Control of developmental regulators by Polycomb in human embryonic stem cells

This 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

Feb 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

Summary

#!. 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.

Link

Chromosome instability leaves its mark

Jonathan R Pollack

SUMMARY: Genomic instability is a common feature of human cancer. A new study identifies a putative gene expression signature of chromosome instability in solid tumors, with

CONTEXT: …has been known, available methods to measure aneuploidy, such as flow cytometry–based ploidy analysis, FISH, CGH and LOH analysis, have yet to be widely adopted in the clinical management of patients with solid tumors. Whether gene…

Nature Genetics 38, 973 – 974 (01 Sep 2006) News and Views

Discovery of previously unidentified genomic disorders from the duplication architecture of the human genome

Andrew J Sharp, Sierra Hansen, …, Evan E Eichler

SUMMARY: Genomic disorders are characterized by the presence of flanking segmental duplications that predispose these regions to recurrent rearrangement. Based on the duplication architecture of

CONTEXT: …abnormalities had also been excluded. None had been previously analyzed by array comparative genomic hybridization (CGH). Parents or guardians of all subjects provided informed consent, and the protocol was reviewed and approved by…

Nature Genetics 38, 1038 – 1042 (01 Sep 2006) Letters

Using array-comparative genomic hybridization to define molecular portraits ofprimary breast cancers

S-F Chin, Y Wang, N P Thorne, A E Teschendorff, S E Pinder, M Vias, A Naderi, I Roberts, N L Barbosa-Morais, M J Garcia, N G Iyer, T Kranjac, J F R Robertson, S Aparicio, S Tavaré, I Ellis, J D Brenton, C Caldas

SUMMARY: We analysed 148 primary breast cancers using BAC-arrays containing 287 clones representing cancer-related gene/loci to obtain genomic molecular portraits. Gains were detected in 136

CONTEXT: …analysis to subtype breast cancers. Cytogenetic methods, including conventional comparative genomic hybridization (CGH), have revealed chromosomal regions that are frequently altered in breast tumors (Kallioniemi et al., 1994;…

Oncogene (25 Sep 2006) Oncogenomics

Small dsRNAs induce transcriptional activation in human cells

Long-Cheng Li^*,, Steven T. Okino, Hong Zhao, Deepa Pookot, Robert F. Place, Shinji Urakami, Hideki Enokida, and Rajvir Dahiya^*,

Department of Urology, Veterans Affairs Medical Center and University of California, San Francisco, CA 94121

…… In conclusion, we have identified several dsRNAs that activate gene expression by targeting noncoding regulatory regions in gene promoters. These findings reveal a more diverse role for small RNA molecules in the regulation of gene expression than previously recognized and identify a potential therapeutic use for dsRNA in targeted gene activation.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

Timothy R. Lezon^*, Jayanth R. Banavar^*, Marek Cieplak, Amos Maritan, and Nina V. Fedoroff^,¶,||

Pennsylvania State University.

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

Next big thing

News

Nature 444, 130-131 (9 November 2006) | doi:10.1038/444130a; Published online 8 November 2006

It’s the junk that makes us human!

Erika Check

‘Non-coding’ DNA may organize brain cell connections.

Link

GGtools

This paper reviews the central concepts and implementation of data structures and methods for studying genetics of gene expression with the GGtools package of Bioconductor. Illustration with a HapMap+expression dataset is provided.

Link