A new approach that scans the modification states of histones along the chromosome allows the identification of enhancer elements in the complex genomes of higher eukaryotes. This is an important step in the functional annotation of the genome.
Archive for February, 2007
Enhancing genome annotation with chromatin
February 28, 2007Stochastic gene expression: from single molecules to the proteome
February 28, 2007Benjamin B Kaufmann1, 2 and Alexander van Oudenaarden1, 
1Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
2Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
Available online 20 February 2007.
Protein production involves a series of stochastic chemical steps. One consequence of this fact is that the copy number of any given protein varies substantially from cell to cell, even within isogenic populations. Recent experiments have measured this variation for thousands of different proteins, revealing a linear relationship between variance and mean level of expression for much of the proteome. This simple relationship is frequently thought to arise from the random production and degradation of mRNAs, but several lines of evidence suggest that infrequent gene activation events also bear responsibility. In support of the latter hypothesis, single-molecule experiments have demonstrated that mRNA transcripts are often produced in large bursts. Moreover, the temporal pattern of these bursts appears to be correlated for chromosomally proximal genes, suggesting the existence of an upstream player.
Enrichment or depletion of a GO category within a class of genes: which test?
February 22, 2007discusses approximate and exact tests for GO enrichment/depletion, the associated p-value computations, and Table 1 contains over 20 GO tools packages.
Bioinformatics 2007 23(4):401-407
http://bioinformatics.oxfordjournals.org/cgi/content/full/23/4/401
CHD5 Is a Tumor Suppressor at Human 1p36
February 22, 2007The authors at Cold Spring Harbor Laboratory functionally identify chromodomain helicase DNA binding domain 5 (Chd5) as a tumor suppressor that controls proliferation, apoptosis, and senescence via the p19Arf/p53 pathway. They demonstrate that Chd5 functions as a tumor suppressor in vivo and implicate deletion of CHD5 in human cancer.
Cell, Vol 128, 459-475, 09 February 2007
Mapping autism risk loci using genetic linkage and chromosomal rearrangements
February 19, 2007The AGP also scanned DNA from these families for copy number variations (CNV), or sub-microscopic genomic insertions and deletions that scientists believe might be involved with this and other common diseases. The innovative combination of these two approaches implicates a previously unidentified region of chromosome 11, and neurexin 1, a member of a family of genes believed to be important in neuronal contact and communication, among other regions and genes in the genome. The neurexin finding in particular highlights a special group of neurons, called glutamate neurons, and the genes affecting their development and function, suggesting they play a critical role in autism spectrum disorders.
Nature Genetics (18 Feb 2007) Article
Control of developmental regulators by Polycomb in human embryonic stem cells
February 5, 2007This paper’s been out for a while, not sure if we’ve seen it:
Polycomb group proteins are essential for early development in metazoans, but their contributions to human development are not well understood. We have mapped the Polycomb Repressive Complex 2 (PRC2) subunit SUZ12 across the entire nonrepeat portion of the genome in human embryonic stem (ES) cells. We found that SUZ12 is distributed across large portions of over two hundred genes encoding key developmental regulators. These genes are occupied by nucleosomes trimethylated at histone H3K27, are transcriptionally repressed, and contain some of the most highly conserved noncoding elements in the genome. We found that PRC2 target genes are preferentially activated during ES cell differentiation and that the ES cell regulators OCT4, SOX2, and NANOG cooccupy a significant subset of these genes. These results indicate that PRC2 occupies a special set of developmental genes in ES cells that must be repressed to maintain pluripotency and that are poised for activation during ES cell differentiation.
Cell. 2006 Apr 21;125(2):301-13.
Lab meeting schedule
February 5, 2007Feb 6 No meeting
Feb 13 Peter K
Feb 20 Peter P
Feb 27 Dan
Mar 6 Jonathan
Mar 13 Hailey
Mar 20 No meeting
Mar 27 Shouyong
Apr 4 Steve
The evolution of gene regulation by transcription factors and microRNAs
February 5, 2007Summary
#!. Gene regulation in multicellular eukaryotes is complex, with many layers of regulation. Two fundamental mechanisms of gene regulation involve transcription factors and microRNAs, a large class of small, non-coding RNAs.
#2. It is widely believed that phenotypic evolution is closely linked to the evolution of gene regulation. To begin to understand the evolution of gene regulatory networks, it is important to first understand how the individual regulators and their regulatory interactions evolve.
#3. A combination of computational and experimental work has made it possible to begin to compare the evolution of transcriptional regulation with post-transcriptional regulation that is carried out by microRNAs.
For both transcription factors and microRNAs, the regulators themselves seem to be well conserved over large evolutionary distances, whereas their targets seem to have evolved much more quickly, indicating that large-scale rewiring of regulatory networks has taken place in the course of evolution.
#4. In animal evolution, the acquisition of new microRNA families seems to have been much more rapid than the acquisition of new transcription-factor families. Several authors have proposed that new microRNA families have had important roles in the development of novel tissue types and organs.
#5. Ultimately, a comprehensive picture of gene-regulation evolution will require a unification of different regulatory mechanisms. As an initial step in this direction, we suggest a simple model that describes the transcription of new microRNA genes. A corollary of this model is that many microRNAs that are expressed at low levels and in specific spatio-temporal domains might have little biological function in regulating target genes in trans.
