of peak expression. The authors point out that the core set of genes is important as it is likely to include those that are important for the functions of the peripheral clocks. Among them, they found genes involved in chromatin regulation, such as DNMT1-associated protein-1, and in ubiquitin pathways, suggesting that gene expression, in general, and protein stability are influenced by circadian rhythms. To determine the kinds of processes that involve genes with circadian regulation, Storch and colleagues used a gene-ontology approach to sort the data into three categories: biological process, molecular function and cellular component. Their analysis indicated that, even in a single tissue, the circadian clock regulates many diverse processes, several of which are shared by the liver and the heart. So, the authors conclude that, although the genes regulated by circadian clocks are different in the two tissues, this type of regulation influences many related or overlapping processes. As the authors point out, there are some limitations to their study. They admit that transcript oscillations need not be reflected at the protein level, which depends, at least in part, on protein turnover. Also, for some proteins, circadian oscillations might have little physiological consequence. Nonetheless, together with another study published in Cell, which looked at circadian gene regulation in the liver and in a part of the hypothalamus that is known to harbour the ‘pacemaker’ of circadian control, this study substantially improves our understanding of circadian gene expression and provides evidence about the core clock mechanism that underlies it. Magdalena Skipper

/pdf/gene-expression-peripheral-oscillations-454w98weza.pdf

Magdalena Skipper

Papers

Gene expression: Peripheral oscillations