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A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks
John S Reece-Hoyes, Bart Deplancke, Jane Shingles, Christian A Grove, Ian A Hope, Albertha JM Walhout
Genome Biology , 2006, DOI: 10.1186/gb-2005-6-13-r110
Abstract: By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks.wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.Metazoan genomes contain thousands of predicted protein-coding genes. During development, pathology, and in response to environmental changes, each of these genes is expressed in different cells, at different times and at different levels. Spatial and temporal gene expression is controlled transcriptionally through the action of regulatory transcription factors (TFs) [1,2]. Transcription of each gene can be up- or down-regulated by TFs that bind to cis-regulatory DNA elements. These elements include upstream elements located in the proximal promoter, and enhancers or silencers that can be located at a greater distance from the transcription start site. Frequently, the expression level of a gene is the result of a balance between transcription activation and repression governed by multiple cis-regulatory elements and, hence, multiple TFs. The combinatorial nature of gene transcription provides a
The WRKY transcription factor superfamily: its origin in eukaryotes and expansion in plants
Yuanji Zhang, Liangjiang Wang
BMC Evolutionary Biology , 2005, DOI: 10.1186/1471-2148-5-1
Abstract: We searched all publicly available sequence data for WRKY genes. A single copy of the WRKY gene encoding two WRKY domains was identified from Giardia lamblia, a primitive eukaryote, Dictyostelium discoideum, a slime mold closely related to the lineage of animals and fungi, and the green alga Chlamydomonas reinhardtii, an early branching of plants. This ancestral WRKY gene seems to have duplicated many times during the evolution of plants, resulting in a large family in evolutionarily advanced flowering plants. In rice, the WRKY gene family consists of over 100 members. Analyses suggest that the C-terminal domain of the two-WRKY-domain encoding gene appears to be the ancestor of the single-WRKY-domain encoding genes, and that the WRKY domains may be phylogenetically classified into five groups. We propose a model to explain the WRKY family's origin in eukaryotes and expansion in plants.WRKY genes seem to have originated in early eukaryotes and greatly expanded in plants. The elucidation of the evolution and duplicative expansion of the WRKY genes should provide valuable information on their functions.Transcriptional control is a major mechanism whereby a cell or organism regulates its gene expression. Sequence-specific DNA-binding transcription regulators, one class of transcription factors [1], play an essential role in modulating the rate of transcription of specific target genes. In this way, they direct the temporal and spatial expressions necessary for normal development and proper response to physiological or environmental stimuli. Comparative genome analysis reveals that genes for transcription regulators are abundantly present in plant and animal genomes, and the evolution and diversity of eukaryotes seem to be related to the expansion of lineage-specific transcription regulator families [2].WRKY proteins are recently identified transcriptional regulators comprising a large gene family [3]. The first cDNA encoding a WRKY protein, SPF1, was cloned from sweet p
On the Diversification of the Translation Apparatus across Eukaryotes  [PDF]
Greco Hernández,Christopher G. Proud,Thomas Preiss,Armen Parsyan
International Journal of Genomics , 2012, DOI: 10.1155/2012/256848
Abstract: Diversity is one of the most remarkable features of living organisms. Current assessments of eukaryote biodiversity reaches 1.5 million species, but the true figure could be several times that number. Diversity is ingrained in all stages and echelons of life, namely, the occupancy of ecological niches, behavioral patterns, body plans and organismal complexity, as well as metabolic needs and genetics. In this review, we will discuss that diversity also exists in a key biochemical process, translation, across eukaryotes. Translation is a fundamental process for all forms of life, and the basic components and mechanisms of translation in eukaryotes have been largely established upon the study of traditional, so-called model organisms. By using modern genome-wide, high-throughput technologies, recent studies of many nonmodel eukaryotes have unveiled a surprising diversity in the configuration of the translation apparatus across eukaryotes, showing that this apparatus is far from being evolutionarily static. For some of the components of this machinery, functional differences between different species have also been found. The recent research reviewed in this article highlights the molecular and functional diversification the translational machinery has undergone during eukaryotic evolution. A better understanding of all aspects of organismal diversity is key to a more profound knowledge of life. 1. Protein Synthesis Is a Fundamental Process of Life Proteins are one of the elementary components of life and account for a large fraction of mass in the biosphere. They catalyze most reactions that sustain life and play structural, transport, and regulatory roles in all living organisms. Hence, “translation,” that is, the synthesis of proteins by the ribosome using messenger (m)RNA as the template, is a fundamental process for all forms of life, and a large proportion of an organism’s energy is committed to translation [1, 2]. Accordingly, regulating protein synthesis is crucial for all organisms. Indeed, many mechanisms to control gene expression at the translational level have evolved in eukaryotes [3]. These mechanisms have endowed eukaryotes with the potential to rapidly and reversibly respond to stress or sudden environmental changes [1, 2, 4]. Translational control also plays a crucial role in tissues and developmental processes where transcription is quiescent, or where asymmetric spatial localization of proteins is required, such as early embryogenesis, learning and memory, neurogenesis, and gametogenesis [5–10]. Moreover, recent global gene expression
From transcription start site to cell biology
Philipp Kapranov
Genome Biology , 2009, DOI: 10.1186/gb-2009-10-4-217
Abstract: Knowledge of the exact position of a 5' transcriptional start site (TSS) of an RNA molecule is crucial for the identification of the regulatory regions that immediately flank it. Traditionally, the most reliable method of identifying a TSS is to map a nucleotide to which a 5' cap structure is added in the RNA. Over the past few years this approach has been used in a number of genome-wide surveys aimed at unbiased identification of TSSs (see [1,2] and references therein). These surveys identified many more sites where 5' ends of capped RNAs could be mapped than those TSSs belonging to annotated genes. At the same time, large amounts of unannotated transcription had been detected in mammalian genomes [2-4] and numerous transcription factor binding sites found outside annotated promoter regions [5,6]. In addition, multiple start sites are often found for annotated, protein-coding genes very far from their 'official' start sites [2,7,8].Three papers published recently in Nature Genetics by members of the FANTOM (Functional Annotation of Mouse) consortium [9-11] reveal yet further complexity of transcription initiation in animal genomes. Taft et al. [9] describe a new class of short RNAs made at promoters, while Faulkner et al. [10] show that repetitive elements can be a rich source of novel promoters. A study from the FANTOM consortium and the RIKEN Omics Science Center [11] shows how information on the precise positions of TSSs can be used to characterize global gene regulatory networks operating during cell differentiation.The critical issue in mapping a true site of transcription initiation is to be able to distinguish it from a 5' end generated by RNA cleavage or degradation and from a 5' end generated by incomplete copying of RNA into cDNA. The conventional hallmark of TSSs in most eukaryotes is addition of a 7-methyl guanosine cap structure to the 5'-triphosphate of the first base transcribed by RNA polymerase II. This unique feature of the transcription initiatio
Transcriptional programs: Modelling higher order structure in transcriptional control
John E Reid, Sascha Ott, Lorenz Wernisch
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-218
Abstract: We applied our method to putative regulatory regions of 18,445 Mus musculus genes. We discovered just 68 transcriptional programs that effectively summarised the action of 149 transcription factors on these genes. Several of these programs were significantly enriched for known biological processes and signalling pathways. One transcriptional program has a significant overlap with a reference set of cell cycle specific transcription factors.Our method is able to pick out higher order structure from noisy sequence analyses. The transcriptional programs it identifies potentially represent common mechanisms of regulatory control across the genome. It simultaneously predicts which genes are co-regulated and which sets of transcription factors cooperate to achieve this co-regulation. The programs we discovered enable biologists to choose new genes and transcription factors to study in specific transcriptional regulatory systems.Organisms ranging in complexity from bacteria to higher eukaryotes are able to react and adapt to environmental and cellular signals. These responses are often encoded as complex gene regulatory networks. In these networks the expression of a gene's products is regulated by the activity of other genes. Although regulation can occur at many levels, we focus on transcriptional regulation, one of the most important and pervasive methods of regulation in eukaryotes. Transcriptional regulation occurs when certain gene products, transcription factors (TFs), bind to the DNA at binding sites (TFBSs) and affect the transcription of the regulated gene by modulation of the RNA polymerase complex. TFBSs often appear in clusters or cis-regulatory modules (CRMs), presumably to enable interactions between TFs binding there.TFs do not work in isolation from each other. Particularly in higher organisms, combinatorial operations are often necessary for the response of a cell to external stimuli or developmental programs. Such a response is frequently implemented as
Phylogeny-guided interaction mapping in seven eukaryotes
Janusz Dutkowski, Jerzy Tiuryn
BMC Bioinformatics , 2009, DOI: 10.1186/1471-2105-10-393
Abstract: We developed a Bayesian inference framework which uses phylogenetic relationships to guide the integration of PPI evidence across multiple datasets and species, providing more accurate predictions. We apply our framework to reconcile seven eukaryotic interactomes: H. sapiens, M. musculus, R. norvegicus, D. melanogaster, C. elegans, S. cerevisiae and A. thaliana. Comprehensive GO-based quality assessment indicates a 5% to 44% score increase in predicted interactomes compared to the input data. Further support is provided by gold-standard MIPS, CYC2008 and HPRD datasets. We demonstrate the ability to recover known PPIs in well-characterized yeast and human complexes (26S proteasome, endosome and exosome) and suggest possible new partners interacting with the putative SWI/SNF chromatin remodeling complex in A. thaliana.Our phylogeny-guided approach compares favorably to two standard methods for mapping PPIs across species. Detailed analysis of predictions in selected functional modules uncovers specific PPI profiles among homologous proteins, establishing interaction-based partitioning of protein families. Provided evidence also suggests that interactions within core complex subunits are in general more conserved and easier to transfer accurately to other organisms, than interactions between these subunits.Protein-protein interactions are essential to most cellular processes. Thus large-scale PPI networks can greatly contribute to our understanding of the cellular machinery at systems level. Experimental techniques such as yeast two-hybrid assays [1-4] and TAP-MS [5,6] have generated large amounts of binary PPIs and protein complex data, providing the first snapshots of eukaryotic interactomes. Unfortunately, the available experimental techniques are far from perfect, both in terms of their accuracy, as well as coverage. For instance, the yeast interactome has recently been estimated to contain from around 37,000 up to even 75,500 protein interactions between approxima
A genomic timescale for the origin of eukaryotes
S Blair Hedges, Hsiong Chen, Sudhir Kumar, Daniel YC Wang, Amanda S Thompson, Hidemi Watanabe
BMC Evolutionary Biology , 2001, DOI: 10.1186/1471-2148-1-4
Abstract: Eukaryotes were found to evolve faster than prokaryotes, with those eukaryotes derived from eubacteria evolving faster than those derived from archaebacteria. We found an early time of divergence (~4 billion years ago, Ga) for archaebacteria and the archaebacterial genes in eukaryotes. Our analyses support at least two horizontal gene transfer events in the origin of eukaryotes, at 2.7 Ga and 1.8 Ga. Time estimates for the origin of cyanobacteria (2.6 Ga) and the divergence of an early-branching eukaryote that lacks mitochondria (Giardia) (2.2 Ga) fall between those two events.We find support for two symbiotic events in the origin of eukaryotes: one premitochondrial and a later mitochondrial event. The appearance of cyanobacteria immediately prior to the earliest undisputed evidence for the presence of oxygen (2.4–2.2 Ga) suggests that the innovation of oxygenic photosynthesis had a relatively rapid impact on the environment as it set the stage for further evolution of the eukaryotic cell.An emerging pattern found in gene and protein phylogenies that include prokaryotes (archaebacteria and eubacteria) and eukaryotes is the variable position of eukaryotes. In proteins involved in transcription and translation, eukaryotes often cluster with archaebacteria whereas in metabolic proteins they often cluster with eubacteria [1]. Among the latter proteins, eukaryotes sometimes group with α-proteobacteria, presumably reflecting the origin of mitochondria, and plants sometimes cluster with cyanobacteria, reflecting the origin of plastids. These patterns have been interpreted as a general signature of the symbiotic origin of eukaryotes [2,3] and horizontal gene transfer (HGT) of symbiont genes to the nucleus [4-9]. On the one hand, this complexity resulting from HGT can obscure some aspects of evolutionary history [8]. However, HGT also can provide the means to investigate otherwise difficult questions, such as inferring the number of symbiotic events and estimating the time o
Polarised Asymmetric Inheritance of Accumulated Protein Damage in Higher Eukaryotes  [PDF]
María A. Rujano,Floris Bosveld,Florian A. Salomons,Freark Dijk,Maria A.W.H van Waarde,Johannes J.L van der Want,Rob A.I de Vos,Ewout R. Brunt,Ody C.M Sibon,Harm H. Kampinga
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.0040417
Abstract: Disease-associated misfolded proteins or proteins damaged due to cellular stress are generally disposed via the cellular protein quality-control system. However, under saturating conditions, misfolded proteins will aggregate. In higher eukaryotes, these aggregates can be transported to accumulate in aggresomes at the microtubule organizing center. The fate of cells that contain aggresomes is currently unknown. Here we report that cells that have formed aggresomes can undergo normal mitosis. As a result, the aggregated proteins are asymmetrically distributed to one of the daughter cells, leaving the other daughter free of accumulated protein damage. Using both epithelial crypts of the small intestine of patients with a protein folding disease and Drosophila melanogaster neural precursor cells as models, we found that the inheritance of protein aggregates during mitosis occurs with a fixed polarity indicative of a mechanism to preserve the long-lived progeny.
Polarised Asymmetric Inheritance of Accumulated Protein Damage in Higher Eukaryotes  [PDF]
María A Rujano,Floris Bosveld,Florian A Salomons,Freark Dijk,Maria A.W.H van Waarde,Johannes J.L van der Want,Rob A.I de Vos,Ewout R Brunt,Ody C.M Sibon,Harm H Kampinga
PLOS Biology , 2006, DOI: 10.1371/journal.pbio.0040417
Abstract: Disease-associated misfolded proteins or proteins damaged due to cellular stress are generally disposed via the cellular protein quality-control system. However, under saturating conditions, misfolded proteins will aggregate. In higher eukaryotes, these aggregates can be transported to accumulate in aggresomes at the microtubule organizing center. The fate of cells that contain aggresomes is currently unknown. Here we report that cells that have formed aggresomes can undergo normal mitosis. As a result, the aggregated proteins are asymmetrically distributed to one of the daughter cells, leaving the other daughter free of accumulated protein damage. Using both epithelial crypts of the small intestine of patients with a protein folding disease and Drosophila melanogaster neural precursor cells as models, we found that the inheritance of protein aggregates during mitosis occurs with a fixed polarity indicative of a mechanism to preserve the long-lived progeny.
Adaptive evolution of transcription factor binding sites
Johannes Berg, Stana Willmann, Michael L?ssig
BMC Evolutionary Biology , 2004, DOI: 10.1186/1471-2148-4-42
Abstract: We show that the selection for factor binding generically leads to specific correlations between nucleotide frequencies at different positions of a binding site. We demonstrate the possibility of rapid adaptive evolution generating a new binding site for a given transcription factor by point mutations. The evolutionary time required is estimated in terms of the neutral (background) mutation rate, the selection coefficient, and the effective population size.The efficiency of binding site formation is seen to depend on two joint conditions: the binding site motif must be short enough and the promoter region must be long enough. These constraints on promoter architecture are indeed seen in eukaryotic systems. Furthermore, we analyse the adaptive evolution of genetic switches and of signal integration through binding cooperativity between different sites. Experimental tests of this picture involving the statistics of polymorphisms and phylogenies of sites are discussed.The expression of a gene is controlled by other genes expressed at the same time and by external signals, a process called gene regulation [1]. Due to the combinatorial complexity of regulation, a large number of functional tasks can be performed by a limited number of genes. Differences in gene regulation are believed to be a major source of diversity in higher eukaryotes.To a large extent, gene regulation is the control of transcription. It is accomplished by a number of regulatory proteins called transcription factors that bind to specific sites on DNA. These binding sites contain about 10 – 15 base pairs relevant for binding and are mostly located in the cis-regulatory promoter region of a gene. A cis-regulatory region in E. coli is about 300 base pairs long and contains a few transcription factor binding sites [2]. There may be two or more sites for the same factor in one promoter region. At the same time, the sequences of binding sites are fuzzy, that is, different sites for the same factor differ b
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