One of the complexes formed by the hematopoietic transcription factor Gata1 is a complex with the Ldb1 (LIM domain-binding protein 1) and Tal1 proteins. It is known to be important for the development and differentiation of the erythroid cell lineage and is thought to be implicated in long-range interactions. Here, the dynamics of the composition of the complex-in particular, the binding of the negative regulators Eto2 and Mtgr1-are studied, in the context of their genome-wide targets. This shows that the complex acts almost exclusively as an activator, binding a very specific combination of sequences, with a positioning relative to transcription start site, depending on the type of the core promoter. The activation is accompanied by a net decrease in the relative binding of Eto2 and Mtgr1. A Chromosome Conformation Capture sequencing (3C-seq) assay also shows that the binding of the Ldb1 complex marks genomic interaction sites in vivo. This establishes the Ldb1 complex as a positive regulator of the final steps of erythroid differentiation that acts through the shedding of negative regulators and the active interaction between regulatory sequences.[Keywords: ChIP sequencing; transcription factor complexes; development; differentiation; erythropoiesis; long-range interactions] Supplemental material is available at http://www.genesdev.org.

These data suggest a favorable outcome regarding recurrence and progression in patients with superficial bladder cancer who undergo ReTURB. ReTURB is suggested at least in those at high risk when bladder preservation is intended.

Retroelements constitute approximately 45% of the human genome. Long interspersed nuclear element (LINE) autonomous retrotransposons are predominantly represented by LINE-1, nonautonomous small interspersed nuclear elements (SINEs) are primarily represented by ALUs, and LTR retrotransposons by several families of human endogenous retroviruses (HERVs). The vast majority of LINE and HERV elements are densely methylated in normal somatic cells and contained in inactive chromatin. Methylation and chromatin structure together ensure a stable equilibrium between retroelements and their host. Hypomethylation and expression in developing germ cells opens a “window of opportunity” for retrotransposition and recombination that contribute to human evolution, but also inherited disease. In somatic cells, the presence of retroelements may be exploited to organize the genome into active and inactive regions, to separate domains and functional regions within one chromatin domain, to suppress transcriptional noise, and to regulate transcript stability. Retroelements, particularly ALUs, may also fulfill physiological roles during responses to stress and infections. Reactivation and hypomethylation of LINEs and HERVs may be important in the pathophysiology of cancer and various autoimmune diseases, contributing to chromosomal instability and chronically aberrant immune responses. The emerging insights into the pathophysiological importance of endogenous retroelements accentuate the gaps in our knowledge of how these elements are controlled in normal developing and mature cells

Ž .Let L L ‫ރ‬ be the variety of complex n-dimensional Lie algebras. The group n Ž . Ž . GL ‫ރ‬ acts on it via change of basis. An orbit O under this action consists of n all structures isomorphic to . The aim of this paper is to give a complete classification of orbit closures of 4-dimensional Lie algebras, i.e., determining all Ž . g O where g L L ‫ރ‬ . Starting with a classification of complex Lie algebras Ž . 4 of dimension n F 4, we study the behavior of several Lie algebra invariants under degeneration, i.e., under transition to the orbit closure. As a corollary, we will show Ž . that all degenerations in L L ‫ރ‬ can be realized via a one-parameter subgroup, but 3 Ž . this is not the case in L L ‫ރ‬ . ᮊ 1999 Academic Press 4 729

In prostate carcinoma (PCa) increased DNA methylation ('hypermethylation') occurs at specific genes such as GSTP1. Nevertheless, overall methylation can be decreased ('hypomethylation') because methylation of repetitive sequences like LINE-1 retrotransposons is diminished. We analysed DNA from 113 PCa and 36 noncancerous prostate tissues for LINE-1 hypomethylation by a sensitive Southern technique and for hypermethylation at eight loci by methylation-specific PCR. Hypermethylation frequencies for GSTP1, RARB2, RASSF1A, and APC in carcinoma tissues were each 470%, strongly correlating with each other (Po10 À6 ). Hypermethylation at each locus was significantly different between tumour and normal tissues (10 À11 oPo10 3 ), although hypermethylation, particularly of RASSF1A, was also observed in noncarcinoma tissues. ASC1 hypermethylation was observed in a subgroup of PCa with concurrent hypermethylation. Hypermethylation of CDH1, CDKN2A, and SFRP1 was rare. LINE-1 hypomethylation was detected in 49% PCa, all with hypermethylation at several loci. It correlated significantly with tumour stage, while hypermethylation was neither related to tumour stage nor Gleason score. Coordinate hypermethylation of several genes may occur early in PCa, with additional hypermethylation events and LINE-1 hypomethylation associated with progression. Hypermethylation allows detection of 482% of PCas. PCa may fall into three classes, that is, with few DNA methylation changes, with frequent hypermethylation, or with additional LINE-1 hypomethylation.

We propose to use Hidden Markov Models (HMMs) to account for the horizontal dependencies along the time axis in time course data and to cope with the prevalent errors and missing values. The HMMs are used within a model-based clustering framework. We are given a number of clusters, each represented by one Hidden Markov Model from a finite collection encompassing typical qualitative behavior. Then, our method finds in an iterative procedure cluster models and an assignment of data points to these models that maximizes the joint likelihood of clustering and models. Partially supervised learning--adding groups of labeled data to the initial collection of clusters--is supported. A graphical user interface allows querying an expression profile dataset for time course similar to a prototype graphically defined as a sequence of levels and durations. We also propose a heuristic approach to automate determination of the number of clusters. We evaluate the method on published yeast cell cycle and fibroblasts serum response datasets, and compare them, with favorable results, to the autoregressive curves method.

Rett syndrome (RTT) is a severe form of mental retardation, which is caused by spontaneous mutations in the X-linked gene MECP2. How the loss of MeCP2 function leads to RTT is currently unknown. Mice lacking the Mecp2 gene initially show normal postnatal development but later acquire neurological phenotypes, including heightened anxiety, that resemble RTT. The MECP2 gene encodes a methyl-CpG-binding protein that can act as a transcriptional repressor. Using cDNA microarrays, we found that Mecp2-null animals differentially express several genes that are induced during the stress response by glucocorticoids. Increased levels of mRNAs for serum glucocorticoid-inducible kinase 1 (Sgk) and FK506-binding protein 51 (Fkbp5) were observed before and after onset of neurological symptoms, but plasma glucocorticoid was not significantly elevated in Mecp2-null mice. MeCP2 is bound to the Fkbp5 and Sgk genes in brain and may function as a modulator of glucocorticoid-inducible gene expression. Given the known deleterious effect of glucocorticoid exposure on brain development, our data raise the possibility that disruption of MeCP2-dependent regulation of stress-responsive genes contributes to the symptoms of RTT.

The molecular changes underlying neural progenitor differentiation are essentially unknown. We applied cDNA microarrays with 13,627 clones to measure dynamic gene expression changes during the in vitro differentiation of neural progenitor cells that were isolated from the subventricular zone of postnatal day 7 mice and grown in vitro as neurospheres. In two experimental series in which we withdrew epidermal growth factor and added the neurotrophins Neurotrophin-4 or BDNF, four time points were investigated: undifferentiated cells grown as neurospheres, and cells 24, 48, and 96 hr after differentiation. Expression changes of selected genes were confirmed by semiquantitative RT-PCR. Ten different groups of gene expression dynamics obtained by cluster analysis are described. To correlate selected gene expression changes to the localization of respective proteins, we performed immunostainings of cultured neurospheres and of brain sections from adult mice. Our results provide new insights into the genetic program of neural progenitor differentiation and give strong hints to as yet unknown cellular communications within the adult subventricular zone stem cell niche.