Evidence for Gene-Specific Rather Than Transcription Rate–Dependent Histone H3 Exchange in Yeast Coding Regions

In eukaryotic organisms, histones are dynamically exchanged independently of DNA replication. Recent reports show that different coding regions differ in their amount of replication-independent histone H3 exchange. The current paradigm is that this histone exchange variability among coding regions is a consequence of transcription rate. Here we put forward the idea that this variability might be also modulated in a gene-specific manner independently of transcription rate. To that end, we study transcription rate–independent replication-independent coding region histone H3 exchange. We term such events relative exchange. Our genome-wide analysis shows conclusively that in yeast, relative exchange is a novel consistent feature of coding regions. Outside of replication, each coding region has a characteristic pattern of histone H3 exchange that is either higher or lower than what was expected by its RNAPII transcription rate alone. Histone H3 exchange in coding regions might be a way to add or remove certain histone modifications that are important for transcription elongation. Therefore, our results that gene-specific coding region histone H3 exchange is decoupled from transcription rate might hint at a new epigenetic mechanism of transcription regulation

Global target mRNA specification and regulation by the RNA-binding protein ZFP36

BACKGROUND: ZFP36, also known as tristetraprolin or TTP, and ELAVL1, also known as HuR, are two disease-relevant RNA-binding proteins (RBPs) that both interact with AU-rich sequences but have antagonistic roles. While ELAVL1 binding has been profiled in several studies, the precise in vivo binding specificity of ZFP36 has not been investigated on a global scale. We determined ZFP36 binding preferences using cross-linking and immunoprecipitation in human embryonic kidney cells, and examined the combinatorial regulation of AU-rich elements by ZFP36 and ELAVL1. RESULTS: Targets bound and negatively regulated by ZFP36 include transcripts encoding proteins necessary for immune function and cancer, and transcripts encoding other RBPs. Using partial correlation analysis, we were able to quantify the association between ZFP36 binding sites and differential target RNA abundance upon ZFP36 overexpression independent of effects from confounding features. Genes with increased mRNA half-lives in ZFP36 knockout versus wild-type mouse cells were significantly enriched for our human ZFP36 targets. We identified thousands of overlapping ZFP36 and ELAVL1 binding sites, in 1,313 genes, and found that ZFP36 degrades transcripts through specific AU-rich sequences, representing a subset of the U-rich sequences ELAVL1 interacts with to stabilize transcripts. CONCLUSIONS: ZFP36-RNA target specificities in vivo are quantitatively similar to previously reported in vitro binding affinities. ZFP36 and ELAVL1 bind an overlapping spectrum of RNA sequences, yet with differential relative preferences that dictate combinatorial regulatory potential. Our findings and methodology delineate an approach to unravel in vivo combinatorial regulation by RNA-binding proteins

Analysis of Biological Features Associated with Meiotic Recombination Hot and Cold Spots in Saccharomyces cerevisiae

Meiotic recombination is not distributed uniformly throughout the genome. There are regions of high and low recombination rates called hot and cold spots, respectively. The recombination rate parallels the frequency of DNA double-strand breaks (DSBs) that initiate meiotic recombination. The aim is to identify biological features associated with DSB frequency. We constructed vectors representing various chromatin and sequence-based features for 1179 DSB hot spots and 1028 DSB cold spots. Using a feature selection approach, we have identified five features that distinguish hot from cold spots in Saccharomyces cerevisiae with high accuracy, namely the histone marks H3K4me3, H3K14ac, H3K36me3, and H3K79me3; and GC content. Previous studies have associated H3K4me3, H3K36me3, and GC content with areas of mitotic recombination. H3K14ac and H3K79me3 are novel predictions and thus represent good candidates for further experimental study. We also show nucleosome occupancy maps produced using next generation sequencing exhibit a bias at DSB hot spots and this bias is strong enough to obscure biologically relevant information. A computational approach using feature selection can productively be used to identify promising biological associations. H3K14ac and H3K79me3 are novel predictions of chromatin marks associated with meiotic DSBs. Next generation sequencing can exhibit a bias that is strong enough to lead to incorrect conclusions. Care must be taken when interpreting high throughput sequencing data where systematic biases have been documented

Patterns and Mechanisms of Ancestral Histone Protein Inheritance in Budding Yeast

Tracking of ancestral histone proteins over multiple generations of genome replication in yeast reveals that old histones move along genes from 3′ toward 5′ over time, and that maternal histones move up to around 400 bp during genomic replication

Tracking the big ones : novel dynamics of organelles and macromolecular complexes during cell division and aging

In this Thesis we address two important aspects of protein dynamics: protein synthesis and distribution upon cell division and dynamics of the protein degradation machinery. In Chapter 2, we present novel technology (Recombination-Induced Tag Exchange)to distinguish and simultaneously track old and new proteins. In Chapter 3 we usedthis technology to make a comprehensive analysis of the inheritance and synthesis of organelles and macromolecular complexes in budding yeast. Thereby we resolved outstanding issues in organelle synthesis and uncovered symmetrical and asymmetrical patterns of inheritance. Asymmetrical inheritance of organelles and macromolecular complexes may induce lineage differences and could be involved in cell differentiation. Next, we address two aspects of the dynamics of the protein degradation machinery that may be relevant for cellular aging: proteasome localization and degradation of the proteasome. In Chapter 4 we show that the localization of the proteasome, like its activity, may be a relevant factor in cellular aging and identify genetic factors affecting proteasome localization and longevity in budding yeast. In Chapter 5 we present data that is consistent with lysosomal degradation of damaged proteasomes, which may represent the first sketches of a quality control mechanism for the proteasome.Netherlands Proteomics CentreUBL - phd migration 201