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.

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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

The human genome is littered with small-scale genetic variants, such as SNPs and repeat-length polymorphisms, but little is known about the way in which variants involving larger regions contribute to genetic diversity. Two studies now reveal that large deletions and duplications are more common than was previously thought, prompting a re-evaluation of the way we view human genetic variation. Large-scale copy-number polymorphisms/variants (CNPs/LCVs) — deletions or duplications of chromosomal segments — have been identified previously from healthy individuals, but technical limitations have prevented an assessment of whether these variants are common on a genome-wide scale. In a collaborative study, Michael Wigler and colleagues developed a method called ROMA (representational oligonucleotide microarray analysis) that enables deletions or duplications to be identified. This involves digesting genomic DNA, amplifying the fragments, attaching a fluorescent label and hybridizing them to an array of complementary probes. The signal strength of each probe indicates the copy-number of the corresponding genomic region, which can be compared between samples. Using an average of 1 probe every 35 kb, Wigler and colleagues analysed samples from 20 unrelated, healthy individuals from a range of geographical locations. They identified a set of 76 different CNPs, involving regions of 100 kb or more, that varied between individuals, with an average of 11 CNP differences between each pair of subjects. The polymorphisms included both deletions and duplications — most of which have not been identified before — with a mean length of 465 kb. Most regions of the genome had CNPs, although they were noticeably more frequent in some regions, suggesting that there might be CNP ‘hotspots’. Importantly, many of these CNPs are in regions that contain genes, so this type of variation might influence levels of gene expression and lead to phenotypic differences between individuals. For example, one CNP-variant contained three copies of the gene PPYR1, which encodes the appetiteregulating neuropeptide Y4-receptor. CNPs are also present in regions that include genes implicated in nervoussystem development, leukaemia and drug resistance. So, it is possible that large-scale CNPs might underlie variation in a diverse range of phenotypes, from body weight to cancer susceptibility. In a second study, Charles Lee and colleagues used a similar technique to identify LCVs in samples from 39 healthy individuals. They identified 255 polymorphisms in the human genome: an average of 12 CNPs for each subject. The authors of both papers point out that their studies are not comprehensive, as the probes that they used represent only a fraction of the genome. Studies using larger sets of probes are planned for the future, which should reveal the full extent to which large-scale polymorphisms contribute to the genetic differences that underlie human individuality.

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Autism Genome Project

Allele Frequency Database http://alfred.med.yale.edu If you are interested in exploring or capitalizing on human genetic diversity then you should know about ALFRED — the Allele Frequency Database. It provides access to allele frequency data from a wide range of human population samples and links these data to the molecular genetics and human genome databases. Although it initially contained only data from the laboratories of Ken and Judy Kidd, it is now being systematically and continuously updated with data from published literature. So far, ALFRED contains 798 polymorphisms in 357 populations. Data can be downloaded for analysis into a single compressed ‘data dump’ file in the declared XML format. The data dump can include either all relevant information (including descriptions) or only the data relevant to statistical analyses. You can also add your own data by contacting the curators. The database can be searched using a unique identifier (UID) — a code that allows identification of a record across many data tables. Relevant publications can be searched for by author name, whereas frequencies can be searched by locus name, chromosome or polymorphism name and genotyping methods, to name but a few. There are also ways of searching by specific population or chromosome. Informative pages on individual populations, including links to external sources of information, are also provided. The database is being continually improved; for example, as of mid-July 2003 you can register with ALFRED for e-mail updates. And for those who might be worried about the ethical implications of an undertaking such as the, there is an ethics statement that clarifies the motives of its creators. Magdalena Skipper WEB WATCH

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Allele Frequency Database

of the genome, heterochromatin is now recognized as an important part of eukaryotic genomes, with functions that include chromosome segregation, nuclear organization and regulation of gene expression. And yet, owing to technical difficulties, all of the currently available genome sequences focus on euchromatin only. This is now set to change — two recent papers describe sequence finishing, mapping and annotation of heterochromatin in Drosophila melanogaster. Between them, they provide insights into the genomic organization of heterochromatic regions and pave the way for similar studies in other organisms. In the first study, Hoskins and Carlson et al. re-analysed the fly whole-genome shotgun sequence (WGS3). The repetitive nature of heterochromatin hinders efficient assembly of individual reads into scaffolds. To overcome this problem, the authors selected a set of 10-kb genomic clones to fill the gaps in sequence; for higherlevel assembly, they relied on BAC-based physical mapping and BAC-end sequences. The result was ~15 Mb of finished or improved hetero chromatic sequence (out of 20 Mb in total), with 50% in scaffolds greater than 378 kb. Using fluorescence in situ hybridization (FISH) (with singlecopy probes) they created an integrated physical and cytogenetic map of the pericentromeric heterochromatin, which they used to order, orient and link scaffolds into larger contigs. Although the authors admit that new technological and computational advances are needed to study highly repetitive regions, they have shown that single-copy and middle-repetitive components of heterochromatin should be within our reach. In the second paper, Smith and colleagues describe their computational and manual annotation of heterochromatic sequences from the same genome release. They estimate that, in the fly, heterochromatin contains ten times more repeats and transposons than euchromatin; in this respect, it resembles human euchromatin. As well as non-protein coding genes and pseudogenes, they identify 230–254 protein-coding genes, many of which are highly conserved in other Drosophila species. Interestingly, DNAand protein-binding domains are overrepresented among heterochromatic genes, prompting the authors to speculate whether these genes might in fact contribute to heterochromatin structure and function. It seems that all nuclear genes on average have similar numbers of exons and transcripts, but heterochromatic introns are on average five times longer. Unlike in the euchromatin, intron lengths tend not to be conserved between orthologues, perhaps because their repetitive nature makes them prone to expansions and contractions. Moreover, the highly repetitive nature of gene-regulatory regions raises a possibility that regulation of heterochromatic gene expression is different from the euchromatic process. The results, fully integrated with those for euchromatin, are now available through FlyBase and GenBank. As the authors point out, now that heterochromatin is revealing its closely guarded secrets, the similarities between it and euchromatin seem more striking than the differences. Magdalena Skipper

Magdalena Skipper

Papers

Autism Genome Project

Allele Frequency Database

Mysteries of heterochromatic sequences unravelled

Gene doping: a new threat for the Olympics?

The holy grail for plant biologists