Candidate Regulatory Sequence Elements for Cell Cycle-Dependent Transcription in Saccharomyces cerevisiae

Characterization of a highly conserved histone related protein, Ydl156w, and its functional associations using quantitative proteomic analyses

A significant challenge in biology is to functionally annotate novel and uncharacterized proteins. Several approaches are available for deducing the function of proteins in silico based upon sequence homology and physical or genetic interaction, yet this approach is limited to proteins with well-characterized domains, paralogs and/or orthologs in other species, as well as on the availability of suitable large-scale data sets. Here, we present a quantitative proteomics approach extending the protein network of core histones H2A, H2B, H3, and H4 in Saccharomyces cerevisiae, among which a novel associated protein, the previously uncharacterized Ydl156w, was identified. In order to predict the role of Ydl156w, we designed and applied integrative bioinformatics, quantitative proteomics and biochemistry approaches aiming to infer its function. Reciprocal analysis of Ydl156w protein interactions demonstrated a strong association with all four histones and also to proteins strongly associated with histones including Rim1, Rfa2 and 3, Yku70, and Yku80. Through a subsequent combination of the focused quantitative proteomics experiments with available large-scale genetic interaction data and Gene Ontology functional associations, we provided sufficient evidence to associate Ydl156w with multiple processes including chromatin remodeling, transcription and DNA repair/replication. To gain deeper insights into the role of Ydl156w in histone biology we investigated the effect of the genetic deletion of ydl156w on H4 associated proteins, which lead to a dramatic decrease in the association of H4 with RNA polymerase III proteins. The implication of a role for Ydl156w in RNA Polymerase III mediated transcription was consequently verified by RNA-Seq experiments. Finally, using these approaches we generated a refined network of Ydl156w-associated proteins.

Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes

Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

Hormonal genomics

The availability of the human genomic sequence is changing the way in which biological questions are addressed. Based on the prediction of genes from nucleotide sequences, homologies among their encoded amino acids can be analyzed and used to place them in distinct families. This serves as a first step in building hypotheses for testing the structural and functional properties of previously uncharacterized paralogous genes. As genomic information from more organisms becomes available, these hypotheses can be refined through comparative genomics and phylogenetic studies. Instead of the traditional single-gene approach in endocrine research, we are beginning to gain an understanding of entire mammalian genomes, thus providing the basis to reveal subfamilies and pathways for genes involved in ligand signaling. The present review provides selective examples of postgenomic approaches in the analysis of novel genes involved in hormonal signaling and their chromosomal locations, polymorphisms, splicing variants, differential expression, and physiological function. In the postgenomic era, scientists will be able to move from a gene-by-gene approach to a reconstructionistic one by reading the encyclopedia of life from a global perspective. Eventually, a community-based approach will yield new insights into the complexity of intercellular communications, thereby offering us an understanding of hormonal physiology and pathophysiology.

Transcriptional regulation: a genomic overview

The availability of the Arabidopsis thaliana genome sequence allows a comprehensive analysis of transcriptional regulation in plants using novel genomic approaches and methodologies. Such a genomic view of transcription first necessitates the compilation of lists of elements. Transcription factors are the most numerous of the different types of proteins involved in transcription in eukaryotes, and the Arabidopsis genome codes for more than 1,500 of them, or approximately 6% of its total number of genes. A genome-wide comparison of transcription factors across the three eukaryotic kingdoms reveals the evolutionary generation of diversity in the components of the regulatory machinery of transcription. However, as illustrated by Arabidopsis, transcription in plants follows similar basic principles and logic to those in animals and fungi. A global view and understanding of transcription at a cellular and organismal level requires the characterization of the Arabidopsis transcriptome and promoterome, as well as of the interactome, the localizome, and the phenome of the proteins involved in transcription.

EBP2 is a member of the yeast RRB regulon, a transcriptionally coregulated set of genes that are required for ribosome and rRNA biosynthesis

In an effort to identify sets of yeast genes that are coregulated across various cellular transitions, gene expression data sets derived from yeast cells progressing through the cell cycle, sporulation, and diauxic shift were analyzed. A partitioning algorithm was used to divide each data set into 24 clusters of similar expression profiles, and the membership of the clusters was compared across the three experiments. A single cluster of 189 genes from the cell cycle experiment was found to share 65 genes with a cluster of 159 genes from the sporulation data set. Many of these genes were found to be clustered in the diauxic-shift experiment as well. The overlapping set was enriched for genes required for rRNA biosynthesis and included genes encoding RNA helicases, subunits of RNA polymerases I and III, and rRNA processing factors. A subset of the 65 genes was tested for expression by a quantitative-relative reverse transcriptase PCR technique, and they were found to be coregulated after release from alpha factor arrest, heat shock, and tunicamycin treatment. Promoter scanning analysis revealed that the 65 genes within this ribosome and rRNA biosynthesis (RRB) regulon were enriched for two motifs: the 13-base GCGATGAGATGAG and the 11-base TGAAAAATTTT consensus sequences. Both motifs were found to be important for promoting gene expression after release from alpha factor arrest in a test rRNA processing gene (EBP2), which suggests that these consensus sequences may function broadly in the regulation of a set of genes required for ribosome and rRNA biosynthesis.

DNA microarrays: new tools in the analysis of plant defence responses

Summary Large-scale DNA sequencing is providing information on the number and organization of genes and genomes of plant species and their pathogens. The next phase is to identify gene functions and gene networks with key roles in compatible and incompatible plant-pathogen interactions. DNA microarrays can provide information on the expression patterns of thousands of genes in parallel. The application of this technology is already revealing new features of plant-pathogen interactions and will be a key tool for a wide range of experiments in molecular plant pathology.

A genomic perspective on plant transcription factors

Data from the Arabidopsis genome project suggest that more than 5% of the genes of this plant encode transcription factors. The necessity for the use of genomic analytical approaches becomes clear when it is considered that less than 10% of these factors have been genetically characterized. A variety of tools for functional genomic analyses in plants have been developed over the past few years. The availability of the full complement of Arabidopsis transcription factors, together with the results of recent studies that illustrate some of the challenges to their functional characterization, now provides the basic framework for future analyses of transcriptional regulation in plants.