Pausing for thought: disrupting the early transcription elongation checkpoint leads to developmental defects and tumourigenesis

Factors affecting transcriptional elongation have been characterized extensively in in vitro, single cell (yeast) and cell culture systems; however, data from the context of multicellular organisms has been relatively scarce. While studies in homogeneous cell populations have been highly informative about the underlying molecular mechanisms and prevalence of polymerase pausing, they do not reveal the biological impact of perturbing this regulation in an animal. The core components regulating pausing are expressed in all animal cells and are recruited to the majority of genes, however, disrupting their function often results in discrete phenotypic effects. Mutations in genes encoding key regulators of transcriptional pausing have been recovered from several genetic screens for specific phenotypes or interactions with specific factors in mice, zebrafish and flies. Analysis of these mutations has revealed that control of transcriptional pausing is critical for a diverse range of biological pathways essential for animal development and survival

The BET protein FSH functionally interacts with ASH1 to orchestrate global gene activity in Drosophila

BACKGROUND: The question of how cells re-establish gene expression states after cell division is still poorly understood. Genetic and molecular analyses have indicated that Trithorax group (TrxG) proteins are critical for the long-term maintenance of active gene expression states in many organisms. A generally accepted model suggests that TrxG proteins contribute to maintenance of transcription by protecting genes from inappropriate Polycomb group (PcG)-mediated silencing, instead of directly promoting transcription. RESULTS AND DISCUSSION: Here we report a physical and functional interaction in Drosophila between two members of the TrxG, the histone methyltransferase ASH1 and the bromodomain and extraterminal family protein FSH. We investigated this interface at the genome level, uncovering a widespread co-localization of both proteins at promoters and PcG-bound intergenic elements. Our integrative analysis of chromatin maps and gene expression profiles revealed that the observed ASH1-FSH binding pattern at promoters is a hallmark of active genes. Inhibition of FSH-binding to chromatin resulted in global down-regulation of transcription. In addition, we found that genes displaying marks of robust PcG-mediated repression also have ASH1 and FSH bound to their promoters. CONCLUSIONS: Our data strongly favor a global coactivator function of ASH1 and FSH during transcription, as opposed to the notion that TrxG proteins impede inappropriate PcG-mediated silencing, but are dispensable elsewhere. Instead, our results suggest that PcG repression needs to overcome the transcription-promoting function of ASH1 and FSH in order to silence genes

HSV-1 ICP4, A Multifaceted RNA PolII Transcription Factor

ICP4, of Herpes Simplex Virus type 1 (HSV-1) is responsible for activation of viral Early and Late genes, and is necessary for viral replication. ICP4 contains two transactivation domains separated by a DNA binding domain. The complex structure of ICP4 indicates the possible diversity of the cellular and viral proteins it interacts with to function. ICP4 interacts with a variety of transcription complexes to promote RNA Polymerase II mediated transcription. The structural basis for these interactions has not yet been clearly defined. To more closely examine the structural requirements for ICP4 activities, mutants in conserved and degenerate regions of the N-terminus, in the presence and absence of the carboxyl terminus, were examined for effects on viral gene expression. It was found that i) the amino terminal transactivation domain is strictly required for E gene transcription, ii) multiple conserved regions within the N-terminus contribute to transcription, and iii) the amino terminal and carboxyl terminal transactivation domains cooperate to mediate transcription. Affinity purification assays demonstrated that many of the observed defects in transcription probably resulted from the deletion of regions involved in stabilizing TFIID. Complementation analyses demonstrated that TFIID interactions are stabilized by the presence of one functional N-terminal and C-terminal transactivation domain within an ICP4 dimer. Affinity purification and mass spectrometry were used to determine the complexity of ICP4 mediated interactions throughout infection in addition to the structural requirements provided by ICP4 for these interactions. Mass spectrometry and western blot data indicated that ICP4 was found in complex with TFIID prior to other components of the transcription machinery including Mediator and TFIIH. Additionally, the amino terminal 774 amino acids were sufficient for interactions with TFIID, Mediator and TFIIH. While ICP4 has previously only been associated with preinitiation complex formation, components of initiation, elongation, mRNA processing, and mRNA export machinery were also found in complexes with ICP4, suggesting that ICP4 functions as a multifaceted RNA PolII transcription factor. Together, the data presented herein provide an understanding of how the structural complexities of ICP4 provide an interface for the formation of transcription complexes. Additionally, a new model for viral transcription is presented

Discovering genetic interactions based on natural genetic variation

Complex traits can be attributed to the effect of two or more genes and their interaction with each other as well as the environment. Unraveling the genetic cause of these traits, especially with regard to disease etiology, is a major goal of current research in statistical genetics. Much effort has been invested in the development of methods detecting genetic loci that are linked to variation of disease traits or intermediate molecular phenotypes such as gene expression levels. A very important aspect to be considered in the modeling of genotype-phenotype associations is that genes often interact with each other in a non-additive fashion, a phenomenon called epistasis. A special case of an epistatic interaction is an allele incompatibility, which is characterized by the inviability of all individuals carrying a certain combination of alleles at two distinct loci in the genome. The relevance and distribution of allele incompatibilities has not been investigated on a genome-wide scale in mammals. In this thesis, I propose a method for inferring allele incompatibilities that is exclusively based on DNA sequence information. We make use of genome-wide SNP data of parent-child trios and inspect 3×3 contingency tables for detecting pairs of alleles from different genomic positions that are under-represented in the population. Our method detected substantially more imbalanced allele pairs than what we got in simulations assuming no interactions. We could validate a significant number of the interactions with external data and we found that interacting loci are enriched for genes involved in developmental processes. Genes do not only interact with one another, their regulatory activity also depends on the environment or cellular context. The impact of genetic variation on gene expression will therefore also depend on cell types or on the cellular state. This aspect has long been neglected in the inference of genetic loci that are linked to gene expression variation (expression quantitative trait loci, eQTL). There is thus a need to develop methods for analyzing the variation of eQTL between different cell types and to assess the impact of genetic variation on expression dynamics rather than just static expression levels. In the second part of this thesis, I show that defining and detecting eQTL regulating expression dynamics is non-trivial. I propose to distinguish “static”, "conditional” and “dynamic” eQTL and suggest new strategies for mapping these eQTL classes. By using murine mRNA expression data from four stages of hematopoiesis, we demonstrate that eQTL from the above three classes yield associations with different modes of expression regulation. Intriguingly, dynamic and conditional eQTL complement one another although they are based on integration of the same expression data. We reveal substantial effects of individual genetic variation on cell state specific expression regulation